Parameterized Complexity of Edge Interdiction Problems

We study the parameterized complexity of interdiction problems in graphs. For an optimization problem on graphs, one can formulate an interdiction problem as a game consisting of two players, namely, an interdictor and an evader, who compete on an objective with opposing interests. In edge interdiction problems, every edge of the input graph has an interdiction cost associated with it and the interdictor interdicts the graph by modifying the edges in the graph, and the number of such modifications is constrained by the interdictor's budget. The evader then solves the given optimization problem on the modified graph. The action of the interdictor must impede the evader as much as possible. We focus on edge interdiction problems related to minimum spanning tree, maximum matching and shortest paths. These problems arise in different real world scenarios. We derive several fixed-parameter tractability and W[1]-hardness results for these interdiction problems with respect to various parameters. Next, we show close relation between interdiction problems and partial cover problems on bipartite graphs where the goal is not to cover all elements but to minimize/maximize the number of covered elements with specific number of sets. Hereby, we investigate the parameterized complexity of several partial cover problems on bipartite graphs

Programming Process, Patterns and Behaviors: Insights from Keystroke Analysis of CS1 Students

With all the experiences and knowledge, I take programming as granted. But learning to program is still difficult for a lot of introductory programming students. This is also one of the major reasons for a high attrition rate in CS1 courses. If instructors were able to identify struggling students then effective interventions can be taken to help them. This thesis is a research done on programming process data that can be collected non-intrusively from CS1 students when they are programming. The data and their findings can be leveraged in understanding students’ thought process, detecting patterns and identifying behaviors that could possibly help instructors to identify struggling students, help them and design better courses

Trade and investment linkages and coordination in Nepal: Impact on productivity and exports and business perceptions

This research paper intends to analyse: (a) the impacts of ASEAN trade liberalization on the macroeconomy variables – gross domestic product (GDP), Terms of Trade (ToT), balance of trade, inflation and real wage – and agricultural industries (output, exports and imports) in the ASEAN 6 countries (Indonesia, Malaysia, the Philippines, Thailand, Singapore, and Viet Nam); and (b) the impact of trade liberalization on income distribution in Indonesia. A multi-country and multi-commodity computable general equilibrium (CGE) GTAP model has been used as the main tool of analysis.Trade and Investment, Nepal, Impact on productivity

Role of the immunoglobulin superfamily member Basigin in sensory neuron dendrite morphogenesis in Drosophila

Neurons develop highly stereotypic dendritic arbors that influence establishment of proper connections and integration of information they receive to generate an appropriate output. Morphogenesis of dendrites is coordinated by both cell-intrinsic and extrinsic factors. Recent studies have begun to elucidate how interactions between neurons shape dendrite morphogenesis. However, influence of the substrate upon which neurons grow their dendritic arbors in this process is relatively poorly understood. Here I have used the peripheral sensory neurons of the Drosophila larva that grow dendrites over epithelial cell substrates to gain insights into how interactions with the substrate may influence dendrite development. In this thesis, I present data showing that Basigin, an immunoglobulin superfamily member, has somatodendritic and axonal localization in sensory neurons, and is enriched at cell borders and beneath class IV dendrites in epithelial cells. Loss of function analyses indicate that Basigin is required both in neurons and epithelial cell substrates for proper morphogenesis of the highly complex dendrites of class IV sensory neurons. Reduced innervation of the dendritic field of basigin mutant neurons was observed even at an immature stage, indicating a requirement of Basigin in these neurons for developmental elaboration of dendritic arbors. Structure-function analysis revealed that membrane-tethering of Basigin on the neuronal surface is essential for its function. In addition, a highly conserved tri-basic motif consisting of positively charged residues that may bind cytoskeletal adaptor proteins is required for its function in neurons. Results of genetic interaction analysis suggest that Basigin-mediated regulation of dendrite morphogenesis does not involve Integrin and matrix metalloproteinases, both of which have been implicated in Basigin function in other cellular contexts. I show that Basigin exhibits genetic interaction with Tropomodulin, an actin-capping protein, suggesting that they function in the same molecular pathway in regulating dendrite development. Taken together, data presented in this thesis support a model in which interaction between Basigin on the surfaces of neurons and epithelial cells regulate the underlying cytoskeleton within dendrites to influence their development. Thus, these results identify a novel molecular pathway that may mediate communication between neurons and their substrates that is essential for proper dendrite morphogenesis

