Miracle-dz/UniFAR-FTUs huggingface dataset:
Digitally-assisted sample-to-sample jitter correction in ADC systems

In this paper we present a technique that permits the correction of errors caused by the timing jitter associated with sampling clocks cadencing analog-to-digital converters (ADCs). The correction system is digital, completely independent of the front-end ADC and corrects the data out of the converter on a sample-to-sample basis. Relative to the ADC under consideration, the proposed technique enables quasi-zero jitter sampling characteristics which is demonstrated experimentally in this paper.
TSA-tree: a wavelet-based approach to improve the efficiency of multi-level surprise and trend queries on time-series data

We introduce a novel wavelet based tree structure, termed TSA-tree, which improves the efficiency of multi-level trend and surprise queries on time sequence data. With the explosion of scientific observation data conceptualized as time sequences, we are facing the challenge of efficiently storing, retrieving and analyzing this data. Frequent queries on this data set are to find trends (e.g., global warming) or surprises (e.g., undersea volcano eruption) within the original time series. The challenge, however is that these trend and surprise queries are needed at different levels of abstractions. To support these multi-level trend and surprise queries, sometimes a huge subset of raw data needs to be retrieved and processed. To expedite this process, we utilize our TSA-tree. Each node of the TSA-tree contains pre-computed trends and surprises at different levels. A wavelet transform is used recursively to construct TSA nodes. As a result, each node of TSA tree is readily available for visualization of trends and surprises. In addition, the size of each node is significantly smaller than that of the original time series, resulting in faster I/O operations. However a limitation of TSA-tree is that its size is larger than the original time series. To address this shortcoming, first we prove that the storage space required to store the optimal subtree of TSA-tree (OTSA-tree) is no more than that required to store the original time series without losing any information. Next, we propose two alternative techniques to reduce the size of the OTSA-tree even further while maintaining an acceptable query precision as compared to querying the original time sequences. Utilizing real and synthetic time sequence databases, we compare our techniques with some well known algorithms.
Education and future fertility trends, with special reference to mid-transitional countries

Of all the indicators of socio-economic status, schooling has been most widely used by demographers. Education of adults persistently emerges as the single most powerful predictor of their demographic behaviour. Thus, length of schooling is associated with the start of reproductive life (age at marriage and maternity), with childbearing and the use of birth control, and with mortality. Until the late 1970s, the pervasive influence of educational background of individuals and couples on a range of demographic outcomes was thought by many researchers to reflect the close link between extent of formal schooling and material circumstances; schooling was typically taken to be an indicator of socioeconomic status, and interest in its association with fertility and mortality was correspondingly diluted. The turning point was the publication of results from a survey in Nigeria that showed the schooling of mothers to be a more powerful predictor of child survival than economic characteristics of the family, such as the father's occupation (Caldwell, 1979) together with an extensive review of the educationalfertility relationships that came to similar conclusions (Cochrane, 1979). Subsequent research has confirmed that the schooling of the mother is generally a more decisive influence on reproduction than characteristics of the father.
Machine learning helps physicians in diagnosing of mitral valve prolapse

In this paper we present a multimethod approach for induction of a specific class of classifiers, which can assist physicians in medical diagnosing in the case of mitral valve prolapse. Mitral valve prolapse is one of the most controversial prevalent cardiac condition and may affect up to ten percent of the population and in the worst case results in sudden death. MultiVeDec is a general framework enabling researchers to generate various intelligent tools based on machine learning. In this paper we focused on various decision tree methods, which are capable of extracting knowledge in a form closer to human perception, a feature that is very important in medical field. The experiment included classifiers with various classical single method approaches, evolutionary approaches, hybrid approaches and also our newest multimethod approach. The main concern of the latest approach is to find a way to enable dynamic combination of methodologies to the somehow quasi unified knowledge representation. The proposed multimethod approach was capable to outperform all other tested approaches by producing classifier for diagnosing mitral valve prolapse with the highest overall and average class accuracy. More importantly, it was also capable to find some new knowledge important in diagnosing of mitral valve prolapse.
U.S. Government Counterinsurgency Guide

