"Leap before you look": Conditions that suppress explicit, knowledge-based learning during visuomotor adaptation.

When learning a novel visuomotor mapping (e.g., mirror writing), accuracy can improve quickly through explicit, knowledge-based learning (e.g., aim left to go right), but after practice, implicit or procedural learning takes over, producing fast, natural movements. This procedural learning occurs automatically, whereas it has recently been found that knowledge-based learning can be suppressed by the gradual introduction of the novel mapping when participants must make fast movements and visuomotor perturbations are small (e.g., 30° rotations). We explored the range of task instructions, perturbation parameters, and feedback that preclude or encourage this suppression. Using a reaching task with a rotation between screen position and movement direction, we found that knowledge-based learning could be suppressed even for an extreme 90° rotation, but only if it was introduced gradually and only under instructions to move quickly. If the rotation was introduced abruptly or if instructions emphasized accuracy over speed, knowledge-based learning occurred. A second experiment indicated that knowledge-based learning always occurred in the absence of continuous motion feedback, evidenced by the time course of learning, the aftereffects of learning when the rotation was abruptly removed, and the outcome of formal model comparison between a dual-state (procedural and knowledge-based) versus a single-state (procedural only) learning model of the data. A third experiment replicated the findings and verified that the knowledge-based component of the dual-state model corresponded to explicit aiming, whereas the procedural component was slow to unlearn. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Electrokinetic transport of CTAB induces multiphasic behavior during capillary adsorption and desorption.

Cationic surfactant coatings (e.g., CTAB) are commonly used in CE to control EOF and thereby improve separation efficiencies. However, our understanding of surfactant adsorption and desorption dynamics under EOF conditions is limited. Here, we apply automated zeta potential analysis to study the adsorption and desorption kinetics of CTAB in a capillary under different transport conditions: diameter, length, voltage alternation pattern and frequency, and applied pressure. In contrast to other studies, we observe slower kinetics at distinct capillary wall zeta potential ranges. Within these ranges, which we call "stagnant regimes," the EOF mobility significantly counteracts the electrophoretic (EP) mobility of CTA+ and hinders the net transport. By constructing a numerical model to compare with our experiments and recasting our experimental data in terms of the net CTA+ transport volume normalized by surface area, we reveal that the EP mobility of CTA+ and the capillary surface-area-to-volume ratio dictate the zeta potential range and the duration of the stagnant regime and thereby govern the overall reaction kinetics. Our results indicate that further transport-oriented studies can significantly aid in the understanding and design of electrokinetic systems utilizing CTAB and other charged surfactants.

The push-pull of serial dependence effects: Attraction to the prior response and repulsion from the prior stimulus.

In the "serial dependence" effect, responses to visual stimuli appear biased toward the last trial's stimulus. However, several kinds of serial dependence exist, with some reflecting prior stimuli and others reflecting prior responses. One-factor analyses consider the prior stimulus alone or the prior response alone and can consider both variables only via separate analyses. We demonstrate that one-factor analyses are potentially misleading and can reach conclusions that are opposite from the truth if both dependencies exist. To address this limitation, we developed two-factor analyses (model comparison with hierarchical Bayesian modeling and an empirical "quadrant analysis"), which consider trial-by-trial combinations of prior response and prior stimulus. Two-factor analyses can tease apart the two dependencies if applied to a sufficiently large dataset. We applied these analyses to a new study and to four previously published studies. When applying a model that included the possibility of both dependencies, there was no evidence of attraction to the prior stimulus in any dataset, but there was evidence of attraction to the prior response in all datasets. Two of the datasets contained sufficient constraint to determine that both dependencies were needed to explain the results. For these datasets, the dependency on the prior stimulus was repulsive rather than attractive. Our results are consistent with the claim that both dependencies exist in most serial dependence studies (the two-dependence model was not ruled out for any dataset) and, furthermore, that the two dependencies work against each other.

Gestalt formation promotes awareness of suppressed visual stimuli during binocular rivalry.

