Miracle-dz/UniFAR-FTUs huggingface dataset:
Translates into Technology : The Case of Self-Assembled Monolayers , Electron-BeamWriting , and Carbon

Asdescribed in this issue of ACS Nano, the scheme of Angelova et al., from Bielefeld, Ulm, Mainz, and Frankfurt, first assembles thiol-containing molecules on gold surfaces, then cross-links them by electron irradiation before release of the resulting membranes from the substrate and (optional) subsequent thermal treatment to yield thin carbon “graphene” sheets. The paper is the latest in a series dating back to the demonstration of crosslinking in self-assembled monolayers (SAMs) by electron irradiation in 1999 and their release to form free-standing membranes in 2005. The key new point in this paper is the replication of the molecular arrangement in the SAMs;as controlled by the selection of the individual molecules themselves from a wide-ranging possible library;into the morphology of the resulting membranes and sheets, so that, for example, regular arrays of pores can be produced in the membranes. In this Perspective, we set in context the two research areas that are combined together in this membrane production scheme: (i) SAMs, including new insights into their detailed atomic structures, and (ii) electron-beam writing and atomic manipulation in adsorbed molecular (as opposed to polymer) layers. We also consider (iii) issues affecting further development of thin membrane production, such as nanopore production. An underlying theme is the richness of the pool of nanoscience research, which technologists can now dip into at will. Self-Assembled Monolayers. The first step in making carbon nanomembranes (CNMs) involves the assembly of aromatic thiol molecules on gold substrates into densely packed, self-assembled monolayers. This is an important step because the number of carbon atoms per unit area can be controlled by selection of the appropriate molecular precursor. The natural tendency of the thiol molecules to form a dense molecular layer with a regular structure also ensures that the carbon atoms are uniformly distributed over the surface and, hence, leads to the uniform thickness of the final CNM. An interesting aspect of CNM formation from SAMs is that the structural and functional properties of the SAMs can be passed on to the CNMs. Since SAMs can exist in a range of structural phases on Au(111), a high degree of control over the * Address correspondence to r.e. palmer@bham.ac. uk.
Real-time 3D fire simulation using a spring-mass model

We present a method for real-time simulation of 3D fire inspired by an old mechanical trick known as the "silk torch". Motivated by the proven illusive effect of silk torch, we model the kinematics of flames by a mass-spring system and its turbulent visual dynamics by texture sequencing with variable speeds and transparencies that depend on the speed of the vaporized fuel. The approach allows for incorporating external forces such as the gravity, and the wind force for added realism. Also, a specific characteristic of our method is that any object inserted in aflame can be modeled simply as an external force in the mass-spring system, making real-time interactions with fire a simple addition to the overall system. While the approach maintains an extremely low computational cost, these flexibilities increase the realism of our 3D fire by allowing for real-time control and the interactivity, which is a highly desirable requirement in applications such as augmented reality
Dynamics of a Vibratory Feeder

Proceedings of DETC'97 1997 ASME Design Engineering Technical Conferences September 14-17, 1997, Sacramento, California DETC97/VIB-3905 DYNAMICS OF A VIBRATORY FEEDER Peter Wolfsteiner Lehrstuhl B fur Mechanik Technische Universitat Munchen 85747 Garching Germany Email: wolfst@lbm.mw. tu-muenchen.de Friedrich Pfei er Lehrstuhl B fur Mechanik Technische Universitat Munchen 85747 Garching Germany Email: pfei er@lbm.mw. tu-muenchen.de ABSTRACT The most common devices used to feed small parts in an automatic assembly framework are vibratory feeders. They are used to store, feed, orientate and isolate the parts. Due to the complex mechanics of the feeding process the design of the feeders is still depending on trial and error. This paper presents a complete dynamical model of the transportation process including unilateral constraints and multiple impacts, both with coulomb friction. Some simulation results, computed with a three dimensional model, explain the practical bene t of the proposed tool.
Power saving for multiple MEMS-based devices by probabilistic data partition

