New hydraulic insights into rapid sand filter bed backwashing using the Carman–Kozeny model

Fluid flow through a bed of solid particles is an important process that occurs in full-scale water treatment operations. The Carman–Kozeny model remains highly popular for estimating the resistance across the bed. It is common practice to use particle shape factors in fixed bed state to match the predicted drag coefficient with experimentally obtained drag coefficients. In fluidised state, however, where the same particles are considered, this particle shape factor is usually simply omitted from the model without providing appropriate reasoning. In this research, it is shown that a shape factor is not a constant particle property but is dependent on the fluid properties as well. This dynamic shape factor for irregularly shaped grains increases from approximately 0.6 to 1.0 in fluidised state. We found that unstable packed beds in moderate up-flow conditions are pseudo-fixed and in a setting state. This results in a decreasing bed voidage and simultaneously in a decreasing drag coefficient, which seems quite contradictory. This can be explained by the collapse of local channels in the bed, leading to a more uniform flow distribution through the bed and improving the available surface for flow-through. Our experimental measurements show that the drag coefficient decreases considerably in the laminar and transition regions. This is most likely caused by particle orientation, realignment and rearrangement in particles’ packing position. A thorough hydraulic analysis shows that up-flow filtration in rapid sand filters under backwash conditions causes the particle bed to collapse almost imperceptibly. In addition, an improved expression of the drag coefficient demonstrated that the Carman–Kozeny model constant, however often assumed to be constant, is in fact not constant for increasing flow rates. Furthermore, we propose a new pseudo-3D image analysis for particles with an irregular shape. In this way, we can explain the successful method using optimisation of the extended terminal sub-fluidisation wash (ETSW) filter backwashing procedure, in which turbidity and peaks in the number of particles are reduced with a positive effect on water quality

Self-prioritization and perceptual matching: The effects of temporal construal.

Recent research has revealed that self-referential processing enhances perceptual judgments - the so-called self-prioritization effect. The extent and origin of this effect remains unknown, however. Noting the multifaceted nature of the self, here we hypothesized that temporal influences on self-construal (i.e., past/future-self continuity) may serve as an important determinant of stimulus prioritization. Specifically, as representations of the self increase in abstraction as a function of temporal distance (i.e., distance from now), self-prioritization may only emerge when stimuli are associated with the current self. The results of three experiments supported this prediction. Self-relevance only enhanced performance in a standard perceptual-matching task when stimuli (i.e., geometric shapes) were connected with the current self; representations of the self in the future (Expts. 1 & 2) and past (Expt. 3) failed to facilitate decision making. To identify the processes underlying task performance, data were interrogated using a hierarchical drift diffusion model (HDDM) approach. Results of these analyses revealed that self-prioritization was underpinned by a stimulus bias (i.e., rate of information uptake). Collectively, these findings elucidate when and how self-relevance influences decisional processing

Individual Variations in Maternal Care Early in Life Correlate with Later Life Decision-Making and c-Fos Expression in Prefrontal Subregions of Rats

Early life adversity affects hypothalamus-pituitary-adrenal axis activity, alters cognitive functioning and in humans is thought to increase the vulnerability to psychopathology–e.g. depression, anxiety and schizophrenia- later in life. Here we investigated whether subtle natural variations among individual rat pups in the amount of maternal care received, i.e. differences in the amount of licking and grooming (LG), correlate with anxiety and prefrontal cortex-dependent behavior in young adulthood. Therefore, we examined the correlation between LG received during the first postnatal week and later behavior in the elevated plus maze and in decision-making processes using a rodent version of the Iowa Gambling Task (rIGT). In our cohort of male and female animals a high degree of LG correlated with less anxiety in the elevated plus maze and more advantageous choices during the last 10 trials of the rIGT. In tissue collected 2 hrs after completion of the task, the correlation between LG and c-fos expression (a marker of neuronal activity) was established in structures important for IGT performance. Negative correlations existed between rIGT performance and c-fos expression in the lateral orbitofrontal cortex, prelimbic cortex, infralimbic cortex and insular cortex. The insular cortex correlations between c-fos expression and decision-making performance depended on LG background; this was also true for the lateral orbitofrontal cortex in female rats. Dendritic complexity of insular or infralimbic pyramidal neurons did not or weakly correlate with LG background. We conclude that natural variations in maternal care received by pups may significantly contribute to later-life decision-making and activity of underlying brain structures

