Twelve experiments in restorative justice: the Jerry Lee program of randomized trials of restorative justice conferences

Objectives: We conducted and measured outcomes from the Jerry Lee Program of 12 randomized trials over two decades in Australia and the United Kingdom (UK), testing an identical method of restorative justice taught by the same trainers to hundreds of police officers and others who delivered it to 2231 offenders and 1179 victims in 1995–2004. The article provides a review of the scientific progress and policy effects of the program, as described in 75 publications and papers arising from it, including previously unpublished results of our ongoing analyses. Methods: After random assignment in four Australian tests diverting criminal or juvenile cases from prosecution to restorative justice conferences (RJCs), and eight UK tests of supplementing criminal or juvenile proceedings with RJCs, we followed intention-to-treat group differences between offenders for up to 18 years, and for victims up to 10 years. Results: We distil and modify prior research reports into 18 updated evidence-based conclusions about the effects of RJCs on both victims and offenders. Initial reductions in repeat offending among offenders assigned to RJCs (compared to controls) were found in 10 of our 12 tests. Nine of the ten successes were for crimes with personal victims who participated in the RJCs, with clear benefits in both short- and long-term measures, including less prevalence of post-traumatic stress symptoms. Moderator effects across and within experiments showed that RJCs work best for the most frequent and serious offenders for repeat offending outcomes, with other clear moderator effects for poly-drug use and offense seriousness. Conclusions: RJ conferences organized and led (most often) by specially-trained police produced substantial short-term, and some long-term, benefits for both crime victims and their offenders, across a range of offense types and stages of the criminal justice processes on two continents, but with important moderator effects. These conclusions are made possible by testing a new kind of justice on a programmatic basis that would allow prospective meta-analysis, rather than doing one experiment at a time. This finding provides evidence that funding agencies could get far more evidence for the same cost from programs of identical, but multiple, RCTs of the identical innovative methods, rather than funding one RCT at a time

Climate change impacts on agriculture in 2050 under a range of plausible socioeconomic and emissions scenarios

Previous studies have combined climate, crop and economic models to examine the impact of climate change on agricultural production and food security, but results have varied widely due to differences in models, scenarios and input data. Recent work has examined (and narrowed) these differences through systematic model intercomparison using a high-emissions pathway to highlight the differences. This paper extends that analysis to explore a range of plausible socioeconomic scenarios and emission pathways. Results from multiple climate and economic models are combined to examine the global and regional impacts of climate change on agricultural yields, area, production, consumption, prices and trade for coarse grains, rice, wheat, oilseeds and sugar crops to 2050. We find that climate impacts on global average yields, area, production and consumption are similar across shared socioeconomic pathways (SSP 1, 2 and 3, as we implement them based on population, income and productivity drivers), except when changes in trade policies are included. Impacts on trade and prices are higher for SSP 3 than SSP 2, and higher for SSP 2 than for SSP 1. Climate impacts for all variables are similar across low to moderate emissions pathways (RCP 4.5 and RCP 6.0), but increase for a higher emissions pathway (RCP 8.5). It is important to note that these global averages may hide regional variations. Projected reductions in agricultural yields due to climate change by 2050 are larger for some crops than those estimated for the past half century, but smaller than projected increases to 2050 due to rising demand and intrinsic productivity growth. Results illustrate the sensitivity of climate change impacts to differences in socioeconomic and emissions pathways. Yield impacts increase at high emissions levels and vary with changes in population, income and technology, but are reduced in all cases by endogenous changes in prices and other variables

Climate change impacts on agriculture in 2050 under a range of plausible socioeconomic and emissions scenarios

Previous studies have combined climate, crop and economic models to examine the impact of climate change on agricultural production and food security, but results have varied widely due to differences in models, scenarios and input data. Recent work has examined (and narrowed) these differences through systematic model intercomparison using a high-emissions pathway to highlight the differences. This paper extends that analysis to explore a range of plausible socioeconomic scenarios and emission pathways. Results from multiple climate and economic models are combined to examine the global and regional impacts of climate change on agricultural yields, area, production, consumption, prices and trade for coarse grains, rice, wheat, oilseeds and sugar crops to 2050. We find that climate impacts on global average yields, area, production and consumption are similar across shared socioeconomic pathways (SSP 1, 2 and 3, as we implement them based on population, income and productivity drivers), except when changes in trade policies are included. Impacts on trade and prices are higher for SSP 3 than SSP 2, and higher for SSP 2 than for SSP 1. Climate impacts for all variables are similar across low to moderate emissions pathways (RCP 4.5 and RCP 6.0), but increase for a higher emissions pathway (RCP 8.5). It is important to note that these global averages may hide regional variations. Projected reductions in agricultural yields due to climate change by 2050 are larger for some crops than those estimated for the past half century, but smaller than projected increases to 2050 due to rising demand and intrinsic productivity growth. Results illustrate the sensitivity of climate change impacts to differences in socioeconomic and emissions pathways. Yield impacts increase at high emissions levels and vary with changes in population, income and technology, but are reduced in all cases by endogenous changes in prices and other variables.University Corporation for Atmospheric Research 10.13039/100005626Peer Reviewe

