Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural Determinants of the Outer Shell of β-Carboxysomes in Synechococcus elongatus PCC 7942: Roles for CcmK2, K3-K4, CcmO, and CcmL

Cyanobacterial CO2-fixation is supported by a CO2-concentrating mechanism which improves photosynthesis by saturating the primary carboxylating enzyme, ribulose 1, 5-bisphosphate carboxylase/oxygenase (RuBisCO), with its preferred substrate CO2. The site of CO2-concentration is a protein bound micro-compartment called the carboxysome which contains most, if not all, of the cellular RuBisCO. The shell of β-type carboxysomes is thought to be composed of two functional layers, with the inner layer involved in RuBisCO scaffolding and bicarbonate dehydration, and the outer layer in selective permeability to dissolved solutes. Here, four genes (ccmK2-4, ccmO), whose products were predicted to function in the outer shell layer of β-carboxysomes from Synechococcus elongatus PCC 7942, were investigated by analysis of defined genetic mutants. Deletion of the ccmK2 and ccmO genes resulted in severe high-CO2-requiring mutants with aberrant carboxysomes, whilst deletion of ccmK3 or ccmK4 resulted in cells with wild-type physiology and normal ultrastructure. However, a tandem deletion of ccmK3-4 resulted in cells with wild-type carboxysome structure, but physiologically deficient at low CO2 conditions. These results revealed the minimum structural determinants of the outer shell of β-carboxysomes from this strain: CcmK2, CcmO and CcmL. An accessory set of proteins was required to refine the function of the pre-existing shell: CcmK3 and CcmK4. These data suggested a model for the facet structure of β-carboxysomes with CcmL forming the vertices, CcmK2 forming the bulk facet, and CcmO, a “zipper protein,” interfacing the edges of carboxysome facets.
Mutational analysis of the conserved motifs of influenza A virus polymerase basic protein 1

Influenza virus polymerase complex is a heterotrimer consisting of polymerase basic protein 1 (PB1), polymerase basic protein 2 (PB2), and polymerase acidic protein (PA). Of these, only PB1, which has been implicated in RNA chain elongation, possesses the four conserved motifs (motifs I, II, III, and IV) and the four invariant amino acids (one in each motif) found among all viral RNA-dependent RNA or RNA-dependent DNA polymerases. We have modified an assay system developed by Huang et al. (T.-J. Huang, P. Palese, and M. Krystal, J. Virol. 64:5669-5673, 1990) to reconstitute the functional polymerase activity in vivo. Using this assay, we have examined the requirement of each of these motifs of PB1 in polymerase activity. We find that each of these invariant amino acids is critical for PB1 activity and that mutation in any one of these residues renders the protein nonfunctional. We also find that in motif III, which contains the SSDD sequence, the signature sequence of influenza virus RNA polymerase, SDD is essentially invariant and cannot accommodate sequences found in other RNA viral polymerases. However, conserved changes in the flanking sequences of SDD can be partially tolerated. These results provide the experimental evidence that influenza virus PB1 possesses a similar polymerase module as has been proposed for other RNA viruses and that the core SDD sequence of influenza virus PB1 represents a sequence variant of the GDN in negative-stranded nonsegmented RNA viruses, GDD in positive-stranded RNA virus and double-stranded RNA viruses, or MDD in retroviruses.
The mouse organellar biogenesis mutant buff results from a mutation in Vps33a, a homologue of yeast vps33 and Drosophila carnation

In the mouse, more than 16 loci are associated with mutant phenotypes that include defective pigmentation, aberrant targeting of lysosomal enzymes, prolonged bleeding, and immunodeficiency, the result of defective biogenesis of cytoplasmic organelles: melanosomes, lysosomes, and various storage granules. Many of these mouse mutants are homologous to the human Hermansky–Pudlak syndrome (HPS), Chediak–Higashi syndrome, and Griscelli syndrome. We have mapped and positionally cloned one of these mouse loci, buff (bf), which has a mutant phenotype similar to that of human HPS. Mouse bf results from a mutation in Vps33a and thus is homologous to the yeast vacuolar protein-sorting mutant vps33 and Drosophila carnation (car). This is the first found defect of the class C vacuole/prevacuole-associated target soluble N-ethylmaleimide-sensitive factor attachment protein receptor (t-SNARE) complex in mammals and the first mammalian mutant found that is directly homologous to a vps mutation of yeast. VPS33A thus is a good candidate gene for a previously uncharacterized form of human HPS.
Stability and stabilisation of planar switched linear systems via LaSalle's invariance principle

