Miracle-dz/UniFAR-FTUs huggingface dataset:
Cadmium- and Flood-Induced Anoxia Stress in Pea Roots Measured by Electrical Impedance

Electrical impedance measurement - complex resistance in the presence of alternating current - is a useful tool for the investigation of structural characteristics of solid materials but also for plant tissues. This measurement is easily done: only two electrodes are inserted into the plant tissue, so it can be considered as a non-invasive technique and it may be a successful method for detecting structural changes in plants caused by environmental stresses. The effects of fl ood and cadmium stress were investigated by electrical impedance measurement, because both of them cause structural changes in plant tissues. Apoplasmic resistance (Ra), symplasmic resistance (Rs), and membrane capacitance (Cm) of pea roots were calculated. In the fi rst fi ve days of fl ood treatment, the Rs and Cm values of roots decreased drastically. In case of cadmium treatment, the Rs and Cm values of roots showed an increasing tendency supposedly as a consequence of the enhanced membrane rigidity, the thickened cell walls and decreased growth phenomena caused by the heavy metal. There also was a remarkable difference in cadmium accumulation patterns and in the changes of the calculated parameters amongst anoxic and aerated seedlings. This initial work revealed that the development of stress caused by two environental stress agents, cadmium and fl ood, can be followed by electrical impedance measurement.
Expressive reading: A phenomenological study of readers' experience of Coleridge's The rime of the ancient mariner.

To articulate what constitutes expressive reading, we conducted a phenomenological study of readers’ responses to Samuel Taylor Coleridge’s poem, The Rime of the Ancient Mariner. After reading the poem twice during 1 week, each of 40 readers chose five passages that they found striking or evocative and then commented on each one. Numerically aided phenomenological methods [(Kuiken, D., & Miall, D. S. (2001). Numerically aided phenomenology: Procedures for investigating categories of experience. Forum Qualitative Sozialforschung/Forum: Qualitative Social Research, 2(1). Retrieved from http:// www.qualitative-research.net/index.php/fqs/article/view/976] were used to (a) compare these commentaries, identifying and paraphrasing recurrent meaning expressions (called constituents); (b) create matrices reflective of the profiles of constituents found in each commentary; (c) create clusters of commentaries according to the similarities in their profiles of constituents; and (d) examine each cluster to ascertain their distinctive attributes. Among the six distinct types of commentary identified, one in particular involved (a) metaphoric and quasi-metaphoric engagement with sensory imagery from the poem; (b) progressive transformation of an emergent affective theme; and (c) metaphoric blurring of boundaries between the reader’s and narrator’s perspectives. This mode of reading, which we call expressive enactment, contrasted with five other types of response: ironic allegoresis, aesthetic feeling, autobiographical assimilation, autobiographical diversion, and nonengagement.
Definitions of schizophrenia, 1908–1987: The failed essentialism

This work examines the historical conceptualization of schizophrenia through definition from 1908–1987. Rather than reveal an essentialist definition of schizophrenia in North America, it reveals a history of varying and competing professional definitions. It demonstrates and historically contextualizes how widespread conceptual instability and disagreement over the nature of the concept gave rise to a new, but still contested, theoretical emphasis on operational definitions. As made manifest through definition, schizophrenia has not been a stable transhistorical object. Rather, the characteristic feature in schizophrenia definition appears to be instability and variance rather than stability or long historical periods of agreement. This analysis nevertheless cautions against overstating the importance of fluctuating definition in assessing the ontological status of contemporary interpretations of schizophrenia.
University students’ motivation, engagement and performance in a large lecture-format general education course

We investigated how high-performers and low-performers differ with regard to motivation and engagement in a university-level, large-format general education geography course. One hundred and ten students participated in the study. A self-report measure was administered three times (at the beginning, middle and end of the semester). Performance data were obtained from final course grades. Results showed there were significant differences between the high- and low-performer groups in motivation but not in engagement. With regard to students’ perceptions of motivational aspects of the course, the low-performer group showed a significant decrease in attention but the high-performer group showed a significant increase. The relevance perceived by both groups decreased over time. The confidence and satisfaction of the low-performer group decreased whereas there was no change in those of the high-performer group throughout the semester. Findings as well as implications for teaching in a college large-format general education course are discussed.
Small-cell lung cancer: ESMO clinical recommendations for diagnosis, treatment and follow-up.

The crude incidence of lung cancer in the European Union is 52.5/100 000 per year, mortality being 48.7/100 000 per year. Rates among men are 82.5 and 77.0/100 000 per year, and among women 23.9 and 22.3/100 000 per year, respectively. Small-cell lung cancer (SCLC) accounts for 18% of all cases. In recent years, the incidence of SCLC is decreasing. SCLC is strongly associated with cigarette smoking.
C332C genotype of glyoxalase 1 and its association with late diabetic complications.

