Miracle-dz/UniFAR-FTUs huggingface dataset:
Algorithm-assisted elucidation of disul W de structure : application of the negative signature mass algorithm to mass-mapping the disul W de structure of the 12-cysteine transforming growth factor type II receptor extracellular domain

The power of an algorithm-driven method for interpreting disulWde mass-mapping data is demonstrated in the context of determining the disulWde structure of the extracellular domain of the transforming growth factor type II receptor, a 14-kDa cystinyl protein containing 12 cysteines in the form of six disulWde bonds. The disulWde mass-mapping methodology is based on partial reduction and cyanylation-induced cleavage of the cystinyl protein. Because the multiplicity of possible disulWde structures that must be considered grows rapidly with the number of cysteines, as does the diYculty in physically isolating each of the partially reduced and cyanylated isoforms of the analyte, manual data interpretation for disulWde mapping a cystinyl protein containing more than eight cysteines becomes unmanageable. Recently, we introduced the concept of a “negative signature mass algorithm” (NSMA) to determine the disulWde structure of a cystinyl protein by processing an input of its amino acid sequence and mass spectral data from analysis of its associated cyanylation-induced cleavage products. Here, we present experimental results to validate the NSMA concept. A key advantage of the NSMA, in addition to convenience and automation, is its capacity to interpret mass spectra from mixtures of cyanylation-induced cleavage fragments without separating the partially reduced isoforms of the cystinyl protein and without knowledge of the extent of partial reduction.  2004 Elsevier Inc. All rights reserved.
Low bitrate source-filter model based compression of vibrotactile texture signals in haptic teleoperation

Vibrotactile signals convey the touch-based characteristics of object surfaces felt through a tool. They particularly enhance the quality of human-machine interactions by providing realistic haptic perception of textures. In this paper, inspired by the similarities observed between vibrotactile texture signals and speech signals, we present a novel vibrotactile texture codec for bilateral teleoperation, based on well-known speech coding techniques. The proposed low bitrate, high quality codec preserves not only the spectral signature vital to the general feel of the texture, but also important temporal features of the texture signal. We report a compression ratio of 8:1 (12.5 %) with a constant output bitrate of 4 kbps, and we validate the perceptual transparency of the codec via rigorous subjective tests and analyses.
The architecture of ArgR-DNA complexes at the genome-scale in Escherichia coli

DNA-binding motifs that are recognized by transcription factors (TFs) have been well studied; however, challenges remain in determining the in vivo architecture of TF-DNA complexes on a genome-scale. Here, we determined the in vivo architecture of Escherichia coli arginine repressor (ArgR)-DNA complexes using high-throughput sequencing of exonuclease-treated chromatin-immunoprecipitated DNA (ChIP-exo). The ChIP-exo has a unique peak-pair pattern indicating 5′ and 3′ ends of ArgR-binding region. We identified 62 ArgR-binding loci, which were classified into three groups, comprising single, double and triple peak-pairs. Each peak-pair has a unique 93 base pair (bp)-long (±2 bp) ArgR-binding sequence containing two ARG boxes (39 bp) and residual sequences. Moreover, the three ArgR-binding modes defined by the position of the two ARG boxes indicate that DNA bends centered between the pair of ARG boxes facilitate the non-specific contacts between ArgR subunits and the residual sequences. Additionally, our approach may also reveal other fundamental structural features of TF-DNA interactions that have implications for studying genome-scale transcriptional regulatory networks.
A matrix model for plane partitions

We construct a matrix model equivalent (exactly, not asymptotically) to the random plane partition model, with almost arbitrary boundary conditions. Equivalently, it is also a random matrix model for a TASEP-like process with arbitrary boundary conditions. Using the known solution of matrix models, this method allows us to find the large size asymptotic expansion of plane partitions, to all orders. It also allows us to describe several universal regimes. On the algebraic geometry point of view, this gives the Gromov–Witten invariants of with branes, i.e. the topological vertex, in terms of the symplectic invariants of the mirror’s spectral curve.
Inference for Deterministic Simulation Models: The Bayesian Melding Approach

Abstract Deterministic simulation models are used in many areas of science, engineering, and policy making. Typically, these are complex models that attempt to capture underlying mechanisms in considerable detail, and they have many user-specified inputs. The inputs are often specified by some form of trial-and-error approach in which plausible values are postulated, the corresponding outputs inspected, and the inputs modified until plausible outputs are obtained. Here we address the issue of more formal inference for such models. A probabilistic approach, called Bayesian synthesis, was shown to suffer from the Borel paradox, according to which the results can depend on the parameterization of the model. We propose a modified approach, called Bayesian melding which takes into full account information and uncertainty about both inputs and outputs to the model, while avoiding the Borel paradox. This is done by recognizing the existence of two priors, one implicit and one explicit, on each input and output; these are combined via logarithmic pooling. Bayesian melding is then standard Bayesian inference with the pooled prior on inputs, and is implemented here by posterior simulation using the sampling-importance-resampling (SIR) algorithm. We develop this initially for invertible models, and then extend it to the more difficult and more common case of noninvertible models. We illustrate the methodology using a number of examples. Simulation studies show that the method outperforms a simpler Bayesian approach in terms of mean squared error. A number of open research problems are discussed.
High-performance online spatial and temporal aggregations on multi-core CPUs and many-core GPUs

