Miracle-dz/UniFAR-FTUs huggingface dataset:
Piecewise sparse linear classification via factorized asymptotic bayesian inference

Piecewise sparse linear regression models using factorized asymptotic Bayesian inference (a.k.a. FAB/HME) have recently been employed in practical applications in many industries as a core algorithm of the Heterogeneous Mixture Learning technology. Such applications include sales forecasting in retail stores, energy demand prediction of buildings for smart city, parts demand prediction to optimize inventory, and so on. This paper extends FAB/HME for classification and conducts the following two essential improvements. First, we derive a refined version of factorized information criterion which offers a better approximation of Bayesian marginal log-likelihood. Second, we introduce an analytic quadratic lower bounding technique in an EM-like iterative optimization process of FAB/HME, which drastically reduces computational cost. Experimental results show that advantages of our piecewise sparse linear classification over state-of-the-art piecewise linear models.
Delayed coalescence of surfactant containing sessile droplets

When two sessile drops of the same liquid touch, they merge into one drop, driven by capillarity. However, the coalescence can be delayed, or even completely stalled for a substantial period of time, when the two drops have different surface tensions, despite being perfectly miscible. A temporary state of non-coalescence arises, during which the drops move on their substrate, only connected by a thin neck between them. Existing literature covers pure liquids and mixtures with low surface activities. In this paper, we focus on the case of large surface activities, using aqueous surfactant solutions with varying concentrations. It is shown that the coalescence behavior can be classified into three regimes that occur for different surface tensions and contact angles of the droplets at initial contact. However, not all phenomenology can be predicted from surface tension contrast or contact angles alone, but strongly depends on the surfactant concentrations as well. This reveals that the merging process is not solely governed by hydrodynamics and geometry, but also depends on the molecular physics of surface adsorption.
Multiscreen Patterns – Interactions Across the Borders of Devices

Abstract Design patterns are solutions for common design problems used in a number of fields including architecture, software development and user experience design. We compiled a pattern library for the usage of gesture-enabled interactions between different devices with screens, the so called multiscreen context. This library provides simple and intuitive gestures for connecting and disconnecting devices wirelessly as well as gestures for the exchange of data between these devices, like swiping a document from one’s tablet to the tablets of the surrounding colleagues in the same room. The library is the result of a 2.5 years running project in cooperation with three small and medium companies. We compiled the library by conducting an intense literature survey in parallel with several iterations of practical software projects in the multiscreen context. The literature survey inspired the practice-oriented project work. Being involved in software projects enabled us to identify challenges in the design and implementation of the gesture set. Therefore, we generated valuable insight for a comprehensive description of gestural interactions. With our set of patterns, we aim to support interaction designers to choose the appropriate gesture for their given context. The patterns serve as inspiration by showing the different possibilities but also provide guidance how to design and implement a selected gesture for a given context. They help designing the details of an interaction by breaking it down into its smallest parts. To support the developers of these interactions our pattern descriptions are enriched with an Android library containing lifecycle events and the necessary gesture recognition logic. This paper provides an overview of the pattern library. In addition, the structure and the usage of the library is described in more detail with the means of one sample pattern. The pattern library is openly accessible.
Efficient Channel Estimator With Angle-Division Multiple Access

Massive multiple input multiple output (M-MIMO) is an enabling technology of 5G wireless communication. The performance of an M-MIMO system is highly dependent on the speed and accuracy of obtaining the channel-state information. The computational complexity of channel estimation for an M-MIMO system can be reduced by making use of the sparsity of the M-MIMO channel. In this paper, we propose the hardware-efficient channel estimator based on angle-division multiple access for the first time. Preamble, uplink, and downlink training are also implemented. For further hardware-efficiency consideration, optimization regarding quantization and approximation strategies has been discussed. Implementation techniques, such as pipelining and systolic processing, are also employed for hardware regularity. Numerical results and field-programmable gate array implementation have demonstrated the advantages of the proposed channel estimator.
Optimal placement and active vibration control for piezoelectric smart flexible manipulators using modal H2 norm

