Miracle-dz/UniFAR-FTUs huggingface dataset:
Individual Differences in Reward Drive Predict Neural Responses to Images of Food

A network of interconnected brain regions, including orbitofrontal, ventral striatal, amygdala, and midbrain areas, has been widely implicated in a number of aspects of food reward. However, in humans, sensitivity to reward can vary significantly from one person to the next. Individuals high in this trait experience more frequent and intense food cravings and are more likely to be overweight or develop eating disorders associated with excessive food intake. Using functional magnetic resonance imaging, we report that individual variation in trait reward sensitivity (as measured by the Behavioral Activation Scale) is highly correlated with activation to images of appetizing foods (e.g., chocolate cake, pizza) in a fronto–striatal–amygdala–midbrain network. Our findings demonstrate that there is considerable personality-linked variability in the neural response to food cues in healthy participants and provide important insight into the neurobiological factors underlying vulnerability to certain eating problems (e.g., hyperphagic obesity).
The Analytic Moment Doesn't Fit Analytic “Technique”: Commentary on Tony Bass's “When the Frame Doesn't Fit the Picture”

Tony Bass in his groundbreaking contribution to the analytic literature argues cogently that the frame remains an essential reference point throughout any psychoanalysis, a statement about which he and I are in agreement. He also argues that for a frame to be therapeutically useful it must be flexible enough to allow negotiation of enactments and their working through in an intersubjective field, another point about which we are in complete accord. He and I each hold a self-state perspective that informs and enriches our clinical work. Where we diverge slightly is in how this perspective shapes the way we think about the nature of the “frame” as it applies to the dissociated self-states of patient and analyst that emerge and engage each other subsymbolically as an ongoing aspect of the work, often in quite bewildering and sometimes confounding ways. This paper speaks to a number of issues that I hope will bring into relief some of the points of contrast that do exist, while underlining the core commonality in our thinking and clinical sensibility that unites us. This paper expands my discussion of Tony Bass's January 13, 2007 presentation at “Reframing the Frame: Creativity and Discipline in Relational Psychoanalysis,” a conference sponsored by the Stephen A. Mitchell Center for Relational Psychoanalysis held at The New School for Social Research, New York City. Dr. Bass's paper can be found in Psychoanalytic Dialogues (2007), Vol. 17, No. 1.
CYCLE SLIPS IN THE PLL SYNCHRONIZER WITH LIMITER PHASE DETECTOR IN THE PRESENCE OF NOISE AND COCHANNEL INTERFERENCE

The paper addresses the cycle slip performance analysis of the phase-locked loop (PLL) synchronizer with limiter phase detector in the presence of noise and cochannel interference. Conditioned on the interference phase, an equivalent loop model of the limiter phase detector is developed under this situation. The conditional cycle slip rate is obtained by adapting a recent formula, and the mean cycle slip rate is reported for the uniformly distributed interference phase. It is shown that the cochannel interference enhances the mean cycle slip rate by reducing the relevant effective loop signal-to-noise ratio. slip statistics of the considered synchronizer is compared to that of a first-order loop with the multiplier phase detector.
Large-scale reconstruction and phylogenetic analysis of metabolic environments

The topology of metabolic networks may provide important insights not only into the metabolic capacity of species, but also into the habitats in which they evolved. Here we introduce the concept of a metabolic network's “seed set”—the set of compounds that, based on the network topology, are exogenously acquired—and provide a methodological framework to computationally infer the seed set of a given network. Such seed sets form ecological “interfaces” between metabolic networks and their surroundings, approximating the effective biochemical environment of each species. Analyzing the metabolic networks of 478 species and identifying the seed set of each species, we present a comprehensive large-scale reconstruction of such predicted metabolic environments. The seed sets' composition significantly correlates with several basic properties characterizing the species' environments and agrees with biological observations concerning major adaptations. Species whose environments are highly predictable (e.g., obligate parasites) tend to have smaller seed sets than species living in variable environments. Phylogenetic analysis of the seed sets reveals the complex dynamics governing gain and loss of seeds across the phylogenetic tree and the process of transition between seed and non-seed compounds. Our findings suggest that the seed state is transient and that seeds tend either to be dropped completely from the network or to become non-seed compounds relatively fast. The seed sets also permit a successful reconstruction of a phylogenetic tree of life. The “reverse ecology” approach presented lays the foundations for studying the evolutionary interplay between organisms and their habitats on a large scale.
MoO3−x-based bipolar switching ReRAM fabricated by atomic layer deposition