This paper considers an optimization problem for minimizing the power consumption of MEMS-based devices. We first map the time-consuming problem from the integer space Zn to the Euclidean space Rn and employ a gradient-based method to solve the mapped problem in Rn. The great strength of the proposed method lies in its linear convergence. Experimental results show that significant energy can be saved by shutting down as many unnecessary MEMS-based devices as possible. The results also suggest that other similar optimization problems can be solved by the same way.
A Study on the Cell Sectorization Using the Wide-beam and Narrow-beam for CDMA Mobile Communication Systems

Cell sectorization and improvement of the Ec/Io are technologies to offer good quality of services (QoS) and coverage for new and sophisticated power control to achieve high capacity in CDMA cellular mobile communication networks. In this paper, in order to efficient cell sector and to improve the Ec/Io of the pilot channel in CDMA mobile communication systems, I analyze and compare the wide- beam three sector cell (WTSC) with the narrow-beam three sector cell (NTSC) as a method for cell sectorization. The NTSC method was compared with the WTSC method, using the results of both a theoretical analysis and a simulation, in order to examine its effectiveness and validity. As a result, I confirm that efficient cell sector method to minimize interference from adjacent base stations and to increase cell coverage.
Protective effect of yoghurt consumption on Helicobacter pylori seropositivity in a Mexican population

Abstract Objective The aim of the study was to determine the relationship between fermented and unfermented dairy product consumption and Helicobacter pylori seropositivity in a Mexican population. Design Dietary interviews were conducted as part of a population-based case–control study in 2005. Serum was obtained for each participant to determine H. pylori seropositivity status. Adjusted odds ratios were estimated from multivariate logistic regression models. Setting Mexico City, Mexico. Subjects A random sample of 464 healthy adult residents. Results The overall seroprevalence of H. pylori in the study sample was 75.4%. In fully adjusted models, compared with those who did not consume yoghurt, there was a protective effect of eating up to one serving per week of yoghurt and more than one serving per week of yoghurt (odds ratio (OR) = 0.57, 95% confidence interval (CI) 0.35–0.94 and OR = 0.45, 95% CI 0.24–0.86, respectively), with a P for trend of 0.01. There were no effects for the consumption of unfermented dairy products (milk and cheese). Conclusions This study suggests that yoghurt consumption may have a protective effect against H. pylori seropositivity. Additional studies are needed to determine whether consumption of yoghurt or other fermented dairy products can prevent or eradicate H. pylori infection.
China’s Financial System: Opportunities and Challenges

We provide a comprehensive review of China's financial system, and explore directions of future development. First, the financial system has been dominated by a large banking sector. In recent years banks have made considerable progress in reducing the amount of non-performing loans and improving their efficiency. Second, the role of the stock market in allocating resources in the economy has been limited and ineffective. We discuss issues related to the further development of China's stock market and other financial markets. Third, the most successful part of the financial system, in terms of supporting the growth of the overall economy, is a non-standard sector that consists of alternative financing channels, governance mechanisms, and institutions. The co-existence of this sector with banks and markets can continue to support the growth of the Hybrid Sector (non-state, non-listed firms). Finally, among the policies that will help to sustain stable economic growth in China are those that reduce the likelihood of damaging financial crises, including a banking sector crisis, a real estate or stock market crash, and a "twin crisis" in the currency market and banking sector.
Real-time trajectory generation for car-like vehicles navigating dynamic environments

