Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating functional network inference using simulations of complex biological systems

MOTIVATION Although many network inference algorithms have been presented in the bioinformatics literature, no suitable approach has been formulated for evaluating their effectiveness at recovering models of complex biological systems from limited data. To overcome this limitation, we propose an approach to evaluate network inference algorithms according to their ability to recover a complex functional network from biologically reasonable simulated data. RESULTS We designed a simulator to generate data representing a complex biological system at multiple levels of organization: behaviour, neural anatomy, brain electrophysiology, and gene expression of songbirds. About 90% of the simulated variables are unregulated by other variables in the system and are included simply as distracters. We sampled the simulated data at intervals as one would sample from a biological system in practice, and then used the sampled data to evaluate the effectiveness of an algorithm we developed for functional network inference. We found that our algorithm is highly effective at recovering the functional network structure of the simulated system-including the irrelevance of unregulated variables-from sampled data alone. To assess the reproducibility of these results, we tested our inference algorithm on 50 separately simulated sets of data and it consistently recovered almost perfectly the complex functional network structure underlying the simulated data. To our knowledge, this is the first approach for evaluating the effectiveness of functional network inference algorithms at recovering models from limited data. Our simulation approach also enables researchers a priori to design experiments and data-collection protocols that are amenable to functional network inference.
Connecting a Human Limb to an Exoskeleton

When developing robotic exoskeletons, the design of physical connections between the device and the human limb to which it is connected is a crucial problem. Indeed, using an embedment at each connection point leads to uncontrollable forces at the interaction port, induced by hyperstaticity. In practice, these forces may be large because in general the human limb kinematics and the exoskeleton kinematics differ. To cope with hyperstaticity, the literature suggests the addition of passive mechanisms inside the mechanism loops. However, empirical solutions that are proposed so far lack proper analysis and generality. In this paper, we study the general problem of connecting two similar kinematic chains through multiple passive mechanisms. We derive a constructive method that allows the determination of all the possible distributions of freed degrees of freedom across different fixation mechanisms. It also provides formal proofs of global isostaticity. Practical usefulness is illustrated through two examples with conclusive experimental results: a preliminary study made on a manikin with an arm exoskeleton controlling the movement (passive mode) and a larger campaign on ten healthy subjects performing pointing tasks with a transparent robot (active mode).
Managing clusters among distributed dynamic environments

We propose a fully decentralized algorithm that constructs and maintains clusters over a network. This algorithm maintains a stable size within the clusters among a network subject to frequent connection and disconnection. We use the notion of a circulating token that collects data (called a circulating word). This token moves according to a random walk scheme. The aim of the algorithm is to adapt solutions that use random walks and circulating words to large scale networks.
Power and Self Image through Transitivity and Modality: Systemic Functional Linguistic Approach

Abstract: The aim of this research was to investigate the transitivity and the modality used by the president of Indonesia “Jokowi”. I wanted to find out the power and the image of the president through the analysis of his utterances and answered the relation between social and context. I analyzed two speeches. I took the speech texts from Rappler.com. It was an online news site. I analyzed the data by using Halliday’s theory of Systemic Functional Linguistics. There were three findings in this research namely: 1) the word ‘say’ as the verbal process could be also as the example for behavioral process but it needed more explanation that it was verbal in action; 2) The most common process types used by Jokowi were material process, relational process, and mental process. 3) The biggest part of speech 1 and speech 2 were in the level of median politeness.
Secretory Bulk Flow of Soluble Proteins Is Efficient and COPII Dependent

COPII-coated vesicles, first identified in yeast and later characterized in mammalian cells, mediate protein export from the endoplasmic reticulum (ER) to the Golgi apparatus within the secretory pathway. In these organisms, the mechanism of vesicle formation is well understood, but the process of soluble cargo sorting has yet to be resolved. In plants, functional complements of the COPII-dependent protein traffic machinery were identified almost a decade ago, but the selectivity of the ER export process has been subject to considerable debate. To study the selectivity of COPII-dependent protein traffic in plants, we have developed an in vivo assay in which COPII vesicle transport is disrupted at two distinct steps in the pathway. First, overexpression of the Sar1p-specific guanosine nucleotide exchange factor Sec12p was shown to result in the titration of the GTPase Sar1p, which is essential for COPII-coated vesicle formation. A second method to disrupt COPII transport at a later step in the pathway was based on coexpression of a dominant negative mutant of Sar1p (H74L), which is thought to interfere with the uncoating and subsequent membrane fusion of the vesicles because of the lack of GTPase activity. A quantitative assay to measure ER export under these conditions was achieved using the natural secretory protein barley α-amylase and a modified version carrying an ER retention motif. Most importantly, the manipulation of COPII transport in vivo using either of the two approaches allowed us to demonstrate that export of the ER resident protein calreticulin or the bulk flow marker phosphinothricin acetyl transferase is COPII dependent and occurs at a much higher rate than estimated previously. We also show that the instability of these proteins in post-ER compartments prevents the detection of the true rate of bulk flow using a standard secretion assay. The differences between the data on COPII transport obtained from these in vivo experiments and in vitro experiments conducted previously using yeast components are discussed.
Overcoming control challenges in the Artificial Pancreas

