Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel data association schemes for the probability hypothesis density filter

The probability hypothesis density (PHD) filter is a practical alternative to the optimal Bayesian multi-target Alter based on finite set statistics. It propagates the PHD function, a first-order moment of the full multi-target posterior density. The peaks of the PHD function give estimates of target states. However, the PHD filter keeps no record of target identities and hence does not produce track-valued estimates of individual targets. We propose two different schemes according to which PHD filter can provide track-valued estimates of individual targets. Both schemes use the probabilistic data-association functionality albeit in different ways. In the first scheme, the outputs of the PHD filter are partitioned into tracks by performing track-to-estimate association. The second scheme uses the PHD filter as a clutter filter to eliminate some of the clutter from the measurement set before it is subjected to existing data association techniques. In both schemes, the PHD filter effectively reduces the size of the data that would be subject to data association. We consider the use of multiple hypothesis tracking (MHT) for the purpose of data association. The performance of the proposed schemes are discussed and compared with that of MHT.
Cognitive Gains from Gist Reasoning Training in Adolescents with Chronic-Stage Traumatic Brain Injury

Adolescents with traumatic brain injury (TBI) typically demonstrate good recovery of previously acquired skills. However, higher-order and later emergent cognitive functions are often impaired and linked to poor outcomes in academic and social/behavioral domains. Few control trials exist that test cognitive treatment effectiveness at chronic recovery stages. The current pilot study compared the effects of two forms of cognitive training, gist reasoning (top-down) versus rote memory learning (bottom-up), on ability to abstract meanings, recall facts, and utilize core executive functions (i.e., working memory, inhibition) in 20 adolescents (ages 12–20) who were 6 months or longer post-TBI. Participants completed eight 45-min sessions over 1 month. After training, the gist reasoning group (n = 10) exhibited significant improvement in ability to abstract meanings and increased fact recall. This group also showed significant generalizations to untrained executive functions of working memory and inhibition. The memory training group (n = 10) failed to show significant gains in ability to abstract meaning or on other untrained specialized executive functions, although improved fact recall approached significance. These preliminary results suggest that relatively short-term training (6 h) utilizing a top-down reasoning approach is more effective than a bottom-up rote learning approach in achieving gains in higher-order cognitive abilities in adolescents at chronic stages of TBI. These findings need to be replicated in a larger study; nonetheless, the preliminary data suggest that traditional cognitive intervention schedules need to extend to later-stage training opportunities. Chronic-stage, higher-order cognitive trainings may serve to elevate levels of cognitive performance in adolescents with TBI.
Orbital Involvement in Primary Paranasal Sinus Space Occupying Lesions

Orbit is an innocent bystander that is afflicted by lesions of the Paranasal Sinuses (PNS). Orbits share 3 walls with the sinuses, frontal sinuses on the supero-medial aspects of the orbits, ethmoid sinuses medially and maxillary sinuses inferiorly. Between the ethmoids and the orbits, there is lamina papyraecea which is a very thin bone. Between the maxillary sinus and the floor of the orbit, the bone is weakened by the passage of the infraorbital nerve. The periorbita or the periosteum of the orbit is a tough structure that resists invasion by tumors. Once the tumor transgresses this robust layer, it spreads to the orbital spaces easily due to lack of barriers that check tumor spread. There is also rich vascular communication between the sinuses and the orbit, which acts as a conduit for spread of infections and tumors. The last but not the least is the communication between the nasal cavity and the orbit through the Nasolacrimal Duct (NLD).
Bilingualism : Language and Cognition

Bilingualism: Language and Cognition / Volume 18 / Issue 01 / January 2015, pp 3 24 DOI: 10.1017/S1366728914000522, Published online: 27 November 2014 Link to this article: http://journals.cambridge. org/abstract_S1366728914000522 How to cite this article: VIRGINIA VALIAN (2015). Bilingualism and cognition. Bilingualism: Language and Cognition, 18, pp 3-24 doi:10.1017/ S1366728914000522 Request Permissions : Click here
Sp1 Transcription Factor and GATA1 cis-Acting Elements Modulate Testis-Specific Expression of Mouse Cyclin A1

