Miracle-dz/UniFAR-FTUs huggingface dataset:
Fronto-temporal disconnectivity and symptom severity in children with autism spectrum disorder

Abstract Objectives. There is increasing evidence that many of the core behavioural impairments in autism spectrum disorders (ASD) emerge from disconnectivity of networks that are important for social communication. The present study aimed at investigating which specific fibre tracts are impaired in ASD and if possible alterations of white matter are associated with clinical symptomatology. Methods. Eighteen children with ASD and 18 carefully matched typically developing controls aged 6–12 years were examined using diffusion tensor imaging (DTI) and voxel-based morphometry (VBM). Fractional anisotropy (FA) values were correlated with symptom severity as indexed by the children's scores on the Autisms Diagnostic Observation Schedule (ADOS) and the Autism Diagnostic Interview-Revised (ADI-R). Results. Decreased FA values were identified for the fornix (FO), the superior longitudinal fasciculus (SLF) the corpus callosum and the uncinate fasciculus (UF) in the ASD group compared to controls, with most prominent differences in the UF bilaterally and the right SLF. FA values of affected fibre tracts were negatively associated with clinical measures of autistic symptomatology. We did not observe significantly altered grey or white matter concentration after correction for multiple comparisons. Conclusion. Our findings support the hypothesis of abnormal white matter microstructure of fronto-temporal cortical networks in ASD, which are associated with core symptoms of the disorder.
Gas Industry Reforms and Consumers’ Prices in the European Union: An Empirical Analysis

This paper offers an empirical analysis of the impact of reforms in the natural gas industry on consumer prices across the EU-15 area. After briefly reviewing the most recent reforms, we study the relationship between regulatory indicators and price dynamics by means of panel data econometrics. Our findings suggest that so far there is limited evidence of beneficial effects for European consumers from the standard package of gas industry reforms.
The impact of fiscal policy and inflation on national saving: the Italian case

Apart from income there are two other main influences on national savings: fiscal policy and inflation. The authors construct a model of the Italian economy to analyse the impact of these two related variables. It is concluded that past government deficits have produced a proportional reduction in national saving. Since the early 1960s national savings have declined by nearly 9 percentage points, of which 3.6 percentage points can be accounted for by a 4 per cent increase in the government's deficit. The results regarding the impact of inflation are not definite, and no conclusion is drawn.
Are Asian Stock Market Returns Predictable?

ABSTRACT We conduct predictability tests for selected Asian stock markets using monthly data from the period March 2001–April 2012. Asian market bears and returns are predicted using the U.S. stock market bears and returns. A two-state Markov-switching model is employed to distinguish between the bull and bear regimes in the U.S. and Asian stock markets. The in-sample predictability analysis suggests that the U.S. market returns and bears are important predictors of Asian market returns and some Asian bears. The out-of-sample predictability exercise is not able to reinforce the in-sample results, which is in large part due to the small forecasting sample size.
An integrated implementation model of strategic planning, BSC and Hoshin management

In pursuit of excellence in business performance and long-term profits, strategic planning and Hoshin management have been widely implemented as strategic-management tools for some time. In recent years, the Balanced Scorecard (BSC) has also been gaining in popularity. Indeed, some organisations have been implementing these three management systems simultaneously. The present study compares and contrasts strategic planning, Hoshin management and BSC. Although differences exist, these strategic-management systems can be integrated on the basis of the features they share in common. Moreover, because each system has its shortcomings, the combination of the differences can overcome the individual weaknesses of each methodology. The paper presents an integrated model of strategic planning, BSC and Hoshin management, and provides a practical case study of its hugely successful implementation. The study confirms that this integrated model is feasible and effective.
Energy Efficient and Load Balanced Routing for Wireless Multihop Network Applications

Wireless Sensor Networks (WSNs) can benefit from ad hoc networking technology characterized by multihop wireless connectivity and infrastructure less framework. These features make them suitable for next-generation networks to support several applications such M2M applications for smart cities and public safety scenarios. Pivotal design requirements for these scenarios are energy efficiency, since many of these devices will be battery powered placing a fundamental limit on network, and specifically node lifetime. Moreover, the way in which traffic is managed also influences network lifetime, since there is a high probability for some nodes to become overloaded by packet forwarding operations in order to support neighbour data exchange. These issues imply the need for energy efficient and load balanced routing approaches that can manage the network load and not only provide reduced energy consumption on the network but also prolong the network lifetime providing robust and continuous. This work proposes a new energy efficient and traffic balancing routing approach that can provide a weighted and flexible trade-off between energy consumption and load dispersion. Simulation results show that the proposed protocol achieves high energy efficiency, decreases the percentage of failed nodes due to lack of battery power, and extends the lifespan of the network.
Genetic improvement of software: from program landscapes to the automatic improvement of a live system

