Miracle-dz/UniFAR-FTUs huggingface dataset:
Multitouch Radial Menu Integrating Command Selection and Control of Arguments with up to 4 Degrees of Freedom

We design and evaluate a multitouch radial menu for large screens with two desirable properties. First, it allows a single gesture to select a command and then continuously control arguments for that command with unbroken kinesthetic tension. Second, arguments are controlled with 1 or 2 fingers for up to 4 degrees of freedom (DoF). For example, the user may select one command for 4 DoF direct manipulation (translation + scaling + rotation), or another command for 3 DoF camera operations (pan + zoom), using the same two-finger pinch gesture, but with different initial orientations of the gesture to disambiguate. We present a taxonomy to classify previous menuing techniques sharing the first property, and discuss how very few techniques have both of these properties. Our work also extends previous work by Banovic et al. in the following ways: our menu supports submenus and a fast default command, and we experimentally evaluate the effect of varying the number of rings in the menu, the symmetry of the menu, and the use of one hand vs. two hands vs. a stylus and hand.
Multivariate regular variation of heavy-tailed Markov Chains

The upper extremes of a Markov chain with regulary varying stationary marginal distribution are known to exhibit under general conditions a multiplicative random walk structure called the tail chain. More generally, if the Markov chain is allowed to switch from positive to negative extremes or vice versa, the distribution of the tail chain increment may depend on the sign of the tail chain on the previous step. But even then, the forward and backward tail chain mutually determine each other through a kind of adjoint relation. As a consequence, the finite-dimensional distributions of the Markov chain are multivariate regularly varying in a way determined by the back-and-forth tail chain. An application of the theory yields the asymptotic distribution of the past and the future of the solution to a stochastic difference equation conditionally on the present value being large in absolute value.
Road Segmentation of Unmanned Aerial Vehicle Remote Sensing Images Using Adversarial Network With Multiscale Context Aggregation

Semantic segmentation using adversarial networks has proved to be effective in image processing fields. However, two problems need to be solved in the field of the road segmentation of unmanned aerial vehicle (UAV) remote sensing images. One is the occupied proportion of road area in UAV remote sensing images; the other is that the constant size of convolutional kernel cannot deal with multiscale feature very well. To solve these two problems, this paper proposed a road segmentation model that combined the adversarial networks with multiscale context aggregation. First, the output feature-maps of three scales (0.5n, 1n, 2n) were obtained, based on an end-to-end training from image segmentation network. Second, after the convolution and deconvolution operations, the processed images were unified to the size scale of original images. Third, with the pixel-by-pixel addition method, the three scales of image feature (0.5n, 1n, 2n) were merged together, then inputted into the discriminative network. Finally, the errors were obtained and propagated backwards compared with the label, and then the parameters of a generative network and a discriminative network could be updated. Further, the segmented results were compared with those from normal adversarial networks, Linknet and D-linknet, and were developed with the morphological operation. The research results show that the proposed model can improve the precision of road segmentation from UAV images with multiscale context aggregation and the regularization property of adversarial networks.
Do political events a¤ect business cycles? The Maastricht treaty, the creation of the ECB and the euro economy

This paper provides some evidence on the e¤ect of the Maastricht treaty and the creation of the ECB on the dynamics of the European business cycles. With a panel VAR approach and quarterly data for seven European countries over the sample 1980:1-2004:4, the paper shows that: (i) an areawide cycle emerges in the 1990s; (ii) volatility, persistence and correlation of national cycles change over time, but not necessarily at the dates of the two political events; (iii) in an out-of-sample forecasting sense, neither event made a huge di¤erence of European business cycles. JEL classi cation: C15, C33, E32, E42
ULF magnetic emissions connected with under sea bottom earthquakes

Abstract. Measurements of ULF electromagnetic disturbances were carried out in Japan before and during a seismic active period (1 February 2000 to 26 July 2000). A network consists of two groups of magnetic stations spaced apart at a distance of ≈140 km. Every group consists of three, 3-component high sensitive magnetic stations arranged in a triangle and spaced apart at a distance of 4–7 km. The results of the ULF magnetic field variation analysis in a frequency range of F = 0.002–0.5 Hz in connection with nearby earth-quakes are presented. Traditional Z/G ratios (Z is the vertical component, G is the total horizontal component), magnetic gradient vectors and phase velocities of ULF waves propagating along the Earth’s surface were constructed in several frequency bands. It was shown that variations of the R(F) = Z/G parameter have a different character in three frequency ranges: F1 = 0.1 ± 0.005, F2 = 0.01 ± 0.005 and F3 = 0.005 ± 0.003 Hz. Ratio R(F3)/R(F1) sharply increases 1–3 days before strong seismic shocks. Defined in a frequency range of F2 = 0.01 ± 0.005 Hz during nighttime intervals (00:00–06:00 LT), the amplitudes of Z and G component variations and the Z/G ratio started to increase ≈ 1.5 months before the period of the seismic activity. The ULF emissions of higher frequency ranges sharply increased just after the seismic activity start. The magnetic gradient vectors (∇ B ≈ 1 – 5 pT/km), determined using horizontal component data (G ≈ 0.03 – 0.06 nT) of the magnetic stations of every group in the frequency range F = 0.05 ± 0.005 Hz, started to point to the future center of the seismic activity just before the seismoactive period; furthermore they continued following space displacements of the seismic activity center. The phase velocity vectors (V ≈ 20 km/s for F = 0.0067 Hz), determined using horizontal component data, were directed from the seismic activity center. Gradient vectors of the vertical component pointed to the closest seashore (known as the "sea shore" effect). The location of the seismic activity centers by two gradient vectors, constructed at every group of magnetic stations, gives an ≈ 10 km error in this experiment.
Uncovering the uncharacterized and unexpected: Unbiased phenotype‐driven screens in the mouse

