Miracle-dz/UniFAR-FTUs huggingface dataset:
Human REV3 DNA Polymerase Zeta Localizes to Mitochondria and Protects the Mitochondrial Genome

To date, mitochondrial DNA polymerase γ (POLG) is the only polymerase known to be present in mammalian mitochondria. A dogma in the mitochondria field is that there is no other polymerase present in the mitochondria of mammalian cells. Here we demonstrate localization of REV3 DNA polymerase in the mammalian mitochondria. We demonstrate localization of REV3 in the mitochondria of mammalian tissue as well as cell lines. REV3 associates with POLG and mitochondrial DNA and protects the mitochondrial genome from DNA damage. Inactivation of Rev3 leads to reduced mitochondrial membrane potential, reduced OXPHOS activity, and increased glucose consumption. Conversely, inhibition of the OXPHOS increases expression of Rev3. Rev3 expression is increased in human primary breast tumors and breast cancer cell lines. Inactivation of Rev3 decreases cell migration and invasion, and localization of Rev3 in mitochondria increases survival and the invasive potential of cancer cells. Taken together, we demonstrate that REV3 functions in mammalian mitochondria and that mitochondrial REV3 is associated with the tumorigenic potential of cells.
Impact of Auditory Context on Executed Motor Actions

The auditory and motor systems are strongly coupled, as is evident in the specifically tight motor synchronization that occurs in response to regularly occurring auditory cues compared with cues of other modalities. Timing of rhythmic action is known to rely on multiple neural centers including the cerebellum and the basal-ganglia which have access to both motor cortical and spinal circuitries. To date, however, there is little information on the motor mechanisms that operate during preparation and execution of rhythmic vs. non-rhythmic movements. We measured acceleration profile and muscle activity while subjects performed tapping movements in response to auditory cues. We found that when tapping at random intervals there was a higher variability of both acceleration profile and muscle activity during motor preparation compared to rhythmic tapping. However, the specific rhythmic context (cued, self-paced, or syncopation) did not affect the motor parameters of the executed taps. Finally, during entrainment we found a gradual as opposed to episodic change in low-level motor parameters (i.e., preparatory muscle activity) that was strongly correlated with changes in high-level parameters (i.e., shift in the reaction time to negative asynchrony). These findings suggest that motor entrainment involves not only adjusting the timing of movement but also modifying parameters that are related to its production. These changes in motor output were insensitive to the specifics of the rhythmic cue: although it took subjects different times to become entrained to different types of rhythmic cues, the motor actions produced once entrainment was obtained were indistinguishable. These findings suggest that motor entrainment involves not only adjusting the timing of movement but also modifying parameters related to its production. The reduced variability of muscle activity during the preparatory period could be one mechanism used by the motor system to enhance the accuracy of motor timing.
Predicting and preventing student failure - using the k-nearest neighbour method to predict student performance in an online course environment

We study the problem of predicting student performance in an online course. Our specific goal is to identify at an early stage of the course those students who have a high risk of failing. We employ the k-nearest neighbour method (KNN) and its many variants on this problem. We present extensive experimental results from a 12-lesson course on touch-typing, with a database of close to 15,000 students. The results indicate that KNN can predict student performance accurately, and already after the very first lessons. We conclude that early tests on skills can also be strong predictors for final scores also in other skill-based courses. Selected methods described in this paper will be implemented as an early warning feature for teachers of the touch-typing course, so they can quickly focus their attention to the students who need help the most.
Six-Dimensional Correction of Intra-Fractional Prostate Motion with CyberKnife Stereotactic Body Radiation Therapy

Large fraction radiation therapy offers a shorter course of treatment and radiobiological advantages for prostate cancer treatment. The CyberKnife is an attractive technology for delivering large fraction doses based on the ability to deliver highly conformal radiation therapy to moving targets. In addition to intra-fractional translational motion (left–right, superior–inferior, and anterior–posterior), prostate rotation (pitch, roll, and yaw) can increase geographical miss risk. We describe our experience with six-dimensional (6D) intra-fraction prostate motion correction using CyberKnife stereotactic body radiation therapy (SBRT). Eighty-eight patients were treated by SBRT alone or with supplemental external radiation therapy. Trans-perineal placement of four gold fiducials within the prostate accommodated X-ray guided prostate localization and beam adjustment. Fiducial separation and non-overlapping positioning permitted the orthogonal imaging required for 6D tracking. Fiducial placement accuracy was assessed using the CyberKnife fiducial extraction algorithm. Acute toxicities were assessed using Common Toxicity Criteria v3. There were no Grade 3, or higher, complications and acute morbidity was minimal. Ninety-eight percent of patients completed treatment employing 6D prostate motion tracking with intra-fractional beam correction. Suboptimal fiducial placement limited treatment to 3D tracking in two patients. Our experience may guide others in performing 6D correction of prostate motion with CyberKnife SBRT.
Mining Individual Behavior Pattern Based on Semantic Knowledge Discovery of Trajectory

