Miracle-dz/UniFAR-FTUs huggingface dataset:
Economism : the New Development Paradigm

The economism paradigm consists of five key elements: capitalist market economy; poverty reduction rather than the pursuit of equality; the “economic fertilizer” role of government; a pro-growth political regime and domestic economic stability. Economism is a paradigm of “more or less”, in which individuals with different income can change positions given equality in economic opportunities. Economic security is the primary concern of the paradigm. Inter-personal comparisons always lead to income inequality, but intra-personal comparison encourages wealth accumulation. Government intervention should produce growth-promoting economic incentives. The export-led strategy that attracted foreign investments has to be supplemented by stable and consistent domestic conditions. Economic freedom is essential to a “pro-growth” regime and economic growth becomes the political priority. This paper aims to establish the paradigm of economism, which can have strong linkage to other disciplines, and serves as a stimulant to a number of economic areas and disciplines.
Strong theory, flexible methods: Evaluating complex community-based initiatives

A growing number of countries are beginning to move from acknowledging the existence of health inequalities to developing policies to reduce them. Many of these policies consist of complex interventions, operating at a number of levels, which aim to make a positive contribution to health improvement in deprived communities. Evaluating the efficacy of such initiatives poses particular challenges for evaluation. This paper argues that there is real potential in applying a theory-based approach to the evaluation of complex community-based initiatives. Using practical examples from the national evaluation of Health Action Zones in England, the paper outlines the key components of such an approach and argues that theory-based evaluation can strengthen programme design and implementation, as well as promote policy and practice learning about the most effective interventions for health improvement. We conclude that sophisticated theory building social change mechanisms in community settings is essential if real learning is to be generated from concerted efforts to achieve social change.
CRIMINAL CAREER RESEARCH: ITS VALUE FOR CRIMINOLOGY*

In a recent paper published in this journal, Gottfredson and Hirschi (1986)1 argue that the concepts of criminal careers, career criminals, selective incapacitation, prevalence, and incidence, and longitudinal studies all have little value for criminology. In our view their paper misrepresents these concepts and our research on these topics. We are pleased to have the opportunity in this paper to develop these concepts more clearly and to show their relevance for criminology.
Recovery of function in dorsal horn following partial deafferentation.

1. Collateral sprouting of L6 dorsal root afferents within the dorsal horn of the L6 spinal cord segment has been shown anatomically to occur following transection of all other lumbosacral dorsal roots in the cat. The present study was performed to examine a possible physiological correlate of that sprouting, namely, an altered somatotopic organization of the dorsal horn at L6. This was evaluated by microelectrode mapping of the L6 dorsal horn in normal cats and in cats with L6 spared, lumbosacral dorsal rhizotomies performed 2 days (subacute spared root) or more than 8 wk (chronic spared root), prior to recording. 2. In normal cats the mediolateral somatotopic sequence of hindlimb representation in the L6 dorsal horn is ventral digits 2 and 3, dorsal digits 2 and 3, dorsal foot, rostral and lateral ankle, lateral leg, lateral thigh, and back. In both subacute and chronic spared-root cats the somatotopic sequence is similar to that of normal cats, but there is a loss of proximal thigh and back representation. This proximal body region is represented at the lateral edge of the dorsal horn in normal animals. 3. There was a partial loss of responsiveness of cells in the dorsal horn in the subacute spared-root group and a partial recovery of responsiveness in the chronic group. In the subacute group punctures exhibiting no responses to tactile input tended to be clustered in the lateral dorsal horn. 4. The lateral one-fourth of the dorsal horn in each animal was analyzed in terms of the percentage of recording loci occurring within it. The percentages of recording loci having receptive fields proximal to, distal to, and spanning the middle of the thigh (proximal, distal, and intermediate RFs) were tabulated for each animal. Subacute animals had a significantly lower-than-normal overall percentage of responsive loci in the lateral dorsal horn, but chronic animals did not. The percentage of distal fields therein was not different for the normal versus the subacute group, signifying that the loss of proximal and intermediate fields was responsible for the difference in overall percentage. Chronic animals, however, had significantly more distal fields than did normals. When all fields having any distal component were compared (i.e., distal and intermediate), the difference between the chronic and normal groups did not reach significance. One possible explanation of these findings is that loci having both proximal and distal RF components are unresponsive 2 days after partial denervation, but recover responsiveness to their spared distal input over an 8-wk period. One possible mechanism mediating these changes is localized sprouting of intact, spared axons. Other mechanisms of functional recovery, such as interneuronal sprouting, denervation supersensitivity, and unmasking of latent synapses, are discussed in relation to these and other data.
CO$_2$ and NO$_2$ Formation on Amorphous Solid Water

