Miracle-dz/UniFAR-FTUs huggingface dataset:
Latent Inputs Improve Estimates of Neural Encoding in Motor Cortex

Typically, tuning curves in motor cortex are constructed by fitting the firing rate of a neuron as a function of some observed action, such as arm direction or movement speed. These tuning curves are then often interpreted causally as representing the firing rate as a function of the desired movement, or intent. This interpretation implicitly assumes that the motor command and the motor act are equivalent. However, any kind of perturbation, be it external, such as a visuomotor rotation, or internal, such as muscle fatigue, can create a difference between the motor intent and the action. How do we estimate the tuning curve under these conditions? Furthermore, it is well known that, during learning or adaptation, the relationship between neural firing and the observed movement can change. Does this change indicate a change in the inputs to the population, or a change in the way those inputs are processed? In this work, we present a method to infer the latent, unobserved inputs into the population of recorded neurons. Using data from nonhuman primates performing brain–computer interface experiments, we show that tuning curves based on these latent directions fit better than tuning curves based on actual movements. Finally, using data from a brain–computer interface learning experiment in which half of the units were decoded incorrectly, we demonstrate how this method might differentiate various aspects of motor adaptation.
hLARP7 C-terminal domain contains an xRRM that binds the 3′ hairpin of 7SK RNA

The 7SK small nuclear ribonucleoprotein (snRNP) sequesters and inactivates the positive transcription elongation factor b (P-TEFb), an essential eukaryotic mRNA transcription factor. The human La-related protein group 7 (hLARP7) is a constitutive component of the 7SK snRNP and localizes to the 3′ terminus of the 7SK long noncoding RNA. hLARP7, and in particular its C-terminal domain (CTD), is essential for 7SK RNA stability and assembly with P-TEFb. The hLARP7 N-terminal La module binds and protects the 3′ end from degradation, but the structural and functional role of its CTD is unclear. We report the solution NMR structure of the hLARP7 CTD and show that this domain contains an xRRM, a class of atypical RRM first identified in the Tetrahymena thermophila telomerase LARP7 protein p65. The xRRM binds the 3′ end of 7SK RNA at the top of stem-loop 4 (SL4) and interacts with both unpaired and base-paired nucleotides. This study confirms that the xRRM is general to the LARP7 family of proteins and defines the binding site for hLARP7 on the 7SK RNA, providing insight into function.
Side Effects of Campaign Finance Reform

Because campaign finance reform is usually motivated by the concern that existing legislation cannot effectively prevent campaign contributions to "buy favors," this article assumes that contributions influence political decisions. But, given that it is also widely recognized that interest groups achieve influence by providing political decision makers with policy relevant information, we also assume that lobbies engage in non-negligible informational lobbying. We focus on a single political decision to be taken and offer a simple model in which the optimal influence strategy is a mixture of both lobbying instruments. Our main result is to show that campaign finance reform may have important side effects: It may deter informational lobbying so that less policy relevant information is available and as a result political decisions become less efficient. (JEL: C72, D72) (c) 2008 by the European Economic Association.
Analysis of interference mitigation in mmWave communications

Millimeter wave (mmWave) cellular systems will enable gigabit-per-second data rates due to the large bandwidth available at mmWave frequencies. Thanks to the small wavelength corresponding to the mmWave frequencies, mmWave systems can benefit from exploiting large antenna arrays at both transmitter and receiver. Although highly directional beamforming has been envisioned to play a key role to realize sufficient link margin, it is also possible to use these large arrays in other ways. For example, a hybrid array architecture can be exploited to either cancel or null an interferer. In this paper we analyse the effect of interference cancellation in downlink mmWave communications. We exploit partial zero forcing (PZF) at the user in order to cancel the interference from a set of interfering base stations (BSs) and derive closed form expression for the probability of coverage. Simulation results show that as the density of base stations increases, interference mitigation through partial zero forcing enhances the probability of coverage implying the necessity of interference mitigation in dense mmWave networks.
Microstructure evolution of gas-atomized Fe–6.5 wt% Si droplets

