Miracle-dz/UniFAR-FTUs huggingface dataset:
Supporting Online Material Materials and Methods Som Text Figs. S1 and S2 Tables S1 to S10 References Understanding Overbidding: Using the Neural Circuitry of Reward to Design Economic Auctions

It is not crucial for our purposes that identical actions lead to high payoffs. Instead, the necessity of coordinated choices for a high payoff is important. Thus, if the choice combination A for player 1 and B for player 2 led to a high payoff, then the players would simply need to coordinate on (A, B). Almost every bargaining problem or economic exchange involves some necessity for coordinating expectations and actions. We take advantage of our knowledge of the neural circuitry of reward to investigate a puzzling economic phenomenon: Why do people overbid in auctions? Using functional magnetic resonance imaging (fMRI), we observed that the social competition inherent in an auction results in a more pronounced blood oxygen level–dependent (BOLD) response to loss in the striatum, with greater overbidding correlated with the magnitude of this response. Leveraging these neuroimaging results, we design a behavioral experiment that demonstrates that framing an experimental auction to emphasize loss increases overbidding. These results highlight a role for the contemplation of loss in understanding the tendency to bid " too high. " Current economic theories suggest overbidding may result from either " joy of winning " or risk aversion. By combining neuroeconomic and behavioral economic techniques, we find that another factor, namely loss contemplation in a social context, may mediate overbidding in auctions. A n unresolved question in the emerging field of neuroeconomics is whether data from neuroscience can inform economic theory such that it motivates behavioral economic institutional design (1–4). In this report, we address this question by taking advantage of our knowledge of the neural circuitry of reward to investigate a puzzling economic phenomenon. Specifically, why do people overbid in auctions? (5, 6). Auctions are an old and widely used method in allocating goods (7). Mention of them dates back to Roman times, when spoils of war were sold on the block. Although there are many different types of auctions, they all share the feature that bidders must determine a bidding strategy (or bid function) to be used in submitting their bid. A bid function for a buyer in an auction is a mapping from the value that the bidder places on the good for sale to the bid chosen. A set of bidding functions is considered to be an equilibrium (Nash equilibrium) if, given the strategy used by one's opponents, no bidder has any incentive to change his or her bidding strategy. …
Genetic Polymorphisms of Multidrug Resistance Gene-1 (MDR1/ABCB1) and Glutathione S-Transferase Gene and the Risk of Inflammatory Bowel Disease among Moroccan Patients

Inflammatory bowel diseases (IBD) are multifactorial disorders resulting from environmental and genetic factors. Polymorphisms in MDR1 and GSTs genes might explain individual differences in susceptibility to IBD. We carried out a case-control study to examine the association of MDR1 (C1236T and C3435T), GSTT1, and GSTM1 polymorphisms with the risk of IBD. Subjects were genotyped using PCR-RFLP for MDR1 gene and multiplex PCR for GSTT1 and GSTM1. Meta-analysis was performed to test the association of variant allele carriage with IBD risk. We report that GSTT1 null genotype is significantly associated with the risk of CD (OR: 2.5, CI: 1.2–5, P = 0.013) and UC (OR: 3.5, CI: 1.5–8.5, P = 0.004) and can influence Crohn's disease behavior. The interaction between GSTT1 and GSTM1 genes showed that the combined null genotypes were associated with the risk of UC (OR: 3.1, CI: 1.1–9, P = 0.049). Furthermore, when compared to combined 1236CC/CT genotypes, the 1236TT genotype of MDR1 gene was associated with the risk of UC (OR: 3.7, CI: 1.3–10.7, P = 0.03). Meta-analysis demonstrated significantly higher frequencies of 3435T carriage in IBD patients. Our results show that GSTT1 null and MDR1 polymorphisms could play a role in susceptibility to IBD.
Singularity-robust modular inverse kinematics for robotic gesture imitation

We present a method of computing the joint angles for an upper body humanoid robot corresponding to task space motion data from a human demonstrator. Using a divide-and-conquer approach, we group the motors into pan-tilt and spherical units, and solve the inverse kinematics in a modular fashion based on the derivative of the inverse tangent function of the relevant task space variables. For robustness to kinematic singularity, we add a regularization parameter that vanishes whenever the task variables are outside a neighborhood of zero. Simulation study on a 7 degree-of-freedom (DOF) robot arm shows a tradeoff of tracking accuracy in a neighborhood of each singularity in favor of robustness, but high accuracy is recovered outside this neighborhood. Experimental implementation of the proposed inverse kinematics on a 17-DOF upper-body humanoid robot shows that user-demonstrated gestures are well-replicated by the robot.
Compressive covariance sampling

