Miracle-dz/UniFAR-FTUs huggingface dataset:
Supporting Online Material Materials and Methods Tables S1 and S2 References the Effect of Oxygen on Biochemical Networks and the Evolution of Complex Life

Leu 402 /a). Moreover, the side chain of Leu 362 /a is buried within the hydrophobic cleft formed by MurNAc(anhydro) from TCT, and Ala 368 /x, Val 383 /x, and Phe 387 /x (Fig. 4A). Most of the interface residues in LCa show an induced-fit conformational change (Fig. 4B). Likewise, the orientations of many side chains of the LCx interface residues may also be induced as a result of TCT docking. The indole ring of Trp 392 /x is stacked against the indole ring of Trp 394 /x, which in turn stacks against the elongated side chain of DAP (Fig. 3); the aromatic ring of Phe 387 /x is in intimate van der Waals contact with MurNAc. Without bound TCT, both Phe 387 /x and Trp 392 /x would not have their side chains oriented properly for LCa interaction. This notion is favored by previous observation that a lactyl-tetrapeptide still retains some stimulatory activity despite the lack of a disaccharide moiety (3, 5); presumably, the stem peptide alone can bind to the LCx docking groove and induce properly oriented Trp 392 /x through stacking interactions to allow heterodimerization. In conclusion, the structure of the LCa-TCT-LCx complex has revealed the molecular interaction between a naturally occurring PG subunit and its PRR complex. The complex structure shows that TCT binds to the docking groove of LCx primarily through its elongated stem peptide and that the bound TCT conformation, which allows its disaccharide GlcNAc-MurNAc(anhydro) to be presented for LCa interaction, is further stabilized by extensive hydrogen bonding. DAP, the specificity determinant of TCT, engages a key electrostatic interaction with Arg 413 /x. Stacking interactions with the DAP side chain and the MurNAc ring induce proper orientations of side chains of Phe 387 /x and Trp 392 /x, which contribute part of the TCT-LCx interface for LCa binding by induced fit. The present complex structure represents the receptor activation step where a monomeric PG ligand brings PGRP-LCa and-LCx receptors together to allow cytoplasmic domains to interact for activation of the immune deficiency pathway. By contrast, activation of this pathway by polymeric PG only requires PGRP-LCx, which can be brought to close proximity by binding to adjacent muropeptide sub-units (9, 10). Protein-protein interaction induced by monomeric ligand as visualized by the present work is likely to serve as the general mechanism for pattern recognition for other PGRPs, such as PGRP-SA, that play a double role …
Sleep-Disordered Breathing Affects Auditory Processing in 5–7-Year-Old Children: Evidence From Brain Recordings

Poor sleep in children is associated with lower neurocognitive functioning and increased maladaptive behaviors. The current study examined the impact of snoring (the most common manifestation of sleep-disordered breathing) on cognitive and brain functioning in a sample of 35 asymptomatic children ages 5–7 years identified in the community as having habitual snoring (SDB). All participants completed polysomnographic, neurocognitive (NEPSY), and psychophysiological (event-related potentials [ERPs] to speech sounds) assessments. The results indicated that sub-clinical levels of SDB may not necessarily lead to reduced performance on standardized behavioral measures of attention and memory. However, brain indices of speech perception and discrimination (N1/P2) are sensitive to individual differences in the quality of sleep. We postulate that addition of ERPs to the standard clinical measures of sleep problems could lead to early identification of children who may be more cognitively vulnerable because of chronic sleep disturbances.
60 GHz injection locked frequency quadrupler with quadrature outputs in 65 nm CMOS process

This paper presents a LC-based sub-harmonic injection-locked frequency quadrupler which multiplies a 15 GHz input to 60 GHz quadrature(I/Q) output signals. The proposed quadrupler can use a lower-frequency PLL for incident signal than doublers and triplers, which is very advantageous to implement a wide-tuning and low-phase-noise PLL. The proposed frequency quadrupler is implemented by using a 65nm CMOS process. It consumes 5.9mW with a 0.6V supply voltage, and the core layout area is 160 µm × 110 µm.
DIFFERENCES IN THE COGNITIVE FUNCTIONING OF PERSONS WITH WILLIAMS SYNDROME AND PERSONS WITH DOWN SYNDROME

The goal of this study was to produce a precise picture of the cognitive profile of persons with Williams Syndrome (WS), through a comparison to the characteristic profile of persons with Down Syndrome (DS), another genetic disorder. We examined 35 persons with WS (average age 13.2 years) and a control group of persons with DS, matched for age and mental development. The research instruments used included Raven’s Colored Matrices, the Brief Intelligence Test, three subtests from the Wechsler Intelligence Scale for Children – Revised (Similarities, Picture Arranging, and Digit Recall), Piaget’s “left-right” test, a fragment from the MMSE, and a test of our own devising for recalling sensible verbal material. The WS group achieved better results than the DS group in respect to verbal intelligence, abstract thinking, cause-andeffect thinking, digit recall, and orientation in place and time. WS has a significant impact on the affected person’s cognitive level and profile. In order to improve rehabilitation, it would be worthwhile to base interventions on relatively well preserved cognitive functions (verbal intelligence and word memory, including name recall) and social-emotional functions.
A Genetic Screen for Modifiers of the Delta1-Dependent Notch Signaling Function in the Mouse

