Structure and properties of an amorphous ferromagnetic alloy

The structure and the electrical and magnetic properties of an amorphous alloy containing approximately 80 at .% iron, 13 at.% phos phorus and 7 at.% carbon (Fe_(80)Fe_(13)C_7) obtained by rapid quenching from the liquid state have been studied. Transmission electron diffraction data confirm the amorphous nature of this alloy. An analysis of the radial distribution function obtained from X-ray diffraction data indicates that the number of nearest neighbors is approximately seven, at a distance of 2.6A. The structure of the alloy can be related to that of silicate glasses and is based on a random arrangement of trigonal prisms of Fe_2P and Fe_3C types in which the iron atoms have an average ligancy of seven. Electrical resistance measurements show that the alloys are metallic. A minimum in the electrical resistivity vs. temperature curve is observed between 10° K to 50° K depending on the specimen, and the temperature at which the minimum occurs is related to the degree of local ordering. The Fe-P-C amorphous alloys are ferromagnetic. The Curie temperature measured by the induction method and by Mossbauer spectroscopy is 315° C. The field dependence of the magneto-resistance at temperatures from liquid helium to room temperature is similar to that found in crystalline iron. The ordinary Hall coefficient is approximately 10^(-11) volt-cm/amp-G. The spontaneous Hall coefficient is about 0.6 x 10^(-9) volt-cm/amp-G and is practically independent of temperature from liquid helium temperature up to 300° c.

Part I. Approximate Hartree-Fock wavefunctions one-electron properties and electronic structure of the water molecule. Part II. Perturbation-variational calculation of the nuclear spin-spin isotope coupling constant in HD

Part I

Several approximate Hartree-Fock SCF wavefunctions for the ground electronic state of the water molecule have been obtained using an increasing number of multicenter s, p, and d Slater-type atomic orbitals as basis sets. The predicted charge distribution has been extensively tested at each stage by calculating the electric dipole moment, molecular quadrupole moment, diamagnetic shielding, Hellmann-Feynman forces, and electric field gradients at both the hydrogen and the oxygen nuclei. It was found that a carefully optimized minimal basis set suffices to describe the electronic charge distribution adequately except in the vicinity of the oxygen nucleus. Our calculations indicate, for example, that the correct prediction of the field gradient at this nucleus requires a more flexible linear combination of p-orbitals centered on this nucleus than that in the minimal basis set. Theoretical values for the molecular octopole moment components are also reported.

Part II

The perturbation-variational theory of R. M. Pitzer for nuclear spin-spin coupling constants is applied to the HD molecule. The zero-order molecular orbital is described in terms of a single 1s Slater-type basis function centered on each nucleus. The first-order molecular orbital is expressed in terms of these two functions plus one singular basis function each of the types e^-r/r and e^-r ln r centered on one of the nuclei. The new kinds of molecular integrals were evaluated to high accuracy using numerical and analytical means. The value of the HD spin-spin coupling constant calculated with this near-minimal set of basis functions is J_HD = +96.6 cps. This represents an improvement over the previous calculated value of +120 cps obtained without using the logarithmic basis function but is still considerably off in magnitude compared with the experimental measurement of J_HD = +43 0 ± 0.5 cps.

The structure of liquid argon as determined by x-ray diffraction

X-ray diffraction measurements and subsequent data analyses have been carried out on liquid argon at five states in the density range of 0.91 to 1.135 gm/cc and temperature range of 127 to 143°K. Duplicate measurements were made on all states. These data yielded radial distribution and direct correlation functions which were then used to compute the pair potential using the Percus-Yevick equation. The potential minima are in the range of -105 to -120°K and appear to substantiate current theoretical estimates of the effective pair potential in the presence of a weak three-body force.

The data analysis procedure used was new and does not distinguish between the coherent and incoherent absorption factors for the cell scattering which were essentially equal. With this simplification, the argon scattering estimate was compared to the gas scattering estimate on the laboratory frame of reference and the two estimates coincided, indicating the data normalized. The argon scattering on the laboratory frame of reference was examined for the existence of the peaks in the structure factor and the existence of an observable third peak was considered doubtful.

Numerical studies of the effect of truncation, normalization, the subsidiary peak phenomenon in the radial distribution function, uncertainties in the low angle data relative to errors in the direct correlation function and the distortion phenomenon are presented.

The distortion phenomenon for this experiment explains why the Mikolaj-Pings argon data yielded pair potential well depths from the Percus-Yevick equation that were too shallow and an apparent slope with respect to density that was too steep compared to theoretical estimates.

The data presented for each measurement are: empty cell and cell plus argon intensity, absorption factors, argon intensity, smoothed argon intensity, smoothed argon intensity corrected for distortion, structure factor, radial distribution function, direct correlation function and the pair potential from the Percus-Yevick equation.

