Miracle-dz/UniFAR-FTUs huggingface dataset:
Chamaecrista debilis Growth Fertilized with Organic Compound Doses in a Degraded Area by Gravel Mining

A B S T R A C T The species Chamaecrista debilis (Vogel) Irwin & Barneby is native from the "Cerrado" biome (Brazilian Savannah) and belongs to the Fabaceae family. Species from this genus, generally own mycorrhizal associations that play important role in the capture and mobilization of nutrients of the soil. The composting process has been widely used by Brazilian enterprises as a way of treatment of the organic soil residues, changing them into humus, which can be used directly in the forest planting as soil conditioners. The current work had as object to evaluate the initial development of the seedlings of Chamaecrista debilis in planting with doses of organic compound of residue of spinning and weaving industries and the species potential in the recovery of an area of "Cerrado" degraded by the gravel mining. The casual randomized blocks experimental delineation was used with three repetitions and four treatments: 0.0; 30.0; 60.0 and 120.0 g dm-3 of organic compound as fertilizer in each pit. The results have indicated that there was not an important difference among the treatments for increasing in height and diameter. The higher value between the amount of compound evaluated of height and diameter increasing occurred without the addition and with the application of 60.0 g dm -3 of organic residue compound from the spinning and weaving industry, however it is necessary to perform future evaluations. The survival rate presented significant decreasing with the application of the highest dosages of organic compound. The Chamaecrista debilis species has presented important features for the recovery of degraded area, as fast growth and production of biomass.
The interaction between supportive and unsupportive manager behaviors on employee work attitudes

Purpose The purpose of this paper is to use social exchange theory (SET) to examine a model where supportive and unsupportive manager behaviors (SMB and UMB) interact to predict employees’ engagement, job satisfaction and turnover intention. Design/methodology/approach A cross-sectional online survey collected data from 252 UK-based employees of a global data management company. Findings Factor analysis confirmed manager behaviors to consist of two constructs: supportive and unsupportive behaviors. Structural equation modeling indicated SMB predicted job satisfaction and turnover intentions, but not engagement. Job satisfaction, but not engagement, mediated the SMB-turnover intention relationship. UMB only predicted job dissatisfaction. Neither job satisfaction nor engagement mediated the UMB-turnover intention relationship. UMB undermined the positive relationship between SMB and turnover intention. Practical implications The behaviors assessed can be integrated into various stages of a manager’s development process to serve as guidelines of good practice. Crucially, findings suggest managers can exhibit both supportive and unsupportive behaviors, and that consistency in behaviors is important. The study also provides evidence that supportive managers can help reduce turnover intention through job satisfaction. Originality/value SET was used as a framework for SMB, UMB and engagement. To the authors’ knowledge this is the first study to examine the interaction between SMB and UMB.
Self-Medication Practice for Dysmenorrhoea in Medical, Paramedical and Non-medical Students

Dysmenorrhea is responsible for significant absenteeism from college in female students. Self-medication and home remedies are used by the students for relief from menstrual discomfort. The pattern of self-medication varies among the medical, paramedical and non-medical students. Hence, the present study was done to analyze and compare the self-medication practice and drugs used for dysmenorrhoea among medical, paramedical and non-medical students. This was a cross-sectional study conducted among female students with dysmenorrhoea in M.S.Ramaiah College Campus, Bangalore. Out of total 261 female students; 84 were medical, 91 paramedical and 86 non-medical students. Data was collected with prevalidated questionnaire related to various aspects like demographic data, symptoms and duration of dysmenorrhoea and pattern of management in the three groups. Data collected was analyzed using SPSS version 20. The mean age of female students with dysmenorrhoea was 19.37 ± 0.99 years. 39% students perceived hormonal changes as causative factor for dysmenorrhoea. About 112(42.9%) were on self-medication and 78(29.9%) of students used home remedies for dysmenorrhoea. Among 112 students, drugs commonly used for self-medication were mefenamic acid + dicyclomine (63.4%) followed by paracetamol (17.9%), dicyclomine (9.8%) and ibuprofen (7.1%). Mefenamic acid was used commonly by students in three groups. Non-medical students used more of dicyclomine (22.2%) when compared with medical (4.2%) and non-medical students (3.6%). Dysmenorrhoea is a common cause for self-medication among females. Selfmedication practice for dysmenorrhoea was seen more in medical students where as non-pharmacological remedies in paramedical and non-medical female students. Analgesics like mefenamic acid and paracetamol are the mainstay of self- medication for dysmenorrhoea.
Towards Accurate and Interpretable Sequential Prediction: A CNN & Attention-Based Feature Extractor

