Returns to schooling in Kazakhstan: OLS and instrumental variables approach

This paper examines rates of return to schooling in Kazakhstan using OLS and instrumental variable (IV) methodologies. We use spouse's education and smoking as instruments. We find that spouse's education is a valid instrument and that conventional OLS estimates that assume the exogenous nature of schooling, and hence do not control for endogeneity bias, may underestimate the true rates of return. The results indicate that the returns to schooling in Kazakhstan have increased with transition. This may reflect the relative scarcities of highly educated people in Kazakhstan with human capital that employers require and, following the market reforms, reward accordingly

Sustainable Advanced Manufacturing of Printed Electronics: An Environmental Consideration

Printing technologies have become a novel and disruptive innovation method of manufacturing electronic components to produce a diverse range of devices including photovoltaic cells, solar panels, energy harvesters, batteries, light sources, and sensors on really thin, lightweight, and flexible substrates. In traditional electronic manufacturing, a functional layer must be deposited, typically through a chemical vapor or physical vapor process for a copper layer for circuitry production. These subtractive techniques involve multiple production steps and use toxic etching chemicals to remove unwanted photoresist layers and metals. In printing, the same functional material can be selectively deposited only where it is needed on the substrate via plates or print heads. The process is additive and significantly reduces not only the number of manufacturing steps, but also the need for energy, time, consumables, as well as the waste. Thereby, printing has been in the focus for many applications as a green, efficient, energy-saving, environmentally friendly manufacturing method. This chapter presents a general vision on green energy resources and then details printed electronics that consolidates green energy and environment relative to traditional manufacturing system

Cold accretion flows and the nature of high column density H I absorption at redshift 3

Simulations predict that galaxies grow primarily through the accretion of gas that has not gone through an accretion shock near the virial radius and that this cold gas flows towards the central galaxy along dense filaments and streams. There is, however, little observational evidence for the existence of these cold flows. We use a large, cosmological, hydrodynamical simulation that has been post‐processed with radiative transfer to study the contribution of cold flows to the observed z= 3 column density distribution of neutral hydrogen, which our simulation reproduces. We find that nearly all of the H I absorption arises in gas that has remained colder than 105.5 K, at least while it was extragalactic. In addition, the majority of the H I is falling rapidly towards a nearby galaxy, with non‐negligible contributions from outflowing and static gas. Above a column density of Graphic cm−2, most of the absorbers reside inside haloes, but the interstellar medium only dominates for Graphic cm−2. Haloes with total mass below 1010 M⊙ dominate the absorption for Graphic cm−2, but the average halo mass increases sharply for higher column densities. Although very little of the H I in absorbers with Graphic cm−2 resides inside galaxies, systems with Graphic cm−2 are closely related to star formation: most of their H I either will become part of the interstellar medium before z= 2 or has been ejected from a galaxy at z > 3. Cold accretion flows are critical for the success of our simulation in reproducing the observed rate of incidence of damped Lyman‐α and particularly that of Lyman limit systems. We therefore conclude that cold accretion flows exist and have already been detected in the form of high column density H I absorbers

The impact of different physical processes on the statistics of Lyman-limit and damped Lyman α absorbers

We compute the z = 3 neutral hydrogen column density distribution function f(NHI) for 19 simulations drawn from the Overwhelmingly Large Simulations project using a post-processing correction for self-shielding calculated with full radiative transfer of the ionizing background radiation. We investigate how different physical processes and parameters affect the abundance of Lyman-limit systems (LLSs) and damped Lyman α absorbers including: (i) metal-line cooling; (ii) the efficiency of feedback from supernovae and active galactic nuclei; (iii) the effective equation of state for the interstellar medium; (iv) cosmological parameters; (v) the assumed star formation law and (vi) the timing of hydrogen reionization. We find that the normalization and slope, D=dlog10f/dlog10NHI, of f(NHI) in the LLS regime are robust to changes in these physical processes. Among physically plausible models, f(NHI) varies by less than 0.2 dex and D varies by less than 0.18 for LLSs. This is primarily due to the fact that these uncertain physical processes mostly affect star-forming gas which contributes less than 10 per cent to f(NHI) in the LLS column density range. At higher column densities, variations in f(NHI) become larger (approximately 0.5 dex at f(NHI) = 1022 cm-2 and 1.0 dex at f(NHI) = 1022 cm-2) and molecular hydrogen formation also becomes important. Many of these changes can be explained in the context of self-regulated star formation in which the amount of star-forming gas in a galaxy will adjust such that outflows driven by feedback balance inflows due to accretion. Tools to reproduce all figures in this work can be found at the following url: https://bitbucket.org/galtay/hi-cddf-owls-

Improving Disaster Response Efforts With Decision Support Systems

As evidenced by Hurricane Katrina in August, 2005, disaster response efforts are hindered by a lack of coordination, poor information flows, and the inability of disaster response managers to validate and process relevant information and make decisions in a timely fashion. A number of factors contribute to current lackluster response efforts. Some are inherent to the complex, rapidly changing decision-making environments that characterize most disaster response settings. Others reflect systematic flaws in how decisions are made within the organizational hierarchies of the many agencies involved in a disaster response. Slow, ineffective strategies for gathering, processing, and analyzing data can also play a role. Information technology, specifically decision support systems, can be used to reduce the time needed to make crucial decisions regarding task assignment and resource allocation. Decision support systems can also be used to guide longer-term decisions involving resource acquisition as well as for training and the evaluation of command and control capability