I. Rigid body penetration into brittle materials. II. Phase change effect on shock wave propagation

Part I.

We have developed a technique for measuring the depth time history of rigid body penetration into brittle materials (hard rocks and concretes) under a deceleration of ~ 10⁵ g. The technique includes bar-coded projectile, sabot-projectile separation, detection and recording systems. Because the technique can give very dense data on penetration depth time history, penetration velocity can be deduced. Error analysis shows that the technique has a small intrinsic error of ~ 3-4 % in time during penetration, and 0.3 to 0.7 mm in penetration depth. A series of 4140 steel projectile penetration into G-mixture mortar targets have been conducted using the Caltech 40 mm gas/ powder gun in the velocity range of 100 to 500 m/s.

We report, for the first time, the whole depth-time history of rigid body penetration into brittle materials (the G-mixture mortar) under 10⁵ g deceleration. Based on the experimental results, including penetration depth time history, damage of recovered target and projectile materials and theoretical analysis, we find:

1. Target materials are damaged via compacting in the region in front of a projectile and via brittle radial and lateral crack propagation in the region surrounding the penetration path. The results suggest that expected cracks in front of penetrators may be stopped by a comminuted region that is induced by wave propagation. Aggregate erosion on the projectile lateral surface is < 20% of the final penetration depth. This result suggests that the effect of lateral friction on the penetration process can be ignored.

2. Final penetration depth, P_max, is linearly scaled with initial projectile energy per unit cross-section area, e_s , when targets are intact after impact. Based on the experimental data on the mortar targets, the relation is P_max(mm) 1.15e_s (J/mm² ) + 16.39.

3. Estimation of the energy needed to create an unit penetration volume suggests that the average pressure acting on the target material during penetration is ~ 10 to 20 times higher than the unconfined strength of target materials under quasi-static loading, and 3 to 4 times higher than the possible highest pressure due to friction and material strength and its rate dependence. In addition, the experimental data show that the interaction between cracks and the target free surface significantly affects the penetration process.

4. Based on the fact that the penetration duration, t_max, increases slowly with e_s and does not depend on projectile radius approximately, the dependence of t_max on projectile length is suggested to be described by t_max(μs) = 2.08e_s (J/mm² + 349.0 x m/(πR²), in which m is the projectile mass in grams and R is the projectile radius in mm. The prediction from this relation is in reasonable agreement with the experimental data for different projectile lengths.

5. Deduced penetration velocity time histories suggest that whole penetration history is divided into three stages: (1) An initial stage in which the projectile velocity change is small due to very small contact area between the projectile and target materials; (2) A steady penetration stage in which projectile velocity continues to decrease smoothly; (3) A penetration stop stage in which projectile deceleration jumps up when velocities are close to a critical value of ~ 35 m/s.

6. Deduced averaged deceleration, a, in the steady penetration stage for projectiles with same dimensions is found to be a(g) = 192.4v + 1.89 x 10⁴, where v is initial projectile velocity in m/s. The average pressure acting on target materials during penetration is estimated to be very comparable to shock wave pressure.

7. A similarity of penetration process is found to be described by a relation between normalized penetration depth, P/P_max, and normalized penetration time, t/t_max, as P/P_max = f(t/t_max, where f is a function of t/t_max. After f(t/t_max is determined using experimental data for projectiles with 150 mm length, the penetration depth time history for projectiles with 100 mm length predicted by this relation is in good agreement with experimental data. This similarity also predicts that average deceleration increases with decreasing projectile length, that is verified by the experimental data.

8. Based on the penetration process analysis and the present data, a first principle model for rigid body penetration is suggested. The model incorporates the models for contact area between projectile and target materials, friction coefficient, penetration stop criterion, and normal stress on the projectile surface. The most important assumptions used in the model are: (1) The penetration process can be treated as a series of impact events, therefore, pressure normal to projectile surface is estimated using the Hugoniot relation of target material; (2) The necessary condition for penetration is that the pressure acting on target materials is not lower than the Hugoniot elastic limit; (3) The friction force on projectile lateral surface can be ignored due to cavitation during penetration. All the parameters involved in the model are determined based on independent experimental data. The penetration depth time histories predicted from the model are in good agreement with the experimental data.

9. Based on planar impact and previous quasi-static experimental data, the strain rate dependence of the mortar compressive strength is described by σ_f/σ⁰_f = exp(0.0905(log(έ/έ_0) ^1.14, in the strain rate range of 10^-7/s to 10³/s (σ⁰_f and έ are reference compressive strength and strain rate, respectively). The non-dispersive Hugoniot elastic wave in the G-mixture has an amplitude of ~ 0.14 GPa and a velocity of ~ 4.3 km/s.

