Miracle-dz/UniFAR-FTUs huggingface dataset:
Bernstein-Gelfand-Gelfand complexes and cohomology of nilpotent groups over $\Z_p$ for representations with p-small weights

We show that for $p$small highest weight $\lambda$, 1) there is a $\Z_p$-integral version of the Bernstein-Gelfand-Gelfand complex, still a direct summand subcomplex of the standard complex for $V(\lambda)$ 2) Similarly, a $\Z_p$-integral (as well as a mod. p) version of Kostant formula holds true. This paper is a companion paper to the one by Mokrane-Tilouine (AG, subm. 12/12/00), where these results are requested.
Erosion control and storm water quality from straw with PAM, mulch, and compost blankets of varying particle sizes

ABSTRACT: Compost and mulch blankets have been widely used for slope stabilization and erosion control at construction sites; however, the majority of research on these erosion control blankets has failed to meet state or federal specifications for particle size distribution. The primary objective of this study was to determine how blending wood mulch with compost may affect its performance as an erosion control practice relative to a straw blanket with polyacrylamide (PAM). The secondary objective of this study was to determine if particle size distribution of the organic erosion control blanket affects runoff, erosion, and vegetation establishment. Researchers concluded that the greater percent of compost used in an erosion control blanket, the lower the total runoff and the slower the runoff rate. Compost erosion control blankets retained 80% of the simulated rainfall applied and reduced cumulative storm runoff by 60%, while the wood mulch blankets reduced runoff by 34% and straw with PAM by 27%. Conversely, the greater the percent of mulch used in the erosion control blanket, the lower the sediment and suspended sediment load. However, any combination of compost and mulch reduced runoff volume, runoff rate, and soil loss relative to a straw blanket with polyacrylamide. The average cover management factor (C factor) for the straw with PAM was 0.189, the compost blanket was 0.065, and the mulch blanket was 0.013. Researchers also concluded that particle size distribution of the compost and mulch blankets was the leading parameter that reduced soil loss and runoff. If particle size distribution specifications are not followed, total soil loss can be four times greater, suspended solids can be five times greater, and turbidity can be eight times greater, relative to blankets that meet particle size distribution specifications. Nitrogen and phosphorus loading from mineral fertilizer used with conventional straw blankets may lead to increased nutrient loading of receiving surface water relative to the compost and mulch blankets. The straw blanket with fertilizer increased total Kjeldahl nitrogen loading by more than 8,000%, the compost blanket increased total Kjeldahl nitrogen by 340%, and the mulch blanket by 18% relative to the control. Although the bare soil and mulch blanket treatments did not contribute any soluble phosphorus (P) to runoff, relative to the compost blanket, the soluble P load from the straw blanket with PAM was 3,800% greater. Results from this study may be used to revise particle size specifications for compost erosion control blankets and to help regulators and design professionals determine which type of erosion control best management practice is best for their particular application.
Website Quality Assessment Criteria

The article presents a hierarchical framework, which supports website quality assessment. The framework is composed of a hierarchical structure of criteria and subcriteria and makes use of the Analytic Hierarchy Process to enhance criterion and subcriterion weight value assessment. To validate the framework we conducted an experiment, which involved the assessment of the websites of the three cellular phone service providers in Greece by 122 users. Results confirmed framework validity and statistical factor analysis supported reduction of the original model to a website quality scoring framework, which involves nine composite criteria.
Yaratıcı Düşünme Becerilerinde Okul Öncesi Eğitimin Etkisi

Bu arastirma, okul oncesi egitimi alan ve almayan cocuklarin yaratici dusunme becerilerini incelemek amaciyla planlanmistir. Arastirmanin evrenini, Ankara il merkezinde bulunan ilkogretim okullarinin anasiniflarina devam eden alti yas grubu cocuklar olusturmaktadir. Arastirmanin orneklemine ise bu okullar arasindan tesadufi ornekleme yontemiyle secilen toplam sekiz okuldaki anasiniflarina devam eden, daha once okul oncesi egitim alan ve almayan, normal gelisim gosteren alti yasindaki 210 cocuk dahil edilmistir. Arastirmada, cocuklar ile ilgili bilgi almak amaciyla “Genel Bilgi Formu” ve cocuklarin yaratici dusunme duzeylerini belirlemek amaciyla Urban ve Jellen (1996) tarafindan gelistirilen Can-Yasar (2009) tarafindan alti yas Turk cocuklari icin gecerlik guvenirlik calismasi yapilan “Yaratici Dusunme-Resim Olusturma Testi (YD-ROT)” kullanilmistir. Cocuklarin yaratici dusunme becerileri ile okul oncesi egitimi alma durumlari ve cinsiyet arasindaki iliski Mann Whitney U-Testi ile analiz edilmistir. Arastirma sonucunda, okul oncesi egitim alan cocuklarin yaratici dusunme puanlari okul oncesi egitim almamis cocuklarin puanlarindan anlamli derecede yuksek bulunmustur (p < 0,05). Cocuklarin cinsiyeti, yaratici dusunme becerileri uzerinde onemli bir fark yaratmamistir.
Paraphrasing with Bilingual Parallel Corpora

