Miracle-dz/UniFAR-FTUs huggingface dataset:
CONVERGENT READINGS OF GROUNDWATER GOVERNANCE? ENGAGING EXCHANGES BETWEEN DIFFERENT RESEARCH PERSPECTIVES

In the last 50 years, the study of groundwater governance has given rise to rich and differentiated analytical approaches. This article proposes an exchange between the main heuristic viewpoints, results and theses of three approaches which studied groundwater governance: the study of groundwater governance as collective action initiated by Ostrom, the analysis made by Shah on informal groundwater economies and the works of Prakash, Mukherji and Birkenholtz drawing on political ecology. The aquifers on which each approach originally built its analysis played a key role in the design of analytical frameworks which, in the case of the first two approaches, were later applied to a much larger set of cases. The three approaches share many commonalities in their heuristic methods. However, they differ in the content of governance systems recommended to achieve sustainable groundwater use, and especially in the benefits of involving water users in the implementation of governance. Therefore, they also differ on what should be the focus of academic analyses. It is thus of interest to organize joint readings of cases of groundwater governance and to discuss the contents of research programmes able to provide fruitful analyses of these cases, based on local specificities. Copyright © 2012 John Wiley & Sons, Ltd.
Improving classification using preprocessing and machine learning algorithms on NSL-KDD dataset

Classification is the category that consists of identification of class labels of records that are typically described by set of features in dataset. The paper describes a system that uses a set of data pre-processing activities which includes Feature Selection and Discretization. Feature selection and dimension reduction are common data mining approaches in large datasets. Here the high data dimensionality of the dataset due to its large feature set poses a significant challenge. In Pre-processing with the help of Feature selection algorithm the various required features are selected, these activities helps to improve the accuracy of the classifier. After this step various classifiers are used such as Naive Bayes, Hidden Naive Bayes and NBTree. The advantage of Hidden Naive Bayes is a data mining model that relaxes the Naive Bayes Method's conditional Independence assumption. Also the next Classifier used is NBTree which induces a hybrid of decision tree classifiers and Naïve Bayes classifiers which significantly improves the accuracy of classifier and decreases the Error rate of the classifier. The output of the proposed method are checked for True positive, True negative, False positive, False negative. Based on these values the Accuracy and error rate of each classifier is computed.
Automatic Testing of Natural User Interfaces

Automated test generation can effectively explore programs through their programmer interfaces and traditional graphical user interfaces, but the recent advent of natural user interfaces (NUI) based on motion and gesture detection, for example the Microsoft Kinect, has outrun software testing research. This leaves a rapidly growing domain of software ranging from entertainment to medical applications without suitable test automation techniques. To address this issue, we propose a technique that automatically tests Kinect-based applications by synthesising realistic sequences of skeletal movement. The novel test cases are generated by a statistical model, which is trained on a corpus of common gestures. Evaluation on a gesture-controlled Kinect web browser application demonstrates that our approach achieves significantly higher code coverage than random test inputs.
Re: Polymicrogyria versus pachygyria in 22q11 microdeletion

Barkovich et al. (2001) published an update in the classification system for malformations of cortical development. Malformations in the lissencephaly/pachygyria spectrum are considered to be etiologically related and due to abnormal neuronal migration. On MRI an abnormally thick cortex and an absence or reduction of the number of gyri and sulci characterize these malformations. Mutations in several genes such asLIS1,DCX, andRELN have been shown to cause brain malformations in this spectrum with variable severity. Polymicrogyria is classified with schizencephaly into another group, as it is considered due to abnormal cortical organization in a later stage of gestation. MRI shows an abnormal cortex with an unusually large number of small gyri, generalized or patchy. There seems to be a predilection for the perisylvian region. The compaction of small gyri can be difficult to distinguish from a smoother thicker cortex especially on CT or sub-optimal quality MRI. In the recent article by Koolen et al. [2004] in this journal, and also a previous article byEhara et al. [2003], a patientwith a 22q11 deletion is described with a cortical brain malformation. In the text of both articles, the MRI images are described as pachygyria and polymicrogyria. The published images, however, show a clear polymicrogyria consistent with earlier reports of brain malformation in 22q11 deletion syndrome [Sztriha et al., 2004]. Possibly other images that do show a pachygyria have not been published or it is indeed a case of misclassification. We would like to stress the importance of correct classification, as this is both important for the search for the underlying mechanism and for correct patient care. Testing for 22q11 deletion should be considered in all the patients with polymicrogyria, whereas this is not indicated in the patients with pachygyria. REFERENCES
The Effects of the Arts IMPACT Curriculum Upon Student Performance on the Ohio Fourth-Grade Proficiency Test

