Miracle-dz/UniFAR-FTUs huggingface dataset:
Emotion research and AI: Some theoretical and technical issues *

This paper describes an approach that uses interactive computer games as an experimental setting for the study of emotion, behavior, and nonverbal communication. In the first, more technical part, we present a method that allows to automatically code facial behavior of a subject playing a computer game. In this procedure, facial behavior is registered automatically with the aid of small plastic dots which are affixed to pre-defined regions of the subjects face. The resulting dot patterns are then classified with an artificial neural network. In the second part of the article, we discuss the theoretical framework of our experimental approach. In this view, the computer game provides a relatively simple but complete context - a microworld in the sense of Toda’s 'Fungus Eater' - for the interpretation of the internal emotional and cognitive regulatory processes. In the third part, we contrast the empirical work with a synthetic approach where we can use the theoretical assumptions and the empirical data to model an autonomous agent as an emotional problemsolver.
Efficient blind speech separation suitable for embedded devices

A blind speech separation method with a low computational complexity is proposed. This method consists of a combination of independent component analysis with frequency band selection, and a frame-wise spectral softmask method based on an inter-channel power ratio of tentative separated signals in the frequency domain. The softmask cancels the transfer function between sources and separated signals. A theoretical analysis is given. Performance and effectiveness are evaluated via source separation simulations and a computational estimate, and experimental results show the significantly improved performance of the proposed method. The segmental signal-to-noise ratio achieves 7 [dB] and 3 [dB], and the cepstral distortion achieves 1 [dB] and 2.5 [dB], in anechoic and reverberant conditions, respectively. Moreover, there can be a reduction of over 80% in computational complexity compared with unmodified FDICA.
The optimal parameter combination for vehicle detection from worldview-2 imagery

Vehicle detection and traffic flow parameters extraction from high resolution imagery have been popular research topics in recent years. Object-based image analysis, with the aid of commercial eCognition® software, has become a widely implemented method for vehicle detection and identification. In the process, the determination of optimal segmentation parameters is of crucial importance for the accuracy of vehicle detection and classification. In this study, we obtained the optimal parameter combination for vehicle detection by a “trial-and-error” strategy using road subsets as sample clipped from WorldView-2 imagery. A better vehicle detect result would be obtained easily in 0.5m resolution images when the scale value was 30, the shape value was set to 0.4, and the compactness value was kept constant as 0.5. At the same time, an obvious tendency was also revealed that the segmentation accuracy of vehicles tended to descend gradually holding the scale value constant with the increasing of shape value, and the accuracy descended sharply when the shape value was larger than 0.5; it was also descending generally holding the shape value constant with the increasing of scale value. The experiment results can be applied directly to the vehicle detection from the same resolution images with similar vehicle size and would also be a useful reference for quick setting of original parameters in other conditions.
Journal of Neuroscience Methods Automated Three-dimensional Detection and Counting of Neuron Somata

Keywords: Neuron counting Neuron density NeuN GAD67 Ca 2+-sensitive dye Two-photon Widefield a b s t r a c t We present a novel approach for automated detection of neuron somata. A three-step processing pipeline is described on the example of confocal image stacks of NeuN-stained neurons from rat somato-sensory cortex. It results in a set of position landmarks, representing the midpoints of all neuron somata. In the first step, foreground and background pixels are identified, resulting in a binary image. It is based on local thresholding and compensates for imaging and staining artifacts. Once this pre-processing guarantees a standard image quality, clusters of touching neurons are separated in the second step, using a marker-based watershed approach. A model-based algorithm completes the pipeline. It assumes a dominant neuron population with Gaussian distributed volumes within one microscopic field of view. Remaining larger objects are hence split or treated as a second neuron type. A variation of the processing pipeline is presented, showing that our method can also be used for co-localization of neurons in multi-channel images. As an example, we process 2-channel stacks of NeuN-stained somata, labeling all neurons, counterstained with GAD67, labeling GABAergic interneurons, using an adapted pre-processing step for the second channel. The automatically generated landmark sets are compared to manually placed counterparts. A comparison yields that the deviation in landmark position is negligible and that the difference between the numbers of manually and automatically counted neurons is less than 4%. In consequence, this novel approach for neuron counting is a reliable and objective alternative to manual detection.
Evolvement of Malmquist Index Study: The Case of Chinese Iron and Steel Industry

