Influential Point Research Articles

Decision‐making factor interactions influencing climate migration: A systems‐based systematic review

AbstractGlobal migration and mobility dynamics are expected to shift in the coming decades as a result of climate change. However, the extent to which migration is caused by climate hazards, in contrast or addition to other intervening factors, is a point of debate in literature. In this study, we conducted a systematic literature review to identify and consolidate factors which directly and indirectly influence climate change migration. In our review of the literature, we found a total of 21 economic, environmental, demographic, political, social, and personal intervening decision‐making factors which affect climate migration. Causal interactions between these factors were identified using an axial qualitative coding technique called purposive text analysis. By combining causal links, a semi‐quantitative causal loop diagram was created that represented factor interaction and feedback within the “climate migration system.” Using this model, we highlight influential feedback loops and point to how intervention strategies may cause downstream effects. This research helps to address calls for a better understanding of the complex decision‐making dynamics in climate migration. In particular, results from our causal feedback loops show that intervention strategies targeted toward economic factors such as financial capital and livelihoods, as well as food security, would have the greatest impact in assisting climate‐affected communities. These results help inform climate migration policy and aid planners in the future to better understand the interconnected system of factors that lead to the emergent outcome of climate migration.This article is categorized under: Vulnerability and Adaptation to Climate Change > Learning from Cases and Analogies The Social Status of Climate Change Knowledge > Climate Science and Decision Making

Quantitative Structure-Activity Relationship (QSAR) Study of a Series of Chalcone Derivatives Inhibiting Plasmodium Falciparum 3D7

This Quantitative Structure-Activity Relationship (QSAR) study was conducted using a series of twenty (20) chalcone derivatives with inhibitory activities against Plasmodium falciparum 3D7. The molecules were optimized at the B3LYP/LanL2DZ computational level, to obtain the molecular descriptors. This work was performed using the Linear Multiple Regression (LMR) method, the NonLinear Regression (NLMR) and the Artificial Neural Network (ANN) method. These tools allowed us to obtain three (3) quantitative models from the quantum descriptors that are, the overall softness (S), the bond lengths l(c=o) and l(c=c), and the polarizability (α). These models have good statistical performance. Among them, the ANN has a significantly better predictive ability <i>R² =</i>0.997; <I>RMCE</I> = 0.035; <I>F</I>= 3571.499. The external validation tests verify all the criteria of Tropsha <i>et al.</i> and Roy <i>et al.</i> Also, the applicability domain of this model determined from the levers shows that a prediction of the pIC50 of new chalcone derivatives is acceptable when its lever value is lower than 1.07. For the ANN method, the Ch19 molecule is certainly outside the applicability domain, but it is not an influential point for the model, because this derivative belongs to the validation set, and therefore was not used in the model development. The behavior of this molecule could be explained by its structural diversity.

Influential Points in Adaptability and Stability Methods Based on Regression Models in Cotton Genotypes

The aim of this work was to answer the following question: can influential points modify the recommendation of genotypes, based on regression methods, in the presence of genotype × environment (G × E)? Therefore, we compared the parameters of the adaptability and stability of three methodologies based on regression in the presence of influential points. Specifically, were evaluated methods based on simple, non-parametric and quantile (τ = 0.50) regressions. The dataset used in this work corresponds to 18 variety trials of cotton cultivars that were conducted in the 2013–2014 and 2014–2015 crop seasons. The evaluated variable was the cotton fiber yield (kg/ha). Once we noticed that the effect of G × E interaction is significant, the statistical procedures adopted for the adaptability and stability analysis of the genotypes. To verify the presence of a possible influential point, we used the leverage values, studentized residuals (SR), DFBETAS and Cook’s distance. As a result, the influential points can modify the recommendation of genotypes, based on regression methods, in the presence of G × E interaction. The non-parametric and quantile (τ = 0.50) regressions, which are based on median estimators, are less sensitive to the presence of influential points avoiding misleading recommendations of genotypes in terms of adaptability.

