Miracle-dz/UniFAR-FTUs huggingface dataset:
Mixed Effects of Elevated pCO2 on Fertilisation, Larval and Juvenile Development and Adult Responses in the Mobile Subtidal Scallop Mimachlamys asperrima (Lamarck, 1819)

Ocean acidification is predicted to have severe consequences for calcifying marine organisms especially molluscs. Recent studies, however, have found that molluscs in marine environments with naturally elevated or fluctuating CO2 or with an active, high metabolic rate lifestyle may have a capacity to acclimate and be resilient to exposures of elevated environmental pCO2. The aim of this study was to determine the effects of near future concentrations of elevated pCO2 on the larval and adult stages of the mobile doughboy scallop, Mimachlamys asperrima from a subtidal and stable physio-chemical environment. It was found that fertilisation and the shell length of early larval stages of M. asperrima decreased as pCO2 increased, however, there were less pronounced effects of elevated pCO2 on the shell length of later larval stages, with high pCO2 enhancing growth in some instances. Byssal attachment and condition index of adult M. asperrima decreased with elevated pCO2, while in contrast there was no effect on standard metabolic rate or pHe. The responses of larval and adult M. asperrima to elevated pCO2 measured in this study were more moderate than responses previously reported for intertidal oysters and mussels. Even this more moderate set of responses are still likely to reduce the abundance of M. asperrima and potentially other scallop species in the world’s oceans at predicted future pCO2 levels.
A Novel Text Representation Model for Text Classification

The text representation in text classification is usually a sequence of terms. As the number of terms becomes very high, it is greatly time-consuming to perform existed text categorization tasks. In this paper we presented a novel text representation model for text classification which greatly reduced the required resources. This model represents text with several features. Each feature corresponds to a theme that emerged from a set of related articles. We also introduce an efficient way to build the model. The proposed model has been applied to naive bayes classifier and experiments on Reuters-21578 corpus have shown that the efficiency is greatly improved without sacrificing classification accuracy even when the dimension of the input space is significantly reduced.
Testing of User-Configurable Software Systems Using Firewalls

User-configurable software systems present many challenges to software testers. These systems are created to address a large number of possible uses, each of which is based on a specific configuration. As configurations are made up of groups of configurable elements and settings, a huge number of possible combinations exist. Since it is infeasible to test all configurations before release, many latent defects remain in the software once deployed. An incremental testing process is presented to address this problem, including examples of how it can be used with various user-configurable systems in the field. The proposed solution is evaluated with a set of empirical studies conducted on two separate ABB software systems using real customer configurations and changes. The three case studies analyzed failures reported by many different customers around the world and show that this incremental testing process is effective at detecting latent defects exposed by customer configuration changes in user-configurable systems.
Comparative Evaluation of Moving Shadow Detection Algorithms

Moving shadows need careful consideration in the development of robust dynamic scene analysis systems. Moving shadow detection is critical for accurate object detection in video streams, since shadow points are often misclassified as object points causing errors in segmentation and tracking. Many algorithms have been proposed in the literature that deal with shadows. However, a comparative evaluation of the existing approaches is still lacking. In this paper, the full range of problems underlying the shadow detection are identified and discussed. We present a comprehensive survey of moving shadow detection approaches. We organize contributions reported in the literature in four classes. We also present a comparative empirical evaluation of representative algorithms selected from these four classes. Quantitative (detection and discrimination accuracy) and qualitative metrics (scene and object independence, flexibility to shadow situations and robustness to noise) are proposed to evaluate these classes of algorithms on a benchmark suite of indoor and outdoor video sequences. These video sequences and associated “ground-truth” data are made available athttp://cvrr.ucsd. edu:88/aton/shadow to allow for others in the community to experiment with new algorithms and metrics. Keywords— Shadow detection, performance evaluation, dynamic scene analysis, object detection, tracking, segmentation, traffic scene analysis, visual surveillance
Inorganic Polyphosphate in Escherichia coli: the Phosphate Regulon and the Stringent Response