The optimal placement and active vibration control for piezoelectric smart single flexible manipulator are investigated in this study. Based on the assumed mode method and Hamilton’s principle, the dynamic equation of the piezoelectric smart single flexible manipulator is established. Then, the singular perturbation method is adopted and the coupled dynamic equation is decomposed into slow (rigid) and fast (flexible) subsystems. After that, the couple optimal placement criterion of piezoelectric actuators is proposed on the base of modal H2 norm of the fast subsystem and the change rate of natural frequencies. Using an improved particle swarm optimization algorithm, the optimal placement of piezoelectric actuators is realized. Subsequently, in order to verify the validity and feasibility of the presented optimal placement criterion, the composite controller is designed for the active vibration control of the piezoelectric smart single flexible manipulator. Finally, numerical simulations and experiments are presented. The results demonstrate that the piezoelectric smart single flexible manipulator system has a better single modal controllability and observability and has a good result on the vibration suppression using the optimization results of actuators. The proposed optimal placement criterion and method are feasible and effective.
Voluntarily controlled but not merely observed visual feedback affects postural sway

Online stabilization of human standing posture utilizes multisensory afferences (e.g., vision). Whereas visual feedback of spontaneous postural sway can stabilize postural control especially when observers concentrate on their body and intend to minimize postural sway, the effect of intentional control of visual feedback on postural sway itself remains unclear. This study assessed quiet standing posture in healthy adults voluntarily controlling or merely observing visual feedback. The visual feedback (moving square) had either low or high gain and was either horizontally flipped or not. Participants in the voluntary-control group were instructed to minimize their postural sway while voluntarily controlling visual feedback, whereas those in the observation group were instructed to minimize their postural sway while merely observing visual feedback. As a result, magnified and flipped visual feedback increased postural sway only in the voluntary-control group. Furthermore, regardless of the instructions and feedback manipulations, the experienced sense of control over visual feedback positively correlated with the magnitude of postural sway. We suggest that voluntarily controlled, but not merely observed, visual feedback is incorporated into the feedback control system for posture and begins to affect postural sway.
ESTIMATING AR PARAMETER-SETS FOR LINEAR-RECURRENT SIGNALS IN CONVOLUTIVE MIXTURES

This article investigates a theoretical basis for estimating autoregressive (AR) processes for linear-recurrent signals in convolutive mixtures. Whitening of such signals is sometimes a problem in multichannel blind equalization which is intended to extract the original signals even if the signals are of a convolutive mixture type. This whitening is due to inverse-filtering which deconvolves the AR processes that generate the linear-recurrent signals. To avoid this excessive deconvolution, it is effective to remove the contributions of such processes from the inverse-filters. Unfortunately, no method seems to have been able to extract the AR parameter-sets for respective signals included in convolutive mixtures.
Conditional approximate message passing with side information

In information theory, side information (SI) is often used to increase the efficiency of communication systems. This work lays the framework for a class of Bayes-optimal signal recovery algorithms referred to as conditional approximate message passing (CAMP) that make use of available SI. CAMP involves a linear inverse problem, where noisy, linear measurements acquire an unknown input vector using a measurement matrix with independent and identically distributed entries, and the SI vector obeys a symbol-wise dependence with the input. Despite having a simple and straightforward derivation, our CAMP algorithm obtains lower mean squared error than other signal recovery algorithms that have been proposed to incorporate SI. The good performance of CAMP is due its Bayes-optimality properties, which are not present in previous approaches to SI-aided signal recovery.
Estimating intraspecific genetic diversity from community DNA metabarcoding data

Background DNA metabarcoding is used to generate species composition data for entire communities. However, sequencing errors in high-throughput sequencing instruments are fairly common, usually requiring reads to be clustered into operational taxonomic units (OTUs), losing information on intraspecific diversity in the process. While Cytochrome c oxidase subunit I (COI) haplotype information is limited in resolving intraspecific diversity it is nevertheless often useful e.g. in a phylogeographic context, helping to formulate hypotheses on taxon distribution and dispersal. Methods This study combines sequence denoising strategies, normally applied in microbial research, with additional abundance-based filtering to extract haplotype information from freshwater macroinvertebrate metabarcoding datasets. This novel approach was added to the R package “JAMP” and can be applied to COI amplicon datasets. We tested our haplotyping method by sequencing (i) a single-species mock community composed of 31 individuals with 15 different haplotypes spanning three orders of magnitude in biomass and (ii) 18 monitoring samples each amplified with four different primer sets and two PCR replicates. Results We detected all 15 haplotypes of the single specimens in the mock community with relaxed filtering and denoising settings. However, up to 480 additional unexpected haplotypes remained in both replicates. Rigorous filtering removes most unexpected haplotypes, but also can discard expected haplotypes mainly from the small specimens. In the monitoring samples, the different primer sets detected 177–200 OTUs, each containing an average of 2.40–3.30 haplotypes per OTU. The derived intraspecific diversity data showed population structures that were consistent between replicates and similar between primer pairs but resolution depended on the primer length. A closer look at abundant taxa in the dataset revealed various population genetic patterns, e.g. the stonefly Taeniopteryx nebulosa and the caddisfly Hydropsyche pellucidula showed a distinct north–south cline with respect to haplotype distribution, while the beetle Oulimnius tuberculatus and the isopod Asellus aquaticus displayed no clear population pattern but differed in genetic diversity. Discussion We developed a strategy to infer intraspecific genetic diversity from bulk invertebrate metabarcoding data. It needs to be stressed that at this point this metabarcoding-informed haplotyping is not capable of capturing the full diversity present in such samples, due to variation in specimen size, primer bias and loss of sequence variants with low abundance. Nevertheless, for a high number of species intraspecific diversity was recovered, identifying potentially isolated populations and taxa for further more detailed phylogeographic investigation. While we are currently lacking large-scale metabarcoding datasets to fully take advantage of our new approach, metabarcoding-informed haplotyping holds great promise for biomonitoring efforts that not only seek information about species diversity but also underlying genetic diversity.
Distributional Prediction of Human Driving Behaviours using Mixture Density Networks

