Miracle-dz/UniFAR-FTUs huggingface dataset:
Single Medial Prefrontal Neurons Cope with Error

Learning from mistakes is a key feature of human behavior. However, the mechanisms underlying short-term adaptation to erroneous action are still poorly understood. One possibility relies on the modulation of attentional systems after an error. To explore this possibility, we have designed a Stroop-like visuo-motor task in monkeys that favors incorrect action. Using this task, we previously found that single neurons recorded from the anterior cingulate cortex (ACC) were closely tuned to behavioral performance and, more particularly, that the activity of most neurons was biased towards the evaluation of erroneous action. Here we describe single neurons engaged in both error detection and response alertness processing, whose activation is closely associated with the improvement of subsequent behavioral performance. Specifically, we show that the effect of a warning stimulus on neuronal firing is enhanced after an erroneous response rather than a successful one and that this outcome is correlated with an error rate decrease. Our results suggest that the anterior cingulate cortex, which exhibits this activity, serves as a powerful computational locus for rapid behavioral adaptation.
Multiple Genetic Elements Carry the Tetracycline Resistance Gene tet(W) in the Animal Pathogen Arcanobacterium pyogenes

ABSTRACT The tet(W) gene is associated with tetracycline resistance in a wide range of bacterial species, including obligately anaerobic rumen bacteria and isolates from the human gut and oral mucosa. However, little is known about how this gene is disseminated and the types of genetic elements it is carried on. We examined tetracycline-resistant isolates of the animal commensal and opportunistic pathogen Arcanobacterium pyogenes, all of which carried tet(W), and identified three genetic elements designated ATE-1, ATE-2, and ATE-3. These elements were found in 25%, 35%, and 60% of tetracycline-resistant isolates, respectively, with some strains carrying both ATE-2 and ATE-3. ATE-1 shows characteristics of a mobilizable transposon, and the tet(W) genes from strains carrying this element can be transferred at low frequencies between A. pyogenes strains. ATE-2 has characteristics of a simple transposon, carrying only the resistance gene and a transposase, while in ATE-3, the tet(W) gene is associated with a streptomycin resistance gene that is 100% identical at the DNA level with the aadE gene from the Campylobacter jejuni plasmid pCG8245. Both ATE-2 and ATE-3 show evidence of being carried on larger genetic elements, but conjugation to other strains was not observed under the conditions tested. ATE-1 was preferentially associated with A. pyogenes strains of bovine origin, while ATE-2 and ATE-3 elements were primarily found in porcine isolates, suggesting that these elements may circulate in different environments. In addition, four alleles of the tet(W) gene, primarily associated with different elements, were detected among A. pyogenes isolates.
Automatic Verification of External Interrupt Behaviors for Microprocessor Design

Interrupt behaviors, particularly the external ones, are difficult to verify in a microprocessor. Because the external interrupt arrival time and the microprocessor response time must be precise, verification requires sophisticated hardware and software design. This paper proposes a computer-aided design tool, called processor exception verification tool (PEVT), to verify the external interrupt behaviors of microprocessors, including individual, multiple, and nested interrupts. An architecture description language extension, called Exception Description Language (EXPDL), is developed for the designer to capture the external interrupt behaviors for the microprocessor under verification. PEVT is responsible for generating the verification cases, consisting of both the hardware and software modules, which are then used to trigger the expected behaviors. A monitor is also generated from the EXPDL description to verify these cases. PEVT has been applied to the verification of an academic implementation of the ARM7 microprocessor core and a public domain scalable processor architecture (SPARC) microprocessor core. The ARM7 has had a system-on-a-chip test chip and software porting including multimedia applications (MP3/JPEG/ .) and a real time operating system muC-OSII. PEVT successfully identified several sophisticated remaining bugs with 527 lines of EXPDL description and took only 4 204 961 cycles of register transfer language simulation with execution time of 4.5 h in a SUN Blade2000 workstation. The experiment shows that PEVT could generate highly focused verification cases, less than 98 cycles per case on the average, which identify potential bugs with much less simulation cycles at the early verification stage, compared with traditional manual-based approaches.
Note on the Khaneja Glaser decomposition

