Miracle-dz/UniFAR-FTUs huggingface dataset:
Household energy consumption prediction by feature selection of lifestyle data

This study proposes a prediction model for the annual power consumption of general households based on the large-scale questionnaire about lifestyle of the household. By combining a feature selection technique with the multivariate linear regression model, we can find important features, i.e., key questionnaires, for estimating seasonal electricity consumption for ordinary households. This may be the first study on feature selection for actual questionnaire data in the energy field. Through numerical experiments, we confirmed the high prediction performance of our method by comparing the test accuracy of our method with that of a naive one.
Basic Semantics of Product Sounds

Product experience is a result of sensory and semantic experiences with product properties. In this paper, we focus on the semantic attributes of product sounds and explore the basic components for product sound related semantics using a semantic differential paradigmand factor analysis. With two experiments, we determined eight factors that underlie the semantic associations of product sounds (attention, roughness, smoothness, temporal constancy, (un)familiarity, unpleasantness, machinery, and power). Correlations of the resultsfrom both experiments indicate that perceptual factors (attention, roughness, smoothness, and temporal constancy) influence cognitivefactors (power, machinery, and (un)familiarity) and emotional factors (unpleasantness). This finding suggests a hierarchical structure in themeaningful associations of product sounds. Furthermore, we have shown that product sound related semantics is sound type dependent
CD98 Increases Renal Epithelial Cell Proliferation by Activating MAPKs

CD98 heavy chain (CD98hc) is a multifunctional transmembrane spanning scaffolding protein whose extracellular domain binds with light chain amino acid transporters (Lats) to form the heterodimeric amino acid transporters (HATs). It also interacts with β1 and β3 integrins by its transmembrane and cytoplasmic domains. This interaction is proposed to be the mechanism whereby CD98 mediates cell survival and growth via currently undefined signaling pathways. In this study, we determined whether the critical function of CD98-dependent amino acid transport also plays a role in cell proliferation and defined the signaling pathways that mediate CD98-dependent proliferation of murine renal inner medullary collecting duct (IMCD) cells. We demonstrate that downregulating CD98hc expression resulted in IMCD cell death. Utilizing overexpression studies of CD98hc mutants that either lacked a cytoplasmic tail or were unable to bind to Lats we showed that CD98 increases serum-dependent cell proliferation by a mechanism that requires the CD98hc cytoplasmic tail. We further demonstrated that CD98-dependent amino acid transport increased renal tubular epithelial cell proliferation by a mechanism that does not require the CD98hc cytoplasmic tail. Both these mechanisms of increased renal tubular epithelial cell proliferation are mediated by Erk and p38 MAPK signaling. Although increased amino transport markedly activated mTor signaling, this pathway did not alter cell proliferation. Thus, these studies demonstrate that in IMCD cells, the cytoplasmic and extracellular domains of CD98hc regulate cell proliferation by distinct mechanisms that are mediated by common MAPK signaling pathways.
Stability and aggregation of ranked gene lists

Ranked gene lists are highly instable in the sense that similar measures of differential gene expression may yield very different rankings, and that a small change of the data set usually affects the obtained gene list considerably. Stability issues have long been under-considered in the literature, but they have grown to a hot topic in the last few years, perhaps as a consequence of the increasing skepticism on the reproducibility and clinical applicability of molecular research findings. In this article, we review existing approaches for the assessment of stability of ranked gene lists and the related problem of aggregation, give some practical recommendations, and warn against potential misuse of these methods. This overview is illustrated through an application to a recent leukemia data set using the freely available Bioconductor package GeneSelector.
Extraction of Physical Parameters from X-ray Spectromicroscopy Data Using Machine Learning

Materials informatics has significantly accelerated the discovery and analysis of materials in the last decade. Spectroscopic data provide essential information about materials and hence are widely used for materials analysis. However, data analysis, that is, the extraction of physical parameters, of spectra is often conducted by manually comparing spectra and on-the-fly data analysis has not been realized yet. Considering that more than 100,000 X-ray absorption spectra (XAS) can be measured per day using the scanning transmission X-ray microscopy system at the Photon Factory [1], an automated analysis methodology is urgently required [2, 3]. If physical parameters are to be estimated from the spectra, the on-the-fly analysis can be realized by space mapping of these parameters using a high-throughput spectromicroscopy experiment capable of adaptive measurements [4]. XAS often shows complex spectral features with a few hundred or more “high-dimensional” data points, and the physical parameters, such as element, charge, and symmetry can be extracted from the XAS [5]. Feature extraction, a popular machine learning approach to treat high-dimensional datasets, involves the projection of data onto a few features (parameters), thus retaining the relevant information [6]. In this study, we propose a methodology to estimate the physical parameters from XAS using feature extraction with dimensionality reduction, as shown in Fig. 1.
Multi-Slot Coverage Probability and SINR-Based Handover Rate Analysis for Mobile User in Hetnet

