Miracle-dz/UniFAR-FTUs huggingface dataset:
Food, state power, and rebellion: The case of maize

ABSTRACT Why do rebellions occur and persist in some countries but not in others? Evidence shows that natural resources affect the fighting capacity of rebel groups; yet, by focusing on lucrative resources that are rare in most rebellion-afflicted countries, such as oil and diamonds, scholars neglected one necessary input for rebellion: staple crops. Focusing on maize, the world’s most prevalent staple, this study argues that, as one of the most important resources for rebel groups, maize can have a destabilizing effect on the state’s ability to thwart rebellion. These claims are corroborated statistically on a new time-varying, high-resolution global dataset of staple crop productivity, and then qualitatively through an analysis of archival records on the Mau Mau rebellion. In identifying an overlooked, global linkage between agricultural abundance, state capacity, and intrastate violence, this study explains strong geographical and temporal variations in rebellions at both the subnational and global levels.
Cytotoxic responses to 405 nm light exposure in mammalian and bacterial cells : Involvement of reactive oxygen species

Article history: Received 12 June 2015 Received in revised form 12 February 2016 Accepted 17 February 2016 Available online 23 February 2016 Light at wavelength 405 nm is an effective bactericide. Previous studies showed that exposing mammalian cells to 405 nm light at 36 J/cm (a bactericidal dose) had no significant effect on normal cell function, although at higher doses (54 J/cm), mammalian cell death became evident. This research demonstrates that mammalian and bacterial cell toxicity induced by 405 nm light exposure is accompanied by reactive oxygen species production, as detected by generation of fluorescence from 6-carboxy-2′,7′-dichlorodihydrofluorescein diacetate. As indicators of the resulting oxidative stress in mammalian cells, a decrease in intracellular reduced glutathione content and a corresponding increase in the efflux of oxidised glutathione were observed from 405 nm light treated cells. Themammalian cells were significantly protected fromdying at 54 J/cm in the presence of catalase, which detoxifiesH2O2. Bacterial cells were significantly protected by sodiumpyruvate (H2O2 scavenger) and by a combination of free radical scavengers (sodium pyruvate, dimethyl thiourea (•OH scavenger) and catalase) at 162 and 324 J/cm. Results therefore suggested that the cytotoxic mechanism of 405 nm light in mammalian cells and bacteria could be oxidative stress involving predominantly H2O2 generation, with other ROS contributing to the damage. © 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Performance Analysis of Classification Methods and Alternative Linear Programming Integrated with Fuzzy Delphi Feature Selection

Among various statistical and data mining discriminant analysis proposed so far for group classification, linear programming discriminant analysis have recently attracted the researchers' interest. This study evaluates multi-group discriminant linear programming (MDLP) for classification problems against well-known methods such as neural networks, support vector machine, and so on. MDLP is less complex compared to other methods and does not suffer from local optima. However, sometimes classification becomes infeasible due to insufficient data in databases such as in the case of an Internet Service Provider (ISP) small and medium-sized market considered in this research. This study proposes a fuzzy Delphi method to select and gather required data. The results show that the performance of MDLP is better than other methods with respect to correct classification, at least for small and medium-sized datasets.
Carotid thickness and atherosclerotic plaque stability, serum inflammation, serum MMP-2 and MMP-9 were associated with acute cerebral infarction

