Miracle-dz/UniFAR-FTUs huggingface dataset:
Importance of the Inverted Control in Measuring Holistic Face Processing with the Composite Effect and Part-Whole Effect

Holistic coding for faces is shown in several illusions that demonstrate integration of the percept across the entire face. The illusions occur upright but, crucially, not inverted. Converting the illusions into experimental tasks that measure their strength – and thus index degree of holistic coding – is often considered straightforward yet in fact relies on a hidden assumption, namely that there is no contribution to the experimental measure from secondary cognitive factors. For the composite effect, a relevant secondary factor is size of the “spotlight” of visuospatial attention. The composite task assumes this spotlight can be easily restricted to the target half (e.g., top-half) of the compound face stimulus. Yet, if this assumption were not true then a large spotlight, in the absence of holistic perception, could produce a false composite effect, present even for inverted faces and contributing partially to the score for upright faces. We review evidence that various factors can influence spotlight size: race/culture (Asians often prefer a more global distribution of attention than Caucasians); sex (females can be more global); appearance of the join or gap between face halves; and location of the eyes, which typically attract attention. Results from five experiments then show inverted faces can sometimes produce large false composite effects, and imply that whether this happens or not depends on complex interactions between causal factors. We also report, for both identity and expression, that only top-half face targets (containing eyes) produce valid composite measures. A sixth experiment demonstrates an example of a false inverted part-whole effect, where encoding-specificity is the secondary cognitive factor. We conclude the inverted face control should be tested in all composite and part-whole studies, and an effect for upright faces should be interpreted as a pure measure of holistic processing only when the experimental design produces no effect inverted.
Fusing global and regional features for image classification

This paper presents a novel approach to image classification based on the fusion of global and regional features, which are helpful to describe image semantics to classification, in which vague sets for positive and negative evidences is applied to analyze and optimize the decisions obtained by multi-classifiers. Through integrating two sides of multiple classification decisions, the classification is optimized and synthesized, thus the processing and results will be both powerful and stable. Experimental results show that the performance of the classification is greatly improved.
Scalable trigger processing

Current database trigger systems have extremely limited scalability. This paper proposes a way to develop a truly scalable trigger system. Scalability to large numbers of triggers is achieved with a trigger cache to use the main memory effectively, and a memory-conserving selection predicate index based on the use of unique expression formats called expression signatures. A key observation is that if a very large number of triggers are created, many will have the same structure, except for the appearance of different constant values. When a trigger is created, tuples are added to special relations created for expression signatures to hold the trigger's constants. These tables can be augmented with a database index or main-memory index structure to serve as a predicate index. The design presented also uses a number of types of concurrency to achieve scalability, including token (tuple)-level, condition-level, rule action-level and data-level concurrency.
Ultra-High-Frequency Transaction Data Modeling and Application

This paper describes ultra-high-frequency data with marked point process, defines transaction process intensity to represent both transaction time interval changes and marks changes, derives sample function density and its maximum likelihood estimating formulation. As an example, when trade prices are Brown motions, price process and transaction arrival time process are independent each other, we have estimated stock price volatility. The results are that the less the sampling time interval, the nearer the estimated price volatility to that in ultra-high-frequency data.
Extracting patterns of single-trial EEG using an adaptive learning algorithm

The improvement of brain imaging technique brings about an opportunity for developing and investigating brain-computer interface (BCI) which is a way to interact with computer and environment. The measured brain activities usually constitute the signals of interest and noises. Applying the portable device and removing noise are the benefits to real-world BCI. In this study, one portable electroencephalogram (EEG) system non-invasively acquired brain dynamics through wireless transmission while six subjects participated in the rapid serial visual presentation (RSVP) paradigm. The event-related potential (ERP) was traditionally estimated by ensemble averaging (EA) to increase the signal-to-noise ratio. One adaptive filter of data-reusing radial basis function network (DR-RBFN) was also utilized as the estimator. The results showed that this portable EEG system stably acquired brain activities. Furthermore, the task-related potentials could be clearly explored from the limited samples of EEG data through DR-RBFN. According to the artifact-free data from the portable device, this study demonstrated the potential to move the BCI from laboratory research to real-life application in the near future.
ELISA reagent coverage evaluation by affinity purification tandem mass spectrometry

