Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimistic register coalescing

Graph-coloring register allocators eliminate copies by coalescing the source and target node of a copy if they do not interfere in the interference graph. Coalescing is, however, known to be harmful to the colorability of the graph because it tends to yield a graph with nodes of higher degrees. Unlike aggressive coalescing which coalesces any pair of non-interfering copy-related nodes, conservative coalescing or iterated coalescing perform safe coalescing that preserves the colorability. Unfortunately, these heuristics give up coalescing too early, losing many opportunities of coalescing that would turn out to be safe. Moreover, they ignore the fact that coalescing may even improve the colorability of the graph by reducing the degree of neighbor nodes that are interfering with both the source and target nodes being coalesced. This paper proposes a new heuristic called optimistic coalescing which optimistically performs aggressive coalescing, thus fully exploiting the positive impact of coalescing, yet when a coalesced node is to be spilled, it is split back into separate nodes; there as a better chance of coloring one of them which reduces the overall spill cost.
Full-chip TSV-to-TSV coupling analysis and optimization in 3D IC

This paper studies TSV-to-TSV coupling in 3D ICs. A full-chip SI analysis flow is proposed based on the proposed coupling model. Analysis results show that TSVs cause significant coupling noise and timing problems despite that TSV count is much smaller com- pared with the gate count. Two approaches are proposed to alleviate TSV-to-TSV coupling, namely TSV shielding and buffer insertion. Analysis results show that both approaches are effective in reducing the TSV-caused-coupling and improving timing.
Adjusting Active Basis Model by Regularized Logistic Regression

Active basis model is a generative model seeking a common wavelet sparse coding of images from the same object category, where the images share the same set of selected wavelet elements, which are allowed to perturb their locations and orientations to account for shape deformations. This work applies discriminative methods to adjust λ’s of selected basis elements, including logistic regression, SVM and AdaBoost. Results on supervised learning show that discriminative post-processing on active basis model improves its classification performance in terms of testing AUC. Among the three methods the L2-regularized logistic regression is the most natural one and performs the best.
Integration of Digital Photogrammetry and Laser Scanning for Heritage Documentation

Within the paper the potential of combining terrestrial laser scanning and close range photogrammetry for the documentation of heritage sites is discussed. Besides improving the geometry of the model, the integration aims on supporting the visual quality of the linear features like edges and cracks in the historical scenes. Although the laser scanner gives very rich surface details, it does not provide sufficient data to construct outlines for all surface features of the scanned object, evene though they are clearly defined in the reality. In our approach, information on edges and linear surface features is based on the analysis of the images. For this purpose an integrated segmentation process based on image data will support the extraction of object geometry information from the laser data. The approach applies image based semi-automated techniques in order to bridge gaps in the laser scanner data and add new details, which are required to build more realistic perception of the scene volume. The investigations and implementation of the experiments are based on data from Al-Khasneh, a well-known monument in Petra, Jordan. ∗ Corresponding author
Integrated force/tactile sensing: The enabling technology for slipping detection and avoidance

This paper proposes an experimental study of slipping avoidance algorithms based on force/tactile perception data. The claim is that contact force measurements alone or tactile data alone are not sufficient for an effective slipping avoidance strategy in real world conditions. Integrated force/tactile sensors able to provide measurements of both the contact force vector and spatially distributed tactile maps are the key enabling technology for efficient slipping avoidance control algorithms that can actually work with real world objects under no restricting assumption on the contact geometry or with unknown physical properties of the objects. The paper proposes a new slipping avoidance control scheme, which usefully exploits an integrated force/tactile sensor mounted on the parallel gripper of a Kuka youBot. The results show how the strategy successfully allows the robot to safely manipulate real-world objects, both rigid and compliant, in various friction conditions of their surface, both stable and slippery.
Leptin Promotes Differentiation and Survival of Human Dendritic Cells and Licenses Them for Th1 Priming 1

