Machine Learning Models for Road Surface and Friction Estimation using Front-Camera Images

Automotive active safety systems can significantlybenefit from real-time road friction estimates (RFE) by adaptingdriving styles, specific to the road conditions. This work presentsa 2-stage approach for indirect RFE estimation using front-viewcamera images captured from vehicles. In stage-1, convolutionalneural network model architectures are implemented to learnregion-specific features for road surface condition (RSC) classification.Texture-based features from the drivable surface, skyand surroundings are found to be separate regions of interest fordry, wet/water, slush and snow/ice RSC classification. In stage-2, a rule-based model that relies on domain-specific guidelinesis implemented to segment the ego-lane drivable surface into[5x3] patches, followed by patch classification and quantization toseparate images with high, medium and low RFE. The proposedmethod achieves average accuracy of 97% for RSC classificationin stage-1 and 89% for RFE classification in stage-2, respectively.The 2-stage models are trained using publicly available datasets to enable benchmarkin

The Parkinson's progression markers initiative (PPMI) - establishing a PD biomarker cohort.

ObjectiveThe Parkinson's Progression Markers Initiative (PPMI) is an observational, international study designed to establish biomarker-defined cohorts and identify clinical, imaging, genetic, and biospecimen Parkinson's disease (PD) progression markers to accelerate disease-modifying therapeutic trials.MethodsA total of 423 untreated PD, 196 Healthy Control (HC) and 64 SWEDD (scans without evidence of dopaminergic deficit) subjects were enrolled at 24 sites. To enroll PD subjects as early as possible following diagnosis, subjects were eligible with only asymmetric bradykinesia or tremor plus a dopamine transporter (DAT) binding deficit on SPECT imaging. Acquisition of data was standardized as detailed at www.ppmi-info.org.ResultsApproximately 9% of enrolled subjects had a single PD sign at baseline. DAT imaging excluded 16% of potential PD subjects with SWEDD. The total MDS-UPDRS for PD was 32.4 compared to 4.6 for HC and 28.2 for SWEDD. On average, PD subjects demonstrated 45% and 68% reduction in mean striatal and contralateral putamen Specific Binding Ratios (SBR), respectively. Cerebrospinal fluid (CSF) was acquired from >97% of all subjects. CSF (PD/HC/SWEDD pg/mL) α-synuclein (1845/2204/2141) was reduced in PD vs HC or SWEDD (P < 0.03). Similarly, t-tau (45/53) and p-tau (16/18) were reduced in PD versus HC (P < 0.01).InterpretationPPMI has detailed the biomarker signature for an early PD cohort defined by clinical features and imaging biomarkers. This strategy provides the framework to establish biomarker cohorts and to define longitudinal progression biomarkers to support future PD treatment trials

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Defining the causes of sporadic Parkinson's disease in the global Parkinson's genetics program (GP2)

The Global Parkinson’s Genetics Program (GP2) will genotype over 150,000 participants from around the world, and integrate genetic and clinical data for use in large-scale analyses to dramatically expand our understanding of the genetic architecture of PD. This report details the workflow for cohort integration into the complex arm of GP2, and together with our outline of the monogenic hub in a companion paper, provides a generalizable blueprint for establishing large scale collaborative research consortia

Multi-ancestry genome-wide association meta-analysis of Parkinson?s disease

Although over 90 independent risk variants have been identified for Parkinson’s disease using genome-wide association studies, most studies have been performed in just one population at a time. Here we performed a large-scale multi-ancestry meta-analysis of Parkinson’s disease with 49,049 cases, 18,785 proxy cases and 2,458,063 controls including individuals of European, East Asian, Latin American and African ancestry. In a meta-analysis, we identified 78 independent genome-wide significant loci, including 12 potentially novel loci (MTF2, PIK3CA, ADD1, SYBU, IRS2, USP8, PIGL, FASN, MYLK2, USP25, EP300 and PPP6R2) and fine-mapped 6 putative causal variants at 6 known PD loci. By combining our results with publicly available eQTL data, we identified 25 putative risk genes in these novel loci whose expression is associated with PD risk. This work lays the groundwork for future efforts aimed at identifying PD loci in non-European populations