Many methods can be used to measure the efficiency of companies, among which DEA-based Malmquist productivity index is the one that can measure the productivity change over different periods. This paper not only presents a new interpretation along with the managerial implication of each Malmquist component and identifies the strategy shifts of individual DMU based upon isoquant changes, but also further generalizes the known study. Traditional study mostly focus on the conditions that one decision making unit lies on the productivity frontier; omitting the case several units are efficient. The present study advances the known method, and evaluates the cases several units lie on the productivity frontier. Furthermore, this paper studies productivity growth, efficiency change, and technical progress of a sample of 23 iron and steel enterprises which are all listed companies and included in top 500 corporations of China after 2000. The results indicate that different iron and steel corporations, although in different magnitudes, have recorded significant productivity gains driven mostly by scale efficiency increases rather than technical progress. Efficiency increases, however, were mostly owing to improved scales rather than improved resource management practices.
Frequency-Tunable Low- $Q$ Lumped-Element Resonator Bandstop Filter With High Attenuation

This paper presents a new lumped-element absorptive bandstop filter topology. It exhibits infinite attenuation at the center frequency and no reflection regardless of the quality factor (Q-factor) of the resonators. The new topology exhibits the absorptive characteristic with extremely low-Q resonators, whereas an absorptive bandstop filter topology in the literature cannot be used for such resonators. This superiority of the new filter topology is verified by comparing it with the topology in the literature. The filter designed using the new topology can change its center frequency by tuning only the capacitor values of the resonators. A 1.6:1 frequency tuning range maintaining the absorptive characteristic has been obtained by measurement.
CD133 Is Not Suitable Marker for Isolating Melanoma Stem Cells from D10 Cell Line

Objective Cutaneous melanoma is the most hazardous malignancy of skin cancer with a high mortality rate. It has been reported that cancer stem cells (CSCs) are responsible for malignancy in most of cancers including melanoma. The aim of this study is to compare two common methods for melanoma stem cell enriching; isolating based on the CD133 cell surface marker and spheroid cell culture. Materials and Methods In this experimental study, melanoma stem cells were enriched by fluorescence activated cell sorting (FACS) based on the CD133 protein expression and spheroid culture of D10 melanoma cell line,. To determine stemness features, the mRNA expression analysis of ABCG2, c-MYC, NESTIN, OCT4-A and -B genes as well as colony and spheroid formation assays were utilized in unsorted CD133+, CD133- and spheroid cells. Significant differences of the two experimental groups were compared using student’s t tests and a two-tailed value of P<0.05 was statistically considered as a significant threshold. Results Our results demonstrated that spheroid cells had more colony and spheroid forming ability, rather than CD133+ cells and the other groups. Moreover, melanospheres expressed higher mRNA expression level of ABCG2, c-MYC, NESTIN and OCT4-A com- pared to other groups (P<0.05). Conclusion Although CD133+ derived melanoma cells represented stemness fea- tures, our findings demonstrated that spheroid culture could be more effective meth- od to enrich melanoma stem cells.
Optimizing extreme learning machine for hyperspectral image classification

Abstract. Extreme learning machine (ELM) is of great interest to the machine learning society due to its extremely simple training step. Its performance sensitivity to the number of hidden neurons is studied under the context of hyperspectral remote sensing image classification. An empirical linear relationship between the number of training samples and the number of hidden neurons is proposed. Such a relationship can be easily estimated with two small training sets and extended to large training sets to greatly reduce computational cost. The kernel version of ELM (KELM) is also implemented with the radial basis function kernel, and such a linear relationship is still suitable. The experimental results demonstrated that when the number of hidden neurons is appropriate, the performance of ELM may be slightly lower than the linear SVM, but the performance of KELM can be comparable to the kernel version of SVM (KSVM). The computational cost of ELM and KELM is much lower than that of the linear SVM and KSVM, respectively.
Transient Mild Hyperthermia Induces E-selectin Mediated Localization of Mesoporous Silicon Vectors in Solid Tumors