Continuous flash suppression leverages binocular rivalry to render observers unaware of a static image for several seconds. To achieve this effect, rapidly flashing noise masks are presented to the dominant eye while a static stimulus is presented to the non-dominant eye. Eventually "breakthrough" occurs, wherein awareness shifts to the static image shown to the non-dominant eye. We tested the hypothesis that Gestalt formation can promote breakthrough. In two experiments, we presented pacman-shaped objects that might or might not align to form illusory Kanizsa objects. To measure the inception of breakthrough, observers were instructed to press a key at the moment of partial breakthrough. After pressing the key, which stopped the trial, observers reported how many pacmen were seen and where they were located. Supporting the Gestalt hypothesis, breakthrough was faster when the pacmen were aligned and observers more often reported pairs of pacmen if they were aligned. To address whether these effects reflected illusory shape perception, a computational model was applied to the pacman report distributions and breakthrough times for an experiment with four pacmen. A full account of the data required an increased joint probability of reporting all four pacmen, suggesting an influence of a perceived illusory cross.

Dynamics of mitochondrial adaptation and energy metabolism in rainbow trout (Oncorhynchus mykiss) in response to sustainable diet and temperature.

Impacts of plant-based ingredients and temperatures on energy metabolism in rainbow trout was investigated. A total of 288 fish (mean body weight: 45.6 g) were fed four isocaloric, isolipidic, and isonitrogenous diets containing 40% protein and 20% lipid and formulated as 100% animal-based protein (AP) and a blend of 50% fish oil (FO) and 50% camelina oil (CO); 100% AP and100% CO; 100% plant-based protein (PP) and a blend of 50% FO and 50% CO or 100% PP and 100% CO at 14 or 18 °C for 150 d. Diet did not significantly affect weight gain (WG) (P = 0.1902), condition factor (CF) (P = 0.0833) or specific growth rate (SGR) (P = 0.1511), but diet significantly impacted both feed efficiency (FE) (P = 0.0076) and feed intake (FI) (P = 0.0076). Temperature did not significantly affect WG (P = 0.1231), FE (P = 0.0634), FI (P = 0.0879), CF (P = 0.8277), or SGR (P = 0.1232). The diet × temperature interaction did not significantly affect WG (P = 0.7203), FE (P = 0.4799), FI (P = 0.2783), CF (P = 0.5071), or SGR (P = 0.7429). Furthermore, temperature did not influence protein efficiency ratio (P = 0.0633), lipid efficiency ratio (P = 0.0630), protein productive value (P = 0.0756), energy productive value (P = 0.1048), and lipid productive value (P = 0.1386); however, diet had significant main effects on PER (P = 0.0076), LPV (P = 0.0075), and PPV (P = 0.0138). Temperature regimens induced increased activities of mitochondrial complexes I (P = 0.0120), II (P = 0.0008), III (P = 0.0010), IV (P < 0.0001), V (P < 0.0001), and citrate synthase (CS) (P < 0.0001) in the intestine; complexes I (P < 0.0001), II (P < 0.0001), and CS (P = 0.0122) in the muscle; and complexes I (P < 0.0001), II (P < 0.0001), and III (P < 0.0001) in the liver. Similarly, dietary composition significantly affected complexes I (P < 0.0001), II (P < 0.0001), IV (P < 0.0001), V (P < 0.0001), and CS (P < 0.0001) in the intestine; complexes I (P < 0.0001), II (P < 0.0001), III (P = 0.0002), IV (P < 0.0001), V (P = 0.0060), and CS (P < 0.0001) in the muscle; and complexes I (P < 0.0001), II (P < 0.0001), IV (P < 0.0001), V (P < 0.0001), and CS (P < 0.0001) in the liver activities except complex III activities in intestine (P = 0.0817) and liver (P = 0.4662). The diet × temperature interaction impacted CS activity in the intestine (P = 0.0010), complex II in the muscle (P = 0.0079), and complexes I (P = 0.0009) and II (P = 0.0348) in the liver. Overall, comparing partial to full dietary substitution of FO with CO, partial dietary replacement showed similar effects on complex activities.