Abstract : In recent years the United States has engaged in prolonged counterinsurgency campaigns. Counterinsurgency (COIN) is the blend of comprehensive civilian and military efforts designed to simultaneously contain insurgency and address its root causes. This Guide distills the best of contemporary thought, historical knowledge, and hard-won practice. This guide employs a COIN model that comprises four main functional components: The political function is the key function, providing a framework of political reconciliation, and reform of governance around which all other COIN activities are organized. In general, a COIN strategy is only as good as the political plan. The economic function seeks to provide essential services and stimulate long term economic growth, thereby generating confidence in the government while at the same time reducing the pool from which insurgents can readily recruit. The security function is an enabler for the other functions and involves development not just of the affected nation's military force, but its whole security sector. Establishing security is not a precursor to economic and governance activity: rather security, economic and governance activity must be developed in parallel. The information function comprises intelligence (required to gain understanding), and influence (to promote the affected government's cause). It is essential that the influence campaign is in tune with the strategic narrative, resonates with the relevant audiences, is based on genuine resolve by the affected government and that physical actions match. What makes COIN different is that both elements of the information function will be conducted in stark competition with the insurgents own information functions. These four functions contribute to the overall objective of enabling the affected government to establish control, consolidating and then transitioning it from intervening forces to national forces and from military to civil institutions.
Firm Heterogeneity and the Structure of Export and FDI:Evidence from Japanese Manufacturing Industries

The percentage of exporters and multinational enterprises (MNEs) varies substantially across industries. We extend the firm heterogeneity model presented in Helpman et al. (2004) to derive testable predictions about the prevalence of these internationalized modes. The model indicates that intra-industry firm heterogeneity and R&D intensity play large roles in the inter-industry variation of the number of internationalized firms. We investigate whether these factors as well as import tariff affect the structure of export and foreign direct investment (FDI) using Japanese industry-level data. We obtain results that are consistent with the model. First, industries with larger productivity dispersion have a larger percentage of non-MNE exporters, a larger percentage of MNEs, and a larger percentage of the sum of exporters and MNEs. Second, MNEs are heavily concentrated in R&D intensive industries. In addition, we reveal that lower import tariffs raise the percentage of exporters and MNEs in line with Melitz (2003).
Restructuring High Schools for Equity and Excellence: What Works (Sociology of Education Series)

Do students who attend restructured high schools learn more? Is learning in these schools equal for students of different social groups? This distinctive volume is the first to explore these questions using data from a large (over 800 private and public schools) national survey. Demonstrating empirical links to achievement, this book investigates how restructuring relates to such organizational and structural properties of schools as their size, the curriculum, instruction, their teachers' attitudes toward students, and how they press their students to work hard and succeed. Going beyond any existing work on this topic, Restructuring High Schools for Equity and Excellence demystifies the statistical analyses to draw implications and make recommendations for school reform and school policy.
A kinodynamic planning-learning algorithm for complex robot motor control

Robot motor control learning is currently one of the most active research areas in robotics. Many learning techniques have been developed for relatively simple problems. However, very few of them have direct applicability in complex robotic systems without assuming prior knowledge about the task, mainly due to three facts. Firstly, they scale badly to continues and high dimensional problems. Secondly, they need too many real robot-environment interactions. Finally, they are not capable of adapting to environment or robot dynamic changes. In order to overcome these problems, we have developed a new algorithm capable of finding from scratch open-loop state-action trajectory solutions by mixing sample-based tree kinodynamic planning with dynamic model learning. Some results demonstrating the viability of this new type of approach in the cart-pole swing-up task problem are presented.
Ectomycorrhizal identity determines respiration and concentrations of nitrogen and non-structural carbohydrates in root tips: a test using Pinus sylvestris and Quercus robur saplings.

Fine roots play a significant role in plant and ecosystem respiration (RS); therefore, understanding factors controlling that process is important both to advancing understanding and potentially in modelling carbon (C) budgets. However, very little is known about the extent to which ectomycorrhizal (ECM) identity may influence RS or the underlying chemistry that may determine those rates. In order to test these relationships, we examined RS, measured as O(2) consumption, of first-order ECM root tips of Pinus sylvestris L. and Quercus robur L. saplings in relation to their ECM fungal symbionts and associated nitrogen (N), C and non-structural carbohydrate concentrations. Roots of P. sylvestris were colonized by Rhizopogon roseolus, Tuber sp. 1 and an unknown species of Pezizales. Fungal species colonizing Q. robur roots were Hebeloma sp. , Tuber sp. 2 and one unidentified ECM fungus described as Tuber-like based on ECM morphology. ECM RS rates for different host species were significantly different and more than 97% of the variation in RS within a host species was explained by ECM root tip N concentrations. This may indicate that some of the variability in fine root RS-N relationships observed between and within different host species or their functional groups may be related to intraspecific host species differences in root tip N concentration among ECM fungal associates.
Decadal Variability and Predictability in the Midlatitude Ocean–Atmosphere System