Phenotype‐based chemical mutagenesis screens for mouse mutations have undergone a transformation in the past five years from a potential approach to a practical tool. This change has been driven by the relative ease of identifying causative mutations now that the complete genome sequence is available. These unbiased screens make it possible to identify genes, gene functions and processes that are uniquely important to mammals. In addition, because chemical mutagenesis generally induces point mutations, these alleles often uncover previously unappreciated functions of known proteins. Here we provide examples of the success stories from forward genetic screens, emphasizing the examples that illustrate the discovery of mammalian‐specific processes that could not be discovered in other model organisms. As the efficiency of sequencing and mutation detection continues to improve, it is likely that forward genetic screens will provide an even more important part of the repertoire of mouse genetics in the future. Developmental Dynamics 235:2412–2423, 2006. © 2006 Wiley‐Liss, Inc.
Analysis and optimization of novel post-processing method for myoelectric pattern recognition

This paper describes a novel post-processing step for an electromyogram (EMG) pattern classification algorithm that is used in the control of myoelectric prosthetic hands. Amputees often find it difficult to control multiple degrees of freedom, but increasing numbers of prosthetic hands have multiple degrees of freedom. In general, larger numbers of classes tend to reduce the classification accuracy, and artificial neural networks have been used in previous studies for EMG pattern classification. The proposed post-processing algorithm stores the temporal sequence of classifications from the EMG pattern classification algorithm, and then runs a second classification based on the sequential patterns. We compared the output accuracy before and after the post-processing step. In our experiment, we set the training time for the EMG pattern classification algorithm to 1 s for each class, and used three channels of surface EMG signals. We considered nine EMG pattern classes, and recorded the output every 10-20 ms. We then analyzed the proposed algorithm and found seven classes to be the number required for optimal performance. The overall accuracy of the proposed system was 90.0% for seven classes and 89.8% for nine classes. The classification accuracy improved by 12.5% when using seven classes, and by 21.2% when using nine classes. We believe that this level of classification accuracy and other elements (the number of EMG channels and the training time) are sufficient for practical use with prosthetic hands.
First principles based NEGF simulations of Si nanowire FETs

In this work, we have performed first-principles density functional theory (DFT) based, self-consistent device simulations for Si nanowire field effect transistors (NW FETs) of cross-section up to 3.24 nm. Through mode space transformation, non-orthogonal DFT Hamiltonian and overlap matrices are reduced in size from a few thousands to around one hundred. Ultra-efficient quantum-mechanical transport calculations in the non-equilibrium Green's function (NEGF) formalism in a nonorthogonal basis are therefore made possible.
Performance Monitoring in Virtual Organization Using Domain Driven Data Mining and Opinion Mining

Performance monitoring is the important problem of virtual organization which is geographical distributed. A virtual team is small variant is an organization network that is structured and managed to function as a complete organization. Unfairness can be more determined virtual organization in which geographically distributed. The papers aims to investigate the main factors that affect the performance of employees in IT industries by using domain driven data mining(D3M)approach and 360 degree feedback for objective measurement and opinion mining for subjective measurement and support vector machine(SVM) to classify the opinions collected.
A 1.8V 30nJ adaptive program-voltage (20V) generator for 3D-integrated NAND flash SSD