Enabling autoscaling for in-memory storage in cluster computing framework

2019 Spring.Includes bibliographical references.IoT enabled devices and observational instruments continuously generate voluminous data. A large portion of these datasets are delivered with the associated geospatial locations. The increased volumes of geospatial data, alongside the emerging geospatial services, pose computational challenges for large-scale geospatial analytics. We have designed and implemented STRETCH , an in-memory distributed geospatial storage that preserves spatial proximity and enables proactive autoscaling for frequently accessed data. STRETCH stores data with a delayed data dispersion scheme that incrementally adds data nodes to the storage system. We have devised an autoscaling feature that proactively repartitions data to alleviate computational hotspots before they occur. We compared the performance of S TRETCH with Apache Ignite and the results show that STRETCH provides up to 3 times the throughput when the system encounters hotspots. STRETCH is built on Apache Spark and Ignite and interacts with them at runtime

Poletsky-Stessin Hardy Spaces on the Unit Disk

The holomorphic functions on the unit disk $\mathbb{D}$ in the complex plane $\mathbb{C}$ have a remarkable property: to know the values of a holomorphic function on $\mathbb{D}$ it suffices to know only its values on the unit circle $\mathbb{T}$. However not all holomorphic functions on $\mathbb{D}$ are defined on $\mathbb{T}$ and the major problem of establishing such values (called boundary values) led to the appearance of Hardy spaces $H^p(\mathbb{D})$, $p\ge1$. If a function lies in a Hardy space then its boundary values can be defined and its values on $\mathbb{D}$ can be obtained using standard Cauchy or Poisson formulas. The theory of Hardy spaces $H^p(\mathbb{D})$ was well developed in the last century and the spaces became the fundamental ground for complex analysis. To create analogous spaces in higher dimensions Poletsky and Stessin introduced new spaces on hyperconvex domains in $\mathbb{C}^n$ in \cite{PS}. We call these spaces the Poletsky--Stessin Hardy spaces. Poletsky and Stessin used them to study composition operators but did not look at their detailed properties. In this thesis we fill this gap studying Poletsky--Stessin Hardy spaces on the unit disk $\mathbb{D}$. As in \cite{PS} for their definition we use subharmonic exhaustion functions $u$ and denote these spaces by $H^p_u(\mathbb{D})$. It was mentioned in \cite{PS} that the classical Hardy spaces form a subclass of Poletsky--Stessin Hardy spaces. Our work begins with producing an example that shows that there are subharmonic exhaustion functions $u$ on $\mathbb{D}$ for which the Poletsky--Stessin Hardy spaces $H^p_u(\mathbb{D})$ are different from classical Hardy spaces $H^p(\mathbb{D})$. Thus we have an abundance of new function spaces to be explored. We show that the theory of boundary values for functions in Poletsky--Stessin Hardy spaces is analogous to the classical theory of Hardy spaces and the most of the classical properties stay true for these new spaces. Since by \cite{PS} the space $H^p_u(\mathbb{D})$ lies in $H^p(\mathbb{D})$ we can use the classical boundary values for functions in $H^p_u(\mathbb{D})$. This allows us to redefine Poletsky--Stessin Hardy spaces as spaces whose boundary values belong to weighted $L^p$ spaces on $\mathbb{T}$ and we completely characterize the weights that produce Poletsky--Stessin Hardy spaces $H^p_u(\mathbb{D})$. Many problems in complex analysis ask for existence of a bounded function in some class. Usually it is easier to find a function in $H^p_u(\mathbb{D})$ but they are not necessarily bounded. As an application of Poletsky--Stessin Hardy spaces we provide a reduction of such problems to the existence of a function in $H^p_u(\mathbb{D})$ and use it to give shortcuts in the proofs of the famous interpolation theorem and corona problem. At the end of the thesis we also study the boundary behavior of functions in the Hardy spaces on the polydisk and discuss the intersection of Poletsky--Stessin spaces on bidisk

Exploring The Physics Of Proteins At Molecular Level By Neutron And X-Ray Scattering