Causal role of thalamic interneurons in brain state transitions: a study using a neural mass model implementing synaptic kinetics

Experimental studies on the Lateral Geniculate Nucleus (LGN) of mammals and rodents show that the inhibitory interneurons (IN) receive around 47.1% of their afferents from the retinal spiking neurons, and constitute around 20–25% of the LGN cell population. However, there is a definite gap in knowledge about the role and impact of IN on thalamocortical dynamics in both experimental and model-based research. We use a neural mass computational model of the LGN with three neural populations viz. IN, thalamocortical relay (TCR), thalamic reticular nucleus (TRN), to study the causality of IN on LGN oscillations and state-transitions. The synaptic information transmission in the model is implemented with kinetic modeling, facilitating the linking of low-level cellular attributes with high-level population dynamics. The model is parameterized and tuned to simulate alpha (8–13 Hz) rhythm that is dominant in both Local Field Potential (LFP) of LGN and electroencephalogram (EEG) of visual cortex in an awake resting state with eyes closed. The results show that: First, the response of the TRN is suppressed in the presence of IN in the circuit; disconnecting the IN from the circuit effects a dramatic change in the model output, displaying high amplitude synchronous oscillations within the alpha band in both TCR and TRN. These observations conform to experimental reports implicating the IN as the primary inhibitory modulator of LGN dynamics in a cognitive state, and that reduced cognition is achieved by suppressing the TRN response. Second, the model validates steady state visually evoked potential response in humans corresponding to periodic input stimuli; however, when the IN is disconnected from the circuit, the output power spectra do not reflect the input frequency. This agrees with experimental reports underpinning the role of IN in efficient retino-geniculate information transmission. Third, a smooth transition from alpha to theta band is observed by progressive decrease of neurotransmitter concentrations in the synaptic clefts; however, the transition is abrupt with removal of the IN circuitry in the model. The results imply a role of IN toward maintaining homeostasis in the LGN by suppressing any instability that may arise due to anomalous synaptic attributes

Optical Atomic Clock Comparison through Turbulent Air

We use frequency comb-based optical two-way time-frequency transfer (O-TWTFT) to measure the optical frequency ratio of state-of-the-art ytterbium and strontium optical atomic clocks separated by a 1.5 km open-air link. Our free-space measurement is compared to a simultaneous measurement acquired via a noise-cancelled fiber link. Despite non-stationary, ps-level time-of-flight variations in the free-space link, ratio measurements obtained from the two links, averaged over 30.5 hours across six days, agree to $6\times10^{-19}$, showing that O-TWTFT can support free-space atomic clock comparisons below the $10^{-18}$ level

Agricultural Investments and Hunger in Africa Modelling Potential Contributions to SDG 2 - Zero Hunger

We use IFPRI’s IMPACT framework of linked biophysical and structural economic models to examine developments in global agricultural production systems, climate change, and food security. Building on related work on how increased investment in agricultural research, resource management, and infrastructure can address the challenges of meeting future food demand, we explore the costs and implications of these investments for reducing hunger in Africa by 2030. This analysis is coupled with a new investment estimation model, based on the perpetual inventory methodology (PIM), which allows for a better assessment of the costs of achieving projected agricultural improvements. We find that climate change will continue to slow projected reductions in hunger in the coming decades—increasing the number of people at risk of hunger in 2030 by 16 million in Africa compared to a scenario without climate change. Investments to increase agricultural productivity can offset the adverse impacts of climate change and help reduce the share of people at risk of hunger in 2030 to five percent or less in Northern, Western, and Southern Africa, but the share is projected to remain at ten percent or more in Eastern and Central Africa. Investments in Africa to achieve these results are estimated to cost about 15 billion USD per year between 2015 and 2030, as part of a larger package of investments costing around 52 billion USD in developing countries

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin