The use and limitations of null-model-based hypothesis testing

In this article I give a critical evaluation of the use and limitations of null-model-based hypothesis testing as a research strategy in the biological sciences. According to this strategy, the null model based on a randomization procedure provides an appropriate null hypothesis stating that the existence of a pattern is the result of random processes or can be expected by chance alone, and proponents of other hypotheses should first try to reject this null hypothesis in order to demonstrate their own hypotheses. Using as an example the controversy over the use of null hypotheses and null models in species co-occurrence studies, I argue that null-model-based hypothesis testing fails to work as a proper analog to traditional statistical null-hypothesis testing as used in well-controlled experimental research, and that the random process hypothesis should not be privileged as a null hypothesis. Instead, the possible use of the null model resides in its role of providing a way to challenge scientists’ commonsense judgments about how a seemingly unusual pattern could have come to be. Despite this possible use, null-model-based hypothesis testing still carries certain limitations, and it should not be regarded as an obligation for biologists who are interested in explaining patterns in nature to first conduct such a test before pursuing their own hypotheses

The Impact of Corporate Social Responsibility on the Trust Repair of Brand with Negative Publicity: Mental Account as a Mediator

With the development of internet and popularity of mobile terminals, negative publicity of brand has become more and more widespread. This paper aims to study the impact of corporate social responsibility（CSR） on the trust repair of brand with negative publicity. From Chinese cultural aspect of the differential mode of association, CSR is divided into public morality behavior and private one. The concept of mental account is introduced as a mediating variable and CSR history as a moderate one. By a 2 (CSR type: public VS. private morality behavior) ×2(CSR history: long VS. short) between group experiment, it is found that public morality is more likely to be classified into charity account by consumers, thereby promoting integrity-based trust repair; private morality is more likely to be classified into remedy account, thereby promoting ability-based trust repair. Public morality behavior with long history is more tend to be attributed to charity account by consumers; and CSR including public and private one with short history are more tend to be attributed to remedy account by consumers

Far-Field Plasmonic Resonance Enhanced Nano-Particle Image Velocimetry within a Micro Channel

In this paper, a novel far-field plasmonic resonance enhanced nanoparticle-seeded Particle Image Velocimetry (nPIV) has been demonstrated to measure the velocity profile in a micro channel. Chemically synthesized silver nanoparticles have been used to seed the flow in the micro channel. By using Discrete Dipole Approximation (DDA), plasmonic resonance enhanced light scattering has been calculated for spherical silver nanoparticles with diameters ranging from 15nm to 200nm. Optimum scattering wavelength is specified for the nanoparticles in two media: water and air. The diffraction-limited plasmonic resonance enhanced images of silver nanoparticles at different diameters have been recorded and analyzed. By using standard PIV techniques, the velocity profile within the micro channel has been determined from the images.Comment: submitted to Review of Scientific Instrument

Understanding Patterns In Nature

Nature is full of interesting patterns. One of the most important tasks across the natural sciences, especially the biological sciences, is to identify and explain real patterns in nature. This dissertation provides a philosophical investigation of the nature and roles of real patterns in biological inquiry and the various strategies that biologists employ to explain and understand real patterns in nature. In Chapter 1, I advocate for a pragmatic approach to the reality of patterns in data. I argue that patterns in data are expected to play different scientific roles in different research contexts and that a pattern in data is real if and only if it fulfills the scientific role it is expected to play in a specific research context. In Chapter 2, I give a critical evaluation of the use and limitations of null-model-based hypothesis testing as a research strategy to explain patterns in the biological sciences. I argue that null-model-based hypothesis testing fails to work as a proper analog to traditional statistical null-hypothesis testing as used in well-controlled experimental research, and that the random process hypothesis should not be privileged as a null hypothesis. Instead, the possible use of the null model resides in its role of providing a way to challenge scientists’ commonsense judgments about how a seemingly unusual pattern could have come to be. In Chapter 3, I clarify the definition of a baseline model and apply it to the niche-neutral debate about how to understand biodiversity patterns. I argue that from a process-based perspective, a neutral model in ecology should not be regarded as a baseline model relative to classical niche-based models. In Chapter 4, I investigate the testability and the scientific value of the notion of overall relative causal importance by carefully examining the controversy over empirical adaptationism in evolutionary biology. My analysis of the case of empirical adaptationism provides reasons for scientists to reconsider the value and necessity of engaging in scientific debates involving the notion of overall relative causal importance

Algorithms to calculate the most reliable maximum flow in content delivery network

Funding Information: Funding Statement: This work was partly supported by Open Research Fund from State Key Laboratory of Smart Grid Protection and Control, China (Zhang B, www.byqsc.net/com/nrjt/), Rapid Support Project (61406190120, Zhang B), the Fundamental Research Funds for the Central Universities (2242021k10011, Zhang B, www.seu.edu.cn) and the National Key R&D Program of China (2018YFC0830200, Zhang B, www.most.gov.cn).Peer reviewedPublisher PD

Empirical adaptationism revisited: Is it testable and is it worth testing?

Empirical adaptationism is often said to be an empirical claim about nature, which concerns the overall relative causal importance of natural selection in evolution compared with other evolutionary factors. Philosophers and biologists who have tried to clarify the meaning of empirical adaptationism usually share, explicitly or implicitly, two assumptions: (1) Empirical adaptationism is an empirical claim that is scientifically testable; (2) testing empirical adaptationism is scientifically valuable. In this article, I challenge these two assumptions and argue that both are unwarranted given how empirical adaptationism is currently formulated. I identify a series of conceptual and methodological difficulties that makes testing empirical adaptationism in a biologically non-arbitrary way virtually impossible. Moreover, I show that those in favor of testing empirical adaptationism have yet to demonstrate the distinctive value and necessity of conducing such a test. My analysis of the case of empirical adaptationism also provides reasons for scientists to reconsider the value and necessity of engaging in scientific debates involving the notion of overall relative causal importance