Miracle-dz/UniFAR-FTUs huggingface dataset:
Fuzzy Expert Systems

In which we present fuzzy set theory, consider how to build fuzzy expert systems and illustrate the theory through an example. 4.1 Introduction, or what is fuzzy thinking? Experts usually rely on common sense when they solve problems. They also use vague and ambiguous terms. For example, an expert might say, 'Though the power transformer is slightly overloaded, I can keep this load for a while'. Other experts have no difficulties with understanding and interpreting this statement because they have the background to hearing problems described like this. However, a knowledge engineer would have difficulties providing a computer with the same level of understanding. How can we represent expert knowledge that uses vague and ambiguous terms in a computer? Can it be done at all? This chapter attempts to answer these questions by exploring the fuzzy set theory (or fuzzy logic). We review the philosophical ideas behind fuzzy logic, study its apparatus and then consider how fuzzy logic is used in fuzzy expert systems. Let us begin with a trivial, but still basic and essential, statement: fuzzy logic is not logic that is fuzzy, but logic that is used to describe fuzziness. Fuzzy logic is the theory of fuzzy sets, sets that calibrate vagueness. Fuzzy logic is based on the idea that all things admit of degrees. Temperature, height, speed, distance, beauty – all come on a sliding scale. The motor is running really hot. Tom is a very tall guy. Electric cars are not very fast. High-performance drives require very rapid dynamics and precise regulation. Hobart is quite a short distance from Melbourne. Sydney is a beautiful city. Such a sliding scale often makes it impossible to distinguish members of a class from non-members. When does a hill become a mountain? Boolean or conventional logic uses sharp distinctions. It forces us to draw lines between members of a class and non-members. It makes us draw lines in the sand. For instance, we may say, 'The maximum range of an electric vehicle is short', regarding a range of 300 km or less as short, and a range greater than 300 km as long. By this standard, any electric vehicle that can cover a distance of 301 km (or 300 km and 500 m or even 300 km and 1 m) would be described as
Methodological approach to the first and second lactate threshold in incremental cardiopulmonary exercise testing

Determination of an ‘anaerobic threshold’ plays an important role in the appreciation of an incremental cardiopulmonary exercise test and describes prominent changes of blood lactate accumulation with increasing workload. Two lactate thresholds are discerned during cardiopulmonary exercise testing and used for physical fitness estimation or training prescription. A multitude of different terms are, however, found in the literature describing the two thresholds. Furthermore, the term ‘anaerobic threshold’ is synonymously used for both, the ‘first’ and the ‘second’ lactate threshold, bearing a great potential of confusion. The aim of this review is therefore to order terms, present threshold concepts, and describe methods for lactate threshold determination using a three-phase model with reference to the historical and physiological background to facilitate the practical application of the term ‘anaerobic threshold’.
16S rRNA Gene-Based Identification of Midgut Bacteria from Field-Caught Anopheles gambiae Sensu Lato and A. funestus Mosquitoes Reveals New Species Related to Known Insect Symbionts

ABSTRACT Field-collected mosquitoes of the two main malaria vectors in Africa, Anopheles gambiae sensu lato and Anopheles funestus, were screened for their midgut bacterial contents. The midgut from each blood-fed mosquito was screened with two different detection pathways, one culture independent and one culture dependent. Bacterial species determination was achieved by sequence analysis of 16S rRNA genes. Altogether, 16 species from 14 genera were identified, 8 by each method. Interestingly, several of the bacteria identified are related to bacteria known to be symbionts in other insects. One isolate, Nocardia corynebacterioides, is a relative of the symbiont found in the vector for Chagas' disease that has been proven useful as a paratransgenic bacterium. Another isolate is a novel species within the γ-proteobacteria that could not be phylogenetically placed within any of the known orders in the class but is close to a group of insect symbionts. Bacteria representing three intracellular genera were identified, among them the first identifications of Anaplasma species from mosquitoes and a new mosquito-Spiroplasma association. The isolates will be further investigated for their suitability for a paratransgenic Anopheles mosquito.
Network Association with Dynamic Pricing over D2D-Enabled Heterogeneous Networks

The growing trend of networks densification has motivated integrating the Device-to-Device (D2D) communication with the dense heterogeneous networks in order to face the intense demand of high data rates and enhance network performance. However, this imposes challenges to develop innovative network association schemes that consider energy efficiency while meeting application quality requirements. In this context, we propose an efficient network association mechanism over D2D-enabled heterogeneous wireless networks. We consider different Quality of service (QoS) requirements, networks characteristics, and application requirements, in order to obtain an efficient- distributed solution that grasps the conflicting nature of the various objectives. The proposed methodology leverages a user-centric networks association approach over D2D-enabled heterogeneous wireless networks to enhance system performance and support reliable connectivity. Our results demonstrate the efficiency of the proposed scheme compared to the state-of-the-art techniques that ignore the potential of D2D communication.
Linear optimal estimation problems in systems with actuator faults

