Miracle-dz/UniFAR-FTUs huggingface dataset:
Is oak establishment in old‐fields and savanna openings context dependent?

1 Multiple factors are known to influence tree seedling establishment, yet the degree to which these factors depend on each other and on spatial context is largely unknown. We examined the influence of herbaceous competition and water and nitrogen limitations on tree seedling establishment as functions of distance from trees (within‐site spatial context) and site history (between‐site spatial context; as old‐fields vs. savanna openings). 2 We grew Quercus ellipsoidalis E.J. Hill (pin oak) and Q. macrocarpa Michx. (bur oak) seedlings for 3 years in abandoned agricultural fields and savannas in central Minnesota, USA, near and distant from adult oak trees, with and without water and nitrogen resource additions, and with and without clipping of herbaceous vegetation (reducing above‐ground competition). 3 The strongest treatment effects were found in response to distance from trees and clipping herbaceous vegetation. Ectomycorrhizal infection, year 1 foliar N concentrations, and survival were greater in seedlings growing near vs. distant from adult trees, while clipping herbaceous vegetation increased above‐ground seedling biomass but reduced seedling heights, regardless of distance from adult trees. 4 There were conflicting effects of resource addition, which were dependent on clipping of herbaceous vegetation and site (savanna vs. old‐field). 5 Distance from adult trees and clipping herbaceous vegetation appear to have largely independent effects. Thus, while being near trees benefits seedlings, probably via increased mycorrhizal infection, competition from herbaceous vegetation limits seedlings regardless of distance from trees. In contrast, the effects of resource addition were more context dependent, interacting significantly with herbaceous context and site. 6 The factors influencing seedling success can perhaps be best conceptualized as a series of largely independent environmental filters: seedlings near trees have increased mycorrhizal infection, nutrient uptake and survival, but face competition from herbaceous vegetation regardless of distance from trees. The slow encroachment of woody vegetation into old‐fields and savanna openings in this region is likely to be the result of the net cumulative effect of such filters.
Extensions of Hausdorff spaces.

A topological property & is called a Hausdorff extension property if each Hausdorff space X can be densely embedded in a space κX this yields a theorem parallel to a similar result for the lattice of Hausdorff compactifications of a locally compact space X and βX\X obtained by Magill.
THE CORRELATION BETWEEN FOREIGN LANGUAGE LISTENING ANXIETY AND LISTENING COMPREHENSION ACHIEVEMENT OF THE TENTH GRADE STUDENTS OF MAN 2 PALEMBANG (Skripsi)

Anxiety is an influential factor in a foreign language learning and plays a crucial role in language learner’s performance. Tension or worry over listening to English and lack of self confidence as the factors of listening anxiety have been proven to influence students’ learning achievement and lower students’ achievement in listening. This research was aimed at investigating if there was any correlation between foreign language listening anxiety and listening comprehension achievement of the tenth grade students of MAN 2 Palembang. One hundred and eighty– eight students participated in this research with the age ranged from 15 to 16 years old. Foreign Laguage Listening Anxiety Scale Questionnaire and TOEFL Junior Listening Section Test were used as the instruments. Analyses by Pearson Product Moment Correlation revealed that there was significant correlation between foreign language listening anxiety and listening comprehension achievement. The study revealed that there was -. 725 correlations between foreign language listening anxiety and listening comprehension achievement. Furthermore, regression analyses showed that anxiety over listening to English could predict listening comprehension achievement by contributing 52.5% of the influence of listening anxiety in listening comprehension test.
Velocity fluctuations in slow flow through porous media