Most research efforts in the field of compressed sensing have been pointed towards analyzing sampling and reconstruction techniques for sparse signals, where sampling rates below the Nyquist rate can be reached. When only second-order statistics or, equivalently, covariance information is of interest, perfect signal reconstruction is not required and rate reductions can be achieved even for non-sparse signals. This is what we will refer to as compressive covariance sampling. In this paper, we will study minimum-rate compressive covariance sampling designs within the class of non-uniform samplers. Necessary and sufficient conditions for perfect covariance reconstruction will be provided and connections to the well-known sparse ruler problem will be highlighted.
Pipeline rendering: interaction and realism through hardware-based multi-pass rendering

While large investments are made in sophisticated graphics hardware most realistic rendering is still performed o line using ray trace or radiosity systems A coordinated use of hardware provided bitplanes and rendering pipelines can however approximate ray trace quality illumination e ects in a user interactive environment as well as provide the tools necessary for a user to declutter such a complex scene A variety of common ray trace and radiosity illumination e ects are presented using multi pass rendering in a pipeline architecture We provide recursive re ections through the use of secondary viewpoints and present a method for using a homogeneous D projective image mapping to extend this method for refractive transparent surfaces This paper then introduces the Dual Z bu er or DZ bu er an evolutionary hardware extension which along with current frame bu er functions such as stencil planes and accumulation bu ers provides the hardware platform to render non refractive transparent surfaces in a back to front or front to back order We extend the traditional use of shadow volumes to provide re ected and refracted shadows as well as specular light reclassi cation The shadow and lighting e ects are then incorporated into our recursive viewpoint paradigm Global direct illumination is provided through a shadow blending technique Hardware surface illumination is t to a physically based BRDF to provide a better local direct model and the framework permits incorporation of a radiosity solution for indirect illumination as well Additionally we incorporate material properties including translucency light scattering and non uniform transmittance to provide a general framework for creating realistic renderings The DZ bu er also provides decluttering facilities such as transparency and clipping This permits selective scene viewing through arbitrary view dependent and non planar clipping and trnasparency surfaces in real time The combination of these techniques provide for understandable realistic scene rendering at typical rates times that of a comperable ray trace images In addition the pixel parallel nature of these methods leads to exploration of further hardware rendering engine extensions which can exploit this coherence
DRIMust: a web server for discovering rank imbalanced motifs using suffix trees

Cellular regulation mechanisms that involve proteins and other active molecules interacting with specific targets often involve the recognition of sequence patterns. Short sequence elements on DNA, RNA and proteins play a central role in mediating such molecular recognition events. Studies that focus on measuring and investigating sequence-based recognition processes make use of statistical and computational tools that support the identification and understanding of sequence motifs. We present a new web application, named DRIMust, freely accessible through the website http://drimust.technion. ac.il for de novo motif discovery services. The DRIMust algorithm is based on the minimum hypergeometric statistical framework and uses suffix trees for an efficient enumeration of motif candidates. DRIMust takes as input ranked lists of sequences in FASTA format and returns motifs that are over-represented at the top of the list, where the determination of the threshold that defines top is data driven. The resulting motifs are presented individually with an accurate P-value indication and as a Position Specific Scoring Matrix. Comparing DRIMust with other state-of-the-art tools demonstrated significant advantage to DRIMust, both in result accuracy and in short running times. Overall, DRIMust is unique in combining efficient search on large ranked lists with rigorous P-value assessment for the detected motifs.
Modeling and synthesis of timed asynchronous circuits

| Most asynchronous compilers do not take into account timing constraints, although these are crucial for industrial interface applications. In this paper we extend the classical signal transition graph model such that timing constraints can be modeled in a concise way. We also propose synthesis algorithms that transform the initial speci cation such that the circuit derived from the transformed speci cation satis es all timing constraints.
CCD photometry of the globular cluster M2: RR Lyrae physical parameters and new variables

We report the results of CCD V and R photometry of the RR Lyrae stars in M2. The periodicities of most variables are revised and new ephemerides are calculated. Light-curve decomposition of the RR Lyrae stars was carried out and the corresponding mean physical parameters [Fe/H] = -1.47, T eff = 6276 K, log L = 1.63 L ⊙ and M V = 0.71 from nine RRab and [Fe/H] = -1.61, M = 0.54 M ⊙ , T eff = 7215 K, logL = 1.74 L ⊙ and M V = 0.71 from two RRc stars were calculated. A comparison of the radii obtained from the above luminosity and temperature with predicted radii from non-linear convective models is discussed. The estimated mean distance to the cluster is 10.49 ± 0.15 kpc. These results place M2 correctly in the general globular cluster sequences for Oosterhoff type, mass, luminosity and temperature, all as a function of the metallicity. Mean relationships for M, log L/L ⊙ , T eff and M V as a function of [Fe/H] for a family of globular clusters are offered. These trends are consistent with evolutionary and structural notions on the horizontal branch. Eight new variables are reported.
High-Level Energy Estimation for Embedded DSP Software