This study compares recent Control Algorithms of Artificial Pancreas; Proportional-Integral-Derivative (PID) and Model Predictive Control (MPC). PID controller is applicable to many controls problem, often performs satisfactorily and eliminates the offset. However, it can perform poorly in some applications, does not in general provide optimal control and is unstable with integral control. On the other hand, MPC is able to deal with large multivariable constraints and can be used for non-minimal phase. Then this study focus on two issues, the first one is the nonlinearity of the control problem, and it is demonstrated how this can be tackled via asymmetric objective functions, the proposed MPC strategy employs an asymmetric, state-dependent objective function that leads to a nonlinear optimization problem, The second issue is to propose a velocity-weighting mechanism, within an MPC problem's cost function, that facilitates penalizing predicted hyperglycemic blood-glucose excursions based on the predicted blood-glucose levels' rates of change.
Intergenerational Transmission of Sociability: The Mediating Role of Maternal Competence and Maternal Child-Centrism

This study focuses on the psychological mechanisms of mothering involved in the association of maternal sociability and the sociability of their preschool children. In particular, it is posited that this association is mediated by two maternal psychological conceptualizations: (a) perception of ability to take on the role of motherhood (i.e., maternal competence) and (b) perception of distribution of resources between child and self (i.e., maternal child-centrism). Participants included 320 Jewish–Israeli mothers of preschool children (age 4-6 years) who completed self-reported questionnaires dealing with social relationships, child sociability, maternal competence, and maternal child-centrism. Multiple regression analyses confirmed the mediating effect of maternal competence and child-centrism as well as the association between the mother’s sociability and child sociability. These findings are discussed in light of social capital theory and contemporary parenting styles. Professionals working with families should be aware of the impact of social networks on maternal perception and their influence on children.
ABELIAN KERNELS, SOLVABLE MONOIDS AND THE ABELIAN KERNEL LENGTH OF A FINITE MONOID

In this paper we do not make a clear distinction between what is introduction and preliminaries. In fact, we have decided to put it all in a single section which is divided into 3 subsections. The first, concerning kernels of finite monoids and related properties, should mainly serve as a general motivation for the study that we will do later with some particular classes of monoids. In the second subsection are introduced those classes of monoids.
Effect of a Comprehensive Health Care Program by Korean Medicine Doctors on Medical Care Utilization for Common Infectious Diseases in Child-Care Centers

As the role of traditional medicine in community health improvement increases, a comprehensive health care program for infectious diseases management in child-care centers by Korean medicine doctors was developed. The purpose of this study is to evaluate the effects of the program intervention on infection-related medical care utilization among children. The study used a quasi-experimental design with nonequivalent control group, comparing pre- and post-intervention data of the same children. The program implemented interventions in terms of management, education, and medical examination for the teachers, parents, and children in 12-week period. The frequency of utilization, cost, and prescription days of drugs and antibiotics due to infectious diseases prior to the intervention were compared with those during the 3-month intervention, using health insurance claim data. A panel analysis was also conducted to support the findings. A significant reduction (12%) in infection-related visit days of hospitals was observed with the intervention (incident rate ratio = 0.88, P = 0.01). And medical cost, drug prescription days, and antibiotics prescription days were decreased, although not statistically significant. A further cost-effectiveness analysis in terms of social perspectives, considering the opportunity costs for guardians to take children to medical institutions, would be needed.
MALE‐BIASED MUTATION, SEX LINKAGE, AND THE RATE OF ADAPTIVE EVOLUTION

Abstract An interaction between sex‐linked inheritance and sex‐biased mutation rates may affect the rate of adaptive evolution. Males have much higher mutation rates than females in several vertebrate and plant taxa. When evolutionary rates are limited by the supply of favorable new mutations, then genes will evolve faster when located on sex chromosomes that spend more time in males. For mutations with additive effects, Y‐linked genes evolve fastest, followed by Z‐linked genes, autosomal genes, X‐linked genes, and finally W‐linked and cytoplasmic genes. This ordering can change when mutations show dominance. The predicted differences in substitution rates may be detectable at the molecular level. Male‐biased mutation could cause adaptive changes to accumulate more readily on certain kinds of chromosomes and favor animals with Z‐W sex determination to have rapidly evolving male sexual displays.
On the Power of Belief Propagation : A Constraint Propagation Perspective