In this thesis, I study the spatial statistical properties of slow flow through porous media on the pore scale by a combination of numerical simulation and theoretical arguments. I demonstrate that the flow patterns undergo a transition from swirls to strongly focused and channel-like patterns for decreasing porosities. Not only is the flow in low-porosity media strongly focused, but the flow also possesses long-tailed, non-Gaussian velocity probability density distributions. A main result of our simulations is that the statistics of the flow through a single channel captures the entire flow, insofar as the patterns and probability distributions are concerned. I have constructed a simplified, phenomenological model for the fast part of the flow in random porous media. This model yields the desired exponential velocity distributions. For high porosities, I find that the statistical properties of the velocity fluctuations behave in a similar way as those observed in dilute suspensions flows: the swirls have a power-law dependency on the solid volume fraction, the correlation length is finite and has also a power-law dependency. I demonstrate that this scaling behavior is consistent with the predictions of theories. Finally, I study creeping flow through a single rough walled channel by numerical simulation and present a theory that predicts scale dependency of the permeability for tight fractures.
Engineered nanoparticles induce cell apoptosis: potential for cancer therapy

Engineered nanoparticles (ENPs) have been widely applied in industry, commodities, biology and medicine recently. The potential for many related threats to human health has been highlighted. ENPs with their sizes no larger than 100 nm are able to enter the human body and accumulate in organs such as brain, liver, lung, testes, etc, and cause toxic effects. Many references have studied ENP effects on the cells of different organs with related cell apoptosis noted. Understanding such pathways towards ENP induced apoptosis may aid in the design of effective cancer targeting ENP drugs. Such ENPs can either have a direct effect towards cancer cell apoptosis or can be used as drug delivery agents. Characteristics of ENPs, such as sizes, shape, forms, charges and surface modifications are all seen to play a role in determining their toxicity in target cells. Specific modifications of such characteristics can be applied to reduce ENP bioactivity and thus alleviate unwanted cytotoxicity, without affecting the intended function. This provides an opportunity to design ENPs with minimum toxicity to non-targeted cells.
Minimising Contrastive Divergence in Noisy, Mixed-mode VLSI Neurons

This paper presents VLSI circuits with continuous-valued probabilistic behaviour realized by injecting noise into each computing unit(neuron). Interconnecting the noisy neurons forms a Continuous Restricted Boltzmann Machine (CRBM), which has shown promising performance in modelling and classifying noisy biomedical data. The Minimising-Contrastive-Divergence learning algorithm for CRBM is also implemented in mixed-mode VLSI, to adapt the noisy neurons' parameters on-chip.
Gender Differences in Psychophysiological Responses to Speech Stress Among Older Social Phobics: Congruence and Incongruence Between Self-Evaluative and Cardiovascular Reactions

Objective Evidence suggests increased cardiovascular risk and autonomic impairment among individuals with chronic anxiety. Little attention, however, has been paid to the anxiety disorder of social phobia despite its high prevalence. Additionally, gender- and age-related cardiovascular profiles have not been examined in relation to social phobia. This study investigated cardiovascular responses to a socially threatening situation among older men and women with social phobia and control subjects. Methods Thirty subjects with social phobia and 30 control subjects (mean age = 65 years) were assessed during baseline, paced breathing, speech preparation, and speech presentation. Electrocardiographic variables, blood pressure, respiration, and emotional state (self-reported) were monitored. Hemodynamic variables included heart rate, blood pressure, cardiac output, and systemic vascular resistance; autonomic measures were respiratory sinus arrhythmia and baroreflex sensitivity, both markers of cardiac vagal control, and 0.10-Hz systolic blood pressure variability, an index of sympathetic vasomotor tone. Results Subjects with social phobia, in contrast to nonanxious control subjects, manifested more anxiety, embarrassment, and somatic complaints in response to stress; however, physiological measures generally did not distinguish groups. Interaction effects indicated that socially phobic women were hyperresponsive to the stressor with respect to self-reported, hemodynamic, and autonomic parameters. Socially phobic men manifested no physiological differences in comparison with control subjects, but they reported more psychological and somatic complaints. Conclusions Gender differences in subjective and physiological responses to a socially threatening situation indicate congruence between perceived social anxiety and physiological responses in older women but not men. We found no evidence of impaired cardiovascular autonomic regulation among socially phobic men despite other reports that phobically anxious men are at greater cardiovascular risk.
Consistent Features in the Forelimb Representation of Primary Motor Cortex in Rhesus Macaques

