Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding Protein Flexibility through Dimensionality Reduction

This work shows how to decrease the complexity of modeling flexibility in proteins by reducing the number of dimensions necessary to model important macromolecular motions such as the induced-fit process. Induced fit occurs during the binding of a protein to other proteins, nucleic acids, or small molecules (ligands) and is a critical part of protein function. It is now widely accepted that conformational changes of proteins can affect their ability to bind other molecules and that any progress in modeling protein motion and flexibility will contribute to the understanding of key biological functions. However, modeling protein flexibility has proven a very difficult task. Experimental laboratory methods, such as x-ray crystallography, produce rather limited information, while computational methods such as molecular dynamics are too slow for routine use with large systems. In this work, we show how to use the principal component analysis method, a dimensionality reduction technique, to transform the original high-dimensional representation of protein motion into a lower dimensional representation that captures the dominant modes of motions of proteins. For a medium-sized protein, this corresponds to reducing a problem with a few thousand degrees of freedom to one with less than fifty. Although there is inevitably some loss in accuracy, we show that we can obtain conformations that have been observed in laboratory experiments, starting from different initial conformations and working in a drastically reduced search space.
Enzyme specificity under dynamic control II: Principal component analysis of α‐lytic protease using global and local solvent boundary conditions

The contributions of conformational dynamics to substrate specificity have been examined by the application of principal component analysis to molecular dynamics trajectories of α‐lytic protease. The wild‐type α‐lytic protease is highly specific for substrates with small hydrophobic side chains at the specificity pocket, while the Met190→Ala binding pocket mutant has a much broader specificity, actively hydrolyzing substrates ranging from Ala to Phe. Based on a combination of multiconformation analysis of cryo‐X‐ray crystallographic data, solution nuclear magnetic resonance (NMR), and normal mode calculations, we had hypothesized that the large alteration in specificity of the mutant enzyme is mainly attributable to changes in the dynamic movement of the two walls of the specificity pocket. To test this hypothesis, we performed a principal component analysis using 1‐nanosecond molecular dynamics simulations using either a global or local solvent boundary condition. The results of this analysis strongly support our hypothesis and verify the results previously obtained by in vacuo normal mode analysis. We found that the walls of the wild‐type substrate binding pocket move in tandem with one another, causing the pocket size to remain fixed so that only small substrates are recognized. In contrast, the M190A mutant shows uncoupled movement of the binding pocket walls, allowing the pocket to sample both smaller and larger sizes, which appears to be the cause of the observed broad specificity. The results suggest that the protein dynamics of α‐lytic protease may play a significant role in defining the patterns of substrate specificity. As shown here, concerted local movements within proteins can be efficiently analyzed through a combination of principal component analysis and molecular dynamics trajectories using a local solvent boundary condition to reduce computational time and matrix size.
Heterogeneous Self-Reconfiguring Robotics Ph.D. Thesis Proposal

Self-reconfiguring robots are modular systems that can change shape, or reconfigure, to match structure to task. They comprise many small, discrete, often identical modules that connect together and that are minimally actuated. Global shape transformation is achieved by composing local motions. Systems with a single module type, known as homogeneous systems, gain fault tolerance, robustness and low production cost from module interchangeability. However, we are interested in heterogeneous systems, which include multiple types of modules such as those with sensors, batteries or wheels. We believe that heterogeneous systems offer the same benefits as homogeneous systems with the added ability to match not only structure to task, but also capability to task. Although significant results have been achieved in understanding homogeneous systems, research in heterogeneous systems is challenging as key algorithmic issues remain unexplored. We propose in this thesis to investigate questions in four main areas: 1) how to classify heterogeneous systems, 2) how to develop efficient heterogeneous reconfiguration algorithms with desired characteristics, 3) how to characterize the complexity of key algorithmic problems, and 4) how to apply these heterogeneous algorithms to perform useful new tasks in simulation and in the physical world. Our goal is to develop an algorithmic basis for heterogeneous systems. This has theoretical significance in that it addresses a major open problem in the field, and practical significance in providing self-reconfiguring robots with increased capabilities.
Bengali Question Classification: Towards Developing QA System

This paper demonstrates the question classification step towards building a question answering system in Bengali. Bengali is an eastern Indo-Aryan language with about 230 million total speakers and one of the most spoken languages in the world. An important first step in developing a question answering system is to classify natural language question properly. In this work, we have studied suitable lexical, syntactic and semantic features to classify the Bengali question. As Bengali question classification is at early stage of development, so for simplicity we have proposed single-layer taxonomy which consists of only nine course-grained classes. We have also studied and categorized the interrogatives in Bengali language. The proposed automated classification work is based on various machine learning techniques. The baseline system based on Naive Bayes classifier has achieved 80.65% accuracy. We have achieved up to 87.63% accuracy using decision tree classifier.
Ethanol extract from portulaca oleracea L. attenuated acetaminophen-induced mice liver injury.