ABSTRACT Host cell proteins (HCPs) must be adequately removed from recombinant therapeutics by downstream processing to ensure patient safety, product quality, and regulatory compliance. HCP process clearance is typically monitored by enzyme-linked immunosorbent assay (ELISA) using a polyclonal reagent. Recently, mass spectrometry (MS) has been used to identify specific HCP process impurities and monitor their clearance. Despite this capability, ELISA remains the preferred analytical approach due to its simplicity and throughput. There are, however, inherent difficulties reconciling the protein-centric results of MS characterization with ELISA, or providing assurance that ELISA has acceptable coverage against all process-specific HCP impurities that could pose safety or efficacy risks. Here, we describe efficient determination of ELISA reagent coverage by proteomic analysis following affinity purification with a polyclonal anti-HCP reagent (AP-MS). The resulting HCP identifications can be compared with the actual downstream process impurities for a given process to enable a highly focused assessment of ELISA reagent suitability. We illustrate the utility of this approach by performing coverage evaluation of an anti-HCP polyclonal against both an HCP immunogen and the downstream HCP impurities identified in a therapeutic monoclonal antibody after Protein A purification. The overall goal is to strategically implement affinity-based mass spectrometry as part of a holistic framework for evaluating HCP process clearance, ELISA reagent coverage, and process clearance risks. We envision coverage analysis by AP-MS will further enable a framework for HCP impurity analysis driven by characterization of actual product-specific process impurities, complimenting analytical methods centered on consideration of the total host cell proteome.
Use of high concentrations of carbon dioxide for stunning rabbits reared for meat production

Abstract: An investigation was performed to determine whether high concentrations of carbon dioxide (CO 2 ) at 70-98% in atmospheric air are a suitable alternative for stunning rabbits compared to conventional approaches such as electronarcosis. Aversion to the gas and efficacy in causing prolonged unconsciousness and death were studied in a total of 480 rabbits by means of behavioural parameters, physiological indicators (presence of rhythmic breathing and corneal reflex) and electroencephalography (EEG, brain function). The use of any of the 4 studied concentrations of the gas caused more nasal discomfort and vocalisations than the use of atmospheric air (P<0.001). EEG activity confirmed that loss of posture is a good indicator of the onset of unconsciousness in rabbits exposed to CO 2 , occurring earlier (P<0.05) at 90 and 98% than at 70 and 80%. Rabbits showed signs of aversion for 15 s before the onset of unconsciousness, which occurred around 30 s after the beginning of the exposure to the gas, similar to species such as swine in which high concentrations of CO 2 are also used for stunning. CO 2 at 80 to 98% is suggested as a reasonable concentration range to induce a long state of unconsciousness and death in rabbits, while 70% CO 2 is not recommended because it requires too long duration of exposure (more than 360 s) to ensure effectiveness. Despite the advantages in terms of pre-stun handling and irreversibility, CO 2 is not free of animal welfare concerns. In consequence, a debate is necessary to ascertain if CO 2 can be considered a suitable alternative to stun rabbits, considering the advantages and drawbacks cited, quantified in the present study as 15 s of aversion (nasal discomfort and vocalisations) before losing posture.
An improved PHD filter based on variational Bayesian method for multi-target tracking

This paper presents an improved probability hypothesis density (PHD) filter for the multi-target tracking scenarios with unknown measurement noise variances. By introducing the variational Bayesian (VB) method into the PHD recursion, not only the states and number of targets, but also the measurement noise variances can be jointly estimated. Moreover, a closed-form solution to the improved PHD filter for linear Gaussian multi-target model is derived using inverse Gamma and Gaussian mixtures. Simulation results demonstrate the effectiveness of the proposed algorithm for the multi-target tracking scenarios with unknown measurement noise variances.
The Web as a Privacy Lab

The privacy dangers of data proliferation on the Web are well-known. Information on the Web has facilitated the deanonymization of anonymous bloggers, the de-sanitization of government records and the identification of individuals based on search engine queries. What has received less attention is Web-mining in support of privacy. In this position paper we argue that the very ability ofWeb data to breach privacy demonstrates its value as a laboratory for the detection of privacy breaches before they happen. In addition, we argue that privacy-invasive services may become privacy-respecting by mining publicly available Web data, with little decrease in performance and efficiency.
Design of adaptive channel equalizer using filterbank FIR sign-regressor FLANN

Modern communication systems need equalizers for reliable communication in noisy and non-linear channels. A properly designed equalizer can overcome the effects of inter-symbol interference which deters the communication process in noisy and bandlimited channels. In this paper a functional link ANN (FLANN) based equalizer has been discussed. The equalizer structure has been created using a filterbank sign regressor FLANN approach. The performance of this equalizer has been compared with the conventional FIR filter based and general FLANN based equalizers. The simulation results show that the proposed equalizer outperforms the other equalizers which are considered for comparison in the study.
Skills-Based International Volunteering Among Older Adults From the United States

International volunteering among older adults is an under-researched, yet growing, market. Policy experts and volunteer resource managers have proposed recruiting older volunteers to meet a demand for skilled volunteers that are able to serve for a longer duration abroad. This article utilizes data from the U.S. Current Population Survey (CPS) to assess how well older international volunteers from the United States fit this profile. Administrative implications are proposed as a way to further increase participation of skilled older adults in mutually beneficial international volunteer service.
Automatic Construction of a Folksonomy-Based Visual Ontology

