Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Multiprocessor Memory Access Patterns with Learning Models

Machine learning techniques are applicable to computer system optimization. We show that shared memory multiprocessors can successfully utilize machine learning algorithms for memory access pattern prediction. In particular three different on-line machine learning prediction techniques were tested to learn and predict repetitive memory access patterns for three typical parallel processing applications, the 2-D relaxation algorithm, matrix multiply and Fast Fourier Transform on a shared memory multiprocessor. The predictions were then used by a routing control algorithm to reduce control latency in the interconnection network by configuring the interconnection network to provide needed memory access paths before they were requested. Three trainable prediction techniques were used and tested: 1). a Markov predictor, 2). a linear predictor and 3). a time delay neural network (TDNN) predictor. Different predictors performed best on different applications, but the TDNN produced uniformly good results.
Constraints on Analogical Mapping: A Comparison of Three Models

Three theories of analogy have been proposed that are supported by computational models and data from experiments on human analogical abilities. In this article we show how these theories can be unified within a common metatheoretical framework that distinguishes among levels of informational, behavioral, and hardware constraints. This framework clarifies the distinctions among three computational models in the literature: the Analogical Constraint Mapping Engine (ACME), the Structure-Mapping Engine (SME), and the Incremental Analogy Machine (IAM). We then go on to develop a methodology for the comparative testing of these models. In two different manipulations of an analogical mapping task we compare the results of computational experiments with these models against the results of psychological experiments. In the first experiment we show that increasing the number of similar elements in two analogical domains decreases the response time taken to reach the correct mapping for an analogy problem. In the second psychological experiment we find that the order in which the elements of the two domains are presented has significant facilitative effects on the ease of analogical mapping. Of the three models, only IAM embodies behavioral constraints and predicts both of these results. Finally, the immediate implications of these results for analogy research are discussed, along with the wider implications the research has for cognitive science methodology.
Early-Life School, Neighborhood, and Family Influences on Adult Health: A Multilevel Cross-Classified Analysis of the Aberdeen Children of the 1950s Study

Lifetime exposures to adverse social environments influence adult health, as do exposures in early life. It is usual to examine the influences of school on teenage health and of adult area of residence on adult health. We examined the combined long-term association of the school attended, as well as the area of residence in childhood, with adult health. A total of 6,285 children from Aberdeen, Scotland, who were aged 5–12 years in 1962, were followed up at a mean age of 47 years in 2001. Cross-classified multilevel logistic regression was used to estimate the associations of family, school, and area of residence with self-reported adult health and mental health, adjusting for childhood family-, school-, and neighborhood-level factors, as well as current adult occupational position. Low early-life social position (as determined by the father's occupational level) was associated with poor adult self-rated health but not poor mental health. There were small contextual associations between childhood school environment (median odds ratio = 1.08) and neighborhood environment (median odds ratio = 1.05) and adult self-rated health. The share of the total variance in health at the family level was 10.1% compared with 89.6% at the individual level. Both socioeconomic context and composition in early life appear to have an influence on adult health, even after adjustment for current occupational position.
Intraparenchymal delivery of GDNF towards a treatment for Parkinson ’ s disease Review Article