Part II.

Stress wave profiles in vitreous GeO₂ were measured using piezoresistance gauges in the pressure range of 5 to 18 GPa under planar plate and spherical projectile impact. Experimental data show that the response of vitreous GeO₂ to planar shock loading can be divided into three stages: (1) A ramp elastic precursor has peak amplitude of 4 GPa and peak particle velocity of 333 m/s. Wave velocity decreases from initial longitudinal elastic wave velocity of 3.5 km/s to 2.9 km/s at 4 GPa; (2) A ramp wave with amplitude of 2.11 GPa follows the precursor when peak loading pressure is 8.4 GPa. Wave velocity drops to the value below bulk wave velocity in this stage; (3) A shock wave achieving final shock state forms when peak pressure is > 6 GPa. The Hugoniot relation is D = 0.917 + 1.711u (km/s) using present data and the data of Jackson and Ahrens [1979] when shock wave pressure is between 6 and 40 GPa for ρ₀ = 3.655 gj cm³ . Based on the present data, the phase change from 4-fold to 6-fold coordination of Ge⁺⁴ with O^-2 in vitreous GeO₂ occurs in the pressure range of 4 to 15 ± 1 GPa under planar shock loading. Comparison of the shock loading data for fused SiO₂ to that on vitreous GeO₂ demonstrates that transformation to the rutile structure in both media are similar. The Hugoniots of vitreous GeO₂ and fused SiO₂ are found to coincide approximately if pressure in fused SiO₂ is scaled by the ratio of fused SiO₂to vitreous GeO₂ density. This result, as well as the same structure, provides the basis for considering vitreous Ge0₂ as an analogous material to fused SiO₂ under shock loading. Experimental results from the spherical projectile impact demonstrate: (1) The supported elastic shock in fused SiO₂ decays less rapidly than a linear elastic wave when elastic wave stress amplitude is higher than 4 GPa. The supported elastic shock in vitreous GeO₂ decays faster than a linear elastic wave; (2) In vitreous GeO₂ , unsupported shock waves decays with peak pressure in the phase transition range (4-15 GPa) with propagation distance, x, as α 1/x^-3.35 , close to the prediction of Chen et al. [1998]. Based on a simple analysis on spherical wave propagation, we find that the different decay rates of a spherical elastic wave in fused SiO₂ and vitreous GeO₂ is predictable on the base of the compressibility variation with stress under one-dimensional strain condition in the two materials.

Mathematical study of complex networks : brain, internet, and power grid

The dissertation is concerned with the mathematical study of various network problems. First, three real-world networks are considered: (i) the human brain network (ii) communication networks, (iii) electric power networks. Although these networks perform very different tasks, they share similar mathematical foundations. The high-level goal is to analyze and/or synthesis each of these systems from a “control and optimization” point of view. After studying these three real-world networks, two abstract network problems are also explored, which are motivated by power systems. The first one is “flow optimization over a flow network” and the second one is “nonlinear optimization over a generalized weighted graph”. The results derived in this dissertation are summarized below.

Brain Networks: Neuroimaging data reveals the coordinated activity of spatially distinct brain regions, which may be represented mathematically as a network of nodes (brain regions) and links (interdependencies). To obtain the brain connectivity network, the graphs associated with the correlation matrix and the inverse covariance matrix—describing marginal and conditional dependencies between brain regions—have been proposed in the literature. A question arises as to whether any of these graphs provides useful information about the brain connectivity. Due to the electrical properties of the brain, this problem will be investigated in the context of electrical circuits. First, we consider an electric circuit model and show that the inverse covariance matrix of the node voltages reveals the topology of the circuit. Second, we study the problem of finding the topology of the circuit based on only measurement. In this case, by assuming that the circuit is hidden inside a black box and only the nodal signals are available for measurement, the aim is to find the topology of the circuit when a limited number of samples are available. For this purpose, we deploy the graphical lasso technique to estimate a sparse inverse covariance matrix. It is shown that the graphical lasso may find most of the circuit topology if the exact covariance matrix is well-conditioned. However, it may fail to work well when this matrix is ill-conditioned. To deal with ill-conditioned matrices, we propose a small modification to the graphical lasso algorithm and demonstrate its performance. Finally, the technique developed in this work will be applied to the resting-state fMRI data of a number of healthy subjects.

Communication Networks: Congestion control techniques aim to adjust the transmission rates of competing users in the Internet in such a way that the network resources are shared efficiently. Despite the progress in the analysis and synthesis of the Internet congestion control, almost all existing fluid models of congestion control assume that every link in the path of a flow observes the original source rate. To address this issue, a more accurate model is derived in this work for the behavior of the network under an arbitrary congestion controller, which takes into account of the effect of buffering (queueing) on data flows. Using this model, it is proved that the well-known Internet congestion control algorithms may no longer be stable for the common pricing schemes, unless a sufficient condition is satisfied. It is also shown that these algorithms are guaranteed to be stable if a new pricing mechanism is used.