MoO3−x-based Transition Metal Oxide Resistive Random Access Memory (ReRAM) devices were fabricated using atomic layer deposition, and their resistance-switching behaviors were investigated. The bipolar phenomenon was observed when 100-nm-thick Au were deposited by electron beam evaporation as bottom electrode (BE) and top electrode (TE), respectively. The proper electrical properties, such as excellent retention characteristic, low current and voltage operation are obtained with an Au/MoO3−x/Au/Si structure.
Student conceptions of peer-assisted learning

This article reports on a programme in which peer-assisted learning (PAL) was combined with case-based learning (CBL) in a second-year radiologic biology unit of study. Our aim is to explore evidence of whether PAL supported the development of qualitative conceptions of learning. The programme involved students in small PAL groups preparing and offering a tutorial based on a case study for the class (large PAL group). The small PAL group assessed the learning of the large PAL group, while the large group gave feedback to the small group. Small groups attended a debriefing session following the tutorial. A six-category framework related to conceptions of learning was developed to guide qualitative analysis of data derived from a student questionnaire, the debriefing sessions and a final focus group. Data analysis indicated some evidence of quantitative conceptions of learning (particularly early in the programme), and showed that PAL played a role in developing students’ qualitative conceptions of learning, particularly through the social and affective processes involved and opportunities for developing metacognitive knowledge. The programme contributed to ‘deep’ processing as students learnt from and with each other. Concurrently, students’ feelings of responsibility to their peers increased their responsibility for their own learning. The PAL approach that was used provides a basis for further exploration of the role of peers in developing students’ conceptions of learning.
Electronic Reprint Biological Crystallography Substructure Search Procedures for Macromolecular Structures Biological Crystallography Substructure Search Procedures for Macromolecular Structures

Author(s) of this paper may load this reprint on their own web site provided that this cover page is retained. Republication of this article or its storage in electronic databases or the like is not permitted without prior permission in writing from the IUCr. This paper accompanies a lecture given at the 2003 CCP4 Study Weekend on experimental phasing. The ®rst part is an overview of the fundamentals of Patterson methods and direct methods with the audience of the CCP4 Study Weekend in mind. In the second part, a new hybrid substructure search is outlined.
A Convergence Proof for Ant Colony Algorithm

A general framework for solving combinatorial optimization problems heuristically by the ant system approach is developed. Based on the two different conditions, some convergence properties for ant colony system (ACS) are presented. The global searching and convergence ability are improved by adaptively changing the lower pheromone bound. It is shown that ACS is guaranteed to find an optimal solution with probability 1
Goal Modelling and Reasoning in Tropos

We overview on-going research on modelling and analyzing goals in requirements engineering. Specifically, we introduce and discuss a qualitative model for goals, which – among other things -- can cope with qualitative relationships and inconsistencies among goals. We then present an axiomatization of the model and propose sound and complete algorithms for forward and backward reasoning. In particular, given a goal model and labels for some of its goal elements, forward reasoning focuses on how to propagate these labels forward, towards root goals. Backward reasoning, on the other hand, focuses on finding a label assignment for leaf nodes of a goal graph that collectively satisfy/deny all root goals. Assuming that the satisfaction/denial of any leaf goal requires some unit cost, we also address the problem of finding a minimum cost label assignment to leaf goals for satisfying/denying all root goals of a goal graph. Both problems are solved by reducing them to the problems of satisfiability (SAT) and minimum-cost satisfiability (minimum-cost SAT) for Boolean formulas. The proposed algorithms have been implemented and are available through a tool named the GR-tool. To illustrate the whole framework, we include a simple case study adopted from the literature where a goal model is built and then analyzed.
A study on class-specifically discounted belief for ensemble classifiers

Ensemble classifiers are known to generally perform better than their constituent classifiers. Whereas a lot of work has been focusing on the generation of classifiers for ensembles, much less attention has been given to the fusion of individual classifier outputs. One approach to fuse the outputs is to apply Shaferpsilas theory of evidence, which provides a flexible framework for expressing and fusing beliefs. However, representing and fusing beliefs is non-trivial since it can be performed in a multitude of ways within the evidential framework. In a previous article, we compared different evidential combination rules for ensemble fusion. The study involved a single belief representation which involved discounting (i.e., weighting) the classifier outputs with classifier reliability. The classifier reliability was interpreted as the classifierpsilas estimated accuracy, i.e., the percentage of correctly classified examples. However, classifiers may have different performance for different classes and in this work we assign the reliability of a classifier output depending on the class-specific reliability of the classifier. Using 27 UCI datasets, we compare the two different ways of expressing beliefs and some evidential combination rules. The result of the study indicates that there is indeed an advantage of utilizing class-specific reliability compared to accuracy in an evidential framework for combining classifiers in the ensemble design considered.
Loss of the Mouse Ortholog of the Shwachman-Diamond Syndrome Gene (Sbds) Results in Early Embryonic Lethality