Abbreviations: 6-hydroxydopamine, (6-OHDA); adeno-associated virus, (AAV); Alzheimer’s disease, (AD); amyotrophic lateral sclerosis, (ALS); brain derived neurotrophic factor, (BDNF); Core Program for Intracerebral Transplantations, (CAPIT); central nervous system, (CNS); ciliary neurotrophic factor, (CNTF); cerebrospinal fluid, (CSF); dopamine, dopaminergic, (DA); deoxyribonucleic acid, (DNA); 3,4-dihydroxyphenylacetic acid, (DOPAC); Escherichia coli, (E coli); epidermal growth factor, (EGF); fibroblast growth factor, (FGF); À-amino butyric acid, (GABA); glial cell line-derived neurotrophic factor, (GDNF); GDNF family receptors-alpha 1 to 4, (GFRα1-4); homovanillic acid, (HVA); intracerebroventricular, (ICV); immunoglobulin (insulin-like) growth factor, (IGF); interleukin, (IL); 3,4-dihydroxyphenylalanine (levodopa), (L-dopa); 1 -methyl-4-phenyl-1,2,3,6-tetrahydropyridine, (MPTP); magnetic resonance imaging, (MRI); nerve growth factor, (NGF); N-methyl-D-aspartate, (NMDA); neurotrophin, (NT); polymerase chain reaction, (PCR); PD, (PD); platelet-derived growth factor, (PDGF); positron – emission tomography, (PET); receptor tyrosine kinase, (Ret); recombinant-methionyl human GDNF, (r-metHuGDNF); substantia nigra pars compacta, (SNc); substantia nigra pars reticulata, (SNr); transforming growth factor, (TGF); tyrosine hydroxylase, (TH); tyrosine kinase, (Trk); Unified Parkinson’s Disease Rating Scale, (UPDRS)
Epidemic Information Diffusion: A Simple Solution to Support Community-based Recommendations in P2P Overlays

Epidemic protocols proved to be very efficient solutions for supporting dynamic and complex information diffusion in highly dis- tributed computing infrastructures, like P2P environments. They are useful bricks for building and maintaining virtual network topologies, in the form of overlay networks as well as to support pervasive diffusion of information when it is injected into the network. This paper proposes a simple architecture exploiting the features of epidemic approaches to foster a collaborative percolation of information between computing nodes belonging to the network aimed at building a system that groups similar users and spread useful information among them.
Mechanisms of the Anatomically Correct Testbed ( ACT ) Hand

We have built an Anatomically Correct Testbed (ACT) hand with the purpose of understanding the intrinsic biomechanical and control features in human hands that are critical for achieving robust, versatile, and dexterous movements as well as rich object and world exploration. By mimicking the underlying mechanics and controls of the human hand in a hardware platform our goal is to achieve previously unmatched grasping and manipulation. In this paper the novel constituting mechanisms, unique muscle to joint relationships, and movement demonstrations of the thumb, index finger, middle finger, and wrist of the ACT Hand are presented. The grasping and manipulation abilities of the ACT Hand are also illustrated. The fully functional ACT Hand platform allows for the possibility to design and experiment with novel control algorithms leading to a deeper understanding of human dexterity. *These authors are all first authors and the author list is in reverse chronological order in contribution.
Steroid avoidance using sirolimus and cyclosporine in pediatric renal transplantation: One year analysis

Iorember FM, Patel HP, Ohana A, Hayes JR, Mahan JD, Baker PB, Rajab A. Steroid avoidance using sirolimus and cyclosporine in pediatric renal transplantation: One year analysis. Pediatr Transplantation 2010: 14: 93–99. © 2009 John Wiley & Sons A/S.
Virus-Associated Tumor Imaging by Induction of Viral Gene Expression

Purpose: EBV and other herpesviruses are associated with a variety of malignancies. The EBV thymidine kinase (TK) is either not expressed or is expressed at very low levels in EBV-associated tumors. However, EBV-TK expression can be induced in vitro with several chemotherapeutic agents that promote viral lytic induction. The goal of this study is to image EBV-associated tumors by induction of viral TK expression with radiolabeled 2′-fluoro-2′-deoxy-β-d-5-iodouracil-arabinofuranoside (FIAU). Experimental Design: Immunoblot, luciferase reporter assay, and in vitro assay with [14C]FIAU were used to show the effects of bortezomib on the induction of lytic gene expression of EBV-associated tumor cells. In vivo imaging and ex vivo biodistribution studies with [125I]FIAU on EBV-associated tumors were done to visualize and confirm, respectively, the EBV(+) tumor–specific effects of bortezomib. Results:In vitro assays with [14C]FIAU and ex vivo biodistribution studies with [125I]FIAU showed that uptake and retention of radiolabeled FIAU was specific for cells that express EBV-TK. Planar gamma imaging of EBV(+) Burkitt's lymphoma xenografts in severe combined immunodeficient mice showed [125I]FIAU localization within tumors following treatment with bortezomib. Conclusions: These results indicate the feasibility of imaging chemotherapy-mediated viral lytic induction by radiopharmaceutical-based techniques such as single photon emission computed tomography and positron emission tomography.
PBC: Animal Models of Cholangiopathies and Possible Endogenous Viral Infections