User mobility brings about the spatial correlation in user association (or handover) over a period of multi slots. The correlation makes the classic user association methodology, i.e., typical user method in stochastic geometry, invalid. In addition, the impact of signal to interference plus noise ratio (SINR) on handover cannot be overlooked due to the strong interference caused by the dense base station deployment. To address the above issues, we aim to explore a methodology to analyze the multi-slot network performance for a mobile user considering the SINR effect at the user’s location before it moves and the user’s location after it moves. The main idea is to find the correlated association (and interference) regions in different time slots. On this basis, the expression of multi-slot coverage probability, SINR-based horizontal, and vertical handover rate are derived under maximum average received power (MARP) strategy. Simulation results prove the positive correlation in the associated distance as well as the multi-slot coverage probability, and the impact of SINR on horizontal and vertical handover rate over a period of multi slots. Moreover, MARP strategy always outperforms the nearest distance strategy on multi-slot coverage probability at the almost same cost of handovers. Finally, we found that increasing the picocell density, transmission powers, and biasing can lead substantial loads offloading to picocell but make no significant contribution to the overall coverage.
Segmented face image verification for age-invariant face recognition

Face recognition has several problems to improve its performance. In particular, aging causes facial appearance variation so that it is the most difficult problem to handle. We propose a face recognition method that is robust against aging. The proposed method employs segmentation verification of frontal face images that consists of the following three steps. (1) Face image segmentation generates three regional subimages from the input face image. (2) A matching score is calculated using gradient features from a pair consisting of the input image and a registered image for each of the three generated subimages and original (whole face) image. We obtain four matching scores. (3) The verifying classifier evaluates the matching score vector and predicts the a posteriori probability that two matching images belong to the same person. The results of an experimental evaluation with the FGNET datasets clarify the effectiveness of the proposed method for age invariant face recognition.
The Usefulness of Dual-Layer Spectral Computed Tomography for Myelography: A Case Report and Review of the Literature

We describe a case of lumbar stenosis in which retrospective spectral analysis using dual-layer spectral detector computed tomography (CT) had the ability to expand the evaluable region in the spinal canal. Spinal canal stenosis is a common condition whose symptoms (such as lower back and leg pain with walking) deteriorate the quality of life. Generally, magnetic resonance imaging (MRI) and CT myelography are performed to diagnose canal stenosis. Dual-layer spectral detector CT can yield virtual monochromatic imaging and retrospective on-demand spectral analysis without a prescan setting. Spectral analysis could expand the evaluable region in the spinal canal for increasing the contrast enhancement in the canal.
Comparing Consider-Covariance Analysis with Sigma-Point Consider Filter and Linear-Theory Consider Filter Formulations

Recent literature in applied estimation theory reflects growing interest in the sigma-point (also called “unscented”) formulation for optimal sequential state estimation, often describing performance comparisons with extended Kalman filters as applied to specific dynamical problems [c.f. 1, 2, 3]. Favorable attributes of sigma-point filters are described as including a lower expected error for nonlinear – even non-differentiable – dynamical systems, and a straightforward formulation not requiring derivation or implementation of any partial derivative Jacobian matrices. These attributes are particularly attractive, e.g. in terms of enabling simplified code architecture and streamlined testing, in the formulation of estimators for nonlinear spaceflight mechanics systems, such as filter software onboard deep-space robotic spacecraft.
Cross-domain Dialogue Policy Transfer via Simultaneous Speech-act and Slot Alignment

Dialogue policy transfer enables us to build dialogue policies in a target domain with little data by leveraging knowledge from a source domain with plenty of data. Dialogue sentences are usually represented by speech-acts and domain slots, and the dialogue policy transfer is usually achieved by assigning a slot mapping matrix based on human heuristics. However, existing dialogue policy transfer methods cannot transfer across dialogue domains with different speech-acts, for example, between systems built by different companies. Also, they depend on either common slots or slot entropy, which are not available when the source and target slots are totally disjoint and no database is available to calculate the slot entropy. To solve this problem, we propose a Policy tRansfer across dOMaIns and SpEech-acts (PROMISE) model, which is able to transfer dialogue policies across domains with different speech-acts and disjoint slots. The PROMISE model can learn to align different speech-acts and slots simultaneously, and it does not require common slots or the calculation of the slot entropy. Experiments on both real-world dialogue data and simulations demonstrate that PROMISE model can effectively transfer dialogue policies across domains with different speech-acts and disjoint slots.
A direct multi-cells-to-multi-cells equalizer based on LC matrix converter for series-connected battery strings