Acetaminophen-induced liver injury represents the most frequent cause of drug-induced liver failure in the world. Portulaca oleracea L. , a widely distributed weed, has been used as a folk medicine in many countries. Previously, we reported that the ethanol extracts of Portulaca oleracea L. (PO) exhibited significant anti-hypoxic activity. In the present study, we investigated the role of PO on acetaminophen (APAP) induced hepatotoxicity. The results demonstrated that PO was an effective anti-oxidative agent, which could, to some extent, reverse APAP-induced hepatotoxicity by regulating the reactive oxygen species (ROS) in the liver of mice. At the same time, PO treatment significantly decreased mice serum levels of IL-6 and TNFα and their mRNA expression in liver tissue IL-α and TNFα play an important role during APAP-induced liver injury. Furthermore, PO inhibited APAP and TNFα-induced activation of JNK, whose activation play an important effect during APAP induced liver injury. These findings suggested that administration of PO may be an effective strategy to prevent or treat liver injury induced by APAP.
Development, testing and selection of attitude determination algorithm for STUDSAT-2

This paper describes development, testing and selection of an attitude determination algorithm for STUDSAT-2 (STUDent SATellite). The algorithms, namely TRIAD, Optimized TRIAD, Davenport's Q and QUEST are considered. For testing, these are coded in MATLAB and then compared on the basis of errors in angle of rotation about Gibbs vector. Least squares criterion is accounted for, by minimization of loss function. Computational efficiency is accessed using stand-alone precompiled optimized codes in embedded C language. A detailed analysis of results obtained by aforementioned means is carried out in selection of the best algorithm for the project.
Toolkit design for interactive structured graphics

Here, we analyze toolkit designs for building graphical applications with rich user interfaces, comparing polylithic and monolithic toolkit-based solutions. Polylithic toolkits encourage extension by composition and follow a design philosophy similar to 3D scene graphs supported by toolkits including JavaSD and Openlnventor. Monolithic toolkits, on the other hand, encourage extension by inheritance, and are more akin to 2D graphical user interface toolkits such as Swing or MFC. We describe Jazz (a polylithic toolkit) and Piccolo (a monolithic toolkit), each of which we built to support interactive 2D structured graphics applications in general, and zoomable user interface applications in particular. We examine the trade offs of each approach in terms of performance, memory requirements, and programmability. We conclude that a polylithic approach is most suitable for toolkit builders, visual design software where code is automatically generated, and application builders where there is much customization of the toolkit. Correspondingly, we find that monolithic approaches appear to be best for application builders where there is not much customization of the toolkit.
The enterocyte microvillus is a vesicle-generating organelle

For decades, enterocyte brush border microvilli have been viewed as passive cytoskeletal scaffolds that serve to increase apical membrane surface area. However, recent studies revealed that in the in vitro context of isolated brush borders, myosin-1a (myo1a) powers the sliding of microvillar membrane along core actin bundles. This activity also leads to the shedding of small vesicles from microvillar tips, suggesting that microvilli may function as vesicle-generating organelles in vivo. In this study, we present data in support of this hypothesis, showing that enterocyte microvilli release unilamellar vesicles into the intestinal lumen; these vesicles retain the right side out orientation of microvillar membrane, contain catalytically active brush border enzymes, and are specifically enriched in intestinal alkaline phosphatase. Moreover, myo1a knockout mice demonstrate striking perturbations in vesicle production, clearly implicating this motor in the in vivo regulation of this novel activity. In combination, these data show that microvilli function as vesicle-generating organelles, which enable enterocytes to deploy catalytic activities into the intestinal lumen.
Decentralized spectrum allocation in D2D underlying cellular networks

The proliferation of novel network access devices and demand for high quality of service by the end users are proving to be insufficient and are straining the existing wireless cellular network capacity. An economic and promising alternate to enhance the spectral efficiency and network throughput is device to device (D2D) communication. However, enabling D2D communication poses significant challenges pertaining to the interference management. In this paper, we address the resource allocation problem for underlay D2D pairs. First, we formulate the resource allocation optimization problem with an objective to maximizes the throughput of all D2D pairs by imposing interference constraints for protecting the cellular users. Second, to solve the underlying mixed-integer non linear resource allocation problem, we propose a stable, self-organizing and distributed solution using matching theory. Finally, we simulate our proposition to validate the convergence, cellular user protection, and network throughput gains achieved by the proposal. Simulation results reveal that D2D pairs can achieve significant throughput gains (i.e., up to 45 - 91%) while protecting the cellular users compared to the scenario in which no D2D pairs exist.
Enhancement of Tumour-Specific Immune Responses In Vivo by ‘MHC Loading-Enhancer’ (MLE)