Electrical Power Networks: Optimal power flow (OPF) has been one of the most studied problems for power systems since its introduction by Carpentier in 1962. This problem is concerned with finding an optimal operating point of a power network minimizing the total power generation cost subject to network and physical constraints. It is well known that OPF is computationally hard to solve due to the nonlinear interrelation among the optimization variables. The objective is to identify a large class of networks over which every OPF problem can be solved in polynomial time. To this end, a convex relaxation is proposed, which solves the OPF problem exactly for every radial network and every meshed network with a sufficient number of phase shifters, provided power over-delivery is allowed. The concept of “power over-delivery” is equivalent to relaxing the power balance equations to inequality constraints.

Flow Networks: In this part of the dissertation, the minimum-cost flow problem over an arbitrary flow network is considered. In this problem, each node is associated with some possibly unknown injection, each line has two unknown flows at its ends related to each other via a nonlinear function, and all injections and flows need to satisfy certain box constraints. This problem, named generalized network flow (GNF), is highly non-convex due to its nonlinear equality constraints. Under the assumption of monotonicity and convexity of the flow and cost functions, a convex relaxation is proposed, which always finds the optimal injections. A primary application of this work is in the OPF problem. The results of this work on GNF prove that the relaxation on power balance equations (i.e., load over-delivery) is not needed in practice under a very mild angle assumption.

Generalized Weighted Graphs: Motivated by power optimizations, this part aims to find a global optimization technique for a nonlinear optimization defined over a generalized weighted graph. Every edge of this type of graph is associated with a weight set corresponding to the known parameters of the optimization (e.g., the coefficients). The motivation behind this problem is to investigate how the (hidden) structure of a given real/complex valued optimization makes the problem easy to solve, and indeed the generalized weighted graph is introduced to capture the structure of an optimization. Various sufficient conditions are derived, which relate the polynomial-time solvability of different classes of optimization problems to weak properties of the generalized weighted graph such as its topology and the sign definiteness of its weight sets. As an application, it is proved that a broad class of real and complex optimizations over power networks are polynomial-time solvable due to the passivity of transmission lines and transformers.

Proteomic analysis of the Cdc48/Ubx network identifies a role for Ubx2 in the regulation of lipid biosynthesis

Cdc48/p97 is an essential, highly abundant hexameric member of the AAA (ATPase associated with various cellular activities) family. It has been linked to a variety of processes throughout the cell but it is best known for its role in the ubiquitin proteasome pathway. In this system it is believed that Cdc48 behaves as a segregase, transducing the chemical energy of ATP hydrolysis into mechanical force to separate ubiquitin-conjugated proteins from their tightly-bound partners.

Current models posit that Cdc48 is linked to its substrates through a variety of adaptor proteins, including a family of seven proteins (13 in humans) that contain a Cdc48-binding UBX domain. As such, due to the complexity of the network of adaptor proteins for which it serves as the hub, Cdc48/p97 has the potential to exert a profound influence on the ubiquitin proteasome pathway. However, the number of known substrates of Cdc48/p97 remains relatively small, and smaller still is the number of substrates that have been linked to a specific UBX domain protein. As such, the goal of this dissertation research has been to discover new substrates and better understand the functions of the Cdc48 network. With this objective in mind, we established a proteomic screen to assemble a catalog of candidate substrate/targets of the Ubx adaptor system.

Here we describe the implementation and optimization of a cutting-edge quantitative mass spectrometry method to measure relative changes in the Saccharomyces cerevisiae proteome. Utilizing this technology, and in order to better understand the breadth of function of Cdc48 and its adaptors, we then performed a global screen to identify accumulating ubiquitin conjugates in cdc48-3 and ubxΔ mutants. In this screen different ubx mutants exhibited reproducible patterns of conjugate accumulation that differed greatly from each other, pointing to various unexpected functional specializations of the individual Ubx proteins.

As validation of our mass spectrometry findings, we then examined in detail the endoplasmic-reticulum bound transcription factor Spt23, which we identified as a putative Ubx2 substrate. In these studies ubx2Δ cells were deficient in processing of Spt23 to its active p90 form, and in localizing p90 to the nucleus. Additionally, consistent with reduced processing of Spt23, ubx2Δ cells demonstrated a defect in expression of their target gene OLE1, a fatty acid desaturase. Overall, this work demonstrates the power of proteomics as a tool to identify new targets of various pathways and reveals Ubx2 as a key regulator lipid membrane biosynthesis.