Leptin is an adipocyte-derived hormone/cytokine that links nutrition, metabolism, and immune homeostasis. Leptin is capable of modulating several immune responses. However, the effect of leptin on dendritic cells (DCs) has not yet been recognized. Because DCs are instrumental in the development of immune responses, in this study, we evaluated the impact of leptin on DC activation. We demonstrated the presence of leptin receptor in human immature and mature DCs both at mRNA and protein level and its capacity to transduce leptin signaling leading to STAT-3 phosphorylation. We found no consistent modulation of DC surface molecules known to be critical for their APC function in response to leptin. In contrast, we found that leptin induces rearrangement of actin microfilaments, leading to uropod and ruffle formation. At a functional level, leptin up-regulates the IL-1β, IL-6, IL-12, TNF-α, and MIP-1α production. Coincident with this, leptin-treated DCs stimulate stronger heterologous T cell responses. Furthermore, we found that leptin down-regulates IL-10 production by DCs and drives naive T cell polarization toward Th1 phenotype. Finally, we found that leptin partly protects DCs from spontaneous and UVB-induced apoptosis. Consistent with the antiapoptotic effect of leptin, we observed the activation of NF-κB and a parallel up-regulation of bcl-2 and bcl-xL gene expression. These results provide new insights on the immunoregulatory function of leptin demonstrating its ability to improve DC functions and to promote DC survival. This is of relevance considering a potential application of leptin in immunotherapeutic approaches and its possible use as adjuvant in vaccination protocols.
KINALYZER, a computer program for reconstructing sibling groups

A software suite KINALYZER reconstructs full‐sibling groups without parental information using data from codominant marker loci such as microsatellites. KINALYZER utilizes a new algorithm for sibling reconstruction in diploid organisms based on combinatorial optimization. KINALYZER makes use of a Minimum 2‐Allele Set Cover approach based on Mendelian inheritance rules and finds the smallest number of sibling groups that contain all the individuals in the sample. Also available is a ‘Greedy Consensus’ approach that reconstructs sibgroups using subsets of loci and finds the consensus of the partial solutions. Unlike likelihood methods for sibling reconstruction, KINALYZER does not require information about population allele frequencies and it makes no assumptions regarding the mating system of the species. KINALYZER is freely available as a web‐based service.
Indirect Modulation by α7 Nicotinic Acetylcholine Receptors of Noradrenaline Release in Rat Hippocampal Slices: Interaction with Glutamate and GABA Systems and Effect of Nicotine Withdrawal

Nicotinic acetylcholine receptors (nAChRs) can modulate transmitter release. Striatal [3H]dopamine ([3H]DA) release is regulated by presynaptic nAChR on dopaminergic terminals and α7 nAChR on neighboring glutamatergic afferents. Here, we explored the role of α7 nAChR in the modulation of [3H]noradrenaline ([3H]NA) release from rat hippocampal slices. The nicotinic agonist anatoxin-a (AnTx) evoked monophasic [3H]NA release (EC50 = 1.2 μM) that was unaffected by α-conotoxin-MII or dihydro-β-erythroidine, antagonists of α3/α6β2* and β2* nAChR, respectively. In contrast AnTx-evoked striatal [3H]DA release was biphasic (EC50 = 138.9 nM; 7.1 μM) and blocked by these antagonists. At a high AnTx concentration (25 μM), α7 nAChR antagonists (methyllycaconitine, α-conotoxin-ImI) and glutamate receptor (GluR) antagonists [kynurenic acid, 6,7-dinitroquinoxaline-2,3-dione (DNQX)] partially inhibited [3H]NA release. The α7 nAChR-selective agonist choline evoked [3H]NA release (Emax = 33% of that of AnTx) that was blocked by GluR antagonists, supporting a model in which α7 nAChRs trigger glutamate release that subsequently stimulates [3H]NA release. A GABAergic component was also revealed: choline-evoked [3H]NA release was partially blocked by the GABAA receptor antagonist bicuculline, and coapplication of bicuculline and DNQX fully abolished this response. These findings support α7 nAChR on GABAergic neurons that can promote GABA release which, in turn, leads to [3H]NA release, probably by disinhibition. To investigate the impact of long-term nicotine exposure on this model, rats were exposed for 14 days to nicotine (4 mg/kg/day) with or without 3 or 7 days of withdrawal. α7 nAChR responses were selectively and transiently up-regulated after 3 days of withdrawal. This functional up-regulation could contribute to the withdrawal effects of nicotine.
16S/23S rRNA Intergenic Spacer Regions for Phylogenetic Analysis, Identification, and Subtyping ofBartonella Species