The dynamics for molecule formation, relaxation, diffusion, and desorption on amorphous solid water is studied in a quantitative fashion. We aim at characterizing, at a quantitative level, the formation probability, stabilization, energy relaxation and diffusion dynamics of CO$_2$ and NO$_2$ on cold amorphous solid water following atom+diatom recombination reactions. Accurate machine-learned energy functions combined with fluctuating charge models were used to investigate the diffusion, interactions, and recombination dynamics of atomic oxygen with CO and NO on amorphous solid water (ASW). Energy relaxation to the ASW and into water-internal-degrees of freedom were determined from analysis of the vibrational density of states. The surface diffusion and desorption energetics was investigated from extended and nonequilibrium MD simulations. The reaction probability on the nanosecond time scale is determined in a quantitative fashion and demonstrates that surface diffusion of the reactants leads to recombination for initial separations up to 20 \AA\/. After recombination both, CO$_2$ and NO$_2$, stabilize by energy transfer to water internal and surface phonon modes on the picosecond time scale. The average diffusion barriers and desorption energies agree with those reported from experiments. After recombination, the triatomic products diffuse easily which contrasts with the equilibrium situation in which both, CO$_2$ and NO$_2$, are stationary on the multi-nanosecond time scale.
A task of anomaly detection for a smart satellite Internet of things system

When the equipment is working, real-time collection of environmental sensor data for anomaly detection is one of the key links to prevent industrial process accidents and network attacks and ensure system security. However, under the environment with specific real-time requirements, the anomaly detection for environmental sensors still faces the following difficulties: (1) The complex nonlinear correlation characteristics between environmental sensor data variables lack effective expression methods, and the distribution between the data is difficult to be captured. (2) it is difficult to ensure the real-time monitoring requirements by using complex machine learning models, and the equipment cost is too high. (3) Too little sample data leads to less labeled data in supervised learning. This paper proposes an unsupervised deep learning anomaly detection system. Based on the generative adversarial network and self-attention mechanism, considering the different feature information contained in the local subsequences, it automatically learns the complex linear and nonlinear dependencies between environmental sensor variables, and uses the anomaly score calculation method combining reconstruction error and discrimination error. It can monitor the abnormal points of real sensor data with high real-time performance and can run on the intelligent satellite Internet of things system, which is suitable for the real working environment. Anomaly detection outperforms baseline methods in most cases and has good interpretability, which can be used to prevent industrial accidents and cyber-attacks for monitoring environmental sensors.
Effectiveness of a Prevention of Mother-to-Child HIV Transmission Programme in an Urban Hospital in Angola

Background Antiretroviral therapy is effective in reducing rates of mother-to child transmission of HIV to low levels in resource-limited contexts but the applicability and efficacy of these programs in the field are scarcely known. In order to explore such issues, we performed a descriptive study on retrospective data from hospital records of HIV-infected pregnant women who accessed in 2007–2010 the Luanda Municipal Hospital service for prevention of mother-to-child transmission (PMTCT). The main outcome measure was infant survival and HIV transmission. Our aim was to evaluate PMTCT programme in a local hospital setting in Africa. Results Data for 104 pregnancies and 107 infants were analysed. Sixty-eight women (65.4%) had a first visit before or during pregnancy and received combination antiretroviral treatment (ART) in pregnancy. The remaining 36 women (34.6%) presented after delivery and received no ART during pregnancy. Across a median cohort follow-up time of 73 weeks, mortality among women with and without ART in pregnancy was 4.4% and 16.7%, respectively (death hazard ratio: 0.30, 95% CI 0.07–1.20, p = 0.089). The estimated rates of HIV transmission or death in the infants over a median follow up time of 74 weeks were 8.5% with maternal ART during pregnancy and 38.9% without maternal ART during pregnancy. Following adjustment for use of oral zidovudine in the newborn and exposure to maternal milk, no ART in pregnancy remained associated with a 5-fold higher infant risk of HIV transmission or death (adjusted odds ratio: 5.13, 95% CI: 1.31–20.15, p = 0.019). Conclusions Among the women and infants adhering to the PMTCT programme, HIV transmission and mortality were low. However, many women presented too late for PMTCT, and about 20% of infants did not complete follow up. This suggests the need of targeted interventions that maintain the access of mothers and infants to prevention and care services for HIV.
Novel CCL21-Vault Nanocapsule Intratumoral Delivery Inhibits Lung Cancer Growth

