Miracle-dz/UniFAR-FTUs huggingface dataset:
Pop-up depth views for improving 3D target acquisition

We present the design and experimental evaluation of pop-up depth views, a novel interaction technique for aiding in the placement or positioning of a 3D cursor or object. Previous work found that in a 3D placement task, a 2D mouse used with multiple orthographic views outperformed a 3D input device used with a perspective view with stereo. This was the case, even though the mouse required two clicks to complete the task instead of only the single click required with the 3D input device. We improve performance with 3D input devices with pop-up depth views, small inset views in a perspective display of the scene. These provide top- and side-views of the immediate 3D neighborhood of the cursor, thereby allowing the user to see more easily along the depth dimension, improving the user's effective depth acuity. In turn, positioning with the 3D input device is also improved. Furthermore, because the depth views are displayed near the 3D cursor, only tiny eye movements are required for the user to perceive the 3D cursor's depth with respect to nearby objects. Pop-up depth views are a kind of depth view, only displayed when the user's cursor slows down. In this manner, they do not occlude the 3D scene when the user is moving quickly. Our experimental evaluation shows that the combination of a 3D input device used with a perspective view, stereo projection, and pop-up depth views, outperforms a 2D mouse in a 3D target acquisition task, in terms of both movement time and throughput, but at the cost of a slightly higher error rate.
Bisphenol A Disrupts Transcription and Decreases Viability in Aging Vascular Endothelial Cells

Bisphenol A (BPA) is a widely utilized endocrine disruptor capable of mimicking endogenous hormones, employed in the manufacture of numerous consumer products, thereby interfering with physiological cellular functions. Recent research has shown that BPA alters epigenetic cellular mechanisms in mammals and may be correlated to enhanced cellular senescence. Here, the effects of BPA at 10 ng/mL and 1 µg/mL, concentrations found in human samples, were analyzed on HT29 human colon adenocarcinona cell line and Human Umbilical Vein Endothelial Cells (HUVEC). Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) transcriptional analysis of the Long Interspersed Element-1 (LINE-1) retroelement showed that BPA induces global transcription deregulation in both cell lines, although with more pronounced effects in HUVEC cells. Whereas there was an increase in global transcription in HT29 exclusively after 24 h of exposure, this chemical had prolonged effects on HUVEC. Immunoblotting revealed that this was not accompanied by alterations in the overall content of H3K9me2 and H3K4me3 epigenetic marks. Importantly, cell viability assays and transcriptional analysis indicated that prolonged BPA exposure affects aging processes in senescent HUVEC. To our knowledge this is the first report that BPA interferes with senescence in primary vascular endothelial cells, therefore, suggesting its association to the etiology of age-related human pathologies, such as atherosclerosis.
Enabling Natural Interaction by Approaching Objects

This paper introduces the research issues to make a major step towards natural human interaction with mobile multimodal systems. Thereby, we aim at combining explicit and implicit interaction to blended multimodal interaction. Natural interaction and the requirement to anticipate a mix of purposive behaviour and uncertainty requires rendering information in a way that is compatible with and aware of the situational context. In two application examples we illustrate our approaches of interaction by movement. As the basis for adaptive behaviour, this paper describes the conclusions drawn from tracking the mobile user in two environments: a museum and a maintenance setting. It also illuminates different aspects of this technology, such as accuracy and costs, and illustrates the results of our project using the specific technology.
Research on Intrusion Detection Based on an Improved SOM Neural Network

Neural networks approach is an advanced methodology used for intrusion detection. As a type of neural network, Self-organizing Maps (SOM) is getting more attention in the field of intrusion detection. In this paper, some improvements on SOM algorithm are made in order to increase detection rate and improve the stability of intrusion detection, include: (1) Modify the strategy of “winner-take-all” to decrease underutilized or completely unutilized neurons. (2) Introduce interaction weight which describes the effect between each neuron in the output layer to enhance the relationships between the input pattern and the weights of all the nodes when adjusting weights; The improved SOM is implemented and applied to the intrusion detection. The validities and feasibilities of the improved SOM are confirmed through experiments on KDD Cup 99 datasets. The experiment result shows that the detection rate has been increased by employing the improved SOM.
Non-Weyl resonance asymptotics for quantum graphs

We consider the resonances of a quantum graph G that consists of a compact part with one or more infinite leads attached to it. We discuss the leading term of the asymptotics of the number of resonances of G in a disc of a large radius. We call G a Weyl graph if the coefficient in front of this leading term coincides with the volume of the compact part of G. We give an explicit topological criterion for a graph to be Weyl. In the final section we analyze a particular example in some detail to explain how the transition from the Weyl to the non-Weyl case occurs.
ITACA: An integrated toolbox for the automatic composition and adaptation of Web services