Role of feedback and dynamics in a gene regulatory network

Cells exhibit a diverse repertoire of dynamic behaviors. These dynamic functions are implemented by circuits of interacting biomolecules. Although these regulatory networks function deterministically by executing specific programs in response to extracellular signals, molecular interactions are inherently governed by stochastic fluctuations. This molecular noise can manifest as cell-to-cell phenotypic heterogeneity in a well-mixed environment. Single-cell variability may seem like a design flaw but the coexistence of diverse phenotypes in an isogenic population of cells can also serve a biological function by increasing the probability of survival of individual cells upon an abrupt change in environmental conditions. Decades of extensive molecular and biochemical characterization have revealed the connectivity and mechanisms that constitute regulatory networks. We are now confronted with the challenge of integrating this information to link the structure of these circuits to systems-level properties such as cellular decision making. To investigate cellular decision-making, we used the well studied galactose gene-regulatory network in \textit{Saccharomyces cerevisiae}. We analyzed the mechanism and dynamics of the coexistence of two stable on and off states for pathway activity. We demonstrate that this bimodality in the pathway activity originates from two positive feedback loops that trigger bistability in the network. By measuring the dynamics of single-cells in a mixed sugar environment, we observe that the bimodality in gene expression is a transient phenomenon. Our experiments indicate that early pathway activation in a cohort of cells prior to galactose metabolism can accelerate galactose consumption and provide a transient increase in growth rate. Together these results provide important insights into strategies implemented by cells that may have been evolutionary advantageous in competitive environments.

Signal transduction, regulation, and developmental logic of EGFR signalling in C. elegans

RTKs-mediated signaling systems and the pathways with which they interact (e.g., those initiated by G protein-mediated signaling) involve a highly cooperative network that sense a large number of cellular inputs and then integrate, amplify, and process this information to orchestrate an appropriate set of cellular responses. The responses include virtually all aspects of cell function, from the most fundamental (proliferation, differentiation) to the most specialized (movement, metabolism, chemosensation). The basic tenets of RTK signaling system seem rather well established. Yet, new pathways and even new molecular players continue to be discovered. Although we believe that many of the essential modules of RTK signaling system are rather well understood, we have relatively little knowledge of the extent of interaction among these modules and their overall quantitative importance.

My research has encompassed the study of both positive and negative signaling by RTKs in C. elegans. I identified the C. elegans S0S-1 gene and showed that it is necessary for multiple RAS-mediated developmental signals. In addition, I demonstrated that there is a SOS-1-independent signaling during RAS-mediated vulval differentiation. By assessing signal outputs from various triple mutants, I have concluded that this SOS-1-independent signaling is not mediated by PTP-2/SHP-2 or the removal of inhibition by GAP-1/ RasGAP and it is not under regulation by SLI-1/Cb1. I speculate that there is either another exchange factor for RASor an as yet unidentified signaling pathway operating during RAS-mediated vulval induction in C. elegans.

In an attempt to uncover the molecular mechanisms of negative regulation of EGFR signaling by SLI-1/Cb1, I and two other colleagues codiscovered that RING finger domain of SLI-1 is partially dispensable for activity. This structure-function analysis shows that there is an ubiquitin protein ligase-independent activity for SLI-1 in regulating EGFR signaling. Further, we identified an inhibitory tyrosine of LET-23/ EGFR requiring sli-1(+)for its effects: removal of this tyrosine closely mimics loss of sli-1 but not loss of other negative regulator function.

By comparative analysis of two RTK pathways with similar signaling mechanisms, I have found that clr-1, a previously identified negative regulator of egl-15 mediated FGFR signaling, is also involved in let-23 EGFR signaling. The success of this approach promises a similar reciprocal test and could potentially extend to the study of other signaling pathways with similar signaling logic.

Finally, by correlating the developmental expression of lin-3 EGF to let-23 EGFR signaling activity, I demonstrated the existence of reciprocal EGF signaling in coordinating the morphogenesis of epithelia. This developmental logic of EGF signaling could provide a basis to understand a universal mechanism for organogenesis.

Neural network design for switching network control

A neural network is a highly interconnected set of simple processors. The many connections allow information to travel rapidly through the network, and due to their simplicity, many processors in one network are feasible. Together these properties imply that we can build efficient massively parallel machines using neural networks. The primary problem is how do we specify the interconnections in a neural network. The various approaches developed so far such as outer product, learning algorithm, or energy function suffer from the following deficiencies: long training/ specification times; not guaranteed to work on all inputs; requires full connectivity.