The protein structures revealed by the crystallographic studies have provided the valuable information over the years regarding their biological functions. However, such snapshots of protein fluctuations averaged over time may not be enough to fully capture the underlying biological phenomena. A deeper understanding of the protein dynamics is crucial for elucidating the structural pathways or the transition mechanism from the initial state to the final state necessary for regulating the physical and chemical processes. Hence, the biological activities and functions are mainly governed by the protein conformational dynamics. However, the direct correlation of a wide range of protein dynamics to function still remains unclear, posing a major challenge to biophysical community. In this dissertation, the relationships among the protein\u27s conformation, dynamics and function are investigated using the state-of-the-art neutron and X-ray scattering techniques. Taking the advantage of comparable wavelength and momentum transfer of neutron and X-ray to that of the atoms, we studied the protein dynamics at molecular level over the timescale of few femtoseconds to nanoseconds regime, which provides the information regarding the conformational flexibility of protein. Interestingly, we observed that the protein dynamic behavior is similar to that of glass forming liquids, where the relaxation process is non-exponential and the collective excitations are highly damped. Specifically, picosecond to nanosecond dynamics, also known as beta-relaxation process decays logarithmically over the time. Remarkably, such dynamic phenomena revealed the direct experimental evidences of structure-dynamics-function relationship of a large variety of protein family such as a large hyperthermophilic protein, a membrane protein, and the native and denatured globular proteins. Simultaneously, we successfully applied the idea of generic free-energy landscape based upon the dynamic behavior possessed by the proteins to explain their activities. The dynamic behavior of a hyperthermophilic protein from the deep-sea is studied using the quasi-elastic neutron scattering (QENS). QENS results revealed that the dynamic property of a mesophilic protein is largely affected by the high pressure and temperature by distorting the protein energy landscape and therefore the activity. On the other hand, the hyperthermophilic protein restrains such effects. In addition, the mechanism of light activation of a G-protein-coupled receptor (GPCR), rhodopsin as a prototype is studied using small-angle neutron scattering (SANS) and QENS. The SANS data indicates the large conformational change in rhodopsin upon photoactivation. On the other hand, the QENS results show the significant difference in the intrinsic protein dynamics between the dark-state rhodopsin and the ligand-free apoprotein, opsin. These observed conformational and dynamical differences in rhodopsin activation are due to the influence of the covalently bound retinal chromophore. The glass-like collective excitations in proteins are also investigated using inelastic neutron and X-ray scattering techniques. Such excitations correspond to the intrinsic protein dynamics necessary to overcome the conformational barriers, crucial for enzyme catalysis and ligand-binding. The data show the apparent softening of protein with rise in temperature, which reveals the protein conformational flexibility. Specifically, these results suggest that the native globular protein balances the protein conformational flexibility and rigidity for the biological activity. Furthermore, the conformational change in periplasmic ligand-binding protein (PBP) upon bound to peptide is studied using the small-angle X-ray scattering (SAXS). The SAXS measurements from the ligand-free and the ligand-bound periplasmic protein, MppA do not show significant conformational change. It may be due to the low-resolution of the instrument such that a few angstrom of change in protein conformation is inaccessible. On the other hand, the three-dimensional shape reconstruction of MppA computed from SAXS intensity profile using ab-initio modeling matches perfectly its crystal structure

Efficiency and Reliability Analysis of AC and 380V DC Data Centers

The rapid growth of the Internet has resulted in colossal increase in the number of data centers. A data center consume a tremendous amount of electricity resulting in high operation cost. Even a slight improvement in the power distribution system of a data center could save millions of dollars in electricity bills. Benchmarks for both AC and 380V DC data centers are developed and efficiency analyses thereof have been performed for an entire year. The efficiency of the power distribution system can be increased if number of power conversion stages can be reduced and more efficient converters are used. Use of wide band gap (WBG) converters will further improve the overall system efficiency because of its high efficiency. The results shows that 380V DC data centers are more efficient than AC data centers with and without PV integration. Using 380V DC distribution system not only improve the efficiency of the system, but it saves millions of dollars by decreasing system downtime. Maintaining high availability at all times is very critical to data centers. The distribution system with higher number of series components is more likely to fail, resulting in increased downtime. This study aims at comparing reliabilities of AC against 380V DC architecture. Reliability assessment was done for both AC and DC systems complying with Tier IV standard. The analysis was done for different level of redundancy (eg. N, N+1, N+2) in the UPS system for both AC and DC systems. Monte Carlo simulation method was used to perform the reliability calculations. The simulation results showed that the 380V DC distribution system has higher level of reliability than AC distribution system in data centers but only up to certain level of redundancy in the UPS system. The reliability level of AC system will approach to that of a DC system when a very high level of redundancy in the UPS system is considered, but this will increase the overall cost of a data center