We consider estimating the state of a dynamic system subject to actuator faults. The discretely-valued fault mechanism renders the system hybrid, and results in anomalous changes in the dynamics equation that may be interpreted as random accelerations. Two closely related problem formulations are considered. In the first formulation multiple models are used to describe the system's behavior: one model stands for the nominal, fault-free actuator condition, all other models correspond to various actuator fault conditions, and the system can freely assume any model at any time. In the second formulation the abnormal mode is described by a single dynamical model, and the system can switch between the nominal and anomalous conditions a bounded number of times, with the bound assumed known. In both formulations, the minimum mean squared error (MMSE) optimal state estimator requires a polynomially growing number of primitive Kalman filters, and is, thus, computationally infeasible. We derive sequential, linear MMSE-optimal state estimation algorithms for both problem formulations. Depending only on the first two moments of the random quantities of the problem, linear optimal filters are robust with respect to the actual driving noise distributions, in the sense that they achieve the smallest worst-case estimation error of all other (nonlinear) filters. Although derived assuming seemingly different problem formulations, both filters share essentially the same structure, thus exposing a certain duality between the underlying problems. The performance of both estimators is demonstrated in a simulation study, where they are compared to the interacting multiple model filter.
Edinburgh Research Explorer Information Coding in Vasopressin Neurons-the Role of Asynchronous Bistable Burst Firing Information Coding in Vasopressin Neurons—the Role of Asynchronous Bistable Burst Firing

General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact openaccess@ed.ac. uk providing details, and we will remove access to the work immediately and investigate your claim. a b s t r a c t The task of the vasopressin system is homeostasis, a type of process which is fundamental to the brain's regulation of the body, exists in many different systems, and is vital to health and survival. Many illnesses are related to the dysfunction of homeostatic systems, including high blood pressure, obesity and diabetes. Beyond the vasopressin system's own importance, in regulating osmotic pressure, it presents an accessible model where we can learn how the features of homeostatic systems generally relate to their function, and potentially develop treatments. The vasopressin system is an important model system in neuroscience because it presents an accessible system in which to investigate the function and importance of, for example, dendritic release and burst firing, both of which are found in many systems of the brain. We have only recently begun to understand the contribution of dendritic release to neu-ronal function and information processing. Burst firing has most commonly been associated with rhythm generation; in this system it clearly plays a different role, still to be understood fully.
Model Uncertainty via the Integration of Hormesis and LNT as the Default in Cancer Risk Assessment

On June 23, 2015, the US Nuclear Regulatory Commission (NRC) issued a formal notice in the Federal Register that it would consider whether “it should amend its ‘Standards for Protection Against Radiation’ regulations from the linear non-threshold (LNT) model of radiation protection to the hormesis model. ” The present commentary supports this recommendation based on the (1) flawed and deceptive history of the adoption of LNT by the US National Academy of Sciences (NAS) in 1956; (2) the documented capacity of hormesis to make more accurate predictions of biological responses for diverse biological end points in the low-dose zone; (3) the occurrence of extensive hormetic data from the peer-reviewed biomedical literature that revealed hormetic responses are highly generalizable, being independent of biological model, end point measured, inducing agent, level of biological organization, and mechanism; and (4) the integration of hormesis and LNT models via a model uncertainty methodology that optimizes public health responses at 10−4. Thus, both LNT and hormesis can be integratively used for risk assessment purposes, and this integration defines the so-called “regulatory sweet spot. ”
Numerical modeling of nonlinear TE waves in multiple-quantum-well waveguides

A computer-aided technique, based on the finite element method, has been developed for analyzing intensity-dependent properties of TE waves guided by multiple-quantum-well (MQW) waveguides with arbitrary nonlinear media. Self-consistent solutions are obtained by a simple iterative procedure. The numerical results for TE power-dependent modes are presented for waveguides with either linear or nonlinear cladding regions. They reveal that, for values of total optical power above a certain threshold, the effect of nonlinear cladding regions on the propagation characteristics can be ignored. The power-dependent behavior of a non-Kerr-like case is also examined. <<ETX>>
Prediction of metastasis to mesorectal, internal iliac and obturator lymph nodes according to size criteria in patients with locally advanced lower rectal cancer.