Classification by voting feature intervals

A new classification algorithm called VFI (for Voting Feature Intervals) is proposed. A concept is represented by a set of feature intervals on each feature dimension separately. Each feature participates in the classification by distributing real-valued votes among classes. The class receiving the highest vote is declared to be the predicted class. VFI is compared with the Naive Bayesian Classifier, which also considers each feature separately. Experiments on real-world datasets show that VFI achieves comparably and even better than NBC in terms of classification accuracy. Moreover, VFI is faster than NBC on all datasets. © Springer-Verlag Berlin Heidelberg 1997

Autekologi dan Fisiologi Percambahan Centaurea kilaea Boiss. dari Turki

In this study germination requirements, plant-soil interactions and population biology of Centaurea kilaea was studied. The plant and soil samples were collected from Sofular Village (Sile District) and shore of Çatalca District (Istanbul) in Turkey by using standard methods. Methods like Scheibler, Wetdigestion, Kjeldahl and Olsen were employed for measurement of soil texture, structure and other physical and chemical characteristics (pH, total protein and electrical conductivity) using spectrophotometer, flame photometer, calcimeter and ICP. The results showed that ranges of different elements in the soil were 0.007-0.2% for N, 0.0007-0.001% for P, 0.001-0.01% for K, 0.0001-0.0002 % for Na. N, P, K and Na values in the plants were 2.17, 0.005, 0.1 and 0.006%, respectively. The data revealed that germination success of the seeds was influenced by the environmental factors such as pH, germination season and temperature.Dalam kajian ini keperluan percambahan, saling tindakan tumbuhan-tanih dan biologi populasi Centaurea kilaea telah dilakukan. Sampel tumbuhan dan tanih telah dikumpul dari Kampung Sofular (Daerah Şile) dan pantai Daerah Çatalca (Istanbul) di Turki dengan menggunakan kaedah piawai. Kaedah seperti Scheibler, Wetdigestion, Kjeldahl dan Olsen telah digunakan bagi pengukuran tekstur tanih, struktur dan sifat fizikal dan kimia lain (pH, jumlah protein dan kekonduksian elektrik) menggunakan spektrofotometer, fotometer api, kalsimeter dan ICP. Hasil menunjukkan bahawa julat unsur berbeza dalam tanih ialah 0.007-0.2% bagi N, 0.0007-0.001% bagi P, 0.001-0.01% bagi K, 0.0001-0.0002% bagi Na. N, P, K dan nilai Na dalam tumbuhan ialah masing-masing 2.17, 0.005, 0.1 dan 0.006%. Data menunjukkan kejayaan percambahan bagi biji benih telah dipengaruhi faktor persekitaran seperti pH, musim percambahan dan suhu

Pathological relevance of post-translationally modified alpha-synuclein (pSer87, pSer129, nTyr39) in idiopathic Parkinson’s disease and Multiple System Atrophy

Aggregated alpha-synuclein (a-synuclein) is the main component of Lewy bodies (LBs), Lewy neurites (LNs), and glial cytoplasmic inclusions (GCIs), which are pathological hallmarks of idiopathic Parkinson’s disease (IPD) and multiple system atrophy (MSA), respectively. Initiating factors that culminate in forming LBs/LNs/GCIs remain elusive. Several species of a-synuclein exist, including phosphorylated and nitrated forms. It is unclear which a-synuclein post-translational modifications (PTMs) appear within aggregates throughout disease pathology. Herein we aimed to establish the predominant a-synuclein PTMs in post-mortem IPD and MSA pathology using immunohistochemistry. We examined the patterns of three a-synuclein PTMs (pS87, pS129, nY39) simultaneously in pathology- affected regions of 15 PD, 5 MSA, 6 neurologically normal controls. All antibodies recognized LBs, LNs, and GCIs, albeit to a variable extent. pS129 a-synuclein antibody was particularly immunopositive for LNs and synaptic dot-like structures followed by nY39 a- synuclein antibody. GCIs, neuronal inclusions, and small threads were positive for nY39 a- synuclein in MSA. Quantification of the LB scores revealed that pS129 a-synuclein was the dominant and earliest a-synuclein PTM followed by nY39 a-synuclein, while lower amounts of pSer87 a-synuclein appeared later in disease progression in PD. These results may have implications for novel biomarker and therapeutic developments

Informal employment in Kazakhstan: a blessing in disguise?

Informality is heterogeneous, dynamic and difficult to quantify; the formal–informal gap in earnings is one major component of it that we wish to examine. Using the 2013 Kazakhstan Labor Force Survey, we analyze the returns that formal and informal workers receive for a given set of characteristics and also use a matching technique to decompose the gap. We observe that in Kazakhstan, there is a substantial earnings gap in favor of formal workers and that a quarter of the gap remains unexplained. Our study also highlights the importance of matching-based decomposition and distributional analysis in explaining the differences in earnings between formal and informal workers

Reverse Engineering Gene Networks with ANN: Variability in Network Inference Algorithms

Motivation :Reconstructing the topology of a gene regulatory network is one of the key tasks in systems biology. Despite of the wide variety of proposed methods, very little work has been dedicated to the assessment of their stability properties. Here we present a methodical comparison of the performance of a novel method (RegnANN) for gene network inference based on multilayer perceptrons with three reference algorithms (ARACNE, CLR, KELLER), focussing our analysis on the prediction variability induced by both the network intrinsic structure and the available data. Results: The extensive evaluation on both synthetic data and a selection of gene modules of "Escherichia coli" indicates that all the algorithms suffer of instability and variability issues with regards to the reconstruction of the topology of the network. This instability makes objectively very hard the task of establishing which method performs best. Nevertheless, RegnANN shows MCC scores that compare very favorably with all the other inference methods tested. Availability: The software for the RegnANN inference algorithm is distributed under GPL3 and it is available at the corresponding author home page (http://mpba.fbk.eu/grimaldi/regnann-supmat