Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Cortical Dark/Bright Asymmetries from Natural Image Statistics and Early Visual Transforms

The nervous system has evolved in an environment with structure and predictability. One of the ubiquitous principles of sensory systems is the creation of circuits that capitalize on this predictability. Previous work has identified predictable non-uniformities in the distributions of basic visual features in natural images that are relevant to the encoding tasks of the visual system. Here, we report that the well-established statistical distributions of visual features -- such as visual contrast, spatial scale, and depth -- differ between bright and dark image components. Following this analysis, we go on to trace how these differences in natural images translate into different patterns of cortical input that arise from the separate bright (ON) and dark (OFF) pathways originating in the retina. We use models of these early visual pathways to transform natural images into statistical patterns of cortical input. The models include the receptive fields and non-linear response properties of the magnocellular (M) and parvocellular (P) pathways, with their ON and OFF pathway divisions. The results indicate that there are regularities in visual cortical input beyond those that have previously been appreciated from the direct analysis of natural images. In particular, several dark/bright asymmetries provide a potential account for recently discovered asymmetries in how the brain processes visual features, such as violations of classic energy-type models. On the basis of our analysis, we expect that the dark/bright dichotomy in natural images plays a key role in the generation of both cortical and perceptual asymmetries.
Posterior Cingulate Cortex-Related Co-Activation Patterns: A Resting State fMRI Study in Propofol-Induced Loss of Consciousness

Background Recent studies have been shown that functional connectivity of cerebral areas is not a static phenomenon, but exhibits spontaneous fluctuations over time. There is evidence that fluctuating connectivity is an intrinsic phenomenon of brain dynamics that persists during anesthesia. Lately, point process analysis applied on functional data has revealed that much of the information regarding brain connectivity is contained in a fraction of critical time points of a resting state dataset. In the present study we want to extend this methodology for the investigation of resting state fMRI spatial pattern changes during propofol-induced modulation of consciousness, with the aim of extracting new insights on brain networks consciousness-dependent fluctuations. Methods Resting-state fMRI volumes on 18 healthy subjects were acquired in four clinical states during propofol injection: wakefulness, sedation, unconsciousness, and recovery. The dataset was reduced to a spatio-temporal point process by selecting time points in the Posterior Cingulate Cortex (PCC) at which the signal is higher than a given threshold (i.e., BOLD intensity above 1 standard deviation). Spatial clustering on the PCC time frames extracted was then performed (number of clusters = 8), to obtain 8 different PCC co-activation patterns (CAPs) for each level of consciousness. Results The current analysis shows that the core of the PCC-CAPs throughout consciousness modulation seems to be preserved. Nonetheless, this methodology enables to differentiate region-specific propofol-induced reductions in PCC-CAPs, some of them already present in the functional connectivity literature (e.g., disconnections of the prefrontal cortex, thalamus, auditory cortex), some others new (e.g., reduced co-activation in motor cortex and visual area). Conclusion In conclusion, our results indicate that the employed methodology can help in improving and refining the characterization of local functional changes in the brain associated to propofol-induced modulation of consciousness.
The Advanced Computing Systems Association Design Principles for Tamper-resistant Smartcard Processors Design Principles for Tamper-resistant Smartcard Processors

We describe techniques for extracting protected software and data from smartcard processors. This includes manual microprobing, laser cutting, fo-cused ion-beam manipulation, glitch attacks, and power analysis. Many of these methods have already been used to compromise widely-fielded conditional-access systems, and current smartcards offer little protection against them. We give examples of low-cost protection concepts that make such attacks considerably more difficult.
The impact of intermediate advertising effects on advertising effectiveness and profitability