Due to the low switching loss, the LC series resonant conversion (LCSRC) as an energy carrier is promising in the battery equalizers. However, when LCSRC is applied to multi-cells series-connected batteries, the balancing speed and efficiency will be seriously low. Therefore, a direct multi-cells-to-multi-cells (MC2MC) equalizer based on LC matrix converter (LCMC) is proposed, which can transfer energy directly from the consecutive higher-voltage cell group to the consecutive lower-voltage cell group, achieving a high balancing speed and efficiency. Moreover, the switching loss for balancing is reduced by operating the LCMC at the zero-current switching (ZCS) condition. An experimental cell balancing circuit for an eight-cell lithium-ion battery string shows that it is possible to realize faster balancing with higher efficiency. The measured balancing efficiencies are 99.2% and 75.9% at the powers of 0.17 W and 0.45 W, respectively.
Locally Optimally Emitting Clouds and the Origin of Quasar Emission Lines

The similarity of quasar line spectra has been taken as an indication that the emission line clouds have preferred parameters, suggesting that the environment is subject to a fine-tuning process. We show here that the observed spectrum is a natural consequence of powerful selection effects. We computed a large grid of photoionization models covering the widest possible range of cloud gas density and distance from the central continuum source. For each line only a narrow range of density and distance from the continuum source results in maximum reprocessing efficiency, corresponding to “locally optimally emitting clouds” (LOCs). These parameters depend on the ionization and excitation potentials of the line and its thermalization density. The mean QSO line spectrum can be reproduced by simply adding together the full family of clouds, with an appropriate covering fraction distribution. The observed quasar spectrum is a natural consequence of the ability of various clouds to reprocess the underlying continuum, and can arise in a chaotic environment with no preferred pressure, gas density, or ionization parameter.
Future Perspectives in HLA Typing Technologies

A wide range of malignant and nonmalignant diseases require hematopoietic stem cell transplantation (HSCT) as last resort therapeutic approach. Graft versus host disease (GVHD), which is one of the major causes of transplant-related mortality, is minimized whenever increased matching of human leukocyte antigens (HLAs) between donor and recipient is present. Suitable donor selection is determined with the utilization of HLA typing. HLAs are highly polymorphic glycoproteins encoded by a region of genes known as the major histocompatibility complex (MHC). Their biological function is to present antigenic peptides to T lymphocytes. However, they also play important role in HSCT acceptance/rejection. During the previous years, various techniques have been acquired in order to better characterize the HLA profile of transplant donors and recipients. This effort is particularly challenging due to MHC size, but most importantly due to high sequence variability in specific regions of the respective genetic loci, between individuals. Initially, HLA typing was performed using serological typing, hybridization techniques, and restriction fragment length polymorphism (RFLP) approaches. Later on, polymerase chain reaction (PCR) based techniques and direct sequencing (dideoxy-based Sanger sequencing) capillary electrophoretic analyses arose. Nowadays, 2nd and 3rd generation sequencing (NGS) technologies show great potential in effectively identifying these polymorphic regions.
Timing of menarche and depressive symptoms in adolescent girls from a UK cohort

Background A growing number of studies suggest a link between timing of menarche and risk of depressive symptoms in adolescence, but few have prospectively examined the emergence of depressive symptoms from late childhood into adolescence. Aims To examine whether girls who experience earlier menarche than their peers have higher levels of depressive symptoms in adolescence. Method The study sample comprised 2184 girls from the Avon Longitudinal Study of Parents and Children. The association between timing of menarche and depressive symptoms at 10.5, 13 and 14 years was examined within a structural equation model. Results Girls with early menarche (<11.5 years) had the highest level of depressive symptoms at 13 (P = 0.007) and 14 years (P<0.001) compared with those with normative and late timing of menarche. Conclusions Early maturing girls are at increased risk of depressive symptoms in adolescence and could be targeted by programmes aimed at early intervention and prevention.
Communication Design for Energy Management Automation in Microgrid

Real-time energy management automation in microgrid can improve energy security, reliability, efficiency, and power quality but is a challenging issue as it requires a robust, deterministic, and interoperable communication architecture. IEC 61850-based communication architecture has the potential to be the promising solution for microgrid automation. Hence, this paper addresses this challenge by proposing IEC 61850-based design and modeling of IEDs for different types of distributed energy resources and a new logical node for controllable loads along with the design of structure and size of communication messages required for energy management automation in microgrid for the first time. This paper demonstrates the validation and implementation of the proposed design and modeling through a real-time system-in-the-loop simulation for a test microgrid. Finally, to justify the feasibility of the proposed design and modeling, dynamic performance of the microgrid communication architecture is evaluated in terms of end-to-end delay and throughput for different network topological configurations. This paper intends to provide a platform to model, configure, and evaluate a promising future standards-based communication for microgrid automation.
Monkey central retinal artery is innervated by nitroxidergic vasodilator nerves.