Background Class II MHC molecules (MHC II) are cell surface receptors displaying short protein fragments for the surveillance by CD4+ T cells. Antigens therefore have to be loaded onto this receptor in order to induce productive immune responses. On the cell surface, most MHC II molecules are either occupied by ligands or their binding cleft has been blocked by the acquisition of a non-receptive state. Direct loading with antigens, as required during peptide vaccinations, is therefore hindered. Principal Findings Here we show, that the in vivo response of CD4+ T cells can be improved, when the antigens are administered together with ‘MHC-loading enhancer’ (MLE). MLE are small catalytic compounds able to open up the MHC binding site by triggering ligand-release and stabilizing the receptive state. Their enhancing effect on the immune response was demonstrated here with an antigen from the influenza virus and tumour associated antigens (TAA) derived from the NY-ESO-1 protein. The application of these antigens in combination with adamantane ethanol (AdEtOH), an MLE compound active on human HLA-DR molecules, significantly increased the frequency of antigen-specific CD4+ T cells in mice transgenic for the human MHC II molecule. Notably, the effect was evident only with the MLE-susceptible HLA-DR molecule and not with murine MHC II molecules non-susceptible for the catalytic effect of the MLE. Conclusion MLE can specifically increase the potency of a vaccine by facilitating the efficient transfer of the antigen onto the MHC molecule. They may therefore open a new way to improve vaccination efficacy and tumour-immunotherapy.
Morphological Alterations of the Esophagus after Endoscopic Sclerotherapy of Varices

With the combined peri- and intravascular sclerosing technique esophageal varices can be completely eliminated in an average of three treatment sessions. In order to check the success of the procedure, endoscopic and histological findings at the various stages of treatment after sclerosing with 1% Polidocanol were compared. Clinical and autopsy findings are in agreement. After sclerosing, necroses of the mucosa and intramural inflammations occur regularly in the first week. The varices are thrombosed. Later, the inner wall of the esophagus is cicatricially changed. Histologically the fibroses extend transmurally and in some parts even reach the musculature.
Anti-Americanism and the American World Order

News stories remind us almost daily that anti-American opinion is rampant in every corner of the globe. Journalists, scholars, and politicians alike reinforce the perception that anti-Americanism is an entrenched sentiment in many foreign countries. Political scientist Giacomo Chiozza challenges this conventional wisdom, arguing that foreign public opinion about the U.S. is much more diverse and nuanced than is generally believed. Chiozza examines the character, source, and persistence of foreign attitudes toward the United States. His findings are based on worldwide public opinion databases that surveyed anti-American sentiment in Islamic countries, Europe, Latin America, Africa, and East Asia. Data compiled from responses in a wide range of categories-including politics, wealth, science and technology, popular culture, and education-indicate that anti-American sentiments vary widely across these geographic regions. Through careful analyses, Chiozza shows how foreign publics balance the political, social, and cultural dimensions of the U.S. in their own perceptions of the country. He finds that popular anti-Americanism is mostly benign and shallow; deep-seated ideological opposition to the U.S. is usually held among a minority of groups. More often, Chiozza explains, foreigners have conflicting attitudes toward the U.S. He finds that while anti-Americanism certainly exists, the United States is equally praised as a symbol of democracy and freedom, its ideals of liberty, equality, and opportunity applauded. Chiozza clearly demonstrates that what is reported as undisputed fact-that various groups abhor American values-is in reality a complex story.
Implications of Subliminal Classical Conditioning for Defeating the Use of Countermeasures in the Detection of Deception: Subliminal Evaluation

Abstract : Traditionally, classical conditioning paradigms have focused on reflexive responses to stimuli that are readily identified. In this research, the probability and magnitude of electrodermal responses elicited by stimuli below awareness levels (subliminal) were investigated. Thirty male college students were randomly assigned to either a supraliminal or subliminal treatment group (15 per group). During conditioning employing a partial reinforcement schedule, one of three geometric shapes presented at awareness level (supraliminal) was paired with a 1 to 4 milliampere electrical shock of 250 milliseconds duration. After conditioning had occurred, subjects electrodermal responses to sub- and supraliminally presented stimuli (the geometric shapes) were measured. Backward masking was used to reduce the probability of accurate stimulus recognition during the subliminal treatment condition. Data analysis showed that subjects in both conditions responded more frequently to target stimuli (CS+) than to stimuli which had not been previously paired with shock (Cs-). While subliminally presented stimulus recognition accuracy did not differ significantly from chance level, the frequency and magnitude of subliminal treatment group responses to both the CS+ and Cs- were greater than those of the supraliminal group. These results suggest that subliminally presented visual stiniuli can elicit differential autonomic nervous system responding to CS+ and Cs-. The higher rate of responding and larger response magnitudes observed in the subliminal group may, however, have been due to generalized Cs+ expectancy in a situation where the stimuli could not be accurately identified.
Quantitative comparison of power management algorithms