With the influence of information explosion, there are more and more choices exposed to public view. Next item recommendation is being a significant and challenging task. Recently, attention mechanism, Convolutional Neural Networks (CNN) and other kinds of deep components are used to model user behaviors. However, the proposed models often fail to extract the feature of user behaviors in different time periods and the CNN-based models before are hard to make the used CNN interpretable. In this paper, we propose a CNN & Attention-based Sequential Feature Extractor (CASFE) module to capture the possible features of user behaviors at different time intervals. Specifically, we import CNN to extract multi-level features of user behaviors with different time periods. After each CNN layer, we use attention module to emphasize the different effect of behaviors on the prediction result. Besides, the features we try to extract here have the similar concept and meaning with the hand-crafted features in Feature Engineering, which proves the validity of CASFE. Accordingly, CASFE becomes a general sequential feature extractor that can be used in various sequential prediction tasks. With Multi-Layer Perceptron (MLP), CASFE would be a state-of-the-art next item recommendation model. The model obtains good performance on Last. fm_1K dataset and MovieLens_1M dataset. Besides, as a compatible extractor module, it can also promote CTR prediction models as well as other sequential prediction tasks.
Disentangling university-industry relationships: evidence from firms in a catch-up region

This article examines the complexity of the links between industry and universities in a peripheral region from the perspective of the firms. It focuses specifically on the diversity of situations in which these university-industry interactions occur. A survey of 737 firms in Andalusia is used for the analysis, reflecting a variety of innovative profiles. The analysis identifies the importance of a wide range of relationships, determines how they are structured and draws a profile of firms according to their links with universities. The results show the multiple channels by which a university system can contribute to firm innovation. They also suggest the need for empirical research and policy options to be adapted for regional environments.
EPA: Exoneration and Prominence based Age for Infection Source Identification

Infection source identification is a well-established problem, having gained a substantial scale of research attention over the years. In this paper, we study the problem by exploiting the idea of the source being the oldest node. For the same, we propose a novel algorithm called Exoneration and Prominence based Age (EPA), which calculates the age of an infected node by considering its prominence in terms of its both infected and non-infected neighbors. These non-infected neighbors hold the key in exonerating an infected node from being the infection source. We also propose a computationally inexpensive variant of EPA, called EPA-LW. Extensive experiments are performed on seven datasets, including 5 real-world and 2 synthetic, of different topologies and varying sizes to demonstrate the effectiveness of the proposed algorithms. We consistently outperform the state-of-the-art single source identification methods in terms of average error distance. To the best of our knowledge, this is the largest scale performance evaluation of the considered problem till date. We also extend EPA to identify multiple sources by developing two new algorithms - one based on K-Means, called EPA_K-Means, and another based on successive identification of sources, called EPA_SSI. Our results show that both EPA_K-Means and EPA_SSI outperform the other multi-source heuristic approaches.
Organic Acid Metabolism and the Impact of Fermentation Practices on Wine Acidity: A Review

The conversion of grape sugar to ethanol and carbon dioxide is the primary biochemical reaction in alcoholic wine fermentation, but microbial interactions, as well as complex secondary metabolic reactions, are equally relevant in terms of the composition of the final wine produced. The chemical composition of a wine determines the taste, flavour and aroma of the product, and is determined by many factors such as grape variety, geographical and viticultural conditions, microbial ecology of the grapes and of the fermentation processes, and the winemaking practices. Through the years, major advances have been made in understanding the biochemistry, ecology, physiology and molecular biology of the various yeast strains involved in wine production, and how these yeasts affect wine chemistry and wine sensory properties. However, many important aspects of the impact of yeast on specific wine-relevant sensory parameters remain little understood. One of these areas of limited knowledge is the contribution of individual wine yeast strains to the total organic acid profile of wine. Wine quality is indeed very directly linked to what wine tasters frequently refer to as the sugar–acid balance. The total acidity of a wine is therefore of prime sensory importance, and acidity adjustments are a frequent and legal practice in many wineries. However, the total acidity is the result of the sum of all the individual organic acids that are present in wine. Importantly, each of these acids has its own sensory attributes, with descriptors ranging from fresh to sour to metallic. It is therefore important not only to consider total acidity, but also the contribution of each individual acid to the overall acid profile of the wine. This review will summarise the current knowledge about the origin, synthesis and analysis of organic acids in wine, as well as on the management of wine acidity.
Who Wins Media Space and Why? Interest Groups and Legislative Lobbying in the European News Media

This paper examines the coverage of legislative lobbying in European news media. The starting point thereby is that lobbying in the crowded EU-level interest community is not only a struggle for direct access to policymakers, but that in order to realize policy goals many interest groups rely on political attention generated by the media. Our main research question is how media attention is skewed towards particular interests and which factors explain these varying levels of prominence. Our empirical analysis is based on a set of 125 legislative proposals adopted by the European Commission between 2008 and 2010. For all these cases we identified 388 interest organizations that made public statements, we coded the amount of media attention for these organized interest, the type of statements they made as well as some key organizational features. While the aggregate levels of attention look pretty balanced, our evidence shows that media prominence is skewed towards particular types of interests and that the uneven distribution of media prominence is significantly explained by the type of policy position organized interests adopt.
High-Resolution Augmentation for Automatic Template-Based Matching of Human Models

