Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive haptic rendering for time‐varying haptic and video frame rates in multi‐modal interactions

In multi‐modal interactions including haptics, problems such as input sensor noise, temporal mismatch between graphics and haptics, and non‐constant refresh rates may cause non‐smooth force/torque display. This paper proposes temporal smoothing technique for haptic interaction using a sensing glove in multi‐modal applications. The proposed technique employs two processes: (1) a noise reduction method is applied to reduce jitter noise at the sensors in the sensing glove and (2) an adaptive force extrapolation is applied for time‐varying haptic and video frame rates. To demonstrate the performance of the proposed method, we developed a test platform to assess a simple box model and relatively complex models such as gamephone, portable media player (PMP). It was subsequently demonstrated that the proposed method can support smooth haptic interactions in multi‐modal applications where a haptic device and a sensing glove are used. Copyright © 2009 John Wiley & Sons, Ltd.
Digital Signatures from Challenge-Divided Σ-Protocols

Digital signature is one of the basic primitives in cryptography. A common paradigm of obtaining signatures, known as the Fiat-Shamir (FS) paradigm, is to collapse any Σ-protocol (which is 3-round public-coin honest-verifier zero-knowledge) into a non-interactive scheme with hash functions that are modeled to be random oracles (RO). The Digital Signature Standard (DSS) and Schnorr’s signature schemes are two salient examples following the FS-paradigm. In this work, we present a modified Fiat-Shamir paradigm, named challenge-divided Fiat-Shamir paradigm, which is applicable to a variant of Σ-protocol with divided random challenges. This new paradigm yields a new family of (online/offline efficient) digital signatures from challenge-divided Σ-protocols, including in particular a variant of Schnorr’s signature scheme called challenge-divided Schnorr signature. We then present a formal analysis of the challenge-divided Schnorr signature in the random oracle model. Finally, we give comparisons between the challenge-divided Schnorr signature and DSS and Schnorr’s signature, showing that the newly developed challenge-divided Schnorr signature can enjoy better (online/offline) efficiency (besides provable security in the random oracle model). Of independent interest is a new forking lemma, referred to as divided forking lemma, for dealing with multiple ordered rewinding points in the RO model, which is of independent interest and can be applied to analyzing other cryptographic schemes in the RO model.
Immune Activation Markers in Peripartum Women in Botswana: Association with Feeding Strategy and Maternal Morbidity

Hormone levels shift the immune state in HIV-uninfected pregnant and breastfeeding women away from Th1 responses and toward regulation to permit fetal tolerance. Limited data exist on inflammation during pregnancy or postpartum in HIV-infected women, though certain inflammatory markers are associated with adverse health outcomes among HIV-infected persons. We measured hsCRP, D-dimer, IFN-γ, IL-6, IL-10 and TNF-α at 34 weeks gestation and six months postpartum in HIV-infected women from the Botswana Mashi PMTCT trial who were randomized to breastfeeding or formula-feeding. Differences in inflammatory markers between gestation and postpartum periods, and by randomized feeding method, were estimated using generalized estimating equations, adjusting for baseline plasma HIV-1 viral load, CD4 count, calendar time, and antiretroviral treatment status. Additionally, we studied the association between marker concentrations at six months postpartum and major adverse clinical events over the following 4.5 years, using case-cohort sampling and adjusted Cox proportional hazards models. In 86 breastfeeding and 75 formula-feeding women, hsCRP and D-dimer decreased significantly between 34 weeks gestation and six months postpartum, while IFN-γ increased. There was no significant association between inflammatory marker change and randomized feeding method after adjusting for multiple comparisons and removing outliers. In univariate analysis, TNF-α, D-dimer, and IFN-γ concentrations at six months postpartum were significant predictors of subsequent clinical events, and TNF-α remained significant in multivariate analysis (HR = 4.16, p = 0.001). In young HIV-infected women in Botswana inflammatory marker concentrations did not differ significantly between women who breast- vs. formula-fed. However, postpartum TNF-α level was predictive of subsequent adverse clinical event.
TIM-3 Dictates Functional Orientation of the Immune Infiltrate in Ovarian Cancer