ABSTRACT Mutations in SBDS are responsible for Shwachman-Diamond syndrome (SDS), a disorder with clinical features of exocrine pancreatic insufficiency, bone marrow failure, and skeletal abnormalities. SBDS is a highly conserved protein whose function remains largely unknown. We identified and investigated the expression pattern of the murine ortholog. Variation in levels was observed, but Sbds was found to be expressed in all embryonic stages and most adult tissues. Higher expression levels were associated with rapid proliferation. A targeted disruption of Sbds was generated in order to understand the consequences of its loss in an in vivo model. Consistent with recessive disease inheritance for SDS, Sbds+/− mice have normal phenotypes, indistinguishable from those of their wild-type littermates. However, the development of Sbds−/− embryos arrests prior to embryonic day 6.5, with muted epiblast formation leading to early lethality. This finding is consistent with the absence of patients who are homozygous for early truncating mutations. Sbds is an essential gene for early mammalian development, with an expression pattern consistent with a critical role in cell proliferation.
Using critics to analyze evolving architectures

Software architectures evolve as the result of numerous, interrelated design decisions. At any point in an architecture’s evolution, current decisions can critically affect alternatives at later stages, and each decision has the potential of requiring previous decisions to be reconsidered. Analysis techniques that provide feedback only after “complete” sequences of design decisions have been made do not directly support the evolutionary nature of the architecture design process. In this paper we present an approach to architectural analysis that more closely supports evolution by providing feedback as design decisions are made.
Modulation of Integrin Activity is Vital for Morphogenesis

Cells can vary their adhesive properties by modulating the affinity of integrin receptors. The activation and inactivation of integrins by inside-out mechanisms acting on the cytoplasmic domains of the integrin subunits has been demonstrated in platelets, lymphocytes, and keratinocytes. We show that in the embryo, normal morphogenesis requires the α subunit cytoplasmic domain to control integrin adhesion at the right times and places. PS2 integrin (αPS2βPS) adhesion is normally restricted to the muscle termini, where it is required for attaching the muscles to the ends of other muscles and to specialized epidermal cells. Replacing the wild-type αPS2 with mutant forms containing cytoplasmic domain deletions results in the rescue of the majority of defects associated with the absence of the αPS2 subunit, however, the mutant PS2 integrins are excessively active. Muscles containing these mutant integrins make extra muscle attachments at aberrant positions on the muscle surface, disrupting the muscle pattern and causing embryonic lethality. A gain- of-function phenotype is not observed in the visceral mesoderm, showing that regulation of integrin activity is tissue-specific. These results suggest that the αPS2 subunit cytoplasmic domain is required for inside-out regulation of integrin affinity, as has been seen with the integrin αIIbβ3.
Monitoring Reactions of Nitric Oxide with Peptides and Proteins by Electrospray Ionization-Mass Spectrometry (*)

Recent studies have demonstrated the biological importance of the interaction of nitric oxide (NO) with proteins. Protein-associated targets of NO include heme, Cys, and Tyr. Electrospray ionization-mass spectrometry was used to monitor the results of exposure of model peptides and an enzyme to NO under different conditions and thus addressed aspects of NO-protein interactions. The molecular mass of a decapeptide containing a single Cys residue increased by 29 Da upon treatment with NO under aerobic and acidic conditions, consistent with the substitution of one NO moiety. The mass of reduced somatostatin, a peptide containing two Cys residues, increased by 58 Da, consistent with the substitution of two NO moieties. These substitutions were prevented by pretreatment of the peptides with Nethylmaleimide. The strength of the nitrosothiol bond was examined by varying the amount of energy applied to the peptide ions and indicated a labile species. Cys residues were very rapidly nitrosated, while other reactions were observed to occur at much slower rates. These include the further oxidation of nitrosothiol to sulfonic acid and nitration of Tyr. Peptides treated with NO at physiological pH were observed to undergo dimerization as well as nitrosation. These studies were extended to the enzyme p21, whose activity has been postulated to be modulated by nitrosothiol formation, and revealed the formation of a single nitrosothiol on p21 upon NO treatment. These data suggest that electrospray ionization-mass spectrometry allows for quantitation and characterization of nitrosothiol bonds in peptides and proteins.
Molecular Diversity of Lactobacillus spp. and Other Lactic Acid Bacteria in the Human Intestine as Determined by Specific Amplification of 16S Ribosomal DNA