We propose a new approach for 3D shape matching of deformable human shapes. Our approach is based on the joint adoption of three different tools: an intrinsic spectral matching pipeline, a morphable model, and an extrinsic details refinement. By operating in conjunction, these tools allow us to greatly improve the quality of the matching while at the same time resolving the key issues exhibited by each tool individually. In this paper we present an innovative High-Resolution Augmentation (HRA) strategy that enables highly accurate correspondence even in the presence of significant mesh resolution mismatch between the input shapes. This augmentation provides an effective workaround for the resolution limitations imposed by the adopted morphable model. The HRA in its global and localized versions represents a novel refinement strategy for surface subdivision methods. We demonstrate the accuracy of the proposed pipeline on multiple challenging benchmarks, and showcase its effectiveness in surface registration and texture transfer.
5 HT 2 A and 5 HT 2 B Receptors Contribute to Serotonin-Induced Vascular Dysfunction in Diabetes

Although 5HT2A receptors mediate contractions of normal arteries to serotonin (5HT), in some cardiovascular diseases, other receptor subtypes contribute to the marked increase in serotonin contractions. We hypothesized that enhanced contractions of arteries from diabetics to 5HT are mediated by an increased contribution from multiple 5HT receptor subtypes. We compared responses to selective 5HT receptor agonists and expression of 5HT receptor isoforms (5HT1B, 5HT2A, and 5HT2B) in aorta from nondiabetic (ND) compared to type 2 diabetic mice (DB, BKS.Cg-Dock7m+/+Leprdb/J). 5HT, 5HT2A (TCB2 and BRL54443), and 5HT2B (norfenfluramine and BW723C86) receptor agonists produced concentration-dependent contractions of ND arteries that were markedly increased in DB arteries. Neither ND nor DB arteries contracted to a 5HT1B receptor agonist. MDL11939, a 5HT2A receptor antagonist, and LY272015, a 5HT2B receptor antagonist, reduced contractions of arteries from DB to 5HT more than ND. Expression of 5HT1B, 5HT2A, and 5HT2B receptor subtypes was similar in ND and DB. Inhibition of rho kinase decreased contractions to 5HT and 5HT2A and 5HT2B receptor agonists in ND and DB. We conclude that in contrast to other cardiovascular diseases, enhanced contraction of arteries from diabetics to 5HT is not due to a change in expression of multiple 5HT receptor subtypes.
Interference Detection and Characterization with an Array based GNSS Receiver using Conformal Antennas in Maritime Environments

The results of the interference measurement campaign carried out on board of a large container ship over the timespan of 2.5 months are presented. The interference situation in L1/E1 and L5/E5a frequency bands of GPS/Galileo that is representative for many maritime signal environments is characterized by observing the variation of the received IF power. Four detected interference events in L1/E1 band are presented. The interference effect of the signals of Distance Measurement Equipment (DME) in L5/E5a band is assessed. The characteristics of observed man-made radio emissions in both frequency bands are analyzed by using the high-rate recorded data. The design of the measurement system and its components is discussed in details.
Decisions on the causal structure of vector autoregressions

This paper ful…lls a double purpose. Firstly, we aim at studying causality tests with respect to their power of classi…cation into the four main competing hypotheses of causal interaction among two variables. We allow for various empirically relevant modi…cations of the basic bivariate autoregressive frame. These experiments result in some tentative recommendations for the empirical researcher. Secondly, we present and advertise the use of the decision maps technique, which builds on Bayes testing and is in itself a powerful simulation tool that can be used for many other statistical decision problems, particularly with a time-series background.
Production, composition and processing of milk from ewes fed soybean seeds

The objective of this study was to evaluate production, chemical composition, and estimates of total solids and fatty acid profile of milk from 1/2 Lacaune × 1/2 Ile de France ewes fed control and soybean seeds-supplemented diets. Additionally, Roquefort type cheese was also produced and subjected to sensory analysis. Twenty four 1/2 Lacaune × 1/2 Ile de France ewes were divided into three groups and fed a control diet and diets containing 70 and 140 g kg-1 soybean as fed, during the lactation period. The remainder milk was used to produce Roquefort cheese. The experimental design was completely randomized, with three treatments (0, 70, and 140 g of soybean kg-1 as fed) and eight repetitions. The diets did not affect significantly the performance (56.72 kg post-birth weight; 62.63 kg weight after 56 lactation days; 2.03 kg day-1 dry matter intake; 0.11 kg average daily weight gain), or milk production (443.61 mL day-1), density (1.035 g mL-1), acidity (19.33 °D), and pH (6.41) of lactating ewes. Milk chemical composition was (per 100 g of milk): 14.86 g total solids, 9.84 g solids not fat, 4.98 g protein, 4.14 g casein, 5.03 g fat, and 4.11 g lactose. Saturated (72.07 g/100 g of fat), monounsaturated (21.48 g/100 g of fat) and polyunsaturated (6.37 g/100 g of fat) fatty acids were not significantly different. However, the polyunsaturated linoleic acid was significantly different in the milk from ewes fed the diet containing 140 g of soybean kg-1 as fed (5.58 g/100 g of fat) compared with those fed the control diet and 70 g of soybean kg-1 as fed (3.82 g/100 g of fat). The Roquefort type cheese had excellent acceptance by the panel. The highest cheese yield was obtained with the milk from ewes fed diets containing 70 g kg-1 soybean as fed. A diet containing 140 g kg-1 soybean as fed is recommended as it leads to greater linoleic acid content in the ewes milk, improving the lipid fractions and nutritional quality of the milk.
Technical change and efficiency in Irish agriculture

This paper calculates average technical efficiency levels and rates of technical change for Irish agriculture using an unbalanced panel of 2,603 farms drawn from the Irish National Farm Survey over the period 1984 to 1998. An average technical efficiency level of between 65 and 70 per cent with a slight upward trend over the period was found. The efficiency of individual farms is positively associated with the size of the farm household, the ratio of debt to assets and the farmer’s age, and negatively related to being located in the West of Ireland, having an off-farm job and size of farm. Technical progress is observed at an unweighted rate of approximately 0.9 per cent and a weighted rate of 2.1 per cent per annum over the 1984-98 period. There is evidence that this rate of growth has been slowing over time. Technical progress was considerably faster on farms in the East of the country compared to Western farms, on larger farms compared to smaller ones, and on dairy and tillage farms compared to cattle and sheep farms.
Modes of ejecta emplacement at Martian craters from laboratory experiments of an expanding vortex ring interacting with a particle layer

Ejecta morphologies of many Martian craters indicate fluidized emplacement which differs from ballistic emplacement in dry, airless environments. Double Layered Ejecta craters possess particularly interesting ejecta morphologies: two lobes and radial lineations on their surface, which probably result from gas‐dominated radial flow during the emplacement. To examine how a radial flow interacts with surface particles to generate some of the observed morphologies on Mars, we have conducted water tank experiments in which a vortex ring encounters a particle layer. The threshold of particle motion and three interaction modes are described by two dimensionless numbers: particle Shields' parameter and particle Reynolds number. Our results show that gas‐dominated flows are possible during cratering and could be used to constrain the ancient Martian environment from observations.
DeepOPF: A Deep Neural Network Approach for Security-Constrained DC Optimal Power Flow

We develop DeepOPF as a Deep Neural Network (DNN) approach for solving security-constrained direct current optimal power flow (SC-DCOPF) problems, which are critical for reliable and cost-effective power system operation. DeepOPF is inspired by the observation that solving SC-DCOPF problems for a given power network is equivalent to depicting a high-dimensional mapping from the load inputs to the generation and phase angle outputs. We first train a DNN to learn the mapping and predict the generations from the load inputs. We then directly reconstruct the phase angles from the generations and loads by using the power flow equations. Such a predict-and-reconstruct approach reduces the dimension of the mapping to learn, subsequently cutting down the size of the DNN and the amount of training data needed. We further derive a condition for tuning the size of the DNN according to the desired approximation accuracy of the load-generation mapping. We develop a post-processing procedure based on $\ell _1$-projection to ensure the feasibility of the obtained solution, which can be of independent interest. Simulation results for IEEE test cases show that DeepOPF generates feasible solutions with less than 0.2% optimality loss, while speeding up the computation time by up to two orders of magnitude as compared to a state-of-the-art solver.
Adversarial NLI: A New Benchmark for Natural Language Understanding

We introduce a new large-scale NLI benchmark dataset, collected via an iterative, adversarial human-and-model-in-the-loop procedure. We show that training models on this new dataset leads to state-of-the-art performance on a variety of popular NLI benchmarks, while posing a more difficult challenge with its new test set. Our analysis sheds light on the shortcomings of current state-of-the-art models, and shows that non-expert annotators are successful at finding their weaknesses. The data collection method can be applied in a never-ending learning scenario, becoming a moving target for NLU, rather than a static benchmark that will quickly saturate.
VDPSOHU LQFXEDWRU IRU VWXG \ LQJ ] RRSODQNWRQ JUD ] LQJ DQG SK \ WRSODQNWRQ SURGXFWLRQ

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