The Notch signaling pathway is an evolutionarily conserved transduction pathway involved in embryonic patterning and regulation of cell fates during development. Recent studies have demonstrated that this pathway is integral to a complex system of interactions, which are also involved in distinct human diseases. Delta1 is one of the known ligands of the Notch receptors. Mice homozygous for a loss-of-function allele of the Delta1 gene Dll1lacZ/lacZ die during embryonic development. Here, we present the results of two phenotype-driven modifier screens. Heterozygous Dll1lacZ knockout animals were crossed with ENU-mutagenized mice and screened for dysmorphological, clinical chemical, and immunological variants that are dependent on the Delta1 loss-of-function allele. First, we show that mutagenized heterozygous Dll1lacZ offspring have reduced body weight and altered specific clinical chemical parameters, including changes in metabolites and electrolytes relevant for kidney function. In our mutagenesis screen we have successfully generated 35 new mutant lines. Of major interest are 7 mutant lines that exhibit a Dll1lacZ/+-dependent phenotype. These mutant mouse lines provide excellent in vivo tools for studying the role of Notch signaling in kidney and liver function, cholesterol and iron metabolism, cell-fate decisions, and during maturation of T cells in the immune system.
Extending scientific computing system with structural quantum programming capabilities

We present a basic high-level structures used for developing quantum programming languages. The presented structures are commonly used in many existing quantum programming languages and we use quantum pseudo-code based on QCL quantum programming language to describe them. We also present the implementation of introduced structures in GNU Octave language for scientific computing. Procedures used in the implementation are available as a package quantum-octave, providing a library of functions, which facilitates the simulation of quantum computing. This package allows also to incorporate high-level programming concepts into the simulation in GNU Octave and Matlab. As such it connects features unique for high-level quantum programming languages, with the full palette of efficient computational routines commonly available in modern scientific computing systems. To present the major features of the described package we provide the implementation of selected quantum algorithms. We also show how quantum errors can be taken into account during the simulation of quantum algorithms using quantum-octave package. This is possible thanks to the ability to operate on density matrices.
Prevalence of Self-Reported Prediabetes Among Adults Participating in a Community-Based Health Awareness Program, New York State

Introduction The purpose of this study was to assess crude, age-adjusted, and risk-factor–specific prevalences of self-reported prediabetes and to identify factors associated with self-reported prediabetes in an adult population. Methods Data were collected through questionnaires completed by a racially diverse sample of diabetes-free adult participants in the statewide community-based wellness and diabetes awareness program in New York State during 2006 (N = 2,572). Prediabetes was determined by the affirmative answer to the question, "Have you ever been told by a doctor that you have prediabetes? " Results The overall crude prevalence of self-reported prediabetes was 9.1%, and the age-adjusted prevalence was 7.6%. The age-adjusted prevalence of prediabetes was significantly lower among non-Hispanic blacks (4.2%) and significantly higher among American Indians (22.4%), compared with the prevalence among non-Hispanic whites (7.3%). The prevalence of self-reported prediabetes was uniformly higher among older (aged ≥45 years) adults than younger (aged <45 years) adults, overall and in each racial/ethnic group. In all age and racial/ethnic groups, the prevalence significantly increased with the number of additional risk factors. The best fit multivariate logistic regression model identified that self-reported prediabetes was associated with family history of diabetes (odds ratio [OR], 3.65), body mass index 25.0 kg/m2 or higher (OR, 2.79), age 45 years or older (OR, 2.77), and having health insurance (OR, 2.38). Conclusion This study found that adults who were at high risk for diabetes and had health insurance were more likely to report having prediabetes. Community-based diabetes prevention needs to consider strategies to increase detection of prediabetes in high-risk uninsured people and to raise general awareness of prediabetes.
An Improved Decision Procedure for Linear Time Mu-Calculus

An improved Present Future form (PF form) for linear time $\mu$-calculus ($\nu$TL) is presented in this paper. In particular, the future part of the new version turns into the conjunction of elements in the closure of a formula. We show that every closed $\nu$TL formula can be transformed into the new PF form. Additionally, based on the PF form, an algorithm for constructing Present Future form Graph (PFG), which can be utilized to describe models of a formula, is given. Further, an intuitive and efficient decision procedure for checking satisfiability of the guarded fragment of $\nu$TL formulas based on PFG is proposed and implemented in C++. The new decision procedure has the best time complexity over the existing ones despite the cost of exponential space. Finally, a PFG-based model checking approach for $\nu$TL is discussed where a counterexample can be obtained visually when a model violates a property.
Quantitatively Different, yet Qualitatively Alike: A Meta-Analysis of the Mouse Core Gut Microbiome with a View towards the Human Gut Microbiome

Background A number of human diseases such as obesity and diabetes are associated with changes or imbalances in the gut microbiota (GM). Laboratory mice are commonly used as experimental models for such disorders. The introduction and dynamic development of next generation sequencing techniques have enabled detailed mapping of the GM of both humans and animal models. Nevertheless there is still a significant knowledge gap regarding the human and mouse common GM core and thus the applicability of the latter as an animal model. The aim of the present study was to identify inter- and intra-individual differences and similarities between the GM composition of particular mouse strains and humans. Methodology/Principal Findings A total of 1509428 high quality tag-encoded partial 16S rRNA gene sequences determined using 454/FLX Titanium (Roche) pyro-sequencing reflecting the GM composition of 32 human samples from 16 individuals and 88 mouse samples from three laboratory mouse strains commonly used in diabetes research were analyzed using Principal Coordinate Analysis (PCoA), nonparametric multivariate analysis of similarity (ANOSIM) and alpha diversity measures. A reliable cutoff threshold for low abundant taxa estimated on the basis of the present study is recommended for similar trials. Conclusions/Significance Distinctive quantitative differences in the relative abundance of most taxonomic groups between the examined categories were found. All investigated mouse strains clustered separately, but with a range of shared features when compared to the human GM. However, both mouse fecal, caecal and human fecal samples shared to a large extent not only representatives of the same phyla, but also a substantial fraction of common genera, where the number of shared genera increased with sequencing depth. In conclusion, the GM of mice and humans is quantitatively different (in terms of abundance of specific phyla and species) but share a large qualitatively similar core.
Influence of Group Size on the Success of Wolves Hunting Bison

An intriguing aspect of social foraging behaviour is that large groups are often no better at capturing prey than are small groups, a pattern that has been attributed to diminished cooperation (i.e., free riding) in large groups. Although this suggests the formation of large groups is unrelated to prey capture, little is known about cooperation in large groups that hunt hard-to-catch prey. Here, we used direct observations of Yellowstone wolves (Canis lupus) hunting their most formidable prey, bison (Bison bison), to test the hypothesis that large groups are more cooperative when hunting difficult prey. We quantified the relationship between capture success and wolf group size, and compared it to previously reported results for Yellowstone wolves hunting elk (Cervus elaphus), a prey that was, on average, 3 times easier to capture than bison. Whereas improvement in elk capture success levelled off at 2–6 wolves, bison capture success levelled off at 9–13 wolves with evidence that it continued to increase beyond 13 wolves. These results are consistent with the hypothesis that hunters in large groups are more cooperative when hunting more formidable prey. Improved ability to capture formidable prey could therefore promote the formation and maintenance of large predator groups, particularly among predators that specialize on such prey.
Fast Reconstruction for Sparse MR Images in Compressed Sensing

In this paper, we apply TV sparsifying MR image reconstruction method proposed in [ Y. G. Zhu and X. L. Yang, Journal of Signal and Information Processing, 2 (2011), pp. 44-51] to compressed sensing MRI model with wavelet sparsity. The fast method to reconstruct MR images with wavelet sparsity in compressed sensing is presented. This approach can exactly reconstruct the MR image from the partial Fourier data. The convergence of the fast method is analyzed. Some MR images are employed to test in the numerical experiments, and the results demonstrate that this method is very efficient in the reconstruction of MR images.
Feature Selection and Parameter Optimization of Support Vector Machines Based on Modified Cat Swarm Optimization

Recently, applications of Internet of Things create enormous volumes of data, which are available for classification and prediction. Classification of big data needs an effective and efficient metaheuristic search algorithm to find the optimal feature subset. Cat swarm optimization (CSO) is a novel metaheuristic for evolutionary optimization algorithms based on swarm intelligence. CSO imitates the behavior of cats through two submodes: seeking and tracing. Previous studies have indicated that CSO algorithms outperform other well-known metaheuristics, such as genetic algorithms and particle swarm optimization. This study presents a modified version of cat swarm optimization (MCSO), capable of improving search efficiency within the problem space. The basic CSO algorithm was integrated with a local search procedure as well as the feature selection and parameter optimization of support vector machines (SVMs). Experiment results demonstrate the superiority of MCSO in classification accuracy using subsets with fewer features for given UCI datasets, compared to the original CSO algorithm. Moreover, experiment results show the fittest CSO parameters and MCSO take less training time to obtain results of higher accuracy than original CSO. Therefore, MCSO is suitable for real-world applications.
Organising Committee Program Committee Let's Go for a Treasure Hunt