In his seminal paper, Pearl [1986] introduced the notion of Bayesian networks and the first processing algorithm, Belief Propagation (BP), that computes posterior marginals, called beliefs, for each variable when the network is singly connected. The paper provided the foundation for the whole area of Bayesian networks. It was the first in a series of influential papers by Pearl, his students and his collaborators that culminated a few years later in his book on probabilistic reasoning [Pearl 1988]. In his early paper Pearl showed that for singly connected networks (e.g., polytrees) the distributed message-passing algorithm converges to the correct marginals in a number of iterations equal to the diameter of the network. In his book Pearl goes further to suggest the use of BP for loopy networks as an approximation algorithm (see page 195 and exercise 4.7 in [Pearl 1988]). During the decade that followed researchers focused on extending BP to general loopy networks using two principles. The first is tree-clustering, namely, the transformation of a general network into a tree of largedomain variables called clusters on which BP can be applied. This led to the join-tree or junction-tree clustering and to the bucket-elimination schemes [Pearl 1988; Dechter 2003] whose time and space complexity is exponential in the tree-width of the network. The second principle is that of cutset-conditioning that decomposes the original network into a collection of independent singly-connected networks all of which must be processed by BP. The cutset-conditioning approach is time exponential in the network’s loop-cutset size and require linear space [Pearl 1988; Dechter 2003]. The idea of applying belief propagation directly to multiply connected networks caught up only a decade after the book was published, when it was observed by researchers in coding theory that high performing probabilistic decoding algorithms such as turbo codes and low density parity-check codes, which significantly outperformed the best decoders at the time, are equivalent to an iterative application of Pearl’s belief propagation algorithm [McEliece, MacKay, and Cheng 1998]. This success intrigued researchers and started massive explorations of the potential of these local computation algorithms for general applications. There is now a significant body of research seeking the understanding and improvement of the inference power of iterative belief propagation (IBP). The early work on IBP showed its convergence for a single loop, provided empirical evidence of its successes and failures on various classes of networks [Rish, Kask, and Dechter 1998; Murphy, Weiss, and Jordan 2000] and explored the relationship between energy min-
Feedback complexity, bounded rationality, and market dynamics

In a set of experimental markets we investigate how the dynamic structure of an economy interacts with different price-setting institutions to determine market performance, stability and learning. We test the standard assumptions of optimality and rational expectations against a behavioral hypothesis in which subjects ignore critical elements of the feedback structure in which they operate (‘misperceptions of feedback’). We find first that the introduction of even modest levels of dynamic complexity to the structure of the experimental economy significantly and substantially degrades performance relative to optimal, supporting the behavioral hypotheses. In the dynamically complex conditions, subjects generate costly, systematic fluctuations in prices and quantities. The institutional structure of the market also has a strong effect on performance relative to optimal. Performance is improved, but remains significantly below, optimal in the presence of market institutions, even in the case of a perfectly functioning market with computer-mediated market clearing. Markets moderate but do not eliminate the negative impact of bounded rationality and poor mental models. We then analyze the decisions of individual subjects by fitting them to various models of decision making. The estimates reject the hypothesis of rationality at the individual level. We then simulate the markets using the estimated decision rules. The simulations reproduce the most salient features of the dynamics, and variations between markets are related to differences the parameters values of the decision rules which characterize the degree to which subjects misunderstand the feedback structure of the market. In this manner, the analysis links microstructure to macrobehavior, coupling observation of individual decision making behavior and the genesis of aggregate market outcomes. Decision timing data and verbal protocols provide evidence that increasing complexity of the decision-making task leads subjects to ignore important aspects of the decision environment, particularly strategic interactions. In the face of dynamic complexity, subjects revert to simple, reactive decision rules, rules which prove to be dysfunctional. Moreover, subjects tend to attribute the oscillations and other systematic dynamics they experience to exogenous shocks rather than to their own interactions with the system. This latter phenomenon may have important implications for the ability of agents to learn and improve their behavior over time.
Wasting Time: the Mission Impossible with Respect to Technology-oriented Security Approaches

Security is still too orientated towards technology and behavioural aspects are under prioritized. Organisations focus on the ability of technology to minimise risks. This paper as a preliminary research of a PhD thesis will argue that this assumption and approach is misguided, so we will focus on how a critical approach is more useful to exposing these issues. The key to secure systems is employees' perception and the action they take in accordance with the learned and perceived need for an understanding of compliance. The paper is about critical approaches to research and it just happens to be information and communication technology (ICT) that is the subject area.
Lapatinib Restores Hormone Sensitivity with Differential Effects on Estrogen Receptor Signaling in Cell Models of Human Epidermal Growth Factor Receptor 2–Negative Breast Cancer with Acquired Endocrine Resistance

