5,190 Matching Annotations
  1. Oct 2017
    1. innovation versus verification

      Innovation refers to coming up with new ideas for research—in other words, generating new hypotheses. Verification refers to checking if a certain idea holds up in subsequent research—in other words, confirming hypotheses.

    2. preregistration

      A preregistration is a document in which researchers compile information on how their study will be run and analyzed before it is conducted. The document often contains information on which research question will be pursued; which hypothesis will be tested; how the data is collected and how the sample is generated; which data is excluded; and how the data will be prepared for analysis and ultimately analyzed. Documenting in advance helps separate confirmatory hypothesis testing from exploratory research.

    3. repeated measurement designs

      A repeated measurement design assesses the same outcome variable at several points in time. For example, let’s say we want to find out whether jogging before class improves students’ ability to follow a class. We might ask 20 students to jog before class and 20 students not to jog before class, and then after class ask them how easy it was for them to follow the class. However, we might be unlucky and conduct our experiment on a day where a particularly difficult topic was covered in class. No one—neither the joggers nor the nonjoggers—could understand the lecture, so all our subjects report they absolutely couldn’t follow the class.

      This problem could be ameliorated if we used a repeated measurement design instead. We would ask our 20 joggers and 20 nonjoggers to either jog nor not jog before class on five days in a row, and then ask them for their ability to follow the class each time. Now, we would have not only one point of measurement from each student, but five points of measurement of their ability to follow the class at several points in time.

    4. within-subjects manipulations

      Within-subjects manipulations refer to situations in experiments where the same person is assigned to multiple experimental conditions.

      For example, let’s say we want to find out which of two different learning techniques (A and B) is more effective in helping students prepare for a vocabulary test. If we conducted a within-subjects manipulation, each student would apply both learning techniques. Let’s say every student must first apply learning technique A, then take a vocabulary test, and then a week later for the next test apply learning technique B. We could now compare following which learning technique the students perform better with.

      In contrast, if we conducted a between-subjects manipulation, each student would only apply one learning technique. We would split the group of students, so that half of them use learning technique A and then take the vocabulary test, while the other students use learning technique B and then take the vocabulary test. Again, we could compare which learning technique the students perform better with.

    5. fixed-effect model

      A fixed effect model is a statistical model which accounts for individual differences in the data which cannot be measured by treating them as nonrandom, or “fixed” at the individual level.

      As an example, let’s say we wanted to study if drinking coffee makes people more likely to cross the street despite a red light. Our outcome variable of interest is how often each subject crosses a street despite a red light on a walk with 10 red traffic lights. The explanatory variable we manipulate for each participant is if they had a cup of coffee before the experiment or a glass of water (our control condition), and we would use this variable to try to explain ignoring red lights. However, there are several other influences on ignoring red lights which we have not accounted for. Next to random and systematic error, we have also not accounted for individual characteristics of the person such as their previous experience with ignoring red lights.

      For instance, have the participants received a fine for this offense? If so, they might be less likely to walk across a red light in our experiment. Using a fixed effect model makes it possible to account for these types of characteristics that rest within each individual participant. This, in turn, gives us a better estimate of the relationship between coffee drinking and crossing red lights, cleaned from other individual-level influences.

    6. multivariate interaction effects

      A multivariate interaction effect is an effect that is the product of several variables working together and influencing each other.

      For example, we might be interested in finding out how water temperature (warm: 38°C; cold: 15°C) affects the body temperature of humans and sea lions. We might find that humans, on average, have a higher body temperature than sea lions, and that body temperature is higher when the body is immersed in warm compared to cold water. However, we might find that a human’s body temperature shows bigger differences between the warm and cold water conditions than the sea lion’s body temperature. Because sea lions have a substantive layer of protective fat, their body temperature does not change as much when water temperature changes, compared to humans. Here, species and water temperature show an interaction effect on body temperature.

    7. standard error

      When experiments are run using a sample instead of the entire population, each sample will show slightly different estimates of the true population parameter. The standard deviation of this range of estimates is called the standard error.