This study investigated the effects of a comprehensive arts curriculum (Arts IMPACT) in two schools in Columbus, Ohio upon students? scores on the Ohio Fourth-Grade Proficiency Test. In the Arts IMPACT program students receive weekly arts instruction with specialists in art, music, drama and dance. The arts team works with classroom teachers in planning experiences, which infuse and integrate the arts into the curriculum in order to reinforce learning in other academics and the arts. To exercise some control over variables known from previous research to affect academic achievement, two schools with similar demographics to the Arts IMPACT schools (family income, school size and racial composition) were chosen for comparison. Results indicated that the Arts IMPACT schools scored significantly higher (p < .05) on Math, Science and Citizenship subtests. No significant differences were found on Reading and Writing subtests. Higher income students performed significantly better (p < .05) than low-income students regardless of curriculum. It was concluded that the intense arts instruction has either a positive effect upon student achievement or no adverse effect.
Electrical Stimulation of Broca's Area Enhances Implicit Learning of an Artificial Grammar

Artificial grammar learning constitutes a well-established model for the acquisition of grammatical knowledge in a natural setting. Previous neuroimaging studies demonstrated that Broca's area (left BA 44/45) is similarly activated by natural syntactic processing and artificial grammar learning. The current study was conducted to investigate the causal relationship between Broca's area and learning of an artificial grammar by means of transcranial direct current stimulation (tDCS). Thirty-eight healthy subjects participated in a between-subject design, with either anodal tDCS (20 min, 1 mA) or sham stimulation, over Broca's area during the acquisition of an artificial grammar. Performance during the acquisition phase, presented as a working memory task, was comparable between groups. In the subsequent classification task, detecting syntactic violations, and specifically, those where no cues to superficial similarity were available, improved significantly after anodal tDCS, resulting in an overall better performance. A control experiment where 10 subjects received anodal tDCS over an area unrelated to artificial grammar learning further supported the specificity of these effects to Broca's area. We conclude that Broca's area is specifically involved in rule-based knowledge, and here, in an improved ability to detect syntactic violations. The results cannot be explained by better tDCS-induced working memory performance during the acquisition phase. This is the first study that demonstrates that tDCS may facilitate acquisition of grammatical knowledge, a finding of potential interest for rehabilitation of aphasia.
Depressive symptoms among rural Bangladeshi mothers: implications for infant development.

OBJECTIVE To examine how maternal depressive symptoms are related to infant development among low-income infants in rural Bangladesh and to examine how the relationship is affected by maternal perceptions of infant irritability and observations of caregiving practices. METHODS Development was measured among 221 infants at 6 and 12 months with the Bayley Scales II. Mothers reported on their depressive symptoms and on perceptions of their infant's temperament, and a home visit was made to complete the HOME Inventory. RESULTS Half (52%) the mothers reported depressive symptoms. In bivariate analyses, maternal depressive symptoms were related to low scores on the Bayley Scales. Infants whose mothers reported depressive symptoms and perceived their infants to be irritable acquired fewer cognitive, motor, and Orientation/Engagement skills between 6-12 months than infants whose mothers reported neither or only one condition. The relationship linking maternal depressive symptoms and perceived infant irritability with infant cognitive skills was partially mediated by parental responsiveness and opportunities for play in the home. CONCLUSIONS The intergenerational risks of maternal depressive symptoms on infant development extend to rural Bangladesh and are accentuated when mothers perceive their infants as irritable. Mothers who report depressive symptoms and infant irritability may lack the capacity to provide responsive, developmentally-oriented caregiving environments.
GraphSC: Parallel Secure Computation Made Easy

We propose introducing modern parallel programming paradigms to secure computation, enabling their secure execution on large datasets. To address this challenge, we present Graph SC, a framework that (i) provides a programming paradigm that allows non-cryptography experts to write secure code, (ii) brings parallelism to such secure implementations, and (iii) meets the need for obliviousness, thereby not leaking any private information. Using Graph SC, developers can efficiently implement an oblivious version of graph-based algorithms (including sophisticated data mining and machine learning algorithms) that execute in parallel with minimal communication overhead. Importantly, our secure version of graph-based algorithms incurs a small logarithmic overhead in comparison with the non-secure parallel version. We build Graph SC and demonstrate, using several algorithms as examples, that secure computation can be brought into the realm of practicality for big data analysis. Our secure matrix factorization implementation can process 1 million ratings in 13 hours, which is a multiple order-of-magnitude improvement over the only other existing attempt, which requires 3 hours to process 16K ratings.
Portraits of Julius Caesar: a proposal for 3D analysis