Recently, Vatan and Williams utilize a matrix decomposition of SU(2n) introduced byKhaneja and Glaser to produce CNOT-efficient circuits for arbitrary three-qubit unitaryevolutions. In this note, we place the Khaneja Glaser Decomposition (KGD) in contextas a SU(2n) = KAK decomposition by proving that its Cartan involution is type AIII,given n ≥ 3. The standard type AIII involution produces the Cosine-Sine Decomposition(CSD), a well-known decomposition in numerical linear algebra which may be computedusing mature, stable algorithms. In the course of our proof that the new decomposition istype AIII, we further establish the following. Khaneja and Glaser allow for a particulardegree of freedom, namely the choice of a commutative algebra a, in their construction.Let χ1n be a SWAP gate applied on qubits 1, n. Then χ1n vχ1n = k1 a k2 is a KGD fora = span R{χ1n(|j〉〈N-j-1|-|N-j-1〉〈j|)χ1n} if and only if v = (χ1nk1χ1n)(χ1naχ1n)(χ1nk2χ1n) is a CSD.
Elastic virtual network function placement

Nowadays, many cloud providers offer Virtual Network Function (VNF) services that are dynamically scaled according to the workload. Enterprises enjoy these services by only paying for the actual consumed resources. From a cloud provider's standpoint, the cost of these services must be kept as low as possible, while QoS is maintained and service downtime is minimized. In this paper, we introduce Elastic Virtual Network Function Placement (EVNFP) problem and present a model for minimizing operational costs in providing VNF services. In this model, the elasticity overhead and the trade-off between bandwidth and host resource consumption are considered together, while the previous works ignored this perspective of the problem. We propose a solution called Simple Lazy Facility Location (SLFL) that optimizes the placement of VNF instances in response to on-demand workload. Our experiments suggest that SLFL can accept two times more workload while incurring similar operational cost compared to first-fit and random placements.
Computer-Aided Design and Manufacture and Rapid Prototyped Polymethylmethacrylate Reconstruction

&NA; This article discusses the application of computer-aided design and rapid prototyping techniques in polymethylmethacrylate reconstruction of craniofacial bone defects. This method avoids the probability of tissue damage due to exothermic reaction during the polymerization process and provides precise implants that exactly fit the defects. Methods A total of 11 patients who have various-sized craniofacial defects underwent polymethylmethacrylate reconstruction. We performed three-dimensional reconstruction and operative design using computer software. According to the design, we determined the shape and size of the implants and made individualized implants for craniofacial bone defects with the rapid prototyping technique. Results With the application of computer-aided design and a rapid prototyping technique, we could accurately determine the shape, size, and embedding location. Prefabricating the individual implant models is useful in improving the accuracy of treatment. No cases of infection, seroma, extrusion, or contour irregularity occurred as a complication, and all patients were satisfied with the results. During the follow-up period, ranging from 1 to 6 years, all patients remained satisfied, and no complications were sustained. Conclusions In cases of various-sized cranial defects and complex maxillofacial defects that have enough soft tissue coverage and that do not have contact with a third space, prefabricated methyl methacrylate implants can be used safely. Patients will feel more comfortable if the postoperative shape resembles the original appearance, so the proposed algorithm effectively creates a customized implant.
Weighted least square estimation algorithm with software phase-locked loop for voltage sag compensation by SMES

A superconducting magnetic energy storage (SMES) system is developed to protect a critical load from momentary voltage sags. This system is composed of a 0.3 MJ SMES coil, a 150 KVA IGBT-based current source inverter and a phase-shift inductor. In order to compensate the load voltage effectively whenever a source voltage sag happens, it is crucial for the signal processing algorithm to extract the fundamental components from the sample signals quickly, precisely and stably. In this paper, an estimation algorithm based on the weighted least square principle is developed to detect the positive- and negative-sequence fundamental components from the measured AC voltages and currents. A software phase-locked loop (SPLL) is applied to track the positive-sequence component of the source voltage. Simulations and experiments are carried out to demonstrate the algorithms. The results are presented.
Kernelized Probabilistic Matrix Factorization: Exploiting Graphs and Side Information

