New amino acid polymorphism, Ala/Val4058, in exon 45 of the polycystic kidney disease 1 gene: evolution of alleles

The PKD1 gene, which is responsible for the most common form of autosomal dominant polycystic kidney disease, has recently been cloned and sequenced. Many disease-causing mutations have been characterized in this gene, most of them resulting in premature protein termination. However, mutation analysis not routinely implemented for family investigations in a clinical setting, because of the large size and complexity of the gene. Instead, genetic linkage analysis using highly polymorphic CA dinucleotide repeats that map around the gene is still the method of choice. Recently, a few intragenic polymorphisms have been described that are also useful for linkage studies. Here, a new diallelic polymorphism is described for amino acid residue 4058, Ala/Val4058, with allelic frequencies of 0.88 and 0.12, respectively, and a heterozygosity of 0.23, in the Greek and Greek-Cypriot populations. Interestingly, this polymorphism and Ala4091-A/G, which has previously been described in Caucasians, were not detected in DNA from 44 Japanese samples tested. This is particularly important when allelic frequencies in a particular population are used for linkage analysis of families of different ethnic origin. Also, observation of the two polymorphisms together as haplotypes suggests that the Ala/Val4058 polymorphism occurred more recently than the establishment of the Ala4091-A/G polymorphism, and specifically on the G allele.     

A Trustworthy Proof Checker

Proof-carrying code (PCC) and other applications in computer security require machine-checkable proofs of properties of machine-language programs. The main advantage of the PCC approach is that the amount of code that must be explicitly trusted is very small: it consists of the logic in which predicates and proofs are expressed, the safety predicate, and the proof checker. We have built a minimal proof checker, and we explain its design principles and the representation issues of the logic, safety predicate, and safety proofs. We show that the trusted computing base (TCB) in such a system can indeed be very small. In our current system the TCB is less than 2,700 lines of code (an order of magnitude smaller even than other PCC systems), which adds to our confidence of its correctness.     

Band-Structure Effects on the Performance of III–V Ultrathin-Body SOI MOSFETs

This paper examines the impact of band structure on deeply scaled III-V devices by using a self-consistent 20-band -SO semiempirical atomistic tight-binding model. The density of states and the ballistic transport for both GaAs and InAs ultrathin-body n-MOSFETs are calculated and compared with the commonly used bulk effective mass approximation, including all the valleys (, , and ). Our results show that for III-V semiconductors under strong quantum confinement, the conduction band nonparabolicity affects the confinement effective masses and, therefore, changes the relative importance of different valleys. A parabolic effective mass model with bulk effective masses fails to capture these effects and leads to significant errors, and therefore, a rigorous treatment of the full band structure is required.     

Spark ignition of turbulent recirculating non-premixed gas and spray flames: A model for predicting ignition probability

A model that synthesizes previous knowledge from experiments and simulations on spark ignition of gas and liquid-fuelled non-premixed recirculating flames has been developed. Attention is focused on the flame expansion process and the overall filling of the combustor volume with flame. The model is meant to provide a quick assessment of the ignition behaviour of a combustor. It uses information from the flow patterns before ignition and calculates possible trajectories that a flame emanating from a spark may experience. The calculation of these trajectories includes flame extinction to capture the experimentally-observed flame quenching, mixture fraction fluctuations to capture the non-premixed nature of the flame, convection by the mean and the random turbulent flow to capture the probabilistic nature of the flame evolution, and uses recent results on the laminar burning velocity in sprays. The model is applied to gas and spray flames and the calculated ignition probability distributions and the timescale of complete ignition agree reasonably well with experiment. The results of the model provide insights into spark ignition processes in complicated flow patterns.     