OBJECTIVE This study was performed to clarify whether size criteria could be applied to the prediction of metastasis to the mesorectal, internal iliac and obturator lymph nodes in patients with lower rectal cancer. METHODS A total of 915 lymph nodes (416 mesorectal, 199 internal iliac and 300 obturator) from 53 patients with lower rectal cancer who underwent a curative resection were examined; 83 lymph nodes were positive. The sizes of the lymph nodes immediately after removal and those of paraffin-embedded sections were compared for 175 lymph nodes. Then, size criteria for discriminating the status of metastasis were evaluated in 915 paraffin-embedded lymph nodes. RESULTS Regardless of the metastatic status and the site of the lymph nodes, a positive relationship was observed between the sizes of the lymph nodes immediately after removal and those of paraffin-embedded sections (P < 0.01). The area under the curve generated by a receiver-operating characteristics curve showed no significant differences between the short-axis diameter and the long-axis diameter, regardless of the lymph node location. Specifically, the optimal cutoff value of the short-axis diameter for discriminating the status of metastasis in mesorectal, internal iliac and obturator lymph nodes extrapolated to the living body was set at 6.2, 5.0 and 4.8 mm, with accuracies of 72.4, 63.8 and 59.3% and with positive predictive values of 29.9, 16.3 and 7.1%, respectively. CONCLUSIONS Size criteria were applicable for discriminating the metastatic status of lymph nodes from three different locations, although the positive predictive values of the size criteria for the internal iliac and obturator lymph nodes were lower than that for the mesorectal lymph nodes.
Pharmacokinetics and pharmacodynamics of atracurium in infants and children.

To determine whether maturational changes in body composition and organ function affect distribution and elimination of and sensitivity to atracurium, the authors determined the pharmacokinetics and pharmacodynamics of atracurium in six infants and five children and compared these results with those obtained in five adults. Atracurium, 15.8 +/- 1.7 micrograms.kg-1.min-1, was infused iv for 6-11 min to subjects anesthetized with nitrous oxide (60%) and halothane (0.9 MAC, age-adjusted) and twitch tension of the adductor pollicis muscle was measured. Plasma samples were obtained for 120 min; concentrations of atracurium were determined using a liquid chromatographic assay. A two-compartment pharmacokinetic model, adapted to account for elimination of atracurium from both central and peripheral compartments, was fit to the plasma concentration data; an effect-compartment model was fit to the twitch tension data. Volume of distribution at steady state (210 +/- 118, 129 +/- 44, and 100 +/- 22 ml/kg for infants, children, and adults, respectively) and total clearance (7.9 +/- 2.0, 6.8 +/- 1.6, and 5.3 +/- 0.9 ml.kg-1.min-1 for the three groups) decreased with increasing age. Neither elimination half-life (20.0 +/- 5.1, 17.2 +/- 5.1, and 15.7 +/- 2.5 min for the three groups) nor the steady state plasma concentration that resulted in 50% neuromuscular blockade (363 +/- 118, 444 +/- 121, and 436 +/- 122 ng/ml for the three groups) varied with age. The authors conclude that these results are consistent with and explain the previously reported findings that recovery from the neuromuscular effects of atracurium is minimally affected by age. (ABSTRACT TRUNCATED AT 250 WORDS)
Human Circulating MicroRNA-1 and MicroRNA-126 as Potential Novel Indicators for Acute Myocardial Infarction

Circulating miRNAs have been shown as promising biomarkers for various pathologic conditions. The aim of this study was to clarify that circulating miR-1 and miR-126 in human plasma might be useful as biomarkers in acute myocardial infarction (AMI). In our study, after pre-test, two candidate miRNAs were detected by using real-time RT-PCR. Cardiac troponin I (cTnI) concentrations were measured by ELISA assay in plasma from patients with AMI (n=17) and healthy subjects (n=25), simultaneously. Increased miR-1 and decreased miR-126 in plasma from patients with AMI after the onset of symptoms compared with healthy subjects were found. A remarkable finding in this study is that miR-1, miR-126 and cTnI expression levels exhibited the same trend. Our results suggest that the plasma concentrations of miR-1 and miR-126 may be useful indicators for AMI.
Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine

Straightforward application of Deep Belief Nets (DBNs) to acoustic modeling produces a rich distributed representation of speech data that is useful for recognition and yields impressive results on the speaker-independent TIMIT phone recognition task. However, the first-layer Gaussian-Bernoulli Restricted Boltzmann Machine (GRBM) has an important limitation, shared with mixtures of diagonal-covariance Gaussians: GRBMs treat different components of the acoustic input vector as conditionally independent given the hidden state. The mean-covariance restricted Boltzmann machine (mcRBM), first introduced for modeling natural images, is a much more representationally efficient and powerful way of modeling the covariance structure of speech data. Every configuration of the precision units of the mcRBM specifies a different precision matrix for the conditional distribution over the acoustic space. In this work, we use the mcRBM to learn features of speech data that serve as input into a standard DBN. The mcRBM features combined with DBNs allow us to achieve a phone error rate of 20.5%, which is superior to all published results on speaker-independent TIMIT to date.
A model of computation for MapReduce

