Miracle-dz/UniFAR-FTUs huggingface dataset:
A Continuum Electrostatic Analysis of Protein Binding: Barnase-Barstar Complex Formation

Understanding the nature of protein–protein recognition is fundamental to the study of biological processes. The complex between barnase, a bacterial RNase, with its intracellular inhibitor, barstar, is a suitable system for the general problem of molecular recognition since the structures of the proteins have been solved, both separately and in the protein complex. This interaction between barnase and barstar is extremely tight with a Kd of 10 14M (Schrieber & Fersht, 1993) and is predominantly electrostatic. We are studying the role of electrostatics in the stability and specificity of the barnase– barstar complex using a continuum method which utilizes iterative finite-difference methods offered in the DELPHI (Gilson et al., 1988) software package. Although electrostatic analysis is much less expensive than molecular-dynamics simulation, our computations required about 10 days of CPU time. Quanta, a high-performance interactive color graphics system, has enabled us to visualize the complex in three-dimensions on an SGI workstation by using coordinates extracted from the X-ray crystal structure of the complex. Background: A considerable amount of research has been done on the barnase–barstar complex. The X-ray crystal structures of barnase–barstar (Buckle et al., 1994) and of barnase alone (Mauguen et al., 1982; Bycroft et al., 1991) have been solved to high resolution. The structure of barstar in solution has been solved by NMR (Lubienski et al., 1994). Several mutagenesis studies of barnase–barstar have been conducted (Hartley, 1993; Schrieber & Fersht, 1993; Schrieber et al., 1994). Accurate free energy values from kinetic and thermodynamic measurements are available in a recent singleand doublemutant cycle study of barnase–barstar (Schrieber & Fersht, 1995). The double-mutant cycle study is especially intriguing because, in principle, it isolates the electrostatic interactions between a pair of residues from interactions with the rest of the protein. This study has revealed several important This work is advised by Prof. Bruce Tidor and supported in part by NIH grant GM-47678 and a Science Partnership from MIT. Address: Room 6-135, 77 Massachusetts Avenue, Cambridge MA 02139. Figure 1: The barnase–barstar complex. The barnase structure is lightly shaded on the left and the barstar structure is heavily shaded on the right.
Fast power system analysis via implicit linearization of the power flow manifold

In this paper, we consider the manifold that describes all feasible power flows in a power system as an implicit algebraic relation between nodal voltages (in polar coordinates) and nodal power injections (in rectangular coordinates). We derive the best linear approximant of such a relation around a generic solution of the power flow equations. Our linear approximant is sparse, computationally attractive, and preserves the structure of the power flow. Thanks to the full generality of this approach, the proposed linear implicit model can be used to obtain a fast approximate solution of a possibly unbalanced three phase power system, with either radial or meshed topology, and with general bus models. We demonstrate how our approximant includes standard existing linearizations, we validate the quality of the approximation via simulations on a standard testbed, and we illustrate its applicability with case studies in scenario-based optimization and cascading failures.
Early Dengue Virus Protein Synthesis Induces Extensive Rearrangement of the Endoplasmic Reticulum Independent of the UPR and SREBP-2 Pathway

The rearrangement of intracellular membranes has been long reported to be a common feature in diseased cells. In this study, we used dengue virus (DENV) to study the role of the unfolded protein response (UPR) and sterol-regulatory-element-binding-protein-2 (SREBP-2) pathway in the rearrangement and expansion of the endoplasmic reticulum (ER) early after infection. Using laser scanning confocal and differential interference contrast microscopy, we demonstrate that rearrangement and expansion of the ER occurs early after DENV-2 infection. Through the use of mouse embryonic fibroblast cells deficient in XBP1 and ATF6, we show that ER rearrangement early after DENV infection is independent of the UPR. We then demonstrate that enlargement of the ER is independent of the SREBP-2 activation and upregulation of 3-hydroxy-3-methylglutaryl-Coenzyme-A reductase, the rate-limiting enzyme in the cholesterol biosynthesis pathway. We further show that this ER rearrangement is not inhibited by the treatment of DENV-infected cells with the cholesterol-inhibiting drug lovastatin. Using the transcription inhibitor actinomycin D and the translation elongation inhibitor cycloheximide, we show that de novo viral protein synthesis but not host transcription is necessary for expansion and rearrangement of the ER. Lastly, we demonstrate that viral infection induces the reabsorption of lipid droplets into the ER. Together, these results demonstrate that modulation of intracellular membrane architecture of the cell early after DENV-2 infection is driven by viral protein expression and does not require the induction of the UPR and SREBP-2 pathways. This work paves the way for further study of virally-induced membrane rearrangements and formation of cubic membranes.
Solving, Estimating and Testing Nonlinear Stochastic Equilibrium Models