A new approach for estimating Digital Signal Processors’ energy consumption is presented. Our energy consumption model is based on a functional analysis of the DSP’s core. Several consumption rules are determined. They give, from specific parameters extracted from the algorithm’s source code, the consumption of every functional block in the DSP, and lead to the application’s overall energy consumption. The last generation Texas Instruments C6201 is studied; the methodology is not restricted to this sole processor however. The method is finally demonstrated on a classical signal processing algorithm; the gap between measures and estimations is lower than 8%.
Modeling and rendering of impossible figures

This article introduces an optimization approach for modeling and rendering impossible figures. Our solution is inspired by how modeling artists construct physical 3D models to produce a valid 2D view of an impossible figure. Given a set of 3D locally possible parts of the figure, our algorithm automatically optimizes a view-dependent 3D model, subject to the necessary 3D constraints for rendering the impossible figure at the desired novel viewpoint. A linear and constrained least-squares solution to the optimization problem is derived, thereby allowing an efficient computation and rendering new views of impossible figures at interactive rates. Once the optimized model is available, a variety of compelling rendering effects can be applied to the impossible figure.
Community Detection with Prior Knowledge

The problem of community detection is a challenging one because of the presence of hubs and noisy links, which tend to create highly imbalanced graph clusters. Often, these resulting clusters are not very intuitive and difficult to interpret. With the growing availability of network information, there is a significant amount of prior knowledge available about the communities in social, communication and several other networks. These community labels may be noisy and very limited, though they do help in community detection. In this paper, we explore the use of such noisy labeled information for finding high quality communities. We will present an adaptive density-based clustering which allows flexible incorporation of prior knowledge in to the community detection process. We use a random walk framework to compute the node densities and the level of supervision regulates the node densities and the quality of resulting density based clusters. Our framework is general enough to produce both overlapping and non-overlapping clusters. We empirically show that even with a tiny amount of supervision, our approach can produce superior communities compared to popular baselines.
Understanding Reliability Implication of Hardware Error in Virtualization Infrastructure

Hardware errors are no longer the exceptions in modern cloud data centers. Although virtualization provides software failure isolation across different virtual machines (VM), the virtualization infrastructure including the hypervisor and privileged VMs remains vulnerable to hardware errors. Making matters worse is that such errors are unlikely bounded by virtualization boundary and may lead to loss of work in multiple guest VMs due to unexpected and/or mishandled failures. To understand reliability implication of hardware errors in virtualized systems, in this paper we develop a simulation-based framework that enables a comprehensive fault injection study on the hypervisor with a wide range of configurations. Our analysis shows that, in current systems, many hardware errors can propagate through various paths for an extended time before an observed failure (e.g., whole system crash). We further discuss the challenges of designing error tolerance techniques for the hypervisor.
Ubiquitous nucleosome crowding in the yeast genome

Significance In eukaryotic cells, up to 90% of genomic DNA is occluded by nucleosomes, fundamental units of chromatin in which DNA is tightly bent around the surface of a histone octamer. We present evidence that many nucleosomes in a single-cell eukaryote, Saccharomyces cerevisiae, are wrapped only partially, allowing them to invade genomic territories of their neighbors. These findings significantly extend the canonical view of nucleosomes as separate “beads on a string” and raise the question of how cellular functions are carried out in this crowded environment. Nucleosomes may undergo a conformational change in which a stretch of DNA peels off the histone octamer surface as a result of thermal fluctuations or interactions with chromatin remodelers. Thus, neighboring nucleosomes may invade each other’s territories by DNA unwrapping and translocation, or through initial assembly in partially wrapped states. A recent high-resolution map of distances between dyads of neighboring nucleosomes in Saccharomyces cerevisiae reveals that nucleosomes frequently overlap DNA territories of their neighbors. This conclusion is supported by lower-resolution maps of S. cerevisiae nucleosome lengths based on micrococcal nuclease digestion and paired-end sequencing. The average length of wrapped DNA follows a stereotypical pattern in genes and promoters, correlated with the well-known distribution of nucleosome occupancy: nucleosomal DNA tends to be shorter in promoters and longer in coding regions. To explain these observations, we have developed a biophysical model that uses a 10–11-bp periodic histone–DNA binding energy profile. The profile is based on the pattern of histone–DNA contacts in nucleosome crystal structures, as well as the idea of linker length discretization caused by higher-order chromatin structure. Our model is in agreement with the observed genome-wide distributions of interdyad distances, wrapped DNA lengths, and nucleosome occupancies. Furthermore, our approach explains in vitro measurements of the accessibility of nucleosome-covered target sites and nucleosome-induced cooperativity between DNA-binding factors. We rule out several alternative scenarios of histone–DNA interactions as inconsistent with the genomic data.
Development of thai word segmentation technique for solving problems with unknown words