Correlations of carotid intima-media thickness (IMT), atherosclerotic plaque stability, serum inflammatory factors and serum matrix metalloproteinase (MMP)-2 and MMP-9 levels with the condition of disease in patients with acute cerebral infarction were analyzed to explore the predictive value of these risk factors. A total of 56 patients diagnosed with acute cerebral infarction in Jingmen First People's Hospital from February 2016 to January 2017 were selected and divided into the plaque stability group (n=25) and plaque instability group (n=31). Our results showed that the level of total cholesterol (TC) in the plaque instability group was significantly higher than that in the plaque stability group (P<0.05). IMT and National Institutes of Health Stroke Scale (NIHSS) score in the plaque instability group were significantly higher than those in the plaque stability group, but eccentricity index (EI) and Barthel index were significantly lower than those in the plaque stability group (P<0.05). The serum C-reactive protein (CRP), tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) levels in the plaque instability group were significantly higher than those in the plaque stability group (P<0.05). The levels of serum MMP-2 and MMP-9 in the plaque instability group were significantly higher than those in the plaque stability group (P<0.05). Barthel index was correlated with IMT (r=−0.693, P<0.01), MMP-2 (r=−0.605, P<0.01), CRP (r=−0.765, P<0.01) and EI (r=0.811, P<0.01), respectively. Hemoglobin A1c (HbA1c), TC, systolic blood pressure, coronary heart disease, diabetes mellitus, IMT, EI, CRP, TNF-α, IL-6, MMP-2 and MMP-9 had independent predictive values for acute cerebral infarction (P<0.05). Carotid IMT, stability of the atherosclerotic plaque, serum inflammation, serum MMP-2 and MMP-9 levels have close correlations with acute cerebral infarction. The larger the carotid IMT is, the more unstable the plaque is and the higher the levels of serum inflammatory factors, MMP-2 and MMP-9 are, the greater the risk of acute cerebral infarction will be.
Habitat Scale Mapping of Fisheries Ecosystem Service Values in Estuaries

Little is known about the variability of ecosystem service values at spatial scales most relevant to local decision makers. Competing definitions of ecosystem services, the paucity of ecological and economic information, and the lack of standardization in methodology are major obstacles to applying the ecosystem-services approach at the estuary scale. We present a standardized method that combines habitat maps and habitat-faunal associations to estimate ecosystem service values for recreational and commercial fisheries in estuaries. Three case studies in estuaries on the U.S. west coast (Yaquina Bay, Oregon), east coast (Lagoon Pond, Massachusetts), and the Gulf of Mexico (Weeks Bay, Alabama) are presented to illustrate our method's rigor and limitations using available data. The resulting spatially explicit maps of fisheries ecosystem service values show within and between estuary variations in the value of estuarine habitat types that can be used to make better informed resource-management decisions.
Villanueva EMPLOYMENT RISK AND HOUSEHOLD FORMATION : EVIDENCE FROM DIF F ERENCES IN FIRING COSTS 2007

The rate of new household formation among young adults who live with their parents has decreased in the last twenty years, specially in Southern Europe. At the same time, exposure to the risk that a young adult loses his or her job has increased. We use differences in firing costs across contract types in the Spanish labor market to identify if there is a causal link between both developments. Our first identification strategy exploits a legally-induced sharp increase in firing costs 3 years after the starting of a fixed-term contract between 1987 and 1996. The second uses variation in regional incentives to promote high-firing cost contracts between 1997 and 2001. Both strategies fail to detect a causal impact of job insecurity on the probability of forming a new household. Tentative evidence supports the notion that lower job insecurity has an impact on the form of tenure of the first house of residence, favoring home-ownership over renting.
Analysis of Growth Behavior of a Cellular and Dendritic Interface under a Constrained Growth Condition using a Phase-Field Model

A phase-field simulation was carried out to investigate the growth behavior of a cellular and dendritic interface of an Fe–C binary alloy in a constrained growth condition. The simulated results were in good agreement with the experimental results. The effect of the magnitude of anisotropy at solid/liquid interface energy was examined, and it was found that the magnitude of anisotropy affected the growth direction when the growth rate was low. Dimensionless growth direction, � 0 , was used to examine the obtained results, and it was found that � 0 increases from zero and approaches unity with increase in growth velocity. A good correlation was obtained between calculated growth velocity and growth direction by using dimensionless growth velocity (V=Vc), and this correlation was in agreement with the experimental results.
Depression in the Elderly: Limits and Challenges - A Nursing Perspective