Previous work has used monolingual parallel corpora to extract and generate paraphrases. We show that this task can be done using bilingual parallel corpora, a much more commonly available resource. Using alignment techniques from phrase-based statistical machine translation, we show how paraphrases in one language can be identified using a phrase in another language as a pivot. We define a paraphrase probability that allows paraphrases extracted from a bilingual parallel corpus to be ranked using translation probabilities, and show how it can be refined to take contextual information into account. We evaluate our paraphrase extraction and ranking methods using a set of manual word alignments, and contrast the quality with paraphrases extracted from automatic alignments.
How organizational green culture influences green performance and competitive advantage

PurposeGrowing public concern about the natural environment is rapidly transforming the competitive landscape and forcing firms to adopt green innovation strategies. Many manufacturing firms have recognized the concept of green innovation, though there has been relatively little research on considerations of its driver and effect. The purpose of this paper is to empirically develop and test a theoretical model that analyzes how organizational green culture (OGC) influences green performance and competitive advantage. Specifically, this model explains how green innovation mediates these relationships.Design/methodology/approachThe paper collected data from 327 manufacturing firms of different industry sectors in Taiwan. Structural equation modeling with AMOS 11 software was applied to analyze the data. Data on specific environmental innovation issues at the firm level are not usually available from published sources, so this paper uses a questionnaire. The questionnaire is developed based on the literature.FindingsThe findings of this paper suggest that OGC significantly predicted green performance and competitive advantage, respectively. Moreover, the results show that both green innovation completely mediates between OGC and green performance, and that it has a partially mediating effect on the relationship between organization green culture and competitive advantage under environmental pressure.Research limitations/implicationsThis study has some limitations that point to the future lines of research. Perhaps, the biggest limitation of the study is that the data are from a single country, which may hamper generalization. This study is also limited in that it is based on cross-sectional data. A final limitation is the origin of organizational culture vs employee attitude culture.Originality/valueThis study contributes to the existing literature on organizational culture and innovation by considering green environmental concerns, which have not been empirically explored. This study also offers a unique theoretical argument describing the relationships by considering the mediating effect of green innovation strategy.
Path availability in ad hoc network

Due to the complexity and high randomness, most current researches on ad hoc networks are based on simulation results and empirical analysis, lacking theoretical understanding of the ad hoc networks and their behavior. This paper presents a general ad hoc network model and derives the statistical results of link and path availability properties in ad hoc network. Simulation results are given to verify our theory. This study could serve as groundwork for further ad hoc network researches including ad hoc network performance analysis and routing algorithms design.
Data Mining a Prostate Cancer Dataset Using Rough Sets

Prostate cancer remains one of the leading causes of cancer death worldwide, with a reported incidence rate of 650,000 cases per annum worldwide. The causal factors of prostate cancer still remain to be determined. In this paper, we investigate a medical dataset containing clinical information on 502 prostate cancer patients using the machine learning technique of rough sets. Our preliminary results yield a classification accuracy of 90%, with high sensitivity and specificity (both at approximately 91%). Our results yield a predictive positive value (PPN) of 81% and a predictive negative value (PNV) of 95%. In addition to the high classification accuracy of our system, the rough set approach also provides a rule-based inference mechanism for information extraction that is suitable for integration into a rule-based system. The generated rules relate directly to the attributes and their values and provide a direct mapping between them
A New Psychometric-inspired Evaluation Metric for Chinese Word Segmentation

Word segmentation is a fundamental task for Chinese language processing. However, with the successive improvements, the standard metric is becoming hard to distinguish state-of-the-art word segmentation systems. In this paper, we propose a new psychometric-inspired evaluation metric for Chinese word segmentation, which addresses to balance the very skewed word distribution at different levels of difficulty 1 . The performance on a real evaluation shows that the proposed metric gives more reasonable and distinguishable scores and correlates well with human judgement. In addition, the proposed metric can be easily extended to evaluate other sequence labelling based NLP tasks.
The Forecasting and Policy System: stochastic simulations of the core model

Uncertainty in applied macroeconomic policy analysis arises from three distinct sources. The first, often referred to as model uncertainty, arises because the models used for policy analysis are simple abstractions of the complex behavioural interactions that occur in an economy. The second source, denoted shock uncertainty, arises from unforeseen events that the analysis cannot explicitly factor in ex ante. Finally, starting-point uncertainty reflects the fact that given data lags and revisions, often it is difficult to assess the current state of the economy. This paper discusses the approach the Reserve Bank has taken to enable its Forecasting and Policy System (FPS) to quantify the implications that the typical level of shock uncertainty might be expected have on the analysis of alternative policy actions designed to achieve the objectives of monetary policy.
Boosting Convolutional Features for Robust Object Proposals