We propose a new matrix completion algorithm— Kernelized Probabilistic Matrix Factorization (KPMF), which effectively incorporates external side information into the matrix factorization process. Unlike Probabilistic Matrix Factorization (PMF) [14], which assumes an independent latent vector for each row (and each column) with Gaussian priors, KMPF works with latent vectors spanning all rows (and columns) with Gaussian Process (GP) priors. Hence, KPMF explicitly captures the underlying (nonlinear) covariance structures across rows and columns. This crucial difference greatly boosts the performance of KPMF when appropriate side information, e.g., users’ social network in recommender systems, is incorporated. Furthermore, GP priors allow the KPMF model to fill in a row that is entirely missing in the original matrix based on the side information alone, which is not feasible for standard PMF formulation. In our paper, we mainly work on the matrix completion problem with a graph among the rows and/or columns as side information, but the proposed framework can be easily used with other types of side information as well. Finally, we demonstrate the efficacy of KPMF through two different applications: 1) recommender systems and 2) image restoration.
Heteromer score—using internal standards to assess the quality of proteomic data

In the cell, the majority of proteins exist in complexes. Most of these complexes have a constant stoichiometry and thus can be used as internal standards. In this rapid communication, we show that it is possible to calculate a correlation coefficient that reflects the reproducibility of the analytical approach used. The abundance of one subunit in a heterodimer is plotted against the abundance of the other, and this is repeated for all subunits in all heteromers found in the data set. The correlation coefficient obtained (the “heteromer score”) is a new bioinformatic tool that is independent of the method used to collect the data, requires no special sample preparation and can be used retrospectively on old datasets. It can be used for quality control, to indicate when a change becomes significant or identify complexes whose stoichiometry has been perturbed during the experiment.
The crystal structure of yeast mitochondrial ThrRS in complex with the canonical threonine tRNA

In mitochondria of Saccharomyces cerevisiae, a single aminoacyl-tRNA synthetase (aaRS), MST1, aminoacylates two isoacceptor tRNAs, tRNA1Thr and tRNA2Thr, that harbor anticodon loops of different size and sequence. As a result of this promiscuity, reassignment of the CUN codon box from leucine to threonine is facilitated. However, the mechanism by which a single aaRS binds distinct anticodon loops with high specificity is not well understood. Herein, we present the crystal structure of MST1 in complex with the canonical tRNA2Thr and non-hydrolyzable analog of threonyl adenylate. Our structure reveals that the dimeric arrangement of MST1 is essential for binding the 5′-phosphate, the second base pair of the acceptor stem, the first two base pairs of the anticodon stem and the first nucleotide of the variable arm. Further, in contrast to the bacterial ortholog that ‘reads’ the entire anticodon sequence, MST1 recognizes bases in the second and third position and the nucleotide upstream of the anticodon sequence. We speculate that a flexible loop linking strands β4 and β5 may be allosteric regulator that establishes cross-subunit communication between the aminoacylation and tRNA-binding sites. We also propose that structural features of the anticodon-binding domain in MST1 permit binding of the enlarged anticodon loop of tRNA1Thr.
A Novel Unpredictable Temporal based Pseudo Random Number Generator

numbers are sequences of integers which show absolutely no relation to each other anywhere in the sequence. Pseudo random numbers (PRNs) are random numbers which can be generated deterministically. Pseudo random numbers are widely used in cryptographic protocols to provide secrecy. A wide variety of pseudo random number generators (PRNGs) were proposed earlier which exhibit characteristics of PRNG and generate pseudo random numbers. In this paper, we propose a temporal based algorithm to generate pseudo random numbers. Our algorithm utilizes dynamic system clock and product of two large prime numbers generated randomly. Using dynamic system clock, we ensure that the seed is obtained from entropy source of some physical phenomenon and product of large prime numbers generated randomly ensure randomness of generated numbers. Our algorithm is easy to implement on any computing device and can be used for generating sequence of pseudo random numbers for desired purpose.
Deep Stereo Matching with Explicit Cost Aggregation Sub-Architecture

