Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonverbal behaviors toward an audience and a screen for a presentation by a humanoid robot

Objective: We propose a model which predicts patterns of nonverbal behaviors for a successful presentation by a humanoidrobot, especially focusing on two types of the behaviors. One is the nonverbal behaviors of eye-contact with its face and openpostures with arms to keep an attention of an audience who are listening to the presentation. The other is pointing with its handand approaching to a screen with a step to emphasis important points on the screen which is used in the presentation. Methods: We tested the hypothesis that both types of nonverbal behaviors are effective for ensuring better understanding of thepresentation. We prepared four conditions which show high or low tendency in each type of the nonverbal behaviors. A totalof 139 participants observed a presentation by a humanoid robot in a between-subject design and then completed a surprisedtest. They also evaluated general impressions of the robot based on a psychological scale which is developed for an evaluationof humanoids. Results: We found that both approaches are related to higher scores regarding the audience’s correct understanding of thepresentation, with higher psychological impressions given in relation to utility of the robot and the clearness of the voice of therobot. Additionally, we found that the behaviors toward a screen is more effective than the behaviors toward an audience in thiscase of the presentation by a humanoid robot. Conclusions: We concluded that both types of the nonverbal behaviors are important for the audience’s correct understandingand also the behaviors which emphasize the key points in the screen is crucial rather than the behaviors which keep the attentionsof the audience when a humanoid robot gives a presentation. Finally, we discuss the universality of the proposed model for usewith other humanoid robots.
Deficiency in Serum Immunoglobulin (Ig)m Predisposes to Development of Igg Autoantibodies

Serum immunoglobulin (Ig)M provides the initial response to foreign antigen and plays a regulatory role in subsequent immune response development, accelerating the production of high-affinity IgG. Here we show that mice deficient in serum IgM have an increased propensity to spontaneous autoimmunity as judged by the development with age of serum IgG anti-DNA antibodies and the renal deposition of IgG and complement. They also exhibit augmented anti-DNA IgG production on exposure to lipopolysaccharide. Thus, deficiency in serum IgM leads to diminished responsiveness to foreign antigens but increased responsiveness to self—a paradoxical association reminiscent of that described in humans deficient in complement or IgA. We wondered whether serum IgM might play an analogous role with regard to the response to self-antigens. However, here—in contrast to the sluggish response to foreign antigens—we find that deficiency in serum IgM actually predisposes to the development of IgG antibodies to autoantigens.
Thin servers with smart pipes: designing SoC accelerators for memcached

Distributed in-memory key-value stores, such as memcached, are central to the scalability of modern internet services. Current deployments use commodity servers with high-end processors. However, given the cost-sensitivity of internet services and the recent proliferation of volume low-power System-on-Chip (SoC) designs, we see an opportunity for alternative architectures. We undertake a detailed characterization of memcached to reveal performance and power inefficiencies. Our study considers both high-performance and low-power CPUs and NICs across a variety of carefully-designed benchmarks that exercise the range of memcached behavior. We discover that, regardless of CPU microarchitecture, memcached execution is remarkably inefficient, saturating neither network links nor available memory bandwidth. Instead, we find performance is typically limited by the per-packet processing overheads in the NIC and OS kernel---long code paths limit CPU performance due to poor branch predictability and instruction fetch bottlenecks. Our insights suggest that neither high-performance nor low-power cores provide a satisfactory power-performance trade-off, and point to a need for tighter integration of the network interface. Hence, we argue for an alternate architecture---Thin Servers with Smart Pipes (TSSP)---for cost-effective high-performance memcached deployment. TSSP couples an embedded-class low-power core to a memcached accelerator that can process GET requests entirely in hardware, offloading both network handling and data look up. We demonstrate the potential benefits of our TSSP architecture through an FPGA prototyping platform, and show the potential for a 6X-16X power-performance improvement over conventional server baselines.
Understanding demographic and socioeconomic biases of geotagged Twitter users at the county level

ABSTRACT Massive social media data produced from microblog platforms provide a new data source for studying human dynamics at an unprecedented scale. Meanwhile, population bias in geotagged Twitter users is widely recognized. Understanding the demographic and socioeconomic biases of Twitter users is critical for making reliable inferences on the attitudes and behaviors of the population. However, the existing global models cannot capture the regional variations of the demographic and socioeconomic biases. To bridge the gap, we modeled the relationships between different demographic/socioeconomic factors and geotagged Twitter users for the whole contiguous United States, aiming to understand how the demographic and socioeconomic factors relate to the number of Twitter users at county level. To effectively identify the local Twitter users for each county of the United States, we integrate three commonly used methods and develop a query approach in a high-performance computing environment. The results demonstrate that we can not only identify how the demographic and socioeconomic factors relate to the number of Twitter users, but can also measure and map how the influence of these factors vary across counties.
Towards a Direct Measure of Video Quality Perception using EEG