This paper describes a method for solving, estimating and testing a fully specified nonlinear stochastic equilibrium model by simulation in the context of an asset pricing model. A nonlinear stochastic asset pricing model with production and money is formulated, which aims to explain observed empirical relations between inflation and asset returns. Complete solution paths to the equilibrium model are generated through a backr-jards mapping simulation methc^ that does not call for any approximation procedures. The parameters of the model are estimated by simulation talcing account of a broad range of dynamics of the model, and overidentifying restrictions of the model are tested by extending C^iM procedijres. October 1986 revised August 1987 * This paper has benefited considerably from the help, advice and comments of Chris Sims, Barry FajLk, Eind two anonymous referees. All errors are my o^vn responsibility.
Web-based Parameterized Questions for Object-Oriented Programming

Web-based questions for assessment and self-assessment of students’ knowledge are important components of modern E-Learning. Parameterized questions allow to enhance the value of Web-based questions while also decreasing the authoring costs. This paper discusses the problems of implementation and evaluation of online parameterized questions for the domain of object-oriented programming. We present QuizJET – a system supporting authoring, delivery, and automatic assessment of parameterized online quizzes and questions—aimed at teaching a non-formula-based domain, Java programming language. The classroom evaluation of QuizJET demonstrated that by working with the system students were able to improve their scores on in-class weekly quizzes. We have also observed a significant relation between the amount of work and the success rate of students and their scores on the final exam.
Multi-target tracking using mixed spatio-temporal features learning model

In image sequence, target's features has two components: the spatial features which include the local background and nearby targets, and the temporal features which include all appearances of the targets seen previously. In this paper, we develop a multi-target visual tracking method based on mixed spatio-temporal features learning model which is a probabilistic inference model considering the above components. The proposed model combine the incremental appearance descriptor update strategy which can update descriptor dynamically according to previous appearances during tracking, and mix probabilistic data association which take targets' spatial features into account. In addition, we also apply the incremental update strategy into HSV histogram and region covariance descriptor, and compare these two descriptors in multi-target visual tracking. The results validate the proposed method in tracking moving multi-target in video streams.
Using Carbonic Anhydrase and Silica Nanomaterials in Carbon Dioxide Mitigation

As carbon dioxide levels in the atmosphere continue to rise, the necessity for efficient and effective carbon mitigation and sequestration techniques increases as well. However, attempts thus far have proven to be too expensive or speculative to be implemented on a global level. Our goal was therefore to devise a solution that is both efficient and cost effective. To do this, we utilized the catalytic properties of carbonic anhydrase, an enzyme contained in the lungs of mammals, to accelerate the reaction that converts carbon dioxide to bicarbonate, which can then be converted to useful products such as baking soda. Because enzymes are normally difficult to recover and can easily denature in suboptimal temperatures and pH levels, we attached them to silica nanospheres via enzyme immobilization in order to make them recoverable and more resilient to changes in environmental conditions. In testing this process, our results showed that a solution containing the immobilized enzymes was around 67 percent more efficient over the control, which contained no enzymes. Furthermore, we saw success in the silica’s ability to immobilize the enzymes, as they were able to immobilize between 66.4 and 77.4 percent of the carbonic anhydrase in solution. Though we need to conduct further research to optimize this procedure, these positive preliminary results indicate that there is much promise in pursuing this method as means for carbon mitigation.
Cosmic ray acceleration by spiral shocks in the galactic wind

Cosmic ray acceleration by shocks related with Slipping Interaction Regions (SIRs) in the Galactic Wind is considered. SIRs are similar to Solar Wind Corotating Interaction Regions. The spiral structure of our Galaxy results in a strong nonuniformity of the Galactic Wind flow and in SIR formation at distances of 50 to 100 kpc. SIRs are not corotating with the gas and magnetic field because the angular velocity of the spiral pattern differs from that of the Galactic rotation. It is shown that the collective reacceleration of the cosmic ray particles with charge $Z\rm e$ in the resulting shock ensemble can explain the observable cosmic ray spectrum beyond the “knee” up to energies of the order of $10^{17}\,Z$ eV. For the reaccelerated particles the Galactic Wind termination shock acts as a reflecting boundary.
INFLUENCE OF FOOD MANIPULATION ON PLASMA CORTICOSTERONE, INNATE IMMUNITY, AND BLOOD CHEMISTRY IN THE BROWN AFRICAN HOUSE SNAKE (LAMPROPHIS FULIGINOSUS)