AIMS/INTRODUCTION Glyoxalase 1 catalyses the detoxification of methylglyoxal, a major precursor of advanced glycation end products associated with aging, neurodegenerative diseases, and microvascular complications of diabetes. Here, we examine a possible association of a single nucleotide polymorphism of glyoxalase 1 gene (Glo1 A332C, rs4746 or rs2736654) with the prevalence of microvascular diabetic complications in patients with type 1 and type 2 diabetes. MATERIALS AND METHODS Genotyping was performed in 209 patients with type 1 and 524 patients with type 2 diabetes using polymerase chain reaction and subsequent cleavage by restriction endonuclease Bsa I. RESULTS Frequencies of the glyoxalase 1 genotypes were different with respect to diabetes type with a significantly higher prevalence of A332A-genotype in type 1 diabetes (35.9% vs. 27.3%; p=0.03). In type 1 diabetes, there was no correlation of any genotype with diabetic retinopathy, nephropathy or neuropathy. In contrast, type 2 diabetic patients homozygous for the C332C allele showed a significantly increased prevalence of diabetic neuropathy (p=0.03; OR=1.49 [95%-CI: 1.04; 2.11]), while no association with diabetic nephropathy or retinopathy was found. However, the significance of this association was lost after correction for multiple testing. CONCLUSIONS Our data suggest a possible association of C332C-genotype of the glyoxalase 1 gene with diabetic neuropathy in type 2 diabetes, supporting the hypothesis that methylglyoxal might be an important mediator of diabetic neuropathy in type 2 diabetes.
Naked singularity in modified gravity theory

The cosmological constant induced by qantum fluctuation of the graviton on a given background is considered as a tool for building a spectrum of different geometries. In particular, we apply the method to the Schwarzschild background with positive and negative mass parameter. In this way, we put on the same level of comparison the related naked singularity (−M) and the positive mass wormhole. We discuss how to extract information in the context of a f (R) theory. We use the Wheeler-De Witt equation as a basic equation to perform such an analysis regarded as a Sturm-Liouville problem. The application of the same procedure used for the ordinary theory, namely f (R) = R, reveals that to this approximation level, it is not possible to classify the Schwarzschild and its naked partner into a geometry spectrum.
Parameter interpretation, regularization and source localization in multivariate linear models

Neuroimaging data are frequently analyzed with multivariate methods. Models expressing the data as a function of underlying factors related to the brain processes under study (signals) are called forward models, while models reversing this functional relationship are called backward models. Weigth vectors of backward models (called extraction filters) indicate the measurement channels informative with respect to isolating the signals. However, being a function of both signal and noise, significant weights may be observed at channels containing pure noise, while a proportion of signal-related channels may be given zero or insignificant weight. In contrast, forward model parameters (activation patterns) may exhibit significant weights only at signal-related channels, and are therefore interpretable with respect to the origin of the brain processes under study. It is sometimes incorrectly assumed that regularization (e.g., sparsification) of backward models makes extraction filters interpretable in the same sense. However, by transforming filters into patterns of corresponding forward models, as outlined here for the linear case, this can be indeed achieved. While these considerations hold for all types of data, the distinction between filters and patterns is particularly crucial for EEG and MEG data: only activation patterns can be localized to brain anatomy using customary inverse methods. We illustrate our theoretical results using a real EEG data example.
Get Me to My GATE on Time: Efficiently Solving General-Sum Bayesian Threat Screening Games

Threat Screening Games (TSGs) are used in domains where there is a set of individuals or objects to screen with a limited amount of screening resources available to screen them. TSGs are broadly applicable to domains like airport passenger screening, stadium screening, cargo container screening, etc. Previous work on TSGs focused only on the Bayesian zero-sum case and provided the MGA algorithm to solve these games. In this paper, we solve Bayesian general-sum TSGs which we prove are NP-hard even when exploiting a compact marginal representation. We also present an al-gorithm based upon a adversary type hierarchical tree decomposition and an efﬁcient branch-and-bound search to solve Bayesian general-sum TSGs. With this we provide four contributions: (1) GATE, the ﬁrst algorithm for solving Bayesian general-sum TSGs, which uses hierarchical type trees and a novel branch-and-bound search, (2) the Branch-and-Guide approach which combines branch-and-bound search with the MGA algorithm for the ﬁrst time, (3) heuristics based on properties of TSGs for accelerated computation of GATE, and (4) experimental results showing the scalability of GATE needed for real-world domains.
The Growth and Plankton Changes of Intensive Ecological AquacultureModel of Pseudosciaena crocea

