Treatment effect estimation with covariate measurement error

This paper investigates the effect that covariate measurement error has on a conventional treatment effect analysis built on an unconfoundedness restriction that embodies conditional independence restrictions in which there is conditioning on error free covariates. The approach uses small parameter asymptotic methods to obtain the approximate generic effects of measurement error. The approximations can be estimated using data on observed outcomes, the treatment indicator and error contaminated covariates providing an indication of the nature and size of measurement error effects. The approximations can be used in a sensitivity analysis to probe the potential effects of measurement error on the evaluation of treatment effects

Food and cash transfers: evidence from Colombia

We study food Engel curves among the poor population targeted by a conditional cash transfer programme in Colombia. After controlling for the endogeneity of total expenditure and for the (unobserved) variability of prices across villages, the best fit is provided by a log-linear specification. Our estimates imply that an increase in total expenditure by 10% would lead to a decrease of 1% in the share of food. However, quasi-experimental estimates of the impact of the programme on total and food consumption show that the share of food increases, suggesting that the programme has more complex impacts than increasing household income. In particular, our results are not inconsistent with the hypothesis that the programme, targeted to women, could increase their bargaining power and induce a more than proportional increase in food consumption

Why is consumption more log normal than income? Gibrat’s Law revisited

Significant departures from log normality are observed in income data, in violation of Gibrat’s law. We identify a new empirical regularity, which is that the distribution of consumption expenditures across households is, within cohorts, closer to log normal than the distribution of income. We explain these empirical results by showing that the logic of Gibrat’s law applies not to total income, but to permanent income and to maginal utility. These findings have important implications for welfare and inequality measurement, aggregation, and econometric model analysis

How effective are conditional cash transfers? Evidence from Colombia

Conditional cash transfer (CCT) programmes are becoming an extremely popular tool for improving the education and health outcomes of poor children in developing countries. An incomplete list of countries in which they are being implemented under the support of the World Bank and other international financial institutions includes Mexico, Honduras, Nicaragua, Brazil, Turkey and Mozambique. While the implementation details vary from country to country, many are modelled on the Mexican PROGRESA. In a typical CCT, mothers from poor backgrounds receive cash conditional on their promoting certain activities on behalf of their children. For their youngest children - usually those below the age of 6 - the conditionality involves visits to preventive healthcare centres in which their growth is monitored. School attendance is the most common stipulation for receipt of cash transfers for older children - usually those between 7 and 17 years old. This targeting of health and education of children is at the essence of the long-term poverty alleviation objective of CCT programmes. Such transfer programmes are also aimed at the short-term reduction of poverty, through the provision of immediate funds to indigent households. In this Briefing Note, we will focus on the programme Familias en Acción (FA), the CCT implemented by the Colombian government from 2001/02. In particular, we will provide estimates of how the programme has influenced key welfare indicators such as school attendance, child nutrition and health status, as well as household consumption. In this respect, we will update the preliminary results that were reported in Attanasio et al. (2003 and 2004)

Post-ischemic brain damage: NF-kappaB dimer heterogeneity as a molecular determinant of neuron vulnerability

Nuclear factor-kappaB (NFkB) has been proposed to serve a dual function as a regulator of neuron survival in pathological conditions associated with neurodegeneration. NF-jB is a transcription family of factors comprising five different proteins, namely p50, RelA ⁄ p65, c-Rel, RelB and p52, which can combine differently to form active dimers in response to external stimuli. Recent research shows that diverse NF-jB dimers lead to cell death or cell survival in neurons exposed to ischemic injury. While the p50 ⁄ p65 dimer participates in the pathogenesis of post-ischemic injury by inducing pro-apoptotic gene expression, c-Rel-containing dimers increase neuron resistance to ischemia by inducing anti-apoptotic gene transcription. We present, in this report, the latest findings and consider the therapeutic potential of targeting different NF-kB dimers to limit ischemia-associated neurodegeneration

Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles

Systems neuroscience relies on two complementary views of neural data, characterized by single neuron tuning curves and analysis of population activity. These two perspectives combine elegantly in neural latent variable models that constrain the relationship between latent variables and neural activity, modeled by simple tuning curve functions. This has recently been demonstrated using Gaussian processes, with applications to realistic and topologically relevant latent manifolds. Those and previous models, however, missed crucial shared coding properties of neural populations. We propose feature sharing across neural tuning curves, which significantly improves performance and leads to better-behaved optimization. We also propose a solution to the problem of ensemble detection, whereby different groups of neurons, i.e., ensembles, can be modulated by different latent manifolds. This is achieved through a soft clustering of neurons during training, thus allowing for the separation of mixed neural populations in an unsupervised manner. These innovations lead to more interpretable models of neural population activity that train well and perform better even on mixtures of complex latent manifolds. Finally, we apply our method on a recently published grid cell dataset, recovering distinct ensembles, inferring toroidal latents and predicting neural tuning curves all in a single integrated modeling framework

The RESEARCH project. Soil-related hazards and archaeological heritage in the challenge of climate change