Cyclin A1 is a male germ cell-specific cell cycle regulator that is essential for spermatogenesis. It is unique among the cyclins by virtue of its highly restricted expression in vivo, being present in pachytene and diplotene spermatocytes and not in earlier or later stages of spermatogenesis. To begin to understand the molecular mechanisms responsible for this narrow window of expression of the mouse cyclin A1 (Ccna1) gene, we carried out a detailed analysis of its promoter. We defined a 170-bp region within the promoter and showed that it is involved in repression of Ccna1 in cultured cells. Within this region we identified known cis-acting transcription factor binding sequences, including an Sp1-binding site and two GATA1-binding sites. Neither Sp1 nor GATA1 is expressed in pachytene spermatocytes and later stages of germ cell differentiation. Sp1 is readily detected at earlier stages of spermatogenesis. Site-directed mutagenesis demonstrated that neither factor alone was sufficient to significantly repress expression driven by the Ccna1 promoter, while concurrent binding of Sp1, and most likely GATA1 and possibly additional factors was inhibitory. Occupancy of Sp1 on the Ccna1 promoter and influence of GATA1-dependent cis-acting elements was confirmed by ChIP analysis in cell lines and most importantly, in spermatogonia. In contrast with many other testis-specific genes, the CpG island methylation status of the Ccna1 promoter was similar among various tissues examined, irrespective of whether Ccna1 was transcriptionally active, suggesting that this regulatory mechanism is not involved in the restricted expression of Ccna1.
Derivation of ontological relations using formal methods in a situation awareness scenario

This paper describes a case study of relation derivation within the context of situation awareness. First we present a scenario in which inputs are supplied by a simulated Level 1 system. The inputs are events annotated with terms from an ontology for situation awareness. This ontology contains concepts used to represent and reason about situations. The ontology and the annotations of events are represented in DAML and Rule-ML and then systematically translated to a formal method language called MetaSlang. Having all information expressed in a formal method language allows us to use a theorem prover, SNARK, to prove that a given relationship among the Level 1 objects holds (or that it does not hold). The paper shows a proof of concept that relation derivation in situation awareness can be done within a formal framework. It also identifies bottlenecks associated with this approach, such as the issue of the large number of potential relations that may have to be considered by the theorem prover. The paper discusses ways of resolving this as well as other problems identified in this study.
Dynamic Aspects of Statistical Classification

This paper discusses ideas for adaptive learning which can capture dynamic aspects of realworld datasets. Although some of these ideas have a general character and could be applied to any supervised algorithm, here we focus attention on a nearest neighbour classifier as well as linear, logistic and quadratic discriminant. The nearest neighbour classifier modifies the "training data" by keeping a record of usefulness as well as the age of the observation. The other classifiers use a quality control type-system to update rules appropriately. These methods are tried out on simulated data and real data from the credit industry.
A Political Approach to Building Female Capacity in Science and Technology for Poverty Alleviation in Transitional Societies in Africa

This paper presents a critical analysis of poverty reduction through female gender capacity building in science and technology. It addresses policy issues and future-oriented planning that best enhance the role of women's contribution towards sustainable development and the improvement of the quality of livelihood of the population. It looks at what factors impeded their participation in science and technology and how this can best possibly be ameliorated. The paper looks at the challenges and strategies for improving the status of women in Africa and how human capital development in the domain of science and technology will greatly enhance female gender input in reducing poverty and promoting growth. It is argued that science and technology have and will play a major role in contributing towards developmental challenges and changes. Furthermore, it will be maintained that without gender empowerment deepening their democratic participation and enhancing their access to the domain of credit facilities, land tenure issues and rights, and capacities in technological skills, the problem of poverty reduction will not be adequately addressed. There is no poverty reduction without female gender empowerment across the board. Female gender empowerment should begin with capacity building, giving greater access to their education in all disciplines so as to enable their climb to vital decision-making positions that enable holistic processes of socio-economic transformation. The conclusion is that there must be a clear vision and a comprehensive agenda for female human capital development.
Energetics of constant height level bounding in quadruped robots

In this paper, we investigate the energetics of constant height level bounding gaits in quadruped robots with asymmetric body-mass distribution along the longitudinal axis. Analytical expressions for mechanical specific resistance for two cases of bounding are derived: bounding with equal front and rear leg step lengths, and bounding with unequal front and rear leg step lengths. Specific resistance is found to be independent of mass distribution in the first case, and dependent in the second case. The quadruped robot has average nonzero acceleration/deceleration due to unsymmetric distribution of mass when front and rear leg step lengths are equal. Results show that lower body lengths, lower step lengths, and higher heights from the ground level give lower specific resistance. The effect of body-mass asymmetry is to accelerate in the first case, and to reduce specific resistance in the second case. This result provides some insight into why certain quadrupedal animals in nature evolved to have body-mass asymmetry.
Sensor Based Localization for Mobile Robots by Exploration and Selection of Best Direction

We present a strategy for resolving multiple hypotheses of a robot's state during global localization. The strategy operates in two stages. In the first stage a unique direction of the motion is sought that resolves or eliminates maximum number of hypotheses. In the second stage, among the frontier areas arising from the multiple hypotheses states, that frontier is chosen which resolves the maximum number of the hypotheses. The two stages are alternated till a unique hypothesis emerges. Simulation and experimental results verify the efficacy of this method. A comparison with other methods based on entropy minimization, and minimum distance travel portrays the advantage of the current methodology. A convergence proof for the algorithm is also presented.
The Generalized Dynamic Factor Model