Abstract The coupled ocean–atmosphere interaction and predictability associated with the tropical El Nino phenomenon has motivated researchers to seek analogous phenomena in the midlatitudes as well. Are there midlatitude coupled ocean–atmosphere modes? Is there significant predictability in the midlatitudes? The authors address these questions in the broader context of trying to understand the mechanisms behind midlatitude variability, using an idealized model of the ocean–atmosphere system. The atmosphere is represented using a global two-level eddy-resolving primitive equation model with simplified physical parameterizations. The ocean is represented using a state-of-the-art ocean general circulation model, but configured in a simple Atlantic-like sector geometry. In addition to a coupled integration using this model, uncoupled integrations of the component oceanic and atmospheric models are also carried out to elucidate the mechanisms behind midlatitude variability. The sea surface temperature in the .
Capturing Arabidopsis Root Architecture Dynamics with root-fit Reveals Diversity in Responses to Salinity1[W][OPEN]

Natural variation in the dynamic response to salt stress of the Arabidopsis root system can be divided between four distinct strategies. The plant root is the first organ to encounter salinity stress, but the effect of salinity on root system architecture (RSA) remains elusive. Both the reduction in main root (MR) elongation and the redistribution of the root mass between MRs and lateral roots (LRs) are likely to play crucial roles in water extraction efficiency and ion exclusion. To establish which RSA parameters are responsive to salt stress, we performed a detailed time course experiment in which Arabidopsis (Arabidopsis thaliana) seedlings were grown on agar plates under different salt stress conditions. We captured RSA dynamics with quadratic growth functions (root-fit) and summarized the salt-induced differences in RSA dynamics in three growth parameters: MR elongation, average LR elongation, and increase in number of LRs. In the ecotype Columbia-0 accession of Arabidopsis, salt stress affected MR elongation more severely than LR elongation and an increase in LRs, leading to a significantly altered RSA. By quantifying RSA dynamics of 31 different Arabidopsis accessions in control and mild salt stress conditions, different strategies for regulation of MR and LR meristems and root branching were revealed. Different RSA strategies partially correlated with natural variation in abscisic acid sensitivity and different Na+/K+ ratios in shoots of seedlings grown under mild salt stress. Applying root-fit to describe the dynamics of RSA allowed us to uncover the natural diversity in root morphology and cluster it into four response types that otherwise would have been overlooked.
Fighting persistent regional unemployment â€“ The Paltamo Full Employment experiment

This study evaluates a regional full employment initiative using the synthetic control method introduced by Abadie and Gardeazabal (2003). The aim of the Paltamo Full Employment (PFE) experiment launched in 2009 is to reverse the trend of high and persistent unemployment in contracting regions. The basic idea behind the experiment is to collect all unemployment related expenditures together and use them in employing all unemployed persons. According to our results, the PFE-experiment has managed to lower the unemployment rate in Paltamo by almost 10 percentage points in just two years time during an era of global financial crisis. The costs of this remarkable drop in unemployment were 3.4 million Euros in 2010. The results show that one fifth of this amount is covered by reduced expenditures on unemployment allowances and housing allowances.
Ieee Transactions on Information Forensics and Security 1 Digital Image Forensics vs. Image Composition: an Indirect Arms Race

—The field of image composition is constantly trying to improve the ways in which an image can be altered and enhanced. While this is usually done in the name of aesthetics and practicality, it also provides tools that can be used to maliciously alter images. In this sense, the field of digital image forensics has to be prepared to deal with the influx of new technology, in a constant arms-race. In this paper, the current state of this arms-race is analyzed, surveying the state-of-the-art and providing means to compare both sides. A novel scale to classify image forensics assessments is proposed, and experiments are performed to test composition techniques in regards to different forensics traces. We show that even though research in forensics seems unaware of the advanced forms of image composition, it possesses the basic tools to detect it.
India-EU mobility : building bonds through remittances and philanthropy

International migration has evolved to be an important component of both economic and social structure of the Indian economy. The economic returns of migration, primarily international remittances have a significant effect on the households’ social and economic well-being. Another form of monetary transfer, the philanthropic donations also significantly contribute towards the regional development in the country. While both these flows are important returns of migration, our existing policies tend to have a dichotomized approach in understanding and facilitating these flows. This study thus broadens the definition of migrants’ private transfers by using the term ‘Private Givings’ which captures different forms of resources transferred by the migrants, primarily, – remittances which are the usual family level household transfers, made specifically for the consumption purposes of the families and philanthropic donations made by the migrants to the local economy and the society as a large. By bringing in different forms of migrants transfers in the same frame, the paper then focuses on the Indian Diasporas in the EU. It tries to map the migration background of the immigrants in the EU, in terms of their destination of migration, duration of migration and occupational profile, with the resources that they send back, i.e., the nature of private givings generated by these emigrants, and eventually map these private givings with the regional development.
Electronically delivered, multicomponent intervention to reduce unnecessary antibiotic prescribing for respiratory infections in primary care: a cluster randomised trial using electronic health records—REDUCE Trial study original protocol