ABSTRACT A Lactobacillus group-specific PCR primer, S-G-Lab-0677-a-A-17, was developed to selectively amplify 16S ribosomal DNA (rDNA) from lactobacilli and related lactic acid bacteria, including members of the genera Leuconostoc, Pediococcus, and Weissella. Amplicons generated by PCR from a variety of gastrointestinal (GI) tract samples, including those originating from feces and cecum, resulted predominantly in Lactobacillus-like sequences, of which ca. 28% were most similar to the 16S rDNA of Lactobacillus ruminis. Moreover, four sequences of Leuconostoc species were retrieved that, so far, have only been detected in environments other than the GI tract, such as fermented food products. The validity of the primer was further demonstrated by using Lactobacillus-specific PCR and denaturing gradient gel electrophoresis (DGGE) of the 16S rDNA amplicons of fecal and cecal origin from different age groups. The stability of the GI-tract bacterial community in different age groups over various time periods was studied. The Lactobacillus community in three adults over a 2-year period showed variation in composition and stability depending on the individual, while successional change of the Lactobacillus community was observed during the first 5 months of an infant’s life. Furthermore, the specific PCR and DGGE approach was tested to study the retention in fecal samples of a Lactobacillus strain administered during a clinical trial. In conclusion, the combination of specific PCR and DGGE analysis of 16S rDNA amplicons allows the diversity of important groups of bacteria that are present in low numbers in specific ecosystems to be characterized, such as the lactobacilli in the human GI tract.
Static graph challenge on GPU

This paper presents the details of a CUDA implementation of the Subgraph Isomorphism Graph Challenge, a new effort aimed at driving progress in the graph analytics field. challenge consists of two graph analytics: triangle counting and k-truss. We present our CUDA implementation of the graph triangle counting operation and of the k-truss subgraph decomposition. Both implementations share the same codebase taking advantage of a set intersection operation implemented via bitmaps. The analytics are implemented in four kernels optimized for different types of graphs. At runtime, lightweight heuristics are used to select the kernel to run based on the specific graph taken as input.
A New Semi-Supervised Multi-Surface Proximal Support Vector Machine Model

The currently proposed Multi-surface Proximal Support Vector Machine Classification via Generalized Eigenvalues (GEPSVM) is an effective method on 2-class problem, which only needs to proximally solve two not parallel planes corresponding to each of two data sets, and the planes can be easily obtained by solving generalized eigenvalues. However, the not parallel planes may not be accurately determined when the labeled samples is not sufficient. To overcome this disadvantage, in this paper, we introduce a new semi-supervised multi-surface proximal support machine model, which can effectively utilize the labeled and unlabeled samples by incorporating the manifold regularization strategy. Based on this model, we propose a linear semi-supervised multi-surface classification algorithm called SGEPSVM. Further, we develop a non-linear classifier by using kernel trick called SKGEPSVM. Experiments on 8 benchmark data sets show the effectiveness of our algorithms.
Online Passive-Aggressive Algorithms for Non-Negative Matrix Factorization and Completion

Stochastic Gradient Descent (SGD) is a popular online algorithm for large-scale matrix factorization. However, SGD can often be di cult to use for practitioners, because its performance is very sensitive to the choice of the learning rate parameter. In this paper, we present non-negative passiveaggressive (NN-PA), a family of online algorithms for non-negative matrix factorization (NMF). Our algorithms are scalable, easy to implement and do not require the tedious tuning of a learning rate parameter. We demonstrate the e↵ectiveness of our algorithms on three large-scale matrix completion problems and analyze them in the regret bound model.
Optimizing Dual-Core Execution for Power Efficiency and Transient-Fault Recovery

Dual-core execution (DCE) is an execution paradigm proposed to utilize chip multiprocessors to improve the performance of single-threaded applications. Previous research has shown that DCE provides a complexity-effective approach to building a highly scalable instruction window and achieves significant latency-hiding capabilities. In this paper, we propose to optimize DCE for power efficiency and/or transient-fault recovery. In DCE, a program is first processed (speculatively) in the front processor and then reexecuted by the back processor. Such reexecution is the key to eliminating the centralized structures that are normally associated with very large instruction windows. In this paper, we exploit the computational redundancy in DCE to improve its reliability and its power efficiency. The main contributions include: 1) DCE-based redundancy checking for transient-fault tolerance and a complexity-effective approach to achieving full redundancy coverage and 2) novel techniques to improve the power/energy efficiency of DCE-based execution paradigms. Our experimental results demonstrate that, with the proposed simple techniques, the optimized DCE can effectively achieve transient-fault tolerance or significant performance enhancement in a power/energy-efficient way. Compared to the original DCE, the optimized DCE has similar speedups (34 percent on average) over single-core processors while reducing the energy overhead from 93 percent to 31 percent.