This paper presents Tiji, a trajectory generation scheme, ie an algorithm that computes a feasible trajectory between a start and a goal state, for a given robotic system. Tiji is geared towards complex dynamic systems subject to differential constraints, such as wheeled vehicles, and its efficiency warrants it can be used in real-time. Above all, Tiji is able to compute a trajectory that reaches the goal state at a prescribed final time in order to avoid collision with the moving objects of the environment. The method proposed, which relies upon a parametric trajectory representation, is variational in nature. The trajectory parameters are incrementally updated in order to optimize of a cost function involving the distance between the end of the trajectory computed and the (goal state, final time) pair. Should the goal state be unreachable (if the final time is ill-chosen), the method returns a trajectory that ends as close as possible to the (goal state, final time) pair, which can be useful in certain applications.
Exploiting temporal idleness to reduce leakage power in programmable architectures

One of the biggest challenges that programmable devices like FPGAs are facing in ultra deep sub-micron regime is the exponential rise in leakage power consumption. As technology shrinks below 90nm, a new design paradigm has to evolve to tackle the issue of leakage power consumption. In this work we focus on a new design methodology for reducing leakage power by exploiting temporal locality in designs and accordingly group them into clusters that can be switched on and off. We propose a power state controller based method, which controls the switching of the clusters from one state to another. We show our technique using data flow graphs where temporal locality can be effectively explored. Our results show that substantial leakage savings can be achieved if temporal idleness of designs can be exploited effectively.
Computing Optimal Cycle Mean in Parallel on CUDA

Computation of optimal cycle mean in a directed weighted graph has many applications in program analysis, performance verification in particular. In this paper we propose a data-parallel algorithmic solution to the problem and show how the computation of optimal cycle mean can be efficiently accelerated by means of CUDA technology. We show how the problem of computation of optimal cycle mean is decomposed into a sequence of data-parallel graph computation primitives and show how these primitives can be implemented and optimized for CUDA computation. Finally, we report a fivefold experimental speed up on graphs representing models of distributed systems when compared to best sequential algorithms.
Ameliorative Effects of Herbal Combinations in Hyperlipidemia

The roots of Glycyrrhiza glabra, Withania somnifera, Asparagus racemosus, and Chlorophytum borivilianum and seeds of Sesamum indicum are ayurvedic medicinal plants used in India to treat several ailments. Our previous studies indicated that these plants possess hypolipidemic and antioxidant potential. The present study was aimed at investigating the composite effects of these plants on hypercholesterolemic rats. Three different combinations (5 gm%, given for four weeks) used in this study effectively reduced plasma and hepatic lipid profiles and increased fecal excretion of cholesterol, neutral sterol, and bile acid along with increasing the hepatic HMG-CoA reductase activity and bile acid content in hypercholesterolemic rats. Further, all three combinations also improved the hepatic antioxidant status (catalase, SOD, and ascorbic acid levels) and plasma total antioxidant capacity with reduced hepatic lipid peroxidation. Overall, combination I had the maximum effect on hypercholesterolemic rats followed by combinations II and III due to varying concentrations of the different classes of phytocomponents.
A Sampling Schema for Rapidly Exploring Random Trees using a Guiding Path

In this paper, a novel sampling schema for Rapidly Exploring Random Trees (RRT) is proposed to address the narrow passage issue. The introduced method employs a guiding path to steer the tree growth towards a given goal. The main idea of the proposed approach stands in a preference of the sampling of the configuration space C along a given guiding path instead of sampling of the whole space. While for a lowdimensional C the guiding path can be found as a geometric path in the robot workspace, such a path does not provide useful information for efficient sampling of a high-dimensional C. We propose an iterative scaling approach to find a guiding path in such high-dimensional configuration spaces. The approach starts with a scaled geometric model of the robot to a fraction of its original size for which a guiding path is found using the RRT algorithm. Then, such a path is iteratively used in the proposed RRT-Path algorithm for a larger robot up to its original size. The experimental results indicate benefit of the proposed technique in significantly higher ratio of the successfully found feasible paths in comparison to the state-of-the-art RRT algorithms.
NII, Japan at the first THUMOS Workshop 2013

We submit the results of our system to the THUMOS’13 Challenge on Recognition Task. We apply a multi-modal approach to recognize actions on UCF101 dataset. These features include Dense Trajectories (motion features), SIFT (image features) and MFCC (audio features). Moreover, we also use the Fisher vector encoding, which is a state-of-theart feature representation on popular image classification and action recognition datasets. 1. Classification Framework
Parents and Children Who Are Estranged in Adulthood: A Review and Discussion of the Literature.