Here I suggest the use of a 3D scanning and rendering to create some virtual copies of ancient artifacts to study and compare them. In particular, this approach could be interesting for some roman marble busts, two of which are portraits of Julius Caesar, and the third is a realistic portrait of a man recently found at Arles, France. The comparison of some images indicates that a three-dimensional visualization is necessary.
Effect of temperature on the morphological characteristics of Botrytis cinerea and its correlated with the genetic variability

Botrytis cinerea (B. cinerea) Pers. Fr. [teleomorph Botryo t in ia fucke l iana (de Bary ) Whetze l ] i s a phytopathogenic fungi responsible for grey mould, which is an important disease in more than 200 species of fruits, vegetables, ornamental crops and affecting a great number of organs[1]. Grey mould, cause important economic losses before and after the harvest[2], worldwide losses from this fungus account for 20% of the harvest of the affected crops, and the cost is estimated at 10-100 billion euros per year. The market size for anti-Botrytis products has been 15-25 million US dollars in recent 3 years[3]. An important biological feature is that the process of infection and growth by B. cinerea is often associated with prior colonization of dead or dying plant debris as a nutrientPEER REVIEW ABSTRACT
Assessing Student Motivation to Participate in FFA Career Development Events

JONES, ALBERT DIXON. Assessing Student Motivation to Participate in FFA Career Development Events. (Under direction of Dr. Barry Croom). Career Development Events (CDE’s) have traditionally been a large part of the FFA program. The benefits FFA members receive from participating in Career development events have been documented in research, however little research has been conducted concerning the motivation of students to participate in career development events. This study examined the intrinsic motivation, extrinsic motivation, and amotivation of students regarding career development events, as well as to determine how students are recruited to participate in them. An adaptation of the Academic Motivation Scale, translated by Vallerand, et. al. (1992) was utilized to assess students’ level of intrinsic motivation, extrinsic motivation, and amotivation with regard to career development event participation. This was combined with researcher-generated items to determine the individual(s) most responsible for students’ decision to participate in career development events. The population for this study included high school FFA members in the Southeast FFA Region of North Carolina who had participated in career development events. Data were collected using paper-based questionnaires. A classroom set of questionnaires was sent to each high school agricultural education teacher in the Southeast Region, who was asked to administer the questionnaire to one of their classes. A total of 408 questionnaires from 26 teachers were completed, which represented 52 percent of all high school agricultural education teachers in the Southeast Region. Descriptive statistics were used to analyze the responses on the questionnaires. High school seniors represented the largest percentage of respondents by grade level. Male students comprised 67% of the total respondents, 67% of FFA membership, and 53% of the career development event participants. Only 21% of all the respondents reported that they had been in at least one career development event. The career development event with the largest number of participants was the Agricultural Tools and Materials career development event. Statistical analysis revealed that students reported high levels of intrinsic motivation to participate in career development events. The means for the statements related to extrinsic motivation were also high. In particular, students agreed strongest with the statement that career development event participation would be helpful in finding a job later on. Students also indicated agreement with the idea that career development event participation would improve one’s chances of entering the job market in a desired field, having a more prestigious job later on, as well as a higher paying job. Students disagreed with the statements related to amotivation. Students also indicated that the FFA advisor plays a key role in recruiting students to participate in career development events, and that they understood that career development event participation was a way to become involved and
TRX-E-002-1 Induces c-Jun–Dependent Apoptosis in Ovarian Cancer Stem Cells and Prevents Recurrence In Vivo

Chemoresistance is a major hurdle in the management of patients with epithelial ovarian cancer and is responsible for its high mortality. Studies have shown that chemoresistance is due to the presence of a subgroup of cancer cells with stemness properties and a high capacity for tumor repair. We have developed a library of super-benzopyran analogues to generate potent compounds that can induce cell death in chemoresistant cancer stem cells. TRX-E-002-1 is identified as the most potent analogue and can induce cell death in all chemoresistant CD44+/MyD88+ ovarian cancer stem cells tested (IC50 = 50 nmol/L). TRX-E-002-1 is also potent against spheroid cultures formed from cancer stem cells, chemosensitive CD44−/MyD88− ovarian cancer cells, and heterogeneous cultures of ovarian cancer cells. Cell death was associated with the phosphorylation and increased levels of c-Jun and induction of caspases. In vivo, TRX-E-002-1 given as daily intraperitoneal monotherapy at 100 mg/kg significantly decreased intraperitoneal tumor burden compared with vehicle control. When given in combination with cisplatin, animals receiving the combination of cisplatin and TRX-E-002-1 showed decreased tumor burden compared with each monotherapy. Finally, TRX-E-002-1 given as maintenance treatment after paclitaxel significantly delayed disease recurrence. Our results suggest that TRX-E-002-1 may fill the current need for better therapeutic options in the control and management of recurrent ovarian cancer and may help improve patient survival. Mol Cancer Ther; 15(6); 1279–90. ©2016 AACR.
Learning Words in Context: An ERP Investigation of Word Experience Effects on Familiarity and Meaning Acquisition