Confident predictions of human driving behaviours are necessary in designing safe and efficient control policies for autonomous vehicles. A better understanding of how human drivers react to their surrounding may avoid the design of overly-conservative control policies which require greater cost (e.g., time, traffic flow disruption) to achieve their objective. In this paper, we explore ways to learn distributions over human driver actions that are typical of a highway setting. We use actions filtered from Next Generation SIMulation (NGSIM) vehicle trajectory data gathered on the US 101 highway as training data for a Recurrent Neural Network. In particular, we use a Mixture Density Network (MDN) model to represent predicted driver actions as a Gaussian Mixture Model. We present and discuss exploratory results on the filtering of the raw NGSIM data and design of the MDN model.
Calcium and Nuclear Signaling in Prostate Cancer

Recently, there have been a number of developments in the fields of calcium and nuclear signaling that point to new avenues for a more effective diagnosis and treatment of prostate cancer. An example is the discovery of new classes of molecules involved in calcium-regulated nuclear import and nuclear calcium signaling, from the G protein-coupled receptor (GPCR) and myosin families. This review surveys the new state of the calcium and nuclear signaling fields with the aim of identifying the unifying themes that hold out promise in the context of the problems presented by prostate cancer. Genomic perturbations, kinase cascades, developmental pathways, and channels and transporters are covered, with an emphasis on nuclear transport and functions. Special attention is paid to the molecular mechanisms behind prostate cancer progression to the malignant forms and the unfavorable response to anti-androgen treatment. The survey leads to some new hypotheses that connect heretofore disparate results and may present a translational interest.
Influence of Musical Enculturation on Brain Responses to Metric Deviants

The ability to recognize metric accents is fundamental in both music and language perception. It has been suggested that music listeners prefer rhythms that follow simple binary meters, which are common in Western music. This means that listeners expect odd-numbered beats to be strong and even-numbered beats to be weak. In support of this, studies have shown that listeners exposed to Western music show stronger novelty and incongruity related P3 and irregularity detection related mismatch negativity (MMN) brain responses to attenuated odd- than attenuated even-numbered metric positions. Furthermore, behavioral evidence suggests that music listeners' preferences can be changed by long-term exposure to non-Western rhythms and meters, e.g., by listening to African or Balkan music. In our study, we investigated whether it might be possible to measure effects of music enculturation on neural responses to attenuated tones on specific metric positions. We compared the magnetic mismatch negativity (MMNm) to attenuated beats in a “Western group” of listeners (n = 12) mainly exposed to Western music and a “Bicultural group” of listeners (n = 13) exposed for at least 1 year to both Sub-Saharan African music in addition to Western music. We found that in the “Western group” the MMNm was higher in amplitude to deviant tones on odd compared to even metric positions, but not in the “Bicultural group. ” In support of this finding, there was also a trend of the “Western group” to rate omitted beats as more surprising on odd than even metric positions, whereas the “Bicultural group” seemed to discriminate less between metric positions in terms of surprise ratings. Also, we observed that the overall latency of the MMNm was significantly shorter in the Bicultural group compared to the Western group. These effects were not biased by possible differences in rhythm perception ability or music training, measured with the Musical Ear Test (MET). Furthermore, source localization analyses suggest that auditory, inferior temporal, sensory-motor, superior frontal, and parahippocampal regions might be involved in eliciting the MMNm to the metric deviants. These findings suggest that effects of music enculturation can be measured on MMNm responses to attenuated tones on specific metric positions.
Bleeding detection in wireless capsule endoscopy images based on color invariants and spatial pyramids using support vector machines