ii ACKNOWLEDGMENTS I would like to thank Dr. Matthew Klukowski for his guidance, patience and encouragement throughout my entire Masters experience. I would also like to thank Dr. Brian Miller and Dr. Frank Bailey for their expertise and guidance. A special thanks to Dr. Neil Ford for letting us use his animals for much longer than planned. To my significant other, family, and friends, you are my heart, moon, and stars. iii ABSTRACT The ability to tolerate the stress of extended periods of food restriction is an evolutionarily important trait that has significant effects on survivorship in the wild. There are different physiological mechanisms by which certain species survive these periods: elevation of the stress hormone corticosterone, reduction of immune function, and reduction in reproductive activity are well documented responses to food restriction. These responses to food shortage have been documented in species ranging from mammals to amphibians, but to my knowledge, have not been performed within a sex-based context in colubrid snakes. Thus the objectives of this project are to document the effects of food manipulation and sex on plasma corticosterone, innate immunity and blood chemistry in the African brown house snake, Lamprophis fuliginosus. Sex differences would seem especially likely in reptile species that are strongly sexually dimorphic, such as the African brown house snake. With their larger body mass, females would be expected to have the capacity for much larger energy reserves than males and thus experience less dramatic changes in physiology in response to food restriction. This project consisted of a ten week food restriction period in which twenty-four snakes (16 female, 8 male) were fed just 5% of their body mass every two weeks and a five week recuperation period during which all snakes were fed ad lib. During the 15week project, four blood samples were collected from each snake to measure corticosterone, bacterial killing capacity (with E. coli), hemolytic capacity (with sheep RBC), leukocytes, testosterone, estradiol, triglyceride, and uric acid concentrations. I predicted that corticosterone would increase during the 10-week period of food restriction and that as iv corticosterone increases, immune function would decrease with varying degrees between the sexes.
CYNTENATOR: Progressive Gene Order Alignment of 17 Vertebrate Genomes

Whole genome gene order evolution in higher eukaryotes was initially considered as a random process. Gene order conservation or conserved synteny was seen as a feature of common descent and did not imply the existence of functional constraints. This view had to be revised in the light of results from sequencing dozens of vertebrate genomes. It became apparent that other factors exist that constrain gene order in some genomic regions over long evolutionary time periods. Outside of these regions, genomes diverge more rapidly in terms of gene content and order. We have developed CYNTENATOR, a progressive gene order alignment software, to identify genomic regions of conserved synteny over a large set of diverging species. CYNTENATOR does not depend on nucleotide-level alignments and a priori homology assignment. Our software implements an improved scoring function that utilizes the underlying phylogeny. In this manuscript, we report on our progressive gene order alignment approach, a and give a comparison to previous software and an analysis of 17 vertebrate genomes for conservation in gene order. CYNTENATOR has a runtime complexity of and a space complexity of with being the gene number in a genome. CYNTENATOR performs as good as state-of-the-art software on simulated pairwise gene order comparisons, but is the only algorithm that works in practice for aligning dozens of vertebrate-sized gene orders. Lineage-specific characterization of gene order across 17 vertebrate genomes revealed mechanisms for maintaining conserved synteny such as enhancers and coregulation by bidirectional promoters. Genes outside conserved synteny blocks show enrichments for genes involved in responses to external stimuli, stimuli such as immunity and olfactory response in primate genome comparisons. We even see significant gene ontology term enrichments for breakpoint regions of ancestral nodes close to the root of the phylogeny. Additionally, our analysis of transposable elements has revealed a significant accumulation of LINE-1 elements in mammalian breakpoint regions. In summary, CYNTENATOR is a flexible and scalable tool for the identification of conserved gene orders across multiple species over long evolutionary distances.
Load balancing for hybrid NoSQL database management systems

NoSQL database systems nowadays need to make trade-offs to optimize for their applications by considering consistency, availability, or partition tolerance. While a hybrid database system can use various kinds of database software and take advantage of their features for individual applications and workloads, how to make the database software work together to achieve the highest performance is still a challenging problem. In this paper, we propose Attila, a data-oriented load balancer that monitors the performance of each database node, dynamically detects the hot spots in a hybrid database system, and migrates data to improve the overall throughput. We also provide an extendable and flexible database interface for integrating NoSQL databases and adding database operations. Our experiment results show that, in average, the additional overhead of Attila is about 140--200 microseconds, residing in request transmission and parsing, which is acceptable, considering the improved throughput from the hybrid database system.
Energy-aware data gathering and routing protocol based on double cluster-heads

