Miracle-dz/UniFAR-FTUs huggingface dataset:
A Three-Way Trade-Off Maintains Functional Diversity under Variable Resource Supply

The resources that organisms depend on often fluctuate over time, and a variety of common traits are thought to be adaptations to variable resource supply. To understand the trait structure of communities, it is necessary to understand the functional trade-offs that determine what trait combinations are possible and which species can persist and coexist in a given environment. We compare traits across phytoplankton species in order to test for proposed trade-offs between maximum growth rate, equilibrium competitive ability for phosphorus (P), and ability to store P. We find evidence for a three-way trade-off between these traits, and we use empirical trait covariation to parameterize a mechanistic model of competition under pulsed P supply. The model shows that different strategies are favored under different conditions of nutrient supply regime, productivity, and mortality. Furthermore, multiple strategies typically coexist, and the range of traits that persist in the model is similar to the range of traits found in real species. These results suggest that mechanistic models informed by empirical trait variation, in combination with data on the trait structure of natural communities, will play an important role in uncovering the mechanisms that underlie the diversity and structure of ecological communities.
Direct and indirect effects of low self-control on the personal victimization of South Korean youth

ABSTRACT To estimate the direct effects of low self-control on the incidence of personal victimization among South Korean elementary and middle school students; to examine whether these effects are mediated by deviant lifestyles and parental attachments, and to determine whether these effects differ by a youth's sex. Data from the Korean Youth Panel Survey were examined. A national sample of 2844 South Korean fourth grade students was followed for five years. Wave-specific analyses consistently revealed significant direct and indirect effects of low self-control on victimization, and the direct effects were not fully mediated by deviant lifestyles and parent-child attachment. Direct effects of low self-control were invariant between the sexes whereas indirect effects involving delinquent peers were not.
Constructing the Evaluation Model for Business-to-consumers Electronic Commerce from Consumer's Perception

An electronic commerce (EC) web site is not only an information system but also a channel of marketing and selling. An evaluation model that takes both the technical factors of developing the web system and the marketing factors of attracting consumers to use it into consideration is therefore very crucial. As far, most of the studies related to EC web sites focused on developing technical principles or guidelines of web design or providing key factors of the business model and the comprehensive evaluation model for EC web sites are still lacking. This paper aims at constructing a model for evaluating EC web sites in both the technical aspects of designing a web system and the marketing aspects of fitting the users’ consumption behavior. After reviewing the related literature we presented a model integrating web-design principles and marketing theories based on the perspective of consumer’s perception. We validated this model by using the web survey method. Through the factor analysis the 33 items of the model were categorized into four factors: interface and content design, system function design, commercial design, and personal interaction. This evaluation instrument is useful for web designers and organizations to provide more attractive and effective web sites for consumers. Moreover, the survey result also revealed that there exists significant gap between the perceived functions and the expected functions of the respondents about the EC web sites. This finding can be used for the EC firms to improve their web site design.
Task Refinement for Autonomous Robots Using Complementary Corrective Human Feedback

A robot can perform a given task through a policy that maps its sensed state to appropriate actions. We assume that a hand-coded controller can achieve such a mapping only for the basic cases of the task. Refining the controller becomes harder and gets more tedious and error prone as the complexity of the task increases. In this paper, we present a new learning from demonstration approach to improve the robot's performance through the use of corrective human feedback as a complement to an existing hand-coded algorithm. The human teacher observes the robot as it performs the task using the hand-coded algorithm and takes over the control to correct the behavior when the robot selects a wrong action to be executed. Corrections are captured as new state-action pairs and the default controller output is replaced by the demonstrated corrections during autonomous execution when the current state of the robot is decided to be similar to a previously corrected state in the correction database. The proposed approach is applied to a complex ball dribbling task performed against stationary defender robots in a robot soccer scenario, where physical Aldebaran Nao humanoid robots are used. The results of our experiments show an improvement in the robot's performance when the default hand-coded controller is augmented with corrective human demonstration.
From blindsight to sight: cognitive rehabilitation of visual field defects.