Tri-doped co-annealed zinc oxide semi-conductor synthesis and characterization: photodegradation of dyes and gas sensing applications

Despite the fact that much of the research has been performed on ZnO-based nanoparticles, still a lot of work is unexplored. The synthesis and characterization of the ZnO nanorods have been co-annealed using a simple combustion method and used for gas sensor and photocatalytic degradations applications. Herein pure and In, Sn and Sb tri-dopants were used, i.e. 0.5 at.wt% 1.0 at.wt% and 1.5 at.wt%, while their effects co-annealed on glass substrate at different temperatures at 500 °C and 1100° have been studied. These samples were coated onto the chosen substrate using spin coating technique. Crystallite scale was measured to the range of 30–50 nm. At such temperatures, the grain size measured for the samples was in range of 50–70 nm. This showed that the prepared nanorods are well crystalline and have strong optical properties to handle. Studies of X-ray diffraction showed the influential point (101). These coated samples designed for nitrogen gas sensing have been tested for the development of smart and functional instruments. Furthermore, it was observed that the samples prepared at higher temperatures exhibit better recovery and better reaction time. Valance ion process explains the gas sensors fast reaction and long recovery time. Thus prepared ZnO nanoparticles have photocatalytic degradation (99.86%) only in 55 min. We observed optimum exposure at an operating temperature of 105 °C. It is notable that morphology of susceptible layer nanoparticles is preserved based on different tri-doping concentrations. The concentration of T2-ZnO nanoparticles for photodegradation of the DR-31 dye and NO2 gas sensing applications were 1.0 at.wt%

Prawo i emocje - synteza ruchu

While Law &amp; Emotions movement made large waves in the international academic community in the last 30 years, it remains virtually unknown in Poland. However, applying perspectives of this multidisciplinary research enterprise in Polish law and jurisprudence could yield promising results. As the field is vast and consists of many voices, an attempt at consolidating its findings and demonstrating their relevance is needed. The objective of the text is thus to provide a cross-section of this influential movement and point out why it potentially revolutionizes thinking about law. To this end, the text analyses a body of works dealing with the relationship between law and emotion, evaluates their usefulness and presents the finding across a range of potential implications for: theory and philosophy of law, study of constitutional law and lawmaking, particular doctrines of law and knowledge about emotions of legal actors.

Evaluation of Different Processor Architecture Organizations for On-Site Electronics in Harsh Environments

Microcontrollers to be used in harsh environmental conditions, e.g., at high temperatures or radiation exposition, need to be fabricated in robust technology nodes in order to operate reliably. However, these nodes are considerably larger than cutting-edge semiconductor technologies and provide less speed, drastically reducing system performance. In order to achieve low silicon area costs, low power consumption and reasonable performance, the processor architecture organization itself is a major influential design point. Parameters like data path width, instruction execution paradigm, code density, memory requirements, advanced control flow mechanisms etc., may have large effects on the design constraints. Application characteristics, like exploitable data parallelism and required arithmetic operations, have to be considered in order to use the implemented processor resources efficiently. In this paper, a design space exploration of five different architectures with MIPS- or ARM-compatible instruction set architectures, as well as transport-triggered instruction execution is presented. Using a 0.18 upmu m SOI CMOS technology for high temperature and an exemplary case study from the fields of communication, i.e., powerline communication encoder, the influence of architectural parameters on performance and hardware efficiency is compared. For this application, a transport-triggered architecture configuration has an 8.5times higher performance and 2.4times higher computational energy efficiency at a 1.6times larger total silicon area than an off-the-shelf ARM Cortex-M0 embedded processor, showing the considerable range of design trade-offs for different architectures.

Bayesian inference for an ordered multiple linear regression with skew normal errors

This paper studies a Bayesian ordered multiple linear regression model with skew normal error. It is reasonable that the kind of inherent information available in an applied regression requires some constraints on the coefficients to be estimated. In addition, the assumption of normality of the errors is sometimes not appropriate in the real data. Therefore, to explain such situations more flexibly, we use the skew-normal distribution given by Sahu et al. (The Canadian Journal of Statistics, 31, 129-150, 2003) for error-terms including normal distribution. For Bayesian methodology, the Markov chain Monte Carlo method is employed to resolve complicated integration problems. Also, under the improper priors, the propriety of the associated posterior density is shown. Our Bayesian proposed model is applied to NZAPB’s apple data. For model comparison between the skew normal error model and the normal error model, we use the Bayes factor and deviance information criterion given by Spiegelhalter et al. (Journal of the Royal Statistical Society Series B (Statistical Methodology), 64, 583-639, 2002). We also consider the problem of detecting an influential point concerning skewness using Bayes factors. Finally, concluding remarks are discussed.

Detection and Diagnostic Methods of Multiple Influential Points in Binary Logistic Regression Model in Animal Breeding

Multiple influential points adversely affect parameter estimation in binary logistic regression models and lead to misinterpretation of results. An influential point is a data point that does not follow the overall slope of remaining data and has extreme value in terms of x. Since the presence of approximately 10% of influential points in a dataset affects parameter estimates, detection and diagnosis of these points greatly matter. Graphical (such as scatter graph and box graph) and analytical methods are adopted in the detection and diagnosis of multiple influential points. Among the commonly used diagnostic methods are Pearson residuals, Standardized Pearson Residuals (SPR), Cook Distance (CD), Hat matrix, DFFITS, and DFBETA. However, these methods mask problems and fail to diagnose if there are multiple influential points. Many statisticians have developed and proposed new diagnostic methods, such as Generalized Standardized Pearson Residual (GSPR) and Generalized Weights (GW), to overcome this problem. This study exploited a dataset containing multiple influential points (15%) for weaning weight (WW), yearling weight (YW), fleece weight (FW), and fertility rate (FR) of Romney ewes and modelled the effects of WW, TW and FW variables on FR by binary logistic regression model. This study is intended to determine the multiple influential points by graphical methods and to examine the performance of commonly used and newly developed methods in the diagnosis of these data points. As a result, it was observed that the commonly used methods mask multiple influential points and the new proposed methods competently identify these points.

Online Distributed IoT Security Monitoring with Multidimensional Streaming Big Data.

Internet of Things (IoT) enables extensive connections between cyber and physical "things". Nevertheless, the streaming data among IoT sensors bring "big data" issues, for example, large data volumes, data redundancy, lack of scalability and so on. Under "big data" circumstances, IoT system monitoring becomes a challenge. Furthermore, cyberattacks which threaten IoT security are hard to be detected. In this paper, we propose an online distributed IoT security monitoring algorithm (ODIS). An advanced influential point selection operation extracts important information from multidimensional time series data across distributed sensor nodes based on the spatial and temporal data dependence structure. Then, an accurate data structure model is constructed to capture the IoT system behaviors. Next, hypothesis testing is carried out to quantify the uncertainty of the monitoring tasks. Besides, the distributed system architecture solves the scalability issue. Using a real sensor network testbed, we commit cyberattacks to an IoT system with different patterns and strengths. The proposed ODIS algorithm demonstrates promising detection and monitoring performances.

Analysis of Rigid Body Swing Effect on SCR Response under Top Motion and Wave Action

The catenary riser such as steel catenary riser (SCR), under wave action or current action, shows a kind of rotation that acts as a rigid body along a similarly fixed axis of oscillation determined by the varying suspension and touch down point, respectively. The characteristics of acceleration of catenary riser influenced by rigid body swing integrity backwards and forwards (RBSIBF) in cross direction cannot be neglected. Based on the large deflection slender beam model, top motion of x direction, RBSIBF, and wave force model, this manuscript studies and explains effect of RBSIBF in cross direction (z direction) on riser in quantitative and qualitative perspectives. The rigid body wiggle effect can be considered by amplitude-value multiplication with the safety factor of 1.2. The calculation shows that, in terms of the overall motion pattern, the motion response in the xy plane develops gradually from the narrow amplitude wiggle in in-line direction of top region to narrow amplitude wiggle in vertical direction of bottom area. Wave load is the main effect load in cross-flow direction. Along the depth increase, the acceleration amplitude of the top hanging point area is maximum, and the amplitude decreases most strongly or violently. With the decrease of case amplitude, the structural acceleration responses of node 10th to 80th significantly reduced by about 30% and the corresponding of node 140th to 200th increased by about 15%. The most influential point of RBSIBF on acceleration is node 200th with an influence level of about 20%. When the structure mainly rotates in the xz plane, rigid body wiggle and swing are positively correlated with rotation vector diameter. The rigid body wiggle and swing increase acceleration of structure. In the rotational yz plane of the structure, rigid body wiggle and swing reduce acceleration response.

