Four-injector variability modeling of FinFET predictive technology models

The usual way of modeling variability using threshold voltage shift and drain current amplification is becoming inaccurate as new sources of variability appear in sub-22nm devices. In this work we apply the four-injector approach for variability modeling to the simulation of SRAMs with predictive technology models from 20nm down to 7nm nodes. We show that the SRAMs, designed following ITRS roadmap, present stability metrics higher by at least 20% compared to a classical variability modeling approach. Speed estimation is also pessimistic, whereas leakage is underestimated if sub-threshold slope and DIBL mismatch and their correlations with threshold voltage are not considered.

3-D modeling of perimeter recombination in GaAs diodes and its influence on concentrator solar cells

This paper describes a complete modelling of the perimeter recombination of GaAs diodes which solves most unknowns and suppresses the limitations of previous models. Because of the three dimensional nature of the implemented model, it is able to simulate real devices. GaAs diodes on two epiwafers with different base doping levels, sizes and geometries, namely square and circular are manufactured. The validation of the model is achieved by fitting the experimental measurements of the dark IV curve of the manufactured GaAs diodes. A comprehensive 3-D description of the occurring phenomena affecting the perimeter recombination is supplied with the help of the model. Finally, the model is applied to concentrator GaAs solar cells to assess the impact of their doping level, size and geometry on the perimeter recombination.

Modeling of GRBAS perceptual evaluation using spectral features obtained from an auditory-based filterbank.

Perceptual voice evaluation according to the GRBAS scale is modelled using a linear combination of acoustic parameters calculated after a filter-bank analysis of the recorded voice signals. Modelling results indicate that for breathiness and asthenia more than 55% of the variance of perceptual rates can be explained by such a model, with only 4 latent variables. Moreover, the greatest part of the explained variance can be attributed to only one or two latent variables similarly weighted by all 5 listeners involved in the experiment. Correlation factors between actual rates and model predictions around 0.6 are obtained.

Bayesian network modeling of the consensus between experts: an application to neuron classification

Neuronal morphology is hugely variable across brain regions and species, and their classification strategies are a matter of intense debate in neuroscience. GABAergic cortical interneurons have been a challenge because it is difficult to find a set of morphological properties which clearly define neuronal types. A group of 48 neuroscience experts around the world were asked to classify a set of 320 cortical GABAergic interneurons according to the main features of their three-dimensional morphological reconstructions. A methodology for building a model which captures the opinions of all the experts was proposed. First, one Bayesian network was learned for each expert, and we proposed an algorithm for clustering Bayesian networks corresponding to experts with similar behaviors. Then, a Bayesian network which represents the opinions of each group of experts was induced. Finally, a consensus Bayesian multinet which models the opinions of the whole group of experts was built. A thorough analysis of the consensus model identified different behaviors between the experts when classifying the interneurons in the experiment. A set of characterizing morphological traits for the neuronal types was defined by performing inference in the Bayesian multinet. These findings were used to validate the model and to gain some insights into neuron morphology.

Atomistic modeling of Ge damage accumulation, amorphization and solid phase epitaxial regrowth