Purpose: In multiple oncological settings, expression of the coinhibitory ligand PD-L1 by malignant cells and tumor infiltration by immune cells expressing coinhibitory receptors such as PD-1, CTLA4, LAG-3, or TIM-3 conveys prognostic or predictive information. Conversely, the impact of these features of the tumor microenvironment on disease outcome among high-grade serous carcinoma (HGSC) patients remains controversial. Experimental Design: We harnessed a retrospective cohort of 80 chemotherapy-naïve HGSC patients to investigate PD-L1 expression and tumor infiltration by CD8+ T cells, CD20+ B cells, DC-LAMP+ dendritic cells as well as by PD-1+, CTLA4+, LAG-3+, and TIM-3+ cells in relation with prognosis and function orientation of the tumor microenvironment. IHC data were complemented with transcriptomic and functional studies on a second prospective cohort of freshly resected HGSC samples. In silico analysis of publicly available RNA expression data from 308 HGSC samples was used as a confirmatory approach. Results: High levels of PD-L1 and high densities of PD-1+ cells in the microenvironment of HGSCs were strongly associated with an immune contexture characterized by a robust TH1 polarization and cytotoxic orientation that enabled superior clinical benefits. Moreover, PD-1+TIM-3+CD8+ T cells presented all features of functional exhaustion and correlated with poor disease outcome. However, although PD-L1 levels and tumor infiltration by TIM-3+ cells improved patient stratification based on the intratumoral abundance of CD8+ T cells, the amount of PD-1+ cells failed to do so. Conclusions: Our data indicate that PD-L1 and TIM-3 constitute prognostically relevant biomarkers of active and suppressed immune responses against HGSC, respectively.
Quality-aware mobile graphics workload characterization for energy-efficient DVFS design

Contemporary mobile platforms use mobile GPUs for graphics-intensive applications, and deploy proprietary Dynamic Voltage Frequency Scaling (DVFS) policies in an attempt to save energy without sacrificing quality. However, there have been no previous systematic studies to correlate the performance, power, and energy efficiency of mobile GPUs based on diverse graphics workloads to enable more efficient mobile platform DVFS policies for energy savings. For the first time we present a study of mobile GPU graphics workload characterization for DVFS design considering user experience and energy efficiency on a real smart-phone. We develop micro-benchmarks that stress specific stages of the graphics pipeline separately, and study the relationship between varying graphics workloads and resulting energy and performance of different mobile graphics pipeline stages. We use these results to outline opportunities for more efficient, integrated DVFS policies across the mobile GPU, memory and CPU hardware components for saving energy without sacrificing user experience. Our experimental results on the Nexus 4 smartphone show that it is important to characterize GPU hardware and graphics workloads accurately in order to achieve increased energy efficiency without degradation in graphics performance for better user experience. We believe that our observations and results will enable more energy-efficient DVFS algorithms for mobile graphics rendering in the face of rapidly changing mobile GPU architectures.
A Structural and Process Analysis of the Implicit Association Test

Abstract The Implicit Association Test (IAT) is based on the observation that participants find it easier to respond in the same way to exemplars of two concepts when these concepts are similar (e.g., “positive” and “flower”) compared to when the concepts are dissimilar (e.g., “positive” and “insect”). In the first part of this article, I argue that the IAT is structurally similar to stimulus–response compatibility tasks. On the basis of this analogy, I then present two response conflict accounts of IAT effects. The data of an experiment that was designed to test these accounts showed that IAT effects reflect attitudes toward the target concepts rather than attitudes toward the individual exemplars of those concepts. The results shed light on the processes that underlie IAT effects, suggest that automatic attitude activation may depend on the construal of the object that is fostered by the context, and clarify the relation between different indirect measures of attitudes.
Diclofenac-Derived Hybrids for Treatment of Actinic Keratosis and Squamous Cell Carcinoma