Multiple Influential Point Detection in High Dimensional Regression Spaces

SummaryInfluence diagnosis is an integrated component of data analysis but has been severely underinvestigated in a high dimensional regression setting. One of the key challenges, even in a fixed dimensional setting, is how to deal with multiple influential points that give rise to masking and swamping effects. The paper proposes a novel group deletion procedure referred to as multiple influential point detection by studying two extreme statistics based on a marginal-correlation-based influence measure. Named the min- and max-statistics, they have complementary properties in that the max-statistic is effective for overcoming the masking effect whereas the min-statistic is useful for overcoming the swamping effect. Combining their strengths, we further propose an efficient algorithm that can detect influential points with a prespecified false discovery rate. The influential point detection procedure proposed is simple to implement and efficient to run and enjoys attractive theoretical properties. Its effectiveness is verified empirically via extensive simulation study and data analysis. An R package implementing the procedure is freely available.

New opinion on the mechanism of Dazhu (BL 11) for gonalgia with flexion-extension dysfunction

The effect of Dazhu (BL 11) for gonalgia with flexion-extension dysfunction is remarkable, and its mechanism of action is interpreted as the influential point of bone treating bone diseases. However, through the exploration of a variety of literature, the relevant classical research, the views of senior experts, and combined with the author's experience, we put forward some new ideas and views for reference. Through in-depth analysis about pathogenesis of gonalgia with flexion-extension dysfunction and the functional attributes of Dazhu (BL 11), combining meridian tendons differentiation and myofascial meridians, we consider that Dazhu (BL 11), with its unique "location" advantage, plays the role of regulating multiple viscera, meridians, meridian tendons and myofascial meridians, which is the mechanism for gonalgia with flexion-extension dysfunction.

Modeling and prediction of octanol/water partition coefficient of pesticides using QSPR methods

PurposeThe purpose of this paper is to predict the octanol/water partition coefficient (Kow) of 43 organophosphorous compounds.Design/methodology/approachA quantitative structure-property relationship analysis was performed on a series of 43 pesticides using multiple linear regression and support vector machines methods, which correlate the octanol-water partition coefficient (Kow) values of these chemicals to their structural descriptors. At first, the data set was randomly separated into a training set (34 chemicals) and a test set (nine chemicals) for statistical external validation.FindingsModels with three descriptors were developed using theoretical descriptors as independent variables derived from Dragon software while applying genetic algorithm-variable subset selection procedure.Originality/valueThe robustness and the predictive performance of the proposed linear model were verified using both internal and external statistical validation. One influential point which reinforces the model and an outlier were highlighted.

Reading Reading: Faulkner's Queer Exercise in Reader Complicity in Light in August