Deep neural networks have shown excellent performance for stereo matching. Many efforts focus on the feature extraction and similarity measurement of the matching cost computation step while less attention is paid on cost aggregation which is crucial for stereo matching. In this paper, we present a learning-based cost aggregation method for stereo matching by a novel sub-architecture in the end-to-end trainable pipeline. We reformulate the cost aggregation as a learning process of the generation and selection of cost aggregation proposals which indicate the possible cost aggregation results. The cost aggregation sub-architecture is realized by a two-stream network: one for the generation of cost aggregation proposals, the other for the selection of the proposals. The criterion for the selection is determined by the low-level structure information obtained from a light convolutional network. The two-stream network offers a global view guidance for the cost aggregation to rectify the mismatching value stemming from the limited view of the matching cost computation. The comprehensive experiments on challenge datasets such as KITTI and Scene Flow show that our method outperforms the state-of-the-art methods.
Development of Selective Bisubstrate‐Based Inhibitors Against Protein Kinase C (PKC) Isozymes By Using Dynamic Peptide Microarrays

Kinase inhibitors are increasingly important in drug development. Because the majority of current inhibitors target the conserved ATP‐binding site, selectivity might become an important issue. This could be particularly problematic for the potential drug target protein kinase C (PKC), of which twelve isoforms with high homology exist in humans. A strategy to increase selectivity is to prepare bisubstrate‐based inhibitors that target the more selective peptide‐binding site in addition to the ATP‐binding site. In this paper a generally applicable, rapid methodology is presented to discover such bisubstrate‐based leads. Dynamic peptide microarrays were used to find peptide‐binding site inhibitors. These were linked with chemoselective click chemistry to an ATP‐binding site inhibitor, and this led to novel bisubstrate structures. The peptide microarrays were used to evaluate the resulting inhibitors. Thus, novel bisubstrate‐based inhibitors were obtained that were both more potent and selective compared to their constituent parts. The most promising inhibitor has nanomolar affinity and selectivity towards PKCθ amongst three isozymes.
How to partition diversity

Diversity measurement underpins the study of biological systems, but measures used vary across disciplines. Despite their common use and broad utility, no unified framework has emerged for measuring, comparing and partitioning diversity. The introduction of information theory into diversity measurement has laid the foundations, but the framework is incomplete without the ability to partition diversity, which is central to fundamental questions across the life sciences: How do we prioritise communities for conservation? How do we identify reservoirs and sources of pathogenic organisms? How do we measure ecological disturbance arising from climate change? The lack of a common framework means that diversity measures from different fields have conflicting fundamental properties, allowing conclusions reached to depend on the measure chosen. This conflict is unnecessary and unhelpful. A mathematically consistent framework would transform disparate fields by delivering scientific insights in a common language. It would also allow the transfer of theoretical and practical developments between fields. We meet this need, providing a versatile unified framework for partitioning biological diversity. It encompasses any kind of similarity between individuals, from functional to genetic, allowing comparisons between qualitatively different kinds of diversity. Where existing partitioning measures aggregate information across the whole population, our approach permits the direct comparison of subcommunities, allowing us to pinpoint distinct, diverse or representative subcommunities and investigate population substructure. The framework is provided as a ready-to-use R package to easily test our approach.
Frequency and Genotype of Hepatitis D Virus Infection in Patients Infected with HIV and Those Undergoing Hemodialysis