Motivated by the practical needs for efficiently processing large-scale taxi trip data, we have developed techniques for high performance online spatial, temporal and spatiotemporal aggregations. These techniques include timestamp compression to reduce memory footprint, simple linear data structures for efficient in-memory scans and utilization of massively data parallel GPU accelerations for spatial joins. Our experiments have shown that the combined performance boosting techniques are able to perform various spatial, temporal and spatiotemporal aggregations on hundreds of millions of taxi trips in the order of a few seconds using commodity personal computers equipped with multi-core CPUs and many-core GPUs. The high throughputs in a personal computing environment are encouraging in the sense that high-performance OLAP queries on large-scale data is feasible when the parallel processing power of modern commodity hardware is fully utilized which is important for interactive OLAP applications.
Trainable Sofware Agents

Software agents usually take a passive approach to learning, acquiring information about a task from watching passively what the user does. Examples are the only information that the user and the learner exchange. The induction task left to the agent is only possible with pre-defined learning biases. Determining a priori the language needed to represent the necessary criteria for performing a task may not always be possible, especially if these criteria must be customizable. The focus of trainable software agents is on acquiring learning biases dynamically from users, being active in asking questions when it is not clear what to learn. The user’s input to the learning process goes beyond concrete examples, providing a more cooperative framework for the learner.
A fully physical model for leakage distribution under process variations in nanoscale double-gate CMOS

Double-gate CMOS is projected to replace classical bulk and SOI technologies around the 32nm node. Predicting the impact of process variations on yield for these novel devices is necessary at an early stage of the design cycle, to enable optimal technology and circuit design choices. This paper presents a fully physical model for double-gate leakage distribution due to gate length (L) and body thickness (tsi) variations, both for single devices and stacks. The model is derived directly from the solution of Poisson's and Schrodinger's equations, and thus captures the effect of unique double-gate phenomena such as volume inversion and quantum confinement. It is scalable to L = 13nm and tsi = 3nm, with less than 2% error for 3sigma variation as large as 20% of nominal process parameters
Data Quality in Inter-Organizational Product Information Sharing: Improving Quality of Product Master Data Exchanged Through Data Pools

Product master data (PMD) can be defined as a set of data that represents a selection of characteristics and aspects of its accompanying physical product. For several reasons, these data sets are increasingly exchanged between organizations within supply chains. Although this process is traditionally often supported by non-automated technologies such as Excel spreadsheet, telephone, email, and fax, the adoption of data pools is on the rise. These inter-organizational systems allow the data supplying party to publish a product’s master data set in one centralized system after which it can be accessed by all subscribed data recipients.
Quality of randomized clinical trials published by plastic surgeons: a long-term
 follow-up study

to the 1996-2003 period ( p < 0.0004); however, there was no significant difference in the 2004-2008 period. Conclusion: There was no difference in the quality of the RCTs published by plastic surgeons in the 2009-2013 period compared to the previous five-year period (2004 to 2008). However, both periods indicated higher quality compared to the 1966-2003 period. ■
Eye HDR: gaze-adaptive system for displaying high-dynamic-range images

The human visual system (HVS) uses several methods to interactively adapt to the incredible real-world range of light intensities, continually changing to effectively perceive visual information. Eye HDR is a new approach to the problem of displaying high-dynamic-range (HDR) content on low-dynamic-range displays. Instead of creating a single static image, it uses a dynamic display system to naturally, interactively adapt to the user's view, just as the HVS changes depending on the environment.
A hybrid subgrid-scale model constrained by Reynolds stress

A novel constrained formulation for the dynamic subgrid-scale model for large eddy simulation (LES) is proposed. An externally prescribed Reynolds stress is used as the constraint and is imposed in the near-wall region of wall-bounded flows. However, unlike conventional zonal approaches, Reynolds stress is not imposed as the solution, but used as a constraint on the subgrid-scale stress so that the computed Reynolds stress closely matches the prescribed one only in the mean sense. In the absence of an ideal wall model or adequate near-wall resolution, a LES solution at coarse resolution is expected to be erroneous very near the wall while giving reasonable predictions away from the wall. The Reynolds stress constraint is limited to the region where the LES solution is expected to be erroneous. The Germano-identity error is used as an indicator of LES quality such that the Reynolds stress constraint is activated only where the Germano-identity error exceeds a certain threshold. The proposed model is applie.
SARS in Hospital Emergency Room