Introduction: There are many difficulties encountered when diagnosing depression in its early stages in the elderly. The role of the GP is vital for prompt diagnosis. Aim: The aim of this paper is to provide a critical citation and discussion of the issues involved when diagnosing depression of the elderly in the community. Method: For this purpose, a systematic literature review of Greek and international databases were performed seeking references on the obstacles encountered when diagnosing depression. Results: Analysis revealed four major themes under which the papers fell: i) General difficulties in diagnosing depression, ii) The limitations GPs have when they diagnose depression, iii) The limits patients place on GPs during the diagnostic procedure and iv) The limits GPs and patients set on each other when depression is being considered Conclusions: The findings show that GPs are confronted with numerous detractors which may lead to misdiagnosis especially when depression is mild or moderate. Yet, early recognition can lead to effective treatment. It is suggested that nurses treating hospitalised patients be alerted to the early warning signs of depression in their patients. In order to support GPs and to make things easier for the patient, nurses should be encouraged to use their observation skills during their greater exposure time with the patient and to advise the patient to discuss these with their GP once discharged so that effective treatment can be initiated if
Antimicrobial activity of fig (Ficus carica Linn.) leaf extract as compared with latex extract against selected bacteria and fungi

Ethanolic leaf extract and latex of fig (Ficus carica L.) were investigated for their antimicrobial activity against six bacterial strains, two gram positive (Staphylococcus aureus, Streptococcus pyogenes) and four gram negative (Klebsiella pneumonae, Pseudomonas aeruginosa, Salmonella typhi, Escherichia coli), and three fungal strains (Candida albicans, Fusarium oxysporum, Aspergillus nigar), using agar well diffusion method for determination of inhibitory zone diameters (IZD). The detection of some active compounds was carried out by chemical methods. The results obtained showed that the extracts of fig contain; flavonoids, tannins, terpenes and steroids, alkaloids and saponins. The ethanolic extract of leaves exhibited strong activity against the bacteria Staph. aureus and Salm. typhi (13 mm, 14 mm IZD),and the fungi Fusarium oxysporum (16 mm IZD), whereas The latex showed higher activity against these bacteria (15 mm IZD) for each of them, and the fungi Aspergillus nigar (18 mm IZD). Kleb. pneumonae and E. coli seemed to be resistant to both extract which showed (8 mm, 9 mm) and (11 mm, 10 mm IZD) with ethanolic extract and latex respectively. This study was indicated that fig leaf and latex extracts have antimicrobial activity against some pathogenic infections.
Heuristics for the single machine scheduling problem with early and quadratic tardy penalties

This paper considers the single machine scheduling problem with linear earliness and quadratic tardiness costs, and no machine idle time. Several dispatching heuristics are proposed, and their performance is analysed on a wide range of instances. The heuristics include simple scheduling rules, as well as a procedure that takes advantage of the strengths of these rules. Linear early/quadratic tardy dispatching rules are also considered, as well as a greedy-type procedure. Extensive experiments are performed to determine appropriate values for the parameters required by some of the heuristics. The computational tests show that the best results are given by the linear early/quadratic tardy dispatching rule. This procedure is also quite efficient, and can quickly solve even very large instances. [Received 15 December 2006; Revised 20 July 2007; Accepted 24 July 2007]
Focus on Implantation Animal models of implantation

Implantation is an intricately timed event necessary in the process of viviparous birth that allows mammals to nourish and protect their young during early development. Human implantation begins when the blastocyst both assumes a ﬁxed position in the uterus and establishes a more intimate relationship with the endometrium. Due to the impracticalities of studying implantation in humans, animal models are necessary to decipher the molecular and mechanical events of this process. This review will discuss the differences in implantation between different animal models and describe how these differences can be utilized to investigate discrete implantation stages. In addition, factors that have been shown to be involved in implantation in the human and other various animal models including growth factors, cytokines, modulators of cell adhesion, and developmental factors will be discussed, and examples from each will be given.
Guest Editorial, part of a Special Feature on Strengthening adaptive capacity Powerless Spectators, Coping Actors, and Adaptive Co-managers: a Synthesis of the Role of Communities in Ecosystem Management