In today’s technology driven society, software is becoming increasingly important in more areas of our lives. The domain of software extends beyond the obvious domain of computers, tablets, and mobile phones. Smart devices and the internet-of-things have inspired the integration of digital and computational technology into objects that some of us would never have guessed could be possible or even necessary. Fridges and freezers connected to social media sites, a toaster activated with a mobile phone, physical buttons for shopping, and verbally asking smart speakers to order a meal to be delivered. This is the world we live in and it is an exciting time for software engineers and computer scientists. The sheer volume of code that is currently in use has long since outgrown beyond the point of any hope for proper manual maintenance. The rate of which mobile application stores such as Google’s and Apple’s have expanded is astounding. The research presented here aims to shed a light on an emerging field of research, called Genetic Improvement (GI) of software. It is a methodology to change program code to improve existing software. This thesis details a framework for GI that is then applied to explore fitness landscape of bug fixing Python software, reduce execution time in a C++ program, and integrated into a live system. We show that software is generally not fragile and although fitness landscapes for GI are flat they are not impossible to search in. This conclusion applies equally to bug fixing in small programs as well as execution time improvements. The framework’s application is shown to be transportable between programming languages with minimal effort. Additionally, it can be easily integrated into a system that runs a live web service. The work within this thesis was funded by EPSRC grant EP/J017515/1 through the DAASE project. 1 1 http://daase.cs. ucl.ac. uk/
Concepts and allgorithms for the deformation, analysis, and compression of digital shapes

This thesis concerns model reduction techniques for the efficient numerical treatment of physical systems governing the deformation behavior of geometrically complex shapes. We present new strategies for the construction of simplified, low-dimensional models that capture the main features of the original complex system and are suitable for use in interactive computer graphics applications. To demonstrate the effectiveness of the new techniques we propose frameworks for real-time simulation and interactive deformation-based modeling of elastic solids and shells and compare them to alternative approaches. In addition, we investigate differential operators that are derived from the physical models and hence can serve as alternatives to the Laplace-Beltrami operator for applications in modal shape analysis. Furthermore, this thesis addresses the compression of digital shapes. In particular, we present a lossless compression scheme that is adapted to the special characteristics of adaptively refined, hierarchical meshes.
Astrocyte reactivity to unconjugated bilirubin requires TNF‐α and IL‐1β receptor signaling pathways

Jaundice and sepsis are common neonatal conditions that can lead to neurodevelopment sequelae, namely if present at the same time. We have reported that tumor necrosis factor (TNF)‐α and interleukin (IL)‐1β are produced by cultured neurons and mainly by glial cells exposed to unconjugated bilirubin (UCB). The effects of these cytokines are mediated by cell surface receptors through a nuclear factor (NF)‐κB‐dependent pathway that we have showed to be activated by UCB. The present study was designed to evaluate the role of TNF‐α and IL‐1β signaling on astrocyte reactivity to UCB in rat cortical astrocytes. Exposure of astrocytes to UCB increased the expression of both TNF‐α receptor (TNFR)1 and IL‐1β receptor (IL‐1R)1, but not TNFR2, as well as their activation, observed by augmented binding of receptors' molecular adaptors, TRAF2 and TRAF6, respectively. Silencing of TNFR1, using siRNA technology, or blockade of IL‐1β cascade, using its endogenous antagonist, IL‐1 receptor antagonist (IL‐1ra), prevented UCB‐induced cytokine release and NF‐κB activation. Interestingly, lack of TNF‐α signal transduction reduced UCB‐induced cell death for short periods of incubation, although an increase was observed after extended exposure; in contrast, inhibition of IL‐1β cascade produced a sustained blockade of astrocyte injury by UCB. Together, our data show that inflammatory pathways are activated during in vitro exposure of rat cortical astrocytes to UCB and that this activation is prolonged in time. This supports the concept that inflammatory pathways play a role in brain damage by UCB, and that they may represent important pharmacological targets. © 2010 Wiley‐Liss, Inc.
Normative data for the letter-cancellation task in school children

Aims: To establish the norms for the letter-cancellation task—a psychomotor performance task. Materials and Methods: Eight hundred nineteen school students were selected in the present study in an age range between nine and 16 years (M = 12.14; SD = 1.78 years). Subjects were assessed once for the cancellation task. Results: Both age and sex influenced performance on the SLCT; therefore, correction scores were obtained on the basis of these factors. Conclusions: The availability of Indian normative data for the SLCT will allow wider application of this test in clinical practice.
Productivity in sports organisational training activities: A DEA study