The magnetic Fe–6.5 wt% Si powder was produced by gas atomization and its microstructure was also investigated. The secondary dendritic arm spacing (SDAS) is related to the droplet size, λ = 0.29 · D ^0.5, and the numerical solidification model was applied to the system, giving rise to the correlation of microstructure to the solidification process of the droplet. It is found that the solid fraction at the end of recalescence is strongly dependent on the undercooling achieved before nucleation; the chances for the smaller droplets to form the grain-refined microstructures are less than the larger ones. Furthermore, the SDAS is strongly influenced by the cooling rate of post-recalescence solidification, and the relationship can be expressed as follows, $$\lambda = 74.2 \cdot {\left({\dot T} \right)^{- 0.347}}$$ λ = 74.2 ⋅ ( T ˙ ) − 0.347 . Then, the growth of the SDAS is driven by the solute diffusion of the interdendritic liquids, leading to a coarsening phenomenon, shown in a cubic root law of local solidification time, $$\lambda = 10.73 \cdot {\left({{t_f}} \right)^{0.296}}$$ λ = 10.73 ⋅ ( t f ) 0.296 .
A*-based Solutions for KNN Queries with Operating Time Constraints in Time-Dependent Road Networks

We consider the problem of finding the k nearest points of interest from a given location in time-dependent road networks, i.e., One where travel time along each edge is a function of the departure time, and where the operating times of the points of interest are also taken into consideration. More specifically, we address the following query: find the k points of interest in which a user can start to be served in the minimum amount of time, accounting for both the travel time to the point of interest and the waiting time, if it is closed. Previous works have proposed solutions to answer kNN queries considering the time dependency of the network but not the operating times of the points of interest. We propose and discuss three solutions to this type of query which are based on the previously proposed incremental network expansion and use the A search algorithm equipped with suitable heuristic functions. We also present experimental results comparing the number of disk access required in each solution with respect to a few different parameters.
The Wavelet Stream – Progressive Transmission of Compressed Light Field Data

In this paper we describe the compression of light field data using 4D nonstandard wavelet decomposition. For progressive transmission, storage, and rendering of the compressed light field data the new wavelet stream data structure is introduced. The wavelet coefficients are ordered in decreasing importance, encoding the position of the non discarded coefficients using significance maps. Compared to the vector quantization compression method, the wavelet stream achieves up to 3 times higher compression ratios while producing the same error during reconstruction of the light field data. Despite of the high compression of the data, reasonable frame rates during light field rendering are achieved. CR Categories: I.3. 6 [Computer Graphics]: Methodology and Techniques—Graphics data structures and data types E.4 [Coding and Information Theory]: Data compaction and compression
Virtual Machine for Parallel Graph Reduction

We present the architecture of nreduce, a distributed virtual machine which uses parallel graph reduction to run programs across a set of computers. It executes code written in a simple functional language which supports lazy evaluation and automatic parallelisation. The execution engine abstracts away details of parallelism and distribution, ands away details of parallelism and distribution, and uses JIT compilation to produce efficient code. This work is part of a broader project to provide a programming environment for developing distributed applications which hides low-level details from the application developer. The language we have designed plays the role of an intermediate form into which existing functional languages can be transformed. The runtime system demonstrates how distributed execution can be implemented directly within a virtual machine, instead of a separate piece of middleware that coordinates the execution of external programs.
Is Inflammation the Link between Atherosclerosis and Vascular Calcification in Chronic Kidney Disease?

Atherosclerosis and vascular calcification often co-exist in chronic kidney disease (CKD) patients. Although the former has been recently recognized as an active inflammatory process, atherosclerosis-related calcification of the intima is still viewed as a passive epiphenomenon. Recent experimental data showed that ossification of the internal vascular wall might also be an active inflammatory process interrelated to atherosclerosis. Factors like RANKL (receptor activator of nuclear factor ĸB ligand), RANK and osteoprotegerin modulate vascular calcification and at the same time are involved in the process of atherosclerosis. Moreover, basic calcium phosphate crystals could interact with and activate monocytes-macrophages that produce proinflammatory cytokines capable of initiating – via endothelial activation and leukocyte adhesion – the atherosclerotic process. Thus, vascular calcification might be an active player and not simply an epiphenomenon in atherosclerosis. Should the above-mentioned data be confirmed in future studies, calcification of the internal vascular wall and atherosclerosis might be viewed and treated as tightly interconnected and linked by inflammation processes in CKD patients.
cNMA: a framework of encounter complex-based normal mode analysis to model conformational changes in protein interactions