This article proposes a new forecasting method that makes use of information from a large panel of time series. Like earlier methods, our method is based on a dynamic factor model. We argue that our method improves on a standard principal component predictor in that it fully exploits all the dynamic covariance structure of the panel and also weights the variables according to their estimated signal-to-noise ratio. We provide asymptotic results for our optimal forecast estimator and show that in finite samples, our forecast outperforms the standard principal components predictor.
Does Small Sample Size E ects Perturb the Dating of Business Cycle Regime Switching ?

Although Hamilton 1989 regime switching model is widely used for business cycle analysis, almost all the contributions deal with monthly or quaterly long series. The problem of small sample size eeect is not straightforward. In this paper we use the Gibbs Sampling simulations tool to derive the estimated parameters and evaluate the small sample bayesian posterior distribution of the estimators and their sensitivity. The results from simulated data and empirical example show evidence of the robustness of dating business cycle regime shifts in small sample case.
Mutant Fault Injection in Functional Properties of a Model to Improve Coverage Metrics

This paper proposes integrating mutation analysis into model checking to improve coverage metrics of digital circuits. In contrast to traditional mutation testing where mutant faults are generated and injected into the code description of the model, we apply a series of newly defined mutation operators directly to the model properties rather than to the model code. We claim that any mutant properties that are generated from the initial properties and validated by the model checker should be considered as new properties that have been missed during the initial verification procedure. Therefore, adding these newly identified properties to the existing list of properties improves the coverage metric of the formal verification and consequently lead to a more reliable design. Preliminary simulation results of applying this approach to a 4x4 Booth-Multiplier with 6 and 8 initial properties, demonstrates a 40% and 45% coverage improvement respectively compared to the initial coverage metric.
What Attributes Are Consumers Looking for in Sweet Cherries? Evidence from Choice Experiments

We investigate heterogeneous consumer preferences and willingness to pay (WTP) for various sweet cherry attributes using choice experiments. A mixed logit model and a latent-class logit model are used to estimate consumer WTP for the attributes and identify groups of consumers based on those preferences. We find that consumers of sweet cherries will pay the greatest premium for sweetness and the smallest premium for fruit size. Three groups of consumers are identified—flavor sensitive, price sensitive, and storage sensitive. The results are useful for suppliers of sweet cherries when adopting targeted marketing strategies.
On the Continuity of the Secrecy Capacity of Compound and Arbitrarily Varying Wiretap Channels

The wiretap channel models secure communication between two users in the presence of an eavesdropper who must be kept ignorant of transmitted messages. The performance of such a system is usually characterized by its secrecy capacity which determines the maximum transmission rate of secure communication. In this paper, the issue of whether or not the secrecy capacity is a continuous function of the system parameters is examined. In particular, this is done for channel uncertainty modeled via compound channels and arbitrarily varying channels, in which the legitimate users know only that the true channel realization is from a prespecified uncertainty set. In the former model, this realization remains constant for the entire duration of transmission, while in the latter the realization varies from channel use to channel use in an unknown and arbitrary manner. These models not only capture the case of channel uncertainty, but are also suitable for modeling scenarios in which a malicious adversary jams or otherwise influences the legitimate transmission. The secrecy capacity of the compound wiretap channel is shown to be robust in the sense that it is a continuous function of the uncertainty set. Thus, small variations in the uncertainty set lead to small variations in secrecy capacity. On the other hand, the deterministic secrecy capacity of the arbitrarily varying wiretap channel is shown to be discontinuous in the uncertainty set meaning that small variations can lead to dramatic losses in capacity.
Interactive indirect illumination using voxel-based cone tracing: an insight

Indirect illumination is an important element for realistic image synthesis, but its computation is expensive and highly dependent on the complexity of the scene and of the BRDF of the surfaces involved. While off-line computation and pre-baking can be acceptable for some cases, many applications (games, simulators, etc.) require real-time or interactive approaches to evaluate indirect illumination. We present a novel algorithm to compute indirect lighting in real-time that avoids costly precomputation steps and is not restricted to low frequency illumination. It is based on a hierarchical voxel octree representation generated and updated on-the-fly from a regular scene mesh coupled with an approximate voxel cone tracing that allows a fast estimation of the visibility and incoming energy. Our approach can manage two light bounces for both Lambertian and Glossy materials at interactive framerates (25-70FPS). It exhibits an almost scene-independent performance and allows for fully dynamic content thanks to an interactive octree voxelization scheme. In addition, we demonstrate that our voxel cone tracing can be used to efficiently estimate Ambient Occlusion.
The study of intracellular reactive oxygen species and mitochondrial membrane potential in normal cells exposed to diagnostic X ray