Thirty-one cases of severe acute respiratory syndrome (SARS) occurred after exposure in the emergency room at the National Taiwan University Hospital. The index patient was linked to an outbreak at a nearby municipal hospital. Three clusters were identified over a 3-week period. The first cluster (5 patients) and the second cluster (14 patients) occurred among patients, family members, and nursing aids. The third cluster (12 patients) occurred exclusively among healthcare workers. Six healthcare workers had close contact with SARS patients. Six others, with different working patterns, indicated that they did not have contact with a SARS patient. Environmental surveys found 9 of 119 samples of inanimate objects to be positive for SARS coronavirus RNA. These observations indicate that although transmission by direct contact with known SARS patients was responsible for most cases, environmental contamination with the SARS coronavirus may have lead to infection among healthcare workers without documented contact with known hospitalized SARS patients.
Detecting conflicts between structure accesses

Two references to a record structure conflict if they access the same field and at least one modifies the location. Because structures can be connected by pointers, deciding if two statements conflict requires knowledge of the possible aliases for the locations that they access. This paper describes a dataflow computation that produces a conservative description of the aliases visible at any point in a program. The data structure that records aliases is an alias graph. It also labels instances of structures so that the objects referenced at different points in a program can be compared. This paper shows how alias graphs can be used to detect potential conflicts.
Genomic Location and Variation of the Gene for CRS, a Complement Binding Protein in the M57 Strains of Streptococcus pyogenes

ABSTRACT All isolates of serotype M1 of group A streptococci possess a gene for streptococcal inhibitor of complement (SIC) in the mga regulon, which harbors genes for other virulence factors, such as M and M-like proteins, C5a peptidase, and a regulator. In serotype M57 the gene for a protein that is closely related to SIC (crs57) is located outside the mga regulon. We mapped the location of the crs57 gene in six strains of emm57 (gene encoding the M57 protein) sequence types to an intergenic region between the ABC transporter gene (SPy0778) and the gene for a small ribosomal protein (rpsU). The noncoding sequences on both sides of crs57 exhibited high degrees of identity to the corresponding regions of sic from M1 strains. This included one of the inverted repeat sequences of IS1562 but not the insertion element itself. These observations suggest that crs57 was recently acquired by serotype M57 or its progenitor via horizontal acquisition from serotype M1. The six emm57 sequence type isolates analyzed in this study belong to two distinct molecular types (vir types VT8 and VT101). Although the crs57 sequences from VT8 strains had very few substitution mutations, the VT101 crs57 sequence had a large number of such mutations. The CRS57 proteins from these strains are secretory products and have the ability to bind to complement proteins. All these proteins contain several tryptophan-rich repeats designated DWS motifs and internal repeat sequences. In all of these structural and biochemical characteristics CRS57 resembles SIC from M1 strains. Hence, CRS57 has a functional role similar to that of SIC in an M1 strain.
Artisan entrepreneurship: a question of personality structure?

Purpose The purpose of this paper is to examine the role of culture in artisan entrepreneurship. It is argued that culture plays a critical role in entrepreneurial behaviour as culture is a key determinant of what it means to be a person. The concept of culture is explored from a micro level of analysis therefore, conceptualising culture from the perspective of the individual entrepreneur’s personality. The main research question being investigated within this paper is: whether artisan entrepreneurs share common personality traits with other entrepreneur groups, using the five factor model (FFM) of personality as the basis of the conceptual model presented herein. Design/methodology/approach A literature review on the emerging field of artisan entrepreneurship, followed by a review of the literature on personality theory and entrepreneurship. Then, drawing upon the FFM of personality, a conceptual framework is introduced which proposes a relationship between the Big Five personality traits and four dimensions of artisan entrepreneurship such as cultural heritage, community entrepreneurship, craftsmanship and innovation, developed from concepts derived from extant literature. Findings The theoretical contribution is in the form of propositions. Four propositions have been formulated around the entrepreneurial personality of artisan business owners for each of the four dimensions: cultural heritage, community entrepreneurship, craftsmanship and innovation. Originality/value The paper is the first to propose a relationship between the Big Five personality dimensions and the likelihood of starting and/or running a business among an entrepreneur group rather than explaining personality differences among entrepreneur and non-entrepreneur groups. The focus of the paper is specifically on artisan entrepreneurs and it has been proposed that the personality trait of agreeableness is important in the decision to start a cultural-based business. It has also been proposed that artisan entrepreneurs possess personal characteristics of openness to newness and openness to innovation that are integral to regional development.
The Adverse Effect of Spasticity on 3-Month Poststroke Outcome Using a Population-Based Model