Alternatively we discuss methods of using the topology and constraints of the problems themselves to design the topology and connections of the neural solution. We define several useful circuits-generalizations of the Winner-Take-All circuitthat allows us to incorporate constraints using feedback in a controlled manner. These circuits are proven to be stable, and to only converge on valid states. We use the Hopfield electronic model since this is close to an actual implementation. We also discuss methods for incorporating these circuits into larger systems, neural and nonneural. By exploiting regularities in our definition, we can construct efficient networks. To demonstrate the methods, we look to three problems from communications. We first discuss two applications to problems from circuit switching; finding routes in large multistage switches, and the call rearrangement problem. These show both, how we can use many neurons to build massively parallel machines, and how the Winner-Take-All circuits can simplify our designs.

Next we develop a solution to the contention arbitration problem of high-speed packet switches. We define a useful class of switching networks and then design a neural network to solve the contention arbitration problem for this class. Various aspects of the neural network/switch system are analyzed to measure the queueing performance of this method. Using the basic design, a feasible architecture for a large (1024-input) ATM packet switch is presented. Using the massive parallelism of neural networks, we can consider algorithms that were previously computationally unattainable. These now viable algorithms lead us to new perspectives on switch design.

Distributed Load Control in Multiphase Radial Networks

The current power grid is on the cusp of modernization due to the emergence of distributed generation and controllable loads, as well as renewable energy. On one hand, distributed and renewable generation is volatile and difficult to dispatch. On the other hand, controllable loads provide significant potential for compensating for the uncertainties. In a future grid where there are thousands or millions of controllable loads and a large portion of the generation comes from volatile sources like wind and solar, distributed control that shifts or reduces the power consumption of electric loads in a reliable and economic way would be highly valuable.

Load control needs to be conducted with network awareness. Otherwise, voltage violations and overloading of circuit devices are likely. To model these effects, network power flows and voltages have to be considered explicitly. However, the physical laws that determine power flows and voltages are nonlinear. Furthermore, while distributed generation and controllable loads are mostly located in distribution networks that are multiphase and radial, most of the power flow studies focus on single-phase networks.

This thesis focuses on distributed load control in multiphase radial distribution networks. In particular, we first study distributed load control without considering network constraints, and then consider network-aware distributed load control.

Distributed implementation of load control is the main challenge if network constraints can be ignored. In this case, we first ignore the uncertainties in renewable generation and load arrivals, and propose a distributed load control algorithm, Algorithm 1, that optimally schedules the deferrable loads to shape the net electricity demand. Deferrable loads refer to loads whose total energy consumption is fixed, but energy usage can be shifted over time in response to network conditions. Algorithm 1 is a distributed gradient decent algorithm, and empirically converges to optimal deferrable load schedules within 15 iterations.

We then extend Algorithm 1 to a real-time setup where deferrable loads arrive over time, and only imprecise predictions about future renewable generation and load are available at the time of decision making. The real-time algorithm Algorithm 2 is based on model-predictive control: Algorithm 2 uses updated predictions on renewable generation as the true values, and computes a pseudo load to simulate future deferrable load. The pseudo load consumes 0 power at the current time step, and its total energy consumption equals the expectation of future deferrable load total energy request.

Network constraints, e.g., transformer loading constraints and voltage regulation constraints, bring significant challenge to the load control problem since power flows and voltages are governed by nonlinear physical laws. Remarkably, distribution networks are usually multiphase and radial. Two approaches are explored to overcome this challenge: one based on convex relaxation and the other that seeks a locally optimal load schedule.

To explore the convex relaxation approach, a novel but equivalent power flow model, the branch flow model, is developed, and a semidefinite programming relaxation, called BFM-SDP, is obtained using the branch flow model. BFM-SDP is mathematically equivalent to a standard convex relaxation proposed in the literature, but numerically is much more stable. Empirical studies show that BFM-SDP is numerically exact for the IEEE 13-, 34-, 37-, 123-bus networks and a real-world 2065-bus network, while the standard convex relaxation is numerically exact for only two of these networks.

Theoretical guarantees on the exactness of convex relaxations are provided for two types of networks: single-phase radial alternative-current (AC) networks, and single-phase mesh direct-current (DC) networks. In particular, for single-phase radial AC networks, we prove that a second-order cone program (SOCP) relaxation is exact if voltage upper bounds are not binding; we also modify the optimal load control problem so that its SOCP relaxation is always exact. For single-phase mesh DC networks, we prove that an SOCP relaxation is exact if 1) voltage upper bounds are not binding, or 2) voltage upper bounds are uniform and power injection lower bounds are strictly negative; we also modify the optimal load control problem so that its SOCP relaxation is always exact.

To seek a locally optimal load schedule, a distributed gradient-decent algorithm, Algorithm 9, is proposed. The suboptimality gap of the algorithm is rigorously characterized and close to 0 for practical networks. Furthermore, unlike the convex relaxation approach, Algorithm 9 ensures a feasible solution. The gradients used in Algorithm 9 are estimated based on a linear approximation of the power flow, which is derived with the following assumptions: 1) line losses are negligible; and 2) voltages are reasonably balanced. Both assumptions are satisfied in practical distribution networks. Empirical results show that Algorithm 9 obtains 70+ times speed up over the convex relaxation approach, at the cost of a suboptimality within numerical precision.

