Miracle-dz/UniFAR-FTUs huggingface dataset:
Plant K Channel Proteins

Almost 40 years ago, Epstein et al. (1963) developed the seminal concept of passive (i.e. low affinity, occurring at high soil solution [K]) and active (occurring at low soil K) pathways for cation nutrient (specifically K) uptake by crop plants. Since that time, numerous plant K transport proteins have been cloned, and associated with specific transport properties of plant cell membranes. We now have a fairly clear, but still incomplete understanding of the specific proteins that facilitate K uptake into, and transport within the plant. Following the model developed by Epstein, passive K uptake into plants, whereby K movement follows the electrochemical gradient across root cell membranes, has been shown to be facilitated by ion channels (passive transport). Active uptake of K (i.e. against the chemical gradient) is facilitated by proton pumps (H-ATPases) and K/H symporters.
Development of weightometer soft sensor

A prototype weightometer soft sensor is under development at DebTech, De Beers in partnership with Venetia Mine. Its main function consists of an online data source; data validation; dynamic weightometer models; online detection of weightometer failure; alarming and replacing a weightometer when it fails. 31 dynamic models have been developed. All models with R2 >= 85% are accepted as good models and they generally have satisfactory results with a daily enor of less than 8% within 90% confidence level. By using those models, a set of soft sensors can be set up to cover all weightometers in the entire processes starting from primary crushing to the stock piles of dense medium separation (DMS). Some practical issues and concerns on model development are discussed, including data collection, data analysis, data pre-processing, variable selection, time delay, model training and model validation. When deploying the weightometer soft sensor system, the potential benefits could include: reduction in plant downtime; reduction in unplanned maintenance and even replacement of non-critical weightometers, particularly where nuclear weightometers are used.
Ecological effects of major injuries in diamondback terrapins : implications for conservation and management

1. Many turtle species frequently suffer major injuries due to attempted predation or anthropogenic factors. Diamondback terrapins (Malaclemys terrapin) are one species known to be affected by anthropogenic activity, but little is known about the causes of injuries. In declining diamondback terrapin populations, learning more about causes and results of injuries can be helpful in developing sound management plans. 2. Patterns of limb loss and major shell injuries were examined in a population of terrapins studied for 24 years at Kiawah Island, South Carolina to infer the causes and effects of injuries and possible predators on terrapins. 3. The rate of shell injuries increased temporally, possibly as a result of increased watercraft activity. Because no differences in rates of limb loss were found between males and females, limb loss probably results from aquatic encounters (i.e. limb loss does not appear to be the result of terrestrial predation during nesting). Furthermore, males experienced reduced body condition when injured, and terrapins with a major injury had lower survivorship than uninjured terrapins. 4. Therefore, in addition to reducing sources of mortality and protecting nesting habitat, measures to protect terrapins from watercraft activity may increase the survivorship of adult terrapins. Copyright r 2008 by John Wiley & Sons, Ltd. Received 25 November 2007; Revised 9 June 2008; Accepted 29 June 2008
Anisotropic fluctuations in turbulent shear flows

An experimental analysis of small-scale anisotropic fluctuations has been performed in two different flows in order to assess possible universal features of shear dominated turbulence, such as the decay rate of anisotropy at small scales and the recovery of isotropy. The two data sets—a homogeneous shear flow and a turbulent boundary layer—are characterized by turbulent Reynolds numbers in the range Reλ=230−330. The measurements in the logarithmic region of the turbulent boundary layer extend from y+=90 up to y+=350. The explicit use of the Taylor hypothesis is avoided by resorting to two-point measurements, with separation in the spanwise direction, z. Streamwise (u) and wall-normal (v) velocity components are simultaneously measured in both positions by means of cross-wire probes. This procedure allows the construction of the mixed transverse structure functions, here addressed up to order 6. According to the SO(3) formalism, the observables we selected are free of any isotropic contribution, thus allow.
Interpreting Predictive Models for Human-in-the-Loop Analytics

Machine learning is increasingly used to inform consequential decisions. Yet, these predictive models have been found to exhibit unexpected defects when trained on real-world observational data, which are plagued with confounders and biases. Thus, it is critical to involve domain experts in an interactive process of developing predictive models; interpretability oﬀers a promising way to facilitate this interaction. We propose a novel approach to interpreting complex, blackbox machine learning models by constructing simple decision trees that summarize their reasoning process. Our algorithm leverages active learning to extract richer and more accurate interpretations than several baselines. Furthermore, we prove that by generating a suﬃcient amount of data through our active learning strategy, the extracted decision tree converges to the exact decision tree, implying that we provably avoid overﬁtting. We evaluate our algorithm on a random forest to predict diabetes risk on a real electronic medical record dataset, and show that it produces signiﬁcantly more accurate interpretations than several baselines. We also conduct a user study demonstrating that humans are able to better reason about our interpretations than state-of-the-art rule lists. We then perform a case study with domain experts (physicians) regarding our diabetes risk prediction model, and describe several insights they derived using our interpretation. Of particular note, the physicians discovered an unexpected causal issue by investigating a subtree in our interpretation; we were able to then verify that this endogeneity indeed existed in our data, underscoring the value of interpretability.
A comprehensive framework for emotional intelligence.