      For example, if we wanted to know the average body mass of Chihuahuas, we couldn’t gather data from every single Chihuahua in the world. If we sampled 20 Chihuahuas, we might find that the average is 2.5 kg. If we sample 20 other Chihuahuas, their average weight might be 2.4 kg. Repeating this process, we would find a range of different average weights in the different samples. Taken together, these means are our estimates for the true average Chihuahua body mass in the population of all Chihuahuas. The dispersion, or the amount of variation in these means, is called standard error.

    8. Wilcoxon signed-rank test

      The Wilcoxon signed-rank test is a statistical procedure used with two related samples. It assesses the differences between each data pair with regard to both direction and size.

      For example, if we wanted to find out if students prefer pasta or salad served in the school cafeteria, we could run an experiment where on three consecutive days, we invite 20 students for lunch and observe how many of them chose pasta and how many chose the salad option. We end up with three pairs of data: On the first day, 18 students chose pasta and two chose salad; on the second day, 15 students chose pasta and four chose salad; on the third day, four students chose pasta and 16 chose salad. The test now calculates the differences between each data pair: On the first day, the difference is 18 – 2 = + 16; on the second day, the difference is 15 – 4 = + 11; on the third day, the difference is 4 – 16 = - 12. Then, the differences are sorted by their absolute size (ignoring the sign: 11, 12, 16) and assigned a rank (11 gets rank 1, 12 gets rank 2, 16 gets rank 3). The sum of the ranks of the positive differences (1 + 3 = 4) is then compared to that of the negative differences (2). The smaller of the two sums of ranks (2) is then compared against a critical value, which informs us whether it is statistically different from zero. If we find a statistically significant result, we can conclude that students have a preference for pasta over salad.

    9.  df

      Df is an abbreviation for the term “degrees of freedom.” The degrees of freedom are an important piece of information for a statistical test, which describes the number of values in the analysis that are free to vary. It depends on how many values are considered (that means, how big the sample size is), and which statistical test is used.

    10. null hypothesis

      The null hypothesis is the assumption that a certain effect does not exist in reality, and that any observations of this effect in data is due to unsystematic error.

    11. exploratory analyses

      An exploratory analysis is conducted in the absence of a specific hypothesis you would like to confirm with your study. They are used to explore the data; that is, to see what data patterns can be found, without trying to prove a specific point.

    12. correlation coefficient (r)

      A correlation coefficient describes the statistical relationship between two variables. It shows both the direction (positive coefficient: as A increases, B increases as well; negative coefficient: as A increases, B decreases), and the strength of the relationship (coefficient close to zero: weak relationship; coefficient close to +/- 1: strong relationship).

      For example, there might be a positive correlation between years of attendance to school and general knowledge: the longer people have attended school, the more knowledge they acquire. On the other hand, there could be a negative correlation between hours spent watching TV and enjoyment of outdoor activities: the more time people spend watching TV, the less they might enjoy going for a hike.

      Importantly, correlation coefficients do not tell us anything about causation.

    13. generalizability

      When we conduct a scientific study, it is often not possible to collect data from every person in the population in the exact situation we want to study. Instead, we often have only a sample of subjects, which we observe in a certain, typical situation. For example, if we want to study adherence to red lights in traffic, we cannot check if every human being will stop at every red light, when driving cars, riding a bike, walking, skateboarding, or using any other means of transportation. We could, however, test 200 pedestrians’ behavior at the traffic light in front of a university.

      Generalizability refers to whether a study’s findings, given its own restricted circumstances, can be extended to make statements about what will be true for the population in general, and for similar situations. For example, imagine we want to study adherence to red lights in traffic by observing 200 pedestrians’ behavior at the traffic light in front of a university. Given that our sample size is small and not representative (because there are mostly students in front of a university, a very specific sample of people), and that the situation we observe is only one facet of participation in traffic (we ignore driving, cycling, skateboarding, etc.), we could not make very good statements about adherence to red lights in general.

    14. sufficient

      Sufficient conditions are one set of circumstances under which a specific effect can be found, but there could be many other circumstances under which the effect would occur.

      For example, if a person asks you for money and you give it to them, asking for money is a sufficient condition. It's enough to make you give the person money. But there are other circumstances in which you would have done the same. For example, you may have given them money in exchange for a bouquet of flowers.