Wireless capsule endoscopy (WCE) is a revolutionary imaging technique that enables detailed inspection of the interior of the whole gastrointestinal tract in a non-invasive way. However, viewing WCE videos is a very time-consuming, and labor intensive task for physicians. In this paper, we propose an automatic method for bleeding detection in WCE images. A novel series of descriptors which combine color and spatial information is designed in a way that local and global features are also incorporated together. And a kernel based classification method using histogram intersection or chi-square is deployed to verify the performance of the proposed descriptors. Experiments demonstrate that the proposed kernel based scheme is very effective in detecting bleeding patterns of WCE images.
Selected mechanical and physical properties of boron filaments

Abstract : Results are presented from an investigation to characterize boron filament with respect to selected mechanical and physical properties. The investigation of 12 different filaments included examination by metallographic techniques and the determination of mechanical properties over the temperature range from room temperature to 2500 deg F (1644 deg K) in argon, air, and vacuum. The study was primarily concerned with the properties of individual boron filaments produced by the deposition of boron on the surface of a fine tungsten substrate wire from a vapor composed of hydrogen and a boron halide compound. These filaments exhibited an average room-temperature strength of 350 ksi (2.42 GN/sq meters) and retained approximately two-thirds of this strength at temperatures up to 2000 deg F (1366 deg K). The range of scatter among individual tensile strength values was generally equal to the mean value of strength. An average Young's modulus value of 60 x 10(exp 3) ksi (414 GN/sq meters) was recorded.
Towards efficient and scalable visual homing

Visual homing describes the ability of a robot to autonomously return to its starting position along a previously traversed path using visual information. In this paper, we propose a method for visual homing that is solely based on bearing angles to landmarks. During the first traversal of a path, the robot creates a sequence of viewframes, which are rotationally aligned landmark angle configurations at certain locations. While homing, the robot calculates homing vectors which subsequently align the currently perceived set of landmark observations with the reference viewframe until the home location is reached. This paper discusses methods for homing vector calculation and proposes new methods which are more robust and yield straighter homing paths in non-isotropic landmark distributions and false landmark matches. Furthermore, we present the Trail-Map, which is a novel data structure for storing a sequence of viewframes in a non-redundant and scalable way. The Trail-Map exploits the fact that the bearing angles to both distant landmarks and landmarks in the direction of movement hardly change when the robot moves, whereas close landmarks change their bearing angles quickly. Thus, the Trail-Map enables easy downscaling by deleting observations that correspond to nearby, fast-changing landmarks and, thus, retains the stable, translation invariant landmark information. We demonstrate the memory efficiency and scalability of the data structure in simulations and in real-world indoor and outdoor experiments. This makes the proposed method for visual homing suitable for mobile robots with limited computational and memory resources.
Consumption of a plant sterol-based spread derived from rice bran oil is effective at reducing plasma lipid levels in mildly hypercholesterolaemic individuals

To establish the effectiveness of a new phytosterol-containing spread derived from rice bran oil (RBO), a randomised, double-blind, cross-over human clinical trial was conducted over 12 weeks. A total of eighty mildly hypercholesterolaemic (total blood cholesterol level ≥ 5 and ≤ 7·5 mmol/l with a serum TAG level of ≤ 4·5 mmol/l) individuals were randomised into two groups (n 40). Group 1 consumed spread only daily for 4 weeks. They were randomised to consume 20 g RBO spread (RBOS), 20 g standard spread (SS) or 20 g phytosterol-enriched spread (PS). After a 4-week period, individuals changed to the next randomised treatment until all three treatments had been consumed. Group 2 consumed spread plus oil daily for 4 weeks. They consumed 20 g RBOS plus 30 ml RBO, 20 g SS plus 30 ml sunflower oil or 20 g RBOS. Blood samples were collected for the analysis of lipid parameters, and 3 d diet records were collected. Compared with SS, RBOS significantly reduced total cholesterol by 2·2 % (P = 0·045), total cholesterol:HDL by 4·1 % (P = 0·005) and LDL-cholesterol by 3·5 % (P = 0·016), but was not as effective overall as PS, which reduced total cholesterol by 4·4 % (P = 0·001), total cholesterol:HDL by 3·4 % (P = 0·014) and LDL-cholesterol by 5·6 % (P = 0·001). In group 2, the addition of RBO to the RBOS produced no differences in cholesterol levels. These results confirm that RBOS is effective in lowering serum cholesterol when consumed as part of a normal diet.