ABSTRACT Escherichia coli transiently accumulates large amounts of inorganic polyphosphate (polyP), up to 20 mM in phosphate residues (Pi), in media deficient in both Pi and amino acids. This transient accumulation is preceded by the appearance of nucleotides ppGpp and pppGpp, generated in response to nutritional stresses. Mutants which lack PhoB, the response regulator of the phosphate regulon, do not accumulate polyP even though they develop wild-type levels of (p)ppGpp when subjected to amino acid starvation. When complemented with a phoB-containing plasmid,phoB mutants regain the ability to accumulate polyP. PolyP accumulation requires high levels of (p)ppGpp independent of whether they are generated by RelA (active during the stringent response) or SpoT (expressed during Pi starvation). Hence, accumulation of polyP requires a functional phoB gene and elevated levels of (p)ppGpp. A rapid assay of polyP depends on its adsorption to an anion-exchange disk on which it is hydrolyzed by a yeast exopolyphosphatase.
Field and lab conditions alter microbial enzyme and biomass dynamics driving decomposition of the same leaf litter

Fluctuations in climate and edaphic factors influence field decomposition rates and preclude a complete understanding of how microbial communities respond to plant litter quality. In contrast, laboratory microcosms isolate the intrinsic effects of litter chemistry and microbial community from extrinsic effects of environmental variation. Used together, these paired approaches provide mechanistic insights to decomposition processes. In order to elucidate the microbial mechanisms underlying how environmental conditions alter the trajectory of decay, we characterized microbial biomass, respiration, enzyme activities, and nutrient dynamics during early (<10% mass loss), mid- (10–40% mass loss), and late (>40% mass loss) decay in parallel field and laboratory litter bag incubations for deciduous tree litters with varying recalcitrance (dogwood < maple < maple-oak mixture < oak). In the field, mass loss was minimal (<10%) over the first 50 days (January–February), even for labile litter types, despite above-freezing soil temperatures and adequate moisture during these winter months. In contrast, microcosms displayed high C mineralization rates in the first week. During mid-decay, the labile dogwood and maple litters in the field had higher mass loss per unit enzyme activity than the lab, possibly due to leaching of soluble compounds. Microbial biomass to litter mass (B:C) ratios peaked in the field during late decay, but B:C ratios declined between mid- and late decay in the lab. Thus, microbial biomass did not have a consistent relationship with litter quality between studies. Higher oxidative enzyme activities in oak litters in the field, and higher nitrogen (N) accumulation in the lab microcosms occurred in late decay. We speculate that elevated N suppressed fungal activity and/or biomass in microcosms. Our results suggest that differences in microbial biomass and enzyme dynamics alter the decay trajectory of the same leaf litter under field and lab conditions.
Barrier Disrupting Effects of Alternaria Alternata Extract on Bronchial Epithelium from Asthmatic Donors

Sensitization and exposure to the allergenic fungus Alternaria alternata has been associated with increased risk of asthma and asthma exacerbations. The first cells to encounter inhaled allergens are epithelial cells at the airway mucosal surface. Epithelial barrier function has previously been reported to be defective in asthma. This study investigated the contribution of proteases from Alternaria alternata on epithelial barrier function and inflammatory responses and compared responses of in vitro cultures of differentiated bronchial epithelial cells derived from severely asthmatic donors with those from non-asthmatic controls. Polarised 16HBE cells or air-liquid interface (ALI) bronchial epithelial cultures from non-asthmatic or severe asthmatic donors were challenged apically with extracts of Alternaria and changes in inflammatory cytokine release and transepithelial electrical resistance (TER) were measured. Protease activity in Alternaria extracts was characterised and the effect of selectively inhibiting protease activity on epithelial responses was examined using protease inhibitors and heat-treatment. In 16HBE cells, Alternaria extracts stimulated release of IL-8 and TNFα, with concomitant reduction in TER; these effects were prevented by heat-treatment of the extracts. Examination of the effects of protease inhibitors suggested that serine proteases were the predominant class of proteases mediating these effects. ALI cultures from asthmatic donors exhibited a reduced IL-8 response to Alternaria relative to those from healthy controls, while neither responded with increased thymic stromal lymphopoietin (TSLP) release. Only cultures from asthmatic donors were susceptible to the barrier-weakening effects of Alternaria. Therefore, the bronchial epithelium of severely asthmatic individuals may be more susceptible to the deleterious effects of Alternaria.
Dietary Factors in Relation to Helicobacter pylori Infection