This paper presents a study designed to explore the effect of feedback on perception of an embodied agent as well as the overall performance and experience of primary school children aged 12-13 carrying out a treasure hunt activity. We use an embodied agent to compare three experimental conditions: no feedback, neutral feedback, and affective feedback. What the students think about the embodied agent and how they feel about the task under the different conditions will be elicited through a questionnaire upon completion of the treasure hunt activity. Moreover, how each condition affects the students’ performance will be analysed.
Reliable face recognition using feature selection and image rejection based on probabilistic face model

Though many studies on robust face recognition have shown good performances at their experiments, they still suffer from diverse environmental variations in real world. In addition, most face recognition methods focus only on classifying subjects using well-aligned facial images, and thus their reliabilities are dependent upon the performance of pre-processors such as face detector. The purpose of this study is to develop a reliable face recognition system that can deal with two common errors caused by automatic face detectors: incorrect localization and false detection of non-facial images. Based on the previous framework using probabilistic face model of local features, we add a feature selection module that can deal with localization error as well as a rejection module that can effectively treat detection error. Through computational experiments using benchmark data and real world images including translation variations and/or detection errors, we confirm significant improvement in the classification performance and reliability.
Hypoxia regulates Toll-like receptor-9 expression and invasive function in human brain cancer cells in vitro

Toll-like receptor-9 (TLR9) is a cellular DNA sensor of the innate immune system. TLR9 is widely expressed in a number of tumors, including brain cancer; however, little is known regarding its regulation and involvement in cancer pathophysiology. The present study demonstrated that hypoxia upregulates and downregulates TLR9 expression in human brain cancer cells in vitro, in a cell-specific manner. In addition, hypoxia-induced TLR9 upregulation was associated with hypoxia-induced invasion; however, such invasion was not detected in cells where hypoxia had suppressed TLR9 expression. Furthermore, suppression of TLR9 expression through TLR9 siRNA resulted in an upregulation of matrix metalloproteinase (MMP)-2, -9 and -13 and tissue inhibitor of matrix metalloproteinases-3 (TIMP-3) mRNA, and a decreased invasion of cells in normoxia, in a cell-specific manner. In cells where hypoxia induced TLR9 expression, TLR9 expression and invasion were reduced by TLR9 siRNA. The decreased invasion observed in hypoxia was associated with the decreased expression of the MMPs and a concomitant increase in TIMP-3 expression. In conclusion, hypoxia regulates the invasion of brain cancer cells in vitro in a TLR9-dependent manner, which is considered to be associated with a complex expression pattern of TLR9-regulated mediators and inhibitors of invasion.
The Area Coverage Problem for Dynamic Sensor Networks

In this section a brief description of area coverage and connectivity maintenance for sensor networks is given together with their collocation in the scientific literature. Particular attention is given to dynamic sensor networks, such as sensor networks in witch sensing nodes moves continuously, under the assumption, reasonable in many applications, that synchronous or asynchronous discrete time measures are acceptable instead of continuous ones.
Efficient and Supervised Anomalous Event Detection in Videos for Surveillance Purposes

In this paper, we consider the challenging problem of anomalous behavior detection in videos. Considering the pixel based anomaly detection, we have used k-mean clustering, a posteriori probability based probabilistic model, and region intersection to detect the anomalies in the video. The proposed technique considers the normal events as the events of higher probabilities. Densely sampled points are passed to a probabilistic model through k-mean clustering to obtain the probability of events. A threshold on the probability values is applied to distinguish anomaly from normal events. The final results of anomalous event detection obtained from different spatial scales are combined through region intersection. The integration of results of multi-scale anomaly detection using region intersection reduces false positives robustly. We have tested our technique over publically available standard video anomaly dataset.
POWER SERIES EXPANSIONS OF MODULAR FORMS AND THEIR INTERPOLATION PROPERTIES

We define a power series expansion of an holomorphic modular form f in the p-adic neighborhood of a CM point x of type K for a split good prime p. The modularity group can be either a classical conguence group or a group of norm 1 elements in an order of an indefinite quaternion algebra. The expansion coefficients are shown to be closely related to the classical Maass operators and give p-adic information on the ring of definition of f. By letting the CM point x vary in its Galois orbit, the rth coefficients define a p-adic K×-modular form in the sense of Hida. By coupling this form with the p-adic avatars of algebraic Hecke characters belonging to a suitable family and using a Rankin–Selberg type formula due to Harris and Kudla along with some explicit computations of Watson and of Prasanna, we obtain in the even weight case a p-adic measure whose moments are essentially the square roots of a family of twisted special values of the automorphic L-function associated with the base change of f to K.