Recently, Folksonomy attracts attentions as a new method to index large-scale image databases. In the Folksonomy-style image databases, they allows users to attach keywords to images as “tags”. Since tag words are uncontrolled, they have various and many kinds of tags associated with images. This is much different from conventional image databases. In this paper, we propose a novel method to extract hierarchical structure on relations between tags from Folksonomy. The tag structure we extract can be used as an ontology for image database search which reflects both textual and visual relations between tags. In the proposed method, at first, we collect millions of tag-attached-images from Flickr which is the world-largest Folksonomy-style image database, and remove noise images from them. Next, we estimate concept vectors for highly-frequent tags based on only visual features, only tag word features and combined features of both visual and textual features, and compute JS divergence and entropy for three kinds of concept vectors. Finally we estimate hierarchical structures between tags regarding three kinds of concept vectors. In the experiments, we show the obtained hierarchical structure, and it includes interesting relations which sometimes are difficult to be discovered by human. In addition, as its application, we used and evaluated the obtained ontology for query expansion of text-tag-based image search over Flickr. These results indicate that the proposed method is promising and the structure is expected to help image search and some other applications.
Parts orienting with shape uncertainty

Parts manufactured to tolerances have shape variations. Most work in robotic manipulation assumes that part shape does not vary. Orienting devices such as bowl feeder frequently fail due to variations in part shape. In this paper we develop techniques to orientate parts with shape uncertainty. We present a shape uncertainty model and describe the nondeterminism in parts orienting that arises from shape uncertainty. We characterize a class of parts that can be reliably oriented with sensor-based and sensorless orienting plans under shape uncertainty. We present implemented planners that generate orienting plans for the entire variational class of part shapes given a nominal part shape and shape uncertainty bounds. We describe experiments to demonstrate generated plans and outline issues for future work.
Stability measure of entropy estimate and its application to language model evaluation

We propose in this paper a stability measure of entropy estimate based on the principle of Bayesian statistics. Stability, or how the estimates vary as training set does, is a critical issue especially for the problems where parameter-to-data ratio is extremely high as in language modeling and text compression. There are two natural estimates of entropy, one being the classical estimate and the other the Bayesian estimate. We show that the difference of them is in strong positive correlation with the variance of the classical estimate when it is not so small, and propose this difference as stability measure of entropy estimate. In order to evaluate it for language models where estimates are available but posterior distribution is not in general, we suggest to use a Dirichlet distribution so that its expectation agrees with the estimated parameters and that the total count is preserved at the same time. Experiments on two benchmark corpora show that the proposed measure indeed reflects the stability of classical entropy estimates.
Exploring New Ways of Integration, Visualization and Interaction with Geotechnical and Geophysical Data

The work presented in this paper aims at exploring new ways of integrating, visualizing and interacting with geotechnical and geophysical data that may be more rich and interactive than those offered by most current Geographic Information Systems (GIS). Some visualization techniques enabling simultaneous visualization of the several data types available in our case study are proposed. Moreover, methods were developed to guide experts while defining layers and other relevant geological structures. The work is still in an early stage and is main goal has been assessing the validity and adequacy of the proposed techniques to the specific geotechnical and geophysical data under consideration.
Mobilizable genomic islands: going mobile with oriT mimicry

Many bacterial chromosomes contain genomic islands, large DNA segments that became incorporated into the chromosome following their horizontal transmission. However, the mechanisms that mediate the lateral transfer of genomic islands are for the most part unknown. In this issue of Molecular Microbiology, Daccord et al. describe a new type of transmissible genomic island that can be mobilized by co‐resident integrating conjugative elements (ICEs). These ‘mobilizable genomic islands’ (MGIs) require many ICE‐encoded factors for their transmission, including transcription activators to induce MGI excision, the relaxase to initiate transfer at the MGI oriT and the conjugation machinery to transport MGI DNA to recipient cells. However, MGIs encode their own integrases, which enable their recombination with the chromosome of a new host, as well as a variety of other genes that do not have functions related to mobility. The MGI oriT, which resembles the ICE oriT, can also serve as a site for initiation of ICE‐mediated conjugative transfer of large regions of chromosomal DNA. Overall, these findings raise the possibility that mobilization of chromosomal DNA from cyptic oriTs within genomic islands or elsewhere on the chromosome could be more common place than has been previously appreciated.
GRAIL: a general purpose localization system