In recent years the MapReduce framework has emerged as one of the most widely used parallel computing platforms for processing data on terabyte and petabyte scales. Used daily at companies such as Yahoo! , Google, Amazon, and Facebook, and adopted more recently by several universities, it allows for easy parallelization of data intensive computations over many machines. One key feature of MapReduce that differentiates it from previous models of parallel computation is that it interleaves sequential and parallel computation. We propose a model of efficient computation using the MapReduce paradigm. Since MapReduce is designed for computations over massive data sets, our model limits the number of machines and the memory per machine to be substantially sublinear in the size of the input. On the other hand, we place very loose restrictions on the computational power of of any individual machine---our model allows each machine to perform sequential computations in time polynomial in the size of the original input. We compare MapReduce to the PRAM model of computation. We prove a simulation lemma showing that a large class of PRAM algorithms can be efficiently simulated via MapReduce. The strength of MapReduce, however, lies in the fact that it uses both sequential and parallel computation. We demonstrate how algorithms can take advantage of this fact to compute an MST of a dense graph in only two rounds, as opposed to Ω(log(n)) rounds needed in the standard PRAM model. We show how to evaluate a wide class of functions using the MapReduce framework. We conclude by applying this result to show how to compute some basic algorithmic problems such as undirected s-t connectivity in the MapReduce framework.
Effect of Stirring Energy, Temperature and Flux Composition on Hot Metal Dephosphorization Kinetics

In order to extend the applicability of a coupled reaction model to the hot metal dephosphorization process, evaluation method for unknown parameters was investigated. The following points were clarified. (1) Mass transfer coefficient in metal phase was increased in proportion to e1/2 and its activation energy was about 125 kJ/mol. (2) Ratio of mass transfer coefficient in metal phase to slag phase did not clearly depend on stirring energy, temperature, or flux composition. (3) Phenomenological rate parameter for CO evolution also did not clearly depend on stirring energy or flux composition but decreased with an increase in temperature. (4) Activity coefficients of FeO and P2O5 in CaF2 and CaCl2 containing oxide slag were able to be estimated by a regular solution model in which the interaction energy was expressed as a function of the CaF2, CaCl2 content.By the application of these results to the coupled reaction model, the change of concentration during the hot metal dephosphorization experiments was calculated without using a parameter fitting method.
Antidepressant use during pregnancy and childhood autism spectrum disorders.

CONTEXT The prevalence of autism spectrum disorders (ASDs) has increased over recent years. Use of antidepressant medications during pregnancy also shows a secular increase in recent decades, prompting concerns that prenatal exposure may contribute to increased risk of ASD. OBJECTIVE To systematically evaluate whether prenatal exposure to antidepressant medications is associated with increased risk of ASD. DESIGN Population-based case-control study. Medical records were used to ascertain case children and control children and to derive prospectively recorded information on mothers' use of antidepressant medications, mental health history of mothers, and demographic and medical covariates. SETTING The Kaiser Permanente Medical Care Program in Northern California. PARTICIPANTS A total of 298 case children with ASD (and their mothers) and 1507 randomly selected control children (and their mothers) drawn from the membership of the Kaiser Permanente Medical Care Program in Northern California. MAIN OUTCOME MEASURES ASDs. RESULTS Prenatal exposure to antidepressant medications was reported for 20 case children (6.7%) and 50 control children (3.3%). In adjusted logistic regression models, we found a 2-fold increased risk of ASD associated with treatment with selective serotonin reuptake inhibitors by the mother during the year before delivery (adjusted odds ratio, 2.2 [95% confidence interval, 1.2-4.3]), with the strongest effect associated with treatment during the first trimester (adjusted odds ratio, 3.8 [95% confidence interval, 1.8-7.8]). No increase in risk was found for mothers with a history of mental health treatment in the absence of prenatal exposure to selective serotonin reuptake inhibitors. CONCLUSION Although the number of children exposed prenatally to selective serotonin reuptake inhibitors in this population was low, results suggest that exposure, especially during the first trimester, may modestly increase the risk of ASD. The potential risk associated with exposure must be balanced with the risk to the mother or fetus of untreated mental health disorders. Further studies are needed to replicate and extend these findings.
Diffusion of dissolved oxygen through concrete

This article describes investigations of the rate of steel corrosion for concrete structures in the ocean. Experiments compared the diffusion of dissolved oxygen through submerged concrete of different qualities and thickness. For a given quality, the flux of oxygen was not proportional to thickness, and for a given thickness not directly related to quality. For the same W/C-ratio, diffusion was lower through mortar than through concrete. The flux was about 10 times lower through a specimen with two cast surfaces than through one with two cut surfaces. The most significant effect on the rate of oxygen diffusion resulted from a twin layer of cement paste on the concrete surface.