Since Salovey and Mayer’s (1990) seminal article on emotional intelligence (EI), a number of alternative models have been developed (e.g., Bar-On, 1997; Cooper & Sawaf, 1997; Goleman, 1995; 1998; 2001a; Mayer & Salovey, 1997; Petrides & Furnham, 2001). This work has provided different approaches to the conceptualization and measurement of EI. However, it has also caused some confusion concerning the nature and boundaries of the concept. Variables ranging from emotional abilities and competencies, to so-called ‘noncognitive’ capabilities and skills have been placed under the banner of EI. Furthermore, while some theoretical models of EI have comprised four salient facets (Mayer & Salovey, 1997), others have comprised twenty or more (e.g., Cooper & Sawaf, 1997). As such, it is not surprising that reviews of the area have described EI as ‘popular but elusive with fuzzy boundaries’ (Pfeiffer, 2001). This confusion has been the impetus of our work which has been to establish a common definition and taxonomic model of EI that comprises the primary facets of the construct. In this chapter we present our model that is based on a large factor analytic study using several measures of EI. We conclude by questioning whether the
Edinburgh Research Explorer How the 'Northern Irish' identity is understood and used by young people and politicians

The conventional understanding of the nation within social psychology is as a category of people or “imagined community. ” However, work within the discursive tradition shows that citizens tend to discuss nationhood in a variety of modes, including the use of nonhuman categories such as references to the physical landscape of the country. This article aims to give a more comprehensive overview of how young people understand the Northern Irish identity, a new and potentially inclusive national category in a divided society, and how politicians articulate it in rhetoric. In Study 1, students (N = 286) discussed this identity in 44 peer-led focus groups. Thematic analysis of their discussions shows four distinct ways in which it is constructed: as a distinctive people, as an identity claim, as a “hot” political project, and as a “cold” or banal indicator of place. In Study 2, Members of the Legislative Assembly at Stormont (N = 49) responded to open-ended questions about the Northern Irish identity. Each of the parties used different conceptualizations for rhetorical effect. These results give a deeper understanding of the multifaceted nature of national identity and its ability to promote political agendas.
Influence of salvage logging on forest recovery following intermediate severity canopy disturbances in mixed beech dominated forests of Slovenia

Abstract: The practice of salvage logging dead and damaged timber following large high severity disturbances has raised much controversy, partly because of the negative ecological effects that such practices have on forest ecosystems. Many of the studies on salvage logging effects, however, have been done on sites damaged by large, severe disturbances. Less is known about the ecological consequences of salvage logging following intermediate severity disturbances that cause partial canopy damage at smaller scales. We examined the response of the herbaceous layer and tree regeneration to salvaged and non-salvaged treatments following small-scale intermediate severity disturbances in eight mixed beech (Fagus sylvatica L.) dominated forest stands in Slovenia. The cover and diversity of herbaceous vegetation, as well as the density and diversity of tree regeneration were similar between treatments across the study sites. The only notable differences between the treatments were that salvaged sites had a larger proportion of shade intolerant tree species in the regeneration layer, while non-salvaged sites tended to have a more well-developed regeneration layer in taller height classes. The results suggest that salvage logging following small-scale intermediate severity disturbances may not hinder forest recovery in mixed beech dominated forests.
Evaluation of Tasks Allocation, Scheduling and Ranking Techniques in a Cloud Computing Environment

Cloud computing presents an architecture that delivers computing services via the internet on demand and payed per use of a pool of resources that are shared, such as networks, storage, servers, services and applications, without having to acquire them. Cloud computing reduces managing cost and time for organizations. Many industries, such as banking, healthcare and education are shifting to the cloud, due to the effectiveness of services delivered by the pay-per-use concept depending on the resources, such as processing power utilized, transactions performed, bandwidth consumed, data transmitted, or storage space occupied etc. Cloud computing is considered as a technology that relies completely on the internet, where client data is saved and kept in the data center of a cloud supplier. The goal of this paper is to implement and evaluate different allocation, scheduling and ranking techniques, where, different methods for the allocation, scheduling and ranking of workflow tasks are proposed, implemented and evaluated. Simulation was performed on these techniques, and the results were analyzed to find the best technique in terms of efficiency and performance in reducing completion time and cost. General Terms Cloud Computing
Orchestrating dynamic analyses of distributed processes for full-stack JavaScript programs