Motivation: It remains both a fundamental and practical challenge to understand and anticipate motions and conformational changes of proteins during their associations. Conventional normal mode analysis (NMA) based on anisotropic network model (ANM) addresses the challenge by generating normal modes reflecting intrinsic flexibility of proteins, which follows a conformational selection model for protein–protein interactions. But earlier studies have also found cases where conformational selection alone could not adequately explain conformational changes and other models have been proposed. Moreover, there is a pressing demand of constructing a much reduced but still relevant subset of protein conformational space to improve computational efficiency and accuracy in protein docking, especially for the difficult cases with significant conformational changes. Method and results: With both conformational selection and induced fit models considered, we extend ANM to include concurrent but differentiated intra- and inter-molecular interactions and develop an encounter complex-based NMA (cNMA) framework. Theoretical analysis and empirical results over a large data set of significant conformational changes indicate that cNMA is capable of generating conformational vectors considerably better at approximating conformational changes with contributions from both intrinsic flexibility and inter-molecular interactions than conventional NMA only considering intrinsic flexibility does. The empirical results also indicate that a straightforward application of conventional NMA to an encounter complex often does not improve upon NMA for an individual protein under study and intra- and inter-molecular interactions need to be differentiated properly. Moreover, in addition to induced motions of a protein under study, the induced motions of its binding partner and the coupling between the two sets of protein motions present in a near-native encounter complex lead to the improved performance. A study to isolate and assess the sole contribution of intermolecular interactions toward improvements against conventional NMA further validates the additional benefit from induced-fit effects. Taken together, these results provide new insights into molecular mechanisms underlying protein interactions and new tools for dimensionality reduction for flexible protein docking. Availability and implementation: Source codes are available upon request. Contact: yshen@tamu.edu
Leveraging determinism in industrial control systems for advanced anomaly detection and reliable security configuration

Industrial automation and control systems (IACS) today are often based on common IT technologies. However, they often lack security mechanisms and those available in enterprise IT environments are often not suitable for IACS. Other mechanisms require significant manual maintenance which is error prone. In this paper we present an approach that leverages the unique characteristics of IACS, in particular their deterministic behavior and often available formal system description, to reliably detect anomalies and reproducibly generate configurations for security mechanisms such as firewalls. In particular, we extend common IDS technology to also detect an IACS specific anomaly: the missing of required traffic.
Effect of Movements on the Electrodermal Response after a Startle Event

Summary Objectives: In this work the effect of quasi-stationary movements on the electrodermal activity (EDA) after a startle event has been investigated and evaluated. In previous EDA research there is a discrepancy between the use of controlled environment studies and daily life surveys. This paper aims to address this by expanding the knowledge about EDA in real life applications. Methods: A minimally obtrusive body-worn measurement device was designed and produced that simultaneously records EDA and finger movements. During this study, five subjects walked at different speeds and listened to startling sound events. The EDA response to these startle events was analyzed for different walking speeds using crosscorrelograms and cumulative frequency plots. Results: The measured response to the startle event is consistent with the signal characteristics described in the literature. The results show that the faster a person is walking the more the signal property of the phasic part of the EDA is approaching a uniform distribution. However, even at a walking speed of 6 km/h the effect of the startle event is statistically still visible in the EDA (p <0.05). Conclusions: The presented work offers a good understanding of the EDA while walking at different speeds. Although the artefacts evoked by walking cannot be determined directly, information on the movement can be useful. Depending on the walking speed a measurement about the reliability of peak detection could be introduced.
Moving Forward in Human Cancer Risk Assessment

Background The current safety paradigm for assessing carcinogenic properties of drugs, cosmetics, industrial chemicals, and environmental exposures relies mainly on in vitro genotoxicity testing followed by 2-year rodent bioassays. This testing battery is extremely sensitive but has low specificity. Furthermore, rodent bioassays are associated with high costs, high animal burden, and limited predictive value for human risks. Objectives We provide a response to a growing appeal for a paradigm change in human cancer risk assessment. Methods To facilitate development of a road map for this needed paradigm change in carcinogenicity testing, a workshop titled “Genomics in Cancer Risk Assessment” brought together toxicologists from academia and industry and government regulators and risk assessors from the United States and the European Union. Participants discussed the state-of-the-art in developing alternative testing strategies for carcinogenicity, with emphasis on potential contributions from omics technologies. Results and Conclusions The goal of human risk assessment is to decide whether a given exposure to an agent is acceptable to human health and to provide risk management measures based on evaluating and predicting the effects of exposures on human health. Although exciting progress is being made using genomics approaches, a new paradigm that uses these methods and human material when possible would provide mechanistic insights that may inform new predictive approaches (e.g., in vitro assays) and facilitate the development of genomics-derived biomarkers. Regulators appear to be willing to accept such approaches where use is clearly defined, evidence is strong, and approaches are qualified for regulatory use.
An Approximate Lp Difference Algorithm for Massive Data Streams