The Brain's Router: A Cortical Network Model of Serial Processing in the Primate Brain

The human brain efficiently solves certain operations such as object recognition and categorization through a massively parallel network of dedicated processors. However, human cognition also relies on the ability to perform an arbitrarily large set of tasks by flexibly recombining different processors into a novel chain. This flexibility comes at the cost of a severe slowing down and a seriality of operations (100–500 ms per step). A limit on parallel processing is demonstrated in experimental setups such as the psychological refractory period (PRP) and the attentional blink (AB) in which the processing of an element either significantly delays (PRP) or impedes conscious access (AB) of a second, rapidly presented element. Here we present a spiking-neuron implementation of a cognitive architecture where a large number of local parallel processors assemble together to produce goal-driven behavior. The precise mapping of incoming sensory stimuli onto motor representations relies on a “router” network capable of flexibly interconnecting processors and rapidly changing its configuration from one task to another. Simulations show that, when presented with dual-task stimuli, the network exhibits parallel processing at peripheral sensory levels, a memory buffer capable of keeping the result of sensory processing on hold, and a slow serial performance at the router stage, resulting in a performance bottleneck. The network captures the detailed dynamics of human behavior during dual-task-performance, including both mean RTs and RT distributions, and establishes concrete predictions on neuronal dynamics during dual-task experiments in humans and non-human primates

The Emergence of Emotions

Emotion is conscious experience. It is the affective aspect of consciousness. Emotion arises from sensory stimulation and is typically accompanied by physiological and behavioral changes in the body. Hence an emotion is a complex reaction pattern consisting of three components: a physiological component, a behavioral component, and an experiential (conscious) component. The reactions making up an emotion determine what the emotion will be recognized as. Three processes are involved in generating an emotion: (1) identification of the emotional significance of a sensory stimulus, (2) production of an affective state (emotion), and (3) regulation of the affective state. Two opposing systems in the brain (the reward and punishment systems) establish an affective value or valence (stimulus-reinforcement association) for sensory stimulation. This is process (1), the first step in the generation of an emotion. Development of stimulus-reinforcement associations (affective valence) serves as the basis for emotion expression (process 2), conditioned emotion learning acquisition and expression, memory consolidation, reinforcement-expectations, decision-making, coping responses, and social behavior. The amygdala is critical for the representation of stimulus-reinforcement associations (both reward and punishment-based) for these functions. Three distinct and separate architectural and functional areas of the prefrontal cortex (dorsolateral prefrontal cortex, orbitofrontal cortex, anterior cingulate cortex) are involved in the regulation of emotion (process 3). The regulation of emotion by the prefrontal cortex consists of a positive feedback interaction between the prefrontal cortex and the inferior parietal cortex resulting in the nonlinear emergence of emotion. This positive feedback and nonlinear emergence represents a type of working memory (focal attention) by which perception is reorganized and rerepresented, becoming explicit, functional, and conscious. The explicit emotion states arising may be involved in the production of voluntary new or novel intentional (adaptive) behavior, especially social behavior

Business groups and corporate responsibility for the public good

This paper analyses the relationship between Business Groups as a distinct way of organizing economic activities and their relation to the public good. We first analyze the phenomenon of Business Groups and discuss some of their core features. Subsequently, the paper moves to analyzing the existing literature on Business Groups and Corporate Social Responsibility (CSR) as the most common label for the topic of this Special Issue. Subsequently, specific peculiarities of Business Groups in the context of CSR and their contribution to the public good are fleshed out. Based on this analysis, the paper delineates some implications for the field of CSR and the wider debate on the nature of the firm. We close with some perspectives for future research

Practical guidelines for rigor and reproducibility in preclinical and clinical studies on cardioprotection

