Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative assessment of phytoremediation feasibility of water caltrop ( Trapa natans L . ) and water hyacinth ( Eichhornia crassipes Solms . ) using pulp and paper mill effluent

Application of aquatic macrophytes in phytoremediation of industrial effluent has become popular due to the high cost and energy intense treatment technologies (Sooknah and Wilkie, 2004; Padmapriya and Murugesan, 2012; Kumar and Chopra, 2016). Ever increasing human population, extensive industrialization and urbanization is continuously creating pressure on the water resources (Kumar and Chopra, 2013a, b; Rohit et al., 2015). Industries like pulp and paper mills consume a large amount of fresh water and generate huge quantity of wastewater which is varied in characteristics with higher inorganic, organic and biological pollution load (Kumar and Chopra, 2014, 2015). The treatments of industrial effluents are quietly expensive and time consuming (Kumar and Chopra, 2011, 2012). The industrial effluents contains various nutrients like nitrogen (N), phosphorus (P), sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), sulphate (SO4 ) and chlorides. Besides this the effluent also have heavy metals such as cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), nickel (Ni), lead (Pb) and zinc (Zn) (Dar et al., 2011; ORIGINAL RESEARCH ARTICLE
Trait structure reveals the processes underlying fish establishment in the Mediterranean

Aim Typically, non-indigenous species have been studied in relation to either the invaded (recipient) community or the donor community. However, we still lack a broad understanding of the mechanisms underlying the establishment of non-indigenous species that combines both perspectives. Since the opening of the Suez Canal, hundreds of species have invaded the Mediterranean from the Red Sea, forming a unique system in which the entire species pool (donor, non-indigenous and recipient) is known. Focusing on species ecological traits, we assess the drivers underlying the establishment of non-indigenous species from the onset of the invasion to the present. Location The Mediterranean and Red Seas. Methods We compiled traits for shallow-water hard-bottom-associated fishes in the Mediterranean (recipient community) and the Red Sea (donor community). We compared the multivariate community trait structure of non-indigenous species with the donor and recipient assemblages, using a novel method to objectively assign trait-weights, thereby increasing the robustness of the results. Patterns were contrasted with two types of null models which provide distinct insights into the ecological processes. Results Non-indigenous fishes are very diverse ecologically, substantially increasing the total community trait diversity of the Mediterranean. Trait similarity between non-indigenous and indigenous Mediterranean species was lower than expected, indicating that non-indigenous fishes tend to occupy relatively vacant niches within the Mediterranean. However, we further found that over time non-indigenous species display increased trait similarity to indigenous Mediterranean species. This suggests that trait constraints associated with successful establishment are weakening. Main conclusions Non-indigenous species establish in relatively vacant ecological niches, opening the possibility for predicting establishment using ecological traits. However, the weakening of trait constraints through time suggests that forecasting future establishment may be difficult. Faced with an accelerating pace of invasion, it appears that the Mediterranean is going to be transformed into an extension of the Red Sea in terms of trait and species composition.
An empirical study on human mobility and its agent-based modeling

This paper aims to analyze the GPS traces of 258 volunteers in order to obtain a better understanding of both the human mobility patterns and the mechanism. We report the regular and scaling properties of human mobility for several aspects, and importantly we identify its Levy flight characteristic, which is consistent with those from previous studies. We further assume two factors that may govern the Levy flight property: (1) the scaling and hierarchical properties of the purpose clusters which serve as the underlying spatial structure, and (2) the individual preferential behaviors. To verify the assumptions, we implement an agent-based model with the two factors, and the simulated results do indeed capture the same Levy flight pattern as is observed. In order to enable the model to reproduce more mobility patterns, we add to the model a third factor: the jumping factor, which is the probability that one person may cancel their regular mobility schedule and explore a random place. With this factor, our model can cover a relatively wide range of human mobility patterns with scaling exponent values from 1.55 to 2.05.
A DYNAMIC AND HUMAN-CENTRIC RESOURCE ALLOCATION FOR MANAGING BUSINESS PROCESS EXECUTION

Generally, resource allocation is essential to efficient the operational execution. More specifically, resource allocation for semi-automatic business processes might be more sophisticated due to human involvement. To this point, human performances are oscillating over time. Hence, upfront and static resource allocation might be suboptimal to deal with human dynamics. For this reason, this study suggests an on-the-fly and human centric resource allocation to manage human-type resources in semi-automatic business process. Here, we use Bayesian approaches to predict resource’s performances according to historical data set. As a result, we can construct a dynamic priority rule to assign an incoming job to a resource with the highest probability to work faster. Finally, we demonstrate that our approach outperforms other priority rules: Random, Lowest Idle, Highest Idle, Order, and previously developed Bayesian Selection Rule from the total completion time and waiting time point of view.
Long-term soil quality degradation along a cultivation chronosequence in western Kenya

