COURTS Juries: Provide the State and the Accused with the Same Number of Peremptory Challenges in Misdemeanor, Felony, and Death Penalty Cases and in Challenging Alternative Jurors; Provide the Manner in Which Peremptory Challenges are Made; Change the Size of the Jury Panel in Felony and Death Penalty Cases; Provide the State with an Equal Number of Additional Peremptory Challenges in Trials for Jointly Indicted Defendants; Provide an Exemption from Jury Duty for a Primary Caregiver of a Child Who Is Four Years of Age or Younger; Provide an Exemption from Jury Duty for a Primary Teacher of Children in a Home Study Program; and for Other Purposes

In 2004, the Georgia General Assembly considered a bill designed to exempt home-school teachers and certain primary caregivers from jury duty. The Senate amended the bill to provide the State and the accused with an equal number of preemptory challenges in death penalty, felony, and misdemeanor cases

COURTS Juries: Provide the State and the Accused with the Same Number of Peremptory Challenges in Misdemeanor, Felony, and Death Penalty Cases and in Challenging Alternative Jurors; Provide the Manner in Which Peremptory Challenges are Made; Change the Size of the Jury Panel in Felony and Death Penalty Cases; Provide the State with an Equal Number of Additional Peremptory Challenges in Trials for Jointly Indicted Defendants; Provide an Exemption from Jury Duty for a Primary Caregiver of a Child Who Is Four Years of Age or Younger; Provide an Exemption from Jury Duty for a Primary Teacher of Children in a Home Study Program; and for Other Purposes

In 2004, the Georgia General Assembly considered a bill designed to exempt home-school teachers and certain primary caregivers from jury duty. The Senate amended the bill to provide the State and the accused with an equal number of preemptory challenges in death penalty, felony, and misdemeanor cases

Product Development Process for Small Unmanned Aerial Systems

The DoD has recognized the need for persistent Intelligence, Surveillance and Reconnaissance (ISR) over the last two decades. Recent developments with commercial drones have changed the market structure; there is now a thriving and extensive market base for drone based remote sensing. This research provides system engineering methods to support the DoD use of this burgeoning market to meet operational ISR needs. The three contributions of this research are: a process to support Small Unmanned Aerial Systems (SUAS) design, tools to support the design process, and tools to support risk assessment and reduction for both design and operations. The process and tools are presented via an exemplar design for an ISR SUAS mission. The exemplar design flows from user needs through to an allocated baseline with an assessment of system reliability based on a compilation of commercial component reliability and failure modes

Latent infection of myeloid progenitors by human cytomegalovirus protects cells from FAS-mediated apoptosis through the cellular IL-10/PEA-15 pathway.

Latent infection of primary CD34(+) progenitor cells by human cytomegalovirus (HCMV) results in their increased survival in the face of pro-apoptotic signals. For instance, we have shown previously that primary myeloid cells are refractory to FAS-mediated killing and that cellular IL-10 (cIL-10) is an important survival factor for this effect. However, how cIL-10 mediates this protection is unclear. Here, we have shown that cIL-10 signalling leading to upregulation of the cellular factor PEA-15 mediates latency-associated protection of CD34(+) progenitor cells from the extrinsic death pathway.We gratefully acknowledge funding from the UK Medical Research Council (J.H.S. G:0701279) which supports the current research in our laboratory and also the support of NIHR UK Biomedical Research Centre (J.H.S.). We thank Linda Teague, Roy Whiston and Stuart McGregor Dallas for technical support and Stuart McGregor Dallas for providing validation data for figure 1.This is the final version. It first appeared at http://jgv.sgmjournals.org/content/journal/jgv/10.1099/vir.0.000180

Measurement of Magnetization Dynamics in Single-Molecule Magnets Induced by Pulsed Millimeter-Wave Radiation

We describe an experiment aimed at measuring the spin dynamics of the Fe8 single-molecule magnet in the presence of pulsed microwave radiation. In earlier work, heating was observed after a 0.2-ms pulse of intense radiation, indicating that the spin system and the lattice were out of thermal equilibrium at millisecond time scale [Bal et al., Europhys. Lett. 71, 110 (2005)]. In the current work, an inductive pick-up loop is used to probe the photon-induced magnetization dynamics between only two levels of the spin system at much shorter time scales (from ns to us). The relaxation time for the magnetization, induced by a pulse of radiation, is found to be on the order of 10 us.Comment: 3 RevTeX pages, including 3 eps figures. The paper will appear in the Journal of Applied Physics as MMM'05 conference proceeding

The European Common Space: Extending the Use of Anchoring Vignettes

In this article, we combine advances in both survey research and scaling techniques to estimate a common dimension for political parties across the member states of the European Union. Most previous scholarship has either ignored or assumed cross-national comparability of party placements across a variety of dimensions. The 2010 wave of the Chapel Hill Expert Survey includes anchoring vignettes which we use as “bridge votes” to place parties from different countries on a common space. We estimate our dimensions using the “blackbox” technique. Our results demonstrate both the usefulness of anchoring vignettes and the broad applicability of the blackbox scaling routine. Further, the resulting scale offers a cross-nationally comparable interval-level measure of a party’s left/right ideological position with a high degree of face validity. In short, we argue that the left/right economic dimension travels well across European countries

Variational Diffusion Models

Diffusion-based generative models have demonstrated a capacity for perceptually impressive synthesis, but can they also be great likelihood-based models? We answer this in the affirmative, and introduce a family of diffusion-based generative models that obtain state-of-the-art likelihoods on standard image density estimation benchmarks. Unlike other diffusion-based models, our method allows for efficient optimization of the noise schedule jointly with the rest of the model. We show that the variational lower bound (VLB) simplifies to a remarkably short expression in terms of the signal-to-noise ratio of the diffused data, thereby improving our theoretical understanding of this model class. Using this insight, we prove an equivalence between several models proposed in the literature. In addition, we show that the continuous-time VLB is invariant to the noise schedule, except for the signal-to-noise ratio at its endpoints. This enables us to learn a noise schedule that minimizes the variance of the resulting VLB estimator, leading to faster optimization. Combining these advances with architectural improvements, we obtain state-of-the-art likelihoods on image density estimation benchmarks, outperforming autoregressive models that have dominated these benchmarks for many years, with often significantly faster optimization. In addition, we show how to use the model as part of a bits-back compression scheme, and demonstrate lossless compression rates close to the theoretical optimum. Code is available at https://github.com/google-research/vdm .Comment: Published at NeurIPS'21. Camera-ready version, with code UR

Zero-Shot Text-Guided Object Generation with Dream Fields

We combine neural rendering with multi-modal image and text representations to synthesize diverse 3D objects solely from natural language descriptions. Our method, Dream Fields, can generate the geometry and color of a wide range of objects without 3D supervision. Due to the scarcity of diverse, captioned 3D data, prior methods only generate objects from a handful of categories, such as ShapeNet. Instead, we guide generation with image-text models pre-trained on large datasets of captioned images from the web. Our method optimizes a Neural Radiance Field from many camera views so that rendered images score highly with a target caption according to a pre-trained CLIP model. To improve fidelity and visual quality, we introduce simple geometric priors, including sparsity-inducing transmittance regularization, scene bounds, and new MLP architectures. In experiments, Dream Fields produce realistic, multi-view consistent object geometry and color from a variety of natural language captions.Comment: CVPR 2022. 13 pages. Website: https://ajayj.com/dreamfield