Dynamic power management saves power by shutting down idle devices. Several management algorithms have been proposed and demonstrated to be effective in certain applications. We quantitatively compare the power saving and performance impact of these algorithms on hard disks of a desktop and notebook computers. This paper has three contributions. First, we build a framework in Windows NT to implement power managers running realistic workloads and directly interacting with users. Second, we define performance degradation that reflects user perception. Finally, we compare power saving and performance of existing algorithms and analyze the difference.
ShadowStream: performance evaluation as a capability in production internet live streaming networks

As live streaming networks grow in scale and complexity, they are becoming increasingly difficult to evaluate. Existing evaluation methods including lab/testbed testing, simulation, and theoretical modeling, lack either scale or realism. The industrial practice of gradually-rolling-out in a testing channel is lacking in controllability and protection when experimental algorithms fail, due to its passive approach. In this paper, we design a novel system called ShadowStream that introduces evaluation as a built-in capability in production Internet live streaming networks. ShadowStream introduces a simple, novel, transparent embedding of experimental live streaming algorithms to achieve safe evaluations of the algorithms during large-scale, real production live streaming, despite the possibility of large performance failures of the tested algorithms. ShadowStream also introduces transparent, scalable, distributed experiment orchestration to resolve the mismatch between desired viewer behaviors and actual production viewer behaviors, achieving experimental scenario controllability. We implement ShadowStream based on a major Internet live streaming network, build additional evaluation tools such as deterministic replay, and demonstrate the benefits of ShadowStream through extensive evaluations.
Spectral and Nonlinear Analyses of MEG Background Activity in Patients With Alzheimer's Disease

The aim of the present study is to analyze the magnetoencephalogram (MEG) background activity from patients with Alzheimer's disease (AD) and elderly control subjects. MEG recordings from 20 AD patients and 21 controls were analyzed by means of two spectral [median frequency (MF) and spectral entropy (SpecEn)] and two nonlinear parameters [approximate entropy (ApEn) and Lempel-Ziv complexity (LZC)]. In the AD diagnosis, the highest accuracy of 75.6% (80% sensitivity, 71.4% specificity) was obtained with the MF according to a linear discriminant analysis (LDA) with a leave-one-out cross-validation procedure. Moreover, we wanted to assess whether these spectral and nonlinear analyses could provide complementary information to improve the AD diagnosis. After a forward stepwise LDA with a leave-one-out cross-validation procedure, one spectral (MF) and one nonlinear parameter (ApEn) were automatically selected. In this model, an accuracy of 80.5% (80.0% sensitivity, 81.0% specificity) was achieved. We conclude that spectral and nonlinear analyses from spontaneous MEG activity could be complementary methods to help in AD detection.
Address Compression and Heterogeneous Interconnects for Energy-Efficient High-Performance in Tiled CMPs

Previous studies have shown that the interconnection network of a chip-multiprocessor (CMP) has significant impact on both overall performance and energy consumption. Moreover, wires used in such interconnect can be designed with varying latency, bandwidth and power characteristics. In this work, we present a proposal for performance- and energy-efficient message management in tiled CMPs that combines both address compression with a heterogeneous interconnect. Our proposal consists of applying an address compression scheme that dynamically compresses the addresses within coherence messages allowing for a significant area slack. The arising area can be exploited for wire latency improvement by using a heterogeneous interconnection network comprised of a small set of very-low-latency wires for critical short-messages in addition to baseline wires. Detailed simulations of a 16-core CMP show that our proposal obtains average improvements of 10% in execution time and 38% in the Energy-Delay2 Product of the interconnect.
Challenges in Market-Driven Requirements Engineering - an Industrial Interview Study

Requirements engineering for commercial off-the-shelf software packages entails special challenges. This paper presents preliminary results from an empirical study investigating these challenges through a qualitative approach using semi-structured interviews. The survey is exploratory with the objective of eliciting relevant topics for further research. Seven employees at five software companies with a market-driven development focus were interviewed. The areas of interest include process-related issues on release planning, requirements quality and decision support, as well as artefact-related issues regarding requirements as discrete entities and their representation. The paper also contains a characterization of each company, regarding aspects such as products, processes and customers. A number of challenging issues were elicited, including communication gaps between marketing and development, the problem of balancing the influence between marketing and development on requirements decisions, as well as the limited value of monolithic requirements specifications and the problem of requirements overloading. (Less)