The growth of Pseudosciaena crocea and changes of plankton was studied under intensive ecological aquacul- ture model that didn't change water. The result indicated that: the growth rate of Pseudosciaena crocea was significantly higher than that in cage culture (p<0.05), the essential amino acids, flavor amino acid and total amino acids of Pseudo- sciaena crocea were significantly higher than that in cage culture(p<0.05), the PUFA and DHA、EPA of Pseudosciaena crocea were also significantly higher than that in cage culture(p<0.05). Plankton biomass of aquaculture water increased with cultivation time. The diversity of phytoplankton was better in the early stage, the diversity index and evenness index decreased in the later stage, the diversity of phytoplankton was poor in the end of the experiment. The diversity of zoo- plankton was better, there was little change in the diversity index and evenness index of zooplankton, the zooplankton was in an equilibrium state.
Labyrinth within: emergence through documentation

This paper outlines our design proposal for the OZCHI 24 hour design challenge. The design brief challenged us to identify an unused space and revitalise it through a design proposal. Through a series of inquires we conceived a design concept, introducing a labyrinthine experience into a linear urban space. Our argument in this paper is that documentation and externalisation serves both as a way of communicating the process, as well as creating an understanding of the design situation.
Essays on Closed-End Funds and Advance Disclosure of Trading

My dissertation is comprised of three essays. In the first essay, I present a dynamic partial equilibrium model of a simple economy with a closed-end fund. My model demonstrates that a combination of management fees and a time-varying information advantage for a fund manager can account for several empirically observed characteristics of closed-end funds simultaneously. The model is consistent with the basic time-series behavior of fund discounts, explains why funds issue at a premium, accounts for the excess volatility of fund returns, justifies the underperformance of funds that trade at a premium, and is consistent with many time-series correlations between discounts, NAV returns, and fund returns. In the second essay, I present a dynamic rational expectations model of closed-end fund discounts that incorporates feedback effects from activist arbitrage and lifeboat provisions. I find that the potential for activism and the existence of a lifeboat both lead to narrower discounts. Furthermore, both activist arbitrage and lifeboats effectuate an ex post transfer of wealth from managers to investors but an ex ante transfer of wealth from low-ability managers to high-ability managers. On average, investor wealth is unaffected by either activist arbitrage or lifeboats because their potential benefits are factored into higher fund prices. Although lifeboats can reduce takeover attempts, they do not increase expected managerial wealth. In the third essay, I present a noisy rational expectations equilibrium model in which agents who possess private information regarding the profitability of a firm are required to provide advance disclosure of their trading activity. I analytically characterize an equilibrium and conduct a numerical analysis to evaluate the implications of advance disclosure relative to a market in which informed agents trade without providing advance disclosure. By altering the information environment along with managerial incentives, advance disclosure increases risk in the financial market while reducing risk in the real economy. I also find that advance disclosure has implications for equilibrium prices and allocations, managerial compensation contracts, investor welfare, and market liquidity.
Effects of Self-Affirmation on Implementation Intentions and the Moderating Role of Affect

Self-affirmation may offset defensiveness to threatening messages, increase intentions to engage in protective behaviors, and facilitate actual change. Relatively little is known about the conditions under which self-affirmation is most beneficial. The authors examined whether self-affirmation facilitates the forming of implementation intentions–plans to engage in specific steps that facilitate behavior change—and whether effects differ by affective state. Undergraduate female drinkers (N = 265) were self-affirmed or not prior to reading an article linking excessive alcohol consumption to breast cancer susceptibility. They then had the opportunity to report implementation intentions, by listing specific steps they planned to take to reduce consumption. Consistent with predictions, self-affirmation promoted formation of implementation intentions, an effect found only among individuals manifesting positive (as opposed to negative) affect following receipt of the message. Self-affirmation may facilitate behavior change by encouraging development of implementation intentions, an effect that is likely enhanced among those experiencing positive affect.
Inequality and Human Rights of African Descendants in Brazil

Race and gender inequalities in Brazil are analyzed in light of international human rights law and standards. The demographic category “blacks” or “African descendants” is new and still controversial in Brazil; it conflicts with the traditional “racial democracy” ideology by grouping together dark-skinned and light-skinned blacks, but official research institutions increasingly employ this methodology. Statistical economic and demographic analysis demonstrates that African descendants’ human rights, particularly those of black women, are violated daily in Brazil. Analysis is made of compliance with international standards for the rights to life (life expectancy, mortality rates, quality of life), physical and mental health, work with dignity and equal opportunity, ongoing improvement of living conditions, and protection in childhood. Brazilian society is traditionally authoritarian and inequality is taken for granted. Meaningful economic and social change must address the specific issues of race discrimination and its legacy, which implies deep structural changes in Brazilian society.
Microgesture detection for remote interaction with mobile devices