Nanograin Effects on the Thermoelectric Properties of Poly-Si Nanowires

In this work we perform a theoretical analysis of the thermoelectric performance of polycrystalline Si nanowires (NWs) by considering both electron and phonon transport. The simulations are calibrated with experimental data from monocrystalline and polycrystalline structures. We show that heavily doped polycrystalline NW structures with grain size below 100 nm might offer an alternative approach to achieve simultaneous thermal conductivity reduction and power factor improvements through improvements in the Seebeck coefficient. We find that deviations from the homogeneity of the channel and/or reduction in the diameter may provide strong reduction in the thermal conductivity. Interestingly, our calculations show that the Seebeck coefficient and consequently the power factor can be improved significantly once the polycrystalline geometry is properly optimized, while avoiding strong reduction in the electrical conductivity. In such a way, ZT values even higher than the ones reported for monocrystalline Si NWs can be achieved.     

Paradoxical Enhancement of the Power Factor of Polycrystalline Silicon as a Result of the Formation of Nanovoids

Hole-containing silicon has been regarded as a viable candidate thermoelectric material because of its low thermal conductivity. However, because voids are efficient scattering centers not just for phonons but also for charge carriers, achievable power factors (PFs) are normally too low for its most common form, i.e. porous silicon, to be of practical interest. In this communication we report that high PFs can, indeed, be achieved with nanoporous structures obtained from highly doped silicon. High PFs, up to a huge 22 mW K^?2 m^?1 (more than six times higher than values for the bulk material), were observed for heavily boron-doped nanocrystalline silicon films in which nanovoids (NVs) were generated by He⁺ ion implantation. In contrast with single-crystalline silicon in which He⁺ implantation leads to large voids, in polycrystalline films implantation followed by annealing at 1000°C results in homogeneous distribution of NVs with final diameters of approximately 2 nm and densities of the order of 10¹⁹ cm^?3 with average spacing of 10 nm. Study of its morphology revealed silicon nanograins 50 nm in diameter coated with 5-nm precipitates of SiB _x . We recently reported that PFs up to 15 mW K^?2 m^?1 could be achieved for silicon–boron nanocomposites (without NVs) because of a simultaneous increase of electrical conductivity and Seebeck coefficient. In that case, the high Seebeck coefficient was achieved as a result of potential barriers on the grain boundaries, and high electrical conductivity was achieved as a result of extremely high levels of doping. The additional increase in the PF observed in the presence of NVs (which also include SiB _x precipitates) might have several possible explanations; these are currently under investigation. Experimental results are reported which might clarify the reason for this paradoxical effect of NVs on silicon PF.     

Numerical study of the thermoelectric power factor in ultra-thin Si nanowires

Low dimensional structures have demonstrated improved thermoelectric (TE) performance because of a drastic reduction in their thermal conductivity, ?? _l . This has been observed for a variety of materials, even for traditionally poor thermoelectrics such as silicon. Other than the reduction in ?? _l , further improvements in the TE figure of merit ZT could potentially originate from the thermoelectric power factor. In this work, we couple the ballistic (Landauer) and diffusive linearized Boltzmann electron transport theory to the atomistic sp³d⁵s*-spin-orbit-coupled tight-binding (TB) electronic structure model. We calculate the room temperature electrical conductivity, Seebeck coefficient, and power factor of narrow 1D Si nanowires (NWs). We describe the numerical formulation of coupling TB to those transport formalisms, the approximations involved, and explain the differences in the conclusions obtained from each model. We investigate the effects of cross section size, transport orientation and confinement orientation, and the influence of the different scattering mechanisms. We show that such methodology can provide robust results for structures including thousands of atoms in the simulation domain and extending to length scales beyond 10?nm, and point towards insightful design directions using the length scale and geometry as a design degree of freedom. We find that the effect of low dimensionality on the thermoelectric power factor of Si NWs can be observed at diameters below ??7?nm, and that quantum confinement and different transport orientations offer the possibility for power factor optimization.     