Primary Biliary Cirrhosis (PBC) is considered an autoimmune disease characterized by immune-mediated destruction of the intrahepatic bile ducts and its characteristic serologic marker, the anti-mitochondrial antibody (AMA). Several factors were proposed to clarify the pathological and immunological mechanisms of PBC. Immunological reaction with a bacterial or a viral association was identified in the previous report, and it seems probable that PBC was thought to have such an etiology. The majority of patients with PBC was reported to have both RT-PCR and immunohistochemistry evidence of human betaretrovirus infection in lymph nodes or in 2008, the patient who developed PBC with high HIV viral load had an antiviral therapy and recovered. To understand the etiology of PBC associated with infection, several factors should be considered and especially animal models may be useful. In this paper, we introduce three typical animal models of PBC: the dominant-negative form of transforming growth factor-β receptor type II (dnTGFβRII) mouse, IL-2Rα −/− mouse and NOD.c3c4 mouse, are enumerated and described, and we discuss previous reports of viral infection associated with PBC and consider the etiology of PBC from our analysis of results in NOD.c3c4 mouse.
Statistical methods for the discovery of co-operative transcription factors: co-bind code revised

Discovering co-operative transcription factors (TF's) within the genome is a computationally challenging problem, tackled through Monte Carlo-like analysis by the Co-Bind code, developed at the Department of Genetics of the St. Louis Washington University. Due to its statistical nature, co-bind is characterized by very long execution times, order of days on current high-end workstations, and could benefit from parallelization and a wise optimization, performed at both the algorithmic and coding levels. This paper presents the results achieved by parallelizing co-bind and optimising the parallel code and shows that, on a 16-processor architecture, a speedup greater than two orders of magnitude is achieved with respect to the serial version released by the code's authors.
Call management based on the mobile terminal-peak velocity: virtues and limitations in a two-tier cellular system

The aim of the presented research is to study an effective algorithm for the admission control and handoff management of mobile user connections in a realistic urban scenario with a two-tier (micro- and macrocell) cellular coverage. The algorithm behavior is strongly related to the knowledge of the mobility profile of the users. Thus, an analysis of analogous algorithms available in literature and which exploit mobility estimation precedes our design activity. Their advantages and drawbacks have been observed and are used as a starting point for the design of our algorithm. It overcomes the weaknesses that the previous algorithms show when operating in a realistic urban scenario. As a consequence, it reduces the call-blocking probability and minimizes the handoff rate.
The use of computerized clinical decision support systems in emergency care: a substantive review of the literature

Objectives : This paper provides a substantive review of international literature evaluating the impact of computerized clinical decision support systems (CCDSSs) on the care of emergency department (ED) patients. Material and Methods : A literature search was conducted using Medline, Cumulative Index of Nursing and Allied Health Literature (CINAHL), Embase electronic resources, and gray literature. Studies were selected if they compared the use of a CCDSS with usual care in a face-to-face clinical interaction in an ED. Results : Of the 23 studies included, approximately half demonstrated a statistically significant positive impact on aspects of clinical care with the use of CCDSSs. The remaining studies showed small improvements, mainly around documentation. However, the methodological quality of the studies was poor, with few or no controls to mitigate against confounding variables. The risk of bias was high in all but 6 studies. Discussion : The ED environment is complex and does not lend itself to robust quantitative designs such as randomized controlled trials. The quality of the research in ∼75% of the studies was poor, and therefore conclusions cannot be drawn from these results. However, the studies with a more robust design show evidence of the positive impact of CCDSSs on ED patient care. Conclusion This is the first review to consider the role of CCDSSs in emergency care and expose the research in this area. The role of CCDSSs in emergency care may provide some solutions to the current challenges in EDs, but further high-quality research is needed to better understand what technological solutions can offer clinicians and patients.
Dynamic balance control of humanoids for multiple grasps and non coplanar frictional contacts