    15. necessary

      Necessary conditions are the circumstance that must be met in order to find a specific effect. If these conditions are not met, the effect cannot be found.

      For example, to find the effect that prosocial people are more likely than selfish people to give change to someone asking for money, a necessary condition would be studying human subjects, not penguins.

    16. predictors

      A predictor (sometimes also called a predictor variable or an independent variable) is a variable that represents the potential reasons why we see a certain result.

      For example, if we wanted to study which factors increase students’ performance in their final exams, we could consider a number of different potential reasons, or predictors, such as how often they did their homework during the past school year, how much time they spent reviewing the materials before the exam, or how well they slept the night before the exam.

    17. random or systematic error

      There are two sources of error which can occur in scientific studies and distort their results.

      Systematic errors are inaccuracies that can be reproduced. For example, imagine we wanted to measure a participant’s weight and we make our participant step on five different scales and measure her weight on each scale 10 times. Four scales report that she weighs 74 kg each time she steps on them. The last scale shows that she weighs 23 kg each time she steps on it. We would say there is a systematic error involved in our study of her weight, because the last scale consistently and erroneously reports her weight as too low.

      Random errors are inaccuracies that occur because there are unknown influences in the environment. For example, imagine we wanted to measure a participant’s weight and had her step on the same scale three times in a row, within one minute. The first time, the scale reports 74.43 kg, the second time 74.34 kg, the third time 74.38 kg. We don’t think that the participant's weight has actually changed in this 1 minute, yet our measurement shows different results, which we would attribute to random errors.

    18. statistically significant

      Results are referred to as statistically significant when we find the result convincing because it is extremely unlikely that the observed effects are due to random chance.

    19. Reproducibility

      Reproducibility is a characteristic of a scientific study, stating that it can be run and run repeatedly, and will in its repetitions yield the same result.

      If an experiment has been reproduced successfully, it has been conducted more than once with similar results each time. Subsequent studies are called reproducing studies, replication studies, or replications.

    20. correlational

      A study is referred to as correlational if it investigates if there is a relationship between two factors without assigning subjects to conditions manipulating a variable of interest. A causal interpretation (that changes in factor A cause changes in factor B) is not possible in correlational studies.

      For example, if we wanted to study the influence of intelligence on students’ biology exam scores in a correlational study, we would first observe students’ intelligence via an IQ test, and then measure their score in the exam. Then we could judge if there was a positive relationship between IQ and exam score: Smarter students might be shown to score better on the test. However, since we did not manipulate students’ IQ to be high or low, we could not say that a higher IQ causes better test scores, only that the two variables are positively related.

    1. polyps

      Though corals may look like plants, they are actually animals. The basic body form of a coral is called a polyp, which has a mouth surrounded by tentacles. Colonial corals consist of many tiny interconnected polyps.

    2. Diadema antillarum

      Diadema antillarum is commonly known as the long-spined sea urchin. Before populations of D. antillarum died off in 1983 in massive numbers, they were a common sight in Caribbean reefs and played an important role in controlling the growth of macroalgae.

    3. arborescent gorgonians

      Gorgonians are part of a group of corals often called "soft corals" due to their lack of a rigid calcified skeleton. Arborescent means "treelike," referring to gorgonians that specifically have upright treelike forms.

    4. Agraria spp.

      Agaricia is a genus of corals that form flat leaf-like or plate-like structures. The "spp." means "multiple species of." So Agaricia spp. means "species of the genus Agaricia."

    5. Acropora palmata

      Acropora palmata is commonly known as Elkhorn coral for its antlerlike appearance. As a result of its complex 3D shape, A. palmata adds significant structure to coral reefs and forms an important habitat for many other marine organisms.

