Physical Modeling of Flow Nets in Groundwater and Determination of Hydraulic Conductivity

The goal of this study is to physically model the paths that water particles take through soil, and estimate hydraulic conductivity for several soil configurations. Water paths, or flow lines, are shown by injecting dye into sand contained in a rectangular acrylic glass tank with a vertical barrier in the center; water is poured on one side of the tank and a pump is used to maintain constant head loss. If flow lines are formed, a flow net is to be drawn using photos of the tank and hydraulic conductivity is to be calculated. This project consists of four phases: design, construction, testing, and analysis. At the time of this report, the design phase is complete and the construction phase is active. Upon completion of the construction phase, testing will begin using four configurations of sand. Sand variables include coarse or fine sand types, and loose or dense sand placement in the tank. Tests consist of injecting potassium permanganate, referred to mainly as “dye” in this study, into the sand surface in two parallel lines running laterally across the tank. Water is then poured on one side of the acrylic glass barrier, and water outflow on the opposite side of the tank is measured. During the analysis phase, which follows directly after testing, hydraulic conductivity is calculated as described in the Methodology section. If possible, a flow net will be drawn as described in the Background Information and Methodology sections. Hydraulic conductivity calculations will be compared to theoretical values for different types of sand and percent differences are calculated. Discrepancies in hydraulic conductivity will demonstrate how closely experimental sand resembles ideal coarse and fine sand. If a flow net is drawn, the applicability of Darcy’s law will be explored and discussed

Constituents Inferences of Local Governments Goals and the Relationship Between Political Party and Belief in COVID-19 Misinformation: Cross-sectional Survey of Twitter Followers of State Public Health Departments.

BACKGROUND: Amid the COVID-19 pandemic, social media have influenced the circulation of health information. Public health agencies often use Twitter to disseminate and amplify the propagation of such information. Still, exposure to local government-endorsed COVID-19 public health information does not make one immune to believing misinformation. Moreover, not all health information on Twitter is accurate, and some users may believe misinformation and disinformation just as much as those who endorse more accurate information. This situation is complicated, given that elected officials may pursue a political agenda of re-election by downplaying the need for COVID-19 restrictions. The politically polarized nature of information and misinformation on social media in the United States has fueled a COVID-19 infodemic. Because pre-existing political beliefs can both facilitate and hinder persuasion, Twitter users belief in COVID-19 misinformation is likely a function of their goal inferences about their local government agencies motives for addressing the COVID-19 pandemic. OBJECTIVE: We shed light on the cognitive processes of goal understanding that underlie the relationship between partisanship and belief in health misinformation. We investigate how the valence of Twitter users goal inferences of local governments COVID-19 efforts predicts their belief in COVID-19 misinformation as a function of their political party affiliation. METHODS: We conducted a web-based cross-sectional survey of US Twitter users who followed their states official Department of Public Health Twitter account (n=258) between August 10 and December 23, 2020. Inferences about local governments goals, demographics, and belief in COVID-19 misinformation were measured. State political affiliation was controlled. RESULTS: Participants from all 50 states were included in the sample. An interaction emerged between political party affiliation and goal inference valence for belief in COVID-19 misinformation (∆R 2=0.04; F 8,249=4.78; P<.001); positive goal inference valence predicted increased belief in COVID-19 misinformation among Republicans (β=.47; t 249=2.59; P=.01) but not among Democrats (β=.07; t 249=0.84; P=.40). CONCLUSIONS: Our results reveal that favorable inferences about local governments COVID-19 efforts can accelerate belief in misinformation among Republican-identifying constituents. In other words, accurate COVID-19 transmission knowledge is a function of constituents sentiment toward politicians rather than science, which has significant implications on public health efforts for minimizing the spread of the disease, as convincing misinformed constituents to practice safety measures might be a political issue just as much as it is a health one. Our work suggests that goal understanding processes matter for misinformation about COVID-19 among Republicans. Those responsible for future COVID-19 public health messaging aimed at increasing belief in valid information about COVID-19 should recognize the need to test persuasive appeals that address partisans pre-existing political views in order to prevent individuals goal inferences from interfering with public health messaging

Costs of colour change in fish: food intake and behavioural decisions

Many animals, particularly reptiles, amphibians, fish and cephalopods, have the ability to change their body colour, for functions including thermoregulation, signalling and predator avoidance. Many fish plastically darken their body colouration in response to dark visual backgrounds, and this functions to reduce predation risk. Here, we tested the hypotheses that colour change in fish (1) carries with it an energetic cost and (2) affects subsequent shoal and habitat choice decisions. We demonstrate that guppies (Poecilia reticulata) change colour in response to dark and light visual backgrounds, and that doing so carries an energetic cost in terms of food consumption. By increasing food intake, however, guppies are able to maintain growth rates and meet the energetic costs of changing colour. Following colour change, fish preferentially choose habitats and shoals that match their own body colouration, and maximise crypsis, thus avoiding the need for further colour change but also potentially paying an opportunity cost associated with restriction to particular habitats and social associates. Thus, colour change to match the background is complemented by behavioural strategies, which should act to maximise fitness in variable environments. © 2013. Published by The Company of Biologists Ltd