Dynamic analyses are commonly implemented by instrumenting the program under analysis. Examples of such analyses for JavaScript range from checkers of user- defined invariants to concolic testers. For a full-stack JavaScript program, these analyses would benefit from reasoning about the state of the client-side and server-side processes it is comprised of. Lifting a dynamic analysis so that it supports full-stack programs can be challenging. It involves distributed communication to maintain the analysis state across all processes, which has to be deadlock-free. In this paper, we advocate maintaining distributed analysis state in a centralized analysis process instead — which is communicated with from the processes under analysis. The approach is supported by a dynamic analysis platform that provides abstractions for this communication. We evaluate the approach through a case study. We use the platform to build a distributed origin analysis, capable of tracking the expressions from which values originate from across process boundaries, and deploy it on collaborative drawing application. The results show that our approach greatly simplifies the lifting process at the cost of a computational overhead. We deem this overhead acceptable for analyses intended for use at development time.
Hypolipidemic Effect of Puerarin and Underlying Mechanism Investigation

Excessive intake of fat in the diet is one of the main reasons leading to hyperlipidaemia, which will result in many diseases that endanger the human health. Puerarin, which is extracted from the dry roots of the legume plant Radix Puerariae, has been reported to be able to improve the regeneration capability of liver cells, recover the normal liver functions, and prevent the accumulation of fat in the liver. However, research on the regulation of blood lipids has never been referred. In this paper, decrease of the blood lipids in rats by puerarin and the underlying mechanism have been thoroughly discussed. Hyperlipidaemia models were established by feeding the rats with high-fat diet, to which puerarin (10mg/kg, 20mg/kg and 40mg/kg) was then given continuously for 15 days by gavage, and blood indexes of the rats were tested and shown as follows: Puerarin could reduce the serum TC, TG and LDL-C values (P<0.05) and elevate the HDL-C values (P<0.05), which was thus demonstrated to exhibit significant hypolipidemic activity. Total RNA of the rat livers of the group treated with 400mg/kg of puerarin was extracted, and cDNA library was constructed utilizing mag-bind oligo (dT) enriched mRNA. Gene sequencing was carried out, the resulting data were assessed and their saturation was also analyzed. Besides, screening, cluster analysis of expression patterns, GO functional significant enrichment analysis and PATHWAY significant enrichment analysis for the differential gene expressions were performed. Gene expression profiling exhibited that 780 gene levels of the control and hyperlipidaemia model groups changed, in which 525 genes were up-regulated, and 255 genes were down-regulated. Meanwhile, 495 gene levels of the model group changed compared to those of the puerarin groups, in which 72 genes were up-regulated, 423 genes were down-regulated, and the number of the changed genes both involved was 163. Moreover, pathway of the fatty acid metabolism of the most significant enriched GO term was most closely related to the blood lipid metabolism in the differentially expressed genes. In this pathway, alcohol dehydrogenase 6 in the fatty alcohol cycle was down-regulated by puerarin. As a result, puerarin reduced the generation of fatty acids, regulated the entire fatty acid metabolism, and lowered the blood lipids eventually.
Constructing Narrative Ecologies as a Site for Teachers' Professional Learning with New Technologies and Media in Primary Education

This article argues that to understand how new technologies and media can become coagents in the process of pedagogical change, we first need to understand teachers' complex relationship with new technologies and media in both their personal and their professional lives. A conceptual framework is delineated for constructing a complex narrative ecology around teachers' professional and personal relationship with new technologies and media. The narrative ecology model, it is proposed, can be used to story the otherwise isolated but constituent aspects of teachers' experiences of technology. It is an approach predicated on a view of professional learning as a narrative process. The model is applied and evaluated in a fine-grained narrative case study of one student teacher's approach to the use of a virtual learning environment (VLE) in an intervention within a primary school in the United Kingdom. The findings suggest that using the narrative ecology model to story teachers' personal and professional experiences with technology brings meaning and new insights to teachers' nuanced relationships with technology, creating a site for further professional development and learning.
Coherent triads and successful inter-professional collaboration: narratives of professional actors in the Swedish child welfare system

ABSTRACT The aim of this study is to analyze how and when the professional actors within the Swedish child welfare system portray successful cooperation and determine which discursive patterns are involved in the construction of this phenomenon. The empirical basis for this study is formed by 147 recorded interviews with institution-placed youths, their parents, and different occupational categories within the social services and the Swedish National Board of Institutional Care. Analytical findings with the following themes are presented: (1) coherent vision triad, (2) coherent rhetorically accepted triad, and (3) coherent exclusive triad. The personal interactive aspect of cooperation among professional actors in the care of children is important for successful collaboration. This aspect also appears to be significant for producing and reproducing joint collaboration identities. However, joint collaboration identities and the coherence triad can limit the sphere of cooperation to the entities involved in the care of youths and the juvenile or his/her parents are left out.
The capability of time- and frequency-domain algorithms for bistatic SAR processing