Diets are one of the most important consideration in aquaculture production as more than 50% of production costs are incurred in raising cultured fish to market size. As the price of FM and FO continues to increase, it is necessary to seek alternative sources of proteins and oils for sustainable aquaculture development. Plant-based ingredient sources have appeared as sustainable alternatives; however, it is uncertain whether the uses of plant-based alternatives will be appropriate in securing the production of carnivorous aquaculture species in the context of global warming, with studies postulating on the potential effects of climate change on fish growth and health. A study was conducted to examine how the replacement of FM and FO with sustainable plant-based protein and camelina oil (CO) as ingredient sources at 14 or 18 °C would affect the growth performance, nutrient utilization efficiencies, and mitochondrial enzyme activity in rainbow trout. Based on the results, mitochondrial enzyme activities were generally higher at 18 °C and CO could replace 50% dietary FO without negative effects on rainbow trout. Overall, our study demonstrated that animal-based protein with CO is as good as animal-based with FO for growth and health, thus providing potentially sustainable diet options for aquaculture.

Differentiating Between Sexual Offending and Violent Non-sexual Offending in Men With Schizophrenia Spectrum Disorders Using Machine Learning.

Forensic psychiatric populations commonly contain a subset of persons with schizophrenia spectrum disorders (SSD) who have committed sex offenses. A comprehensive delineation of the features that distinguish persons with SSD who have committed sex offenses from persons with SSD who have committed violent non-sex offenses could be relevant to the development of differentiated risk assessment, risk management and treatment approaches. This analysis included the patient records of 296 men with SSD convicted of at least one sex and/or violent offense who were admitted to the Centre for Inpatient Forensic Therapy at the University Hospital of Psychiatry Zurich between 1982 and 2016. Using supervised machine learning, data on 461 variables retrospectively collected from the records were compared with respect to their relative importance in differentiating between men who had committed sex offenses and men who had committed violent non-sex offenses. The final machine learning model was able to differentiate between the two types of offenders with a balanced accuracy of 71.5% (95% CI = [60.7, 82.1]) and an AUC of .80 (95% CI = [.67, .93]). The main distinguishing features included sexual behaviours and interests, psychopathological symptoms and characteristics of the index offense. Results suggest that when assessing and treating persons with SSD who have committed sex offenses, it appears to be relevant to not only address the core symptoms of the disorder, but to also take into account general risk factors for sexual recidivism, such as atypical sexual interests and sexual preoccupation.

Nanofluidic diodes based on asymmetric bio-inspired surface coatings in straight glass nanochannels.

In this study, we present nanofluidic diodes fabricated from straight glass nanochannels and functionalized using bio-inspired polydopamine (PDA) and poly-L-lysine (PLL) coatings. The resulting PDA coatings are shown to be asymmetric due to a combination of transport considerations which can be leveraged to provide a measure of control over the effective channel geometry. By subsequently introducing a layer of amine-bearing PLL chains covalently bound to the PDA, we enhance heterogeneities in the charge and ion distributions within the channel and enable significant current rectification between forward-bias and reverse-bias modes; our PDA-PLL-coated channels yielded a rectification ratio greater than 1000 in a 100 nm channel filled with 0.01× phosphate-buffered saline solution (PBS). We further demonstrated that at higher ionic strength conditions, reducing the solution pH increased the number of protonated amines within the PLL layer, amplifying the charge disparities along the channel and leading to greater rectification. As nanofluidic diodes with bipolar surface charge distributions tend to provide superior performance compared to those with a single wall charge polarity, we imposed a more bipolar charge distribution in our devices by partially coating our PDA-PLL-coated channels with negatively charged polyacrylic acid (PAA). These enhanced bipolar channels exhibited greater current rectification than the PDA-PLL-coated channels, reaching rectification ratios in excess of 100 even in more physiologically-relevant 1× PBS solutions. Our fabrication approach and the results herein provide a promising platform from which the scientific community can build upon in the relentless endeavor for improved sensitivity in biosensors and other analytical devices.