This paper attempts to mine the hidden individual behavior pattern from the raw users’ trajectory data. Based on DBSCAN, a novel spatio-temporal data clustering algorithm named Speed-based Clustering Algorithm was put forward to find slow-speed subtrajectories (i.e., stops) of the single trajectory that the user stopped for a longer time. The algorithm used maximal speed and minimal stopping time to compute the stops and introduced the quantile function to estimate the value of the parameter, which showed more effectively and accurately than DBSCAN and certain improved DBSCAN algorithms in the experimental results. In addition, after the stops are connected with POIs that have the characteristic of an information presentation, the paper designed a POI-Behavior Mapping Table to analyze the user’s activities according to the stopping time and visiting frequency, on the basis of which the user’s daily regular behavior pattern can be mined from the history trajectories. In the end, LBS operators are able to provide intelligent and personalized services so as to achieve precise marketing in terms of the characteristics of the individual behavior.
Cerebellar cortical degeneration disrupts discrimination learning but not delay or trace classical eyeblink conditioning.

The authors investigated classical eyeblink conditioning in a relatively rare patient, B.R. , with extensive cerebellar cortical atrophy and marked sparing of the dentate nucleus. Patient B.R. 's ability to acquire and extinguish simple associations (delay and trace conditioning tasks) as well as her ability to acquire more complex associations (temporal and simple discrimination tasks) were examined. There are 2 primary findings from this study. First, B.R. showed normal acquisition and extinction in delay and trace conditioning. Second, she demonstrated a complete inability to learn associative discriminations, even in the case of a simple 2-tone discrimination within the context of a delay paradigm. The latter finding was unexpected because of the sparing of her deep cerebellar nuclei. These data suggest that the cerebellar cortex, or pathways traversing cerebellar cortex, play an important role in classical eyeblink discrimination learning.
Reversible Paired Helical Filament-Like Phosphorylation of Tau Is an Adaptive Process Associated with Neuronal Plasticity in Hibernating Animals

Neurofibrillary pathology [paired helical filaments (PHFs)] formed by the microtubule-associated protein tau in a hyperphosphorylated form is a major hallmark of Alzheimer's disease and related disorders. The process of tau phosphorylation, thought to be of critical importance for PHF formation, and its potential link to neurodegeneration, however, is not understood very well, mostly because of the lack of a physiological in vivo model of PHF-like tau phosphorylation. Here we describe the formation of highly phosphorylated tau, containing a number of PHF-like epitopes in torpor during hibernation. PHF-like phosphorylation of tau was not associated with fibril formation and was fully reversible after arousal. Distribution of PHF-like tau followed a consistent pattern, being most intense in the entorhinal cortex, hippocampus, and isocortical areas. Within the hippocampus, a particularly high labeling was seen in CA3 pyramidal cells. Somewhat lesser reactivity was present in CA1 neurons while dentate gyrus granule cells were not reactive. Formation of PHF-like tau in CA3 neurons was paralleled by the regression of synaptic contacts of the mossy fiber system terminating on CA3 apical dendrites. Mossy fiber afferentation was re-established during arousal, concomitantly with the decrease of PHF-like tau in CA3 neurons. These findings implicate an essential link between neuronal plasticity and PHF-like phosphorylation of tau. The repeated formation and degradation of PHF-like tau might, thus, represent a physiological mechanism not necessarily associated with pathological effects. Hibernation will, therefore, be a valuable model to study the regulation of PHF-like tau-phosphorylation and its cell biological sequelae under physiological in vivo conditions.
A multivariate approach to integrating Datasets using made4 and ade4

The public microarray repositories, ArrayExpress and the GeneExpression Omnibus (GEO), now contain over 100,000 microarray gene expression profiles (Table 1). This is a considerable data resource. However the average number of arrays per study is only between 30 and 40 (Table 1). Given that the number of features (genes) on microarrays now exceeds 50,000, this presents a considerable dimensionality problem. Low case to feature ratio is likely to remain an issue, as cost and availability of biomaterial, such as biopsy tissue, are often limiting. As a result, meta-analysis or merging data from multiple studies is attractive.
A polynomial training algorithm for calculating perceptrons of optimal stability

RECOMI (Repeated correlation matrix inversion) is a polynomially fast algorithm for searching optimally stable solutions of the perceptron learning problem. For random unbiased and biased patterns it is shown that the algorithm is able to find optimal solutions, if any exist, in at worst O(N4) floating point operations. Even beyond the critical storage capacity alpha c the algorithm is able to find locally stable solutions (with negative stability) at the same speed. There are no divergent timescales in the learning process. A full proof of convergence cannot yet be given, only major constituents of a proof are shown.
Comparison of Transcriptional Changes to Chloroplast and Mitochondrial Perturbations Reveals Common and Specific Responses in Arabidopsis

