Miracle-dz/UniFAR-FTUs huggingface dataset:
Lentiviral Gag Assembly Analyzed through the Functional Characterization of Chimeric Simian Immunodeficiency Viruses Expressing Different Domains of the Feline Immunodeficiency Virus Capsid Protein

To gain insight into the functional relationship between the capsid (CA) domains of the Gag polyproteins of simian and feline immunodeficiency viruses (SIV and FIV, respectively), we constructed chimeric SIVs in which the CA-coding region was partially or totally replaced by the equivalent region of the FIV CA. The phenotypic characterization of the chimeras allowed us to group them into three categories: the chimeric viruses that, while being assembly-competent, exhibit a virion-associated unstable FIV CA; a second group represented only by the chimeric SIV carrying the N-terminal domain (NTD) of the FIV CA which proved to be assembly-defective; and a third group constituted by the chimeric viruses that produce virions exhibiting a mature and stable FIV CA protein, and which incorporate the envelope glycoprotein and contain wild-type levels of viral genome RNA and reverse transcriptase. Further analysis of the latter group of chimeric SIVs demonstrated that they are non-infectious due to a post-entry impairment, such as uncoating of the viral core, reverse transcription or nuclear import of the preintegration complex. Furthermore, we show here that the carboxyl-terminus domain (CTD) of the FIV CA has an intrinsic ability to dimerize in vitro and form high-molecular-weight oligomers, which, together with our finding that the FIV CA-CTD is sufficient to confer assembly competence to the resulting chimeric SIV Gag polyprotein, provides evidence that the CA-CTD exhibits more functional plasticity than the CA-NTD. Taken together, our results provide relevant information on the biological relationship between the CA proteins of primate and nonprimate lentiviruses.
Oscar: A Practical Page-Permissions-Based Scheme for Thwarting Dangling Pointers

Using memory after it has been freed opens programs up to both data and control-flow exploits. Recent work on temporal memory safety has focused on using explicit lock-and-key mechanisms (objects are assigned a new lock upon allocation, and pointers must have the correct key to be dereferenced) or corrupting the pointer values upon free(). Placing objects on separate pages and using page permissions to enforce safety is an older, wellknown technique that has been maligned as too slow, without comprehensive analysis. We show that both old and new techniques are conceptually instances of lockand-key, and argue that, in principle, page permissions should be the most desirable approach. We then validate this insight experimentally by designing, implementing, and evaluating Oscar, a new protection scheme based on page permissions. Unlike prior attempts, Oscar does not require source code, is compatible with standard and custom memory allocators, and works correctly with programs that fork. Also, Oscar performs favorably – often by more than an order of magnitude – compared to recent proposals: overall, it has similar or lower runtime overhead, and lower memory overhead than competing systems.
Automatic extraction of table metadata from digital documents

Tables are used to present, list, summarize, and structure important data in documents. In scholarly articles, they are often used to present the relationships among data and highlight a collection of results obtained from experiments and scientific analysis. In digital libraries, extracting this data automatically and understanding the structure and content of tables are very important to many applications. Automatic identification extraction, and search for the contents of tables can be made more precise with the help of metadata. In this paper, we propose a set of medium-independent table metadata to facilitate the table indexing, searching, and exchanging. To extract the contents of tables and their metadata, an automatic table metadata extraction algorithm is designed and tested on PDF documents
Faster numerical algorithms via exception handling

An attractive paradigm for building fast numerical algorithms is the following: (1) try a fast but occasionally unstable algorithm, (2) test the accuracy of the computed answer, and (3) recompute the answer slowly and accurately in the unlikely event it is necessary. This is especially attractive on parallel machines where the fastest algorithms may be less stable than the best serial algorithms. Since unstable algorithms can overflow or cause other exceptions, exception handling is needed to implement this paradigm safely. To implement it efficiently, exception handling cannot be too slow. This paradigm is illustrated with numerical linear algebra algorithms from the LAPACK library. <<ETX>>
Activation of botulinum C2 toxin by trypsin