An approach for the direct measurement of video quality change perception using electroencephalography (EEG) is presented. Subjects viewed 8s video clips while their brain activity was registered using EEG. The video signal was either uncompressed at full length or changed from uncompressed to a lower quality level at a random time point. The distortions were introduced by a hybrid video codec. Subjects had to indicate whether or not they had perceived a quality change. In response to a quality change, a positive voltage change in EEG (the socalled P3 component) was observed at a latency of about 400-600 ms for all subjects. The voltage change positively correlated with the magnitude of the video quality change, substantiating the P3 component as a graded neural index of video quality change perception within the presented paradigm. By applying machine learning techniques, we could classify on a single-trial basis whether or not a subject perceived a quality change. Interestingly, some video clips wherein changes were missed (i.e., not reported) by the subject were classified as quality changes, suggesting that the brain detected a change although the subject did not press a button. Concluding, abrupt changes of video quality give rise to specific components in the EEG that can be detected on a single-trial basis. Potentially, a neurotechnological approach to video assessment could lead to a more objective quantification of quality change detection, overcoming the limitations of subjective approaches (such as subjective bias and the requirement of an overt response). Furthermore, it allows for real-time applications wherein the brain response to a video clip is monitored while it is being viewed.
Concentrations and Seasonal Variation in Heavy Metal Contamination of Leachates, Borehole Water, Soil and Edible Plants near Unengineered Dumpsites in Port Harcourt, Nigeria

There are two major seasons in Nigeria – wet and dry season. This study was carried out to assess concentrations and seasonal variations in heavy metals in leachates, borehole water, soil and edible plants around unengineered dumpsites in Port Harcourt, Nigeria. Samples of leachates, borehole water within 300m from each unengineered dumpsites, soil samples, and two edible plants were collected around each unengineered dumpsites; all for analysis of heavy metal contaminations. The heavy metals studied include Cadmium (Cd), Lead (Pb), Zinc (Zn), Iron (Fe), and Copper (Cu). Analysis of the leachates, borehole waters, soil and edible plants showed that there is high concentration of heavy metals in the environments studied. This may be due to transport from the dumpsite nearby to the leachates, soil, edible plants and borehole waters. Higher concentrations were recorded during wet season than dry season in most of the heavy metals studied. This may be as a result of seasonal rainfall, dilution and run-off during the wet season that flushed the contaminants from the dumpsites into the environment.
App Store Analysis: Mining App Stores for Relationships between Customer, Business and Technical Characteristics

This paper argues that App Store Analysis can be used to understand the rich interplay between app customers and their developers. We use data mining to extract price and popularity information and natural language processing and data mining to elicit each app�s claimed features from the Blackberry App Store, revealing strong correlations between customer rating and popularity (rank of app downloads). We found evidence for a mild correlation between price and the number of features claimed for an app and also found that higher priced features tended to be lower rated by their users. We also found that free apps have significantly (p-value <0.001) higher rating than non-free apps, with a moderately high effect size (�12 = 0.68). We also provide initial evidence that extracted claimed features are meaningful to developers (precision = 0.71, recall = 0.77). All data from our experiments and analysis are made available on-line to support further analysis.
Modeling variable frequency drive and motor systems in power systems dynamic studies

Variable frequency drives (VFD) are widely used in industrial facilities, however, dynamic models for VFD-motor systems suitable for power system dynamic studies are not available. In this paper, a generic VFD-motor system modeling technique is proposed for the case that VFDs are able to ride through the fault. To illustrate the proposed technique, a dynamic model for a low voltage 6-pulse voltage source inverter (VSI) based drive and induction motor system with voltage per Hz control is created. To verify the accuracy of the developed dynamic model, a case study is conducted using a sample VFD-motor system, both derived dynamic model and detailed switching model for the same system are simulated using Matlab/Simulink, and their dynamic responses are compared. It is found that there are good agreements between the two models, and thus the accuracy of the developed dynamic model is verified. For the case that VFDs will trip out of lines, a VFD trip characteristic curve is proposed, and a simple screening procedure is recommended for evaluating whether the VFD-motor system shall remain in service or trip out of lines in power systems dynamic studies.
A framework for development of universal rules for microgrids stability and control