This paper proposed an Energy-aware Data Gathering Protocol Based on Double Cluster-heads EAGRDC. Vice cluster head is added in the cluster to responsible for data forwarding, thus it can unload part of the energy consumption of the main cluster head, so the frequency of the cluster head become death node can be decreased in the network, thus effectively balance the residual energy of nodes in the network. When routing between clusters, a layer structure is used to seek the next hop node. The experiment results showed that, compared to LEACH and EADEEG, EAGRDC can effectively extend the time of death of node 30 rounds, and its number of cluster head is the most stable, thus it can significantly prolong the lifetime of network.
KRAS Mutant Pancreatic Cancer: No Lone Path to an Effective Treatment

Pancreatic ductal adenocarcinoma (PDAC) is among the deadliest cancers with a dismal 7% 5-year survival rate and is projected to become the second leading cause of cancer-related deaths by 2020. KRAS is mutated in 95% of PDACs and is a well-validated driver of PDAC growth and maintenance. However, despite comprehensive efforts, an effective anti-RAS drug has yet to reach the clinic. Different paths to inhibiting RAS signaling are currently under investigation in the hope of finding a successful treatment. Recently, direct RAS binding molecules have been discovered, challenging the perception that RAS is an “undruggable” protein. Other strategies currently being pursued take an indirect approach, targeting proteins that facilitate RAS membrane association or downstream effector signaling. Unbiased genetic screens have identified synthetic lethal interactors of mutant RAS. Most recently, metabolic targets in pathways related to glycolytic signaling, glutamine utilization, autophagy, and macropinocytosis are also being explored. Harnessing the patient’s immune system to fight their cancer is an additional exciting route that is being considered. The “best” path to inhibiting KRAS has yet to be determined, with each having promise as well as potential pitfalls. We will summarize the state-of-the-art for each direction, focusing on efforts directed toward the development of therapeutics for pancreatic cancer patients with mutated KRAS.
Intrusion detection system using Optimum-Path Forest

Intrusion detection systems that make use of artificial intelligence techniques in order to improve effectiveness have been actively pursued in the last decade. Neural networks and Support Vector Machines have been also extensively applied to this task. However, their complexity to learn new attacks has become very expensive, making them inviable for a real time retraining. In this research, we introduce a new pattern classifier named Optimum-Path Forest (OPF) to this task, which has demonstrated to be similar to the state-of-the-art pattern recognition techniques, but extremely more efficient for training patterns. Experiments on public datasets showed that OPF classifier may be a suitable tool to detect intrusions on computer networks, as well as allow the algorithm to learn new attacks faster than the other techniques.
Principal Component Null Space Analysis for Image / Video Classification

We present a new classification algorithm, Principal Component Null Space Analysis (PCNSA), which is designed for “apples from oranges” type classification problems like object recognition where different classes have unequal and non-white noise covariance matrices. PCNSA first obtains a principal components subspace (PCA space) for the entire data in order to maximize the between-class variance. In this PCA space, it finds for each class ‘ i’, n Mi dimensional subspace along which the class’s intra-class variance is the smallest. We call this subspace an Approximate Null Space (ANS) since the lowest variance is usually “much smaller” than the highest. A query is classified into class ‘ i’ if its distance from the class’s mean in the class’s ANS is a minimum. We derive tight upper bounds on classification error probability. We use these expressions to compare classification performance of PCNSA with that of Subspace Linear Discriminant Analysis (SLDA) [1]. We propose a practical modification of PCNSA called progressive-PCNSA that also detects ‘new’ (untrained classes). Finally, we provide a brief experimental comparison of PCNSA, progressive-PCNSA and SLDA for three image classification problems object recognition, facial feature matching and face recognition under large pose/expression variation. We also show application of PCNSA to two classification problems in video an abnormal activity detection problem and an action retrieval problem.
Challenges and Solutions for Handoff Issues in 4G Wireless Systems An Overview

As the wireless communications technologies evolve dramatically, the recent research focus has shifted to the development of fourth-generation (4G) mobile systems. Instead of developing a new uniform standard for all wireless communications systems, 4G communication networks strive to seamlessly integrate various existing wireless communication technologies. One of the major challenges in this migration is to realize seamless handoffs among various communications systems with small handoff latency and packet loss. In this paper, we give a survey on existing handoff schemes for IP-Based 4G mobile networks. Specifically, we describe three handover algorithms, Mobile IPv6 protocol, Hierarchical Mobile IPv6 protocol, and IDMP-based fast handoffs. In addition, we compare these handover schemes at the end.