Background Based on our preclinical findings, we are assessing the efficacy of intratumoral injection of dendritic cells (DC) transduced with an adenoviral vector expressing the secondary lymphoid chemokine (CCL21) gene (Ad-CCL21-DC) in a phase I trial in advanced non-small cell lung cancer (NSCLC). While this approach shows immune enhancement, the preparation of autologous DC for CCL21 genetic modification is cumbersome, expensive and time consuming. We are evaluating a non-DC based approach which utilizes vault nanoparticles for intratumoral CCL21 delivery to mediate antitumor activity in lung cancer. Principal Findings Here we describe that vault nanocapsule platform for CCL21 delivery elicits antitumor activity with inhibition of lung cancer growth. Vault nanocapsule packaged CCL21 (CCL21-vaults) demonstrated functional activity in chemotactic and antigen presenting activity assays. Recombinant vaults impacted chemotactic migration of T cells and this effect was predominantly CCL21 dependent as CCL21 neutralization abrogated the CCL21 mediated enhancement in chemotaxis. Intratumoral administration of CCL21-vaults in mice bearing lung cancer enhanced leukocytic infiltrates (CXCR3+T, CCR7+T, IFNγ+T lymphocytes, DEC205+ DC), inhibited lung cancer tumor growth and reduced the frequencies of immune suppressive cells [myeloid derived suppressor cells (MDSC), T regulatory cells (Treg), IL-10 T cells]. CCL21-vaults induced systemic antitumor responses by augmenting splenic T cell lytic activity against parental tumor cells. Significance This study demonstrates that the vault nanocapsule can efficiently deliver CCL21 to sustain antitumor activity and inhibit lung cancer growth. The vault nanocapsule can serve as an “off the shelf” approach to deliver antitumor cytokines to treat a broad range of malignancies.
Intelligibility in speech disorders : theory, measurement, and management

1. Introduction (by Kent, Raymond D.) 2. 1. Scaling procedures for the measurement of speech intelligibility (by Schiavetti, Nicholas) 3. 2. An application of structural linguistics to intelligibility measurement of impaired speakers of English (by Bross, Rida S.) 4. 3. Acoustic and perceptual approaches to the study of intelligibility (by Weismer, Gary) 5. 4. The role of phonation in speech intelligibility: A review and preliminary data from patients with Parkinson's disease (by Ramig, L.O.) 6. 5. The intelligibility of English vowels spoken by British and Dutch talkers (by Flege, James Emil) 7. 6. Speech intelligibility in the hearing impaired: Research and clinical implications (by Osberger, Mary Joe) 8. 7. Intelligibility measurement as a tool in the clinical management of dysarthric speakers (by Yorkston, Kathryn M.) 9. 8. EPG-based description of apraxic speech errors (by Hardcastle, William J.) 10. 9. Prospects for neurophysiology approaches to the study of speech intelligibility (by Barlow, Steven M.) 11. Index
Toward Caching Symmetrical Subtheories for Weighted Model Counting

Model counting and weighted model counting are key problems in artificial intelligence. Marginal inference can be reduced to model counting in many statistical-relational systems, such as Markov Logic. One common approach used by model counters is splitting a theory into disjoint subtheories, performing model counting on the subtheories, and then caching the result. If an identical subtheory is encountered again in the search, the cached result is used, greatly reducing runtime. In this work we introduce a way to cache symmetric subtheories compactly, which could potentially decrease required cache size, increase cache hits, and decrease runtime
Two-scale Analysis for Multiscale Landau-Lifshitz-Gilbert Equation: Theory and Numerical Methods

This paper discusses the theory and numerical method of two-scale analysis for the multiscale Landau-Lifshitz-Gilbert equation in composite ferromagnetic materials. The novelty of this work can be summarized in three aspects: Firstly, the more realistic and complex model is considered, including the effects of the exchange field, anisotropy field, stray field, and external magnetic field. The explicit convergence orders in the $H^1$ norm between the classical solution and the two-scale solution are obtained. Secondly, we propose a robust numerical framework, which is employed in several comprehensive experiments to validate the convergence results for the Periodic and Neumann problems. Thirdly, we design an improved implicit numerical scheme to reduce the required number of iterations and relaxes the constraints on the time step size, which can significantly improve computational efficiency. Specifically, the projection and the expansion methods are given to overcome the inherent non-consistency in the initial data between the multiscale problem and homogenized problem.
Politics and Organizational Learning

In this paper it is argued that organizational learning is facilitated by a free and open form of politics in the workplace based on a system of political, social and civil rights and obligations within a framework of legitimate authority, parallel to the system that exists in the wider society. The argument is developed by examining issues at three related levels: why ‘psychic’ space is needed to nurture selfidentity and learning; the institutional pressures in the wider social environment that bring about learning within a whole business sector through open political activity; and how existing organizational learning theory and practice reveal numerous ways in which space for learning and innovation can be made available within work organizations through political processes. Finally, suggestions are made for ways of creating a framework within organizations that will enable such processes to develop.
Anonymous Identification for Ad Hoc Group