C2 toxin (C2T) elaborated by Clostridium botulinum types C and D is composed of two dissimilar protein components, designated components I and II. The biological activity of C2T is enhanced by treating the toxin with trypsin. This activation of C2T is observed as a result of mixing untrypsinized component I and trypsinized component II but not as a result of mixing trypsinized component I and untrypsinized component II. The data presented here show that the maximum lethality of C2T, determined by mixing untrypsinized component I and trypsinized component II, was attained by treating component II with trypsin at a ratio of 10:1 on a protein basis for 30 min at 35 degrees C at pH 7.5. The activation of component II was always accompanied by a change in the molecular weight of the component from 101,000 to 88,000 as determined by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). However, the gel filtration of trypsinized component II resulted in the separation of two active components, with apparent molecular weights, estimated from the elution volume by gel filtration, of 365,000 and 74,000. The high-molecular-weight component II had hemagglutination and hemolytic activities, whereas the low-molecular-weight component II has only hemagglutination activity. These two molecular species of active component II had approximately the same lethality, when mixed with component I, and gave a single band in SDS-PAGE, with a molecular weight of 88,000, the same as that of trypsin-activated component II under different reaction conditions. The results indicate that the activation of C2T by trypsin is due to the molecular conversion of component II from molecular weight 101,000 to 88,000 as determined by SDS-PAGE and that the trypsin-activated component II tends to form an oligomer of the active component II.
DVB Detector for Cognitive Radio

Cognitive radio (CR) is seen as one of the revolutionary techniques for future spectrum utilization. The first and probably the most challenging task for CR is to detect/sense the white space of the spectrum for its usage. In this paper, detection of DVB-T signals is studied since TV band has been considered by Federal Communications Commission (FCC) to be pioneered for CR usage. Cyclostationary feature of DVB signals is explored so that the robust single-cycle detector (SCD) can be employed to handle the problem of noise uncertainty, to which the widely used energy detector (ED) is susceptible. Due to complexity concerns for real-time implementation, a blind twin peak (BTP) detector is proposed to approximate the performance of SCD while keep the complexity as low as ED.
The Commercialization of Knowledge Management Practices to K-based Development in Malaysia Raja Suzana

The purpose of this research is to study the connection between the commercialization of knowledge management practices and its contributions towards the knowledge-based development in Malaysia. Theoretical relations in this research are tested through an empirical study carried out on among public-listed organizations in the industrial products, consumer products and services industries in Malaysia. The findings of this paper reveal that it is important for corporations to focus on knowledge management in the development of the organization’s corporate strategy. Empirical evidence supports the view that firms with knowledge management capabilities and understanding will utilize these capabilities to drive their quality strategy thus performing better than those that do not. In addition, the finding serves as an initial move among private sector towards a knowledge-based country. The paper concludes that these practices have a positive incidence not only on the performance of the firm but it also gives some initial contributions towards the development of Malaysia as knowledge-based country.
Sentiment Classification Using Semantic Features Extracted from WordNet-based Resources

In this paper, we concentrate on the 3 of the tracks proposed in the NTCIR 8 MOAT, concerning the classification of sentences according to their opinionatedness, relevance and polarity. We propose a method for the detection of opinions, relevance, and polarity classification, based on ISR-WN (a resource for the multidimensional analysis with Relevant Semantic Trees of sentences using different WordNet-based information sources). Based on the results obtained, we can conclude that the resource and methods we propose are appropriate for the task, reaching the level of state-of-the-art approaches.
Parallel Scientiic Computing on the Ibm Sp2 at Rensselaer's Scientiic Computation Research Center 1 Adaptive Finite Element Methods