Loss of agroecosystem soil functions due to soil quality (SQ) degradation impacts Africa’s agricultural viability and food security. Primary forest and farm fields deforested between 1930 and 2000 were sampled along a chronosequence on two parent materials in western Kenya. Two traditional long-term management systems were sampled: continuous low-input maize (Zea mays; Co), and kitchen garden (Ki) polyculture with organic inputs. Physical, biological, and chemical SQ indicators were measured. Degradation in Co followed exponential decay trends for most indicators (organic matter, active C, water-stable aggregates, available water capacity, electrical conductivity, CEC, pH, Ca, Mg and Zn), as well as for yield. Organic matter quality declined linearly, suggesting degradation will continue. For both parent materials and most indicators degradation of 25–93% below initial values resulted, but with ≤40% further drop below initial values and for more indicators under Co than Ki. P, Zn and possibly K accumulated over time under Ki. The extent of degradation was influenced by parent material. In conclusion, a basic accessible set of SQ indicators was successfully used to describe soil degradation dynamics under cultivation. Results suggest that regular organic inputs can significantly reduce degradation, especially of nutrient retention and soil structure, after forest conversion. © 2011 Elsevier B.V. All rights reserved.
Easy on the mind: how rankings influence attribute weights in multi-attribute decision tasks

This research examines two alternative mechanisms through which rankings may influence attribute weights. While the choice of sorting attribute may serve as a sign of relevance (conversational norms mechanism), consumers could also deduce importance from the ease of processing (comparison fluency mechanism). In four studies we provide evidence for the fluency mechanism. We demonstrate that rankings only influence the weight of less interpretable attributes (study 1). Moreover, the effect increases under a cognitive load manipulation (study 2) and decreases when interpretability is facilitated (study 3). Using eyemovement data, we show that ease of comparison mediates the sorting effect (study 4).
Changes in non protein thiols, some antioxidant enzymes activity and ultrastructural alteration in radish plant (Raphanus sativus L.) grown under lead toxicity.

Forty days old radish plants (Raphanus sativus L.) were exposed to different regimes of lead stress as Pb(NO3)2 at the following concentrations 0, 25, 50, 100, 150, 250 and 500 ppm. The possible generation of oxidative stress, antioxidant metabolism and changes in the chloroplast and cell membrane ultrastructure were investigated. Greater loss of the photosynthetic pigments (Chl. a, Chl. b and total carotenoids) were observed especially under 500 ppm lead (Pb). The accumulation of lead in roots and leaves of plant were measured and the results showed that lead accumulation increased with increasing of the metal treatment concentration. An increasing trend was observed in levels of ascorbate and decreasing trend in glutathione. Also, the antioxidant enzymes, viz., guaiacol peroxidase (GPX) ascorbate peroxidase (APX), catalase (CAT) and glutathione S-transferase (GST) showed significant variation with the increase in lead stress compared to control (untreated) plants. The rapid inducibility of some of these enzymes is useful early and sensitive indicators of heavy metal toxicity. Native polyacrylamide gel electrophoresis revealed an increase in the isoenzymes profile of CAT in both leaves and roots. While POD isoenzymes bands prominently increased in leaves and slightly decreased in roots at the higher Pb concentration in the growth media. The ultrastructural studies at selected concentrations; 100 and 500 ppm of Pb showed distortion of the structure and cell membranes in roots. Therefore, the changes in the levels of some antioxidants may play an important role against oxidative injury.
Nutritional Evaluation of Sweet Orange (Citrus sinensis) Fruit Peel as a Feed Resource in Broiler Production

A study was conducted with broiler chicks to evaluate the nutritional potential of Sweet orange fruit (Citrus sinensis) peel as a feed resource. Sweet orange peels were sun dried, milled and used as a dietary substitute for maize. Six experimental diets coded as M100P0, M90P10, M80P20, M70P30, M60P40 and M50P50 were compounded such that Sweet Orange Peel Meal (SOPM) substituted maize at levels of 0, 10, 20, 30, 40 and 50%, respectively in broiler starter and finisher diets. One hundred and eighty (180) day-old Anak titan chicks were randomly divided into six groups and one of each was allotted to a diet of three replicates. The birds which were raised in deep litter pens for sixty-three days were fed ad libitum and had access to fresh cool drinking water daily. Performance data: feed intake, water consumption, body weight, Body Weight Gain (BWG), Feed Conversion Ratio (FCR) were collected during the feeding trial and carcass evaluation was done at the termination of the trial. In both starter and finisher phases, the diets had no effect (p>0.05) on feed intake, water consumption, body BWG and FCR but had significant effect (p 0.05) among the dietary groups. The diets had no effect (p>0.05) on kidney, liver, heart, spleen, gall bladder and lung but had significant effect (p<0.01) on proventriculus and gizzard as the SOPM level increased. The organs were normal and there were no observable adverse effects on the health of broilers. SOPM can be a dietary substitute for maize up to 20% level in the diet for broiler.
Effect of Replacing Maize (Zea Mays L.) with Orange Fleshed Sweet Potato Tuber (Ipomoea Batatas) on Performance of Cobb 500 Broiler Chickens