Using an instance-based approach to word learning (Reichle & Perfetti, 2003), two experiments tested the general hypothesis that differences in word experience give rise to encoded memories of words that differ in strength and quality, and that these differences affect meaning acquisition and subsequent word processing. Adult learners were exposed to rare unknown words in contexts that differed by type (definition or sentence context), variability (varied or repeated content), and semantic constraint (high or low) in an incidental word learning paradigm. Words were learned over the exposure of four learning trials that was followed by a testing phase during which ERPs were recorded. Of interest were the FN400, P600, and N400 components, which are neural signatures of familiarity, recollection, and meaning acquisition, respectively. Learners completed three tasks (semantic judgment, sentence judgment, and definition generation) that measured their acquisition of definitional and contextual meaning knowledge. For Experiment 1, the type of context and variability of content were manipulated. Our results showed FN400 effects for definition conditions, and N400 effects for varied context conditions, indicating differential effects of word experience for familiarity and meaning acquisition. For Experiment 2, the semantic constraint and the variability of single-sentence contexts were manipulated. Familiarity effects as indexed by the FN400 indicated an effect for repetition; words learned in repeated contexts of high or low semantic constraint showed increased familiarity, whereas no familiarity effects were found for varied content conditions. Differences in N400 effects were found for contextual-related decisions; larger N400 effects were found for varied content conditions that facilitated the acquisition of the contextual knowledge of the word. Correlations with ERP effects, behavioral measures, and individual difference measures showed that the acquisition of meaning knowledge is related to vocabulary, comprehension, and lexical skill. These results suggest that different word experiences have differential effects on word familiarity and meaning acquisition, and that these differences can be interpreted in terms of the strength, quantity, and availability of the encoded memory traces for those word experiences.
Conducting Probabilistic Sensitivity Analysis for Decision Models Based on Markov Chains

Models based on Markov chains are used for decision-making studies in many application domains; however , there are no widely adopted methods for performing sensitivity analysis on the associated transition probability matrices (TPMs). This article describes two simulation-based approaches for probabilistic sensitivity analysis of a given finite-state, finite-horizon, discrete-time Markov chain with a stationary TPM and an uncertainty set within which the chain's TPM may vary according to an appropriate probability distribution. Both approaches sample each row of the TPM independently. The first approach assumes no prior knowledge of the TPM's distribution, and each row is sampled uniformly over its uncertainty set. The second approach involves random sampling from the (truncated) multivariate normal distribution of the TPM's maximum likelihood estimator subject to the condition that each row has nonnega-tive elements, and sums to one. The proposed methods are easy to implement and have reasonable computation times. As an illustrative example, these two methods are applied to a medical decision-making problem involving the evaluation of treatment guidelines for glycemic control of patients with type 2 diabetes in which the natural variation in glycated hemoglobin (HbA1c) is modeled as a Markov chain.
One-step solvothermal synthesis of Fe3O4@C core–shell nanoparticles with tunable sizes

We report the synthesis of Fe3O4@C core–shell nanoparticles (FCNPs) by using a facile one-step solvothermal method. The FCNPs consisted of Fe3O4 particles as the cores and amorphous uniform carbon shells. The content of Fe3O4 is up to 81.6 wt%. These core–shell nanoparticles are aggregated by primary nanocrystals with a size of 10–12 nm. The FCNPs possess a hollow interior, high magnetization, excellent absorption properties and abundant surface hydroxyl groups. A possible growth mechanism of the FCNPs is proposed. The role of glucose in regulating the grain size and morphology of the particles is discussed. The absorption properties of the FCNPs towards Cr(VI) in aqueous solution is investigated. We demonstrate that the FCNPs can effectively remove more than 90 wt% of Cr(VI) from aqueous solution.
Heat Shock Protein 70 in Alzheimer's Disease

Alzheimer's disease (AD) is the most common neurodegenerative disease that caused dementia which has no effective treatment. Growing evidence has demonstrated that AD is a “protein misfolding disorder” that exhibits common features of misfolded, aggregation-prone proteins and selective cell loss in the mature nervous system. Heat shock protein 70 (HSP70) attracts extensive attention worldwide, because it plays a crucial role in preventing protein misfolding and inhibiting aggregation and represents a class of proteins potentially involved in AD pathogenesis. Numerous studies have indicated that HSP70 could suppress the progression of AD with in vitro and in vivo experiments. Thus, targeting HSP70 and the related compounds might represent a promising strategy for the treatment of AD.