PURPOSE Traditionally, post-chiasmatic lesions were believed to result in complete and permanent visual loss in the topographically related areas of the visual field. However, a number of studies with monkeys, and later with humans, have demonstrated spared implicit visual functioning, referred to as 'blindsight'. The present study assessed whether training this phenomenon would induce an objective restoration of conscious vision in the blind field of hemianopic patients. METHODS For a period of 22 weeks nine patients with unilateral occipital damage participated in several forced-choice visual tasks known to elicit blindsight: pointing to visual targets, letter recognition, visual comparison between the two hemifields, target localization, and letter identification. Before and after rehabilitation, patients were submitted to a behavioral pre- and post-test, including visual detection and letter identification as well as to automated perimetry visual field testing (Humphrey Automated 24-2 Full Threshold). RESULTS An objective improvement was found in the behavioral tasks for all patients at the post-test stage as well as an objective enlargement of the contralesional visual field for all except one of the nine patients. An overall decrease is seen in the number of undetected points (out of 30) on automated perimetry visual field testing after rehabilitation (F (1, 16)=22.57; p<0.001) for both eyes (Right Eye, RE: T=0; z=2.52; p<0.05; Left Eye, LE: T=0, z=2.37; p<0.05) regardless of lesion side. CONCLUSIONS The results suggest that explicit (conscious) visual detection can be restored in the blind visual field by using implicit (unconscious) visual capacities. Results are discussed regarding visual field defect rehabilitation, blindsight, attention, and brain plasticity hypotheses.
Language Model Expansion Using Webdata for Spoken Document Retrieval

In recent years, there has been increasing demand for ad hoc retrieval of spoken documents. We can use existing text retrieval methods by transcribing spoken documents into text data using a Large Vocabulary Continuous Speech Recognizer (LVCSR). However, retrieval performance is severely deteriorated by recognition errors and out-of-vocabulary (OOV) words. To solve these problems, we previously proposed an expansion method that compensates the transcription by using text data downloaded from the Web. In this paper, we introduce two improvements to the existing document expansion framework. First, we use a large-scale sample database of webdata as the source of relevant documents, thus avoiding the bias introduced by choosing keywords in the existing methods. Next, we use a document retrieval method based on a statistical language model (SLM), which is a popular framework in information retrieval, and also propose a new smoothing method considering recognition errors and missing keywords. Retrieval experiments show that the proposed methods yield a good results. Index Terms: Spoken document retrieval, statistical language models, World Wide Web
Helix-Loop-Helix Protein p8, a Transcriptional Regulator Required for Cardiomyocyte Hypertrophy and Cardiac Fibroblast Matrix Metalloprotease Induction

ABSTRACT Cardiomyocyte hypertrophy and extracellular matrix remodeling, primarily mediated by inflammatory cytokine-stimulated cardiac fibroblasts, are critical cellular events in cardiac pathology. The molecular components governing these processes remain nebulous, and few genes have been linked to both hypertrophy and matrix remodeling. Here we show that p8, a small stress-inducible basic helix-loop-helix protein, is required for endothelin- and α-adrenergic agonist-induced cardiomyocyte hypertrophy and for tumor necrosis factor-stimulated induction, in cardiac fibroblasts, of matrix metalloproteases (MMPs) 9 and 13—MMPs linked to general inflammation and to adverse ventricular remodeling in heart failure. In a stimulus-dependent manner, p8 associates with chromatin containing c-Jun and with the cardiomyocyte atrial natriuretic factor (anf) promoter and the cardiac fibroblast mmp9 and mmp13 promoters, established activator protein 1 effectors. p8 is also induced strongly in the failing human heart by a process reversed upon therapeutic intervention. Our results identify an unexpectedly broad involvement for p8 in key cellular events linked to cardiomyocyte hypertrophy and cardiac fibroblast MMP production, both of which occur in heart failure.
Extracting spam blogs with co-citation clusters

This paper reports the estimated number of spam blogs in order to assess their current state in the blogosphere. To extract spam blogs, I developed a traversal method among co-citation clusters of blogs from a spam seed. Spam seeds were collected in terms of high out-degree and spam keyword. According to the experiment, a mixed seed set composed of high out-degree and spam keyword seeds is more effective than individual seed sets in terms of F-Measure. In conclusion, mixed seeds from different methods are effective in improving the F-Measure results of spam extraction with co-citation clusters.
Analysis of brain activation during visual tasks

In the area of brain activity monitoring, the technique of transcranial Doppler (TCD) is widely used in neuroscience laboratories because it is non-invasive and can be used in a wide variety of environments, which makes it appropriate to conduct practical tests. The objective of this work is to propose a new methodology to analyze changes in blood flow velocity (BFV) in main cerebral vessels measured by TCD during some visual tasks initiated via a multimedia screen. To conduct this experiment, 23 volunteers of different ages (19 to 66 years) and different sexes were selected. The tests involve measuring -using a Doppler device- the brain activity of each person during the execution of the predefined visual tasks. The BFV data are analyzed with a methodology based on the analysis of statistical differences between repose and activation periods.
Analysis Ball Grid Array defects by using new image technique