ABSTRACT Species of the genus Bartonella are currently recognized in growing numbers and are involved in an increasing variety of human diseases, mainly trench fever, Carrion's disease, bacillary angiomatosis, endocarditis, cat scratch disease, neuroretinitis, and asymptomatic bacteremia. Such a wide spectrum of infections makes it necessary to develop species and strain identification tools in order to perform phylogenetic and epidemiological studies. The 16S/23S rRNA intergenic spacer region (ITS) was sequenced for four previously untested species, B. vinsonii subsp. arupensis, B. tribocorum, B. alsatica, and B. koehlerae, as well as for 28 human isolates of B. quintana (most of them from French homeless people), six human or cat isolates of B. henselae, five cat isolates of B. clarridgeiae, and four human isolates of B. bacilliformis. Phylogenetic trees inferred from full ITS sequences of the 14 recognizedBartonella species using parsimony and distance methods revealed high statistical support, as bootstrap values were higher than those observed with other tested genes. Five well-supported lineages were identified within the genus and the proposed phylogenetic organization was consistent with that resulting from protein-encoding gene sequence comparisons. The ITS-derived phylogeny appears, therefore, to be a useful tool for investigating the evolutionary relationships of Bartonella species and to identifyBartonella species. Further, partial ITS amplification and sequencing offers a sensitive means of intraspecies differentiation of B. henselae, B. clarridgeiae, andB. bacilliformis isolates, as each strain had a specific sequence. The usefulness of this approach in epidemiological investigations should be highlighted. Among B. quintanastrains, however, the genetic heterogenity was low, as only three ITS genotypes were identified. It was nevertheless sufficient to show that the B. quintana population infecting homeless people in France was not clonal.
Study on the Effect of Porosity on the Reflection Coefficient and Wave Pressure on the Partially Perforated Plates

2D numerical wave flume is established based on the VOF method and k- model to numerically simulate the interaction of wave with perforated plates. The internal source generation of wave is applied in making wave area whose end is placed the sponge layer to absorb the reflection of wave. The numerical results of reflection coefficient before perforated plate are compared with the experimental results of reference (Liu, 2008) to verify the numerical method. By changing porosity, the effect of porosity on reflection coefficient can be analyzed. Moreover, the pressure difference between the outer and inner of perforated plate was studied, and then the mutual influence of porosity on the pressure difference is obtained according to the substantive numerical results.
Emotion Perception and Empathy: An Individual Differences Test of Relations

Numerous theories posit a positive relation between perceiving emotion expressed in the face of a stranger (emotion perception) and feeling or cognitively understanding the emotion of that person (affective and cognitive empathy, respectively). However, when relating individual differences in emotion perception with individual differences in affective or cognitive empathy, effect sizes are contradictory, but often not significantly different from zero. Based on 4 studies (study ns range from 97 to 486 persons; ntotal = 958) that differ from one another on many design and sample characteristics, applying advanced modeling techniques to control for measurement error, we estimate relations between affective empathy, cognitive empathy, and emotion perception. Relations are tested separately for each of the 6 basic emotions (an emotion-specific model) as well as across all emotions (an emotion-general model). Reflecting the literature, effect sizes and statistical significance with an emotion-general model vary across the individual studies (rs range from −.001 to .24 for emotion perception with affective empathy and −.01 to .39 for emotion perception with cognitive empathy), with a meta-analysis of these results indicating emotion perception is weakly related with affective (r = .13, p = .003) and cognitive empathy (r = .13, p = .05). Relations are not strengthened in an emotion-specific model. We argue that the weak effect sizes and inconsistency across studies reflects a neglected distinction of measurement approach—specifically, empathy is assessed as typical behavior and emotion perception is assessed as maximal effort—and conclude with considerations regarding the measurement of each construct.
Simple2Complex: Global Optimization by Gradient Descent