Archaeological Heritage, naturally endangered by environmental processes and anthropogenic pressures, is today increasingly at risk, because of intense human activities and climate change, and their impact on atmosphere and soil. European research is increasingly dedicated to the development of good practices for monitoring archaeological sites and their preservation. One of the running projects about these topics is RESEARCH (Remote Sensing techniques for Archaeology; H2020-MSCA-RISE, grant agreement: 823987), started in 2018 and ending in 2022. RESEARCH aims at testing risk assessment methodology using an integrated system of documentation and research in the fields of archaeology and environmental studies. It will introduce a strategy and select the most efficient tools for the harmonization of different data, criteria, and indicators in order to produce an effective risk assessment. These will be used to assess and monitor the impact of soil erosion, land movement, and land-use change on tangible archaeological heritage assets. As a final product, the Project addresses the development of a multi-task thematic platform, combining advanced remote sensing technologies with GIS application. The demonstration and validation of the Platform will be conducted on six case studies located in Italy, Greece, Cyprus, and Poland, and variously affected by the threats considered by the Project. In the frame of RISE (Research and Innovation Staff Exchange), RESEARCH will coordinate the existing expertise and research efforts of seven beneficiaries into a synergetic plan of collaborations and exchanges of personnel (Ph.D. students and research staff), to offer a comprehensive transfer of knowledge and training environment for the researchers in the specific area. This paper aims at illustrating the results of the activities conducted during the first year of the Project, which consisted in developing an effective risk assessment methodology for soil-related threats affecting archaeological heritage, and defining the scientific requirements and the user requirements of the Platform. The activities have been conducted in synergy with all the Partners and were supported by the possibility of staff exchange allowed by the funding frame MSCA-RISE

Design of a high power production target for the Beam Dump Facility at CERN

The Beam Dump Facility (BDF) project is a proposed general-purpose facility at CERN, dedicated to beam dump and fixed target experiments. In its initial phase, the facility is foreseen to be exploited by the Search for Hidden Particles (SHiP) experiment. Physics requirements call for a pulsed 400 GeV/c proton beam as well as the highest possible number of protons on target (POT) each year of operation, in order to search for feebly interacting particles. The target/dump assembly lies at the heart of the facility, with the aim of safely absorbing the full high intensity Super Proton Synchrotron (SPS) beam, while maximizing the production of charmed and beauty mesons. High-Z materials are required for the target/dump, in order to have the shortest possible absorber and reduce muon background for the downstream experiment. The high average power deposited on target (305 kW) creates a challenge for heat removal. During the BDF facility Comprehensive Design Study (CDS), launched by CERN in 2016, extensive studies have been carried out in order to define and assess the target assembly design. These studies are described in the present contribution, which details the proposed design of the BDF production target, as well as the material selection process and the optimization of the target configuration and beam dilution. One of the specific challenges and novelty of this work is the need to consider new target materials, such as a molybdenum alloy (TZM) as core absorbing material and Ta2.5W as cladding. Thermo-structural and fluid dynamics calculations have been performed to evaluate the reliability of the target and its cooling system under beam operation. In the framework of the target comprehensive design, a preliminary mechanical design of the full target assembly has also been carried out, assessing the feasibility of the whole target system.Comment: 17 pages, 18 figure

A Combine On-Line Acoustic Flowmeter and Fluorocarbon Coolant Mixture Analyzer for The ATLAS Silicon Tracker

An upgrade to the ATLAS silicon tracker cooling control system may require a change from C3F8 (octafluoro-propane) to a blend containing 10-30% of C2F6 (hexafluoro-ethane) to reduce the evaporation temperature and better protect the silicon from cumulative radiation damage with increasing LHC luminosity. Central to this upgrade is a new acoustic instrument for the real-time measurement of the C3F8/C2F6 mixture ratio and flow. The instrument and its Supervisory, Control and Data Acquisition (SCADA) software are described in this paper. The instrument has demonstrated a resolution of 3.10-3 for C3F8/C2F6 mixtures with ~20%C2F6, and flow resolution of 2% of full scale for mass flows up to 30gs-1. In mixtures of widely-differing molecular weight (mw), higher mixture precision is possible: a sensitivity of < 5.10-4 to leaks of C3F8 into the ATLAS pixel detector nitrogen envelope (mw difference 160) has been seen. The instrument has many potential applications, including the analysis of mixtures of hydrocarbons, vapours for semi-conductor manufacture and anaesthesia

Human Red Blood Cells as Oxygen Carriers to Improve Ex-Situ Liver Perfusion in a Rat Model

Ex-situ machine perfusion (MP) has been increasingly used to enhance liver quality in different settings. Small animal models can help to implement this procedure. As most normothermic MP (NMP) models employ sub-physiological levels of oxygen delivery (DO2), the aim of this study was to investigate the effectiveness and safety of different DO2, using human red blood cells (RBCs) as oxygen carriers on metabolic recovery in a rat model of NMP. Four experimental groups (n = 5 each) consisted of (1) native (untreated/control), (2) liver static cold storage (SCS) 30 min without NMP, (3) SCS followed by 120 min of NMP with Dulbecco-Modified-Eagle-Medium as perfusate (DMEM), and (4) similar to group 3, but perfusion fluid was added with human RBCs (hematocrit 15%) (BLOOD). Compared to DMEM, the BLOOD group showed increased liver DO2 (p = 0.008) and oxygen consumption ( V O \u2d9 2) (p &lt; 0.001); lactate clearance (p &lt; 0.001), potassium (p &lt; 0.001), and glucose (p = 0.029) uptake were enhanced. ATP levels were likewise higher in BLOOD relative to DMEM (p = 0.031). V O \u2d9 2 and DO2 were highly correlated (p &lt; 0.001). Consistently, the main metabolic parameters were directly correlated with DO2 and V O \u2d9 2. No human RBC related damage was detected. In conclusion, an optimized DO2 significantly reduces hypoxic damage-related effects occurring during NMP. Human RBCs can be safely used as oxygen carriers