This paper investigates the problem of uniformly asymptotical stability (UAS) and stabilisation of planar switched linear systems using LaSalle's invariance principle of switched systems. First, we show that a common weak quadratic Lyapunov function (WQLF) is enough to assure the UAS of a switched linear system with stable modes. Then the necessary and sufficient conditions for the existence of common WQLF are obtained. Secondly, we consider the problem of uniformly asymptotical stabilisation (UASZ) of single-input planar switched linear systems. Necessary and sufficient conditions for the closed-loop system with proper feedback to share a common WQLF are presented. It is also proved that a common WQLF is enough to assure the UAS of the closed-loop system.
A 1‐step Bayesian predictive approach for evaluating in vitro in vivo correlation (IVIVC)

IVIVC (in vitro in vivo correlation) methods may support approving a change in formulation of a drug using only in vitro dissolution data without additional bioequivalence trials in human subjects. Most current IVIVC methods express the in vivo plasma concentration of a drug formulation as a function of the cumulative in vivo absorption. The absorption is not directly observable, so is estimated by the cumulative dissolution of the drug formulation in in vitro dissolution trials. The calculations conventionally entail the complex and potentially unstable mathematical operations of convolution and deconvolution, or approximations aimed at omitting their need. This paper describes, and illustrates with data on a controlled‐release formulation, a Bayesian approach to evaluating IVIVC that does not require convolution, deconvolution or approximation. This approach incorporates between‐ and within‐subject (or replicate) variability without assuming asymptotic normality. The plasma concentration curve is expressed in terms of the in vitro dissolution percentage instead of time, recognizing that this correspondence may be noisy because of the various sources of error. All conventional functions of the concentration curve such as AUC, Cmax and Tmax can be expressed in terms of dissolution percentage, with uncertainties arising from variability in measuring absorption and dissolution accounted for explicitly. Copyright © 2009 John Wiley & Sons, Ltd.
A classification system of lung nodules in CT images based on fractional Brownian motion model

In this paper, we present a classification system for differentiating malignant pulmonary nodules from benign nodules in computed tomography (CT) images based on a set of fractal features derived from the fractional Brownian motion (fBm) model. In a set of 107 CT images obtained from 107 different patients with each image containing a solitary pulmonary nodule, our experimental result show that the accuracy rate of classification and the area under the Receiver Operating Characteristic (ROC) curve are 83.11% and 0.8437, respectively, by using the proposed fractal-based feature set and a support vector machine classifier. Such a result demonstrates that our classification system has highly satisfactory diagnostic performance by analyzing the fractal features of lung nodules in CT images taken from a single post-contrast CT scan.
AGMI - An Agent-mining Tool and its Application to Brazilian Government Auditing

This paper presents research combining two originally separated areas increasingly interrelated: distributed multi-agent systems and data mining. In our approach, we prove the interaction features in a bilateral and complementary way, since we have defined an integrated architecture and developed a prototype, which has been used in a government auditing study case. In Brazil, government auditing is performed by the Office of the Comptroller General (CGU), where several approaches are being used to prevent and fight corruption. However, some activities such as government purchasing fraud detection are limited by the difficulty in finding effective ways to implement. Considering data mining perspective, we have used different model functions, such as clusterization and link analysis with association rules. Our approach integrating multi-agent and data mining techniques resulted in expressive discovered knowledge, which would help detection of cartels acting in public bidding processes at CGU.
Stereoscopic to Multi-view Video Conversion System FPGA Implementation