Structure-Function Studies of Nicotinic Acetylcholine Receptors Using Selective Agonists and Positive Allosteric Modulators

This dissertation primarily describes chemical-scale studies of nicotinic acetylcholine receptors (nAChRs) in order to better understand ligand-receptor selectivity and allosteric modulation influences during receptor activation. Electrophysiology coupled with canonical and non-canonical amino acids mutagenesis is used to probe subtle changes in receptor function.

The first half of this dissertation focuses on differential agonist selectivity of α4β2-containing nAChRs. The α4β2 nAChR can assemble in alternative stoichiometries as well as assemble with other accessory subunits. Chapter 2 identifies key structural residues that dictate binding and activation of three stoichiometry-dependent α4β2 receptor ligands: sazetidine-A, cytisine, and NS9283. These do not follow previously suggested hydrogen-bonding patterns of selectivity. Instead, three residues on the complementary subunit strongly influence binding ability of a ligand and receptor activation. Chapter 3 involves isolation of a α5α4β2 receptor-enriched population to test for a potential alternative agonist binding location at the α5 α4 interface. Results strongly suggest that agonist occupation of this site is not necessary for receptor activation and that the α5 subunit only incorporates at the accessory subunit location.

The second half of this dissertation seeks to identify residue interactions with positive allosteric modulators (PAMs) of the α7 nAChR. Chapter 4 focuses on methods development to study loss of potentiation of Type I PAMs, which indicate residues vital to propagation of PAM effects and/or binding. Chapter 5 investigates α7 receptor modulation by a Type II PAM (PNU 120596). These results show that PNU 120596 does not alter the agonist binding site, thus is relegated to influencing only the gating component of activation. From this, we were able to map a potential network of residues from the agonist binding site to the proposed PNU 120596 binding site that are essential for receptor potentiation.

The Molecular Basis of Lysine Acetylation: Addition, Removal, and Recognition

Acetyltransferases and deacetylases catalyze the addition and removal, respectively, of acetyl groups to the epsilon-amino group of protein lysine residues. This modification can affect the function of a protein through several means, including the recruitment of specific binding partners called acetyl-lysine readers. Acetyltransferases, deacetylases, and acetyl-lysine readers have emerged as crucial regulators of biological processes and prominent targets for the treatment of human disease. This work describes a combination of structural, biochemical, biophysical, cell-biological, and organismal studies undertaken on a set of proteins that cumulatively include all steps of the acetylation process: the acetyltransferase MEC-17, the deacetylase SIRT1, and the acetyl-lysine reader DPF2. Tubulin acetylation by MEC-17 is associated with stable, long-lived microtubule structures. We determined the crystal structure of the catalytic domain of human MEC-17 in complex with the cofactor acetyl-CoA. The structure in combination with an extensive enzymatic analysis of MEC-17 mutants identified residues for cofactor and substrate recognition and activity. A large, evolutionarily conserved hydrophobic surface patch distal to the active site was shown to be necessary for catalysis, suggesting that specificity is achieved by interactions with the alpha-tubulin substrate that extend outside of the modified surface loop. Experiments in C. elegans showed that while MEC-17 is required for touch sensitivity, MEC-17 enzymatic activity is dispensible for this behavior. SIRT1 deacetylates a wide range of substrates, including p53, NF-kappaB, FOXO transcription factors, and PGC-1-alpha, with roles in cellular processes ranging from energy metabolism to cell survival. SIRT1 activity is uniquely controlled by a C-terminal regulatory segment (CTR). Here we present crystal structures of the catalytic domain of human SIRT1 in complex with the CTR in an apo form and in complex with a cofactor and a pseudo-substrate peptide. The catalytic domain adopts the canonical sirtuin fold. The CTR forms a beta-hairpin structure that complements the beta-sheet of the NAD^+-binding domain, covering an essentially invariant, hydrophobic surface. A comparison of the apo and cofactor bound structures revealed conformational changes throughout catalysis, including a rotation of a smaller subdomain with respect to the larger NAD^+-binding subdomain. A biochemical analysis identified key residues in the active site, an inhibitory role for the CTR, and distinct structural features of the CTR that mediate binding and inhibition of the SIRT1 catalytic domain. DPF2 represses myeloid differentiation in acute myelogenous leukemia. Finally, we solved the crystal structure of the tandem PHD domain of human DPF2. We showed that DPF2 preferentially binds H3 tail peptides acetylated at Lys14, and binds H4 tail peptides with no preference for acetylation state. Through a structural and mutational analysis we identify the molecular basis of histone recognition. We propose a model for the role of DPF2 in AML and identify the DPF2 tandem PHD finger domain as a promising novel target for anti-leukemia therapeutics.