In this study, we introduce a new approach to measuring the impact of TV advertising on the demand for consumer goods. We combine three data sources (i.e., store-level scanner data, advertising spending data and advertising tracking data) to assess the impact of advertising on demand. We estimate demand by employing a random coefficient logit model that uses aggregate data, in accordance with Berry, Levinsohn & Pakes (1995). We model the effect of advertising on consumer utility by applying an individual goodwill production function that is calibrated based on a firm’s advertising efforts and tracking data. In turn, the tracking data assess individual responses to various measures of intermediate advertising effects which are related to consumers’ product experiences, advertising knowledge and appreciation of advertising. These intermediate advertising effects help to improve researchers’ ability to identify the goodwill production function and to estimate the effects of advertising on sales via goodwill. Our empirical findings show indeed that experience, cognition and the appreciation of advertising significantly influence goodwill production and advertising effectiveness. In other words, these factors determine how a company’s advertising strategy ∗Address: Grueneburgplatz 1, 60323 Frankfurt am Main, Germany, telephone: ++49-69-798-34648, email: dklapper@wiwi.uni-frankfurt.de. †Address: Grueneburgplatz 1, 60323 Frankfurt am Main, Germany, telephone: ++49-69-798-34642, email: zenetti@wiwi.uni-frankfurt.de.
A new fuzzy membership computation method for fuzzy support vector machines

Support vector machine (SVM) considers all data points with the same importance in classification problems, therefore SVM is very sensitive to noisy data or outliers. Current fuzzy approach to two-class SVM introduces a fuzzy membership to each data point in order to reduce the sensitivity of less important data, however computing fuzzy memberships is still a challenge. It has been found that the performance of fuzzy SVM highly depends on the computation of fuzzy memberships, hence in this paper, we propose a new method to compute fuzzy memberships and we also extend the fuzzy approach for two-class SVM to one-class SVM. Experiments performed on a number of popular data sets to evaluation the proposed fuzzy SVMs show promising classification results.
A Graph-Based Evolutionary Algorithm: Genetic Network Programming (GNP) and Its Extension Using Reinforcement Learning

This paper proposes a graph-based evolutionary algorithm called Genetic Network Programming (GNP). Our goal is to develop GNP, which can deal with dynamic environments efficiently and effectively, based on the distinguished expression ability of the graph (network) structure. The characteristics of GNP are as follows. 1) GNP programs are composed of a number of nodes which execute simple judgment/processing, and these nodes are connected by directed links to each other. 2) The graph structure enables GNP to re-use nodes, thus the structure can be very compact. 3) The node transition of GNP is executed according to its node connections without any terminal nodes, thus the past history of the node transition affects the current node to be used and this characteristic works as an implicit memory function. These structural characteristics are useful for dealing with dynamic environments. Furthermore, we propose an extended algorithm, GNP with Reinforcement Learning (GNPRL) which combines evolution and reinforcement learning in order to create effective graph structures and obtain better results in dynamic environments. In this paper, we applied GNP to the problem of determining agents' behavior to evaluate its effectiveness. Tileworld was used as the simulation environment. The results show some advantages for GNP over conventional methods.
Accurate quantification and transformation of arsenic compounds during wet ashing with nitric acid and microwave assisted heating.

Arsenous acid, dimethylarsinic acid (DMA), methylarsonic acid (MA), arsenic acid, arsenobetaine bromide (AB), trimethylarsine oxide (TMAO), arsenocholine iodide (AC), and tetramethylarsonium iodide (TETRA) were heated in a microwave autoclave with nitric acid to 100-300 degrees C. The arsenic compounds in the digests were separated with anion- and cation-exchange chromatography and determined with an inductively coupled plasma mass spectrometer as arsenic-specific detector. Arsenous acid was completely oxidized to arsenic acid at 100 degrees C. For a complete oxidation of MA and DMA to arsenic acid temperatures > 220 degrees C and > 280 degrees C were necessary. AB decomposed to arsenic acid via TMAO. Complete conversion was only obtained after heating the sample for 90 min to 300 degrees C. For a complete conversion of TMAO similar harsh conditions were necessary. AC was already substantially degraded to TMAO, TETRA and two unknown compounds at 100 degrees C. The unknown arsenic compounds were found only in the digests up to 160 degrees C. Quantitative conversion of AC to arsenic acid went also via TMAO. At temperatures above 220 degrees C TETRA started to convert to TMAO, which then was further converted to arsenic acid. To investigate whether the results obtained for the arsenic standards are transferable to real samples, the certified reference material DORM-2 was also heated in nitric acid with variable digestion temperatures and times. For an almost complete conversion of the AB present in DORM-2 90 min at 300 degrees C were necessary. Total organic carbon (TOC) was less < 0.2% when DORM-2 was heated at temperatures > or = 260 degrees C for 60 min. UV photo-oxidation of DORM-2 was investigated as an alternative sample decomposition. Only 6% of AB was converted to arsenic acid when DORM-2 was irradiated for 2 h at 1000 W. In contrast to microwave heating substantial amounts of MA were observed as degradation product.
On the Need for Rectification of Surface Emg