The purpose of this study was to systematically map the forelimb area of primary motor cortex (M1) in rhesus macaques in an effort to investigate further the organization of motor output to distal and proximal muscles. We used stimulus-triggered averaging (StTAing) of electromyographic activity to map the cortical representation of 24 simultaneously recorded forelimb muscles. StTAs were obtained by applying 15 μA stimuli to M1 sites while the monkey performed a reach and prehension task. Motor output to body regions other than the forelimb (e.g., face, trunk, and hindlimb) was identified using repetitive intracortical microstimulation to evoke movements. Detailed, muscle-based maps of M1 revealed a central core of distal (wrist, digit, and intrinsic hand) muscle representation surrounded by a “horseshoe”-shaped zone of proximal (shoulder and elbow) muscle representation. The core distal and proximal zones were separated by a relatively large region representing combinations of both distal and proximal muscles. On the basis of its size and characteristics, we argue that this zone is not simply the result of stimulus-current spread, but rather a distinct zone within the forelimb representation containing cells that specify functional synergies of distal and proximal muscles. Electrode tracks extending medially from the medial arm of the proximal muscle representation evoked trunk and hindlimb responses. No distal or proximal muscle poststimulus effects were found in this region. These results argue against the existence of a second, major noncontiguous distal or proximal forelimb representation located medially within the macaque M1 representation.
Rethinking Data-Intensive Science Using Scalable Analytics Systems

"Next generation" data acquisition technologies are allowing scientists to collect exponentially more data at a lower cost. These trends are broadly impacting many scientific fields, including genomics, astronomy, and neuroscience. We can attack the problem caused by exponential data growth by applying horizontally scalable techniques from current analytics systems to accelerate scientific processing pipelines. In this paper, we describe ADAM, an example genomics pipeline that leverages the open-source Apache Spark and Parquet systems to achieve a 28x speedup over current genomics pipelines, while reducing cost by 63%. From building this system, we were able to distill a set of techniques for implementing scientific analyses efficiently using commodity "big data" systems. To demonstrate the generality of our architecture, we then implement a scalable astronomy image processing system which achieves a 2.8--8.9x improvement over the state-of-the-art MPI-based system.
The misdiagnosis of hypertension: the role of patient anxiety.

BACKGROUND The white coat effect (defined as the difference between blood pressure [BP] measurements taken at the physician's office and those taken outside the office) is an important determinant of misdiagnosis of hypertension, but little is known about the mechanisms underlying this phenomenon. We tested the hypothesis that the white coat effect may be a conditioned response as opposed to a manifestation of general anxiety. METHODS A total of 238 patients in a hypertension clinic wore ambulatory blood pressure monitors on 3 separate days 1 month apart. At each clinic visit, BP readings were manually triggered in the waiting area and the examination room (in the presence and absence of the physician) and were compared with the mercury sphygmomanometer readings taken by the physician in the examination room. Patients completed trait and state anxiety measures before and after each BP assessment. RESULTS A total of 35% of the sample was normotensive, and 9%, 37%, and 19% had white coat, sustained, and masked hypertension, respectively. The diagnostic category was associated with the state anxiety measure (F(3,237) = 6.4, P < . 001) but not with the trait anxiety measure. Patients with white coat hypertension had significantly higher state anxiety scores (t = 2.67, P < .01), with the greatest difference reported during the physician measurement. The same pattern was observed for BP changes, which generally paralleled the changes in state anxiety (t = 4.86, P < .002 for systolic BP; t = 3.51, P < .002 for diastolic BP). CONCLUSIONS These findings support our hypothesis that the white coat effect is a conditioned response. The BP measurements taken by physicians appear to exacerbate the white coat effect more than other means. This problem could be addressed with uniform use of automated BP devices in office settings.
Codevelopment of externalizing and internalizing problems in early childhood