Human beings perform complex tasks while even keeping balance. Though this is evident for a human, it is very difficult to adapt human motion to humanoid robots, due to the posture redundancy. In this paper we propose a conceptually simple framework of human posture control, scoping in a general way with grasp, task achievement and being on the same time robust to external disturbances. We do this by establishing physically meaningful constraints on the force level. In order to respect all constraints, we solve for a quadratic minimization problem (quadratic programming), yielding the required joint torque controls. Contrarily to most other approaches, we deal also with unilateral contacts (due to friction) as well as bilateral grasps which allow for example for arbitrarily steering or pulling on a handhold. Additionally, and in contrast to classical methods based on ZMP, we account also for contacts not all being in the same plane, as hand-wall contact.
The cycle of abductive and inductive knowledge development

Abduction and Induction have existed mostly as separate subjects in Artificial Intelligence and other disciplines. They have each been studied as central inference mechanisms in order to tackle a set of particular but largely different problems. Abduction is mainly used to address problems of diagnosis and planning whereas induction is primarily used in the problem of machine learning. Within the wider context of the formation and the development of a knowledge theory, however, these two forms of reasoning interact and can be integrated together in a cooperative and enhancing way. In this paper we study this possibility of integration between abduction and induction and present a cycle of knowledge development based on this integration. This paper is a summary of part of the introductory chapter of a recent book [5] which addresses more generally the issues of the relation and integration between abduction and induction.
Association of prior infection with Chlamydia pneumoniae and angiographically demonstrated coronary artery disease.

OBJECTIVE To evaluate the association between prior infection with Chlamydia pneumoniae, as measured by IgG antibody, and coronary artery disease. DESIGN A population-based, case-control study. SETTING Group Health Cooperative of Puget Sound, a Seattle-based health maintenance organization. PARTICIPANTS Men 55 years of age and younger and women 65 years of age and younger. Cases (n = 171) were members of Group Health Cooperative undergoing diagnostic coronary angiography who had at least one coronary artery lesion occupying 50% or more of the luminal diameter. The population controls (n = 120) were Group Health Cooperative members without known coronary heart disease. MAIN OUTCOME MEASURE The adjusted odds ratio (OR) for coronary artery disease associated with prior C pneumoniae infection as measured by the presence of IgG antibody. RESULTS After adjusting for age, gender, and calendar quarter of blood drawing, the OR for coronary artery disease associated with the presence of antibody was 2.6 (95% confidence interval, 1.4 to 4.8). The association was limited to cigarette smokers, in whom the OR was 3.5 (95% confidence interval, 1.7 to 7.0). Among never-smokers, the OR was 0.8 (95% confidence interval, 0.3 to 1.9). When cases and controls were restricted to those assayed concurrently, the adjusted OR (smokers and nonsmokers combined) was 4.2 (95% confidence interval, 1.8 to 10.0). Adjustment for serum cholesterol, hypertension, alcohol use, diabetes, and socioeconomic status did not change these results. Only a week association was found when cases were compared with 63 subjects whose angiographic results were normal (OR, 1.2; 95% confidence interval, 0.6 to 2.2). CONCLUSIONS These results generally support the previously reported association between C pneumoniae infection and coronary heart disease. However, caution should be used in interpreting the basis for this association.
Energy Detection Based Spectrum Sensing Over Two-Wave With Diffuse Power Fading Channels

