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1. Eliciting imitation in early infancy

   https://doi.org/10.1111/desc.12738  

   Meltzoff, Andrew N.; Murray, Lynne; Simpson, Elizabeth A.; Heimann, Mikael; Nagy, Emese; Nadel, Jacqueline; Pedersen, Eric J.; Brooks, Rechele; Messinger, Daniel S.; De Pascalis, Leonardo; et al (September 2018, Developmental Science)

   We (Meltzoff et al., 2018) described how Oostenbroek et al.’s (2016) design likely dampened infant imitation. In their commentary, Oostenbroek et al. (2018) argue that our points are post hoc. It is important for readers to know that they are not. Our paper restated “best practices” described in published papers. Based on the literature, the design used by Oostenbroek et al. (2016) would be predicted to dampen infant imitation. First, Oostenbroek et al.’s (2016) test periods were too brief. The stimulus presentation for each type of gesture was too short to ensure that neonates saw the display. The response measurement period did not allow neonates sufficient time to organize a motor response. Meltzoff and Moore (1983a, 1994) introduced experimental procedures specifically designed to address these issues (also, Simpson, Murray, Paukner, & Ferrari, 2014). Oostenbroek et al. did not capitalize on these procedural advances. Second, Oostenbroek et al. allowed uncontrolled experimenter–infant interactions during the test session itself. Previous papers on imitation provided analyses of how uncontrolled interactions with the experimenter can introduce “noise” in experiments of facial imitation (Meltzoff & Moore, 1983b, 1994). Third, Oostenbroek et al. used suboptimal eliciting conditions. Neonates cannot support their own heads; in Oostenbroek et al., infants’ heads were allowed to flop from side-to-side unsupported on the experimenter’s lap while the experimenter gestured with both hands. In addition, papers have listed techniques for maximizing visual attention (controlled lighting, homogeneous background) (Meltzoff & Moore, 1989, 1994). Oostenbroek et al. tested infants on a couch in the home. Despite a design that would blunt imitation, our reanalysis of Oostenbroek et al.’s data showed a response pattern that is consistent with the imitation of tongue protrusion (TP). In their commentary, Oostenbroek et al. (2018) now propose limiting analyses to a subset of their original controls. We reanalyzed their data accordingly. Again, the results support early imitation. Their cross-sectional data (Oostenbroek et al., 2016, Table S4) collapsed across age show significantly more infant TP in response to the TP demonstration than to the mean of the six dynamic face controls (mouth, happy, sad, mmm, ee, and click): t(104) = 4.62, p = 0.00001. The results are also significant using a narrower subset of stimuli (mouth, happy, and sad): t(104) = 3.20, p = 0.0018. These results rule out arousal, because the adult TP demonstration was significantly more effective in eliciting infant tongue protrusions than the category of dynamic face controls. Tongue protrusion matching is a robust phenomenon successfully elicited in more than two dozen studies (reviews: Meltzoff & Moore, 1997; Nagy, Pilling, Orvos, & Molnar, 2013; Simpson et al., 2014). There are more general lessons to be drawn. Psychology is experiencing what some call a “replication crisis.” Those who attempt to reproduce effects have scientific responsibilities, as do original authors. Both can help psychology become a more cumulative science. It is crucial for investigators to label whether or not a study is a direct replication attempt. If it is not a direct replication, procedural alterations and associated limitations should be discussed. It sows confusion to use procedures that are already predicted to dampen effects, without alerting readers. Psychology will be advanced by more stringent standards for reporting and evaluating studies aimed at reproducing published effects. Infant imitation is a fundamental skill prior to language and contributes to the development of social cognition. On this both Oostenbroek et al. and we agree. 

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2. Comment on “Resolving the Tropical Pacific/Atlantic Interaction Conundrum” by Feng Jiang et al. (2023)

   https://doi.org/10.1029/2024GL111563  

   Richter, Ingo; Keenlyside, Noel; Tozuka, Tomoki; Okumura, Yuko; Wang, Chunzai; Chang, Ping; Kido, Shoichiro; Tokinaga, Hiroki (December 2024, Geophysical Research Letters)

   Abstract Jiang et al. (2023),https://doi.org/10.1029/2023gl103777argue that the apparent impact of the equatorial Atlantic on El Niño‐Southern Oscillation (ENSO) is a statistical artifact, and that the 6‐month lead correlation reported in previous studies stems from early developing ENSO events driving the equatorial Atlantic zonal mode (AZM) in boreal summer and maturing in winter. Closer examination, however, reveals that most AZM events develop too early to be driven by developing ENSO, and that the influence of decaying ENSO events has to be considered too. Thus, while early developing ENSO events may play a role, they do not fully explain observed AZM behavior. Our aim is not to argue for or against an AZM influence on ENSO, but rather to show that Jiang et al.’s analysis is insufficient to resolve this issue. More analysis will be needed for a deeper understanding of Atlantic‐Pacific interaction. 