The aim was to study the intracellular reactive oxygen species and mitochondrial membrane potential in normal cells exposed to diagnostic X ray. Human peripheral blood mononucleated cells (PBMCs) were exposed to X ray from diagnostic x-ray machine operated at 50 killovoltage (kV), 25 milliampere (mA), 4 seconds (s) and 100 kV, 25 mA, 4 s for total doses at 1.24 mGy and 6.92 mGy, respectively. The intracellular reactive oxygen species and mitochondrial membrane potential were determined by using spectrofluorometric technique. The results show that the intracellular reactive oxygen species level and mitochondrial membrane potential are changed in irradiated cells when compared to control. However, the changing of intracellular reactive oxygen species level and mitochondrial membrane potential are not statistically significant (p > 0.05). These findings suggest that diagnostic x-ray does not affect to the intracellular reactive oxygen species level and mitochondrial membrane potential in PBMCs.
A Large-Scale Empirical Comparison of Object-Oriented Cohesion Metrics

Cohesion is an attribute of software design quality for which many metrics have been proposed. The different proposals have been made largely on theoretical grounds, with little evidence of actual use. This makes it difficult to provide advice to software developers as to how to interpret the measurements any given metric produces. This paper presents the first large-scale empirical study of object- oriented cohesion metrics. We apply 16 metrics from the literature, as well as a number of variations, to 92 open source and industry Java applications ranging in size from a few classes to several thousand, over 100,000 classes in all. Our results show that by and large applications have similar distributions of measurements according to any given metric, but that the distributions can be quite different across metrics. This provides useful information for the ongoing empirical validation efforts for cohesion metrics.
Nitrogen retention and plant uptake on a highly weathered central Amazonian Ferralsol amended with compost and charcoal

Leaching losses of N are a major limitation of crop production on permeable soils and under heavy rainfalls as in the humid tropics. We established a field trial in the central Amazon (near Manaus, Brazil) in order to study the influence of charcoal and compost on the retention of N. Fifteen months after organic-matter admixing (0–0.1 m soil depth), we added 15N-labeled (NH4)2SO4 (27.5 kg N ha–1 at 10 atom% excess). The tracer was measured in top soil (0–0.1 m) and plant samples taken at two successive sorghum (Sorghum bicolor L. Moench) harvests. The N recovery in biomass was significantly higher when the soil contained compost (14.7% of applied N) in comparison to only mineral-fertilized plots (5.7%) due to significantly higher crop production during the first growth period. After the second harvest, the retention in soil was significantly higher in the charcoal-amended plots (15.6%) in comparison to only mineral-fertilized plots (9.7%) due to higher retention in soil. The total N recovery in soil, crop residues, and grains was significantly (p < 0.05) higher on compost (16.5%), charcoal (18.1%), and charcoal-plus-compost treatments (17.4%) in comparison to only mineral-fertilized plots (10.9%). Organic amendments increased the retention of applied fertilizer N. One process in this retention was found to be the recycling of N taken up by the crop. The relevance of immobilization, reduced N leaching, and gaseous losses as well as other potential processes for increasing N retention should be unraveled in future studies.
Prior information preshapes the population representation of movement direction in motor cortex

SINGLE neuron activity was recorded in monkey motor cortex during the execution of pointing movements in six directions. The amount of prior information was manipulated by varying the range of precued directions. A distribution of neural population activation was constructed in the space of movement directions. This population representation of movement direction was preshaped by the precue. Peak location and width reflected the precued range of movement directions. From this preshaped form, the population representation evolved continuously in time and gradually in parameter space toward a more sharply peaked distribution centered on the parameter value specified by the response signal. A theoretical model of motor programming generated a similar temporal evolution of an activation field representing movement direction.
Pororobot: A Deep Learning Robot That Plays Video Q&A Games

Recent progress in machine learning has lead to great advancements in robot intelligence and human-robot interaction (HRI). It is reported that robots can deeply understand visual scene information and describe the scenes in natural language using object recognition and natural language processing methods. Imagebased question and answering (Q&A) systems can be used for enhancing HRI. However, despite these successful results, several key issues still remain to be discussed and improved. In particular, it is essential for an agent to act in a dynamic, uncertain, and asynchronous environment for achieving human-level robot intelligence. In this paper, we propose a prototype system for a video Q&A robot “Pororobot”. The system uses the state-of-the-art machine learning methods such as a deep concept hierarchy model. In our scenario, a robot and a child plays a video Q&A game together under real world environments. Here we demonstrate preliminary results of the proposed system and discuss some directions as future works.