Ethiopia is one of the few African countries with a large population of chicken which covers 60% of the population [1]. Poultry plays an important economic, nutritional and socio-cultural role in the livelihood of rural households in many developing countries, including Ethiopia. Many scholars are of the opinion that developing the poultry industry in the developing nations can be the fastest means of bridging the existing gap in protein deficiency [2,3]. The scarcity and prohibitive cost of commercial energy sources like maize and sorghum for poultry rations, has been the main cause of the high cost of poultry products especially in developing countries. This will subsequently lead to inhibition of the cost of production of poultry meat. According to the production data base [4], the total number of chickens for meat production in the world was 59.7 billion in 2012. Maize serves as the major energy ingredient in the diets of most livestock and especially non-ruminants like poultry. A decrease in the availability of maize and an increase in the price for feed have a direct impact on the broiler industry worldwide [5]. In order to step down the problem of high and unstable price situation and save the collapse of the poultry industry, there is the need to broaden the energy source base by assessing unconventional feedstuffs [6]. In order to compensate for this change, alternative feed ingredients must be identified [7]. The new ingredients must be able to substitute for maize totally or partially and not have a negative impact on the efficiency of broilers [8].
Towards a Deeper Understanding of TCP BBR Congestion Control

In 2016, Google published the bottleneck bandwidth and round-trip time (BBR) congestion control algorithm. Unlike established loss- or delay-based algorithms like CUBIC or Vegas, BBR claims to operate without creating packet loss or filling buffers. Because of these prospects and promising initial performance results, BBR has gained wide-spread attention. As such it has been subject to behavior and performance analysis, which confirmed the results, but also revealed critical flaws.Because BBR is still work in progress, measurement results have limited validity for the future. In this paper we present our publicly available framework for reproducible TCP measurements based on network emulation. In a case study, we analyze the TCP BBR algorithm, reproduce and confirm weaknesses of the current BBR implementation, and provide further insights. We also contribute an analysis of BBR’s inter-flow synchronization behavior, showing that it reaches fairness equilibrium for long lived flows.
Developing Self-Efficacy through a Massive Open Online Course on Study Skills

Self-efficacy is a strong predictor of academic performance, and an area of interest for higher education institutions. This paper reports on a massive open online course (MOOC) on study skills, aimed at increasing self-efficacy. Participants (n=32) were from Mexico and Colombia, with ages ranging from 21 to 45 years. At the beginning and the end of the MOOC, learners answered a survey that included the General Self-Efficacy Scale, items on specific study skills, and space for optional comments. Findings show statistically significant increases in general self-efficacy after completing the MOOC, as well as in the perceived self-efficacy related to five out of six study skills. Comments suggest that participants are aware of and value their own improvement. For students, MOOCs can represent low-risk, formative opportunities to widen their knowledge and increase their self-efficacy. For academic institutions, well-designed MOOCs on study skills provide a means to support students.
Changing attitudes: supporting teachers in effectively including students with emotional and behavioural difficulties in mainstream education

Pupils with emotional and behavioural difficulties (EBD) are often considered the most challenging group to manage within mainstream education. The challenges perceived by teachers may be due, in part, to negative attitudes towards this cohort of pupils, which may exacerbate feelings of inadequacy and impact negatively upon direct interactions with pupils. The current study comprised a combination of implicit (i.e. the Implicit Relational Assessment Procedure, IRAP) and explicit (The Opinions Relative to Mainstreaming Scale, ORMS) technologies to assess the attitudes of teachers (N = 25) and teachers in training (N = 20) towards pupils with EBD. When these attitudes proved to be negative (relative to typically developing pupils), the utility of a combined behaviour intervention (BI) and stress-management intervention (SMI), in conjunction with a series of pre and post measures, was examined. The IRAP results for teachers indicated that the SMI enhanced their implicit positivity towards pupils with EBD (EBD PUPIL) to a considerable extent (0.025-0.175), and this was greater than the impact recorded with the BI. The teachers in training showed implicit negativity towards EBD PUPIL (0.13) and this decreased, albeit marginally, at post-BI (0.05) and post-SMI (0.06). Significant differences were recorded in teachers’ general attitudes towards inclusion (p < 0.001) and efficacy (p < 0.008). Significant effects were recorded for teachers in training in relation to their attitudes towards having a child with EBD and having a previously excluded child with EBD in their classrooms (all ps < 0.001). For this latter group, reductions were also recorded in their levels of depression, anxiety and stress (p < 0.001) and there was an increase in their psychological flexibility (p < 0.001). The current results indicate that a range of positive implicit and explicit outcomes was associated with the current BI and SMI package in terms of fostering more effective inclusion of pupils with EBD in mainstream education.
Distributionally Robust Deep Learning as a Generalization of Adversarial Training