We provide a synthesis of the papers in the Special Issue, the Communities Ecosystems and Livelihoods component of the Millennium Ecosystem Assessment (MA), and other recent publications on the adaptive capacity of communities and their role in ecosystem management. Communities adapt because they face enormous challenges due to policies, conflicts, demographic factors, ecological change, and changes in their livelihood options, but the appropriateness of their responses varies. Based on our synthesis, three broad categories of adaptive communities are identified. "Powerless spectator" communities have a low adaptive capacity and weak capacity to govern, do not have financial or technological options, and lack natural resources, skills, institutions, and networks. "Coping actor" communities have the capacity to adapt, but are not managing social-ecological systems. They lack the capacity for governance because of lack of leadership, of vision, and of motivation, and their responses are typically short term. "Adaptive manager" communities have both adaptive capacity and governance capacity to sustain and internalize this adaptation. They invest in the long-term management of ecosystem services. Such communities are not only aware of the threats, but also take appropriate action for long-term sustainability. Adaptive co- management becomes possible through leadership and vision, the formation of knowledge networks, the existence or development of polycentric institutions, the establishment and maintenance of links between culture and management, the existence of enabling policies, and high levels of motivation in all role players. Adaptive co-managers are empowered, but empowerment is a consequence of the capacity for governance and the capacity to adapt, rather than a starting point. Communities that are able to enhance their adaptive capacity can deal with challenges such as conflicts, make difficult trade-offs between their short- and long- term well-being, and implement rules for ecosystem management. This improves the capacity of the ecosystem to continue providing services.
Ullah, Amjad and Li, Jingpeng and Hussain, Amir and Yang, Erfu (2016) Towards a biologically Inspired soft switching approach for cloud

Cloud elasticity augments applications to dynamically adapt to changes in demand by acquiring or releasing computational resources on the fly. In the past, we developed a framework for cloud elasticity utilizing multiple feedback controllers simultaneously. Each controller determines the scaling action with different intensity, whereby the selection of a suitable controller is realized with a fuzzy inference system. In this paper, we aim to identify the similarities between cloud elasticity and action selection mechanism in animals. We treat each controller of our previous framework as an action and propose a novel bio-inspired, soft switching approach. This approach integrates basal ganglia computational model as an action selection mechanism. Initial experimental results are presented, which demonstrate that the basal ganglia based approach has higher potential to improve the overall system performance and stability. A. Ullah Divisions of Computer science and Maths, University of Stirling, UK E-mail: aul@cs.stir. ac.uk J. Li Divisions of Computer science and Maths, University of Stirling, UK E-mail: jli@cs.stir. ac.uk A. Hussain Divisions of Computer science and Maths, University of Stirling, UK E-mail: ahu@cs.stir. ac.uk E. Yang Department of Design, Manufacture and Engineering Management, University of Strathclyde, UK E-mail: erfu.yang@strath.ac.uk
Navigation of Quantum-Controlled Mobile Robots

The actions of autonomous mobile robots in stochastic medium imply certain intellectual behavior, which allows fulfilling the mission in spite of the environmental uncertainty and the robot’s influence on the characteristics of the medium. To provide such a behavior, the controllers of the robots are considered as probabilistic automata with decision-making and, in some cases, learning abilities. General studies in this direction began in the 1960s (Fu & Li, 1969; Tsetlin, 1973) and resulted in practical methods of on-line decision-making and navigation of mobile robots (Unsal, 1998; Kagan & Ben-Gal, 2008). Along with the indicated studies, in recent years, the methods of mobile robot’s navigation and control are considered in the framework of quantum computation (Nielsen & Chuang, 2000), which gave rise to the concept of quantum mobile robot (Benioff, 1998; Dong, et al., 2006). Such approach allowed including both an environmental influence on the robot’s actions and the changes of the environment by the robot by the use of the same model, and the ability to apply the methods of quantum communication and decision-making (Levitin, 1969; Helstrom, 1976; Davies, 1978; Holevo, 2001) to the mobile robot’s control. Following Benioff, quantum robots are “mobile systems that have a quantum computer and any other needed ancillary systems on board. Quantum robots move in and interact (locally) with environments of quantum systems” (Benioff, 1998). If, in contrast, the quantum robots interact with a non-quantum environment, then they are considered as quantum-controlled mobile robots. According to Perkowski, these robots are such that “their controls are quantum but sensors and effectors are classical” (Raghuvanshi, et al., 2007). In the other words, in the quantum-controlled mobile robot, the input data obtained by classical (non-quantum) sensors are processed by the use of quantum-mechanical methods, and the results are output to classical (non-quantum) effectors. In this chapter, we present a brief practical introduction into quantum computation and information theory and consider the methods of path planning and navigation of quantumcontrolled mobile robots based on quantum decision-making.
Finding the Most Uniform Changes in Vowel Polygon Caused by Psychological Stress