En los últimos años, el Ge ha ganado de nuevo atención con la finalidad de ser integrado en el seno de las existentes tecnologías de microelectrónica. Aunque no se le considera como un canddato capaz de reemplazar completamente al Si en el futuro próximo, probalemente servirá como un excelente complemento para aumentar las propiedades eléctricas en dispositivos futuros, especialmente debido a su alta movilidad de portadores. Esta integración requiere de un avance significativo del estado del arte en los procesos de fabricado. Técnicas de simulación, como los algoritmos de Monte Carlo cinético (KMC), proporcionan un ambiente atractivo para llevar a cabo investigación y desarrollo en este campo, especialmente en términos de costes en tiempo y financiación. En este estudio se han usado, por primera vez, técnicas de KMC con el fin entender el procesado “front-end” de Ge en su fabricación, específicamente la acumulación de dañado y amorfización producidas por implantación iónica y el crecimiento epitaxial en fase sólida (SPER) de las capas amorfizadas. Primero, simulaciones de aproximación de clisiones binarias (BCA) son usadas para calcular el dañado causado por cada ión. La evolución de este dañado en el tiempo se simula usando KMC sin red, o de objetos (OKMC) en el que sólamente se consideran los defectos. El SPER se simula a través de una aproximación KMC de red (LKMC), siendo capaz de seguir la evolución de los átomos de la red que forman la intercara amorfo/cristalina. Con el modelo de amorfización desarrollado a lo largo de este trabajo, implementado en un simulador multi-material, se pueden simular todos estos procesos. Ha sido posible entender la acumulación de dañado, desde la generación de defectos puntuales hasta la formación completa de capas amorfas. Esta acumulación ocurre en tres regímenes bien diferenciados, empezando con un ritmo lento de formación de regiones de dañado, seguido por una rápida relajación local de ciertas áreas en la fase amorfa donde ambas fases, amorfa y cristalina, coexisten, para terminar en la amorfización completa de capas extensas, donde satura el ritmo de acumulación. Dicha transición ocurre cuando la concentración de dañado supera cierto valor límite, el cual es independiente de las condiciones de implantación. Cuando se implantan los iones a temperaturas relativamente altas, el recocido dinámico cura el dañado previamente introducido y se establece una competición entre la generación de dañado y su disolución. Estos efectos se vuelven especialmente importantes para iones ligeros, como el B, el cual crea dañado más diluido, pequeño y distribuido de manera diferente que el causado por la implantación de iones más pesados, como el Ge. Esta descripción reproduce satisfactoriamente la cantidad de dañado y la extensión de las capas amorfas causadas por implantación iónica reportadas en la bibliografía. La velocidad de recristalización de la muestra previamente amorfizada depende fuertemente de la orientación del sustrato. El modelo LKMC presentado ha sido capaz de explicar estas diferencias entre orientaciones a través de un simple modelo, dominado por una única energía de activación y diferentes prefactores en las frecuencias de SPER dependiendo de las configuraciones de vecinos de los átomos que recristalizan. La formación de maclas aparece como una consecuencia de esta descripción, y es predominante en sustratos crecidos en la orientación (111)Ge. Este modelo es capaz de reproducir resultados experimentales para diferentes orientaciones, temperaturas y tiempos de evolución de la intercara amorfo/cristalina reportados por diferentes autores. Las parametrizaciones preliminares realizadas de los tensores de activación de tensiones son también capaces de proveer una buena correlación entre las simulaciones y los resultados experimentales de velocidad de SPER a diferentes temperaturas bajo una presión hidrostática aplicada. Los estudios presentados en esta tesis han ayudado a alcanzar un mejor entendimiento de los mecanismos de producción de dañado, su evolución, amorfización y SPER para Ge, además de servir como una útil herramienta para continuar el trabajo en este campo. In the recent years, Ge has regained attention to be integrated into existing microelectronic technologies. Even though it is not thought to be a feasible full replacement to Si in the near future, it will likely serve as an excellent complement to enhance electrical properties in future devices, specially due to its high carrier mobilities. This integration requires a significant upgrade of the state-of-the-art of regular manufacturing processes. Simulation techniques, such as kinetic Monte Carlo (KMC) algorithms, provide an appealing environment to research and innovation in the field, specially in terms of time and funding costs. In the present study, KMC techniques are used, for the first time, to understand Ge front-end processing, specifically damage accumulation and amorphization produced by ion implantation and Solid Phase Epitaxial Regrowth (SPER) of the amorphized layers. First, Binary Collision Approximation (BCA) simulations are used to calculate the damage caused by every ion. The evolution of this damage over time is simulated using non-lattice, or Object, KMC (OKMC) in which only defects are considered. SPER is simulated through a Lattice KMC (LKMC) approach, being able to follow the evolution of the lattice atoms forming the amorphous/crystalline interface. With the amorphization model developed in this work, implemented into a multi-material process simulator, all these processes can be simulated. It has been possible to understand damage accumulation, from point defect generation up to full amorphous layers formation. This accumulation occurs in three differentiated regimes, starting at a slow formation rate of the damage regions, followed by a fast local relaxation of areas into the amorphous phase where both crystalline and amorphous phases coexist, ending in full amorphization of extended layers, where the accumulation rate saturates. This transition occurs when the damage concentration overcomes a certain threshold value, which is independent of the implantation conditions. When implanting ions at relatively high temperatures, dynamic annealing takes place, healing the previously induced damage and establishing a competition between damage generation and its dissolution. These effects become specially important for light ions, as B, for which the created damage is more diluted, smaller and differently distributed than that caused by implanting heavier ions, as Ge. This description successfully reproduces damage quantity and extension of amorphous layers caused by means of ion implantation reported in the literature. Recrystallization velocity of the previously amorphized sample strongly depends on the substrate orientation. The presented LKMC model has been able to explain these differences between orientations through a simple model, dominated by one only activation energy and different prefactors for the SPER rates depending on the neighboring configuration of the recrystallizing atoms. Twin defects formation appears as a consequence of this description, and are predominant for (111)Ge oriented grown substrates. This model is able to reproduce experimental results for different orientations, temperatures and times of evolution of the amorphous/crystalline interface reported by different authors. Preliminary parameterizations for the activation strain tensors are able to also provide a good match between simulations and reported experimental results for SPER velocities at different temperatures under the appliance of hydrostatic pressure. The studies presented in this thesis have helped to achieve a greater understanding of damage generation, evolution, amorphization and SPER mechanisms in Ge, and also provide a useful tool to continue research in this field.