BGA (Ball Grid Array) is one type of integrated circuit (IC) has been used in electronics assembly. To inspect the BGA quality, it normally used the X-ray image for detection BGA defects. Most of research in the field of BGA quality detection can be detected short circuit, big ball and small ball. This work presents the new image processing technique to detect all cases above and also detect the void case. All of these defects effect to reliability and quality of products. This work analyzes the X-Ray images of BGA 48 and 100 balls. The results of this technique can detect short circuit, big ball, small ball and void case 100%. The advantage results of this technique can help and feedback to process for the quality improvement of products and production lines.
“I Can’t Get No Satisfaction”: Helping Autonomous Systems Identify Their Unsatisfied Interdomain Interests

Given the distributed and business-driven nature of the Internet, economic interests of autonomous systems (ASes) may be incompatible. Previous works studied specific effects of incompatible interests, especially BGP policy conflicts leading to routing and forwarding anomalies. In this paper, we focus on the effects of incompatible interests that do not trigger such anomalies. We take the perspective of a single AS: we show that incompatible interests can have a tangible impact on its business and provide a classification of its unsatisfied interests. Since incompatible interests cannot be solved automatically, our effort is directed to support network managers in their business decisions. Hence, we describe algorithms to identify and assess their impact, as well as a prototype of a warning system aimed at signaling the most relevant unsatisfied interests. We evaluate our prototype on real data from two operational networks. In addition, to illustrate the potential of our system, our evaluation shows that unsatisfied interest are relatively frequent and likely affect a significant amount of traffic in practice.
Persistent B+-Trees in Non-Volatile Main Memory

Computer systems in the near future are expected to have N on- V olatile M ain M emory (NVMM), enabled by a new generation of N on- V olatile M emory (NVM) technologies, such as Phase Change Memory (PCM), STT-MRAM, and Memristor. The non-volatility property has the promise to persist in-memory data structures for instantaneous failure recovery. However, realizing such promise requires a careful design to ensure that in-memory data structures are in known consistent states after failures. This paper studies persistent in-memory B+-Trees as B+-Trees are widely used in database and data-intensive systems. While traditional techniques, such as undo-redo logging and shadowing, support persistent B+-Trees, we find that they incur drastic performance overhead because of extensive NVM writes and CPU cache flush operations. PCM-friendly B+-Trees with unsorted leaf nodes help mediate this issue, but the remaining overhead is still large. In this paper, we propose write atomic B+-Trees (wB+-Trees), a new type of main-memory B+-Trees, that aim to reduce such overhead as much as possible. wB+-Tree nodes employ a small indirect slot array and/or a bitmap so that most insertions and deletions do not require the movement of index entries. In this way, wB+-Trees can achieve node consistency either through atomic writes in the nodes or by redo-only logging. We model fast NVM using DRAM on a real machine and model PCM using a cycle-accurate simulator. Experimental results show that compared with previous persistent B+-Tree solutions, wB+-Trees achieve up to 8.8x speedups on DRAM-like fast NVM and up to 27.1x speedups on PCM for insertions and deletions while maintaining good search performance. Moreover, we replaced Memcached's internal hash index with tree indices. Our real machine Memcached experiments show that wB+-Trees achieve up to 3.8X improvements over previous persistent tree structures with undo-redo logging or shadowing.
Cap-binding complex (CBC)

The 7mG (7-methylguanosine cap) formed on mRNA is fundamental to eukaryotic gene expression. Protein complexes recruited to 7mG mediate key processing events throughout the lifetime of the transcript. One of the most important mediators of 7mG functions is CBC (cap-binding complex). CBC has a key role in several gene expression mechanisms, including transcription, splicing, transcript export and translation. Gene expression can be regulated by signalling pathways which influence CBC function. The aim of the present review is to discuss the mechanisms by which CBC mediates and co-ordinates multiple gene expression events.
Virtual reality study of paranoid thinking in the general population

Background Judging whether we can trust other people is central to social interaction, despite being error-prone. A fear of others can be instilled by the contemporary political and social climate. Unfounded mistrust is called paranoia, and in severe forms is a central symptom of schizophrenia. Aims To demonstrate that individuals without severe mental illness in the general population experience unfounded paranoid thoughts, and to determine factors predictive of paranoia using the first laboratory method of capturing the experience. Method Two hundred members of the general public were comprehensively assessed, and then entered a virtual reality train ride populated by neutral characters. Ordinal logistic regressions (controlling for age, gender, ethnicity, education, intellectual functioning, socio-economic status, train use, playing of computer games) were used to determine predictors of paranoia. Results The majority agreed that the characters were neutral, or even thought they were friendly. However, a substantial minority reported paranoid concerns. Paranoia was strongly predicted by anxiety, worry, perceptual anomalies and cognitive inflexibility. Conclusions This is the most unambiguous demonstration of paranoid ideation in the general public so far. Paranoia can be understood in terms of cognitive factors. The use of virtual reality should lead to rapid advances in the understanding of paranoia.
Polymer principles of protein calorimetric two‐state cooperativity