In this work, hybrid compounds 1–4 obtained by conjugation of the non-steroidal anti-inflammatory drug diclofenac, with natural molecules endowed with antioxidant and antiproliferative activity were prepared. The antiproliferative activity of these hybrids was evaluated on immortalized human keratinocyte (HaCaT) cells stimulated with epidermal growth factor (EGF), an actinic keratosis (AK) model, and on human squamous cell carcinoma (SCC) cells (A431). Hybrid 1 presented the best activity in both cell models. Self-assembling surfactant nanomicelles have been chosen as the carrier to drive the hybrid 1 into the skin; the in vitro permeation through and penetration into pig ear skin have been evaluated. Among the nanostructured formulations tested, Nano3Hybrid20 showed a higher tendency of the hybrid 1 to be retained in the skin rather than permeating it, with a desirable topical and non-systemic action. On these bases, hybrid 1 may represent an attractive lead scaffold for the development of new treatments for AK and SCC.
Equivariant Cyclic Cohomology of Hopf Module Algebras

We define an equivariant K 0-theory for Yetter-Drinfeld algebras over a Hopf algebra with an invertible antipode. We show that there exists a pairing, generalizing Connes' pairing, between this theory and a suitably defined Hopf algebra equivariant cyclic cohomology theory.
Application of graph combinatorics to rational identities of type A

To a word $w$, we associate the rational function $\Psi_w = \prod (x_{w_i} - x_{w_{i+1}})^{-1}$. The main object, introduced by C. Greene to generalize identities linked to the Murnaghan-Nakayama rule, is a sum of its images by certain permutations of the variables. The sets of permutations that we consider are the linear extensions of oriented graphs. We explain how to compute this rational function, using the combinatorics of the graph $G$. We also establish a link between an algebraic property of the rational function (the factorization of the numerator) and a combinatorial property of the graph (the existence of a disconnecting chain).
Directed test suite augmentation via exploiting program dependency

Regression testing is a practice to discover faults introduced in the program modification. However, the existing test suite is usually designed at an early stage of software development and is therefore insensitive to subsequent program changes. Although symbolic execution such as JPF-SE is able to produce test cases for the modified program by exhaustively exploring program paths, it is not tailored for testing program changes and is not scalable. In this paper, we propose an efficient approach called Directed Test Suite Augmentation (DTSA) to automatically generate test cases that can reach the changed statements, produce different program states after executing the changed statements, and propagate the different states to the output of the program. The key insight of DTSA is to reorder the generated test cases tailored for testing program changes compared with JPF-SE. We implemented a prototype of our approach and the experiment results show that DTSA requires about 60.1% and 45.6% fewer Dynamic Symbolic Execution (DSE) runs to generate the desired test case than JPF-SE and another test suite augmentation tool eXpress, respectively.
Alternative Splicing of a β4 Subunit Proline-Rich Motif Regulates Voltage-Dependent Gating and Toxin Block of Cav2.1 Ca2+ Channels

Ca2+ channel β subunits modify α1 subunit gating properties through direct interactions with intracellular linker domains. In a previous report (Helton and Horne, 2002), we showed that alternative splicing of the β4 subunit had α1 subunit subtype-specific effects on Ca2+ channel activation and fast inactivation. We extend these findings in the present report to include effects on slow inactivation and block by the peptide toxin ω-conotoxin (CTx)-MVIIC. N-terminal deletion and site-directed mutagenesis experiments revealed that the effects of alternative splicing on toxin block and all aspects of gating could be attributed to a proline-rich motif found within N-terminal β4b amino acids 10–20. Interestingly, this motif is conserved within the third postsynaptic density-95 (PSD-95)/Discs large/zona occludens-1 domain of the distantly related membrane-associated guanylate kinase homolog, PSD-95. Sequence identity of ∼30% made possible the building of β4a and β4bthree-dimensional structural models using PSD-95 as the target sequence. The models (1) reveal that alternative splicing of the β4 N terminus results in dramatic differences in surface charge distribution and (2) localize the proline-rich motif of β4b to an extended arm structure that flanks what would be the equivalent of a highly modified PSD-95 carboxylate binding loop. Northern blot analysis revealed a markedly different pattern of distribution for β4a versus β4bin the human CNS. Whereas β4a is distributed throughout evolutionarily older regions of the CNS, β4b is concentrated heavily in the forebrain. These results raise interesting questions about the functional role that alternative splicing of the β4 subunit has played in the evolution of complex neural networks.
CaverDock: a molecular docking-based tool to analyse ligand transport through protein tunnels and channels