A method named simple2complex for modeling and training deep neural networks is proposed. Simple2complex train deep neural networks by smoothly adding more and more layers to the shallow networks, as the learning procedure going on, the network is just like growing. Compared with learning by end2end, simple2complex is with less possibility trapping into local minimal, namely, owning ability for global optimization. Cifar10 is used for verifying the superiority of simple2complex.
Primary hip replacement stem taper fracture due to corrosion in 3 patients

Wear and corrosion of taper connections in modular hip prostheses have gained much attention due to the serious biological response that can occur due to the metallic debris originating from this articulation (Pivec et al. 2014). This has been observed especially for metal-on-metal (MoM) bearing articulations with large-diameter heads (Gunther et al. 2013). The biological response is attributed to cobalt (Co) and chromium (Cr) ions originating from the female taper interface of the ball head, which is made of CoCr alloy (McGrory et al. 2015, Bishop et al. 2013). No mechanical implant failures (i.e. fractures) have been documented. In contrast, bi-modular primary and revision hip systems with necks and stems made of titanium-aluminium-vanadium alloy (Ti alloy) have shown fracture rates of up to 2.4% due to corrosion without any previous biological responses (Grupp et al. 2010, Norman et al. 2014). Taper fractures of primary Ti alloy THA stems with a modular head taper have not been reported in the literature, but major taper corrosion and material loss have been found for one design in particular (Witt et al. 2014). We present 3 cases of stem taper fracture as the ultimate failure mode of this design.
Differences by Gender, Ethnicity, and Acculturation in the Efficacy of the keepin’ it Real Model Prevention Program

This study examined whether the efficacy of keepin’ it REAL, a model program for substance use prevention in schools, was moderated by gender, ethnicity, and acculturation. Gender differences in program efficacy may arise through boys' higher risk of drug use, inadequate attention to girls' developmental issues, or cultural factors like polarized gender expectations. Data came from a randomized trial in 35 Phoenix, Arizona, middle schools involving 4,622 mostly Latino 7th graders. Using multi-level mixed models and multiple imputation missing techniques, results for the total sample showed no gender differences in program effects on recent substance use, but the program was more effective in fostering boys' than girls' anti-drug norms. Subgroup analyses demonstrated several more beneficial program effects for boys than girls (less alcohol and cigarette use and stronger anti-drug norms), but only among less acculturated Latinos. There were no gender differences in program effects among more acculturated Latinos, nor among non-Latino whites.
Dendritic cells

Dendritic cells are potent stimulators of immune responses against foreign antigens. Recent advances in this area include the delineation of distinct developmental pathways for different dendritic cell subsets; the emerging concept that one dendritic cell subset has regulatory functions that may contribute to induction of tolerance to self antigens; increased understanding of the interaction of dendritic cells with microbial products and viruses, such as HIV; and the application of dendritic cells for immunotherapy in certain cancers and possibly for the induction of transplantation tolerance.
Removal of adherent noises from image sequences by spatio-temporal image processing

This paper describes a method for removing adherent noises from image sequences. In outdoor environments, it is often the case that scenes taken by a camera are deteriorated because of adherent noises such as waterdrops on the surface of the lens-protecting glass of the camera. To solve this problem, our method takes advantage of image sequences captured with a moving camera. The method makes a spatio-temporal image to extract the regions of adherent noises by examining differences of track slopes in cross section images between adherent noises and other objects. Finally, regions of noises are eliminated by replacing with image data corresponding to object regions. Experimental results show the effectiveness of our method.
Distributional Lexical Entailment by Topic Coherence