The ERK MAP Kinase Cascade Mediates Tail Swelling and a Protective Response to Rectal Infection in C. elegans

AbstractThe nematode Caenorhabditis elegans is proving to be an attractive model organism for investigating innate immune responses to infection [1]. Among the known pathogens of C. elegans is the bacterium Microbacterium nematophilum, which adheres to the nematode rectum and postanal cuticle, inducing swelling of the underlying hypodermal tissue and causing mild constipation [2]. We find that on infection by M. nematophilum, an extracellular signal-regulated kinase (ERK) mitogen-activated protein (MAP) kinase cascade mediates tail swelling and protects C. elegans from severe constipation, which would otherwise arrest development and cause sterility. Involvement in pathogen defense represents a new role for ERK MAP kinase signaling in this organism

Anaphoric Structure Emerges Between Neural Networks

Pragmatics is core to natural language, enabling speakers to communicate efficiently with structures like ellipsis and anaphora that can shorten utterances without loss of meaning. These structures require a listener to interpret an ambiguous form - like a pronoun - and infer the speaker's intended meaning - who that pronoun refers to. Despite potential to introduce ambiguity, anaphora is ubiquitous across human language. In an effort to better understand the origins of anaphoric structure in natural language, we look to see if analogous structures can emerge between artificial neural networks trained to solve a communicative task. We show that: first, despite the potential for increased ambiguity, languages with anaphoric structures are learnable by neural models. Second, anaphoric structures emerge between models 'naturally' without need for additional constraints. Finally, introducing an explicit efficiency pressure on the speaker increases the prevalence of these structures. We conclude that certain pragmatic structures straightforwardly emerge between neural networks, without explicit efficiency pressures, but that the competing needs of speakers and listeners conditions the degree and nature of their emergence.Comment: Published as a conference paper at the Annual Meeting of the Cognitive Science Society 2023: 6 Pages, 3 Figures, code available at https://github.com/hcoxec/emerg

Ascorbate deficiency influences the leaf cell wall glycoproteome in Arabidopsis thaliana

© 2014 The Authors. Plant, Cell & Environment published by John Wiley & Sons Ltd.The cell wall forms the first line of interaction between the plant and the external environment. Based on the observation that ascorbate-deficient vtc mutants of Arabidopsis thaliana have increased cell wall peroxidase activity, the cell wall glycoproteome of vtc2-2 was investigated. Glycoproteins were purified from fully expanded leaves by Concanavalin A affinity chromatography and analysed by liquid chromatography quadrupole time-of-flight mass spectrometry. This procedure identified 63 proteins with predicted glycosylation sites and cell wall localization. Of these, 11 proteins were differentially expressed between vtc2-2 and wild type. In particular, PRX33/34 were identified as contributing to increased peroxidase activity in response to ascorbate deficiency. This is the same peroxidase previously shown to contribute to hydrogen peroxide generation and pathogen resistance. Three fasciclin-like arabinogalactan proteins (FLA1, 2 and 8) had lower abundance in vtc2-2. Inspection of published microarray data shows that these also have lower gene expression in vtc1 and vtc2-1 and are decreased in expression by pathogen challenge and oxidative stresses. Ascorbate deficiency therefore impacts expression of cell wall proteins involved in pathogen responses and these presumably contribute to the increased resistance of vtc mutants to biotrophic pathogens.Hazara University (Mansehra, NWFP, Pakistan)Higher Education Commission (Pakistan)BBSRCExeter University Science Strategy Fun

ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning

We present ATOMIC, an atlas of everyday commonsense reasoning, organized through 877k textual descriptions of inferential knowledge. Compared to existing resources that center around taxonomic knowledge, ATOMIC focuses on inferential knowledge organized as typed if-then relations with variables (e.g., "if X pays Y a compliment, then Y will likely return the compliment"). We propose nine if-then relation types to distinguish causes vs. effects, agents vs. themes, voluntary vs. involuntary events, and actions vs. mental states. By generatively training on the rich inferential knowledge described in ATOMIC, we show that neural models can acquire simple commonsense capabilities and reason about previously unseen events. Experimental results demonstrate that multitask models that incorporate the hierarchical structure of if-then relation types lead to more accurate inference compared to models trained in isolation, as measured by both automatic and human evaluation.Comment: AAAI 2019 C