This research has an objective to develop an efficient technique for Thai word segmentation, especially those nonexistent in dictionaries. The researchers developed a model for Thai word segmentation by relying on grammar and rules to solve the problems with words not found in dictionaries. The model was intended to be used as the best approach of word segmentation, which applied the segmentation technique developed by the researchers called PTTSF (Parsing Thai Text with Syntax and Feature of Word). The system of this technique operates by starting from finding the boundary of each word in Thai sentences. If the system finds a word that does not exist in the dictionary or a meaningless word, it would not be able to solve the problem with the method of longest-matching algorithm. Therefore, rules need to be specified to solve such problems. In this study, 28 rules were created and Digraph method was used to find a pattern of word segmentation with the highest probability based on the grammatical principle. After the procedure of finding boundary of the word, the result from correct word segmentation can be used for further processes. In analyzing efficiency of the system, its accuracy in word segmentation was the main point of concern. The results revealed that the derived mapping technique could solve the problem concerned with segmentation words that do not exist in the dictionary with an average accuracy over 90% of the whole document. However, the researchers encountered with ambiguous words problem. Although this problem rarely occurs, it could affect accuracy of word segmentation.
Performance Analysis of Energy Detection with Multiple Correlated Antenna Cognitive Radio in Nakagami-m Fading

This letter analyzes the performance of energy- detection-based spectrum sensing in a cognitive radio (CR) possessing multiple correlated antennas when the channel from the primary user (PU) to the CR is Nakagami-m faded. The probability of detection of the CR by employing square law combining (SLC) is derived by using the MGF-based approach. Special cases of equally correlated, exponentially correlated and a linear array of 2, 3 and 4 arbitrarily correlated antennas are treated. Numerical and simulation results are used to quantify the detector performance as a function of antenna correlation across the branches, number of antennas, fading severity and the time-bandwidth product.
Asymmetric neural coding revealed by in vivo calcium imaging in the honey bee brain

Left–right asymmetries are common properties of nervous systems. Although lateralized sensory processing has been well studied, information is lacking about how asymmetries are represented at the level of neural coding. Using in vivo functional imaging, we identified a population-level left–right asymmetry in the honey bee's primary olfactory centre, the antennal lobe (AL). When both antennae were stimulated via a frontal odour source, the inter-odour distances between neural response patterns were higher in the right than in the left AL. Behavioural data correlated with the brain imaging results: bees with only their right antenna were better in discriminating a target odour in a cross-adaptation paradigm. We hypothesize that the differences in neural odour representations in the two brain sides serve to increase coding capacity by parallel processing.
Dominant negative mutation in cell surface beta 1,4- galactosyltransferase inhibits cell-cell and cell-matrix interactions

In addition to its traditional location within the Golgi complex, beta 1,4-galactosyltransferase (GalTase) is also present on the cell surface, where it is thought to function as a cell adhesion molecule by binding to extracellular oligosaccharide ligands. Recent studies suggest that cells contain two forms of GalTase with distinct cytoplasmic domains. The longer form of GalTase contains a 13-amino acid cytoplasmic extension and is preferentially targeted to the plasma membrane, relative to the shorter GalTase protein that is confined primarily to the Golgi compartment. In this study, we created a dominant negative mutation that interferes with the function of cell surface GalTase by transfecting into cells cDNAs encoding truncated versions of the long form of GalTase containing the complete cytoplasmic and transmembrane domains, but devoid of the catalytic domain. In both F9 embryonal carcinoma cells and Swiss 3T3 fibroblasts, overexpressing the truncated long GalTase (TLGT) protein displaced the endogenous cell surface GalTase from its association with the cytoskeleton, resulting in a loss of intercellular adhesion and cell spreading specifically on matrices that use GalTase as a cell surface receptor. In contrast, overexpressing the analogous truncated short GalTase (TSGT) protein did not affect cell morphology or GalTase activity. In control assays, inducing the TLGT protein had no effect on cell interactions with fibronectin (which is independent of GalTase), or on the cytoskeleton attachment of another matrix receptor (beta 1 integrin), or on overall glycoprotein synthesis, thus eliminating nonspecific effects of the TLGT protein on cellular adhesion and metabolism. These results represent the first molecular manipulation of cell surface GalTase expression and confirm its function as a cell adhesion molecule. These studies further suggest that the cytoskeleton contains a defined, saturable number of binding sites for GalTase, which enables it to function as an adhesion molecule.