MOTIVATION Protein tunnels and channels are key transport pathways that allow ligands to pass between proteins' external and internal environments. These functionally important structural features warrant detailed attention. It is difficult to study the ligand binding and unbinding process experimentally, while molecular dynamics simulations can be time-consuming and computationally demanding. RESULTS CaverDock is a new software tool for analysing the ligand passage through the biomolecules. The method uses the optimised docking algorithm of AutoDock Vina for ligand placement docking and implements a parallel heuristic algorithm to search the space of possible trajectories. The duration of the simulations takes from minutes to a few hours. Here we describe the implementation of the method and demonstrate CaverDock's usability by: i) comparison of the results with other available tools, ii) determination of the robustness with large ensembles of ligands and iii) the analysis and comparison of the ligand trajectories in engineered tunnels. Thorough testing confirms that CaverDock is applicable for the fast analysis of ligand binding and unbinding in fundamental enzymology and protein engineering. AVAILABILITY User guide and binaries for Ubuntu are freely available for non-commercial use at https://loschmidt.chemi. muni.cz/caverdock/. The web implementation is available at https://loschmidt.chemi. muni.cz/caverweb/. The source code is available on request. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Convergent evolution of the lateral line system in Apogonidae (Teleostei: Percomorpha) determined from innervation

The lateral line system and its innervation were examined in two species of the family Apogonidae (Cercamia eremia [Apogoninae] and Pseudamia gelatinosa [Pseudamiinae]). Both species were characterized by numerous superficial neuromasts (SNs; total 2,717 in C. eremia; 9,650 in P. gelatinosa), including rows on the dorsal and ventral halves of the trunk, associated with one (in C. eremia) and three (in P. gelatinosa) reduced trunk canals. The pattern of SN innervation clearly demonstrated that the overall pattern of SN distribution had evolved convergently in the two species. In C. eremia, SN rows over the entire trunk were innervated by elongated branches of the dorsal longitudinal collector nerve (DLCN) anteriorly and lateral ramus posteriorly. In P. gelatinosa, the innervation pattern of the DLCN was mirrored on the ventral half of the trunk (ventral longitudinal collector nerve: VLCN). Elongated branches of the DLCN and VLCN innervated SN rows on the dorsal and ventral halves of the trunk, respectively. The reduced trunk canal(s) apparently had no direct relationship with the increase of SNs, because these branches originated deep to the lateral line scales, none innervating canal neuromast (CN) homologues on the surface of the scales. In P. gelatinosa, a CN (or an SN row: CN homologue) occurred on every other one of their small lateral line scales, while congeners (P. hayashii and P. zonata) had an SN row (CN homologue) on every one of their large lateral line scales.
Representation Learning for Clustering: A Statistical Framework

We address the problem of communicating domain knowledge from a user to the designer of a clustering algorithm. We propose a protocol in which the user provides a clustering of a relatively small random sample of a data set. The algorithm designer then uses that sample to come up with a data representation under which $k$-means clustering results in a clustering (of the full data set) that is aligned with the user's clustering. We provide a formal statistical model for analyzing the sample complexity of learning a clustering representation with this paradigm. We then introduce a notion of capacity of a class of possible representations, in the spirit of the VC-dimension, showing that classes of representations that have finite such dimension can be successfully learned with sample size error bounds, and end our discussion with an analysis of that dimension for classes of representations induced by linear embeddings.
Multiple downy mildew effectors target the stress‐related NAC transcription factor LsNAC069 in lettuce