Safety evaluation of the Guardian device on the common carotid artery in sheep.

Background: Pulse pressure intensity in middle-aged adults is a risk factor for dementia. The Guardian device (The Brain Protection Company, Sydney, Australia) has been developed to reduce pulse pressure, as a potential therapy. Objectives: The aim of this study was to evaluate the safety of the Guardian, a novel pulse modulation device designed to reduce the intensity of the pulse pressure that penetrates into the cerebral small vessels. The Guardian is a helix that gently wraps around the common carotid artery (CCA) to slightly change its shape, to absorb pulsatility, without lowering flow. Methods: The Guardian was implanted bilaterally on the CCAs of 10 mature sheep for chronic implant periods of 3, 6 or 8 months. The ratio of internal device diameter to outer diameter of the CCA varied from 63% to 92% (n = 20). The implant position on the vessel was marked surgically at implant. Gross pathology and histopathology of the CCA were examined at 3- and 6-months post explant. Most devices were explanted using open surgery, however minimally invasive surgical explant techniques were examined in 2 animals to assess the potential of this approach for explant in humans if required. Results: The Guardian was successfully implanted with no adverse events, and minimally invasive explant appeared to be viable for removal. Following implant, the device was surrounded by a thin fibrous capsule, with similar pathology at 3- and 6-months. Minimal or no movement was observed. CCA sections appeared histologically normal, with no evidence of thrombosis, stenosis, fibrosis, chronic inflammatory response, or vessel degeneration. Conclusions: The feasibility of surgical implantation and biomaterial safety of the Guardian was confirmed over 8 months. Minimally invasive explant of the Guardian has the potential to be viable. Further work is required to demonstrate efficacy in vitro and/or in vivo before evaluation in humans.

Correlates of Social Isolation in Forensic Psychiatric Patients with Schizophrenia Spectrum Disorders: An Explorative Analysis Using Machine Learning.

The detrimental effects of social isolation on physical and mental health are well known. Social isolation is also known to be associated with criminal behavior, thus burdening not only the affected individual but society in general. Forensic psychiatric patients with schizophrenia spectrum disorders (SSD) are at a particularly high risk for lacking social integration and support due to their involvement with the criminal justice system and their severe mental illness. The present study aims to exploratively evaluate factors associated with social isolation in a unique sample of forensic psychiatric patients with SSD using supervised machine learning (ML) in a sample of 370 inpatients. Out of >500 possible predictor variables, 5 emerged as most influential in the ML model: attention disorder, alogia, crime motivated by ego disturbances, total PANSS score, and a history of negative symptoms. With a balanced accuracy of 69% and an AUC of 0.74, the model showed a substantial performance in differentiating between patients with and without social isolation. The findings show that social isolation in forensic psychiatric patients with SSD is mainly influenced by factors related to illness and psychopathology instead of factors related to the committed offences, e.g., the severity of the crime.

Self-Harm Among Forensic Psychiatric Inpatients With Schizophrenia Spectrum Disorders: An Explorative Analysis.

The burden of self-injury among offenders undergoing inpatient treatment in forensic psychiatry is substantial. This exploratory study aims to add to the previously sparse literature on the correlates of self-injury in inpatient forensic patients with schizophrenia spectrum disorders (SSD). Employing a sample of 356 inpatients with SSD treated in a Swiss forensic psychiatry hospital, patient data on 512 potential predictor variables were retrospectively collected via file analysis. The dataset was examined using supervised machine learning to distinguish between patients who had engaged in self-injurious behavior during forensic hospitalization and those who had not. Based on a combination of ten variables, including psychiatric history, criminal history, psychopathology, and pharmacotherapy, the final machine learning model was able to discriminate between self-injury and no self-injury with a balanced accuracy of 68% and a predictive power of AUC = 71%. Results suggest that forensic psychiatric patients with SSD who self-injured were younger both at the time of onset and at the time of first entry into the federal criminal record. They exhibited more severe psychopathological symptoms at the time of admission, including higher levels of depression and anxiety and greater difficulty with abstract reasoning. Of all the predictors identified, symptoms of depression and anxiety may be the most promising treatment targets for the prevention of self-injury in inpatient forensic patients with SSD due to their modifiability and should be further substantiated in future studies.