    1. oscillating dipole

      Dipoles are equal magnetic positive and negative charges separated by a distance. In this case oscillate means to cause the electric current to move in a way that influences the dipoles to change and fluctuate. Picture strings vertically tied to a rope in the middle, movement to the rope cause the strings to ripple in the direction they are facing outward. -Kierra Hobdy

    2. neural substrates

      Functional units of the Central Nervous System that are organized systematically based on function and vary in their anatomical location in the body; they all work together to carry out complex body functions, in this case the process of electrolocation. -Kierra Hobdy

    3. interpolating

      The act of inserting one object or substance into another. so for this study , the slices from the EOD records taken through time are put into the slices from EOD records taken through space to create a map that shows the potential and amplitude of the EOD. - Michelle Gomez-Guevara

    4. neurocomputational

      "neuro" refers to the organism's nerves and nervous system and "computional" refers to any act that the organisms does. The study , is measuring the work that the nervous system is conducting in order to use electrolocation. - Michelle Gomez-Guevara

    1. adaptive selection

      The mechanism of choosing the most beneficial trait for survival in an environment, the other traits that are not needed are kept in small reserves, but not wiped out. The rest die off due to having less relative fitness. -Elder

    2. phylogeny

      is the branch of biology that deals with phylogenesis; the evolutionary development and diversification of a species or group of organisms, or of a particular feature of an organism -Melanie

    1. Parafilm

      primarily used in laboratories. It is commonly used for sealing or protecting vessels (such as flasks or cuvettes). It is a ductile, malleable, waterproof, odorless, translucent and cohesive thermoplastic.

      -Mikaela

    1. Linear regression

      Linear Regression is a statistical way to determine the relationship between the independent and dependent variable displayed as a straight line on a graph to indicate a set of real data values. -Sindy

    1. active prostheses

      Prostheses are an artificial part of a body. It can play an unconscious or conscious role in the body. For example, a titanium leg can replace a leg and adapt itself to the host walking patterns.

    2. The double-reversal validation test

      Double-reversal validation test tries to define and remove bias in the data. For example, consider a natural factor that could remove one parameter, and ask if you should counter this evolution to keep the status quo. If so, consider when the natural factor is about to vanish and ask if it is a good thing to act again to reverse the first intervention you made. If not, it is preferable to think that the first intervention is usefull even in the absence of the natural factor.

    3. (CMA-ES)

      Evolution strategy (ES) is an optimisation technique based on the principle of evolution. The Covariance Matrix Adaptation (CMA) is one method that proved itself to be one of the more effective by recalculate at each iteration the Covariance matrix of the distribution.

    4. Exoskeletons

      An exoskeleton refers to a skeleton outside the body - or external skeleton. It has a role of protection in addition to the support role of the internal skeleton. It is commonly found in the insect kingdom.

    5. quadratic approximations

      In Mathematics, approximation means a function can be estimated by a simpler function. The quadratic approximation makes use of the second derivative of the function of interest.

    6. time-varying dynamics

      The dynamic of a system is how this system will evolve with time. Time-varying means here that the system will have different patterns according to the time it was recorded.

    1. RT-PCR

      Reverse transcriptase polymerase chain reaction is a variation of polymerase chain reaction (PCR). RT-PCR begins with an "extra" step in which RNA is reverse transcribed into its DNA complement and then amplified using traditional PCR.

      It is commonly used to analyze the expression patterns of infections and diseases.

    1. inertia

      Inertia is a Newtonian law of motion that describes the tendency of matter to be in an unchanging state of motion when not acted upon by external forces. This could either be an object moving along a trajectory or stationary.

    2. conserved

      Conservation in evolution refers to a trait of a species that remains unchanged over generations. It is maintained and passed down to the next generation because it is usually essential and helps the organism to survive.

  2. Sep 2017
    1. electromotor

      This usually term refers to a machine that is able to produce electricity in order to produce motion. For electric fish and similar organisms , it means their organs have the ability to produce electricity , that is used to produce movement.- Michelle Gomez-Guevara

    2. electrosensory

      The ability of the nervous system if certain organisms to sense electrical impulses in their environment . It's similar to when a person uses their nose to smell a certain scent or odor in the proximity ; in this case the electric fish are able to use their organs to sense electrical pulses nearby. - Michelle Gomez-Guevara

    1. deleterious pleiotropic effects

      You can break this down into two main parts: deleterious, and pleiotropic. "Deleterious" meaning something that is harmful or causes damage, while "pleiotropic" means one gene is adversely affecting other phenotypic traits . In this way we can conclude that a "deleterious pleiotropic effect" is when one gene causes harm or damage to phenotypic traits. -Jake Barbee

    1. biosphere reserve

      a UNESCO label given to an ecosystem with plants and animals of unusual scientific and natural interest to help protect the site UNESCO- United Nations Educational, Scientific, and Cultural Organization -M.A.S.