Adaptation is of utmost importance in systems developed by assembling reusable software services accessed through their public interfaces. This process aims at solving, as automatically as possible, mismatch cases which may be given at the different interoperability levels among interfaces by synthesizing a mediating adaptor. In this paper, we present a toolbox that fully supports the adaptation process, including: (i) different methods to construct adaptation contracts involving several services; (ii) simulation and verification techniques which help to identify and correct erroneous behaviours or deadlocking executions; and (iii) techniques for the generation of centralized or distributed adaptor protocols based on the aforementioned contracts. Our toolbox relates our models with implementation platforms, starting with the automatic extraction of behavioural models from existing interface descriptions, until the final adaptor implementation is generated for the target platform.
Antidepressant drugs reverse the loss of adult neural stem cells following chronic stress

In rodents, adult neurogenesis occurs in the olfactory bulb and the dentate gyrus of the hippocampus. It has been shown that exposure to psychosocial stress reduces cell proliferation in the dentate gyrus. However, little is known about how stress affects the proliferation kinetics of neural stem cells (NSCs) in the subventricular zone (SVZ), which provide new neurons to the olfactory bulb. We utilized a forced‐swim model of stress in the mouse and found that chronic stress decreased the number of NSCs in the SVZ. The reduction of NSC number persisted for weeks after the cessation of stress but was reversed by treatment with the antidepressant drugs fluoxetine and imipramine. We demonstrated by in vitro colony‐forming neurosphere assay that corticosterone attenuated neurosphere formation by adult NSCs and, in contrast, that serotonin increased the survival of NSCs. In addition, serotonin expanded the size of the NSC pool in the SVZ when it was infused into the lateral ventricle in vivo. These results suggest that, under chronic stress conditions, the number of NSCs is regulated by the actions of glucocorticoids and serotonin. These data provide insights into the molecular mechanisms underlying the pharmacological actions of antidepressant drugs. © 2007 Wiley‐Liss, Inc.
COMPOUND OBJECT DETECTION USING REGION CO-OCCURRENCE STATISTICS

Detection of heterogeneous objects that cannot be delineated as a single region through image segmentation is a difficult task in the analysis of very high spatial resolution images. We describe an approach that uses individual region occurrence and pairwise co-occurrence histograms in image windows using logistic regression classifiers that simultaneously perform feature selection and learn classification models from a small number of examples. The proposed generic method is used to learn a sparse discriminative model to localize different compound objects in large image scenes. Experiments using WorldView-2 data show that the method can successfully detect objects like school, retail, park, and residential areas using similar parameter settings.
Chk1-Mediated Phosphorylation of FANCE Is Required for the Fanconi Anemia/BRCA Pathway

ABSTRACT The eleven Fanconi anemia (FA) proteins cooperate in a novel pathway required for the repair of DNA cross-links. Eight of the FA proteins (A, B, C, E, F, G, L, and M) form a core enzyme complex, required for the monoubiquitination of FANCD2 and the assembly of FANCD2 nuclear foci. Here, we show that, in response to DNA damage, Chk1 directly phosphorylates the FANCE subunit of the FA core complex on two conserved sites (threonine 346 and serine 374). Phosphorylated FANCE assembles in nuclear foci and colocalizes with FANCD2. A nonphosphorylated mutant form of FANCE (FANCE-T346A/S374A), when expressed in a FANCE-deficient cell line, allows FANCD2 monoubiquitination, FANCD2 foci assembly, and normal S-phase progression. However, the mutant FANCE protein fails to complement the mitomycin C hypersensitivity of the transfected cells. Taken together, these results elucidate a novel role of Chk1 in the regulation of the FA/BRCA pathway and in DNA cross-link repair. Chk1-mediated phosphorylation of FANCE is required for a function independent of FANCD2 monoubiquitination.
A Multivariate Study of Medium Density Housing Development and Neighbourhood Change Within Australian Cities

Abstract The introduction of medium density housing development within suburban areas has been favoured by government as a means of improving the efficiency of land use, reducing the costs associated with the delivery of government infrastructure and services, increasing the opportunity for affordable housing and balancing social mix. However, it has been hypothesised that such development may be having a negative impact on local neighbourhoods in terms of social structure; for example, reducing diversity as measured by economic status and family makeup or in terms of local housing market performance as measured by price. This paper considers whether such outcomes are able to be measured in terms of social structure and housing market performance for three Australian cities: Adelaide, Sydney and Melbourne between 2001 and 2006. The analysis is conducted at a disaggregated level to more accurately measure impacts at the local level. The paper attempts to identify whether medium density housing development has any impact on housing market performance at a suburb level as measured by median price and if there are associated changes in neighbourhood structure as measured by social constructs developed using the technique of principal components analysis.
Rooted branching bisimulation as a congruence for probabilistic transition systems