In this paper, we analyse the productivity of organisational sports training courses implemented by Portuguese sports federations with the aim of improving competitive performance within each respective sport. This training is financed by the State and, depending on the management procedure adopted by the federations, it can induce improvements or deterioration of training productivity. We analyse the efficiency of this activity using a benchmark procedure, data envelopment analysis (DEA), which permits us to separate total productivity into technical efficiency and technological change. We find that there is every possible combination of technical efficiency and technological change In the sample analysed, with only a small group of federations simultaneously exhibiting improvements in both areas, denoting that there is room for further improvement in this activity.
A Longitudinal Investigation of Mammographic Density: The Multiethnic Cohort

Mammographic densities are hypothesized to reflect the cumulative exposure to risk factors that influence breast cancer incidence. This report analyzed percent densities over time and explored predictors of density change in relation to age. The study population consisted of 607 breast cancer cases and 667 frequency matched controls with 1,956 and 1,619 mammographic readings, respectively. Mammograms done over >20 years and before a diagnosis of breast cancer were assessed for densities using a computer-assisted method. Using multilevel modeling to allow for repeated measurements, we estimated the effect of ethnicity, case status, reproductive characteristics, hormonal therapy, body mass index, and soy intake on initial status and longitudinal change. After integrating the area under the percent density curve, cumulative percent density was compared with age-specific breast cancer rates in Hawaii. Percent densities decreased ∼5.6% per 10 years but a nonlinear effect indicated a faster decline earlier in life. Cumulative percent densities and age-specific breast cancer rates increased at very similar rates; both standardized regression coefficients were >0.9. Japanese ancestry, overweight, estrogen/progestin treatment, and, to a lesser degree, estrogen-only therapy predicted a slower decline in densities with age. Case status and adult soy intake were related to higher densities whereas overweight and having any child were associated with lower densities at initial status. Risk factors that influence the decline in mammographic densities over time may be important for breast cancer prevention because cumulative percent densities may reflect the age-related increase in breast cancer risk. (Cancer Epidemiol Biomarkers Prev 2006;15(4):732–9)
The Asymptotic Distribution of Extreme Stock Market Returns

This article presents a study of extreme stock market price movements. According to extreme value theory, the form of the distribution of extreme returns is precisely known and independent of the process generating returns. Using data for an index of the most traded stocks on the New York Stock Exchange for the period 1885-1990, the author shows empirically that the extreme returns obey a Frechet distribution. Copyright 1996 by University of Chicago Press.
The Language, Working Memory, and Other Cognitive Demands of Verbal Tasks

Purpose: To gain a better understanding of the cognitive processes supporting verbal abilities, the underlying structure and interrelationships between common verbal measures were investigated. Methods: An epidemiological sample (n = 374) of school-aged children completed standardized tests of language, intelligence, and short-term and working memory, as well as nonstandardized measures of grammaticality judgment, rapid naming, and sentence recall. Results: Results of a principal component analysis revealed 4 factors corresponding to domain-general working memory, language processing, phonological short-term memory, and fluid reasoning. In corresponding analyses based on younger and older halves of the data, more variables loaded on the fluid reasoning factor for the younger group, and more task variance was explained by the language or phonological storage factors for the older group. The language processing factor correlated with all of the nonstandardized measures, whereas rapid naming was additionally correlated with working memory. Discussion/conclusions: Separable cognitive processes influence performance on common verbal measures, which has implications for assessment and intervention of children with developmental language impairments.
Peer review expert selection method research based on knowledge set theory

Peer review expert selection is an important link of fund project review; it can not only improve the matching accuracy of domain experts and projects, but also improve the appraisal quality in fund project review. This paper mainly studies the peer review expert selection method in fund project review. With the actual experience of fund project management, based on the author's knowledge set theory, paper analyzes deeply knowledge set representation of expert knowledge, improves the similarity calculation of expert and project knowledge, builds the peer review expert selection method, and gives the actual example.
Deep learning for hydrophone big data

This paper presents an efficient deep learning framework for long-term monitoring of acoustic events from hydrophone big data. The large-scale noisy ONC (Ocean Networks Canada) data may contain rare acoustic events, which can be automatically recognized by utilizing a deep convolutional neural network. Few works have been reported in the area of deep learning for the recognition of different kinds of marine mammal calls which however is crucial for many applications such as marine navigation. In this proposed scheme, deep learning feature sets are adopted and processed by a support vector machione (SVM) classifier. The proposed method is tested with 28685 minutes of data, spanning a single year with 5573 whale calls/acoustic events, and using a human operator's annotations. The experimental results show that the average accuracy rate of recognition using deep feature learning are 98.69% (two-class) and 94.48% (multi-class), respectively, for the proposed recognition scheme, which outperforms the MFCC-based method.
A safety evaluation of canakinumab for the treatment of systemic onset juvenile idiopathic arthritis