Improved modeling of photoluminescent and electroluminescent coupling in multijunction solar cells

The performance of tandem stacks of Group III?V multijunction solar cells continues to improve rapidly, both through improved performance of the individual cells in the stack and throughi ncrease in the number of stacked cells. As the radiative efficiency of these individual cells increases, radiative coupling between the stacked cells becomes an increasingly important factor not only in cell design, but also in accurate efficiency measurement and in determining performance of cells and systems under varying spectral conditions in the field. Past modeling has concentrated on electroluminescent coupling between the cells, although photoluminescent coupling is shown to be important for cells operating near their maximum power point voltage or below or when junction defect recombination is significant. Extension of earlier models i sproposed to allow this non-negligible component of luminescent coupling to be included. Therefined model is validated by measurement of the closely related external emission from both single and double junction cells.

Induction of solid tumor differentiation by the peroxisome proliferator-activated receptor-γ ligand troglitazone in patients with liposarcoma

Agonist ligands for the nuclear receptor peroxisome proliferator-activated receptor-γ have been shown to induce terminal differentiation of normal preadipocytes and human liposarcoma cells in vitro. Because the differentiation status of liposarcoma is predictive of clinical outcomes, modulation of the differentiation status of a tumor may favorably impact clinical behavior. We have conducted a clinical trial for treatment of patients with advanced liposarcoma by using the peroxisome proliferator-activated receptor-γ ligand troglitazone, in which extensive correlative laboratory studies of tumor differentiation were performed. We report here the results of three patients with intermediate to high-grade liposarcomas in whom troglitazone administration induced histologic and biochemical differentiation in vivo. Biopsies of tumors from each of these patients while on troglitazone demonstrated histologic evidence of extensive lipid accumulation by tumor cells and substantial increases in NMR-detectable tumor triglycerides compared with pretreatment biopsies. In addition, expression of several mRNA transcripts characteristic of differentiation in the adipocyte lineage was induced. There was also a marked reduction in immunohistochemical expression of Ki-67, a marker of cell proliferation. Together, these data indicate that terminal adipocytic differentiation was induced in these malignant tumors by troglitazone. These results indicate that lineage-appropriate differentiation can be induced pharmacologically in a human solid tumor.

Induction of ARF tumor suppressor gene expression and cell cycle arrest by transcription factor DMP1

Expression of the DMP1 transcription factor, a cyclin D-binding Myb-like protein, induces growth arrest in mouse embryo fibroblast strains but is devoid of antiproliferative activity in primary diploid fibroblasts that lack the ARF tumor suppressor gene. DMP1 binds to a single canonical recognition site in the ARF promoter to activate gene expression, and in turn, p19ARF synthesis causes p53-dependent cell cycle arrest. Unlike genes such as Myc, adenovirus E1A, and E2F-1, which, when overexpressed, activate the ARF-p53 pathway and trigger apoptosis, DMP1, like ARF itself, does not induce programmed cell death. Therefore, apart from its recently recognized role in protecting cells from potentially oncogenic signals, ARF can be induced in response to antiproliferative stimuli that do not obligatorily lead to apoptosis.