We propose a probabilistic transition system specification format, referred to as probabilistic RBB safe, for which rooted branching bisimulation is a congruence. The congruence theorem is based on the approach of Fokkink for the qualitative case. For this to work, the theory of transition system specifications in the setting of labeled transition systems needs to be extended to deal with probability distributions, both syntactically and semantically. We provide a scheduler-free characterization of probabilistic branching bisimulation as adapted from work of Andova et al. for the alternating model. Counter examples are given to justify the various conditions required by the format.
An Adaptive Personalized Recommender Based on Web-Browsing Behavior Learning

In order to identify a user's personal preference in navigating the Web or to recommend collected Web information, it is very useful to analyze the user's Web-browsing behavior. However, it is difficult to determine which Web-browsing behaviors are influential on predicting a user's interest because each individual has his/her own habit and personal manner in surfing the Web and locating documents of interest. In this study, we propose an adaptive personalized recommender system based on a preference-thesaurus constructed by learning a user's Web-browsing behavior. The major components of the proposed recommender system are the Web-browsing behavior monitor, preference-thesaurus constructor, relevant document recommender, and user feedback learner. The adaptive nature of the proposed system allows the personalization of recommendation and the identification of the ever-changing influential Web-browsing behaviors. A proof-of-concept system is implemented and experiments are performed to verify the system's capability to personalize recommendation and to learn through user's feedbacks.
A 2.5D APPROACH TO SKIN WRINKLES SEGMENTATION

Wrinkles or creases are common structures on surfaces. Their detection is often challenging, and can be an important step for many different applications. For instance, skin wrinkle segmentation is a crucial step for quantifying changes in skin wrinkling and assessing the beneficial effects of dermatological and cosmetic anti-ageing treatments. A 2.5D approach is proposed in this paper to segment individual wrinkles on facial skin surface described by 3D point clouds. The method, based on mathematical morphology, only needs a few physical parameters as input, namely the maximum wrinkle width, the minimum wrinkle length, and the minimum wrinkle depth. It has been applied to data acquired from eye wrinkles using a fringe projection system. An accurate evaluation was made possible thanks to manual annotations provided by three different experts. Results demonstrate the accuracy of this novel method.
In the Body’s Eye: The computational anatomy of interoceptive inference

A growing body of evidence highlights the intricate linkage of exteroceptive perception to the rhythmic activity of the visceral body. In parallel, interoceptive inference theories of emotion and self-consciousness are on the rise in cognitive science. However, thus far no formal theory has emerged to integrate these twin domains; instead most extant work is conceptual in nature. Here, we introduce a formal model of cardiac active inference, which explains how ascending cardiac signals entrain exteroceptive sensory perception and confidence. Through simulated psychophysics, we reproduce the defensive startle reflex and commonly reported effects linking the cardiac cycle to fear perception. We further show that simulated ‘interoceptive lesions’ blunt fear expectations, induce psychosomatic hallucinations, and exacerbate metacognitive biases. Through synthetic heart-rate variability analyses, we illustrate how the balance of arousal-priors and visceral prediction errors produces idiosyncratic patterns of physiological reactivity. Our model thus offers the possibility to computationally phenotype disordered brain-body interaction.
MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows

MACS-VRPTW, an Ant Colony Optimization based approach useful to solve vehicle routing problems with time windows is presented. MACS-VRPTW is organized with a hierarchy of artificial ant colonies designed to successively optimize a multiple objective function: the first colony minimizes the number of vehicles while the second colony minimizes the traveled distances. Cooperation between colonies is performed by exchanging information through pheromone updating. We show that MACS-VRPTW is competitive with the best known existing methods both in terms of solution quality and computation time. Moreover, MACS-VRPTW improves some of the best solutions known for a number of problem instances in the literature.
The Development of a Motor-Free Short-Form of the Wechsler Intelligence Scale for Children–Fifth Edition

Purpose. This study aimed to develop a motor-free short-form of the Wechsler Intelligence Scale for Children–Fifth Edition (WISC-V) that allows clinicians to estimate the Full Scale Intelligence Quotients of youths with motor impairments. Method. Using the reliabilities and intercorrelations of six WISC-V motor-free subtests, psychometric methodologies were applied to develop look-up tables for four Motor-free Short-form indices: Verbal Comprehension Short-form, Perceptual Reasoning Short-form, Working Memory Short-form, and a Motor-free Intelligence Quotient. Index-level discrepancy tables were developed using the same methods to allow clinicians to statistically compare visual, verbal, and working memory abilities. Results. The short-form indices had excellent reliabilities (r = .92-.97) comparable to the original WISC-V. Conclusion. This motor-free short-form of the WISC-V is a reliable alternative for the assessment of intellectual functioning in youths with motor impairments. Clinicians are provided with user-friendly look-up tables, index level discrepancy tables, and base rates, displayed similar to those in the WISC-V manuals to enable interpretation of assessment results.
In vitro Antimicrobial Activities of Crude Extracts of Vernonia amygdalina and Croton macrostachyus against Some Bacterial and Fungal Test Pathogens