The potential for ischemic preconditioning to reduce infarct size was first recognized more than 30 years ago. Despite extension of the concept to ischemic postconditioning and remote ischemic conditioning and literally thousands of experimental studies in various species and models which identified a multitude of signaling steps, so far there is only a single and very recent study, which has unequivocally translated cardioprotection to improved clinical outcome as the primary endpoint in patients. Many potential reasons for this disappointing lack of clinical translation of cardioprotection have been proposed, including lack of rigor and reproducibility in preclinical studies, and poor design and conduct of clinical trials. There is, however, universal agreement that robust preclinical data are a mandatory prerequisite to initiate a meaningful clinical trial. In this context, it is disconcerting that the CAESAR consortium (Consortium for preclinicAl assESsment of cARdioprotective therapies) in a highly standardized multi-center approach of preclinical studies identified only ischemic preconditioning, but not nitrite or sildenafil, when given as adjunct to reperfusion, to reduce infarct size. However, ischemic preconditioning—due to its very nature—can only be used in elective interventions, and not in acute myocardial infarction. Therefore, better strategies to identify robust and reproducible strategies of cardioprotection, which can subsequently be tested in clinical trials must be developed. We refer to the recent guidelines for experimental models of myocardial ischemia and infarction, and aim to provide now practical guidelines to ensure rigor and reproducibility in preclinical and clinical studies on cardioprotection. In line with the above guideline, we define rigor as standardized state-of-the-art design, conduct and reporting of a study, which is then a prerequisite for reproducibility, i.e. replication of results by another laboratory when performing exactly the same experiment

Improvement of voidage prediction in liquid-solid fluidized beds by inclusion of the Froude number in effective drag relations

A novel effective drag relation for liquid-solid fluidisation is proposed, suitable for application in full-scale installations. This is achieved by presenting new insights related to the influence of the temporal-spatial heterogeneity on the effective hydrodynamic drag for large fluidised systems. While heterogeneous flow behaviour can be predicted increasingly accurately in CFD simulations that explicitly model the heterogeneous solids distribution, for the operation of many large-scale applications it is infeasible to perform such computationally intensive simulations. Therefore, there is a clear need for full-scale drag relations that effectively take into account the heterogeneous behaviour and irregular spatial particle distributions. Our new drag relation is based on a large set of experiments, which shows that the degree of overall expansion is not only dependent on the ratio of laminar-turbulent flow, but also on the amount of homogenous versus heterogeneous flow, which is not included in current full-scale drag relations. To include the effect of heterogeneity, the standard drag relation, based on the Reynolds number, is extended with a specific type of Froude number. Because fully turbulent flow regimes are rare in applications of liquid-solid fluidisation, our focus is not on the turbulent flow regime but instead on laminar and transitional flow regimes. In these regimes, three types of models are investigated. The first type is based on a theoretical similarity with terminal settling, the second is based on the semi-empirical Carman-Kozeny model, and the third is based on empirical equations using symbolic regression techniques. For all three types of models, coefficients are calibrated on experimental data with monodisperse and almost spherical glass beads. The models are validated with a series of calcium carbonate grains applied in drinking water treatment processes as well as data obtained from the literature. Using these models, we show that the voidage prediction average relative error decreases from approximately 5% (according to the best literature equations which use Reynolds number only) to 1-2% (using both Reynolds and Froude number). This implies that our new models are more suitable for operational control in full-scale fluidised bed applications, such as pellet softening in drinking water treatment processes.Complex Fluid ProcessingSanitary Engineerin

Accurate voidage prediction in fluidisation systems for full-scale drinking water pellet softening reactors using data driven models

In full-scale drinking water production plants in the Netherlands, central softening is widely used for reasons related to public health, client comfort, and economic and environmental benefits. Almost 500 million cubic meters of water is softened annually through seeded crystallisation in fluidised bed reactors. The societal call for a circular economy has put pressure on this treatment process to become more sustainable. By optimising relevant process conditions, the consumption of chemicals can be reduced, and raw materials reused. Optimal process conditions are feasible if the specific crystallisation surface area in the fluidised bed is large enough to support the performance of the seeded crystallisation process. To determine the specific surface area, crucial variables including voidage and particle size must be known. Numerous models can be found in the literature to estimate the voidage in liquid-solid fluidisation processes. Many of these models are based on semi-empirical porous-media-based drag relations like Ergun or semi-empirical terminal-settling based models such as Richardson-Zaki and fitted for monodisperse, almost perfectly round particles. In this study, we present new voidage prediction models based on accurate data obtained from elaborate pilot plant experiments and non-linear symbolic regression methods. The models were compared with the most popular voidage prediction models using different statistical methods. An explicit model for voidage estimation based on the dimensionless Reynolds and Froude numbers is presented here that can be used for a wide range of particle sizes, fluid velocities and temperatures and that can therefore be directly used in water treatment processes such as drinking water pellet softening. The advantage of this model is that there is no need for applying numerical solutions; therefore, it can be explicitly implemented. The prediction errors for classical models from the literature lie between 2.7 % and 11.4 %. With our new model, the voidage prediction error is reduced to 1.9 %.Complex Fluid ProcessingSanitary Engineerin