Background and Aim. Helicobacter pylori (HP) and diet are both risk factors for gastric cancer. The aim of this study was to evaluate the Helicobacter pylori infection and dietary habits common in Khuzestan province. Methods. This cross-sectional study was conducted in 2011–2013 on 374 patients. Participants were interviewed using a food frequency questionnaire and tissue sample of the antrum was sent for pathology lab. The histopathological major variables were graded on a scale of 3 (mild, moderate, and severe) and data analyzed using nonparametric tests. Results. In this study, of 160 patients (43%) that were determined, 8.1 percent had severe contamination. Among dietary patterns, relationship between energy intake and carbohydrate with H. pylori was significant. A direct association was found between mean daily intakes of sausage (P = 0.001) and burgers (P < 0.05) with HP infection. Low intake of fresh vegetables and fruits was the most significant risk factors (P < 0.05). Conclusion. There is a possibility that some dietary factors such as consumption of fast foods and low intake of fresh vegetables may increase the chance of HP and severity of this infection.
Circular Road Sign Analysis and Visual Localization Approach Based on Monocular Vision

This paper proposes a circular road sign detection and analysis method based on monocular vision, which can be used for visual localization of mobile robots. To achieve a stable and reliable real-time detection, a simple but useful circular road sign has been designed. By color-based image segmentation, edge detection, contour selection, ellipse fitting and sign verification, road sign can be detected from monocular vision. Furthermore, perspective geometry is carried out to calculate the robots position based on sign detection result and sign position. The proposed method is experimented on a robot platform. The experimental results show that the method achieves a promising performance and meets the requirement of real-time and practical situations.
The Effect of Platelet Rich Plasma on Chondrogenic Differentiation of Human Adipose Derived Stem Cells in Transwell Culture

Objective(s): Platelet-rich plasma (PRP) has recently emerged as a promising strategy in regenerative medicine due to its multiple endogenous growth factors. Little is known about the role of PRP as a promoter in chondrogenesis of human adipose derived stem cells (hADSCs). The aim of this study was to determine whether PRP may be considered as a natural and easy achievable source of growth factors to promote the chondrogenic differentiation of hADSCs in Transwell culture. Materials and Methods : Biochemical, immunohistological and molecular assays were used to evaluate the effect of different concentrations (5%, 10%, and 15%) of PRP on chondrogenic differentiation of hADSCs in Transwell culture. Results : The cells in the presence of 10% PRP produced markedly higher amounts of GAG and DNA, in comparison to the control group. PRP also increased chondrogenic markers in these cells, such as sox-9, aggrecan and collagen type II. A high expression level of collagen type X as a hypertrophic marker was observed in cartilage produced by using either PRP or TGF-β1. Conclusion : Our findings indicate that autologous PRP at an optimum concentration had beneficial effects on differentiation of hADSCs in Transwell culture. Further, in vivo studies are necessary to fully define the clinical implications of PRP.
Visualizing Trumps Vision in Training Attention