Automatic detection of lexical entailment, or hypernym detection, is an important NLP task. Recent hypernym detection measures have been based on the Distributional Inclusion Hypothesis (DIH). This paper assumes that the DIH sometimes fails, and investigates other ways of quantifying the relationship between the cooccurrence contexts of two terms. We consider the top features in a context vector as a topic, and introduce a new entailment detection measure based on Topic Coherence (TC). Our measure successfully detects hypernyms, and a TC-based family of measures contributes to multi-way relation classification.
Asymmetric Pruning for Learning Cascade Detectors

Cascade classifiers are one of the most important contributions to real-time object detection. Nonetheless, there are many challenging problems arising in training cascade detectors. One common issue is that the node classifier is trained with a symmetric classifier. Having a low misclassification error rate does not guarantee an optimal node learning goal in cascade classifiers, i.e., an extremely high detection rate with a moderate false positive rate. In this work, we present a new approach to train an effective node classifier in a cascade detector. The algorithm is based on two key observations: 1) Redundant weak classifiers can be safely discarded; 2) The final detector should satisfy the asymmetric learning objective of the cascade architecture. To achieve this, we separate the classifier training into two steps: finding a pool of discriminative weak classifiers/features and training the final classifier by pruning weak classifiers which contribute little to the asymmetric learning criterion (asymmetric classifier construction). Our model reduction approach helps accelerate the learning time while achieving the pre-determined learning objective. Experimental results on both face and car data sets verify the effectiveness of the proposed algorithm. On the FDDB face data sets, our approach achieves the state-of-the-art performance, which demonstrates the advantage of our approach.
A Fast Approximation Algorithm for MIN-ONE SAT

In this paper, we propose a novel approximation algorithm (RelaxSAT) for MIN-ONE SAT. RelaxSAT generates a set of constraints from the objective function to guide the search. The constraints are gradually relaxed to eliminate the conflicts with the original Boolean SAT formula until a solution is found. The experiments demonstrate that RelaxSAT is able to handle very large instances which cannot be solved by existing MIN-ONE algorithms; furthermore, very tight bounds on the solution were obtained with one to two orders of magnitude speedup.
Further Investigations into Regular XORSAT

Recent years have witnessed rapid progress both in the foundations of and in applying state-of-art solvers for the propositional satisfiability problem (SAT). The study of sources for hard SAT instances is motivated by the need for interesting benchmarks for solver development and on the other hand by theoretical analysis of different proof systems. In this respect satisfiable instance families are especially interesting. In contrast to unsatisfiable instance families, there are few theoretical results for satisfiable formulas (Alekhnovich, Hirsch, & Itsykson); for the successful DPLL method, restricted heuristics need to be considered. While real-world problems serve as best benchmark instances in many sense, such instances are typically very large and unavailable in abundance. More “artificial” empirically hard satisfiable CNF families include (see references therein for more) regular random k-SAT (Boufkhad et al.), encodings of quasi-group completion (Achlioptas et al. 2000), XORSAT models inspired by statistical physics (Ricci-Tersenghi, Weight, & Zecchina 2001; Jia, Moore, & Selman 2005), and the regular XORSAT model (Haanpaa et al. 2006) motivated by expansion properties of random regular bipartite graphs. Experimental comparison with other available generators for notably hard satisfiable 3-CNF formulas shows that the regular XORSAT model gives extremely hard instances for state-of-the art clausal SAT solvers (Haanpaa et al. 2006). In this paper we generalize the regular XORSAT model for k > 3, and investigate how this relates to the hardness of the instances. By increasing the degree of the underlying regular constraint graphs, we observe a sharp increase in problem difficulty with respect to the number of variables, motivating further analysis of regular XORSAT.