The experimental calorimetric two-state criterion requires the van't Hoff enthalpy DeltaH(vH) around the folding/unfolding transition midpoint to be equal or very close to the calorimetric enthalpy DeltaH(cal) of the entire transition. We use an analytical model with experimental parameters from chymotrypsin inhibitor 2 to elucidate the relationship among several different van't Hoff enthalpies used in calorimetric analyses. Under reasonable assumptions, the implications of these DeltaH(vH)'s being approximately equal to DeltaH(cal) are equivalent: Enthalpic variations among denatured conformations in real proteins are much narrower than some previous lattice-model estimates, suggesting that the energy landscape theory "folding to glass transition temperature ratio" T(f) /T(g) may exceed 6.0 for real calorimetrically two-state proteins. Several popular three-dimensional lattice protein models, with different numbers of residue types in their alphabets, are found to fall short of the high experimental standard for being calorimetrically two-state. Some models postulate a multiple-conformation native state with substantial pre-denaturational energetic fluctuations well below the unfolding transition temperature, or predict a significant post-denaturational continuous conformational expansion of the denatured ensemble at temperatures well above the transition point, or both. These scenarios either disagree with experiments on protein size and dynamics, or are inconsistent with conventional interpretation of calorimetric data. However, when empirical linear baseline subtractions are employed, the resulting DeltaH(vH)/DeltaH(cal)'s for some models can be increased to values closer to unity, and baseline subtractions are found to correspond roughly to an operational definition of native-state conformational diversity. These results necessitate a re-assessment of theoretical models and experimental interpretations.
Physical Conditions in the Narrow-Line Region of M51

We have investigated the physical conditions in the narrow-line region (NLR) of M51 by using long-slit spectra obtained with the Space Telescope Imaging Spectrograph aboard the Hubble Space Telescope and 3.6 cm radio continuum observations obtained with the Very Large Array. Emission-line diagnostics were employed for nine NLR clouds, which extend 2. ″5 (102 pc) from the nucleus, to examine the electron density, temperature, and ionization state of the NLR gas. The emission-line ratios are consistent with those typically found in Seyfert nuclei and indicate that within the inner near-nuclear region (r ≲ 1′′) the ionization decreases with increasing radius. Upper limits to the [O III] electron temperature (Te ≲ 11,000 K) for the inner NLR clouds indicate that photoionization is the dominant ionization mechanism close to the nucleus. The emission-line fluxes for most of the NLR clouds can be reproduced reasonably well by simple photoionization models using a central power-law continuum source and supersolar nitrogen abundances. Shock+precursor models, however, provide a better fit to the observed fluxes of an NLR cloud ~2. ″5 south of the nucleus that is identified with the extranuclear cloud. The large [O III] electron temperature of this cloud (Te = 24,000 K) further suggests the presence of shocks. This cloud is straddled by two radio knots and lies near the location where a weak radio jet, ~2. ″5 (102 pc) in extent, connects the near-nuclear radio emission with a diffuse lobe structure spanning ~4′′ (163 pc). It is plausible that this cloud represents the location where the radio jet impinges on the disk ISM.
Teamwork evaluation with a microworld platform

We developed a platform supporting the evaluation of teamwork. The platform logs oral communications, collaborative tool usage and simulated physical action in the work environment. The paper brings forward observations derived from a comprehensive study of maintenance teams operating simulated network infrastructures. As positive results, we highlight that the platform supports a comprehensive analysis of teamwork at macro and micro levels, including individual and team activities, conducted in quasi naturalistic settings.
Low-rank tensor completion: a Riemannian manifold preconditioning approach

We propose a novel Riemannian manifold preconditioning approach for the tensor completion problem with rank constraint. A novel Riemannian metric or inner product is proposed that exploits the least-squares structure of the cost function and takes into account the structured symmetry that exists in Tucker decomposition. The specific metric allows to use the versatile framework of Riemannian optimization on quotient manifolds to develop preconditioned nonlinear conjugate gradient and stochastic gradient descent algorithms for batch and online setups, respectively. Concrete matrix representations of various optimization-related ingredients are listed. Numerical comparisons suggest that our proposed algorithms robustly outperform state-of-the-art algorithms across different synthetic and real-world datasets.
Device modeling of statistical dopant fluctuations in MOS transistors

This paper addresses the numerical requirements for device modeling of statistical dopant fluctuations in MOS transistors. It is found that the standard deviation of the threshold voltage V/sub T/ can be properly derived from 2D or 3D simulations using a relatively coarse simulation grid. Evaluating the threshold voltage shift arising from dopant fluctuations, on the other hand, calls for a full 3D approach with a numerical grid that is sufficiently refined to represent the discrete nature of the dopant distribution. The average V/sub T/-shift is found to be positive for long, narrow devices, and negative for short, wide devices.