Throughout the life of a plant, the biogenesis and fine-tuning of energy organelles is essential both under normal growth and stress conditions. Communication from organelle to nucleus is essential to adapt gene regulation and protein synthesis specifically to the current needs of the plant. This organelle-to-nuclear communication is termed retrograde signaling and has been studied extensively over the last decades. In this study we have used large-scale gene expression data sets relating to perturbations of chloroplast and mitochondrial function to gain further insights into plant retrograde signaling and how mitochondrial and chloroplast retrograde pathways interact and differ. Twenty seven studies were included that assess transcript profiles in response to chemical inhibition as well as genetic mutations of organellar proteins. The results show a highly significant overlap between gene expression changes triggered by chloroplast and mitochondrial perturbations. These overlapping gene expression changes appear to be common with general abiotic, biotic, and nutrient stresses. However, retrograde signaling pathways are capable of distinguishing the source of the perturbation as indicated by a statistical overrepresentation of changes in genes encoding proteins of the affected organelle. Organelle-specific overrepresented functional categories among others relate to energy metabolism and protein synthesis. Our analysis also suggests that WRKY transcription factors play a coordinating role on the interface of both organellar signaling pathways. Global comparison of the expression profiles for each experiment revealed that the recently identified chloroplast retrograde pathway using phospho-adenosine phosphate is possibly more related to mitochondrial than chloroplast perturbations. Furthermore, new marker genes have been identified that respond specifically to mitochondrial and/or chloroplast dysfunction.
The Development of Preschoolers' Living Kinds Concept: A Longitudinal Study.

Given limitations in the integrative scope of past research, basic questions about the organization and development of preschoolers' living kinds concept remain open to debate. This study was designed to address past limitations through use of a longitudinal design, extensive stimulus set, and alternate indices of understanding. Thirty-five English-speaking 3-year-olds from middle-class families in Albuquerque, NM participated in four testing sessions over 1 year. Indices of understanding included statements that preschoolers generated about various living and nonliving objects, biological properties they attributed to the objects, and their characterization of objects as "alive" or not. Results reveal a multifaceted picture of developmental change in preschoolers' living kinds concept involving both the construction and elaboration of a core biological understanding.
Asymptotic Capacity of the Separated MIMO Two-Way Relay Channel

A multiple-input multiple-output two-way relay channel consisting of two communication nodes and a full-duplex relay node in which no direct link exists between the two communication nodes is considered. We propose an achievable scheme that employs horizontally encoded lattice codes combined with generalized singular value decomposition-based precoding for the first phase. The second phase of the proposed scheme follows the fundamentals of the previous scheme, which uses vertically encoded structural bining, with the only difference that the added codeword of the two codewords from the communication nodes, instead of those two individual codewords, is decoded and retransmitted in the proposed scheme. We show that the proposed scheme achieves the cut-set bound asymptotically as the signal-to-noise ratios of the channels tend to infinity.
GridBatch: Cloud Computing for Large-Scale Data-Intensive Batch Applications

To be competitive, enterprises are collecting and analyzing increasingly large amount of data in order to derive business insights. However, there are at least two challenges to meet the increasing demand. First, the growth in the amount of data far outpaces the computation power growth of a uniprocessor. The growing gap between the supply and demand of computation power forces Enterprises to parallelize their application code. Unfortunately, parallel programming is both time-consuming and error-prone. Second, the emerging Cloud Computing paradigm imposes constraints on the underlying infrastructure, which forces enterprises to rethink their application architecture. We propose the GridBatch system, which aims at solving large-scale data-intensive batch problems under the Cloud infrastructure constraints. GridBatch is a programming model and associated library that hides the complexity of parallel programming, yet it gives the users complete control on how data are partitioned and how computation is distributed so that applications can have the highest performance possible. Through a real client example, we show that GridBatch achieves high performance in Amazon's EC2 computing Cloud.
A scalable P2P model for optimizing application layer multicast

Multicast avoids sending repeated packets over the same network links and thus offers the promise of supporting multimedia streaming over wide-area networks. Previously, two opposite multicast schemes forward-path forwarding and reverse-path forwarding have been proposed on top of structured peer-to-peer (p2p) overlay networks. In this paper, we propose a new model for optimizing application layer multicast in the context of Peer-to-Peer networks (structured and unstructured). In this contribution, we consider two approaches for multicast tree construction: a "primitive " approach, and an optimized one based on a distributed algorithm. The proposed model inherits from main P2P attributes such as: scalability, fault tolerance, while taking into consideration the respective characteristics of "one to many" and "many to many" applications. We also give a performance evaluation for validation and comparison purposes. For this we consider some main existing application layer multicast protocols.
Algorithms for Adapting Materialised Views in Data Warehouses