TO THE EDITOR: The electromyogram (EMG) as an indirect measure of motor unit activity has proved invaluable in motor control studies. Increasingly, the application of frequency domain techniques to EMG signals has provided important insight into the structure and function of the human motor system. In a recent publication Neto and Christou (2010) claimed that rectification of the EMG impairs identification of oscillatory input to the muscle. This is a controversial claim since it is at odds with the prepro-cessing step of EMG rectification adopted in a number of significant studies examining oscillations in the motor system. If Neto and Christou (2010) are correct, then the findings of earlier studies are drawn into question. The contribution of Neto and Christou is important in making us think about what information is contained in an EMG signal and how best to extract it. Oscillatory drive to human motoneurons during isometric contraction was first identified by Farmer et al. (1993). Using single motor unit recordings they demonstrated that the firing times of individual motor units are modulated in two distinct frequency bands, one of which (16 –32 Hz) was hypothesized to reflect oscillatory activity in descending corticospinal pathways. The analysis used by Farmer et al. (1993) was based on a framework in which individual motor units are treated as distinct events or pulses. The finite Fourier transform is used to generate a statistical description that provides a measure of the correlation between paired motor unit firing times. This type of treatment is part of a broader approach, in which the Fourier transform is viewed as a statistical quantity (Brillinger 1983) and the focus is on providing a description of stochastic data; in the case of motor unit activity, the focus is on rhythmic modulation of firing times. An alternative use for the Fourier transform is accurate reconstruction of a signal using Fourier synthesis. This deterministic approach is used, for example, in Fourier synthesis of audio signals using a sum of sines model. Recent studies of oscillatory corticospinal interactions have used surface EMG recordings as an indicator of motor unit activity. An important question that arises is how to treat the surface EMG to extract information related to motor unit firing; in this case the firing times will be across a population of motor units. A statistical approach can be adopted using the finite Fourier transform to construct spectral and related parameters (coherence, phase, …
Syndrome Diagnosis: Human Intuition or Machine Intelligence?

The aim of this study was to investigate whether artificial intelligence methods can represent objective methods that are essential in syndrome diagnosis. Most syndromes have no external criterion standard of diagnosis. The predictive value of a clinical sign used in diagnosis is dependent on the prior probability of the syndrome diagnosis. Clinicians often misjudge the probabilities involved. Syndromology needs objective methods to ensure diagnostic consistency, and take prior probabilities into account. We applied two basic artificial intelligence methods to a database of machine-generated patients - a ‘vector method’ and a set method. As reference methods we ran an ID3 algorithm, a cluster analysis and a naive Bayes’ calculation on the same patient series. The overall diagnostic error rate for the the vector algorithm was 0.93%, and for the ID3 0.97%. For the clinical signs found by the set method, the predictive values varied between 0.71 and 1.0. The artificial intelligence methods that we used, proved simple, robust and powerful, and represent objective diagnostic methods.
A Comparative Analysis and Review of lysyl Residues Affected by Posttranslational Modifications

Post-translational modification is the most common mechanism of regulating protein function. If phosphorylation is considered a key event in many signal transduction pathways, other modifications must be considered as well. In particular the side chain of lysine residues is a target of different modifications; notably acetylation, methylation, ubiquitylation, sumoylation, neddylation, etc. Mass spectrometry approaches combining highly sensitive instruments and specific enrichment strategies have enabled the identification of modified sites on a large scale. Here we make a comparative analysis of the most representative lysine modifications (ubiquitylation, acetylation, sumoylation and methylation) identified in the human proteome. This review focuses on conserved amino acids, secondary structures preference, subcellular localization of modified proteins, and signaling pathways where these modifications are implicated. We discuss specific differences and similarities between these modifications, characteristics of the crosstalk among lysine post translational modifications, and single nucleotide polymorphisms that could influence lysine post-translational modifications in humans.
A hybrid TIM-NOMA scheme for the Broadcast Channel