This review examines what is known about estrangement between parents and their adult children in terms of definition, prevalence, causes, and consequences. Estrangement has been defined and conceptualised in different ways, although most definitions have focused on the negative quality of the relationship and the voluntarily or intentional decision of at least one family member to initiate and maintain distance. A diverse range of factors which are often interlinked has been found to contribute to estrangement. The consequences of estrangement from a parent or child include experiencing reduced levels of psychological well-being, feelings of loss, and experiences and/or perceptions of stigma. The estrangement literature has the potential to reveal variation in the quality of parent-child relationships in adulthood so that family scholars can move beyond our assumptions and understand family relationships as they are, rather than how they could or ‘should’ be.
Exemplar-Based Sparse Representation for Language Recognition on I-Vectors

In this paper, a new automatic language identification method using sparse representation on i-vectors in low-dimensional total variability space is proposed. It is mainly based on the recently proposed i-vector based language recognition systems. In our proposed method, an over-complete dictionary is first constructed by randomly sampling of the low-dimensional total variability space after Within-Class Covariance Normalization (WCCN) and Linear Discriminate Analysis (LDA). And then for each test sample, the classification score is derived from sparse linear representation with respect to the over-complete dictionary. Furthermore, a random subspace method, which combines different sparse representation classifiers, is introduced to address the possible over-fitting issue. Evaluations on NIST LRE 2007 dataset show that the proposed method outperforms the state-of-the-art i-vector based language recognition system. Especially for 30s test condition, our proposed method achieves relative reduction of 29.6% on Equal Error Rate (EER) compared with the baseline system.
Preferential Cytoplasmic Localization of δ-Opioid Receptors in Rat Striatal Patches: Comparison with Plasmalemmal μ-Opioid Receptors

The activation of δ-opioid receptors (DORs) in the caudate-putamen nucleus (CPN) produces regionally distinct changes in motor functions, many of which are also influenced by opioids active at μ-opioid receptors (MORs). These actions most likely occur in MOR-enriched patch compartments in the CPN. To determine the functional sites for DOR activation and potential interactions involving MOR in these regions, immunoperoxidase and immunogold–silver labeling methods were applied reversibly for the ultrastructural localization of DOR and MOR in single rat brain sections containing patches of the CPN. DOR immunoreactivity was commonly seen within the cytoplasm of spiny and aspiny neurons, many of which also expressed MOR. In dendrites and spines, DOR labeling was preferentially localized to membranes of the smooth endoplasmic reticulum and spine apparatus, whereas MOR showed a prominent plasmalemmal distribution. DOR- and/or MOR-labeled spines received asymmetric, excitatory synapses, some of which showed notable perforations, suggesting the involvement of these receptors in activity-dependent synaptic plasticity. DORs were more frequently detected than were MORs within axon terminals that formed either asymmetric synapses with spine heads or symmetric synapses with spine necks. Our results suggest that in striatal patches, DORs, often in cooperation with MORs, play a direct modulatory role in controlling the postsynaptic excitability of spines, whereas presynaptic neurotransmitter release onto spines is mainly influenced by DOR activation. In comparison with MOR, the prevalent association of DOR with cytoplasmic organelles that are involved in intracellular trafficking of cell surface proteins suggests major differences in availability of these receptors to extracellular opioids.
On networking and computing environments' integration: A novel mobile cloud resources provisioning approach