Using cross-domain latent growth modeling, we examined trajectories of externalizing and internalizing problems in disadvantaged boys followed from ages 2 to 6 years (N = 303). On average, externalizing problems gradually decreased and internalizing problems gradually increased. However, we found significant variability in individual-level trajectories. Higher levels of externalizing problems were associated with higher levels of internalizing problems; rates of change were also positively correlated across domains. In addition, high levels of externalizing problems predicted rapid increases in internalizing problems. In follow-up analyses involving child and parenting factors, the combination of high negative emotionality, low fearfulness, and high negative maternal control preceded high, nondecreasing externalizing trajectories. The combination of high negative emotionality, high fearfulness, and high negative maternal control preceded high, increasing internalizing trajectories. Taken together, the results indicate both general and specific processes in the development of early externalizing and internalizing problems.This research was supported by National Institute of Mental Health (NIMH) Grants MH50907 and MH01666 to the second author and NIMH National Research Service Award 1F31MH12226 to the first author. We thank Emily Winslow and Elizabeth Owens for developing the Early Parenting Coding System and the Negative Emotionality Coding System, respectively. We also thank the study participants for teaching us about child development.
Insights Into Analysis Operator Learning: From Patch-Based Sparse Models to Higher Order MRFs

This paper addresses a new learning algorithm for the recently introduced co-sparse analysis model. First, we give new insights into the co-sparse analysis model by establishing connections to filter-based MRF models, such as the field of experts model of Roth and Black. For training, we introduce a technique called bi-level optimization to learn the analysis operators. Compared with existing analysis operator learning approaches, our training procedure has the advantage that it is unconstrained with respect to the analysis operator. We investigate the effect of different aspects of the co-sparse analysis model and show that the sparsity promoting function (also called penalty function) is the most important factor in the model. In order to demonstrate the effectiveness of our training approach, we apply our trained models to various classical image restoration problems. Numerical experiments show that our trained models clearly outperform existing analysis operator learning approaches and are on par with state-of-the-art image denoising algorithms. Our approach develops a framework that is intuitive to understand and easy to implement.
"A Robust Time-varying Style Analysis for Hedge Funds based on Dynamic Quantiles" ∗

In the original approach by Sharpe (1992), style analysis aims to explain portfolio performances according to the fund exposure to a set of asset classes. Typically, multivariate regression is involved to obtain the fund sensitivity to various benchmarks. However, this approach has been criticized because of the non-robustness of the estimation. Moreover, the analysis framework remains static whereas fund allocation could be dynamic. To remedy to these drawbacks, we propose a robust time-varying global estimation involving Quantile Regression. The advantage of the Quantile Regression is that the whole shape of the distribution is taken into account rather than the simple mean in the case of OLS. Moreover, Quantile Regression is a robust statistical method that gives less weight to “outliers”. We propose a new time-varying framework for quantile regression in order to capture the dynamic style allocation. Our robust approach is finally applied to the main hedge fund strategy indexes from HFR.
Key tree and Chinese remainder theorem based group key distrubution scheme

Abstract A group key distribution scheme based on static key tree structure and the Chinese Remainder Theorem (KTCRT‐GKD) is proposed. It deal with the scenario of a pre‐defined static prospective user set U containing all potential customs of multicast services and concentrate on the stateless receiver case. Given a privileged group member set G ⊆ U consisting of authorized users in a multicast session, a set of subtrees of the user tree whose leaves just host all the privileged group members is called group member subtrees. We design an algorithm to compute the root IDs of group member subtrees. The key server uses the root keys of the group member subtrees and the Chinese Remainder Theorem to distribute a group key. It can reduce the key server's computation complexity for each group key distribution. Especially, an interesting feature is that, when the number of group members exceeds a certain number, the computing time of the key server will decrease with the increase of the size of the group.
Mindful or mind full? the effectiveness of a small scale mindfulness-based intervention in a mainstream primary school with year four children