Path Representation in Circuit Netlists Using Linear-Sized ZDDs with Optimal Variable Ordering

The efficient representation and manipulation of a large number of paths in a Directed Acyclic Graph (DAG) requires the usage of special data structures that may become of exponential size with respect to the size of the graph. Several methodologies targeting Electronic Design Automation problems such as timing analysis, physical design, verification and testing involve path representation and necessary manipulation. Previous works proposed an encoding using Zero-suppressed Binary Decision Diagrams (ZDDs), which has been shown experimentally to cope well when representing structural or logical paths in VLSI circuits. However, it is well known that the ordering of the variables in a ZDD highly affects its size and, therefore, the efficiency of the methodologies utilizing these data structures. In this work, we show that using a reverse topological order for the ZDD variables bounds the number of nodes in the ZDD representing structural paths to the number of edges in the DAG considered, hence, making the ZDD size linear to the DAG’s size. This result, supported here both theoretically and experimentally, is very important as it can render methodologies with questionable scalability applicable to larger industrial designs. We demonstrate the applicability of the proposed variable ordering in one such methodology which utilizes ZDDs to grade the Path Delay Fault coverage of a given test set.     

Atomistic calculations of the electronic, thermal, and thermoelectric properties of ultra-thin Si layers

Low-dimensional semiconductors are considered promising candidates for thermoelectric applications with enhanced performance because of a drastic reduction in their thermal conductivity, κ _l , and possibilities of enhanced power factors. This is also the case for traditionally poor thermoelectric materials such as silicon. This work presents atomistic simulations for the electronic, thermal, and thermoelectric properties of ultra-thin Si layers of thicknesses below 10 nm. The Linearized Boltzmann theory is coupled: (i) to the atomistic sp³d⁵s^? tight-binding (TB) model for the electronic properties of the thin layers, and (ii) to the modified valence-force-field method (MVFF) for the calculation of the thermal conductivity of the thin layers. We calculate the room temperature electrical conductivity, Seebeck coefficient, power factor, thermal conductivity, and ZT figure of merit of ultra-thin p-type Si layers (UTLs). We describe the numerical formulation of coupling TB and MVFF to the linearized Boltzmann transport formalism. The properties of UTLs are highly anisotropic, and optimized thermoelectric properties can be achieved by the choice of the appropriate transport and confinement orientations, as well as layer thickness.     

An inter-comparison of three urban wind models using Oklahoma City Joint Urban 2003 wind field measurements

Three wind models are compared to near-surface time-averaged wind measurements obtained in downtown Oklahoma City during the Joint Urban 2003 Field Campaign. The models cover several levels of computational approximation and include in increasing order of computational demand: a mass-consistent empirical-diagnostic code, a Reynolds-averaged Navier-Stokes (RANS) computational fluid dynamics (CFD) model, and a Large Eddy Simulation (LES) CFD code. The models were run with identical inlet and boundary conditions using the same grid resolution; the choice of the specific computational set-up reflects demands for fast-response models, although it may be a sub-optimal choice for the more complex models. A qualitative comparison of the model-computed flow fields with the Joint Urban 2003 wind measurements shows that all three models compare favorably to the near-surface wind measurements in many locations, although there are often instances of winds being calculated poorly in specific locations. The CFD models, however, had clearly superior looking flow fields, whereas the empirical-diagnostic code produced fields that were less smoothly varying. The inter-comparison exercise was supported by point-by-point quantitative comparisons of the wind speed and wind direction and with statistical measures. The RANS-CFD code, for example, was within 50% of the measured wind speed 62% of the time as compared to 53% for the LES model and 49% for the empirical-diagnostic code. For wind direction, the RANS-CFD code was within 30° of the measured wind direction 58% of the time as compared to 50% for the LES code and 43% for the empirical diagnostic code. It is noticeable that throughout the various IOP cases examined, and under the specific computational set-up used in the simulations for fast-response needs, there is no clear superiority of one model over another. In addition, for the LES model, which in theory should provide the most realistic representation of the flow field, it appears that further to the sub-optimal computational set-up, as well as the uncertainty and natural variability persistent in the real world, has resulted in diminished performance.