Various research applications using the adaptive solution of partial diierential equations and parallel discrete event simulation as well as the investigation of object oriented programming paradigms are described. This work utilizes the IBM SP2 at Rensselaer's Scientiic Computation Research Center (SCOREC). The software is designed using C, C++ and Fortran 90, together with MPI. Tools described include a parallel mesh database, load balancers and run-time code optimizers. Additionally, using plasma codes as an example, we compare compilers and architecture performance of the SP2 to competing distributed memory parallel machines. Applications studying nite element analysis of problems in biomechanics and uid dynamics, the simulation of fusion plasma processes and the spread of Lyme disease are presented. The nite element method (FEM) has become a standard engineering analysis tool for solving partial diierential equations (PDEs). Adaptive FEMs have gained importance because they provide greater accuracy, reliability, robustness, and time and space eeciency. In such an analysis, the computational domain is rst discretized to create a mesh. During the solution process, portions of the discrete domain are spatially reened or coarsened (h-reenement), the method order is varied (p-reenement), and/or the mesh is moved to follow evolving phenomena (r-reenement), each of which concentrates the computational eeort in regions where the solution resolution is inadequate 1]. In order to solve large problems within a reasonable period of time, these methods have been implemented on parallel computers. While parallelism can yield faster solution times or greater accuracy in the same computing time, there are complications such as coordinating interprocessor communication and managing distributed data structures. The standard methodology for optimizing parallel FEM programs relies on the initial partitioning of the meshes involved in the computation. However, in parallel adaptive codes, a good initial partitioning is not suucient to assure high performance throughout the computation. Load imbalance caused by adaptive enrichment necessitates a dynamic redistribution of data. Our focus is to build an eecient load balancer for parallel adaptive methods that can be used to solve complex problems. The tools that have been developed at Rensselaer Polytechnic Institute to facilitate this focus are described in the following sections.
Pituitary adenylyl cyclase‐activating polypeptide controls the proliferation of retinal progenitor cells through downregulation of cyclin D1

During retinal development, cell proliferation and exit from the cell cycle must be precisely regulated to ensure the generation of the appropriate numbers and proportions of the various retinal cell types. Previously, we showed that pituitary adenylyl cyclase‐activating polypeptide (PACAP) exerts a neuroprotective effect in the developing retina of rats, through the cAMP–cAMP‐dependent protein kinase (protein kinase A) (PKA) pathway. Here, we show that PACAP also regulates the proliferation of retinal progenitor cells. PACAP, PACAP‐specific receptor (PAC1), and the receptors activated by both PACAP and vasoactive intestinal peptide (VIP), VPAC1 and VPAC2, are expressed during embryonic and postnatal development of the rat retina. Treatment of retinal explants with PACAP38 reduced the incorporation of [3H]thymidine as well as the number of 5‐bromo‐2′‐deoxyuridine‐positive and cyclin D1‐positive cells. Pharmacological experiments indicated that PACAP triggers this antiproliferative effect through the activation of both PAC1 and VPACs, and the cAMP–PKA pathway. In addition, PACAP receptor activation decreased both cyclin D1 mRNA and protein content. Altogether, the data support the hypothesis that PACAP is a cell‐extrinsic regulator with multiple roles during retinal development, including the regulation of proliferation in a subpopulation of retinal progenitor cells.
Negative-Sequence Second-Order Circulating Current Injection for Hybrid MMC Under Over-Modulation Conditions

Due to the presence of full-bridge submodules (FBSMs), hybrid modular multilevel converters (HMMCs) consisting of FBSMs and half-bridge submodules (HBSMs) can work under the over-modulation conditions, which means that half of the dc voltage is less than the magnitude of the ac voltage. However, because of the different charging and discharging characteristics of FBSMs and HBSMs under over-modulation conditions, capacitor voltages imbalance may occur if the modulation index exceeds a specific limit. To address this issue, this article first investigates the principles of HMMCs and the energy balance mechanism between the two types of submodules. Based on the theoretical analysis, a negative-sequence second-order circulating current injection method is proposed to keep the capacitor voltage balanced under over-modulation conditions. Finally, the proposed method is validated by both simulation and experimental results.
Deep SubMicron SRAM Design for Ultra-Low Leakage Standby Operation by Huifang