Background Hepatitis D virus (HDV) is a defective virus dependent on hepatitis B virus (HBV) for its replication. Due to HDV transmission routes, patients undergoing hemodialysis and those with HIV infection are at risk of acquiring HDV. Objectives This study was aimed to determine the frequency and genotype of HDV infection among patients with HIV infection and those undergoing hemodialysis. Patients and Methods 720 cases including 120 patients undergoing hemodialysis, and 600 patients with HIV infection were studied. All cases with positive results for HBsAg were evaluated for the presence of anti-HDV antibodies. Samples with Anti-HDV positive results were subjected to nested PCR for HDV-RNA confirmation, and sequenced for HDV genotype determination. Results HBsAg was found in 9 (7.5%) of 120 patients undergoing hemodialysis, and 9 (1.5%) of 600 patients with HIV infection. 3 (33.3%) of patients undergoing hemodialysis with positive results for HBsAg, and 5 (55.5%) of cases with HIV infection and positive results for HBsAg, had positive findings for anti-HDV which were then subjected to nested PCR. The amplification results confirmed that in 3 (37.5%) samples HDV-RNA was detected. Overall 2.5% of patients undergoing hemodialysis, and 0.8% of cases infected with HIV had positive results for anti-HDV and 1.7% and 0.2% of cases undergoing hemodialysis and patients infected with HIV had positive findings for HDV-RNA respectively. All of the HDV isolates were clustered in clade 1. Conclusions The survey showed that overall HDV frequency was not high in our high risk cases. Therefore, practitioners and health care managers should become aware of the risk of dual infection with HBV and HDV especially in high risk patients.
The High Sensitivity to Rotenone of Striatal Dopamine Uptake Suggests the Existence of a Constitutive Metabolic Deficiency in Dopaminergic Neurons From the Substantia Nigra

The toxicity of the 1‐methyl‐4‐phenylpyridinium ion (MPP+), an inhibitor of complex I of the respiratory chain, on nigrostriatal dopaminergic neurons contrasts with its relative inefficiency towards other catecholaminergic cell populations in spite of their ability to accumulate this neurotoxin through their high‐affinity uptake system. A constitutive metabolic deficiency of the nigrostriatal dopaminergic neurons could account for their particular vulnerability to MPP+. In order to substantiate this hypothesis, we compared the inhibitory effects of rotenone, an inhibitor of mitochondrial oxidative phosphorylation, on the uptake of dopamine, serotonin, noradrenaline and GABA in mouse striatal synaptosomes, and of dopamine, serotonin and GABA in cultured mesencephalic neurons. In both preparations, the uptake of dopamine was much more affected than that of other neurotransmitters by rotenone. This result was confirmed using two other unrelated inhibitors of oxidative phosphorylation. Moreover, dopamine uptake in synaptosomes from the dorsolateral striatum was more sensitive to rotenone than uptake in synaptosomes from the nucleus accumbens. This indicates that intrinsic metabolic properties of the nigrostriatal dopaminergic neurons may explain the strong inhibition by rotenone of striatal dopamine uptake. Altogether, these results suggest that a constitutive metabolic deficiency could account, at least in part, for the selective vulnerability of the nigrostriatal dopaminergic pathway to the action of the neurotoxin MPP+.
O-trees: a constraint-based index structure

Constraint search trees are a generic approach to search trees where all operations are defined in terms of constraints. This abstract viewpoint makes clear the fundamental operations of search trees and immediately points to new possibilities for search trees. In this paper we present height-balanced constraint search trees (HCSTs), a general approach to building height-balanced index structures, and exemplify the approach with a new spatial index structure, the O-tree. An object in an O-tree is represented by constraints of the form ax/sub i/+bx/sub j//spl les/d where {a,b}/spl sube/{-1,0,1} and x/sub 1/,. ,x/sub n/ are the dimensions of the spatial data. We define the basic operations to build and search HCSTs, as well as constraint joins. We illustrate these algorithms using O-trees showing how the algorithms can make use of the more accurate information in the O-tree nodes. Experiments compare the IO-performance of the 2-dimensional O-tree with the R-tree.