Today, the stereoscopic 3D movie is already mainstream, and almost all new devices support stereoscopic 3D movie. The content generation and the necessity to wear glasses, however, hinder the broader acceptance of the technology. Audiences who have poor vision prefer to the glasses free stereoscopic movie. Multi-view video enables a glasses free perception of stereoscopic 3D movie. To support this, the paper proposes a novel and simplified hardware system to generate multi-view video from stereo video by image domain warping. Additionally, we elaborate the memory management and the algorithm of each module. Relied on the sparse matched feature points and saliency image extracted from the stereoscopic video, the system has already realized the conversion from stereoscopic video to multi-view video real-time based on FPGA.
Cube surface modeling for human detection in crowd

Human detection in dense crowds poses to be a demanding task owing to complex background and serious occlusion. In this paper, we propose a novel real-time and reliable human detection system. We solve the human detection problem by presenting a novel cube surface model captured by a binocular stereo vision camera. We first propose a cube surface model to estimate the 3D background cubes in the surveillance area. We then develop a shadow-free strategy for cube surface model updating. Thereafter, we present a shadow weighted clustering method to efficiently search for human as well as remove false alarms. Ultimately, we have developed a highly robust human detection system, and we carefully evaluate our system in many real challenge indoor and outdoor scenes. Expensive experiments demonstrate our system achieves real-time performance, higher detection rate and lower face alarms in comparison with state-of-the-art human detection methods.
Evaluating Embeddings using Syntax-based Classification Tasks as a Proxy for Parser Performance

Most evaluations for vector space models are semantically motivated, e.g. by measuring how well they capture word similarity. If one is interested in syntax-related downstream applications such as dependency parsing, a syntactically motivated evaluation seems preferable. As we show, the choice of embeddings has a noticeable impact on parser performance. Since evaluating embeddings directly in a parser is costly, we analyze the correlation between the full parsing task and a simple linear classification task as a potential proxy.
The infrastructure of a global field and baby step-giant step algorithms

In Computational Number Theory, one is interested in the computation of invariants. One such invariant is the regulator of a number field or a global function field. The regulator can be obtained from the unit lattice, whose structure corresponds to the structure of the so called infrastructure. In this thesis, we generalize the infrastructure to the n-dimensional case; so far, the infrastructure was mainly investigated in the one-dimensional case. For that purpose, we generalize f -representations and use them to obtain a reduction map. Furthermore, we relate the infrastructure to the (Arakelov) divisor class group and describe the divisor class group using f -representations. This allows both to do explicit arithmetic in the divisor class group and to compute giant steps in the infrastructure. This extends work particularly by J. Buchmann and R. Schoof in the number field case and S. Paulus and H. -G. Rück in the function field case. We also discuss an implementation of computation of boxes in the function field case, and explain how it can be used to compute giant steps and baby steps. Moreover, we describe existing algorithms for computation of the unit lattice and, hence, the regulator. We present two approaches for the function field case, one using algorithms designed for operating on finite abelian groups in the case that one infinite place has degree one, and one using a lifting strategy for reducing to the case of at least one infinite place of degree one. Finally, we extend J. Buchmann’s baby step-giant step algorithm for number fields to the global field case and combine it with an optimization by D. Terr for the classic baby step-giant step algorithm.
Optimal Spectrum Handoff Control for CRN Based on Hybrid Priority Queuing and Multi-Teacher Apprentice Learning

An optimal spectrum handoff scheme for cognitive radio networks (CRNs) is presented in this paper. This scheme has two novel features: 1) Hybrid rule-based priority queuing model: To overcome the limitations of preemptive resume priority and nonpreemptive resume priority (PRP/NPRP) queuing models, a hybrid queuing model with discretion rule is proposed to characterize the spectrum access priority among secondary users (SUs). This hybrid queuing model is then used to calculate the channel waiting time during spectrum handoff; and 2) Multiteacher apprentice learning: Unlike existing CRN cognition engine designs that focus on spectrum adaptation through SU self-learning (i.e., an SU learns how to adapt to the dynamic CRN environment by itself), we propose the concept of multiteacher knowledge transfer, wherein the multiple SUs that already have mature spectrum adaptation strategies share their knowledge with an inexperienced SU. Our simulation results show that the proposed new designs improve the spectrum handoff accuracy for the complex CRN environments.
Optical Flow Analysis Based on Cellular Neural Networks