Deep Sub-Micron SRAM Design for Ultra-Low Leakage Standby Operation by Huifang Qin Doctor of Philosophy in Engineering Electrical Engineering and Computer Sciences University of California, Berkeley Professor Jan M. Rabaey, Chair Suppressing the standby current in memories is critical in low-power design. By lowering the supply voltage (VDD) to its standby limit, the data retention voltage (DRV), SRAM leakage power can be reduced substantially. The DRV theoretical limit is derived to be 52mV for a 90nm technology at room temperature. The DRV increases with transistor mismatches. Based on sub-threshold circuit analysis, a practical DRV model is developed and verified with measurement data from several test chips in 130nm and 90nm technologies. By reducing the standby VDD of a 32K-bit 130nm industrial IP SRAM module to 490 mV (390 mV worst-case DRV + 100 mV electrical-noise guardband), an 85% leakage power saving is measured, compared to the standby power at 1V. Since the DRV is a strong function of both process and design parameters, the SRAM cell can be optimized to reduce DRV. It is shown that the body bias and device channel length are the most effective knobs in minimizing DRV. This is confirmed with measurement data from a 90nm SRAM test chip. Building on these results, feasibility of a 270mV standby VDD is demonstrated for an optimized 4K-bit SRAM in a 90nm technology, leading to a 97% leakage power reduction. By dynamically configuring the body bias during read and write operations, the active operation noise margins and data access speed are also improved according to simulation results. Correcting the low-voltage retention errors with error correction code (ECC) provides another opportunity to further reduce the SRAM standby VDD. To establish a power-perbit metric, the SRAM leakage power is modeled as a function of the ECC parameters, DRV distribution and the standby VDD. This power metric is optimized based on ECC theory to obtain fundamental bounds of the power saving enabled by error-tolerant design. Taking into account the practical design requirements, an error-tolerant SRAM design with a (31, 26) Hamming code is proposed introducing a further power reduction of 33%. Both the circuit optimization and the error-tolerant architecture are implemented in a 90nm 26K-bit ultra-low leakage SRAM chip. Measurement result proves that the memory data can be reliably retained at a 255mV standby VDD, with a 50X leakage power reduction. While the optimization also improves active SRAM operation, the only tradeoff is a 50% larger area caused by the larger channel length and ECC overhead. In summary, this work is the first analytical investigation into the voltage limit of SRAM standby operation. The theoretical and practical DRV models provide insights to the future low-voltage SRAM designs. Besides the analytical study, we also develop two novel design solutions that aggressively reduce SRAM leakage. The error-tolerant SRAM standby scheme is the first time the ECC is used for memory power minimization. Professor Jan M. Rabaey Thesis Committee Chair
Acts of reciprocity: Analyzing social exchange in a university theater for social change project

In this study I sought to understand the complexities of the processes of reciprocity within a theater for social change service-learning project. My sample included three university students, one university faculty member, four high school students, one high school principal, and one high school teacher. As a participantobserver, I conducted an ethnographic study from within an interpretive paradigm that focuses on reality as perceived by participants. I collected my data through interviews, observations, and course related documents. In this study, I accomplish four things: 1) I present a user-friendly model of the processes of reciprocity 2) I make concrete nebulous notions of exchange by defining reciprocated goods between partners. 3) I emphasize a physical component to our understanding of reciprocity 4) I suggest that tools and elements of TFSC practice can be applied to other non-theater service-learning and civic engagement projects. My model includes three core building blocks to reciprocity: trust, covenant, and power sharing; and consists of a continuous cycle of four steps that partners engage cooperatively around a central common goal. These four steps include: understanding the social milieu of the partners, fostering integrative bonds through group development, identifying niches of exchange, and isolating and addressing imbalances in the interactions. My results illuminate that reciprocity is not achieved through a simple agreement at the beginning of a project partnership, but rather is a complex, iterative and volatile process that needs attention throughout a partnership.
Survivor Bonds: A Comment on Blake and Burrows