The aim of the present study was to investigate the antibacterial and antifungal activities of crude extracts of Vernonia amygdalina and Croton macrostachyus against four bacterial pathogenic species (i.e. Staphylococcus aureus, Streptococcus agalactiae, Salmonella typhi, Escherichia coli) and two fungal pathogenic species (i.e. Aspergillus flavus and Aspergillus niger). Antimicrobial activities of the resulting extracts were determined by measuring zone of inhibitions on cultures of six selected pathogens using the disc diffusion method. The minimum inhibitory concentration (MIC) of the two plant extracts against the same pathogens was determined using the broth dilution method. Chloroamphenicol was used as positive control for for bacterial pathogen and Tilt was also used as positive controls fungal pathogens. Meanwhile Dimethyl Sulfoxide was taken as a negative control for both. Highest percentage yield was recorded for methanol extract of V. amygdalina (14.89±0.25%) and the lowest yield was observed for the water extract of V. amygdalina (4.58±0.27). All the methanolic and ethanolic crude extracts had the highest growth inhibitory effects as compared with the water crude extracts on all bacterial pathogens. The methanol crude extract of C. macrostachyus had highest zone of inhibition (21±0.29 mm) against S. aureus, with a minimum inhibitory concentration of 25mg/ml. Similarly, the ethanol crude extract of C. macrostachyus had shown highest antifungal activity against A. niger with inhibition zone of 15.5±0.29. The results indicate the potential of these medicinal plants in treating some bacterial and fungal infection. Thus, further detailed studies are recommended to be carried out to characterize their bioactive compounds for development of new effective antimicrobial drugs.
Learning Traffic Patterns at Intersections by Spectral Clustering of Motion Trajectories

We address the problem of automatically learning the layout of a traffic intersection from trajectories of vehicles obtained by a vision tracking system. We present a similarity measure which is suitable for use with spectral clustering in problems that emphasize spatial distinctions between vehicle trajectories. The robustness of the method to small perturbations and its sensitivity to the choice of parameters are evaluated using real-world data
Large-time regular solutions to the modified quasi-geostrophic equation in Besov spaces

This paper is devoted to the study of the modified quasi-geostrophic equation \begin{document}$ \partial_t\theta+u\cdot\nabla\theta+\nu\Lambda^\alpha\theta = 0 \ \ \mbox{ with } \ \ u = \Lambda^\beta\mathcal{R}^\perp\theta $\end{document} in \begin{document}$ \mathbb{R}^2 $\end{document} . By the Littlewood-Paley theory, we obtain the local well-posedness and the smoothing effect of the equation in critical Besov spaces. These results are applied to show the global existence of regular solutions for the critical case \begin{document}$ \beta = \alpha-1 $\end{document} and the existence of regular solutions for large time \begin{document}$ t>T $\end{document} with respect to the supercritical case \begin{document}$ \beta >\alpha -1 $\end{document} in Besov spaces. Earlier results for the equation in Hilbert spaces \begin{document}$ H^s $\end{document} spaces are improved.
DDM : Statistical Admission Control Using Delay Distribution Measurement

Measurement-based admission control algorithms exploit the statistical multiplexing nature of input traffic to admit more flows into a system than is possible when assuming that each admitted flow is fully loaded. However, most previous measurement-based admission control algorithms did not have a satisfactory solution to the problem of guaranteeing distinct per-flow delay bounds while exploiting statistical multiplexing. This paper presents a novel technique, called Delay Distribution Measurement (DDM) based admission control algorithm, which effectively exploits statistical multiplexing by dynamically measuring the distribution of the ratios between actual packet delay and worst-case delay bound. With this delay ratio distribution, DDM is able to gauge the actual load of a system, estimate the actual resource requirement of new flows with distinct delay bound requirements, and eventually determine whether to admit them. The DDM algorithm develops a novel quantitative framework to exploit the well known fact that the actual delay experienced by most packets of a real-time flow is usually far smaller than its worst-case delay bound requirement. This framework also provides the additional flexibility to support flows with probabilistic delay bound requirements, i.e., flows for which a certain percentage of delay bound violations is tolerable. Flows that can tolerate more delay bound violations can reserve less resource than those that tolerate less, even though they have the same delay bound requirement. A comprehensive simulation study using Voice over IP traces shows that, when compared to deterministic admission control algorithms, the DDM algorithm can potentially increase the number of admitted flows (and link utilization) by up to a factor of3.0 when the delay violation probability is as small as10−5.