The optical flow is widely used in detection and dynamic analysis of moving objects, but it has the heavy computational burden, so it has not been able to in the real-time progress needs. Cellular Neural Network is a kind of neural network with outstanding image processing capabilities, and can be utilized in real-time applications. This paper presents an optical flow analysis method based on CNN, and for extract the interested moved object accurately, an approach which can be realized by CNN was given. Simulation results confirm the validity of the approach developed herein.
Emotional Life of the Family: Parental Meta-Emotions, Children's Temperament and Internalising and Externalising Problems

Cilj istraživanja bio je ispitati neke pretpostavke Gottmanova modela roditeljskih metaemocija na uzorku roditelja djece predskolske dobi. U istraživanju je sudjelovalo 506 roditelja. Upitnike o metaemocijama, dimenzijama temperamenta te djecjim internaliziranim i eksternaliziranim problemima ispunjavali su zasebno majka i otac. Majcina i oceva svjesnost vlastitih i djecjih emocija i postupanje s djecjim emocijama indirektno je povezana s djecjim eksternaliziranim i internaliziranim problemima preko djecje negativne afektivnosti i samokontrole a dodatno je svjesnost izravno povezana s djecjim internaliziranim i eksternaliziranim problemima. Rezultati dobivenih modela pokazuju da je majcina i oceva svjesnost vlastitih i djecjih emocija i postupanje s djecjim emocijama pozitivno povezana sa samokontrolom i negativno povezana s negativnom afektivnosti, dok je jedino majcina i oceva svjesnost vlastitih i djecjih emocija negativno povezana s eksternaliziranim i internaliziranim problemima. Istodobno, negativna je afektivnost pozitivno povezana s djecjim eksternaliziranim i internaliziranim problemima, a samokontrola je negativno povezana s djecjim eksternaliziranim i internaliziranim problemima. Ovim istraživanjem potvrdili smo dio pretpostavki iz Gottmanova modela kako roditeljske metaemocije utjecu na djecje izlazne varijable.
Identification of Circulating Fibrocytes and Dendritic Derivatives in Corneal Endothelium of Patients With Fuchs' Dystrophy.

Purpose Fuchs' endothelial corneal dystrophy (FECD) is a degenerative eye disorder affecting 4% of Americans older than 40. It is the leading indication for corneal endothelial (CE) transplantation for which there is a global donor shortage. This study aimed to gain further insight into the pathophysiology of FECD and identify targets for nonsurgical therapy. Methods CE from patients with late-onset FECD was compared with that of normal controls using microarray expression analysis (n = 4 FECD, n = 4 normal), reverse transcriptase quantitative PCR (n = 9 FECD, n = 8 normal), and immunohistology (n = 55 FECD, n = 15 normal). Results This led to the identification of circulating fibrocytes and their dendritic derivatives in all examined CE samples with FECD (in all clinical stages of symptomatic FECD and independent of prior cataract surgery). These cells were not present in normal CE. In this study we characterize their morphology, protein expression profile, number, and localization within the CE layer of patients with FECD. Conclusions Circulating fibrocytes and their dendritic derivatives are a new aspect of FECD that deserves further investigation. Because they are known to cause fibrosis in a variety of organs, they may play a similar role in FECD and might be a valuable target for nonsurgical therapy.
Spontaneous baroreflex measures are unable to detect age‐related impairments in cardiac baroreflex function during dynamic exercise in humans