Several recent papers have shown how to approximate the difference ∑ _i|a_i-b_i| or ∑ |a_i-b_i|^2 between two functions, when the function values a_i and b_i are given in a data stream, and their order is chosen by an adversary. These algorithms use little space (much less than would be needed to store the entire stream) and little time to process each item in the stream. They approximate with small relative error. Using different techniques, we show how to approximate the L^p-difference ∑ _i|a_i-b_i|^p for any rational-valued p∈(0,2], with comparable efficiency and error. We also show how to approximate ∑ _i|a_i-b_i|^p for larger values of p but with a worse error guarantee. Our results fill in gaps left by recent work, by providing an algorithm that is precisely tunable for the application at hand. These results can be used to assess the difference between two chronologically or physically separated massive data sets, making one quick pass over each data set, without buffering the data or requiring the data source to pause. For example, one can use our techniques to judge whether the traffic on two remote network routers are similar without requiring either router to transmit a copy of its traffic. A web search engine could use such algorithms to construct a library of small ''sketches,'' one for each distinct page on the web; one can approximate the extent to which new web pages duplicate old ones by comparing the sketches of the web pages. Such techniques will become increasingly important as the enormous scale, distributional nature, and one-pass processing requirements of data sets become more commonplace.
PID controller design for an industrial hydraulic actuator with servo system

Electro-hydraulic system (EHS) consists of several dynamic parts which are widely used in motion control application. These dynamic parts need to be controlled to determine direction of the motion. Mathematical model of EHS is required in order to design a controller for the system. In this paper, system identification technique is used for system modeling. Model of the system is estimated by using System Identification Toolbox in Matlab. This process began with collection of input and output data from experimental works. The data collected is used for model estimation. Auto Regressive with eXogeneous input (ARX) model is chosen as model structure of the system. Based on the input and output data of the system, best fit criterion and correlation analysis of the residual is analyze to determine the adequate model for representing the EHS system. By using Ziegler-Nichols tuning method, PID controller is designed for the model chosen through simulation in Simulink. In order to verify this controller, it is applied to the real time system and the performance of the system is monitored. The result obtained shows that the output of the system with controller in simulation mode and experimental works is almost similar. The output of the system also tracked the input given successfully.
Complete Genome Sequence of Phage-Like Plasmid pECOH89, Encoding CTX-M-15

ABSTRACT A nonconjugative and nontypable plasmid of a clinical Escherichia coli isolate expressing resistance to extended-spectrum cephalosporins (ESCs) was isolated and sequenced. The plasmid pECOH89 contains a CTX-M-15 resistance cassette and comprises 111,741 bp, with strong homology to bacteriophage-like plasmids and to the Salmonella-specific bacteriophage SSU5.
Fungal Lactamases: Their Occurrence and Function

Fungi are absorptive feeders and thus must colonize and ramify through their substrate to survive. In so doing they are in competition, particularly in the soil, with myriad microbes. These microbes use xenobiotic compounds as offensive weapons to compete for nutrition, and fungi must be sufficiently resistant to these xenobiotics. One prominent mechanism of xenobiotic resistance is through production of corresponding degrading enzymes. As typical examples, bacterial β-lactamases are well known for their ability to degrade and consequently confer resistance to β-lactam antibiotics, a serious emerging problem in health care. We have identified many fungal genes that putatively encode proteins exhibiting a high degree of similarity to β-lactamases. However, fungal cell walls are structurally different from the bacterial peptidoglycan target of β-lactams. This raises the question, why do fungi have lactamases and what are their functions? Previously, we identified and characterized one Fusarium verticillioides lactamase encoding gene (FVEG_08291) that confers resistance to the benzoxazinoid phytoanticipins produced by maize, wheat, and rye. Since benzoxazinoids are γ-lactams with five-membered rings rather than the four-membered β-lactams, we refer to the predicted enzymes simply as lactamases, rather than β-lactamases. An overview of fungal genomes suggests a strong positive correlation between environmental niche complexity and the number of fungal lactamase encoding genes, with soil-borne fungi showing dramatic amplification of lactamase encoding genes compared to those fungi found in less biologically complex environments. Remarkably, Fusarium species frequently possess large (>40) numbers of these genes. We hypothesize that many fungal hydrolytic lactamases are responsible for the degradation of plant or microbial xenobiotic lactam compounds. Alignment of protein sequences revealed two conserved patterns resembling bacterial β-lactamases, specifically those possessing PFAM domains PF00753 or PF00144. Structural predictions of F. verticillioides lactamases also suggested similar catalytic mechanisms to those of their bacterial counterparts. Overall, we present the first in-depth analysis of lactamases in fungi, and discuss their potential relevance to fitness and resistance to antimicrobials in the environment.