Several devices and medications have been used to address poststroke spasticity. Yet, spasticity's impact on outcomes remains controversial. Using data from a cohort of 460 ischemic stroke patients, we previously published a validated multivariable regression model for predicting 3-month modified Rankin Score (mRS) as an indicator of functional outcome. Here, we tested whether including spasticity improved model fit and estimated the effect spasticity had on the outcome. Spasticity was defined by a positive response to the question “Did you have spasticity following your stroke? ” on direct interview at 3 months from stroke onset. Patients who had expired by 90 days (n = 30) or did not have spasticity data available (n = 102) were excluded. Spasticity affected the 3-month functional status (β = 0.420, 95 CI = 0.194 to 0.645) after accounting for age, diabetes, leukoaraiosis, and retrospective NIHSS. Using spasticity as a covariable, the model's R 2 changed from 0.599 to 0.622. In our model, the presence of spasticity in the cohort was associated with a worsened 3-month mRS by an average of 0.4 after adjusting for known covariables. This significant adverse effect on functional outcomes adds predictive value beyond previously established factors.
Medium access control design for full duplex wireless systems: challenges and approaches

Recent advances in self-interference cancellation techniques enable in-band full-duplex (FD) transmission in which a wireless node can simultaneously transmit and receive in the same frequency band. However, to fully exploit the benefits of FD technology in a wireless network, in addition to the physical (PHY) layer issues, medium access control (MAC) layer issues such as inter-node collisions, fairness between half-duplex (HD) and FD users, opportunistic selection of different modes of FD transmission, and synchronization issues need to be resolved. To this end, this article first discusses the fundamental concepts, potential benefits, and primary network topologies of FD transmission. We then highlight immediate challenges (both in the PHY and MAC layers) that need to be addressed in designing FD wireless systems. A qualitative comparison among the existing full-duplex MAC (FD-MAC) protocols is then provided. Finally, the primary requirements and research issues for the design of FD-MAC protocols are discussed, and implications of FD technology in cellular wireless networks are highlighted.
Imputed Welfare Estimates in Regression Analysis 1

We discuss the use of imputed data in regression analysis, in particular the use of highly disaggregated welfare indicators (from so-called “poverty maps”). We show that such indicators can be used both as explanatory variables on the right-hand side and as the phenomenon to explain on the left-hand side. We try out practical ways of adjusting standard errors of the regression coefficients to reflect the error introduced by using imputed, rather than actual, welfare indicators. These are illustrated by regression experiments based on data from Ecuador. For regressions with imputed variables on the left-hand side, we argue that essentially the same aggregate relationships would be found with either actual or imputed variables. We address the methodological question of how to interpret aggregate relationships found in such regressions.
A Venue-Based Method for Sampling Hard-to-Reach Populations

Constructing scientifically sound samples of hard-to-reach populations, also known as hidden populations, is a challenge for many research projects. Traditional sample survey methods, such as random sampling from telephone or mailing lists, can yield low numbers of eligible respondents while non-probability sampling introduces unknown biases. The authors describe a venue-based application of time-space sampling (TSS) that addresses the challenges of accessing hard-to-reach populations. The method entails identifying days and times when the target population gathers at specific venues, constructing a sampling frame of venue, day-time units (VDTs), randomly selecting and visiting VDTs (the primary sampling units), and systematically intercepting and collecting information from consenting members of the target population. This allows researchers to construct a sample with known properties, make statistical inference to the larger population of venue visitors, and theorize about the introduction of biases that may limit generalization of results to the target population. The authors describe their use of TSS in the ongoing Community Intervention Trial for Youth (CITY) project to generate a systematic sample of young men who have sex with men. The project is an ongoing community level HIV prevention intervention trial funded by the Centers for Disease Control and Prevention. The TSS method is reproducible and can be adapted to hard-to-reach populations in other situations, environments, and cultures.
Behavior recognition using Pictorial Structures and DTW

In recent years, there has been an increasing interest in monocular human behavior recognition system. The first step in behavior recognition is the measurement stage. We use an extended Pictorial Structure to speed up the detection. This extension adds a temporal term to the global energy function of the framework. We use a simple to complex approach in action recognition by decomposing it to its basic elements. The human body parts motions are tracked and classified individually. The body parts motions are matched using an adapted Dynamic Time Warping (DTW) that use a multilevel approach that projects a solution from a coarse resolution and refines the projected solution. The results of the DTW matching are used to activate hierarchical Petri Nets, or to act as input to Neural Network, used to classify the behavior.