This article offers a critical assessment of the “survivor bonds” (SBs) proposal recently put forward by Blake and Burrows, which calls for the government to issue bonds whose coupon payments are contingent on the proportions of retirees surviving to particular ages. It suggests that the proposal has considerable merit and discusses the circumstances in which SBs would be useful risk management tools for insurance companies. It also discusses alternatives such as reinsurance, hedging with life contracts, dynamic hedging, and other forms of survivor derivative. Finally, it evaluates and rejects the argument that SBs should be issued by the state.
Universal delay estimation for discrete channels

The use of information theory concepts for universal estimation of delay for classes of discrete channels is discussed. The problem is presented as one of hypothesis testing. Although the channel statistics are not known, for large enough signal duration, the exponent of the average error probability is equal to that associated with the optimal maximum-likelihood (ML) decision procedure which utilizes full knowledge of the channel parameters. Two categories of problems are discussed: the single-channel problem, where the random transmitted signal is known to the receiver, and the two-sensor problem, where the random signal is unknown.
The Graphical Lasso: New Insights and Alternatives

The graphical lasso [5] is an algorithm for learning the structure in an undirected Gaussian graphical model, using ℓ1 regularization to control the number of zeros in the precision matrix Θ = Σ-1 [2, 11]. The R package GLASSO [5] is popular, fast, and allows one to efficiently build a path of models for different values of the tuning parameter. Convergence of GLASSO can be tricky; the converged precision matrix might not be the inverse of the estimated covariance, and occasionally it fails to converge with warm starts. In this paper we explain this behavior, and propose new algorithms that appear to outperform GLASSO. By studying the "normal equations" we see that, GLASSO is solving the dual of the graphical lasso penalized likelihood, by block coordinate ascent; a result which can also be found in [2]. In this dual, the target of estimation is Σ, the covariance matrix, rather than the precision matrix Θ. We propose similar primal algorithms P-GLASSO and DP-GLASSO, that also operate by block-coordinate descent, where Θ is the optimization target. We study all of these algorithms, and in particular different approaches to solving their coordinate sub-problems. We conclude that DP-GLASSO is superior from several points of view.
Automatic Speech Recognition using correlation analysis

The growth in wireless communication and mobile devices has supported the development of Speech recognition systems. So for any speech recognition system feature extraction and patter matching are two very significant terms. In this paper we have developed a simple algorithm for matching the patterns to recognize speech. We used Mel frequency cepstral coefficients (MFCCs) as the feature of the recorded speech. This algorithm is implemented simply by using the principle of correlation. All the simulation experiments were carried out using MATLAB where the method produced relatively good results. This paper gives a details introduction of recorded speech processing, design considerations and evaluation results.
System level performance analysis of carbon nanotube global interconnects for emerging chip multiprocessors

Although carbon nanotubes (CNTs) have been widely proposed as interconnect fabrics for future ultra deep submicron (UDSM) technologies, there is a lack of system-level performance analysis using these interconnects. In this paper, we investigate the performance of four CNT alternatives that may replace conventional copper (Cu) interconnects at the global interconnect level - (i) single walled CNTs (SWCNTs), (ii) SWCNT bundles, (Hi) multi-walled CNTs (MWCNTs) and (iv) bundles of mixed SWCNTs/MWCNTs. Detailed RLC equivalent circuit models for conventional CNT interconnects are described and used to calculate propagation delays. These models are then incorporated into a system-level environment to estimate the impact of using CNT global interconnects on the overall performance of several multi-core chip multiprocessor (CMP) applications. Our results indicate that MWCNTs can provide the most significant performance speedup among the CNT alternatives (up to 1.9x) over Cu global interconnects. With further improvements in CNT fabrication technology, it is shown that mixed SWCNT/MWCNT bundles and SWCNT bundles can also become viable global interconnect alternatives.