Deep Convolutional Neural Networks (CNNs) have demonstrated excellent performance in image classification, but still show room for improvement in object-detection tasks with many categories, in particular for cluttered scenes and occlusion. Modern detection algorithms like Regions with CNNs (Girshick et al., 2014) rely on Selective Search (Uijlings et al., 2013) to propose regions which with high probability represent objects, where in turn CNNs are deployed for classification. Selective Search represents a family of sophisticated algorithms that are engineered with multiple segmentation, appearance and saliency cues, typically coming with a significant run-time overhead. Furthermore, (Hosang et al., 2014) have shown that most methods suffer from low reproducibility due to unstable superpixels, even for slight image perturbations. Although CNNs are subsequently used for classification in top-performing object-detection pipelines, current proposal methods are agnostic to how these models parse objects and their rich learned representations. As a result they may propose regions which may not resemble high-level objects or totally miss some of them. To overcome these drawbacks we propose a boosting approach which directly takes advantage of hierarchical CNN features for detecting regions of interest fast. We demonstrate its performance on ImageNet 2013 detection benchmark and compare it with state-of-the-art methods.
Development of a Short Version of the Visual Function Questionnaire Using Item-Response Theory

Purpose In clinical ophthalmology as in other fields, measuring patient-reported outcomes imposes a burden on patients. To decrease that burden, we used item-response theory (IRT) to develop and test a short version of the National Eye Institute's Visual Function Questionnaire (VFQ). Methods We analyzed VFQ data from 276 adults in Japan. Most of them had glaucoma, cataract, or macular degeneration. Their visual acuity (Snellen fraction) averaged 20/120 (range: 20/13 to 20/2000) for the better eye, and 20/200 (range: 20/13 to 20/2000) for the worse eye. We used a polytomous IRT model, the Generalized Partial Credit Model as implemented in software for parameter scaling of rating data (PARSCALE). To select items for inclusion in the short version we examined each item's location on the latent-trait continuum, its slope, and its frequency of missing data. We also ensured representation of all 7 domains that are important in Japan. To examine the characteristics of the resulting scale, we computed its test information (an index of precision that can vary with the value of the latent trait), and carried out validation testing. Results From 32 of the original VFQ items, we selected 11. The scale comprising those 11 items (the VFQ-J11) had test information greater than 9 for values of the latent trait between −2.0 and +0.8. The item thresholds were well-targeted for patients with vision problems. Scores on the VFQ-J11 correlated strongly and in the expected direction with measures of visual field and corrected visual acuity. As expected for a valid measure, those scores also improved by a large amount (almost one standard deviation) after cataract surgery. Conclusion This 11-item instrument can provide reliable and the valid data on visual functioning in patients with ophthalmic problems. It is expected to be less of a burden on respondents, while it maintains good psychometric properties.
Solving Hyperbolic PDEs Using Interpolating Wavelets

A method is presented for adaptively solving hyperbolic PDEs. The method is based on an interpolating wavelet transform using polynomial interpolation on dyadic grids. The adaptability is performed automatically by thresholding the wavelet coefficients. Operations such as differentiation and multiplication are fast and simple due to the one-to-one correspondence between point values and wavelet coefficients in the interpolating basis. Treatment of boundary conditions is simplified in this sparse point representation (SPR). Numerical examples are presented for one- and two-dimensional problems. It is found that the proposed method outperforms a finite difference method on a uniform grid for certain problems in terms of flops.
Antioxidant Activity of the Extracts of Some Cowpea (Vigna unguiculata (L) Walp.) Cultivars Commonly Consumed in Pakistan

The present investigation has been carried out to determine the antioxidant activity of the methanolic extracts obtained from four cultivars of cowpea (Vigna unguiculata (L) Walp. ) seeds. Phenolic compounds present in the extracts showed the antioxidant and antiradical properties when investigated using a linoleic acid peroxidation model, FRAP, ORAC and TRAP assays, as well as DPPH, hydroxyl, nitric oxide and superoxide radical scavenging activity. The HPLC analysis of the cowpea extracts showed the presence of neochlorogenic acid, chlorogenic acid and caffeic acids. The results indicated that methanolic extract of the cowpea resembled in the aforementioned activities those from other leguminous seeds and pulses. Phenolic constituents contained in cowpea may have a future role as ingredients in the development of functional foods.
The Remarkable Rise and Particular Context of Younger One–Person Households in Seoul and Tokyo

