57 research outputs found
Designing an Accessible, Technology-Driven Justice System: An Exercise in Testing the Access to Justice Technology Bill of Rights
The Access to Justice Technology Bill of Rights project, sponsored by the Access to Justice Board of Washington State, included a committee composed of attorneys, judges, technologists, and librarians charged with envisioning an ideal civil justice system. Our goals were to design a system with certain core values (e.g., due process and access to justice), test the system using a complex family law scenario, determine what opportunities technology brings to the table, and identify what barriers technology creates for persons using the system. This Article describes an idealized civil justice system (System) unlike anything that presently exists. The System is composed of people and technology that together provide a factual information-delivery system, an advocate, an adversary, a mediator, an adjudicator, and a proactive enforcer. To be successful, our System needs to use a wide variety of current and next-generation technologies and processes. The System gives the participants in a legal issue the opportunity to resolve their issue by themselves before escalating the issue for mediation or adjudication. In addition, the System plays an active role in the enforcement of whatever resolution is reached. At the core of the System is a cycle in which all participants simultaneously review and choose options. The interaction of all the participants choosing options allows the System to converge to a mutually acceptable resolution of the issue
Emergent autonomous scientific research capabilities of large language models
Transformer-based large language models are rapidly advancing in the field of
machine learning research, with applications spanning natural language,
biology, chemistry, and computer programming. Extreme scaling and reinforcement
learning from human feedback have significantly improved the quality of
generated text, enabling these models to perform various tasks and reason about
their choices. In this paper, we present an Intelligent Agent system that
combines multiple large language models for autonomous design, planning, and
execution of scientific experiments. We showcase the Agent's scientific
research capabilities with three distinct examples, with the most complex being
the successful performance of catalyzed cross-coupling reactions. Finally, we
discuss the safety implications of such systems and propose measures to prevent
their misuse.Comment: Version 1, April 11, 2023. 48 page
Photogrammetry and ballistic analysis of a high-flying projectile in the STS-124 space shuttle launch
A method combining photogrammetry with ballistic analysis is demonstrated to
identify flying debris in a rocket launch environment. Debris traveling near
the STS-124 Space Shuttle was captured on cameras viewing the launch pad within
the first few seconds after launch. One particular piece of debris caught the
attention of investigators studying the release of flame trench fire bricks
because its high trajectory could indicate a flight risk to the Space Shuttle.
Digitized images from two pad perimeter high-speed 16-mm film cameras were
processed using photogrammetry software based on a multi-parameter optimization
technique. Reference points in the image were found from 3D CAD models of the
launch pad and from surveyed points on the pad. The three-dimensional reference
points were matched to the equivalent two-dimensional camera projections by
optimizing the camera model parameters using a gradient search optimization
technique. Using this method of solving the triangulation problem, the xyz
position of the object's path relative to the reference point coordinate system
was found for every set of synchronized images. This trajectory was then
compared to a predicted trajectory while performing regression analysis on the
ballistic coefficient and other parameters. This identified, with a high degree
of confidence, the object's material density and thus its probable origin
within the launch pad environment. Future extensions of this methodology may
make it possible to diagnose the underlying causes of debris-releasing events
in near-real time, thus improving flight safety.Comment: 26 pages, 11 figures, 3 table
Three allele combinations associated with Multiple Sclerosis