Decreasing power consumption is the key design issue of SSDs. A typical SSD consists of more than 16 NAND Flash memories, DRAMs and a NAND controller. Since the NAND write performance is 10MB/s [1,2], to raise the write speed of SSD to the level of HDD, 100MB/s, 8 or more NAND chips in SSD are simultaneously programmed. As the feature size decreases, the total bitline capacitance in a chip increases beyond 200nF. If 8 or more NAND chips operate in parallel, a large current of 800mA flows to charge the bitline capacitance in a sub-30nm SSD [3]. A good strategy to decrease the power is lowering the supply voltage, VDD, from 3.3 to 1.8V. Yet, at 1.8V, the power consumption of conventional charge pumps, used to generate the 20V program voltage, VPGM, drastically increases and the total power consumption of the NAND does not decrease, as shown in Fig. 13.2. 1(a). The charge-pump area more than doubles, which increases the NAND chip area by 5 to 10%. To overcome this problem, we implement a low-power program-voltage generator (PVG) using a boost converter with an adaptive-frequency and duty-cycle (AFD) controller.
Data placement in HPC architectures with heterogeneous off-chip memory

The performance of HPC applications is often bounded by the underlying memory system's performance. The trend of increasing the number of cores on a chip imposes even higher memory bandwidth and capacity requirements. The limitations of traditional memory technologies are pushing research in the direction of hybrid memory systems that, besides DRAM, include one or more modules based on some of the higher-density non-volatile memory technologies, where one of them will provide the required bandwidth, while the other will provide the required capacity for the application. This creates many challenges with data placement and migration policies between the modules of such hybrid memory system. In this paper, we propose an architecture with a hybrid memory design that places two technologically different memory modules in a flat address space. On such system, we evaluate several HPC workloads against different data placement and migration policies, compare their performance by means of execution time and the number of non-volatile memory writes, and consider how it can be applied to the future HPC architectures. Our results show that the hybrid memory system with dynamic page migration and limited DRAM capacity, can achieve performance that is comparable to a hypothetical, hard to implement, DRAM-only system.
Regulation of the mPTP by SIRT3-mediated deacetylation of CypD at lysine 166 suppresses age-related cardiac hypertrophy

Cardiac failure is a leading cause of age-related death, though its root cause remains unknown. Mounting evidence implicates a decline in mitochondrial function due to increased opening of the mitochondrial permeability transition pore (mPTP). Here we report that the NAD+-dependent deacetylase SIRT3 deacetylates the regulatory component of the mPTP, cyclophilin D (CypD) on lysine 166, adjacent to the binding site of cyclosporine A, a CypD inhibitor. Cardiac myocytes from mice lacking SIRT3 exhibit an age-dependent increase in mitochondrial swelling due to increased mPTP opening, a phenotype that is rescued by cyclosporine A. SIRT3 knockout mice show accelerated signs of aging in the heart including cardiac hypertrophy and fibrosis at 13 months of age. SIRT3 knockout mice are also hypersensitive to heart stress induced by transverse aortic constriction (TAC), as evidenced by cardiac hypertrophy, fibrosis, and increased mortality. Together, these data show for the first time that SIRT3 activity is necessary to prevent mitochondrial dysfunction and cardiac hypertrophy during aging and shed light on new pharmacological approaches to delaying aging and treating diseases in cardiac muscle and possibly other post-mitotic tissues.
A delay-dependent functional observer for linear time-invariant systems with input delay

A delay-dependent functional observer is designed for linear time-invariant (LTI) systems with time-varying input delay. Compared to delay-free observers, delay-dependent functional observers are less conservative and cover more systems. The designed functional observer is with minimum possible order (minimal). Necessary and sufficient conditions of the existence of the observer and asymptomatic stability of it are illustrated. The proposed observer is extended to multiple input delayed systems with time-varying delays. An algorithm is developed for designing of the minimal order observer based on the methodology of this paper. Two numerical examples and simulations are used to support our proposed methodology.
POSTER: On the anonymity of Israel's general elections

This work presents an attack on the privacy of some voting systems. We show that by combining information from several sources, some of it publicly available, and some of it can be easily collected ad-hoc, an adversary can greatly reduce the size of a voter's anonymity set. In many cases the obtained information is sufficient to deduce the content of a vote (or approximate a small set of possible values). As a test case, we present this attack in the context of the Israeli general parliamentary elections. Simulations we ran show that we can successfully determine the value of about 50% of the votes after observing three election systems.
The development of Model Predictive Control in automotive industry: A survey

Model Predictive Control (MPC) is an established control technique in chemical process control, due to its capability of optimally controlling multivariable systems with constraints on plant and actuators. In recent years, the advances in MPC algorithms and design processes, the increased computational power of electronic control units, and the need for improved performance, safety and reduced emissions, have drawn considerable interest in MPC from the automotive industry. In this paper we survey the investigations of MPC in the automotive industry with particular focus on the developments at Ford Motor Company. First, we describe the basic MPC techniques used in the automotive industry, and the early exploratory investigations. Then we present three applications that have been recently prototyped in fully functional production-like vehicles, highlighting the features that make MPC a good candidate strategy for each case. We finally present our perspectives on the next challenges and future applications of MPC in the automotive industry.
Arp2/3 Complex and Actin Depolymerizing Factor/Cofilin in Dendritic Organization and Treadmilling of Actin Filament Array in Lamellipodia