Numbers of one–person households in East Asia have expanded dramatically in recent decades, especially among younger cohorts living in cities. In explaining this shift, research has largely addressed changes in socioeconomic and policy conditions that have interacted with family and marriage norms. This paper, however, is concerned with interactions of shifting urban and housing conditions that have channeled particular manifestations of single–dwelling featuring shifts in housing pathways among younger–adult cohorts toward living alone in rental housing. Focusing on Seoul and Tokyo as centers of growth, we consider how urban features, specifically housing markets and high–speed renewal of the built–environment, have shaped and contributed to the rise in one–person households, as well as how the proliferation of singlehood and living alone is reshaping the lives of younger people in urban neighborhoods. This shift represents a particular disruption in social and spatial reproduction that has implications for cities in this region more generally.
The Influence of Nature Relatedness on Decision Making Regarding Mate Selection in College-Educated Young Adults

Research to date has mainly focused on the influenc e of nature relatedness on a person’s subjective well-being (Nisbet, 2011) and as a predi ctor of happiness (Zelenski & Nisbet, 2014). There are few, if any, studies that look at the inf luence of nature relatedness on mate selection. The research question is Does nature relatedness influence mate selection in college-educated adults between the ages of 25 and 40? A secondary goal of this study is to begin to descr ibe the role of the natural environment in the lives of col lege-educated young adults. Through a modified snowball sampling technique using electron ic mail and social media, participants (n=266) completed an electronic questionnaire. Parti cipants’ levels of nature relatedness were measured using the Nature Relatedness Scale (NRS; N isbet, Zelenski, & Murphy, 2009). They filled out researcher-created questions that inquir ed into the influence of nature relatedness on mate selection, frequency of outdoor activities wit h a romantic partner, important characteristics and attributes when looking for a mate, and demogra phic information. Results show nature relatedness is a factor that almost half (49%) of t he participants look for in a romantic partner and more than half (63%) value in a romantic partne r. More than a quarter (29%) of the participants selected “enjoys spending time outdoor s” as one of the top five attributes they look for in a potential mate. The results demonstrate a positive correlation between an individual’s level of nature relatedness, the degree to which na ture relatedness plays a role in mate selection, and the frequency of engaging in outdoor activities with a romantic partner. Selected demographic variables such as gender, age group, ge ographical location, and geographical region show statistically significant differences on some of the NRS subscales. This study is important because it is one of the few, if any, studies exami ning the influence of nature relatedness on mate
Computational mapping of brain networks

Magnetic resonance imaging (MRI) has developed into an indispensible diagnostic tool in medicine. MRI has also demonstrated immense potential for researchers who are making progress in every aspect of this modality expanding its applications into uncharted territories. Computational techniques have made major contributions to MRI enabling detection of minute signals from human brain. Functional MRI (fMRI) offers imaging of the mind as well as the brain in the same session. Complex computational tools are used to visualize brain networks that offer a new powerful tool to study the brain and its disorders. Functional connectivity (fc) maps using resting state fMRI (rsfMRI) is computed by detecting temporal synchronicity of neuronal activation patterns of anatomically separated brain regions. But, a great deal of technological advancement, both in hardware and software, had to be made to make computation of brain networks possible. The critical technologies that made computational modeling of functional brain networks possible were high quality gradients for implementation of distortion free fMRI, faster pulse sequences and radio frequency (RF) coils to capture the fluctuation frequency of neuronal activity, and complex post processing computation of brain networks. rsfMRI is capable of detecting brain function that mediate high cognitive processes in normal brain. We aim to ultimately detect the disruption of this mediation in psychiatric patients. We have already obtained functional connectivity in normal subjects using fMRI data during resting state. We did this as a function of spatial resolution to explore the required computational sources and susceptibility effects on the sensitivity of fMRI to anatomic specialization. We provide a conceptual summary of the role of computational techniques in fMRI data analysis. In exploring this question, ultimately MRI's capability in accessing information at the neuronal level comes to surface. We use latest computational tools for analysis of data from human brain and offer a vision for future developments that could revolutionize the use of computational techniques in making neuropsychiatry a quantitative practice.
Detections of molecular hydrogen in the outer filaments of NGC 1275

We present clear spectroscopic detections of molecular hydrogen in the outer filaments of the Ha nebula surrounding the central galaxy of the Perseus cluster, NGC 1275. This implies the presence of warm molecular gas clouds at projected distances up to 24 kpc from the nucleus of the host galaxy, embedded in the hot intracluster medium. The emission-line intensity ratios reveal that the H 2 is predominately thermally excited with excitation temperatures of 1600-2200 K, suggesting a lack of pressure balance between the molecular component and its surrounding medium. Excitation by stellar ultraviolet or by the central active galactic nucleus is shown to be unlikely, while thermal excitation by X-rays or conduction from the ICM or shocks are all possibilities. Evidence for a non-thermal component is found in the spectra of some regions based on a low ortho-to-para ratio.