In this paper we consider the problem of materi-alised view adaptation in data warehouses. Materi-alised views are important in data warehousing where they are used to speed up query processing on large amounts of data. User requirements change over time, which may change the de(cid:12)nitions of views dynamically. For such situations, the question arises whether the materialised views should be recomputed from scratch for every change in the de(cid:12)nition or they should be obtained by adapting old materialised views. Changes to a view de(cid:12)nition may be expensive, if the view is recomputed from scratch. Therefore, it is worthwhile to examine ways of performing changes to the materialised view without recomputing the entire view which has undergone a change in de(cid:12)nition. We present adaptation algorithms for adapting views when the changes are made in each SELECT, FROM, and WHERE clause. The main idea of our algorithms is to augment the schemas of base relations by adding ‘join-count’ attributes to them, and augment the schemas of views by keeping ‘derive-count’ attributes on them as extra information.
Modularity and the Cultural Mind

A central question in the study of the mind is how cognitive functions are shaped by a complex interplay of genetic and experiential processes. Recent evidence from cultural neuroscience indicates that cultural values, practices, and beliefs influence brain function across a variety of cognitive processes from vision to social cognition. This evidence extends to low-level perceptual systems comprised of domain-specific mechanisms, suggesting the importance of ecological and cultural variation in the evolutionary and developmental processes that give rise to the human mind and brain. In this article, we argue that investigating the architecture of the human mind will require understanding how the human mind and brain shape and are shaped by culture–gene coevolutionary processes.
Increasing Activity in Enterprise Online Communities Using Content Recommendation

Although online communities have become popular both on the web and within enterprises, many of them often experience low levels of activity and engagement from their members. Previous studies identified the important role of community leaders in maintaining the health and vitality of their communities. One of their key means for doing so is by contributing relevant content to the community. In this paper, we study the effects of recommending social media content on enterprise community leaders. We conducted a large-scale user survey with four recommendation rounds, in which community leaders indicated their willingness to share social media items with their communities. They also had the option to instantly share these items. Recommendations were generated based on seven types of community interest profiles that were member-based, content-based, or hybrid. Our results attest that providing content recommendations to leaders can help uplift activity within their communities.
PCD03VH LTE and 1xEV–DO Turbo Decoder

PCD03VH Features Turbo Decoder 8 state 3GPPTM LTE and 3GPP2 1xEV–DO Release B compatible Rate 1/2, 1/3, 1/4 or 1/5 40 to 6144 (3GPPTM LTE) or 17 to 20730 (3GPP2) bit interleaver Includes ping–pong input and output memories. Optional external interleaver parameters for 3GPPTM LTE and programmable row coefficients for 3GPP2 interleaver Up to 107 MHz internal clock Up to 10.2 Mbit/s with 5 decoder iterations 6–bit signed magnitude or two’s complement input data with serial input Optional log–MAP or max–log–MAP constituent decoder algorithms Up to 128 iterations in 1/2 iteration steps. Optional power efficient early stopping Optional extrinsic information scaling and limiting 16 or 24 bit CRC check Implement one or two different standards from the one core Free simulation software
Risk-Constrained Reinforcement Learning with Percentile Risk Criteria

In many sequential decision-making problems one is interested in minimizing an expected cumulative cost while taking into account \emph{risk}, i.e., increased awareness of events of small probability and high consequences. Accordingly, the objective of this paper is to present efficient reinforcement learning algorithms for risk-constrained Markov decision processes (MDPs), where risk is represented via a chance constraint or a constraint on the conditional value-at-risk (CVaR) of the cumulative cost. We collectively refer to such problems as percentile risk-constrained MDPs. Specifically, we first derive a formula for computing the gradient of the Lagrangian function for percentile risk-constrained MDPs. Then, we devise policy gradient and actor-critic algorithms that (1) estimate such gradient, (2) update the policy in the descent direction, and (3) update the Lagrange multiplier in the ascent direction. For these algorithms we prove convergence to locally optimal policies. Finally, we demonstrate the effectiveness of our algorithms in an optimal stopping problem and an online marketing application.
Joint source-channel coding of scalable video with partially coded index assignment using Reed-Muller codes

Joint source-channel coding of scalable video using motion-compensated temporal filtering is considered. The proposed coding scheme consists of a structured vector quantizer based on lattice constellations and a linear index assignment, which minimizes simultaneously the channel and source distortions. Both uncoded linear index assignment as well as partially coded linear index assignment via Reed-Muller codes are considered. The proposed system is compared to an unstructured quantizer with minimax index assignment. Simulation results indicate that, for a Gaussian channel, the structured-codebook scheme is very robust, maintaining near-noiseless performance even when the channel is very noisy. Additionally, the proposed structured-quantizer scheme outperforms its unstructured counterpart when channel noise levels are high.