Quantitative modeling of stochastic systems in molecular biology by using stochastic Petri nets

An integrated understanding of molecular and developmental biology must consider the large number of molecular species involved and the low concentrations of many species in vivo. Quantitative stochastic models of molecular interaction networks can be expressed as stochastic Petri nets (SPNs), a mathematical formalism developed in computer science. Existing software can be used to define molecular interaction networks as SPNs and solve such models for the probability distributions of molecular species. This approach allows biologists to focus on the content of models and their interpretation, rather than their implementation. The standardized format of SPNs also facilitates the replication, extension, and transfer of models between researchers. A simple chemical system is presented to demonstrate the link between stochastic models of molecular interactions and SPNs. The approach is illustrated with examples of models of genetic and biochemical phenomena where the UltraSAN package is used to present results from numerical analysis and the outcome of simulations.

Semirational design of active tumor suppressor p53 DNA binding domain with enhanced stability

We have designed a p53 DNA binding domain that has virtually the same binding affinity for the gadd45 promoter as does wild-type protein but is considerably more stable. The design strategy was based on molecular evolution of the protein domain. Naturally occurring amino acid substitutions were identified by comparing the sequences of p53 homologues from 23 species, introducing them into wild-type human p53, and measuring the changes in stability. The most stable substitutions were combined in a multiple mutant. The advantage of this strategy is that, by substituting with naturally occurring residues, the function is likely to be unimpaired. All point mutants bind the consensus DNA sequence. The changes in stability ranged from +1.27 (less stable Q165K) to −1.49 (more stable N239Y) kcal mol−1, respectively. The changes in free energy of unfolding on mutation are additive. Of interest, the two most stable mutants (N239Y and N268D) have been known to act as suppressors and restored the activity of two of the most common tumorigenic mutants. Of the 20 single mutants, 10 are cancer-associated, though their frequency of occurrence is extremely low: A129D, Q165K, Q167E, and D148E are less stable and M133L, V203A and N239Y are more stable whereas the rest are neutral. The quadruple mutant (M133LV203AN239YN268D), which is stabilized by 2.65 kcal mol−1 and Tm raised by 5.6°C is of potential interest for trials in vivo.

A subset of skin tumor modifier loci determines survival time of tumor-bearing mice

Studies of mouse models of human cancer have established the existence of multiple tumor modifiers that influence parameters of cancer susceptibility such as tumor multiplicity, tumor size, or the probability of malignant progression. We have carried out an analysis of skin tumor susceptibility in interspecific Mus musculus/Mus spretus hybrid mice and have identified another seven loci showing either significant (six loci) or suggestive (one locus) linkage to tumor susceptibility or resistance. A specific search was carried out for skin tumor modifier loci associated with time of survival after development of a malignant tumor. A combination of resistance alleles at three markers [D6Mit15 (Skts12), D7Mit12 (Skts2), and D17Mit7 (Skts10)], all of which are close to or the same as loci associated with carcinoma incidence and/or papilloma multiplicity, is significantly associated with increased survival of mice with carcinomas, whereas the reverse combination of susceptibility alleles is significantly linked to early mortality caused by rapid carcinoma growth (χ2 = 25.22; P = 5.1 × 10−8). These data indicate that host genetic factors may be used to predict carcinoma growth rate and/or survival of individual backcross mice exposed to the same carcinogenic stimulus and suggest that mouse models may provide an approach to the identification of genetic modifiers of cancer survival in humans.