Introduction Respiratory tract infections (RTIs) account for about 60% of antibiotics prescribed in primary care. This study aims to test the effectiveness, in a cluster randomised controlled trial, of electronically delivered, multicomponent interventions to reduce unnecessary antibiotic prescribing when patients consult for RTIs in primary care. The research will specifically evaluate the effectiveness of feeding back electronic health records (EHRs) data to general practices. Methods and analysis 2-arm cluster randomised trial using the EHRs of the Clinical Practice Research Datalink (CPRD). General practices in England, Scotland, Wales and Northern Ireland are being recruited and the general population of all ages represents the target population. Control trial arm practices will continue with usual care. Practices in the intervention arm will receive complex multicomponent interventions, delivered remotely to information systems, including (1) feedback of each practice's antibiotic prescribing through monthly antibiotic prescribing reports estimated from CPRD data; (2) delivery of educational and decision support tools; (3) a webinar to explain and promote effective usage of the intervention. The intervention will continue for 12 months. Outcomes will be evaluated from CPRD EHRs. The primary outcome will be the number of antibiotic prescriptions for RTIs per 1000 patient years. Secondary outcomes will be: the RTI consultation rate; the proportion of consultations for RTI with an antibiotic prescribed; subgroups of age; different categories of RTI and quartiles of intervention usage. There will be more than 80% power to detect an absolute reduction in antibiotic prescription for RTI of 12 per 1000 registered patient years. Total healthcare usage will be estimated from CPRD data and compared between trial arms. Ethics and dissemination Trial protocol was approved by the National Research Ethics Service Committee (14/LO/1730). The pragmatic design of the trial will enable subsequent translation of effective interventions at scale in order to achieve population impact. Trial registration number ISRCTN95232781; Pre-results.
Isolation of anti-angiogenesis antibodies from a large combinatorial repertoire by colony filter screening.

We describe here a method, based on iterative colony filter screening, for the rapid isolation of binding specificities from a large synthetic repertoire of human antibody fragments in single-chain Fv configuration. Escherichia coli cells, expressing the library of antibody fragments, are grown on a porous master filter, in contact with a second filter coated with the antigen, onto which antibodies secreted by the bacteria are able to diffuse. Detection of antigen binding on the second filter allows the recovery of a number of E.coli cells, including those expressing the binding specificity of interest, which can be submitted to a second round of screening for the isolation of specific monoclonal antibodies. We tested the methodology using as antigen the ED-B domain of fibronectin, a marker of angiogenesis. From an antibody library of 7 x 10(8) clones, we recovered a number of specifically-binding antibodies of different aminoacid sequence. The antibody clone showing the strongest enzyme-linked immunosorbent assay signal (ME4C) was further characterised. Its epitope on the ED-B domain was mapped using the SPOT synthesis method, which uses a set of decapeptides spanning the antigen sequence synthesised and anchored on cellulose. ME4C binds to the ED-B domain with a dissociation constant K:(d) = 1 x 10(-7) M and specifically stains tumour blood vessels, as shown by immunohistochemical analysis on tumour sections of human and murine origin.
In-situ multi-scattering tomography

To recover the three dimensional (3D) volumetric distribution of matter in an object, images of the object are captured from multiple directions and locations. Using these images tomographic computations extract the distribution. In highly scattering media and constrained, natural irradiance, tomography must explicitly account for o-axis scattering. Furthermore, the tomographic model and recovery must function when imaging is done in-situ, as occurs in medical imaging and ground-based atmospheric sensing. We formulate tomography that handles arbitrary orders of scattering, using a monte-carlo model. Moreover, the model is highly parallelizable in our formulation. This enables large scale rendering and recovery of volumetric scenes having a large number of variables. We solve stability and conditioning problems that stem from radiative transfer (RT) modeling in-situ.
Assessing Immigrant Policy Options : Labor Market Conditions and Post-Reform Declines in Immigrant Welfare Receipt *

Researchers have infrequently focused on assessing the degree to which the changes in welfare policy legislated during the 1990s have affected welfare receipt among immigrants. Using March Current Population Survey (CPS) data, this paper analyzes the contribution of local labor market conditions to the explanation of relative declines in immigrant welfare receipt for the period 1994 to 2000. The results from a series of models including labor market area and state fixed effects indicate that employment and unemployment rates across MSAs and states account for at least one-third of the observed relative decrease among immigrants. The paper discusses the policy implications of the findings.