BACKGROUND: Multiple sclerosis (MS) is an immune-mediated disease of polygenic etiology. Dissection of its genetic background is a complex problem, because of the combinatorial possibilities of gene-gene interactions. As genotyping methods improve throughput, approaches that can explore multigene interactions appropriately should lead to improved understanding of MS. METHODS: 286 unrelated patients with definite MS and 362 unrelated healthy controls of Russian descent were genotyped at polymorphic loci (including SNPs, repeat polymorphisms, and an insertion/deletion) of the DRB1, TNF, LT, TGFβ1, CCR5 and CTLA4 genes and TNFa and TNFb microsatellites. Each allele carriership in patients and controls was compared by Fisher's exact test, and disease-associated combinations of alleles in the data set were sought using a Bayesian Markov chain Monte Carlo-based method recently developed by our group. RESULTS: We identified two previously unknown MS-associated tri-allelic combinations: -509TGFβ1*C, DRB1*18(3), CTLA4*G and -238TNF*B1,-308TNF*A2, CTLA4*G, which perfectly separate MS cases from controls, at least in the present sample. The previously described DRB1*15(2) allele, the microsatellite TNFa9 allele and the biallelic combination CCR5Δ32, DRB1*04 were also reidentified as MS-associated. CONCLUSION: These results represent an independent validation of MS association with DRB1*15(2) and TNFa9 in Russians and are the first to find the interplay of three loci in conferring susceptibility to MS. They demonstrate the efficacy of our approach for the identification of complex-disease-associated combinations of alleles
Precision medicine driven by cancer systems biology
Molecular insights from genome and systems biology are influencing how cancer is diagnosed and treated. We critically evaluate big data challenges in precision medicine. The melanoma research community has identified distinct subtypes involving chronic sun-induced damage and the mitogen-activated protein kinase driver pathway. In addition, despite low mutation burden, non-genomic mitogen-activated protein kinase melanoma drivers are found in membrane receptors, metabolism, or epigenetic signaling with the ability to bypass central mitogen-activated protein kinase molecules and activating a similar program of mitogenic effectors. Mutation hotspots, structural modeling, UV signature, and genomic as well as non-genomic mechanisms of disease initiation and progression are taken into consideration to identify resistance mutations and novel drug targets. A comprehensive precision medicine profile of a malignant melanoma patient illustrates future rational drug targeting strategies. Network analysis emphasizes an important role of epigenetic and metabolic master regulators in oncogenesis. Co-occurrence of driver mutations in signaling, metabolic, and epigenetic factors highlights how cumulative alterations of our genomes and epigenomes progressively lead to uncontrolled cell proliferation. Precision insights have the ability to identify independent molecular pathways suitable for drug targeting. Synergistic treatment combinations of orthogonal modalities including immunotherapy, mitogen-activated protein kinase inhibitors, epigenetic inhibitors, and metabolic inhibitors have the potential to overcome immune evasion, side effects, and drug resistance
Dendritic Spikes Amplify the Synaptic Signal to Enhance Detection of Motion in a Simulation of the Direction-Selective Ganglion Cell
The On-Off direction-selective ganglion cell (DSGC) in mammalian retinas responds most strongly to a stimulus moving in a specific direction. The DSGC initiates spikes in its dendritic tree, which are thought to propagate to the soma with high probability. Both dendritic and somatic spikes in the DSGC display strong directional tuning, whereas somatic PSPs (postsynaptic potentials) are only weakly directional, indicating that spike generation includes marked enhancement of the directional signal. We used a realistic computational model based on anatomical and physiological measurements to determine the source of the enhancement. Our results indicate that the DSGC dendritic tree is partitioned into separate electrotonic regions, each summing its local excitatory and inhibitory synaptic inputs to initiate spikes. Within each local region the local spike threshold nonlinearly amplifies the preferred response over the null response on the basis of PSP amplitude. Using inhibitory conductances previously measured in DSGCs, the simulation results showed that inhibition is only sufficient to prevent spike initiation and cannot affect spike propagation. Therefore, inhibition will only act locally within the dendritic arbor. We identified the role of three mechanisms that generate directional selectivity (DS) in the local dendritic regions. First, a mechanism for DS intrinsic to the dendritic structure of the DSGC enhances DS on the null side of the cell's dendritic tree and weakens it on the preferred side. Second, spatially offset postsynaptic inhibition generates robust DS in the isolated dendritic tips but weak DS near the soma. Third, presynaptic DS is apparently necessary because it is more robust across the dendritic tree. The pre- and postsynaptic mechanisms together can overcome the local intrinsic DS. These local dendritic mechanisms can perform independent nonlinear computations to make a decision, and there could be analogous mechanisms within cortical circuitry
Insights into the relationship between crystallite size, sintering pressure, temperature sensitivity, and persistent luminescence color of Gd2.97Pr0.03Ga3Al2O12 powders and ceramics
Synthesis and physical behavior of amphiphilic dendrimers with layered organization of hydrophilic and hydrophobic blocks
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