PURPOSE To determine whether the monkey central retinal artery is innervated by vasodilator nerves and to analyze the mechanism underlying the neurogenic response. METHODS Changes in isometric tension were recorded in helical strips of the arteries, which were stimulated by transmurally applied electrical pulses or nicotine. The presence of perivascular nerve fibers containing nitric oxide (NO) synthase immunoreactivity was determined histologically. RESULTS Transmural electrical stimulation (5 Hz) and nicotine produced a relaxation of the arterial strips denuded of the endothelium, treated with prazosin, and contracted with prostaglandin F2 alpha. The response was not influenced by timolol, atropine, and indomethacin, but it was abolished by methylene blue and oxyhemoglobin. NG-nitro-L-arginine, a NO synthase inhibitor, abolished the neurogenic relaxation, and L-arginine restored the response. Antagonists of calcitonin gene-related peptide and vasoactive intestinal polypeptide in sufficient concentrations did not influence the response to nerve stimulation by nicotine. There were abundant nerve fibers and bundles containing NO synthase immunoreactivity in the adventitia. CONCLUSIONS Monkey central retinal arteries are innervated by NO synthase-containing nerves that liberate NO possibly as a neurotransmitter on excitation to produce muscular relaxation.
Genetically optimized on-chip wideband ultracompact reflectors and Fabry–Perot cavities

Reflectors are an essential component for on-chip integrated photonics. Here, we propose a new method for designing reflectors on the prevalent thin-film-on-insulator platform by using genetic-algorithm optimization. In simulation, the designed reflector with a footprint of only 2.16 μm×2.16 μm can achieve ∼97% reflectivity and 1 dB bandwidth as wide as 220 nm. The structure is composed of randomly distributed pixels and is highly robust against the inevitable corner rounding effect in device fabrication. In experiment, we fabricated on-chip Fabry–Perot (FP) cavities constructed from optimized reflectors. Those FP cavities have intrinsic quality factors of >2000 with the highest value beyond 4000 in a spectral width of 200 nm. The reflectivity fitted from the FP cavity resonances is >85% in the entire wavelength range of 1440–1640 nm and is beyond 95% at some wavelengths. The fabrication processes are CMOS compatible and require only one step of lithography and etch. The devices can be used as a standard module in integrated photonic circuitry for wide applications in on-chip semiconductor laser structures and optical signal processing.
A dual domain digital image watermarking scheme

The paper presents a method combining two frequency domain techniques for watermarking digital images. A novel procedure based on selective application of Discrete Cosine Transform and Discrete Wavelet Transform is discussed. The objective of the work is to achieve higher robustness and imperceptibility by applying more than one transform domain operation on a host image in such a way that one will offset the shortcomings of the other. The method attempts to derive the best from discrete wavelet transform and discrete cosine transform techniques based on their individual suitability to distinct regions in the image. The resulting watermarked image is analyzed using the quality parameter PSNR. Resilience to watermark removal attacks is also studied and the experimental outcomes are outlined in the experimental analysis section.
Human Weapon-Activity Recognition in Surveillance Videos Using Structural-RNN

In today's world, video surveillance systems play a vital role in commercial and industrial environments. The important goal of a surveillance activity is to observe suspicious behavior of humans and objects in a scene using camera or other sensors. Most of the current surveillance systems perform such activities by identifying persons, tracking their individual paths independently, not in conjunction with the objects in the scene. However, in a real world surveillance scenario, the behavior of people and their interaction with objects need to be modeled to reason about suspicious activities. Our contribution, through this work is in using the state-of-the-art Structural Recurrent Neural Networks (SRNN) method to model the complex spatio-temporal human-object interactions in surveillance. Our best results have a final F1 score of 87.3 on the human sub-activity recognition task and 82.7 on the object affordances recognition task. Our work considered weapons as objects of interest.
Towards a grid-wide, high-fidelity electrical substation honeynet

After a number of real-world cyber incidents targeting power grid systems in the recent years, early detection of such cyber attacks and analysis of their attack vectors are in urgent need. One of the technologies that serve such purposes is honeypot. Although the concept of honeypot is not new, its use in a smart grid context is still nascent. Moreover, honeynet, a network of honeypots, is not yet systematically explored in a smart grid context. In this paper, we design and implement a smart grid honeynet system that can emulate an entire smart grid field communication infrastructure including multiple networked substations by taking advantage of virtualization technologies. Our honeynet system is tied to a simulated power grid to provide consistent and realistic view to deceive attackers for a prolonged period. Especially, our system can emulate high-fidelity power grid behavior when a sophisticated attacker launches grid-wide probing at his preparation phase, by changing settings in one substation and examining the expected changes in another. Finally, we present our proof-of-concept implementation and preliminary evaluation of its realism and scalability.