Part I: Latent heat of vaporization of n-decane. Part II: Heat and mass transfer from a cylinder placed in a turbulent air stream - Sherwood and Frössling numbers as a function of free stream turbulence level and Reynolds number

Part I

The latent heat of vaporization of n-decane is measured calorimetrically at temperatures between 160° and 340°F. The internal energy change upon vaporization, and the specific volume of the vapor at its dew point are calculated from these data and are included in this work. The measurements are in excellent agreement with available data at 77° and also at 345°F, and are presented in graphical and tabular form.

Part II

Simultaneous material and energy transport from a one-inch adiabatic porous cylinder is studied as a function of free stream Reynolds Number and turbulence level. Experimental data is presented for Reynolds Numbers between 1600 and 15,000 based on the cylinder diameter, and for apparent turbulence levels between 1.3 and 25.0 per cent. n-heptane and n-octane are the evaporating fluids used in this investigation.

Gross Sherwood Numbers are calculated from the data and are in substantial agreement with existing correlations of the results of other workers. The Sherwood Numbers, characterizing mass transfer rates, increase approximately as the 0.55 power of the Reynolds Number. At a free stream Reynolds Number of 3700 the Sherwood Number showed a 40% increase as the apparent turbulence level of the free stream was raised from 1.3 to 25 per cent.

Within the uncertainties involved in the diffusion coefficients used for n-heptane and n-octane, the Sherwood Numbers are comparable for both materials. A dimensionless Frössling Number is computed which characterizes either heat or mass transfer rates for cylinders on a comparable basis. The calculated Frössling Numbers based on mass transfer measurements are in substantial agreement with Frössling Numbers calculated from the data of other workers in heat transfer.

The ionic basis of frequency selectivity in hair cells of the bullfrog's sacculus

Hair cells from the bull frog's sacculus, a vestibular organ responding to substrate-borne vibration, possess electrically resonant membrane properties which maximize the sensitivity of each cell to a particular frequency of mechanical input. The electrical resonance of these cells and its underlying ionic basis were studied by applying gigohm-seal recording techniques to solitary hair cells enzymatically dissociated from the sacculus. The contribution of electrical resonance to frequency selectivity was assessed from microelectrode recordings from hair cells in an excised preparation of the sacculus.

Electrical resonance in the hair cell is demonstrated by damped membrane-potential oscillations in response to extrinsic current pulses applied through the recording pipette. This response is analyzed as that of a damped harmonic oscillator. Oscillation frequency rises with membrane depolarization, from 80-160 Hz at resting potential to asymptotic values of 200-250 Hz. The sharpness of electrical tuning, denoted by the electrical quality factor, Q_e, is a bell-shaped function of membrane voltage, reaching a maximum value around eight at a membrane potential slightly positive to the resting potential.

In whole cells, three time-variant ionic currents are activated at voltages more positive than -60 to -50 mV; these are identified as a voltage-dependent, non-inactivating Ca current (I_ca), a voltage-dependent, transient K current (I_a), and a Ca-dependent K current (I_c). The C channel is identified in excised, inside-out membrane patches on the basis of its large conductance (130-200 pS), its selective permeability to Kover Na or Cl, and its activation by internal Ca ions and membrane depolarization. Analysis of open- and closed-lifetime distributions suggests that the C channel can assume at least two open and three closed kinetic states.

Exposing hair cells to external solutions that inhibit the Ca or C conductances degrades the electrical resonance properties measured under current-clamp conditions, while blocking the A conductance has no significant effect, providing evidence that only the Ca and C conductances participate in the resonance mechanism. To test the sufficiency of these two conductances to account for electrical resonance, a mathematical model is developed that describes I_ca, I_c, and intracellular Ca concentration during voltage-clamp steps. I_ca activation is approximated by a third-order Hodgkin-Huxley kinetic scheme. Ca entering the cell is assumed to be confined to a small submembrane compartment which contains an excess of Ca buffer; Ca leaves this space with first-order kinetics. The Ca- and voltage-dependent activation of C channels is described by a five-state kinetic scheme suggested by the results of single-channel observations. Parameter values in the model are adjusted to fit the waveforms of I_ca and I_c evoked by a series of voltage-clamp steps in a single cell. Having been thus constrained, the model correctly predicts the character of voltage oscillations produced by current-clamp steps, including the dependencies of oscillation frequency and Q_e on membrane voltage. The model shows quantitatively how the Ca and C conductances interact, via changes in intracellular Ca concentration, to produce electrical resonance in a vertebrate hair cell.