The leading edge (∼1 μm) of lamellipodia in Xenopus laevis keratocytes and fibroblasts was shown to have an extensively branched organization of actin filaments, which we term the dendritic brush. Pointed ends of individual filaments were located at Y-junctions, where the Arp2/3 complex was also localized, suggesting a role of the Arp2/3 complex in branch formation. Differential depolymerization experiments suggested that the Arp2/3 complex also provided protection of pointed ends from depolymerization. Actin depolymerizing factor (ADF)/cofilin was excluded from the distal 0.4 μm of the lamellipodial network of keratocytes and in fibroblasts it was located within the depolymerization-resistant zone. These results suggest that ADF/cofilin, per se, is not sufficient for actin brush depolymerization and a regulatory step is required. Our evidence supports a dendritic nucleation model (Mullins, R.D., J.A. Heuser, and T.D. Pollard. 1998. Proc. Natl. Acad. Sci. USA. 95:6181–6186) for lamellipodial protrusion, which involves treadmilling of a branched actin array instead of treadmilling of individual filaments. In this model, Arp2/3 complex and ADF/cofilin have antagonistic activities. Arp2/3 complex is responsible for integration of nascent actin filaments into the actin network at the cell front and stabilizing pointed ends from depolymerization, while ADF/cofilin promotes filament disassembly at the rear of the brush, presumably by pointed end depolymerization after dissociation of the Arp2/3 complex.
An novel two layer user identification method

This paper proposed a two layer authorization mechanism, including traditional password system and rhythm recognition. The whole system includes two phases: preprocessing and usual operation for users. In preprocessing phase, users type password in a specific rhythm in order to record and analyse the characteristics of behaviour of users. In the second phase, how to verify a user in usual operation is described. The main recognition procedure consists of two stages: password check and rhythm recognition separately. User shall input correct password in correct rhythm. Here rhythm is a sequence of beats with various time intervals in between. The beat is in correspondent with every key down event. In the authorization procedure, system will check ID and password first. At the same time, system will record all time intervals of key down events. After recording all time intervals, system compares the characteristics of the resultant rhythm with that in user database. If the distance is under some threshold of error tolerance, user will be authorized. Otherwise, entering system will not be approved. The proposed two layer authorization method successfully enhances the security and efficiency of password system. The proposed distance calculation enables our calculation to be much cost effective than that of other rhythm recognition methods.
Usability Evaluations of a Wearable Inertial Sensing System and Quality of Movement Metrics for Stroke Survivors by Care Professionals

Background Inertial motion capture systems are used in many applications such as measuring the movement quality in stroke survivors. The absence of clinical effectiveness and usability evidence in these assistive technologies into rehabilitation has delayed the transition of research into clinical practice. Recently, a new inertial motion capture system was developed in a project, called INTERACTION, to objectively measure the quality of movement (QoM) in stroke survivors during daily-life activity. With INTERACTION, we are to be able to investigate into what happens with patients after discharge from the hospital. Resulting QoM metrics, where a metric is defined as a measure of some property, are subsequently presented to care professionals. Metrics include for example: reaching distance, walking speed, and hand distribution plots. The latter shows a density plot of the hand position in the transversal plane. The objective of this study is to investigate the opinions of care professionals in using these metrics obtained from INTERACTION and its usability. Methods By means of a semi-structured interview, guided by a presentation, presenting two patient reports. Each report includes several QoM metric (like reaching distance, hand position density plots, shoulder abduction) results obtained during daily-life measurements and in clinic and were evaluated by care professionals not related to the project. The results were compared with care professionals involved within the INTERACTION project. Furthermore, two questionnaires (5-point Likert and open questionnaire) were handed over to rate the usability of the metrics and to investigate if they would like such a system in their clinic. Results Eleven interviews were conducted, where each interview included either two or three care professionals as a group, in Switzerland and The Netherlands. Evaluation of the case reports (CRs) by participants and INTERACTION members showed a high correlation for both lower and upper extremity metrics. Participants were most in favor of hand distribution plots during daily-life activities. All participants mentioned that visualizing QoM of stroke survivors over time during daily-life activities has more possibilities compared to current clinical assessments. They also mentioned that these metrics could be important for self-evaluation of stroke survivors. Discussion The results showed that most participants were able to understand the metrics presented in the CRs. For a few metrics, it remained difficult to assess the underlying cause of the QoM. Hence, a combination of metrics is needed to get a better insight of the patient. Furthermore, it remains important to report the state (e.g., how the patient feels), its surroundings (outside, inside the house, on a slippery surface), and detail of specific activities (does the patient grasps a piece of paper or a heavy cooking pan but also dual tasks). Altogether, it remains a questions how to determine what the patient is doing and where the patient is doing his or her activities.