Purpose – The purpose of this paper is to describe a general purpose localization system, GRAIL. GRAIL provides real‐time, adaptable, indoor localization for wireless devices.Design/methodology/approach – In order to localize as diverse a set of devices as possible, GRAIL utilizes a centralized, anchor‐based approach. GRAIL defines an abstract data model for various system components to support different physical modalities. The scalable architecture of GRAIL provides maximum flexibility to integrate various localization algorithms.Findings – The authors show through real deployments that GRAIL functions over a variety of physical modalities, networks, and algorithms. Further, the authors found that a centralized solution has critical advantages over distributed implementations for handling privacy concerns.Originality/value – A key contribution of this system is its universal approach: it can integrate different hardware and software capabilities within a single localization framework. The deployment of .
A high‐resolution chemical and structural study of framboidal pyrite formed within a low‐temperature bacterial biofilm

A novel, anaerobically grown microbial biofilm, scraped from the inner surface of a borehole, 1474 m below land surface within a South African, Witwatersrand gold mine, contains framboidal pyrite. Water flowing from the borehole had a temperature of 30.9 °C, a pH of 7.4, and an Eh of –50 mV. Examination of the biofilm using X‐ray diffraction, field emission gun scanning electron microscope equipped for energy dispersive X‐ray microanalysis demonstrated that the framboids formed within a matrix of bacteria and biopolymers. Focused ion beam sectioning of framboids followed by NEXAFS measurements using both scanning transmission X‐ray microscopy and X‐ray photoelectron emission microscopy revealed that the pyrite crystals grew within an organic carbon matrix consisting of exopolysaccharides and possibly extracellular DNA, which is intuitively important in sulfide mineral diagenesis. Growth of individual pyrite crystals within the framboid occurred inside organic templates confirms the association between framboidal pyrite and organic materials in low‐temperature diagenetic environments and the important role of microenvironments in biofilms in regulating geochemical cycles.
Fueling Low-Level AGN Activity through Stochastic Accretion of Cold Gas

Using a simple description of feedback from black hole growth, we develop an analytic model for the fueling of Seyferts (low-luminosity active galactic nuclei [AGNs]) and their relation to their host galaxies, Eddington ratio distributions, and cosmological evolution. We derive a solution for the time evolution of accretion rates in a feedback-driven blast wave, applicable to large-scale outflows from bright quasars in galaxy mergers, low-luminosity AGNs, and black holes or neutron stars in supernova remnants. Under the assumption that cold gas stochastically accretes onto a central supermassive black hole at a rate set by the dynamics of that gas, our solution determines the evolution of Seyfert light curves. Using this model, we predict the Seyfert luminosity function, duty cycles and AGN "lifetimes," and the distribution of host morphologies, Eddington ratios, and obscuration as a function of AGN luminosity and black hole mass, and we find agreement with observations at z = 0. We consider the breakdown of the contribution from this mechanism and from stellar wind and virialized hot gas accretion and merger-driven activity. We also make specific predictions for the weak evolution of the Seyfert luminosity function; i.e., luminosity function of quiescent as opposed to merger-driven activity, as a function of redshift, and for changes in both the slope and scatter of the MBH-σ relation at low MBH. Our modeling provides a quantitative and physical distinction between local, low-luminosity quiescent AGN activity and violent, merger-driven bright quasars. In our picture, the quiescent mode of fueling dominates over a wide range of luminosities (-15 ≳ MB ≳ -22) at z = 0, where most black hole growth occurs in objects with MBH ≲ 107 M☉, in S0 and Sa/b galaxies. However, quasar activity from gas-rich mergers evolves more rapidly with redshift, and by z = 1, quiescent fueling is important only at luminosities an order of magnitude or more below the "break" in the luminosity function. Consequently, although non-merger-driven fueling is important for black hole growth and the MBH-σ relation at low MBH, it does not significantly contribute to the black hole mass density of the universe or to cosmological backgrounds.
The return migration experiences of Ethiopian women trafficked to Bahrain: ‘ … for richer or poorer, let me be on the hands of my people … ’

ABSTRACT This study draws upon the return experiences of Ethiopian women trafficked to the Middle East. Understanding these experiences is critical to informing the design of effective government policy to mitigate obstacles to return and reintegration. This study was conducted in Addis Ababa with five women who were trafficked to Bahrain and later returned to Ethiopia. Action research was used to establish an inquiry group of women in order to produce a viable vision for successful reintegration. Despite initial high hopes, the returnees did not see migration as producing positive returns. All five participants agreed that their experiences in the destination were devastating and thus they were relieved to have returned to their home country. Nonetheless, reintegration was a difficult process for them. In addition to not accumulating enough savings to enable them to reintegrate economically, they all faced misunderstandings and impractical expectations from their families and community. The women suggested that adequate protection from law enforcement, facilitation of income-generating activities, and improved access to rehabilitation and medical services are important elements of successful return and reintegration. Effective return and reintegration policy is needed to ensure that trafficked returnees can become productive citizens in their home country.