Multiscale responses and recovery of soils to wildfire in a sagebrush steppe ecosystem.

Ecological theory predicts a pulse disturbance results in loss of soil organic carbon and short-term respiration losses that exceed recovery of productivity in many ecosystems. However, fundamental uncertainties remain in our understanding of ecosystem recovery where spatiotemporal variation in structure and function are not adequately represented in conceptual models. Here we show that wildfire in sagebrush shrublands results in multiscale responses that vary with ecosystem properties, landscape position, and their interactions. Consistent with ecological theory, soil pH increased and soil organic carbon (SOC) decreased following fire. In contrast, SOC responses were slope aspect and shrub-microsite dependent, with a larger proportional decrease under previous shrubs on north-facing aspects compared to south-facing ones. In addition, respiratory losses from burned aspects were not significantly different than losses from unburned aspects. We also documented the novel formation of soil inorganic carbon (SIC) with wildfire that differed significantly with aspect and microsite scale. Whereas pH and SIC recovered within 37 months post-fire, SOC stocks remained reduced, especially on north-facing aspects. Spatially, SIC formation was paired with reduced respiration losses, presumably lower partial pressure of carbon dioxide (pCO2), and increased calcium availability, consistent with geochemical models of carbonate formation. Our findings highlight the formation of SIC after fire as a novel short-term sink of carbon in non-forested shrubland ecosystems. Resiliency in sagebrush shrublands may be more complex and integrated across ecosystem to landscape scales than predicted based on current theory.

A modeling framework for determining modulation of neural-level tuning from non-invasive human fMRI data.

Many neuroscience theories assume that tuning modulation of individual neurons underlies changes in human cognition. However, non-invasive fMRI lacks sufficient resolution to visualize this modulation. To address this limitation, we developed an analysis framework called Inferring Neural Tuning Modulation (INTM) for "peering inside" voxels. Precise specification of neural tuning from the BOLD signal is not possible. Instead, INTM compares theoretical alternatives for the form of neural tuning modulation that might underlie changes in BOLD across experimental conditions. The most likely form is identified via formal model comparison, with assumed parametric Normal tuning functions, followed by a non-parametric check of conclusions. We validated the framework by successfully identifying a well-established form of modulation: visual contrast-induced multiplicative gain for orientation tuned neurons. INTM can be applied to any experimental paradigm testing several points along a continuous feature dimension (e.g., direction of motion, isoluminant hue) across two conditions (e.g., with/without attention, before/after learning).

Model Building in Forensic Psychiatry: A Machine Learning Approach to Screening Offender Patients with SSD.

Today's extensive availability of medical data enables the development of predictive models, but this requires suitable statistical methods, such as machine learning (ML). Especially in forensic psychiatry, a complex and cost-intensive field with risk assessments and predictions of treatment outcomes as central tasks, there is a need for such predictive tools, for example, to anticipate complex treatment courses and to be able to offer appropriate therapy on an individualized basis. This study aimed to develop a first basic model for the anticipation of adverse treatment courses based on prior compulsory admission and/or conviction as simple and easily objectifiable parameters in offender patients with a schizophrenia spectrum disorder (SSD). With a balanced accuracy of 67% and an AUC of 0.72, gradient boosting proved to be the optimal ML algorithm. Antisocial behavior, physical violence against staff, rule breaking, hyperactivity, delusions of grandeur, fewer feelings of guilt, the need for compulsory isolation, cannabis abuse/dependence, a higher dose of antipsychotics (measured by the olanzapine half-life) and an unfavorable legal prognosis emerged as the ten most influential variables out of a dataset with 209 parameters. Our findings could demonstrate an example of the use of ML in the development of an easy-to-use predictive model based on few objectifiable factors.

A visual sense of number emerges from divisive normalization in a simple center-surround convolutional network.