The rise of smart rings enables for ubiquitous control of computers that are wearable or mobile. We developed a ring interface using a 9 DOF IMU for detecting microgestures that can be executed while performing another task that involve hands, e.g. riding a bicycle. For the gesture classification we implemented 4 classifiers that run on the Android operating system without the need of clutch events. In a user study, we compared the success of 4 classifiers in a cycling scenario. We found that Random Forest (RF) works better for microgesture detection on Android than Dynamic Time Warping (DTW), K-Nearest-Neighbor (KNN), and than a Threshold (TH)-based approach as it has the best detection rate while it runs in real-time on Android. This work shell encourages other researchers to develop further mobile applications for using remote microgesture control in encumbered contexts.
Energy Consumption Analysis and Prediction of Hot Mix Asphalt

Hot mix asphalt (HMA) mixture is a major building material in paving engineering. To decrease energy consumption in HMA, a prediction model of energy consumption was investigated systematically in this paper, employing kernel principal component analysis (KPCA) and a support vector machine (SVM). The purpose of the work is to optimize production and structure parameters of an HMA plant. A prediction model of energy consumption cannot only be used for understanding but can also be used to develop new asphalt mixing plants and to achieve optimization. The main relationships between energy consumption and production parameters are studied in some field tests. To build a multi-parameter model of energy consumption, eigenvectors of many factors are optimized employing KPCA. The three kernel principal components of higher contribution rates are chosen. A prediction model of energy consumption is built using KPCA and SVM. Energy consumption of aggregate drying is predicted using the constructed model. The prediction model is optimized by particle swarm optimization (PSO). Influence coefficients of energy consumption are obtained by SVM and piecewise least-squares regression (PLSR) and are found to be consistent with test results. There is about a 5% error in energy consumption between the model prediction and the test. The prediction error can meet engineering requirements in the hot mix asphalt mixing plant.
Mass Spectrometry Screening Reveals Peptides Modulated Differentially in the Medial Prefrontal Cortex of Rats with Disparate Initial Sensitivity to Cocaine

To better understand why certain individuals are more vulnerable to cocaine abuse and addiction, we identify peptide markers associated with individual variation in sensitivity to the behavioral effects of cocaine. Previous studies in rats show that low, compared to high, cocaine responders are more sensitive to cocaine-induced behavioral plasticity (sensitization), exhibit enhanced conditioning to cocaine’s rewarding effects, and are more motivated to self administer cocaine. In the current study, we combine matrix-assisted laser desorption/ionization mass spectrometry with multivariate statistical methods to analyze tissue extracts from rat dorsal striatum, nucleus accumbens, and medial prefrontal cortex (mPFC) to examine trends in peptide changes that coincide with behavioral phenotype. Peptide profiles of these three regions from individual animals were characterized via mass spectrometry. Resulting mass peaks that were statistically different between these groups were identified using principal component analysis. The mass peaks were then identified in pooled samples via multistage liquid chromatography mass spectrometry. A total of 74 peptides from 28 proteins were sequenced from defined brain regions. Statistically significant changes in peak intensities for seven peptides were found in the mPFC of rats given a single injection of 10 mg/kg cocaine, with low cocaine responders showing ∼2-fold increase in peak intensities for the acetylated N terminus peptides of stathmin and Hint 1, as well as truncated ATP synthase. These results suggest that distinct peptide profiles in the mPFC are associated with individuals that exhibit reduced sensitivity to the behavioral effects of cocaine.
Automatic road crack segmentation using entropy and image dynamic thresholding

Human observation is commonly used to collect pavement surface distress data, during periodic road surveys. This method is labour-intensive, subjective and potentially hazardous for both inspectors and road users. This paper presents a novel framework for automatic crack detection and classification using survey images acquired at high driving speeds. The resulting images are pre-processed using morphological filters for reducing pixel intensity variance. Then, a dynamic thresholding is applied to identify dark pixels in images, as these correspond to potential crack pixels. Thresholded images are divided into non-overlapping blocks for entropy computation. A second dynamic thresholding is applied to the resulting entropy blocks matrix, used as the basis for identification of image blocks containing crack pixels. The classification system then labels images as containing horizontal, vertical, miscellaneous or no cracks. Two image databases are used for test purposes, to infer about the method's robustness, one of which acquired using professional high speed equipment.