Future mobile communication networks will require enhanced network efficiency and reduced system overhead. Research on Blind Interference Alignment and Topological Interference Management (TIM) has shown that optimal Degrees of Freedom can be achieved, in the absence of Channel State Information at the transmitters. Moreover, the recently emerged Non-Orthogonal Multiple Access (NOMA) scheme suggests a different multiple access approach, compared to the orthogonal methods employed in 4G, resulting in high capacity gains. Our contribution is a hybrid TIM-NOMA scheme in K -user cells, where users are divided into T groups. By superimposing users in the power domain, we introduce a two-stage decoding process, managing “inter-group” interference based on the TIM principles, and “intra-group” interference based on Successful Interference Cancellation, as proposed by NOMA. We show that the hybrid scheme can improve the sum rate by at least 100% compared to Time Division Multiple Access, for high SNR values.
Catalytic Mechanism of Sep-tRNA:Cys-tRNA Synthase

Background: SepCysS catalyzes the conversion of tRNA-bound O-phosphoserine to Cys. Results: Three Cys residues are essential for SepCysS activity, and two of them form disulfide and persulfide intermediates. Conclusion: SepCysS transfers sulfur through generating disulfide and persulfide enzyme adducts. Significance: Elucidation of the sulfur transfer mechanism of SepCysS is crucial for understanding the tRNA-dependent Cys biosynthesis and sulfur metabolism in methanogens. Sep-tRNA:Cys-tRNA synthase (SepCysS) catalyzes the sulfhydrylation of tRNA-bound O-phosphoserine (Sep) to form cysteinyl-tRNACys (Cys-tRNACys) in methanogens that lack the canonical cysteinyl-tRNA synthetase (CysRS). A crystal structure of the Archaeoglobus fulgidus SepCysS apoenzyme provides information on the binding of the pyridoxal phosphate cofactor as well as on amino acid residues that may be involved in substrate binding. However, the mechanism of sulfur transfer to form cysteine was not known. Using an in vivo Escherichia coli complementation assay, we showed that all three highly conserved Cys residues in SepCysS (Cys64, Cys67, and Cys272 in the Methanocaldococcus jannaschii enzyme) are essential for the sulfhydrylation reaction in vivo. Biochemical and mass spectrometric analysis demonstrated that Cys64 and Cys67 form a disulfide linkage and carry a sulfane sulfur in a portion of the enzyme. These results suggest that a persulfide group (containing a sulfane sulfur) is the proximal sulfur donor for cysteine biosynthesis. The presence of Cys272 increased the amount of sulfane sulfur in SepCysS by 3-fold, suggesting that this Cys residue facilitates the generation of the persulfide group. Based upon these findings, we propose for SepCysS a sulfur relay mechanism that recruits both disulfide and persulfide intermediates.
Axial Differences in Community Structure ofCrenarchaeota and Euryarchaeota in the Highly Compartmentalized Gut of the Soil-Feeding TermiteCubitermes orthognathus

ABSTRACT Methanogenesis represents an important electron sink reaction in the hindgut of soil-feeding termites. This is the first comprehensive analysis of the archaeal community structure within the highly compartmentalized intestinal tract of a humivorous insect, combining clonal analysis and terminal restriction fragment (T-RF) length polymorphism (T-RFLP) fingerprinting of the archaeal communities in the different gut compartments of Cubitermes orthognathus. We found that the morphological and physicochemical heterogeneity of the gut is reflected in a large phylogenetic diversity and pronounced axial differences in the composition of the archaeal gut microbiota, notably among those clones or ribotypes that could be assigned to methanogenic taxa. Comparative analysis of the relative frequencies of different archaeal lineages among the small-subunit rRNA gene (SSU rDNA) clones and their corresponding T-RF indicated that the archaeal community in the anterior, extremely alkaline hindgut compartment (P1) consists mainly of members of theMethanosarcinaceae, whereasMethanobacteriaceae andMethanomicrobiales predominate in the subsequent, more posterior compartments (P3/4a and P4b). The relative abundance ofThermoplasmales increased towards the rectum (P5). SSU rDNA sequences representing Crenarchaeota, which have not yet been reported to occur in the intestinal tracts of arthropods, were detected in all gut sections. We discuss how the spatial distribution of methanogenic populations may be linked to axial heterogeneity in the physicochemical gut conditions and to functional adaptations to their respective ecological niches.
Competence for Chemical Reprogramming of Sexual Fate Correlates with an Intersexual Molecular Signature in Caenorhabditis elegans