Many species of animals exhibit an intuitive sense of number, suggesting a fundamental neural mechanism for representing numerosity in a visual scene. Recent empirical studies demonstrate that early feedforward visual responses are sensitive to numerosity of a dot array but substantially less so to continuous dimensions orthogonal to numerosity, such as size and spacing of the dots. However, the mechanisms that extract numerosity are unknown. Here, we identified the core neurocomputational principles underlying these effects: (1) center-surround contrast filters; (2) at different spatial scales; with (3) divisive normalization across network units. In an untrained computational model, these principles eliminated sensitivity to size and spacing, making numerosity the main determinant of the neuronal response magnitude. Moreover, a model implementation of these principles explained both well-known and relatively novel illusions of numerosity perception across space and time. This supports the conclusion that the neural structures and feedforward processes that encode numerosity naturally produce visual illusions of numerosity. Taken together, these results identify a set of neurocomputational properties that gives rise to the ubiquity of the number sense in the animal kingdom.

Electrooxidation of Phenol on Polyelectrolyte Modified Carbon Electrodes for Use in Insulin Pump Infusion Sets.

BACKGROUND: Many type 1 diabetes patients using continuous subcutaneous insulin infusion (CSII) suffer from the phenomenon of unexplained hypoglycemia or "site loss." Site loss is hypothesized to be caused by toxic excipients, for example, phenolic compounds within insulin formulations that are used as preservatives and stabilizers. Here, we develop a bioinspired polyelectrolyte-modified carbon electrode for effective electrooxidative removal of phenol from insulin and eventual incorporations into an infusion set of a CSII device. METHODS: We modified a carbon screen printed electrode (SPE) with poly-L-lysine (PLL) to avoid passivation due to polyphenol deposition while still removing phenolic compounds from insulin injections. We characterized these electrodes using scanning electron microscopy (SEM) and electrochemical impedance spectroscopy (EIS) and compared their data with data from bare SPEs. Furthermore, we performed electrochemical measurements to determine the extent of passivation, and high-performance liquid chromatography (HPLC) measurements to confirm both the removal of phenol and the integrity of insulin after phenol removal. RESULTS: Voltammetry measurements show that electrode passivation due to polyphenol deposition is reduced by a factor of 2X. HPLC measurements confirm a 10x greater removal of phenol by our modified electrodes relative to bare electrodes. CONCLUSION: Using bioinspired polyelectrolytes to modify a carbon electrode surface aids in the electrooxidation of phenolic compounds from insulin and is a step toward integration within an infusion set for mitigating site loss.

The effects of microclimatic winter conditions in urban areas on the risk of establishment for Aedes albopictus.

The tiger mosquito, Aedes albopictus, has adjusted well to urban environments by adopting artificial water containers as oviposition sites. Its spread in temperate regions is favoured by the deposition of cold-tolerant diapausing eggs that survive winter temperatures to a certain degree. The probability of establishment in new geographical areas is estimated using predictive models usually based on meteorological data measured at coarse resolution. Here, we investigated if we could obtain more precise and realistic risk scenarios for the spread of Ae. albopictus when considering the winter microclimatic conditions of catch basins, one of the major sites of oviposition and egg overwintering in temperate urban areas. We monitored winter microclimatic conditions of catch basins in four Swiss cities and developed a regression model to predict the average microclimatic temperatures of catch basins, based on available meteorological parameters, accounting for the observed differences between cities. We then used the microclimatic model to correct the predictions of our previously developed risk model for the prediction of Ae. albopictus establishment. Comparison of the predictive model's results based on local climate data and microclimate data indicated that the risk of establishment for Ae. albopictus in temperate urban areas increases when microhabitat temperatures are considered.

Setting adequate wages for workers: Managers' work experience, incentive scheme and gender matter.