Inverter based microgrids are becoming a viable and attractive choice for future power distribution systems with substantial renewable penetration. The control architectures of such microgrids are currently designed to mimic conventional power systems with droop-based control, coupling active power to frequency and reactive power to voltage. However, the dynamic behavior of low-voltage microgrids is very different from large-scale power systems. In particular, the electromagnetic network dynamics plays an unexpectedly important role despite its very small timescales. This makes simplified swing-type equations inappropriate for microgrid stability assessment requiring an explicit consideration of line currents dynamics. In the present work we elucidate the role of network dynamics in such micro-grids and uncover the major factors affecting microgrids stability. We then present a systematic approach for proper accounting for the network dynamics by a special model-order reduction procedure. Based on this reduced-order model we derive a set of stability certificates each based only on local parameters, namely the settings of each pair of interconnected inverters and parameters of the corresponding interconnection line. This set of constraints establishes a natural foundation for plug-and-play interconnection standards. Possible applications of the derived stability criteria are discussed ranging from microgrid network planning to multi-microgrid interconnection/reconfiguration decision tools.
The bZIP Transcription Factor PERIANTHIA: A Multifunctional Hub for Meristem Control

As sessile organisms, plants are exposed to extreme variations in environmental conditions over the course of their lives. Since plants grow and initiate new organs continuously, they have to modulate the underlying developmental program accordingly to cope with this challenge. At the heart of this extraordinary developmental plasticity are pluripotent stem cells, which are maintained during the entire life-cycle of the plant and that are embedded within dynamic stem cell niches. While the complex regulatory principles of plant stem cell control under artificial constant growth conditions begin to emerge, virtually nothing is known about how this circuit adapts to variations in the environment. In addition to the local feedback system constituted by the homeodomain transcription factor WUSCHEL (WUS) and the CLAVATA signaling cascade in the center of the shoot apical meristem (SAM), the bZIP transcription factor PERIANTHIA (PAN) not only has a broader expression domain in SAM and flowers, but also carries out more diverse functions in meristem maintenance: pan mutants show alterations in environmental response, shoot meristem size, floral organ number, and exhibit severe defects in termination of floral stem cells in an environment dependent fashion. Genetic and genomic analyses indicate that PAN interacts with a plethora of developmental pathways including light, plant hormone, and meristem control systems, suggesting that PAN is as an important regulatory node in the network of plant stem cell control.
Lanes and Road Signs Recognition for Driver Assistance System

Driver assistance systems become one of the most important features of the modern vehicles to ensure driver safety and decrease vehicles accidents on roads. According to their type and functionality, they intervene in different levels of the control processes involved in driving. In this paper, multitasks driver assistance system has been proposed. First, the system provides the driver with real time information from lanes markers and road signs, which consist the most important and challenging tasks. Secondly, generate an acoustic warning to the driver in advance of any danger. This warning then allows the driver to take appropriate corrective actions in order to mitigate or completely avoid the event. The proposed system was tested on real road scene captured from moving vehicle. From the experimental results, the system has demonstrated a robust performance for detecting the road lanes and signs under different conditions.
Riparian and geomorphic controls on thermal habitat dynamics of pools in a temperate headwater stream

Stream pools serve as habitat for diverse communities composed of microbes, macroinvertebrates, and fish. Every pool presents a combination of geomorphological features, and each pool habitat hosts a unique community. These communities are tied to the physical characteristics of their habitat, especially water temperature. The effects of geomorphology and hydraulic variables on thermal habitat dynamics in pools are not well understood. In this study, the thermal regime in important stream pool habitats was investigated in relation to their riparian and geomorphological features. Our results indicate that instream wood, groundwater resurgence, and depth can locally modify the pool thermal habitat and increase thermal buffering capacity during heat‐stress events. Our findings highlight the importance of riparian vegetation and in‐channel hydrogeomorphic features in controlling pool thermal habitats.
Introducing LensCharm A charming Bayesian strong lensing reconstruction framework

Strong gravitational lensing, a phenomenon rooted in the principles of general relativity, grants us a unique window into the distant cosmos by offering a direct probe into dark matter and providing independent constraints on the Hubble constant. These research objectives call for the utmost precision in the estimation of the lens mass and the source brightness distributions. Recent strides in telescope technology promise to provide an abundance of yet undiscovered strong-lensing systems, presenting observations of unprecedented quality. Realizing the full potential of these advancements hinges on achieving the highest fidelity in both source and lens reconstruction. In this study, we introduce LensCharm , a novel Bayesian approach for strong-lensing signal reconstruction. Unlike more prevalent methods, LensCharm enables the nonparametric reconstruction of both the source and lens concurrently, along with their associated uncertainties. We showcase the distinctive strengths of our approach through comprehensive analyses of both real-world and simulated astronomical data, underscoring its superiority in achieving precise reconstructions. We have made LensCharm publicly accessible, envisioning its empowerment of the next generation of astronomical observation reconstructions and cosmological constraints derived from strong gravitational lensing.
Effect of Multispecies Cover Crop Mixture on Soil Properties and Crop Yield