The Non-MFN Effects of MFN Specific Tariffs

This paper explores the sources, extent and two consequences of the non-MFN effects of US MFN specific tariffs resulting from within-commodity cross-exporter variation in f.o.b prices. The first consequence is the bias against the developing countries exporting to the US, which is a result of these countries exporting low quality and low priced varieties (Schott, 2004). This bias is measured as the additional loss in imports faced by these countries, from US MFN specific tariffs as opposed to from a benchmark tariff vector defined as the average Advalorem Equivalent (AVE) of the MFN specific tariffs. For fixed world prices, my results using the Anderson-Neary Mercantilist Trade Restrictiveness Index (MTRI) suggest that doubling per capita GDP reduces AVEs by 14%§ . This is equivalent to an additional import loss of 5-8% or 60-80 million dollars, from the group of 120 developing countries exporting to the US. This value is as high as 15-24%, equivalent to 13-20 million dollars for a subsample of the 48 low income countries which export to the US. Another consequence of the Non-MFN effects of MFN specific tariffs is the additional deadweight losses (DWL) accruing to the US on account of US MFN specific tariffs. Since the DWL is proportional to the squares of tariffs, the AVEs of MFN specific tariffs being non-MFN, have an additional cross-country level of variation associated with them, inducing greater welfare losses. With fixed world prices, my results using the Anderson-Neary Trade Restrictiveness Index (TRI) suggest that levying MFN specific tariffs as opposed to the benchmark tariffs, increases the US trade restrictiveness and DWL by an additional 6% and 12% respectively. All my results are robust to five alternative specifications of AVEs, each of which control for the measurement and reporting errors in unit values to various degrees

The Joint Impact of Specific Tariffs and Preferential Trade Agreements: Do Low Income Countries Gain or Lose?

My paper attempts to evaluate the distortions from the non-MFN features of the applied import tariff schedules of WTO member countries, in agricultural trade. Although these countries are bound by the WTO MFN clause to levy MFN import tariffs, the advalorem equivalents of their applied tariff schedule contains non-MFN features – due to the presence of specific tariffs and preferential trade agreements (PTAs). My results show that the global distortions generated by specific tariffs in agriculture are big enough to completely wash out any gains from PTAs in agriculture, suggesting that the non-MFN features of applied import tariff schedules generate a net loss in global welfare and trade surplus. Moreover, the biggest chunk of these losses accrue to the low income countries (LICs)1 and developing countries, which is ironical since it is the interests of precisely these low income countries that the WTO’s MFN clause is meant to protect A policy implication of these results is that future WTO ministerial conferences should focus more on eliminating specific tariffs in agriculture rather than on increasing PTAs in agriculture, since the efficacy of these PTAs is compromised in the presence of specific tariffs

Empirical essays in international trade policy

This dissertation has three essays. The first essay quantifies the distortions from specific tariffs levied by rich countries. The most-favored-nation (MFN) specific tariffs levied by rich countries translate into higher tariff barriers for poor countries exporting low price goods. We show that for poor countries, these higher tariff barriers from specific tariffs offset the gains from preferential tariffs. We apply a two-stage sequential analysis using both a partial and a general equilibrium model to show that the specific tariffs levied by rich countries on their agricultural imports wash away 80% of the welfare benefits and 73% of the market access benefits enjoyed by poor countries from preferential tariffs. The second essay measures the restrictiveness of the EU\u27s applied tariff structure, including the additional restrictiveness from specific tariffs and the reduced restrictiveness from preferential tariffs. We apply the restrictiveness indices proposed by Anderson and Neary (1994, 2003) to a CES model to show that the restrictiveness of the EU\u27s tariff structure in terms of welfare was 16% in the year 2004. In addition, the presence of specific tariffs increase the restrictiveness index by 2 percentage points relative to ad valorem tariffs, and preferential tariffs reduce the restrictiveness index by 8 percentage points relative to most favored nation (MFN) tariffs. Finally, the increase in restrictiveness contributed by specific tariffs is significantly higher when considering only agricultural imports. The third essay estimates the price elasticities of export supply for a broad group of countries at the HS6 level of product classification. We follow the production based GDP function approach to estimate export supply elasticities for 5016 tariff lines in 113 countries. We obtain a mean elasticity of 3.82 across all commodities and all countries, after controlling for endogeneity and measurement errors in unit values, selection bias and serial correlation. Our results show that homogenous commodities have larger export supply elasticities relative to differentiated commodities, and low-income countries have lower export supply elasticities relative to rich countries in capital and skill intensive goods