Growth suppression of glioma cells by PTEN requires a functional phosphatase catalytic domain

Deletions of all or part of chromosome 10 are the most common genetic alterations in high-grade gliomas. The PTEN gene (also called MMAC1 and TEP1) maps to chromosome region 10q23 and has been implicated as a target of alteration in gliomas and also in other cancers such as those of the breast, prostate, and kidney. Here we sought to provide a functional test of its candidacy as a growth suppressor in glioma cells. We used a combination of Northern blot analysis, protein truncation assays, and sequence analysis to determine the types and frequency of PTEN mutations in glioma cell lines so that we could define appropriate recipients to assess the growth suppressive function of PTEN by gene transfer. Introduction of wild-type PTEN into glioma cells containing endogenous mutant alleles caused growth suppression, but was without effect in cells containing endogenous wild-type PTEN. The ectopic expression of PTEN alleles, which carried mutations found in primary tumors and have been shown or are expected to inactivate its phosphatase activity, caused little growth suppression. These data strongly suggest that PTEN is a protein phosphatase that exhibits functional and specific growth-suppressing activity.

Three-dimensional modeling of and ligand docking to vitamin D receptor ligand binding domain

The ligand binding domain of the human vitamin D receptor (VDR) was modeled based on the crystal structure of the retinoic acid receptor. The ligand binding pocket of our VDR model is spacious at the helix 11 site and confined at the β-turn site. The ligand 1α,25-dihydroxyvitamin D3 was assumed to be anchored in the ligand binding pocket with its side chain heading to helix 11 (site 2) and the A-ring toward the β-turn (site 1). Three residues forming hydrogen bonds with the functionally important 1α- and 25-hydroxyl groups of 1α,25-dihydroxyvitamin D3 were identified and confirmed by mutational analysis: the 1α-hydroxyl group is forming pincer-type hydrogen bonds with S237 and R274 and the 25-hydroxyl group is interacting with H397. Docking potential for various ligands to the VDR model was examined, and the results are in good agreement with our previous three-dimensional structure-function theory.

Highly efficient electro-gene therapy of solid tumor by using an expression plasmid for the herpes simplex virus thymidine kinase gene

We report successful electro-gene therapy (EGT) by using plasmid DNA for tumor-bearing mice. Subcutaneously inoculated CT26 tumor was subjected to EGT, which consists of intratumoral injection of a naked plasmid encoding a marker gene or a therapeutic gene, followed by in vivo electroporation (EP). When this treatment modality is carried out with the plasmid DNA for the green fluorescent protein gene, followed by in vivo EP with the optimized pulse parameters, numerous intensely bright green fluorescent signals appeared within the tumor. EGT, by using the “A” fragment of the diphtheria toxin gene significantly inhibited the growth of tumors, by about 30%, on the flank of mice. With the herpes simplex virus thymidine kinase gene, followed by systemic injection of ganciclovir, EGT was far more effective in retarding tumor growth, varying between 50% and 90%, compared with the other controls. Based on these results, it appears that EGT can be used successfully for treating murine solid tumors.

Diverse roles of the tumor necrosis factor family member TRANCE in skeletal physiology revealed by TRANCE deficiency and partial rescue by a lymphocyte-expressed TRANCE transgene

Tumor necrosis factor-related, activation-induced cytokine (TRANCE), a tumor necrosis factor family member, mediates survival of dendritic cells in the immune system and is required for osteoclast differentiation and activation in the skeleton. We report the skeletal phenotype of TRANCE-deficient mice and its rescue by the TRANCE transgene specifically expressed in lymphocytes. TRANCE-deficient mice showed severe osteopetrosis, with no osteoclasts, marrow spaces, or tooth eruption, and exhibited profound growth retardation at several skeletal sites, including the limbs, skull, and vertebrae. These mice had marked chondrodysplasia, with thick, irregular growth plates and a relative increase in hypertrophic chondrocytes. Transgenic overexpression of TRANCE in lymphocytes of TRANCE-deficient mice rescued osteoclast development in two locations in growing long bones: excavation of marrow cavities permitting hematopoiesis in the marrow spaces, and remodeling of osteopetrotic woven bone in the shafts of long bones into histologically normal lamellar bone. However, osteoclasts in these mice failed to appear at the chondroosseous junction and the metaphyseal periosteum of long bones, nor were they present in tooth eruption pathways. These defects resulted in sclerotic metaphyses with persistence of club-shaped long bones and unerupted teeth, and the growth plate defects were largely unimproved by the TRANCE transgene. Thus, TRANCE-mediated regulation of the skeleton is complex, and impacts chondrocyte differentiation and osteoclast formation in a manner that likely requires local delivery of TRANCE.