Mental imagery can have powerful training effects on behavior, but how this occurs is not well understood. Here we show that even a single instance of mental imagery can improve attentional selection of a target more effectively than actually practicing visual search. By recording subjects’ brain activity, we found that these imagery-induced training effects were due to perceptual attention being more effectively focused on targets following imagined training. Next, we examined the downside of this potent training by changing the target after several trials of training attention with imagery and found that imagined search resulted in more potent interference than actual practice following these target changes. Finally, we found that proactive interference from task-irrelevant elements in the visual displays appears to underlie the superiority of imagined training relative to actual practice. Our findings demonstrate that visual attention mechanisms can be effectively trained to select target objects in the absence of visual input, and this results in more effective control of attention than practicing the task itself.
A Novel Robust Colour Watermarking Scheme for Colour Watermark Images in Frequency Domain

Digital colour watermarking has become essential and important copyright protection schemes in multimedia industry. Distribution of digital documents, especially colour images, over the internet has also become increasingly cost-efficient and widespread. The increased importance of digital media brings new challenges for securing the distribution of digital multimedia to make it both profitable for the document owner and reliable for the customer. This paper presents a novel and robust colour watermarking scheme of embedding colour watermark into colour host image. The technique shows efficient extraction of watermark with high PSNR of embedded image. The proposed algorithm is experimented in frequency domain in which combination of DWT and DCT is applied on the host image. The high energy content of colour watermark i.e. low frequency DCT coefficients are embedded into mid frequency DCT coefficients of high frequency components of multi resolved host colour image. The proposed algorithm is more secure, robust and efficient because of use of DWT and DCT. Performance evaluation and testing of the proposed algorithm using standard benchmarks reveals that it is fairly robust against a wide range of signal and image processing operations.
The Economic Dimensions of the Foreclosure Crisis

This paper proposes to examine the significance of both loan/borrower characteristics and macroeconomic factors in the mortgage default and foreclosure crisis in the New York City metropolitan area in the years immediately preceding the collapse of the housing bubble. Matching the full set of 2010 New York State pre-foreclosure filings to home loans originated from 2004 through 2008; the proposal seeks to expand upon the scope of earlier studies, incorporating measures of macroeconomic conditions together with loan characteristics and borrower demographics. Following a review of the literature and of the relative success of loan modification programs, we conclude with a brief proposal for a comprehensive study.
On the Periodic Lorentz Gas and the Lorentz Kinetic Equation (

We prove that the Boltzmann-Grad limit of the Lorentz gas with periodic distribution of scatterers cannot be described with a linear Boltzmann equation. This is at variance with the case of a Pois- son distribution of scatterers, for which the convergence to the linear Boltzmann equation was proved by Gallavotti (Phys. Rev. (2) 185, 308 (1969)). The arguments presented here complete the analysis in (Golse- Wennberg, M2AN Model. Math. et Anal. Numer. 34, 1151 (2000)), where the impossibility of a kinetic description was established only in the case of absorbing obstacles. The proof is based on estimates on the distribu- tion of free-path lengths established in (Golse-Wennberg loc.cit.) and in (Bourgain-Golse-Wennberg, Commun. Math. Phys. 190, 491 (1998)), and on a classical result on the spectrum of the linear Boltzmann equation which can be found in (Ukai-Point-Ghidouche, J. Math. Pures Appl. (9) 57, 203 (1978)).
CVaR hedging under stochastic interest rate

In this paper we assess the partial hedging problems by formulating hedging strategies that minimize conditional value-at-risk (CVaR) of the portfolio loss under stochastic interest rate environment. The combination of stochastic interest and CVaR hedging method makes the valuing approach more complex than the existing model with constant interest rate. We take up two issues in searching the optimal CVaR hedging strategy: given the initial capital constraint we minimize the CVaR of the portfolio loss; by prescribing a bound on the risk, we also minimize the hedging cost. As an illustration of this hedging technique we derive hedging strategies for a European call option with the Black Scholes setting under HJM framework; explicit formulas are presented. We also investigate CVaR hedging problems by using the real financial data.
Optimized backoff algorithm of IEEE 802.11 DCF for collision resolution