This research aimed to establish the effectiveness of a mindfulness-based intervention facilitated by a trainee educational psychologist and a class teacher, with a class of Year Four children. The study took a pragmatist approach to research, whereby a mixed method approach was considered the best way to address the study’s research questions. The Year Four children in a mainstream primary school participated in a six week mindfulness-based intervention, with activities from ‘60 Mindful Minutes’ (The Nurture Group Network, 2014). Quantitative data were collected and analysed in relation to the children’s social and emotional well-being, levels of mindfulness, and observable behaviour (peer relationship difficulties, prosocial behaviour, conduct problems and hyperactivity and inattention) at four time-points. Qualitative data was collected at follow-up: the class teacher was interviewed and the children were asked to provide written feedback. Both the quantitative and qualitative data indicated that the children became more “mindful” after completing the intervention. Additionally, positive effects for their social and emotional well-being were found. The intervention was well-accepted by the children and their class teacher, and evidence was found at follow-up for the maintenance of mindfulness practices. The findings provide positive implications for practice, in regards to educational settings and educational psychologists.
Visualizing Higher-Layer Features of a Deep Network

Deep architectures have demonstrated state-of-the-art results in a variety of settings, especially with vision datasets. Beyond the model definitions and the quantitative analyses, there is a need for qualitative comparisons of the solutions learned by various deep architectures. The goal of this paper is to find good qualitative interpretations of high level features represented by such models. To this end, we contrast and compare several techniques applied on Stacked Denoising Autoencoders and Deep Belief Networks, trained on several vision datasets. We show that, perhaps counter-intuitively, such interpretation is possible at the unit level, that it is simple to accomplish and that the results are consistent across various techniques. We hope that such techniques will allow researchers in deep architectures to understand more of how and why deep architectures work.
Margination of white blood cells: a computational approach by a hydrodynamic phase field model

We numerically investigate margination of white blood cells and demonstrate the dependency on a number of conditions including haematocrit, the deformability of the cells and the Reynolds number. The approach, which is based on a mesoscopic hydrodynamic Helfrich-type model, reproduces previous results, e.g. a decreasing tendency for margination with increasing deformability and a non-monotonic dependency on haematocrit. The consideration of inertia effects, which may be of relevance in various parts of the cardiovascular system, indicates a decreasing tendency for margination with increasing Reynolds number. The effect is discussed by analysing inertial and non-inertial lift forces for single cells under different flow conditions and large-scale two-dimensional simulations of interacting red blood cells and white blood cells in an idealized blood vessel.
Examining cognitive fatigue in multiple sclerosis : can self-reported fatigue predict deteriorating test performance?

Multiple Sclerosis (MS) is the most prevalent neurological disorder affecting younger adults. A symptom affecting the majority of people with MS (pwMS), and which can significantly impede the person’s ability to engage in everyday activities, is fatigue. This study aimed to further current understandings of the little understood concept of cognitive fatigue in pwMS. Cognitive fatigue was examined through objective and subjective (intellectual and online) measures. Participants included 31 pwMS (M = 47.77, SD = 12.19) and 30 healthy controls (M = 44.37, SD = 11.37), who completed neuropsychological assessments, including a task of sustained attention administered twice during testing. Participants completed a single intellectual assessment of cognitive fatigue, and online assessments of cognitive fatigue repeated three times throughout testing. The findings indicated that fatigue in MS is experienced temporally, with higher self-reports of fatigue following sustained mental effort. The online measures were the strongest predictor of actual test performance. Further, pwMS overestimated their levels of fatigue relative to actual test performance indicating possible reduced levels of insight into actual declining abilities. The results highlight the need for clinicians to utilise various measures when examining the multifaceted phenomenon of cognitive fatigue, and address perceptions pwMS may have about their fatigue.