Introduction: Interleukin-1 (IL-1) is the key molecule of a strong pro-inflammatory pathway in the innate immune system. The IL-1 family harbors components with pro- and anti-inflammatory effects essential for the regulation of the inflammation process. Auto-inflammatory diseases and systemic onset juvenile idiopathic arthritis (JIA) are examples of chronic inflammatory diseases that are IL-1 dependent. IL-1 blockade has proven to be very effective and has greatly improved the outcome of these disorders. Areas covered: This review describes the components of the IL-1 family and the available IL-1 blocking agents for clinical practice. Among them, canakinumab was more recently introduced. Based on the published clinical trials one can conclude that the clinical efficacy in auto-inflammatory diseases is at least as good as other IL-1 blocking agents. The safety data are limited to those registration studies (Phase 2 and 3). In short term the adverse events described are not very different from the other IL-1 blockers. Expert opinion: Longer term use in larger numbers of patients and adequate data collection using large-scale registries are necessary to provide us with a well-balanced overview of safety issues of canakinumab. Registration studies and open label extension studies show an acceptable safety profile so far.
Estimating the supply response of cotton and cereal crops in smallholder production systems: recent evidence from Mali

Cotton is one of the most important crops in West Africa and is a major catalyst of economic development in rural areas, but the sector has suffered from a decline in the world cotton price after 1999. This article exploits an unusual data set following 82 farmers over 14 years, from 1994 through 2007, to estimate a Nerlovian supply response model for cotton, maize, sorghum, and millet in long-term rotation. The resulting system of equations is estimated with two-stage least squares (2SLS), showing that this sample of Malian cotton producers have responded to prices in a relatively inelastic manner, with supply elasticities only about one-half of those estimated for producers in developed countries. Policy reforms could help producers respond more easily to prices changes, as well as to raise average productivity levels. Copyright (c) 2009 International Association of Agricultural Economists.
Does a Switch of Budget Regimes Affect Investment and Managerial Discretion of State-Owned Enterprises? Evidence from Italian Firms

Abstract We investigate the investment decisions of Italian state-owned enterprises (SOEs) across budget constraint regimes and carry out a natural experiment that exploits a regime switch in 1987. Drawing on the theory of capital market imperfections, we apply an empirical framework for investment analysis to a panel of manufacturing SOEs in competitive industries. We identify parallels between SOEs and widely held, quoted companies afflicted by agency problems, managerial discretion, and overinvestment. We argue that, in the case of SOEs, the soft budget regime increases managerial discretion, facilitates collusion with vote-seeking politicians, and results in wasteful investment. Consistent with our predictions, we find that the regime switch disciplines SOE's investment behavior. Following a hardening of the budget constraint, managers lose discretion to indulge in collusion and overinvestment. J. Comp. Econ. , June 2002 30 (4), pp. 787–811. London School of Economics and Political Science, Houghton Street, London WC2A 2AE, United Kingdom; and CERIS–CNR, Institute for Economic Research on Firms and Growth, National Research Council, Via Avogadro, 8, 10121 Turin, Italy. © 2002 Association for Comparative Economic Studies. Published by Elsevier Science (USA). All rights reserved. Journal of Economic Literature Classification Numbers: E32, G31, G32, L32, M40.
Robust control of a piezoelectric stage under thermal and external load disturbances

Piezoelectric actuators are widely used in micromanipulation tasks such as Atomic Force Microscopy and Cell Manipulation. However, the hysteresis nonlinearity and the creep reduce their fidelity and cause difficulties in the micromanipulation control procedure. Besides, variation of temperature and external loads could change the model parameters identified for the piezo actuator. In this paper, a novel feedforward-feedback controller is proposed. The Prandtl-Ishlinskii model is utilized to linearize the actuator hysteresis in feedforward scheme and a sliding mode based impedance control with perturbation estimation is used to cancel out the thermal and external load disturbances in feedback scheme. The efficiency of the proposed controller is verified by experiments.
Thinking Harder About Outcomes for Collaborative Governance Arrangements

In recent years, a growing number of scholars have urged greater intellectual effort regarding the outcomes, or impacts, being produced, or not produced by collaborative governance arrangements. Some progress has been made with “process” and “social” outcomes, outcomes affecting systemic collaborative capacity, the identification of second- and third-order consequences, and in refining approaches to incorporating and measuring real world environmental improvements. But what about other creative, important, and potentially useful governance outcomes that may well be unique to collaborative governance arrangements? Are we measuring all of the important things? We put this hypothesis to the test by examining four successful cases of collaborative governance in four Western states. The research, by discovering and developing three new types of governance outcomes—enhancing agency resources, developing and transferring technology, and going beyond compliance—suggests that our current frameworks for thinking about and measuring outcomes produced by collaborative governance arrangements are necessarily incomplete.