Mobile/wireless networking and cloud computing are nowadays revolutionizing the ways of communication and computation and the newly founded Mobile Cloud Computing (MCC) research area is inspired by the notion of complete networking and computing environments' integration. As a result, efficient MCC resource management frameworks should simultaneously take into consideration both: a) wireless/radio access resources pool aiming at always-best connectivity contexts and b) computing resources pool for data processing/storage aiming at flexible virtualized infrastructure sharing solutions. In this paper, we propose a Mobile Cloud Resources Provisioning (MCRP) scheme, which is flexible enough to adapt to the various general MCC reference use cases being described. The main novelty feature of the employed MCC Service Admission Control algorithm lies in the fact that it jointly handles radio and computing resources rather than confronting the problem as two independent resource management sub-problems. The performance of MCRP scheme is evaluated via simulation results showing that the assumed context-aware service admission control policies can lead to efficient mobile cloud resources provisioning outcomes.
A CAUTIONARY NOTE ON SCALING VARIABLES THAT APPEAR ONLY IN PRODUCTS IN ORDINARY LEAST SQUARES

Variables may be used as products in a regression model to correct or adjust for the effects of other variables. Such variables may be transformed to become indices; for example, to be constrained to be between 0 and 1. We provide a theoretical and a practical demonstration that the choice of transformation can affect the statistical significance of tests associated with estimates of effects and coefficients unless the variables are included in the model as well as their products. This is the strong-heredity principle of Nelder (1988). We demonstrate the effects with a case study of the middle-infrared correction to the Normalized Difference Vegetation Index to improve predictions of leaf area index.
Edinburgh Research Explorer Learning an Inverse Rig Mapping for Character Animation

We propose a general, real-time solution to the inversion of the rig function - the function which maps animation data from a charac-ter’s rig to its skeleton. Animators design character movements in the space of an animation rig, and a lack of a general solution for mapping motions from the skeleton space to the rig space keeps the animators away from the state-of-the-art character animation meth-ods, such as those seen in motion editing and synthesis. Our so-lution is to use non-linear regression on sparse example animation sequences constructed by the animators, to learn such a mapping ofﬂine. When new example motions are provided in the skeleton space, the learned mapping is used to estimate the rig space values that reproduce such a motion. In order to further improve the precision, we also learn the derivative of the mapping, such that the movements can be ﬁne-tuned to exactly follow the given motion. We test and present our system through examples including full-body character models, facial models and deformable surfaces. With our system, animators have the freedom to attach any motion synthesis algorithms to an arbitrary rigging and animation pipeline, for immediate editing. This greatly improves the productivity of 3D animation, while retaining the ﬂexibility and creativity of artistic input.
Understanding the Performance of Statistical MT Systems: A Linear Regression Framework

We present a framework for the analysis of Machine Translation performance. We use multivariate linear models to determine the impact of a wide range of features on translation performance. Our assumption is that variables that most contribute to predict translation performance are the key to understand the differences between good and bad translations. During training, we learn the regression parameters that better predict translation quality using a wide range of input features based on the translation model and the first-best translation hypotheses. We use a linear regression with regularization. Our results indicate that with regularized linear regression, we can achieve higher levels of correlation between our predicted values and the actual values of the quality metrics. Our analysis shows that the performance for in-domain data is largely dependent on the characteristics of the translation model. On the other hand, out-of domain data can benefit from better reordering strategies.
An optimal multigrid algorithm for continuous state discrete time stochastic control

The application of multigrid methods to a class of discrete-time, continuous-state, discounted, infinite-horizon dynamic programming problems is studied. The authors analyze the computational complexity of computing the optimal cost function to within a desired accuracy of epsilon , as a function of epsilon and the discount factor alpha . Using an adversary argument, they obtain lower bound results on the computational complexity for this class of problems. They also provide a multigrid version of the successive approximation algorithm whose requirements are (as a function of alpha and epsilon ) within a constant factor from the lower bounds when a certain mixing condition is satisfied. Hence the algorithm is optimal. <<ETX>>