Chronic non-cancer pain (CNCP) involves one-third of the US population, and prescription opioids contribute to the opioid epidemic. The Centers for Disease Control and Prevention emphasizes maximizing non-opioid treatment, but many rural populations cannot access alternative therapies. Clinical and Translational Science Award hubs across four rural states performed a multi-site, single-arm intervention feasibility study testing methods and procedures of implementing a behavioral intervention, acceptance and commitment therapy, in primary care CNCP patients on chronic opioids. Using the CONSORT extension for feasibility studies, we describe lessons learned in recruiting/retaining participants, intervention implementation, data measurement, and multi-site procedures. Results inform a future definitive trial and potentially others conducting rural trials.

Project management expertise is employed across many professional sectors, including clinical research organizations, to ensure that efforts undertaken by the organization are completed on time and according to specifications and are capable of achieving the needed impact. Increasingly, project leaders (PLs) who possess this expertise are being employed in academic settings to support clinical and preclinical translational research team science. Duke University’s clinical and translational science enterprise has been an early adopter of project management to support clinical and preclinical programs. We review the history and evolution of project management and the PL role at Duke, examine case studies that illustrate their growing value to our academic research environment, and address challenges and solutions to employing project management in academia. Furthermore, we describe the critical role project leadership plays in accelerating and increasing the success of translational team science and team approaches frequently required for systems biology and “big data” scientific studies. Finally, we discuss perspectives from Duke project leadership professionals regarding the training needs and requirements for PLs working in academic clinical and translational science research settings.

Autonomous landing on the deck of a boat or an unmanned surface vehicle (USV) is the minimum requirement for increasing the autonomy of water monitoring missions. This paper introduces an end-to-end control technique based on deep reinforcement learning for landing an unmanned aerial vehicle on a visual marker located on the deck of a USV. The solution proposed consists of a hierarchy of Deep Q-Networks (DQNs) used as high-level navigation policies that address the two phases of the flight: the marker detection and the descending manoeuvre. Few technical improvements have been proposed to stabilize the learning process, such as the combination of vanilla and double DQNs, and a partitioned buffer replay. Simulated studies proved the robustness of the proposed algorithm against different perturbations acting on the marine vessel. The performances obtained are comparable with a state-of-the-art method based on template matching.

Bacterial cultures exposed to iron-doped apatite nanoparticles (IDANPs) prior to the introduction of antagonistic viruses experience up to 2.3 times the bacterial destruction observed in control cultures. Maximum antibacterial activity of these bacteria-specific viruses, or phage, occurs after bacterial cultures have been exposed to IDANPs for 1 hr prior to phage introduction, demonstrating that IDANP-assisted phage therapy would not be straight forward, but would instead require controlled time release of IDANPs and phage. These findings motivated the design of an electrospun nanofiber mesh treatment delivery system that allows burst release of IDANPs, followed by slow, consistent release of phage for treatment of topical bacterial infections. IDANPs resemble hydroxyapatite, a biocompatible mineral analogous to the inorganic constituent of mammalian bone, which has been approved by the Food and Drug Administration for many biomedical purposes. The composite nanofiber mesh was designed for IDANP-assisted phage therapy treatment of topical wounds and consists of a superficial, rapid release layer of polyethylene oxide (PEO) fibers doped with IDANPs, followed by inner, coaxial polycaprolactone / polyethylene glycol (PCL/PEG) blended polymer fiber layer for slower phage delivery. Our investigations have established that IDANP-doped PEO fibers are effective vehicles for dissemination of IDANPs for bacterial exposure and resultant increased bacterial death by phage. In this work, slower delivery of the phage behind IDANPs was accomplished using coaxial, electrospun fibers composed of PCL/PEG polymer blend.

The adoption of a robust collision avoidance module is required to realise fully autonomous Unmanned Surface Vehicles (USVs). In this work, collision detection and path planning methods for USVs are presented. Attention is focused on the difference between local and global path planners, describing the most common techniques derived from classical graph search theory. In addition, a dedicated section is reserved for intelligent methods, such as artificial neural networks and evolutionary algorithms. Born as optimisation methods, they can learn a close-to-optimal solution without requiring large computation effort under certain constraints. Finally, the deficiencies of the existing methods are highlighted and discussed. It has been concluded that almost all the existing method do not address sea or weather conditions, or do not involve the dynamics of the vessel while defining the path. Therefore, this research area is still far from being considered fully explored.