The dynamic relationship between ‘spontaneous’ fluctuations in arterial blood pressure (BP) and heart rate (HR) is increasingly being used to provide an estimate of resting cardiac baroreflex sensitivity. Given the ease of use and clinical utility, spontaneous methods are now also being used to examine cardiac baroreflex sensitivity in distinct subject groups during various laboratory stressors and tasks encountered during daily life, such as physical activity. However, the utility of such spontaneous measures to estimate cardiac baroreflex function during exercise remains unclear, particularly when comparing groups. Therefore, we tested the ability of spontaneous indices to detect age‐related differences in cardiac baroreflex function during dynamic exercise. Beat‐to‐beat HR and BP were measured in eighteen healthy young subjects (24 ± 1 years) and sixteen healthy middle‐aged subjects (59 ± 1 years) at rest and during steady‐state leg cycling. Estimates of spontaneous cardiac baroreflex sensitivity using the sequence technique (GSEQ) and low‐frequency transfer function gain (GTF) were compared with the operating point (GOP) and maximal gain (GMAX) of the full carotid–cardiac baroreflex function curve. At rest GSEQ, GTF, GOP and GMAX were all significantly lower in older subjects. During moderate‐intensity steady‐state exercise no differences were observed in GSEQ and GTF (older 0.26 ± 0.03 beats min−1 mmHg−1versus younger 0.32 ± 0.04 beats min−1 mmHg−1; P > 0.05), whereas GOP and GMAX (older −0.21 ± 0.02 beats min−1 mmHg−1versus younger −0.39 ± 0.03 beats min−1 mmHg−1; P < 0.05) remained lower in older subjects. These data indicate that spontaneous measures of cardiac baroreflex sensitivity alone provide limited information when comparing age‐groups during exercise, which makes genuine differences in baroreflex function difficult to identify.
Topological Cluster Analysis Reveals the Systemic Organization of the Caenorhabditis elegans Connectome

The modular organization of networks of individual neurons interwoven through synapses has not been fully explored due to the incredible complexity of the connectivity architecture. Here we use the modularity-based community detection method for directed, weighted networks to examine hierarchically organized modules in the complete wiring diagram (connectome) of Caenorhabditis elegans (C. elegans) and to investigate their topological properties. Incorporating bilateral symmetry of the network as an important cue for proper cluster assignment, we identified anatomical clusters in the C. elegans connectome, including a body-spanning cluster, which correspond to experimentally identified functional circuits. Moreover, the hierarchical organization of the five clusters explains the systemic cooperation (e.g., mechanosensation, chemosensation, and navigation) that occurs among the structurally segregated biological circuits to produce higher-order complex behaviors.
Object Recognition Techniques in Behavioral Analysis

In this paper we present two methods for automatic quantification of TV consumer attention. The problem has been divided into two main parts: the first one is oriented toward appropriate image analysing techniques which are problem specific and include superposition of several well defined technology for object recognition, movement analysis and tracking, whereas the second part includes more sociological aspects of image analysis interpretation in the context of typical human (kids) behaviour during their, unfortunately time consuming, usual daily activities.
Generalization asymmetry in multivariate cross-classification: When representation A generalizes better to representation B than B to A

In recent years, the use of multivariate cross-classification (MVCC) has grown in popularity as a way to test for the consistency of information in neural patterns of activation across cognitive states. In this approach, a classification algorithm is trained on dataset A and then tested on a different dataset B in order to test for commonalities in the information representation in both datasets. Interestingly, several papers report an asymmetry in the generalization direction: training on A and testing on B returns significantly better decoding results than training on B and testing on A. Whereas several neurocognitive hypotheses have been put forward as an explanation for this phenomenon, none of them has been demonstrated directly. Through simple simulations, we show that asymmetry can arise as soon as two datasets with identical ground truths have a different signal-to-noise ratio (SNR) – generalization is best from the lower SNR to the higher SNR dataset. The extent of the asymmetry is further modulated by the overlap in informative voxels and whether the two datasets have an equal number of informative voxels. These findings demonstrate that the observation of decoding direction asymmetry in MVCC can be explained by simple SNR differences and not necessarily implies complex neurocognitive mechanisms.
Ultrathin nucleoporin FG repeat films and their interaction with nuclear transport receptors

Nico B. Eisele, Steffen Frey, Jacob Piehler, Dirk Görlich, and Ralf P. Richter * 1 Biosurfaces Unit, CIC biomaGUNE, Paseo Miramon 182, 20009 Donostia San Sebastian, Spain 2 Department of Cellular Logistics, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany 3 Department of Biology, University of Osnabrück, Barbarastraße 11, 49076 Osnabrück, Germany 4 Max Planck Institute for Metals Research, Heisenbergstraße 3, 70569 Stuttgart, Germany