Many societies report an increasingly divergent development of managers' salaries compared to that of their workforce. Moreover, there is often a lack in diversity amongst managerial boards. We investigate the role of managers' gender and incentive scheme on wages chosen for workers by conducting two experimental studies. The data reveal male managers respond in more self-oriented ways to their incentive scheme. Further, we find that experience with the workers' task can increase appreciation of workers. Effects are strongest when the managers' compensation scheme rules out self-orientation. Overall, female managers display more consistency in choosing adequate wages for workers, i.e. their choices are less affected by incentives. An increase in diversity may thus help reducing salary disparities and foster work atmosphere.

Hiding in plain sight: How incorporating honest discussion of racial and social (in)justice into medical education can inspire change.

The carnage wrought by systemic racism through social, judicial, and health injustices compels us to work towards a system that is fair and just for patients and colleagues. The evidence that change is necessary in medicine is hiding in plain sight in literature, oral histories, medical records, and news media. Notwithstanding this evidence, changing a system 400 years in the making will require a major paradigm shift. One of the many ways our department sought to catalyze such a shift was through media consumption, reflection, and discussion. Reading and studying literature and humanities in medicine can awaken our consciousness by making medicine an embodied practice that considers the totality of patients' lives in ways that a disembodied, purely scientific approach cannot. Thus, we started a Racial and Social Justice Book Club to normalize discussions about racial and social (in)justice and examine everything through an anti-racist lens. Herein, we describe our experiences in the inaugural year of the Book Club, a space to lend credence and dignity to the voices, experiences, and stories of folks who have long been marginalized by power structures in America, including medicine.

A 'compensatory selection' effect with standardized tests: Lack of correlation between test scores and success is evidence that test scores are predictive of success.

We introduce the statistical concept of 'compensatory selection', which arises when selecting a subset of applicants based on multiple predictors, such as when standardized test scores are used in combination with other predictors required in a school application (e.g., previous grades, references letters, and personal statements). Post-hoc analyses often fail to find a positive correlation between test scores and subsequent success, and this failure is sometimes taken as evidence against the predictive validity of the standardized test. The present analysis reveals that the failure to find a negative correlation indicates that the standardized test is in fact a valid predictor of success. This is due to compensation between predictors during selection: Some students are admitted despite a low test score because their application is exceptional in other respects, while other students are admitted primarily based on a high test score despite weakness in the rest of their application. This compensatory selection process introduces a negative correlation between test scores and other predictors among those admitted (a 'collider bias' or 'Berkson's paradox' effect). If test scores are valid predictors of success, this negative correlation between the predictors counteracts the positive correlation between test scores and success that would have been observed if all applicants were admitted. If test scores are not predictive of success, but were nevertheless used in a compensatory selection process, there would be a spurious negative correlation between test scores and success (i.e., an admitted student with a weak application except for a high test score would be unlikely to succeed). The selection effect that is described here is fundamentally different from the well-known 'restricted range' problem and can powerfully alter results even in situations that accept most applicants.

Risk-Based Mapping Tools for Surveillance and Control of the Invasive Mosquito Aedes albopictus in Switzerland.

BACKGROUND: In Switzerland, Aedes albopictus is well established in Ticino, south of the Alps, where surveillance and control are implemented. The mosquito has also been observed in Swiss cities north of the Alps. Decision-making tools are urgently needed by the local authorities in order to optimize surveillance and control. METHODS: A regularized logistic regression was used to link the long-term dataset of Ae. albopictus occurrence in Ticino with socioenvironmental predictors. The probability of establishment of Ae. albopictus was extrapolated to Switzerland and more finely to the cities of Basel and Zurich. RESULTS: The model performed well, with an AUC of 0.86. Ten socio-environmental predictors were selected as informative, including the road-based distance in minutes of travel by car from the nearest cell established in the previous year. The risk maps showed high suitability for Ae. albopictus establishment in the Central Plateau, the area of Basel, and the lower Rhone Valley in the Canton of Valais. CONCLUSIONS: The areas identified as suitable for Ae. albopictus establishment are consistent with the actual current findings of tiger mosquito. Our approach provides a useful tool to prompt authorities' intervention in the areas where there is higher risk of introduction and establishment of Ae. albopictus.