Reading Reading:Faulkner's Queer Exercise in Reader Complicity in Light in August Daniella Gáti (bio) William Faulkner's Light in August ends with a brutal lynching and a scene of hopeful love.1 Yet between the tragic dimension of Joe Christmas's violent murder and the comic satisfaction of Byron Bunch's suit for love, the novel offers a third plot ending—the apparent death of the Reverend Gail Hightower. The novel's penultimate chapter, chapter 20, both evokes and obscures Hightower's death; the minister glimpses and yet does not achieve ultimate clarity. Readers of Light in August have systematically found this chapter "puzzling" (Watson 169): it is, to quote Doreen Fowler, "at best, mysterious, at worst, anti-climactic," and its function among the other plot endings is "seemingly unaccountabl[e]" (Fowler 139). What is the purpose of this ambiguous chapter, which teases with cathartic significance but never quite provides it? I argue that the "mysterious" and "puzzling" effect of chapter 20 is a product of a deliberate textual construction that asks us to reassess our reading of the novel. Hightower, whom the text has hitherto encouraged us to regard as relatively insignificant, is suddenly at the center of an important, if ambiguous, epiphanic moment at odds with his previous, seemingly sidelined role. Indeed, I propose that Light in August uses Hightower across the novel to complement its analysis of normative power by juxtaposing Christmas's manifestly brutal death with a hidden, participatory violence that excludes Hightower from full humanity. Through a crafty management of the narratee's attention and sympathies, Faulkner's novel guides the reader's evaluation of the relative significances of characters towards an assessment in which Hightower does not attain the status of protagonist in his own drama. According to Alex Woloch, arranging characters in a [End Page 153] system of distributed attention fundamentally informs "our sense of the human figure" (13): in Light in August, that system replicates Jefferson's assessments of whose fate matters and whose does not. Hightower's plot denouement is "puzzling," then, because it affords the minister a significance that runs counter to what the narrative has hitherto encouraged. Chapter 20 gains its force from its gesture towards the novel's mechanisms to manage readers' sympathies towards an alignment with Jefferson's normative system. My project in this essay, then, is to carry out what might be called a reading of a reading to explore the dynamics of readers' participation in oppressive systems of valuation and to draw out what I propose is Faulkner's critique of ethically motivated—but ultimately compromised—reading practices. Christmas's story demonstrates Foucault's influential point that power structures an individual's every interaction with society (Discipline and Punish 26–28), but an attention to Hightower allows us to go further than the recognition of power's omnipresence. Because, arguably, the text does not invite the reader to dismiss Christmas's fate as insignificant, the minister's case demonstrates how forceful coercion, as with Christmas, is only one part of normative boundary policing. Simultaneously, and equally effectively, power works in a subtle and veiled way through what Edward Said describes as "unself-conscious bad innocence" (116), precisely through those well-meaning agents whose values may not even align with the normative order. Innocence, even benevolence, plays a key role in enabling a position of complicit indifference towards Hightower. Byron's good intentions towards Lena and Christmas both allow and require that he reduce Hightower from friend to aide, degrading the minister from the subject of his story to an instrument in theirs. To save Christmas from lynching, for example, Byron has to ask Hightower to confirm Jefferson's suspicions regarding his "queerness" by "outing" himself as having put up Christmas for those nights when the latter was actually with Joanna Burden. The gravity of this request is mollified by the fact that preventing Christmas's lynching is morally good. The sense of being morally right invites the reader's emotional and ethical participation in Byron's project by testifying to Byron's benevolence, which makes it easier to regard him as innocent of other, similarly violent, erasures. For the narratee, then, Byron...

Towards a Reconceptualization of “(Post)Transitional” South African Cultural Expression

In this paper, I problematize the notion of the “post-transitional” (Samuelson 2008; Frenkel and MacKenzie 2010) as a way of theorizing and delineating recent South African cultural expression. I argue that this idea relies – whether intentionally or not – on a limiting conception of South Africa’s contemporary socio-political history and transition in terms that are inevitably linear and teleological. I propose that contemporary cultural expression in South Africa (and indeed across Africa) may be productively considered, in broad terms, as literatures of transition. This is an overarching non-linear and non-teleological continuum embracing multiple transitions that are not necessarily discrete or mutually exclusive, and that can be delineated in connection with specific contexts and moments. Without rejecting the general features and trends of recent South African cultural expression identified under the problematical rubric of “post-transitional,” I propose that the emergent post-2000 literatures be theorized as “post-TRC.” This highlights the significance of the Truth and Reconciliation Commission as an influential point of reference without ignoring the wider, non-linear, and non-teleological frame of on-going multiple transitions – social, political, economic, and cultural.

Empirical evaluation of the inverse Gaussian regression residuals for the assessment of influential points

Influential analysis is the main diagnostic process to obtain reliable regression results. Same is true for the generalized linear model. The present article empirically compares the performance of different residuals of the inverse Gaussian regression model to detect the influential points. The inverse Gaussian regression model residuals are further divided into two categories, that is, standardized and adjusted residuals. Cook's distance has been computed for both of the stated residuals, and then comparison of these residuals for the detection of influential point has been carried out with the help of simulation and a chemical related data set. The simulation results show that for small dispersion, the likelihood residuals are better than others and all the adjusted forms of residuals perform identically but not better than the standardized form. While for larger dispersion, all the standardized residuals perform in the same fashion, and they are better than the likelihood residuals for detection of influential points. Copyright © 2016 John Wiley &amp; Sons, Ltd.

