Providentia - A Large-Scale Sensor System for the Assistance of Autonomous Vehicles and Its Evaluation

The environmental perception of an autonomous vehicle is limited by its physical sensor ranges and algorithmic performance, as well as by occlusions that degrade its understanding of an ongoing traffic situation. This not only poses a significant threat to safety and limits driving speeds, but it can also lead to inconvenient maneuvers. Intelligent Infrastructure Systems can help to alleviate these problems. An Intelligent Infrastructure System can fill in the gaps in a vehicle's perception and extend its field of view by providing additional detailed information about its surroundings, in the form of a digital model of the current traffic situation, i.e. a digital twin. However, detailed descriptions of such systems and working prototypes demonstrating their feasibility are scarce. In this paper, we propose a hardware and software architecture that enables such a reliable Intelligent Infrastructure System to be built. We have implemented this system in the real world and demonstrate its ability to create an accurate digital twin of an extended highway stretch, thus enhancing an autonomous vehicle's perception beyond the limits of its on-board sensors. Furthermore, we evaluate the accuracy and reliability of the digital twin by using aerial images and earth observation methods for generating ground truth data

Exploiting structure similarity in refinement: automated NCS and target-structure restraints in BUSTER

Local structural similarity restraints (LSSR) provide a novel method for exploiting NCS or structural similarity to an external target structure. Two examples are given where BUSTER re-refinement of PDB entries with LSSR produces marked improvements, enabling further structural features to be modelled

The AP-1-BATF and -BATF3 module is essential for growth, survival and TH17/ILC3 skewing of anaplastic large cell lymphoma.

Transcription factor AP-1 is constitutively activated and IRF4 drives growth and survival in ALK+ and ALK- anaplastic large cell lymphoma (ALCL). Here we demonstrate high-level BATF and BATF3 expression in ALCL. Both BATFs bind classical AP-1 motifs and interact with in ALCL deregulated AP-1 factors. Together with IRF4, they co-occupy AP-1-IRF composite elements, differentiating ALCL from non-ALCL. Gene-specific inactivation of BATFs, or global AP-1 inhibition results in ALCL growth retardation and/or cell death in vitro and in vivo. Furthermore, the AP-1-BATF module establishes TH17/group 3 innate lymphoid cells (ILC3)-associated gene expression in ALCL cells, including marker genes such as AHR, IL17F, IL22, IL26, IL23R and RORγt. Elevated IL-17A and IL-17F levels were detected in a subset of children and adolescents with ALK+ ALCL. Furthermore, a comprehensive analysis of primary lymphoma data confirms TH17-, and in particular ILC3-skewing in ALCL compared with PTCL. Finally, pharmacological inhibition of RORC as single treatment leads to cell death in ALCL cell lines and, in combination with the ALK inhibitor crizotinib, enforces death induction in ALK+ ALCL. Our data highlight the crucial role of AP-1/BATFs in ALCL and lead to the concept that some ALCL might originate from ILC3

Moving Just Like You: Motor Interference Depends on Similar Motility of Agent and Observer

Recent findings in neuroscience suggest an overlap between brain regions involved in the execution of movement and perception of another’s movement. This so-called “action-perception coupling” is supposed to serve our ability to automatically infer the goals and intentions of others by internal simulation of their actions. A consequence of this coupling is motor interference (MI), the effect of movement observation on the trajectory of one’s own movement. Previous studies emphasized that various features of the observed agent determine the degree of MI, but could not clarify how human-like an agent has to be for its movements to elicit MI and, more importantly, what ‘human-like’ means in the context of MI. Thus, we investigated in several experiments how different aspects of appearance and motility of the observed agent influence motor interference (MI). Participants performed arm movements in horizontal and vertical directions while observing videos of a human, a humanoid robot, or an industrial robot arm with either artificial (industrial) or human-like joint configurations. Our results show that, given a human-like joint configuration, MI was elicited by observing arm movements of both humanoid and industrial robots. However, if the joint configuration of the robot did not resemble that of the human arm, MI could longer be demonstrated. Our findings present evidence for the importance of human-like joint configuration rather than other human-like features for perception-action coupling when observing inanimate agents

Priorities to Promote Participant Engagement in the Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network.

BACKGROUND: Engaging diverse populations in cancer genomics research is of critical importance and is a fundamental goal of the NCI Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network. Established as part of the Cancer Moonshot, PE-CGS is a consortium of stakeholders including clinicians, scientists, genetic counselors, and representatives of potential study participants and their communities. Participant engagement is an ongoing, bidirectional, and mutually beneficial interaction between study participants and researchers. PE-CGS sought to set priorities in participant engagement for conducting the network\u27s research. METHODS: PE-CGS deliberatively engaged its stakeholders in the following four-phase process to set the network\u27s research priorities in participant engagement: (i) a brainstorming exercise to elicit potential priorities; (ii) a 2-day virtual meeting to discuss priorities; (iii) recommendations from the PE-CGS External Advisory Panel to refine priorities; and (iv) a virtual meeting to set priorities. RESULTS: Nearly 150 PE-CGS stakeholders engaged in the process. Five priorities were set: (i) tailor education and communication materials for participants throughout the research process; (ii) identify measures of participant engagement; (iii) identify optimal participant engagement strategies; (iv) understand cancer disparities in the context of cancer genomics research; and (v) personalize the return of genomics findings to participants. CONCLUSIONS: PE-CGS is pursuing these priorities to meaningfully engage diverse and underrepresented patients with cancer and posttreatment cancer survivors as participants in cancer genomics research and, subsequently, generate new discoveries. IMPACT: Data from PE-CGS will be shared with the broader scientific community in a manner consistent with participant informed consent and community agreement

Molecular Mechanisms Associated with Nicotine Pharmacology and Dependence.

Tobacco dependence is a leading cause of preventable disease and death worldwide. Nicotine, the main psychoactive component in tobacco cigarettes, has also been garnering increased popularity in its vaporized form, as derived from e-cigarette devices. Thus, an understanding of the molecular mechanisms underlying nicotine pharmacology and dependence is required to ascertain novel approaches to treat drug dependence. In this chapter, we review the field's current understanding of nicotine's actions in the brain, the neurocircuitry underlying drug dependence, factors that modulate the function of nicotinic acetylcholine receptors, and the role of specific genes in mitigating the vulnerability to develop nicotine dependence. In addition to nicotine's direct actions in the brain, other constituents in nicotine and tobacco products have also been found to alter drug use, and thus, evidence is provided to highlight this issue. Finally, currently available pharmacotherapeutic strategies are discussed, along with an outlook for future therapeutic directions to achieve to the goal of long-term nicotine cessation