Background Hyperthermia treatment has been explored as a strategy to overcome biological barriers that hinder effective drug delivery in solid tumors. Most studies have used mild hyperthermia treatment (MHT) to target the delivery of thermo-sensitive liposomes carriers. Others have studied its application to permeabilize tumor vessels and improve tumor interstitial transport. However, the role of MHT in altering tumor vessel interfacial and adhesion properties and its relationship to improved delivery has not been established. In the present study, we evaluated effects of MHT treatment on tumor vessel flow dynamics and expression of adhesion molecules and assessed enhancement in particle localization using mesoporous silicon vectors (MSVs). We also determined the optimal time window at which maximal accumulation occur. Results In this study, using intravital microscopy analyses, we showed that temporal mild hyperthermia (∼1 W/cm2) amplified delivery and accumulation of MSVs in orthotopic breast cancer tumors. The number of discoidal MSVs (1000×400 nm) adhering to tumor vasculature increased 6-fold for SUM159 tumors and 3-fold for MCF-7 breast cancer tumors. By flow chamber experiments and Western blotting, we established that a temporal increase in E-selectin expression correlated with enhanced particle accumulation. Furthermore, MHT treatment was shown to increase tumor perfusion in a time-dependent fashion. Conclusions Our findings reveal that well-timed mild hyperthermia treatment can transiently elevate tumor transport and alter vascular adhesion properties and thereby provides a means to enhance tumor localization of non-thermally sensitive particles such as MSVs. Such enhancement in accumulation could be leveraged to increase therapeutic efficacy and reduce drug dosing in cancer therapy.
Extending Gaussian copula with jumps to match correlation smile

We present an extension to the Gaussian copula model with jumps. We mix normal distributions which have negative means and small weights with the standard normal distribution in the Gaussian copula model to generate jumps in the default probability distribution for each underlying credit. The means and weights of the new normal distributions are used to control the size and intensity of the jumps. Our model can replicate the type of default probability distribution observed in HullWhite’s implied copula model. It has a perfect fit with the recent Itraxx index tranche market prices, and uses different approach than the existing stochastic correlation model.
The effects of linearly moving sound images on self-motion perception

1. Introduction To develop new man-machine interfaces and new communication systems, clarification of human multi-modal information processing has become a crucial, challenging and interesting topic. Self-motion perception is well known as a multi-modal information process influenced by visual, postural, and somatic information. However, we do not always use all of these kinds of information to perceive self-motion. With even only visual information, we often perceive self-motion, e.g., we may have an illusory feeling that our train is moving when we see a train departing on the next track. This phenomenon is called ''vection. '' This suggests that visual information highly influences self-motion perception. Visual information can provide rich and accurate spatial information and this may be the reason why self-motion perception is highly influenced by such information. However , not only visual information but also auditory information can provide certain spatial information, and it is likely that auditory information may influence self-motion perception. In the past, Lackner [1] generated rotating sound field by using six loudspeakers and reported that subjects perceived rotating self-motion under this condition. Nara et al. [2] used similar equipments and reported that the amount of head sway was increased by rotating sound images. These studies show that vection is evoked also by auditory information. However, there seems to be no research on auditory vection with linearly moving sound images. In this study, we investigated whether or not self-motion could be perceived based only on auditory information of linear motion. We generated linearly moving sound images by using eight loudspeakers and assessed the acoustically induced self-motion. Moreover, as an objective measure, we measured the sway of the center of gravity due to body movement.
Symbolic Stochastic Focused Dynamic Programming with Decision Diagrams

We present a stochastic planner based on Markov Decision Processes (MDPs) that participates to the probabilistic planning track of the 2006 International Planning Competition. The planner transforms the PPDDL problems into factored MDPs that are then solved with a structured modified value iteration algorithm based on the safest stochastic path computation from the initial states to the goal states. First, a state subspace is computed by making all the transitions deterministic. Then, a step of modified value iteration on the current reachable state subspace alternates with a step of reachable state expansion by following the current policy.
SAGE: A logical and physical design tool for entity-group based new SQL systems

Entity-group based new SQL systems achieve scalability and consistency at the same time by using a key-value store as the storage layer and limiting each transaction's boundary to a collection of data (called an entity-group). Examples of such systems are Google's Megastore, NEC's Partiqle, and LinkedIn's Espresso. Application developers of such systems face tremendous challenges, both in designing entity-groups (and hence transaction boundaries) and physical layout of data in key-value stores. Entity-group designs directly impact consistency semantics of the workload, and physical layout impacts the application throughput. Both problems are challenging for users to solve manually. In this demonstration, we show a system that solves both problems with a user-friendly GUI built on our principled formal methods. We demonstrate the system using a simple Auction benchmark, and a more complex TPC-W benchmark.
2-D two-channel lifting based filter bank design to allow switching between filter banks