After 3 yr, soybean yield was higher from multispecies than from single‐ and double‐species cover cropping. Multispecies cover cropping had higher soil water and inorganic N content than less‐diverse treatments. Soil organic C was unaffected by cover crop species diversity. Several years of cover cropping are needed to achieve ecosystem benefits.
Classifier Cascade for Minimizing Feature Evaluation Cost

Machine learning algorithms are increasingly used in large-scale industrial settings. Here, the operational cost during test-time has to be taken into account when an algorithm is designed. This operational cost is affected by the average running time and the computation time required for feature extraction. When a diverse set of features is used, the latter can vary drastically. In this paper we propose an algorithm that constructs a cascade of classifiers which explicitly trades-off operational cost and classifier accuracy while accounting for on-demand feature extraction costs. Different from previous work, our algorithm reoptimizes trained classifiers and allows expensive features to be scheduled at any stage within the cascade to minimize overall cost. Experiments on actual web-search ranking data sets demonstrate that our framework leads to drastic test-time improvements.
Concomitant inhibition of epidermal growth factor and vascular endothelial growth factor receptor tyrosine kinases reduces growth and metastasis of human salivary adenoid cystic carcinoma in an orthotopic nude mouse model

We hypothesized that epidermal growth factor (EGF) receptor (EGFR) activation and vascular endothelial growth factor (VEGF)–induced angiogenic signals are important for the progression and metastasis of human salivary adenoid cystic carcinoma (ACC). To test this hypothesis, we evaluated the therapeutic effect of AEE788, a dual inhibitor of EGF and VEGF receptor (VEGFR) tyrosine kinases, on human salivary ACC. In clinical specimens of salivary ACC, EGF and VEGF signaling proteins were expressed at markedly higher levels than in adjacent normal glandular tissues. We examined the effects of AEE788 on salivary ACC cell growth and apoptosis and on the phosphorylation of EGFR and VEGFR-2 in salivary ACC cells. Treatment of salivary ACC cells with AEE788, alone or in combination with chemotherapy, led to growth inhibition, induction of apoptosis, and dose-dependent inhibition of EGFR and VEGFR-2 phosphorylation. To determine the in vivo antitumor effects of AEE788, nude mice with orthotopic parotid tumors were randomized to receive oral AEE788 alone, paclitaxel alone, cisplatin alone, a combination of AEE788 plus paclitaxel, a combination of AEE788 plus cisplatin, or a placebo. AEE788 inhibited tumor growth and prevented lung metastasis in nude mice. To study the mechanism of interaction between AEE788 and chemotherapy, AEE788 was found to potentiate growth inhibition and apoptosis of ACC tumor cells mediated by chemotherapy. Tumors of mice treated with AEE788 and AEE788 plus chemotherapy exhibited down-regulation of activated EGFR and VEGFR-2, increased tumor and endothelial cell apoptosis, and decreased microvessel density, which correlated with a decrease in the level of matrix metalloproteinase-9 and matrix metalloproteinase-2 expression and a decrease in the incidence of vascular metastasis. These data show that EGFR and VEGFR can be molecular targets for therapy of salivary ACC. [Mol Cancer Ther 2006;5(11):2696–705]
Phosphorylation of Intrinsically Disordered Regions in Remorin Proteins

Plant-specific remorin proteins reside in subdomains of plasma membranes, originally termed membrane rafts. They probably facilitate cellular signal transduction by direct interaction with signaling proteins such as receptor-like kinases and may dynamically modulate their lateral segregation within plasma membranes. Recent evidence suggests such functions of remorins during plant–microbe interactions and innate immune responses, where differential phosphorylation of some of these proteins has been described to be dependent on the perception of the microbe-associated molecular pattern (MAMP) flg22 and the presence of the NBS–LRR resistance protein RPM1. A number of specifically phosphorylated residues in their highly variable and intrinsically disordered N-terminal regions have been identified. Sequence diversity of these evolutionary distinct domains suggests that remorins may serve a wide range of biological functions. Here, we describe patterns and features of intrinsic disorder in remorin protein and discuss possible functional implications of phosphorylation within these rapidly evolving domains.