Summary To cause disease in lettuce, the biotrophic oomycete Bremia lactucae secretes potential RxLR effector proteins. Here we report the discovery of an effector‐target hub consisting of four B. lactucae effectors and one lettuce protein target by a yeast‐two‐hybrid (Y2H) screening. Interaction of the lettuce tail‐anchored NAC transcription factor, LsNAC069, with B. lactucae effectors does not require the N‐terminal NAC domain but depends on the C‐terminal region including the transmembrane domain. Furthermore, in Y2H experiments, B. lactucae effectors interact with Arabidopsis and potato tail‐anchored NACs, suggesting that they are conserved effector targets. Transient expression of RxLR effector proteins BLR05 and BLR09 and their target LsNAC069 in planta revealed a predominant localization to the endoplasmic reticulum. Phytophthora capsici culture filtrate and polyethylene glycol treatment induced relocalization to the nucleus of a stabilized LsNAC069 protein, lacking the NAC‐domain (LsNAC069Δ NAC ). Relocalization was significantly reduced in the presence of the Ser/Cys‐protease inhibitor TPCK indicating proteolytic cleavage of LsNAC069 allows for relocalization. Co‐expression of effectors with LsNAC069Δ NAC reduced its nuclear accumulation. Surprisingly, LsNAC069 silenced lettuce lines had decreased LsNAC069 transcript levels but did not show significantly altered susceptibility to B. lactucae. In contrast, LsNAC069 silencing increased resistance to Pseudomonas cichorii bacteria and reduced wilting effects under moderate drought stress, indicating a broad role of LsNAC069 in abiotic and biotic stress responses.
Towards compressing SLAM maps for 6 D relocalisation

We develop and evaluate a novel data compression strategy for visual SLAM centered on traveled trajectory analysis. Beyond compressing scene structure based purely on geometrical information as commonly done, we aim at developing representations that are useful for re-exploration, that use low memory footprint and low CPU computation. Our work is evaluated on data collected from a visual sensor and exploits the information intrinsic to the trajectory of exploration together with the visual information of map points. We perform rigorous statistical evaluation and Pareto analysis to show how this approach compares with a traditional keyframe-based data representation and the compromises achievable in terms of compression rate and relocalisation success.
Joint Tensor Factorization and Outlying Slab Suppression With Applications

We consider factoring low-rank tensors in the presence of outlying slabs. This problem is important in practice, because data collected in many real-world applications, such as speech, fluorescence, and some social network data, fit this paradigm. Prior work tackles this problem by iteratively selecting a fixed number of slabs and fitting, a procedure which may not converge. We formulate this problem from a group-sparsity promoting point of view, and propose an alternating optimization framework to handle the corresponding ℓp (0 <; p ≤ 1) minimization-based low-rank tensor factorization problem. The proposed algorithm features a similar per-iteration complexity as the plain trilinear alternating least squares (TALS) algorithm. Convergence of the proposed algorithm is also easy to analyze under the framework of alternating optimization and its variants. In addition, regularization and constraints can be easily incorporated to make use of a priori information on the latent loading factors. Simulations and real data experiments on blind speech separation, fluorescence data analysis, and social network mining are used to showcase the effectiveness of the proposed algorithm.
Sound spotting – an approach to content-based sound retrieval

We present an approach to content-based sound retrieval using auditory models, self-organizing neural networks, and string matching techniques. It addresses the issues of spotting perceptually similar occurrences of a particular sound event in an audio document. After introducing the problem and the basic approach we describe the individual stages of the system and give references to additional literature. The third section of the paper summarizes the preliminary experiments involving auditory models and self-organizing maps we carried out so far, and the final discussion reflects on the overall concept and suggests further directions.