An anonymous identification scheme for ad hoc group allows a participant to identify himself as a member of a group of users in a way that his actual identity is not revealed. We propose a highly efficient construction of this cryptographic primitive in the symmetric key setting based on the idea of program obfuscation. The salient feature of our scheme is that only hash evaluations are needed. Consequently, our scheme outperforms all existing constructions for a reasonably large ad hoc group size (of around 50000 users) since no exponentiation nor pairing operation is involved. Technically, the participant only needs to evaluate one hash operation to identify himself. While the time complexity of the verifier is linearly in the size of the ad hoc group, the actual running time is rather insignificant since the constant factor of this linear dependence is the time of a single hash evaluation. To analyse the security of our proposal, we develop a security model to capture the security requirements of this primitive and prove that our construction satisfies these requirements in the random oracle model against unbounded attackers. Similar to other identification schemes secure in the random oracle model, our proposed protocol requires only two message flow.
Network-Scale Traffic Modeling and Forecasting with Graphical Lasso and Neural Networks

Traffic flow forecasting, especially the short-term case, is an important topic in intelligent transportation systems (ITS). This paper does a lot of research on network-scale modeling and forecasting of short-term traffic flows. Firstly, we propose the concepts of single-link and multi-link models of traffic flow forecasting. Secondly, we construct four prediction models by combining the two models with single-task learning and multi-task learning. The combination of the multi-link model and multi-task learning not only improves the experimental efficiency but also the prediction accuracy. Moreover, a new multi-link single-task approach that combines graphical lasso (GL) with neural network (NN) is proposed. GL provides a general methodology for solving problems involving lots of variables. Using L1 regularization, GL builds a sparse graphical model making use of the sparse inverse covariance matrix. In addition, Gaussian process regression (GPR) is a classic regression algorithm in Bayesian machine learning. Although there is wide research on GPR, there are few applications of GPR in traffic flow forecasting. In this paper, we apply GPR to traffic flow forecasting and show its potential. Through sufficient experiments, we compare all of the proposed approaches and make an overall assessment at last.
Complexity of Multi-Dimensional Spontaneous EEG Decreases during Propofol Induced General Anaesthesia

Emerging neural theories of consciousness suggest a correlation between a specific type of neural dynamical complexity and the level of consciousness: When awake and aware, causal interactions between brain regions are both integrated (all regions are to a certain extent connected) and differentiated (there is inhomogeneity and variety in the interactions). In support of this, recent work by Casali et al (2013) has shown that Lempel-Ziv complexity correlates strongly with conscious level, when computed on the EEG response to transcranial magnetic stimulation. Here we investigated complexity of spontaneous high-density EEG data during propofol-induced general anaesthesia. We consider three distinct measures: (i) Lempel-Ziv complexity, which is derived from how compressible the data are; (ii) amplitude coalition entropy, which measures the variability in the constitution of the set of active channels; and (iii) the novel synchrony coalition entropy (SCE), which measures the variability in the constitution of the set of synchronous channels. After some simulations on Kuramoto oscillator models which demonstrate that these measures capture distinct ‘flavours’ of complexity, we show that there is a robustly measurable decrease in the complexity of spontaneous EEG during general anaesthesia.
Palliative Care and the Humanities: Centralizing the Patient at the End of Life

Palliative care is a quickly growing facet of modern medicine. While scientific advancements have broken new ground for the possibilities of end-of-life care, sensitive treatment of the patient as an individual has lagged behind and has frequently led to an unsatisfactory experience for patients, families, and the medical community at large. This essay argues that centralizing patients during the terminal phases of treatment by using humanistic perspectives has the potential to bring new meaning and improved effectiveness to patients and physicians alike.
Smoking and poverty

The problem of poverty leads to increased use of both legal and illegal drugs. Tobacco and alcohol are legal drugs that cause particular concern. Both drugs are widely abused in Germany by people attempting to escape their everyday problems. For decades it has been known that tobacco and alcohol use are more prevalent in lower socio-economic groups of society (those with low educational achievement, compared with people with further or higher education qualifications). Tobacco and alcohol use is particularly high among the unemployed, either temporarily or long-term, as well as people living alone. Children and women are more concerned about smoking than men. Female loneliness, often accompanied by the appearance of depressive reactions or of depression, increases the likelihood of cigarette smoking. Poor people spend up to 20% of their income on tobacco. In many industrialized countries, the age of onset of smoking is becoming younger and younger, increasing the risk of development of avoidable tobacco-related illnesses at an earlier age. This means that young smokers who develop chronic tobacco-related illnesses will require medical care over many years, increasing the cost of treating tobacco-related disease. Within the next few years, effective prevention programs against smoking must be developed, particularly for the lower socio-economic populations, in order to stop the cost of healthcare systems spiraling over the coming decades. Eur J Cardiovasc Prev Rehabil 13:312–318 © 2006 The European Society of Cardiology