Machine learning models are vulnerable to adversarial attacks at test time: a correctly classiﬁed test example can be slightly perturbed to cause a misclassiﬁcation. Training models that are robust to these attacks, and theoretical understanding of such defenses are active research areas. Adversarial Training (AT) via robust optimization is a promising approach, where the model is trained against an adversary acting on the training set, but it is less clear how to reason about perturbations on the unseen test set. Distributionally Robust Optimization (DRO) with Wasserstein distance is an interesting theoretical tool for understanding robustness and generalization, but it has been limited algorithmically to simple models. We link DRO and AT both theoretically and algorithmically: AT is a special case of DRO, and in general DRO yields a stronger adversary. We also give an algorithm for DRO for neural networks that is no more expensive than AT.
Treating Resistance as Data in Qualitative Interviews

Abstract Scientific interviews provide a useful resource for qualitative researchers studying people’s perceptions on contemporary phenomena. This article contributes to the large body of literature on qualitative interviews by investigating a rather common but under-reported pattern in interviews, that of resistance. Resistance is a form of power that the participant maintains and can exercise at any moment. The phenomenon knows various expressions from a refusal on the side of the participant to sign the consent form to question dodging or embellished accounts. Two case studies are used to underpin the basic argument that resistance in interviews may be a valuable finding in itself if contextualized properly. Scientific interviews provide a useful resource for qualitative researchers studying people’s perceptions on contemporary phenomena. This article contributes to the large body of literature on qualitative interviews by investigating a rather common but under-reported pattern in interviews, that of resistance. Resistance is a form of power that the participant maintains and can exercise at any moment. The phenomenon knows various expressions from a refusal on the side of the participant to sign the consent form to question dodging or embellished accounts. Two case studies are used to underpin the basic argument that resistance in interviews may be a valuable finding in itself if contextualized properly.
Revisiting LSTM Networks for Semi-Supervised Text Classification via Mixed Objective Function

In this paper, we study bidirectional LSTM network for the task of text classification using both supervised and semisupervised approaches. Several prior works have suggested that either complex pretraining schemes using unsupervised methods such as language modeling (Dai and Le 2015; Miyato, Dai, and Goodfellow 2016) or complicated models (Johnson and Zhang 2017) are necessary to achieve a high classification accuracy. However, we develop a training strategy that allows even a simple BiLSTM model, when trained with cross-entropy loss, to achieve competitive results compared with more complex approaches. Furthermore, in addition to cross-entropy loss, by using a combination of entropy minimization, adversarial, and virtual adversarial losses for both labeled and unlabeled data, we report state-of-theart results for text classification task on several benchmark datasets. In particular, on the ACL-IMDB sentiment analysis and AG-News topic classification datasets, our method outperforms current approaches by a substantial margin. We also show the generality of the mixed objective function by improving the performance on relation extraction task.1
Identification of Gender of the Author of a Written Text using Topic-Independent Features

Authorship profiling, which is the process of extraction of information about a text’s author through linguistics analysis, is now gaining momentum as an interdisciplinary subject. Scholars who employ this technique (i.e. data analysis specialists, linguists, psychologists) study the identification of demographics, personality traits, education and the native language of authors of texts, among others. Gender, in this context, is the most popular variable. Some studies report accuracy as high as 80% or even higher in identifying the gender of a text’s author. However, there are still many issues that must be addressed. Firstly, most of the previous research concerns English texts. Secondly, most of the papers focus on content-based features, which are obviously easily to imitate. Thirdly, many recent papers in the field make use of machine-learning algorithms with emphasis on accuracy, not on the differences between male and female writing. The objective of this paper is to reveal differences in male and female Russian written texts and to design a mathematical model to identify the gender of authors of texts using only high-frequency topic-independent text parameters. Special emphasis is made on comparing the obtained data on the differences in male and female written texts with those previously obtained for Russian and other languages. An original mathematical solution for identification of author’s gender is set forth.
Impact of parenting style on children’s academic achievement

The purpose of the present study was to explore the impact of parenting style on children’s academic performance. In order to achieve this, 110 students whose age ranging between 20 and 22 years were taken as sample, among them 55 were male and 50 were female. The Bangla translated version of Parental Acceptance Rejection Questionnaire (PARQ) was used for data collection. Pearson product moment correlation was carried out to see the relations of PARQ-M and PARQ-F with academic performance of children. Correlation analysis indicated that academic result has positive correlation with authoritative parenting style for both parents (Mother, r=. 790** p<0.01