This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

Adaptive Control

Single-cell RNA sequencing (scRNA-seq) data are commonly affected by technical artifacts known as "doublets," which limit cell throughput and lead to spurious biological conclusions. Here, we present a computational doublet detection tool-DoubletFinder-that identifies doublets using only gene expression data. DoubletFinder predicts doublets according to each real cell's proximity in gene expression space to artificial doublets created by averaging the transcriptional profile of randomly chosen cell pairs. We first use scRNA-seq datasets where the identity of doublets is known to show that DoubletFinder identifies doublets formed from transcriptionally distinct cells. When these doublets are removed, the identification of differentially expressed genes is enhanced. Second, we provide a method for estimating DoubletFinder input parameters, allowing its application across scRNA-seq datasets with diverse distributions of cell types. Lastly, we present "best practices" for DoubletFinder applications and illustrate that DoubletFinder is insensitive to an experimentally validated kidney cell type with "hybrid" expression features.

DoubletFinder: Doublet Detection in Single-Cell RNA Sequencing Data Using Artificial Nearest Neighbors.

Goals Reduce greenhouse gas emissions to 1990 levels by 2020. All new residential buildings meet zero-­‐net-­‐energy (ZNE) goals by 2020, all new commercial buildings by 2030. Why it is Important Combustion of fossil fuels to power vehicles and buildings is the largest source of greenhouse gas emissions in the state. Energy use in residential and commercial buildings and the industrial sector is the second largest source of greenhouse gas (GHG) emissions in California. California has significantly reduced building energy demand through a series of progressive appliance and building standards that promote energy efficiency. These standards, combined with the state's mild climate, mean that California has among the lowest per capita electricity consumption rates of any state in the nation. In 2011, California had the fifth lowest per capita energy demand of any state. 1 Recent Trends Energy consumption occurs in all sectors of state's economy. In California, the transportation sector accounts for the highest share of the state's energy consumption. This demand is met, primarily, through the combustion of fossil fuels to power passenger cars and trucks. Consumption in the industrial, commercial, and industrial sectors is primarily accounted for by electricity and natural gas consumption. 1 Electricity use per capita in California is well below the national average 2 , owing to the state's appliance and building energy efficiency standards and mild climate. Even as the state's population has continued to grow, per capita electricity use has remained steady, while the national average has increased slightly. When comparing per capita energy consumption by sector, it is clear that California's energy efficiency efforts have been most successful in the building sector.

Energy on demand

https://jnnp.bmj.com/content/jnnp/26/5/476.1.full.pdf

The perception of causality

/pdf/handbook-of-the-psychology-of-aging-5th-ed-2h2dalfk25.pdf

Handbook of the Psychology of Aging, 5th ed

Valued by statisticians, enforced by editors, and confused by many authors, standard errors (SEs) and confidence intervals (CIs) remain a controversial issue in the psychological literature. This is especially true for the proper use of CIs for within-subjects designs, even though several recent publications elaborated on possible solutions for this case. The present paper presents a short and straightforward introduction to the basic principles of CI construction, in an attempt to encourage students and researchers in cognitive psychology to use CIs in their reports and presentations. Focusing on a simple but prevalent case of statistical inference, the comparison of two sample means, we describe possible CIs for between- and within-subjects designs. In addition, we give hands-on examples of how to compute these CIs and discuss their relation to classical t-tests.

/pdf/confidence-intervals-for-two-sample-means-calculation-205ewgoan7.pdf

Confidence intervals for two sample means: Calculation, interpretation, and a few simple rules

A commentary on
Assessing bimodality to detect the presence of a dual cognitive process

by Freeman, J. B., and Dale, R. (2013). Behav. Res. Methods 45, 83–97. doi: 10.3758/s13428-012-0225-x

/pdf/good-things-peak-in-pairs-a-note-on-the-bimodality-1k8jjfwqz2.pdf

Good things peak in pairs: a note on the bimodality coefficient.

In psychological experiments, participants are typically instructed to respond as fast as possible without sacrificing accuracy. How they interpret this instruction and, consequently, which speed-accuracy trade-off they choose might vary between experiments, between participants, and between conditions. Consequently, experimental effects can appear unpredictably in either RTs or error rates (i.e., accuracy). Even more problematic, spurious effects might emerge that are actually due only to differential speed-accuracy trade-offs. An often-suggested solution is the inverse efficiency score (IES; Townsend & Ashby, 1983), which combines speed and accuracy into a single score. Alternatives are the rate-correct score (RCS; Woltz & Was, 2006) and the linear-integrated speed-accuracy score (LISAS; Vandierendonck, 2017, 2018). We report analyses on simulated data generated with the standard diffusion model (Ratcliff, 1978) showing that IES, RCS, and LISAS put unequal weights on speed and accuracy, depending on the accuracy level, and that these measures are actually very sensitive to speed-accuracy trade-offs. These findings stand in contrast to a fourth alternative, the balanced integration score (BIS; Liesefeld, Fu, & Zimmer, 2015), which was devised to integrate speed and accuracy with equal weights. Although all of the measures maintain "real" effects, only BIS is relatively insensitive to speed-accuracy trade-offs.

/pdf/combining-speed-and-accuracy-to-control-for-speed-accuracy-5fow8vctia.pdf

Combining speed and accuracy to control for speed-accuracy trade-offs(?)

http://bernhard-hommel.eu/Who%20is%20talking%20in%20backward%20crosstalk.pdf

Who is talking in backward crosstalk? Disentangling response- from goal-conflict in dual-task performance

The last decades have seen a growing interest in the impact of action on perception and other concurrent cognitive processes. One particularly interesting example is that manual rotation actions facilitate mental rotations in the same direction. The present study extends this research in two fundamental ways. First, Experiment 1 demonstrates that not only manual rotations facilitate mental rotations but that mental rotations also facilitate subsequent manual rotations. Second, Experiments 2 and 3 targeted the mechanisms underlying this interplay. Here, manual steering wheel rotations produced salient visual effects, namely the rotation of either a plane or a horizon in an aviation display. The rotation direction of these visual effects either did or did not correspond to the direction of the manual rotation itself. These experiments clearly demonstrate an impact of sensory action effects: Mental rotations facilitate manual rotations with visual effects of the same direction (as the mental rotation), irrespective of the direction of the manual rotation. These findings highlight the importance of effect anticipation in action planning. As such they support the contentions of ideomotor theory and shed new light on the cognitive source of the interplay between visual imagery and motor control.

/pdf/effective-rotations-action-effects-determine-the-interplay-1lgnx4eqt6.pdf

Markus Janczyk

Papers

Confidence intervals for two sample means: Calculation, interpretation, and a few simple rules

Good things peak in pairs: a note on the bimodality coefficient.

Combining speed and accuracy to control for speed-accuracy trade-offs(?)

Who is talking in backward crosstalk? Disentangling response- from goal-conflict in dual-task performance

Effective rotations: action effects determine the interplay of mental and manual rotations.