Using vowel polygons, exactly their parameters, is chosen as the criterion for achievement of differences between normal state of speaker and relevant speech under real psychological stress. All results were experimentally obtained by created software for vowel polygon analysis applied on ExamStress database. Selected 6 methods based on cross-correlation of different features were classified by the coefficient of variation and for each individual vowel polygon, the efficiency coefficient marking the most significant and uniform differences between stressed and normal speech were calculated. Using the mean of cross- correlation values received for area difference with vector length and angle can be classified as the best method for observing generated differences. Generally, best results for stress detection are achieved by vowel triangles created by /i/-/o/-/u/ and /a/-/i/-/o/ vowel triangles in formant planes containing the fifth formant F5 combined with other formants.
Enhancing Topical Word Semantic for Relevance Feature Selection

Unsupervised topic models, such as Latent Dirichlet Allocation (LDA), are widely used as automated feature engineering tools for textual data. They model words semantics based on some latent topics on the basis that semantically related words occur in similar documents. However, words weights that are assigned by these topic models do not represent the semantic meaning of these words to user information needs. In this paper, we present an innovative and effective extended random sets (ERS) model to enhance the semantic of topical words. The proposed model is used as a word weighting scheme for relevance feature selection (FS). It accurately weights words based on their appearance in the LDA latent topics and the relevant documents. The experimental results, based on 50 collections of the standard RCV1 dataset and TREC topics for information filtering, show that the proposed model significantly outperforms eight, state-of-the-art, baseline models in five standard performance measures.
Bayesian Analysis In Mplus : A Brief Introduction

This paper uses a series of examples to give an introduction to how Bayesian analysis is carried out in Mplus. The examples are a mediation model with estimation of an indirect effect, a structural equation model, a two-level regression model with estimation of a random intercept variance, a multiple-indicator binary growth model with a large number of latent variables, a two-part growth model, and a mixture model. It is shown how the use of Mplus graphics provides information on estimates, convergence, and model fit. Comparisons are made with frequentist estimation using maximum likelihood and weighted least squares. Data and Mplus scripts are available on the Mplus website.
Positive and Negative Structures and Processes Underlying Academic Performance : A Chained Mediation Model Journal Item

This study proposed and tested a comprehensive, chained mediation model of university students' academic performance. The hypothesized model included adaptivepositive and maladaptive-negative submodels. The structures and processes in the adaptivepositive submodel were hypothesized to facilitate students’ academic performance, whereas the structures and processes in the maladaptive-negative submodel were hypothesized to undermine it. A sample of 373 university students completed a set of questionnaires measuring their approaches to studying, positive and negative affect, evaluation anxiety, use of creative cognition, motivational orientations, and adaptive and maladaptive metacognitions. Participants’ end-of-semester and prior semester academic performance was retrieved from the university registry. A structural equation model explained 90% of the variance in students’ future academic performance, supported all but one hypothesized intermediate paths, and revealed that only positive affect in studying and prior academic performance predict directly future academic performance. The theoretical and practical implications of these findings are outlined.