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3. Dynamically monitoring crowd-worker's reliability with interval-valued labels

   https://doi.org/10.54941/ahfe1003270  

   Hu, Chenyi; Spurling, Makenzie (January 2023, AHFE International)

   Crowdsourcing has rapidly become a computing paradigm in machine learning and artificial intelligence. In crowdsourcing, multiple labels are collected from crowd-workers on an instance usually through the Internet. These labels are then aggregated as a single label to match the ground truth of the instance. Due to its open nature, human workers in crowdsourcing usually come with various levels of knowledge and socio-economic backgrounds. Effectively handling such human factors has been a focus in the study and applications of crowdsourcing. For example, Bi et al studied the impacts of worker's dedication, expertise, judgment, and task difficulty (Bi et al 2014). Qiu et al offered methods for selecting workers based on behavior prediction (Qiu et al 2016). Barbosa and Chen suggested rehumanizing crowdsourcing to deal with human biases (Barbosa 2019). Checco et al studied adversarial attacks on crowdsourcing for quality control (Checco et al 2020). There are many more related works available in literature. In contrast to commonly used binary-valued labels, interval-valued labels (IVLs) have been introduced very recently (Hu et al 2021). Applying statistical and probabilistic properties of interval-valued datasets, Spurling et al quantitatively defined worker's reliability in four measures: correctness, confidence, stability, and predictability (Spurling et al 2021). Calculating these measures, except correctness, does not require the ground truth of each instance but only worker’s IVLs. Applying these quantified reliability measures, people have significantly improved the overall quality of crowdsourcing (Spurling et al 2022). However, in real world applications, the reliability of a worker may vary from time to time rather than a constant. It is necessary to monitor worker’s reliability dynamically. Because a worker j labels instances sequentially, we treat j’s IVLs as an interval-valued time series in our approach. Assuming j’s reliability relies on the IVLs within a time window only, we calculate j’s reliability measures with the IVLs in the current time window. Moving the time window forward with our proposed practical strategies, we can monitor j’s reliability dynamically. Furthermore, the four reliability measures derived from IVLs are time varying too. With regression analysis, we can separate each reliability measure as an explainable trend and possible errors. To validate our approaches, we use four real world benchmark datasets in our computational experiments. Here are the main findings. The reliability weighted interval majority voting (WIMV) and weighted preferred matching probability (WPMP) schemes consistently overperform the base schemes in terms of much higher accuracy, precision, recall, and F1-score. Note: the base schemes are majority voting (MV), interval majority voting (IMV), and preferred matching probability (PMP). Through monitoring worker’s reliability, our computational experiments have successfully identified possible attackers. By removing identified attackers, we have ensured the quality. We have also examined the impact of window size selection. It is necessary to monitor worker’s reliability dynamically, and our computational results evident the potential success of our approaches.This work is partially supported by the US National Science Foundation through the grant award NSF/OIA-1946391. 

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4. Intertidal foraging by gentoo penguins in a macroalgal raft

   https://doi.org/10.1017/S095410201900052X  

   McClintock, James B.; Amsler, Charles D.; Amsler, Margaret O.; Fraser, William R. (February 2020, Antarctic Science)

   Foraging strategies in gentoo penguins ( Pygoscelis papua ) have been well studied (e.g. Croxall et al. 1988, Robinson & Hindell 1996, Lescroël et al. 2004, Takahashi et al. 2008, Xavier et al. 2017). The general consensus is this largest member of the three pygoscelid penguins displays both nearshore benthic and pelagic foraging tactics to consume combinations of crustaceans and fish. In a recent study, Carpenter-Kling et al. (2017) reported that gentoos at sub-Antarctic Marion Island displayed a novel foraging strategy that consisted of alternating typical lengthy foraging trips with much shorter nearshore afternoon trips. They suggest the latter foraging behaviour may be a response to suboptimal feeding conditions caused by local environmental change. This novel discovery reinforces the fact that, despite considerable study, not all foraging tactics in penguins have been documented. In this paper, we describe what we believe to be, yet another undocumented foraging tactic employed by gentoos. 

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5. Coordinated regulation of RNA metabolism and silencing by ABA signaling in plant abiotic stress responses

   Gregory, BD (September 2025, Molecular Plant)

   Abscisic acid (ABA) is an essential plant hormone that regulates multiple aspects of plant development and numerous abiotic stress responses (Cutler et al., 2010; Waadt et al., 2022). In fact, at the heart of plants’ responses to stresses such as salinity, drought, and hypertonic conditions, among others, is this phytohormone (Cutler et al., 2010; Waadt et al., 2022). Interestingly, stress-triggered and developmental responses to this hormone have been found to involve basic RNA metabolism components, including the two subunits of the nuclear cap-binding complex, ABA HYPERSENSITIVE1 (ABH1/CBP80) and CBP20 (Hugouvieux et al., 2001). Additionally, multiple lines of evidence have linked small RNA (smRNA)-mediated RNA silencing to ABA responses (Gregory et al., 2008; Laubinger et al., 2008). A new study by Yan et al. (2025) has provided new insights regarding how RNA degradation and silencing factors modulate smRNA biogenesis from NITRATE REDUCTASE1/2 transcripts to affect ABA-regulated abiotic stress responses. 

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