    1. hydrocoral Millepora spp.

      A hydrocoral looks like a coral, but is actually in the class Hydrozoa rather than the class Anthozoa, like true corals. Millepora hydrocorals are also known as fire corals due to their painful sting.

    2. significant at P < .001, Mann-Whitney U test

      The Mann-Whitney U test is a statistical test used when values are not normally distributed. Here, it is used to compare live tissue coverage before and after the hurricane. The P-value of less than 0.001 indicates that there was a statistically significant difference between the two groups (a P-value of less than 0.05 is commonly accepted as statistically significant under convention).

    3. natural experiment

      When natural events (i.e. fires, hurricanes, or other disturbances) happen to only some areas, scientists can study the effects by comparing affected and unaffected sites.

      This is a natural experiment.

    4. Coral reefs

      Corals are a group of colonial marine animals that form hard calcium skeletons. They have stinging cells that can be used to catch and kill small prey, but they also often carry symbiotic algae inside that they can use to convert sunlight into cellular energy.

      When corals live together in large groups, they can form a buildup of sediment and minerals in the ocean called a reef. The complex structures of reefs create habitats for many other ocean animals.

    1. geographic centroids of the alleles

      In this study the geographic centroid of an allele is the average location calculated from every location where the allele is present. Such that if an allele is most abundant in Portugal than its geographic centroid will be in Portugal.

    2. heritable variation

      Heritability is a measurement of how much variation in a trait is caused by genetic factors, rather than environmental factors. Heritable variation occurs in a population when the influence of genetic factors on a trait differs between individuals.

    3. selection

      Environmental pressures result in individuals with certain characteristics reproducing more than others. This results in these individuals genes becoming more common in the population. This is the process of evolution.

    4. alleles

      A variation of a gene. Most multi-cellular organisms, including Arabidopsis, have duplicated chromosomes meaning that every gene is present twice in the genome and hence may have two variations of a gene.

    5. fitness

      This evolutionary term describes how successful an organism is at reproducing and passing its genes through the next generations. Factors such as lifespan and percentage of offspring that survive contribute to this.

    6. genome-wide association study

      This method searches for small variations in the genomes of a large population and investigates whether these variations are associated with certain characteristics. This helps researchers identify which genes might control traits in an organism. The method is used in a large variety of research including human and plant science.

    7. Local adaptation

      Local adaptation occurs when a population that is spatially separate from others of its species faces selective pressures unique to its environment. Therefore, the population evolves to be best suited to its local environment.

    1. Inertial entrainment

      Inertial entrainment, (see inertia, already referenced) describes the physical dynamics of motion caught in stasis.

      Entrainment uses the law of inertia as a method of synchronising two events. In this case, the water travelling in constant motion with the tongue.

    2. Froude number

      Froude number, a quantity without dimensions, describes water flowing in an open channel. It is calculated as a ratio of flow of inertia (the ease in which water flows) and gravity (water moving down a surface).

    3. Gaussian profile

      The Gaussian profile, commonly referred to as ‘the normal distribution’, is characterised by a graph representing a bell shaped curve. The ‘bell’ of the curve represents a probability distribution, giving the approximation of an event. In this case, the graph characterises the vertical velocity, where the highest point of the curve shows the likeliest vertical velocity of the cats tongue.

    4. physiological

      Physiology refers to the area of biology studying the function of living organism and their constituent parts.

      Physiological constraits are limits of the ability of the organism based on the function of the organism.

    5. adhesion

      Adhesion refers to the attraction of the molecular properties of a liquid to a surface wall. This will define the particular adhesion between the liquid and the surface of the tongue.

      Antonym: cohesion (water molecules attraction and hydrogen bond to other molecules of water).

    6. temporal derivative

      Derivative refers to the rate of the change of a function. Temporal refers to the time component of the function.

      A temporal derivative is the rate of change of the function with respect to time.

    1. metabolic energy cost,

      Metabolism is how the body will use "fuel", such as sugar, for the cell activity. Metabolic energy cost referes to the amount of energy needed for a specific metabolic task in an organism.