One of the most important factors that affects the performance of energy detection (ED) is the fading channel between the wireless nodes. This paper investigates the performance of ED-based spectrum sensing, for cognitive radio (CR), over two-wave with diffuse power (TWDP) fading channels. The TWDP fading model characterizes a variety of fading channels, including well-known canonical fading distributions, such as Rayleigh and Rician, as well as worse-than-Rayleigh fading conditions modeled by the two-ray fading model. Novel analytic expressions for the average probability of detection over TWDP fading that account for single-user and cooperative spectrum sensing and square law selection diversity reception are derived. These expressions are used to analyze the behavior of ED-based spectrum sensing over moderate, severe, and extreme fading conditions and to investigate the use of cooperation and diversity as a means of mitigating the fading effects. The obtained results indicate that TWDP fading conditions can significantly degrade sensing performance; however, it is shown that detection performance can be improved when cooperation and diversity are employed. The presented outcomes enable identifying the limits of ED-based spectrum sensing and quantifying the tradeoffs between detection performance and energy efficiency for CR systems deployed within confined environments, such as in-vehicular wireless networks.
Inflammation as a predictor for delayed cerebral ischemia after aneurysmal subarachnoid haemorrhage

Background The mechanism of development of delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (SAH) is poorly understood. Inflammatory processes are implicated in the development of ischemic stroke and may also predispose to the development of DCI following SAH. The objective of this study was to test whether concentrations of circulating inflammatory markers (C-reactive protein (CRP), interleukin-6 (IL-6) and interleukin 1 receptor antagonist (IL-1Ra)) were predictive for DCI following SAH. Secondary analyses considered white cell count (WCC) and erythrocyte sedimentation rate (ESR). Methods This was a single-center case-control study nested within a prospective cohort. Plasma inflammatory markers were measured in patients up to 15 days after SAH (initial, peak, average, final and rate of change to final). Cases were defined as those developing DCI. Inflammatory markers were compared between cases and randomly selected matched controls. Results Among the 179 participants there were 46 cases of DCI (26%). In primary analyses the rate of change of IL-6 was associated with DCI (OR 2.3 (95% CI 1.1 to 5.0); p=0.03). The final value and rate of change of WCC were associated with DCI (OR 1.2 (95% CI 1.0 to 1.3) and OR 1.3 (95% CI 1.0 to 1.6), respectively). High values of ESR were associated with DCI (OR 2.4 (95% CI 1.3 to 4.6) initial; OR 2.3 (95% CI 1.3 to 4.2) average; OR 2.1 (95% CI 1.1 to 3.9) peak; and OR 2.0 (95% CI 1.2 to 3.3) final value). Conclusions Leucocytosis and change in IL-6 prior to DCI reflect impending cerebral ischemia. The time-independent association of ESR with DCI after SAH may identify this as a risk factor. These data suggest that systemic inflammatory mechanisms may increase the susceptibility to the development of DCI after SAH.
Maximum conditional mutual information modeling for speaker verification

This paper describes a novel approach for class-dependent modeling and its application to automatic text-independent speaker verification. This approach maximizes the conditional mutual information between the model scores and the class identity given some constraints on the scores. It is shown in the paper that maximizing the differential entropy of the scores generated by the classifier or the detector is an equivalent criterion. This approach allows emphasizing different features, in the feature vector used in the detection, for different target speakers. In this paper, we apply this approach to the NIST 2003 1-speaker verification task. Compared to the baseline system, around 10% relative improvement in the minimum detection cost function (DCF) is obtained.
Adaptive population size for univariate marginal distribution algorithm

Population size is an important parameter in univariate marginal distribution algorithm (UMDA). Too large or too small value both goes against its search. A good population sizing method should consider the distribution of individuals. Since the distribution of individuals varies from generation to generation, static population sizing method probably isn't a good choice. Like Darwinian-type genetic algorithm, UMDA is an intelligent search strategy, it should have the ability to adjust its parameters. In this study, two adaptive population sizing methods are presented for UMDA in continuous domain and in discrete domain respectively. Numerical results show that both of them can get a good balance between convergent velocity and convergent reliability.