Purpose: Acquired endocrine resistance in estrogen receptor (ER)α+/human epidermal growth factor receptor 2–negative (HER2−) breast cancer has been associated with modest adaptive increases in HER2, although exactly how aberrant HER2 signaling affects the ERα pathway is poorly understood. We investigated (a) whether the epidermal growth factor receptor/HER2 inhibitor lapatinib could restore endocrine responsiveness in cell models of acquired endocrine resistance with modest increases in HER2, and (b) the nature of ERα-HER2 cross-talk in this process. Methods: Combination growth studies, ERα transcription, immunoblot, and gene expression assays were conducted in two models of acquired resistance to (a) estrogen deprivation (long-term estrogen-deprived cells) and (b) tamoxifen (long-term tamoxifen-treated cells), and in hormone sensitive controls. Changes in ERα, PgR, and HER2 were assessed in samples from patients treated with tamoxifen. Results: Both cell models of acquired endocrine resistance showed modest adaptive upregulation in HER2, and lapatinib restored endocrine sensitivity in both. The effect of lapatinib on ERα signaling varied markedly depending on the nature of the HER2/ERα cross-talk. In long-term estrogen-deprived cells characterized by enhanced ERα function, lapatinib suppressed ERα genomic activity (as measured by pERSer118, ERα transcriptional activity, and PGR gene expression). In contrast, in long-term tamoxifen-treated cells with reduced ERα activation, lapatinib reactivated ERα genomic function. Twenty percent of tamoxifen-resistant patients relapsed with modest increases in HER2 and either suppressed or enhanced ERα/PgR expression. Conclusions: Aberrant GFR signaling can augment or suppress ERα function. Regardless, interrupting the HER2/ERα cross-talk with lapatinib can restore endocrine sensitivity and should be investigated as a therapeutic strategy in combination with endocrine therapy in ERα+/HER2− patients with acquired endocrine resistance. Clin Cancer Res; 16(5); 1486–97
Using Likelihood-Free Inference to Compare Evolutionary Dynamics of the Protein Networks of H. pylori and P. falciparum

Gene duplication with subsequent interaction divergence is one of the primary driving forces in the evolution of genetic systems. Yet little is known about the precise mechanisms and the role of duplication divergence in the evolution of protein networks from the prokaryote and eukaryote domains. We developed a novel, model-based approach for Bayesian inference on biological network data that centres on approximate Bayesian computation, or likelihood-free inference. Instead of computing the intractable likelihood of the protein network topology, our method summarizes key features of the network and, based on these, uses a MCMC algorithm to approximate the posterior distribution of the model parameters. This allowed us to reliably fit a flexible mixture model that captures hallmarks of evolution by gene duplication and subfunctionalization to protein interaction network data of Helicobacter pylori and Plasmodium falciparum. The 80% credible intervals for the duplication–divergence component are [0.64, 0.98] for H. pylori and [0.87, 0.99] for P. falciparum. The remaining parameter estimates are not inconsistent with sequence data. An extensive sensitivity analysis showed that incompleteness of PIN data does not largely affect the analysis of models of protein network evolution, and that the degree sequence alone barely captures the evolutionary footprints of protein networks relative to other statistics. Our likelihood-free inference approach enables a fully Bayesian analysis of a complex and highly stochastic system that is otherwise intractable at present. Modelling the evolutionary history of PIN data, it transpires that only the simultaneous analysis of several global aspects of protein networks enables credible and consistent inference to be made from available datasets. Our results indicate that gene duplication has played a larger part in the network evolution of the eukaryote than in the prokaryote, and suggests that single gene duplications with immediate divergence alone may explain more than 60% of biological network data in both domains.
Interesting, but Less Interested: Gender Differences and Similarities in Mathematics Interest

ABSTRACT The purpose of the present study was to examine gender differences in mathematics interest. In a sample of middle school students (N = 366), we examined mathematics interest as a trait (i.e., individual interest) and as a current state (i.e., situational interest) during a learning activity in mathematics. Assessment of perceived competence, performance, and effort during learning was also included. Results revealed a significant difference between boys and girls in their ratings of individual interest, but not in the current experience of situational interest. Furthermore, boys and girls did not differ in performance during learning, but girls invested significantly more effort than boys. Results and their implications are discussed in relation to interest development, gender differences, and subjective beliefs.