The materiality of ritual performance is a growing focus for archaeologists. In Europe, collective ritual performance is expected to be highly structured and to leave behind a loud archaeological signature. In Australia and Papua New Guinea, ritual is highly structured; however, material signatures for performance are not always apparent, with ritual frequently bound up in the surrounding natural and cultural landscape. One way of assessing long-term ritual in this context is by using archaeology to historicize ethno-historical and ethnographic accounts. Examples of this in the Torres Strait region, islands between Papua New Guinea and mainland Australia, suggest that ritual activities were materially inscribed at kod sites (ceremonial men's meeting places) through distribution of clan fireplaces, mounds of stone/bone and shell. This paper examines the structure of Torres Strait ritual for a site ethnographically reputed to be the ancestral kod of the Mabuyag Islanders. Intra-site partitioning of ritual performance is interpreted using ethnography, rock art and the divergent distribution of surface and sub-surface materials (including microscopic analysis of dugong bone and lithic material) across the site. Finally, it discusses the materiality of ritual at a boundary zone between mainland Australia and Papua New Guinea and the extent to which archaeology provides evidence for Islander negotiation through ceremony of external incursions.

We analyze 3,547 initial public offerings (IPOs) from 1985 through 2003 to determine the impact of acquisition activity on long-run stock performance. The results show that IPOs that acquire within a year of going public significantly underperform for 1- through 5-year holding periods following the 1st year, whereas nonacquiring IPOs do not significantly underperform over these time frames. For example, the mean 3-year style-adjusted abnormal return is – 15.6% for acquirers and 5.9% for nonacquirers. Our cross-sectional and calendar-time results suggest that the acquisition activity of newly public firms plays an important and previously unrecognized role in the long-run underperformance of IPOs.

Visual and auditory evoked potentials were recorded from the scalp under conditions of uncertainty versus certainty, correctness versus incorrectness of pretrial guess, and shift versus repetition of the sensory modality of the stimulus. Schizophrenic patients, psychotic depressive patients, and normal controls were matched for age, sex, race, and socioeconomic status and educational level. The two patient groups were matched for medication (chlorpromazine) dosage level. Under all conditions normals exhibited the largest N1-P3 evoked potential amplitudes, while depressives exhibited the next largest and schizophrenics the smallest. All three groups had larger Ni-Pa amplitudes in the uncertain condition than in the certain condition. However, the effect of uncertainty was greatest in the normal group and least in the schizophrenic group. There were no significant interactions between group membership and guessing correctly and incorrectly. On the other hand, there was a significant interaction between group membership and modality shift. Depressives and normals tended to have larger N1-P3 amplitudes in the crossmodal condition, while schizophrenics tended to have larger amplitudes in the ipsimodal condition.

Stability and change of attachment was examined longitudinally in a group of 48 children at 14, 24, and 58 months of age. Whereas attachment classifications showed stability between 14 and 24 months, lack of stability was the case between either 14 or 24 months and 58 months. Mothers of children who did not exhibit stability of attachment reported more negative and less positive life events. No correspondence was found between attachment classification at 14 or 24 months and mental representations at 58 months. However there was agreement between representational and behavioral measures of attachment at 58 months, where mental representations of attachment appeared to mirror and complement behavioral classification of the attachment relationship with the mother. Evidence for continuity of attachment from infancy to childhood internal representations was found only in a subgroup of children who showed stability of secure attachment between infancy and 58 months of age. These children exhibited greater Emotional Openness in the SAT at 4.5 years. Findings are discussed in terms of different positions in attachment theory and research regarding the stability and change of attachment relationships.

In recent years, both the offshore industry and the navies of the world have become increasingly interested in the potential operational usage of unmanned underwater vehicles. This paper provides a comprehensive review of a number of modern control approaches and artificial intelligence techniques which have been applied to the autopilot design problem for such craft.

Artificial neural networks offer an alternative strategy for the nonlinear control of unmanned underwater vehicles (UUVS). This paper investigates the use of a multi-layered perceptron (MLP) network in controlling an UUV over a sea-bed profile and compares the use of applying chemotaxis learning to that of the more commonly employed back propagation algorithm. The results show that, for differing sized MLPs, the chemotaxis algorithm produces a successful controller over the sea-bed profile in an improved training time. Also it will be shown that, in the presence of noise and change in vehicle mass, the neural controller out-performed a classical proportional-integral-derivative controller.

The feasibility of using a genetic algorithm to optimize a fuzzy fixed rule based autopilot is considered in this paper. Simulation results are presented to show the applicability of the approach. It is concluded such a procedure gives more credence to the resulting design than can be achieved by totally heuristic methods.

As a result of the general recognition given to the robustness qualities of fuzzy control algorithms, studies have been undertaken in the marine field to develop autopilots based on this approach. Indeed, a fuzzy autopilot was recently installed in a small leisure vessel and very successful fullscale sea trials were undertaken. In the past, the main problem in designing a fuzzy autopilot, or any other fuzzy controller, has been the reliance on purely heuristic methods to obtain an optimum solution. To compensate for such shortcomings in the design cycle analytical approaches are now being proposed.