In multicellular organisms, genetic programs guide cells to adopt cell fates as tissues are formed during development, maintained in adults, and repaired after injury. Here we explore how a small molecule in the environment can switch a genetic program from one fate to another. Wild-type Caenorhabditis elegans XX adult hermaphrodites make oocytes continuously, but certain mutant XX adults make sperm instead in an otherwise hermaphrodite soma. Thus, puf-8; lip-1 XX adults make only sperm, but they can be switched from sperm to oocyte production by treatment with a small-molecule MEK inhibitor. To ask whether this chemical reprogramming is common, we tested six XX sperm-only mutants, but found only one other capable of cell fate switching, fbf-1; lip-1. Therefore, reprogramming competence relies on genotype, with only certain mutants capable of responding to the MEK inhibitor with a cell fate change. To gain insight into the molecular basis of competence for chemical reprogramming, we compared polyadenylated transcriptomes of competent and noncompetent XX sperm-only mutants in the absence of the MEK inhibitor and hence in the absence of cell fate reprogramming. Despite their cellular production of sperm, competent mutants were enriched for oogenic messenger RNAs relative to mutants lacking competence for chemical reprogramming. In addition, competent mutants expressed the oocyte-specific protein RME-2, whereas those lacking competence did not. Therefore, mutants competent for reprogramming possess an intersexual molecular profile at both RNA and protein levels. We suggest that this intersexual molecular signature is diagnostic of an intermediate network state that poises the germline tissue for changing its cellular fate in response to environmental cues.
Contribution of PPi-Hydrolyzing Function of Vacuolar H+-Pyrophosphatase in Vegetative Growth of Arabidopsis: Evidenced by Expression of Uncoupling Mutated Enzymes

The vacuolar-type H+-pyrophosphatase (H+-PPase) catalyzes a coupled reaction of pyrophosphate (PPi) hydrolysis and active proton translocation across the tonoplast. Overexpression of H+-PPase improves growth in various plant species, and loss-of-function mutants (fugu5s) of H+-PPase in Arabidopsis thaliana have post-germinative developmental defects. Here, to further clarify the physiological significance of this important enzyme, we newly generated three varieties of H+-PPase overexpressing lines with different levels of activity that we analyzed together with the loss-of-function mutant fugu5-3. The H+-PPase overexpressors exhibited enhanced activity of H+-PPase during vegetative growth, but no change in the activity of vacuolar H+-ATPase. Overexpressors with high enzymatic activity grew more vigorously with fresh weight increased by more than 24 and 44%, compared to the wild type and fugu5-3, respectively. Consistently, the overexpressors had larger rosette leaves and nearly 30% more cells in leaves than the wild type. When uncoupling mutated variants of H+-PPase, that could hydrolyze PPi but could not translocate protons, were introduced into the fugu5-3 mutant background, shoot growth defects recovered to the same levels as when a normal H+-PPase was introduced. Taken together, our findings clearly demonstrate that additional expression of H+-PPase improves plant growth by increasing cell number, predominantly as a consequence of the PPi-hydrolyzing activity of the enzyme.
A rot Mutation Restores Parental Virulence to an agr-Null Staphylococcus aureus Strain in a Rabbit Model of Endocarditis

ABSTRACT Mutations in rot restore in vitro toxin production to agr-negative strains of Staphylococcus aureus. We show that a rot mutation returns wild-type virulence to an agr mutant, as measured in experimental endocarditis infections by target organ bacterial counts. Implications of our data are discussed in terms of agr antagonist strategies.