Bayesian change-point problem using Bayes factor with hierarchical prior distribution

We consider the hierarchical Bayesian models of change-point problem in a sequence of random variables having either normal population or skew-normal population. Further, we consider the problem of detecting an influential point concerning change point using Bayes factors. Our proposed models are illustrated with the real data example, the annual flow volume data of Nile River at Aswan from 1871 to 1970. The result using our proposed models indicated the largest influential observation in the year 1888 among outliers. We have shown that it is useful to measure the influence of observations on Bayes factors. Here, we consider omitting single observation as well.

The influential point of bone should be Dàzhuī ( GV 14) rather than Dàzhù ( BL 11)

ObjectiveThe influential point of bone in acupuncture should be Dàzhuī (▪ GV 14), but it is wrongly believed as Dàzhù (▪ BL 11) in the modern acupuncture literature and textbooks. This wrong academic theory has widely influenced acupuncture field domestically and abroad, and misguided acupuncture medicine theory and the treatment of acupuncture on bone diseases. This essay aims to clear up the misunderstanding and restore the academic status of “the influential point of bone is GV 14” in the acupuncture theory and the treatment on bone diseases.

Influential point detection diagnostics in the context of hydrological model calibration

Summary Influential data are those that have a disproportionate impact on model performance, parameters and/or predictions. This paper evaluates two classes of diagnostics that identify influential data for hydrological model calibration: (1) numerical “case-deletion” diagnostics, which directly measure the influence of each data point on the calibrated model; and (2) analytical diagnostics based on Cook’s distance, which combine information on the model residuals with a measure of the distance of each input point from the centre of the range of the input data (i.e., the leverage). Case-deletion methods rank influence by changes in the model parameters (measured through the Mahalanobis distance), performance (using objective function displacement) and predictions (e.g. mean and maximum streamflow). For the analytical methods, both linear and nonlinear estimates of leverage are used to calculate Cook’s distance, which is used to rank influential data. We apply these diagnostics to three case studies and show that a single point could change mean/maximum streamflow predictions by 7%/9% for a rating curve model, and 13%/25%, for a hydrological model (GR4J) in an ephemeral catchment. In contrast, the influence was far less for GR4J in a humid catchment (0.2%/2.3%). Assuming the data are of high quality this indicates deficiencies in the ability of the GR4J model structure to reproduce the flow regime in the ephemeral catchment. The linear Cook’s distance-based metric produced reasonably similar rankings to the case-deletion metrics at a fraction of the computational cost (300–1000 times faster), but with less flexibility to rank influence using specific aspects of model behaviour. The nonlinear distance produced rankings that were virtually the same as the case-deletion metrics for all case studies – this highlights the importance of its use for nonlinear hydrological models. Visual assessment was not a reliable method of influence analysis as there was no direct relationship between the most influential data and the highest observed streamflows. The findings establish the feasibility and importance of including influence detection diagnostics as a standard tool in hydrological model calibration.

Increasing flexural strength and toughness of cement mortar using multi-walled Carbon nanotubes

In this study the effect of using multi-walled carbon nanotube (MWCNT) on flexural and compressive strengths, ultimate displacement and energy absorption capability of standard cement mortar considering different weight percentages of nanotubes as well as different dispersion methods has been investigated. Influential point in adding nanotubes to the composites is their proper dispersion, which is considered by comparing the results of two different dispersion methods. According to the test results and scanning electron microscope (SEM) images, the method using functionalized MWCNTs together with ultrasonication is pointed as an appropriate dispersion method. Using nanotubes resulted in significantly increase in the flexural strength and specially toughness of cement mortar which represents the ability of properly dispersed nanotubes in bridging and closure of the micro cracks. Finally, the observed results has been assessed with a statistical analysis and validated with acceptable significance levels.