The paper presents a study of the capability of time- and frequency-domain algorithms for bistatic SAR processing. Two typical algorithms, Bistatic Fast Backprojection (BiFBP) and Bistatic Range Doppler (BiRDA), which are both available for general bistatic geometry, are selected as the examples of time- and frequency-domain algorithms in this study. Their capability is evaluated based on some criteria such as processing time required by the algorithms to reconstruct SAR images from bistatic SAR data and the quality assessments of those SAR images.
Comprehensive Classification Model for Diagnosing Multiple Disease Condition from Chest X-Ray

Classification plays a significant role in the diagnosis of any form of radiological images in the healthcare sector. After reviewing existing classification approaches carried out over chest radiographs, it was explored that existing techniques are highly restricted to perform binary classification that is not comprehensive for assisting in an effective diagnosis process of chest disease condition. This paper presents a novel approach to classifying chest x-rays on the basis of the practical disease condition. Harnessing the potential features of content-based image retrieval, the proposed system introduces a novel concept of attribute map that not only performs comprehensive classification but also makes the complete computational model extremely lightweight. The study outcome proved to offer better accuracy with the proposed non-iterative process in contrast to existing classifier design.
Familial Patterns and Biological Markers of Dyslexia

Abstract Dyslexia is one of the most common learning disability. Though dyslexia is a major educational problem, studies on biological aspects of dyslexia are very limited in India. Here we report prevalence, inheritance patterns and biological markers of dyslexia in 179 selected families from South India. Families were ascertained through probands attending special schools for dyslexic students as well as from regular schools from Karnataka state, South India. Prevalence and types of inheritance patterns were recorded. A questionnaire concerning allergies, asthma, arthritis, migraine etc. was used to assess the prevalence of immune disorders. Occurrence of chicken pox, measles, mumps, delayed milestones, birth complications, motor coordination problems, short sight and left handedness, fatty acid deficiency signs were recorded in the dyslexic probands. Among school children, prevalence of dyslexia is found to be 9.87% and in the selected families the prevalence is 28.32%. Based on the affectedness, dyslexia phenotypes were classified as severe and mild deficits. Mild deficits were better compensated than the severe deficits. Among the selected families autosomal dominant mode of inheritance was found to be more prevalent. Consanguinity plays a major role in familial aggregation of dyslexia. Allergy, migraine, delayed milestones, low level of blood cholesterol and certain fatty acid deficiency signs were found to be associated with dyslexia. Since complex array of symptoms are associated with dyslexia an integrated research approach is needed for effective diagnosis and remediation of dyslexia.
Stochastic assessment of climate impacts on hydrology and geomorphology of semiarid headwater basins using a physically based model

Hydrologic and geomorphic responses of watersheds to changes in climate are difficult to assess due to projection uncertainties and nonlinearity of the processes that are involved. Yet such assessments are increasingly needed and call for mechanistic approaches within a probabilistic framework. This study employs an integrated hydrology‐geomorphology model, the Triangulated Irregular Network‐based Real‐time Integrated Basin Simulator (tRIBS)‐Erosion, to analyze runoff and erosion sensitivity of seven semiarid headwater basins to projected climate conditions. The Advanced Weather Generator is used to produce two climate ensembles representative of the historic and future climate conditions for the Walnut Gulch Experimental Watershed located in the southwest U.S. The former ensemble incorporates the stochastic variability of the observed climate, while the latter includes the stochastic variability and the uncertainty of multimodel climate change projections. The ensembles are used as forcing for tRIBS‐Erosion that simulates runoff and sediment basin responses leading to probabilistic inferences of future changes. The results show that annual precipitation for the area is generally expected to decrease in the future, with lower hourly intensities and similar daily rates. The smaller hourly rainfall generally results in lower mean annual runoff. However, a non‐negligible probability of runoff increase in the future is identified, resulting from stochastic combinations of years with low and high runoff. On average, the magnitudes of mean and extreme events of sediment yield are expected to decrease with a very high probability. Importantly, the projected variability of annual sediment transport for the future conditions is comparable to that for the historic conditions, despite the fact that the former account for a much wider range of possible climate “alternatives. ” This result demonstrates that the historic natural climate variability of sediment yield is already so high, that it is comparable to the variability for a projected and highly uncertain future. Additionally, changes in the scaling relationship between specific sediment yield/runoff and drainage basin area are detected.