Switching between 2-D filter banks is important in constructing 2-D adaptive transforms, and lifting factorization has been at the heart of many successful 2-D adaptive transforms. However, switching between filter banks with arbitrary number of lifting steps will induce transients in the transition region between the filter banks. In this paper, we derive conditions on lifting steps of a 2-D two-channel filter bank such that switching between filter banks designed with such conditions will not induce transients. We design 2-D directional filter banks with the proposed conditions, and show successful switching between them within an adaptive directional transform for image coding.
Who is Most Vulnerable to Macroeconomic Shocks?: Hypotheses Tests Using Panel Data from Peru

This paper attempts to answer the question: Who is most vulnerable to declines in welfare during a macroeconomic shock? After clarifying the difference between poverty and vulnerability, an analytical framework is presented and then applied to household panel data from Peru. Major findings are: (a) households with better educated heads are less vulnerable; (b) female headed households are not more vulnerable to declines than male headed households; (c) households with more children are more vulnerable to macroeconomic shocks; and (d) transfer networks that may assist the poor in relatively stable periods do not appear to protect them during a major shock, with the exception of transfers that originate from outside Peru.
Anisotropy in the interaction of ultracold dysprosium.

The nature of the interaction between ultracold atoms with a large orbital and spin angular momentum has attracted considerable attention. It was suggested that such interactions can lead to the realization of exotic states of highly correlated matter. Here, we report on a theoretical study of the competing anisotropic dispersion, magnetic dipole-dipole, and electric quadrupole-quadrupole forces between two dysprosium atoms. Each dysprosium atom has an orbital angular momentum of L = 6 and a magnetic moment of μ = 10 μ(B). We show that the dispersion coefficients of the ground state adiabatic potentials lie between 1865 a.u. and 1890 a.u. , creating a non-negligible anisotropy with a spread of 25 a.u. and that the electric quadrupole-quadrupole interaction is weak compared to the other interactions. We also find that for interatomic separations R < 50a(0) both the anisotropic dispersion and magnetic dipole-dipole potential are larger than the atomic Zeeman splittings for external magnetic fields of order 10 G to 100 G. At these separations the atomic angular momentum can be reoriented. We finish by describing two scattering models for these inelastic m-changing collisions. A universal scattering theory is used to model loss due to the anisotropy in the dispersion and a Born approximation is used to model losses from the magnetic dipole-dipole interaction for the (164)Dy isotope. These models find loss rates that are of the same order of magnitude as the experimental value.
Stereo evaluation of ALOS PRISM and IKONOS in Yemen

DLR's Remote Sensing Technology Institute has a long lasting experience in developing spaceborne stereo scanners (MEOSS, MOMS) and the corresponding photogrammetric software systems for stereo evaluation and orthorectification. It takes part in the ESA/JAXA-AO Program to evaluate the performance and potential of the three-line stereo scanner PRISM and the multispectral imaging sensor AVNIR-2 on-board the Japanese satellite ALOS as a principal investigator. The high geometric resolution of PRISM (2.5 m ground sampling distance at nadir) combined with the medium swath width of 35 km has the potential to achieve high quality Digital Elevation Models up to 1:25.000 scale topographic maps for various applications. One of the proposed test sites is located near Sana'a, Yemen, where additionally to the PRISM stereo data also an IKONOS stereo image pair exists, which is used for DEM comparison and performance analysis. The results of this test site are evaluated in cooperation with the Advanced Data processing Research INstitute (ADRIN), India and the Federal Institute for Geosciences and Natural Resources (BGR), Hannover.
Developing an International and Technology-Driven Business School Program

Abstract Academics and practitioners alike have voiced their concerns about how to continuously improve the quality of education in the business school. Two central issues that have received recent attention are (1) how to address a rapidly changing and increasingly global economy, and (2) how to infuse technology into the business school curriculum. Both of these issues are changing at break-neck speed, whereas the academic environment, by its very nature and structure, is struggling to meet these demands ata much slower pace. We attempt to offer solutions to these major issues by developing an action plan for international business and technology. One key factor in developing global and technological programs in business schools is the input of its stakeholders-the international and technological business community. In this study, we report the results of an investigation of the international business and technological community's perceptions of the skills they require of recent business school graduates. A total of 126 business organizations provide insights for business schools to develop action plans to address international and technological needs. A discussion and implications of our findings provides an initial avenue for schools to follow in their strategic planning for the future.