IEEE802.11 DCF (Distributed Coordination Function) protocol adopts binary exponential backoff (BEB) algorithm to reduce the probability of collision. However, when the network reaches saturation, throughput declines sharply with the increase of the number of stations (STAs) because of more collisions. In order to further avoid collisions and optimize the system, this paper proposes an improved algorithm based on the RTS / CTS (request to send /dear to send) mechanism. A STA intended to send packet sets an appropriate contention window (CW) and selects a backoff value different from that of other STAs according to the result of previous packet and the current backoff value of other STAs in the network. Theoretical analysis and OPNET simulation results show that the new algorithm outperforms BEB in performance of throughput, network delay and data dropped.
Design of Networked Control Systems with Two Different Working Status

This paper is concerned with stability and controller design of networked control systems (NCSs) with two dif- ferent working status. Firstly, the working status of NCSs are considered as two different cases: the normal case and the un-normal case. In normal case, the work process of NCSs are described by two independent working process: one is the packet dropouts process; the other is the network induced delay process. In un-normal case, there are two goals should be achieved for designing: one is to simulate the initial system for restarting the normal case; the other is to ensure the stabil- ity of NCSs as much as possible. Secondly, according to the designed networked controller, a novel necessary and suffi- cient condition for guaranteeing the stability of the NCSs under the un-normal case is proposed. Furthermore, the dynamic behavior of the NCSs where switching between the normal case and the un-normal case is considered. Finally, a numeri- cal example illustrates the effectiveness of the results.
Dynamically feasible task-constrained motion planning with moving obstacles

We present a randomized algorithm for planning dynamically feasible motions of robots subject to geometric task constraints in the presence of moving obstacles. The proposed method builds upon our previous results on task-constrained motion planning with moving obstacles. With respect to our previous formulation, the inclusion of bounds on the available actuator torques leads to the adoption of an acceleration-level motion generation scheme. Therefore, the new planner must operate in a task-constrained state space extended with time. The generated trajectories are collision-free, obey velocity and torque bounds, and satisfy the task constraint with arbitrary accuracy. The effectiveness of the proposed approach is shown by results on various scenarios involving a 7-dof manipulator.
A Learning Approach for Call Admission Control under QoS Constraints in Cellular Networks

A new approach for learning call admission control (CAC) schemes that can provide quality of service (QoS) guarantees to ongoing calls from several classes of traffic with different resource requirements is presented. Comparison with two other CAC schemes shows that the new approach is not only capable of utilizing the network resource to maximize revenue but also maintain the handover dropping rate (CDR) under a prescribed upper bound while still maintaining an acceptable call blocking rate (CBR). The learning CAC scheme is shown to work successfully in the presence of smoothly changing arrival rates of traffic. The CAC policy is obtained through a form of neuroevolution (NE) algorithm
When Love Is Not Digested : Underlying Reasons for Source to Target Domain Pairings in the Contemporary Theory of Metaphor

The goal of this paper is to present a processing account (the Conceptual Mapping Model) for the Contemporary Theory of Metaphor (Lakoff and Johnson 1980) and to present experimental evidence that supports this model. In particular, I will point out that the conceptual correspondences between a source and target domain must be analyzed in order to determine the underlying reasons for the source-target pairings. This underlying reason is formulated in terms of a Mapping Principle. Once this principle is discovered, predictions may be made concerning the acceptability of both conventional and novel metaphors.
Economics and Policy Preferences: Causal Evidence of the Impact of Economic Conditions on Support for Redistribution and Other Ballot Proposals

Abstract Using California ballot proposition returns and exogenous shifts to labor demand, we provide the first large-scale causal evidence of the impact of economic conditions on policy preferences. Consistent with economic theory, we find that positive economic shocks decrease support for redistributive policies. More notably, we find evidence of a need for cognitive consistency in voting behavior as economic shocks have a smaller significant impact on voting on noneconomic ballot issues. While we also demonstrate that positive shocks decrease turnout, we present evidence that our results reflect changes in the electorate's preferences and not simply to its composition.