The Role of Ontogeny in the Evolution of Human Cooperation

To explain the evolutionary emergence of uniquely human skills and motivations for cooperation, Tomasello et al. (2012, in Current Anthropology 53(6):673–92) proposed the interdependence hypothesis. The key adaptive context in this account was the obligate collaborative foraging of early human adults. Hawkes (2014, in Human Nature 25(1):28–48), following Hrdy (Mothers and Others, Harvard University Press, 2009), provided an alternative account for the emergence of uniquely human cooperative skills in which the key was early human infants’ attempts to solicit care and attention from adults in a cooperative breeding context. Here we attempt to reconcile these two accounts. Our composite account accepts Hrdy’s and Hawkes’s contention that the extremely early emergence of human infants’ cooperative skills suggests an important role for cooperative breeding as adaptive context, perhaps in early Homo. But our account also insists that human cooperation goes well beyond these nascent skills to include such things as the communicative and cultural conventions, norms, and institutions created by later Homo and early modern humans to deal with adult problems of social coordination. As part of this account we hypothesize how each of the main stages of human ontogeny (infancy, childhood, adolescence) was transformed during evolution both by infants’ cooperative skills “migrating up” in age and by adults’ cooperative skills “migrating down” in age

Interactions between the hippocampus, prefrontal cortex, and amygdala support complex learning and memory.

One of the guiding principles of memory research in the preceding decades is multiple memory systems theory, which links specific task demands to specific anatomical structures and circuits that are thought to act orthogonally with respect to each other. We argue that this view does not capture the nature of learning and memory when any degree of complexity is introduced. In most situations, memory requires interactions between these circuits and they can act in a facilitative manner to generate adaptive behavior

An overlooked family-group name among bees: Availability of Coelioxoidini (Hymenoptera: Apidae)

Recent phylogenetic analysis of the family Apidae has applied the tribal name Coelioxoidini to the distinctive genus Coelioxoides Cresson, which has been thought to be related to Tetrapedia Klug.  However, the nomenclatural status of such a family-group name has not yet been assessed.  Herein, we determine that this family-group name is available and discuss its authorship and proposal date

Mesoscopic approach to granular crystal dynamics

We present a mesoscopic approach to granular crystal dynamics, which comprises a three-dimensional finite-element model and a one-dimensional regularized contact model. The approach investigates the role of vibrational-energy trapping effects in the dynamic behavior of one-dimensional chains of particles in contact (i.e., granular crystals), under small to moderate impact velocities. The only inputs of the models are the geometry and the elastic material properties of the individual particles that form the system. We present detailed verification results and validate the model comparing its predictions with experimental data. This approach provides a physically sound, first-principle description of dissipative losses in granular systems

Inferring land use from mobile phone activity

Understanding the spatiotemporal distribution of people within a city is crucial to many planning applications. Obtaining data to create required knowledge, currently involves costly survey methods. At the same time ubiquitous mobile sensors from personal GPS devices to mobile phones are collecting massive amounts of data on urban systems. The locations, communications, and activities of millions of people are recorded and stored by new information technologies. This work utilizes novel dynamic data, generated by mobile phone users, to measure spatiotemporal changes in population. In the process, we identify the relationship between land use and dynamic population over the course of a typical week. A machine learning classification algorithm is used to identify clusters of locations with similar zoned uses and mobile phone activity patterns. It is shown that the mobile phone data is capable of delivering useful information on actual land use that supplements zoning regulations.Comment: To be presented at ACM UrbComp201

Algorithms for Del Pezzo Surfaces of Degree 5 (Construction, Parametrization)

It is well known that every Del Pezzo surface of degree 5 defined over k is parametrizable over k. In this paper we give an efficient construction for parametrizing, as well as algorithms for constructing examples in every isomorphism class and for deciding equivalence.Comment: 15 page

An Educational Module on the Benefits of Telehealth Assisted Preanesthetic Evaluations

Title An Educational Module on the Benefits of Telehealth Assisted Preanesthetic Evaluations Impact Statement Healthcare systems are always seeking new ways to increase efficiency, save on costs, and provide quality care for their patients. The use of telehealth in the preanesthesia setting is a tool that can help to further improve a healthcare system’s ability to achieve these goals. This project will be a step towards determining the support for and viability of telehealth utilization in the preanesthesia setting. Background/Purpose/Question Surgery cancellations are a significant problem with the potential for far-reaching consequences. Unexpected day-of-surgery cancellations can be costly to both the patient and the health care team. Telemedicine and telehealth are readily available tools for overcoming obstacles to accessing health care. Their use can improve patient outcomes, primarily by reducing the transportation time and costs and increasing the access to physicians. However, there is relatively little data on provider attitudes on the use of telemedicine to reduce cancellations and surgical delays. This project aims to answer: Among anesthesia providers (P), is an educational module designed to improve knowledge of the effectiveness of telehealth-assisted PAE (I), when compared to face-to-face preoperative assessment (C), effective in increasing provider knowledge (O) that leads to an improvement in the quality of patient care, the experience of the patient, its effect on staff, productivity, and cost-savings potential? Methods/Evidence Search Using the keywords listed under “Eligibility Criteria,” a search was conducted on CINAHL. Non-English, non-peer-reviewed articles were eliminated from the search, as well as articles older than 10 years. The same steps were taken with PubMed and Google Scholar. A total of 152 articles were found as potential evidence sources. Sources meeting criteria based on title were 44. Sources meeting criteria based on abstract were 13. Finally, sources meeting criteria based on full text were 8: a systematic literature review, a prospective randomized trial, a case-controlled study, a quasi-experimental study, a retrospective study, 2 descriptive studies, and a mixed methods approach. A total of 7 of the studies were performed in the United Sates while 1 was done in Australia. Synthesis of Literature/Results/Discussion A systematic literature review was conducted by Schoen and Prater. The results of their systematic review found that PAE can be successfully performed using telehealth and that patients also reported satisfaction with utilization of telehealth when performing PAE. For this project, the pre-test and post-test assessed if the educational module enhanced the participants attitude and perception of the use of telehealth during the PAE. The results show that after an educational module was shown, perception of the technology improved. Future research should focus on creating experiments with larger sample sizes and implementing the technology to see what real-world benefits the technology can offer. Conclusions/Recommendations for Practice 4 Telehealth is an increasingly relevant topic in the healthcare industry. It can provide many benefits to both the provider and the consumer. The project shows that presenting the topic and educating providers about the topic can make them more open to using the technology in their practice. Information gained from this project can be used to determine the feasibility of implementing this technology at health care facility where anesthesia providers practice

Optimistic Concurrency Control for Distributed Unsupervised Learning

Research on distributed machine learning algorithms has focused primarily on one of two extremes - algorithms that obey strict concurrency constraints or algorithms that obey few or no such constraints. We consider an intermediate alternative in which algorithms optimistically assume that conflicts are unlikely and if conflicts do arise a conflict-resolution protocol is invoked. We view this "optimistic concurrency control" paradigm as particularly appropriate for large-scale machine learning algorithms, particularly in the unsupervised setting. We demonstrate our approach in three problem areas: clustering, feature learning and online facility location. We evaluate our methods via large-scale experiments in a cluster computing environment.Comment: 25 pages, 5 figure