Safe From Harm: Learned,Instructed, and Symbolic Generalization Pathways of Human Threat-Avoidance

Avoidance of threatening or unpleasant events is usually an adaptive behavioural strategy. Sometimes, however, avoidance can become chronic and lead to impaired daily functioning. Excessive threat-avoidance is a central diagnostic feature of anxiety disorders, yet little is known about whether avoidance acquired in the absence of a direct history of conditioning with a fearful event differs from directly learned avoidance. In the present study, we tested whether avoidance acquired indirectly via verbal instructions and symbolic generalization result in similar levels of avoidance behaviour and threat-beliefs to avoidance acquired after direct learning. Following fear conditioning in which one conditioned stimulus was paired with shock (CS+) and another was not (CS−), participants either learned or were instructed to make a response that cancelled impending shock. Three groups were then tested with a learned CS+ and CS− (learned group), instructed CS+ (instructed group), and generalized CS+ (derived group) presentations. Results showed similar levels of avoidance behaviour and threat-belief ratings about the likelihood of shock across each of the three pathways despite the different mechanisms by which they were acquired. Findings have implications for understanding the aetiology of clinical avoidance in anxiety.     

Building Electron/Proton Nanohighways for Full Utilization of Water Splitting Catalysts

Low electron/proton conductivities of electrochemical catalysts, especially earth‐abundant nonprecious metal catalysts, severely limit their ability to satisfy the triple‐phase boundary (TPB) theory, resulting in extremely low catalyst utilization and insufficient efficiency in energy devices. Here, an innovative electrode design strategy is proposed to build electron/proton transport nanohighways to ensure that the whole electrode meets the TPB, therefore significantly promoting enhance oxygen evolution reactions and catalyst utilizations. It is discovered that easily accessible/tunable mesoporous Au nanolayers (AuNLs) not only increase the electrode conductivity by more than 4000 times but also enable the proton transport through straight mesopores within the Debye length. The catalyst layer design with AuNLs and ultralow catalyst loading (≈0.1 mg cm^?2) augments reaction sites from 1D to 2D, resulting in an 18‐fold improvement in mass activities. Furthermore, using microscale visualization and unique coplanar‐electrode electrolyzers, the relationship between the conductivity and the reaction site is revealed, allowing for the discovery of the conductivity‐determining and Debye‐length‐determining regions for water splitting. These findings and strategies provide a novel electrode design (catalyst layer + functional sublayer + ion exchange membrane) with a sufficient electron/proton transport path for high‐efficiency electrochemical energy conversion devices.     

Stejneger's beaked whale strandings in Alaska, 1995–2020

Presented here is the first comprehensive and updated compilation of history, distribution, and findings of Stejneger's beaked whales (Mesoplodon stejnegeri) in Alaska. Stejneger's beaked whales are a poorly understood, elusive, deep-diving cetacean species found in the North Pacific Ocean. Since Stejneger's beaked whale strandings data in Alaska through 1994 were last published, 35 additional strandings have been documented. Twenty-seven animals stranded in the Aleutian Islands, seven stranded in Southcentral Alaska, and one animal stranded on St. Lawrence Island. Twenty-two carcasses were necropsied, but only four were fresh. Seventeen of the 22 died during mass stranding events and cause of death could not be definitively determined. Barotrauma was suspected in three cases and infectious disease possibly complicated by barotrauma occurred in two cases. We documented an expansion of strandings into the northern Bering Sea, characterized a sex bias, examined stomach contents that included macroplastic, and identified parasites not previously associated with Stejneger's beaked whales. Also included are data on the largest known mass stranding of Stejneger's beaked whales, which occurred on Adak Island in 2018. The history, distribution, and findings presented here are central to further our understanding of this species.     

A framework to evaluate whether to pool or separate behaviors in a multilayer network

A multilayer network approach combines different network layers,which are connected by interlayer edges,to create a single mathematical object.These networks can contain a variety of information types and represent different aspects of a system.However,the process for selecting which information to include is not always straightforward.Using data on 2 agonistic behaviors in a captive population of monk parakeets(Myiopsitta monachus),we developed a framework for investigating how pooling or splitting behaviors at the scale of dyadic relationships(between 2 individuals)affects individual-and group-level social properties.We designed 2 reference models to test whether randomizing the number of interactions across behavior types results in similar structural patterns as the observed data.Although the behaviors were correlated,the first reference model suggests that the 2 behaviors convey different information about some social properties and should therefore not be pooled.However,once we controlled for data sparsity,we found that the observed measures corresponded with those from the second reference model.Hence,our initial result may have been due to the unequal frequencies of each behavior.Overall,our findings support pooling the 2 behaviors.Awareness of how selected measurements can be affected by data properties is warranted,but nonetheless our framework disentangles these efforts and as a result can be used for myriad types of behaviors and questions.This framework will help researchers make informed and data-driven decisions about which behaviors to pool or separate,prior to using the data in subsequent multilayer network analyses.