Miracle-dz/UniFAR-FTUs huggingface dataset:
The Theory of Optimal Targeting

I consider the issue of optimal targeting in information diffusion networks. The initial information possessor is to target a single node so as to diffuse the information to all other nodes most effectively. For the purpose, the concept of closeness centrality may be useful, but if the value from delayed information is discounted by a discount factor, the concept should be properly modified. With this respect, I propose a modified concept of closeness centrality which I will call δ-(closeness)-centrality. The δ-centrality of a node is defined by the sum of discounted values generated from information transmission starting from the node given discount factor δ. Some advantages of δ-centrality over the closeness centrality are discussed.
The Evolution of Behavioural and Linguistic Skills to Execute and Generate Two-word Instructions in Agents Controlled by Dynamical Neural Networks

This paper illustrates an agent-based simulation model focused on the acquisition of linguistic skills. Populations of simulated agents controlled by dynamical neural networks are trained by artificial evolution to perfom two tasks: the behaviour-production task which consists in accessing and executing linguistic instructions; and the behaviourrecognition task which consists in linguistically recognising behaviours. During training the agent experiences only a subset of all linguistic instructions/behaviours. Trained agents successfully acquire an ability to perform both tasks. Moreover some of the successfull agents proved to be able to access and execute also linguistic instructions not experienced during training. However, none of the successfull agents manage to linguistically recognise behaviours corresponding to the execution of linguistic instructions not experienced during training. We conclude by speculating on potential factors that may have inhibited the agents from developing fully compositional semantics structures.
A double-directional BLAST detection algorithm

Recently, the Bell laboratory layered space-time (BLAST) architecture with multiple transmit and multiple receiver antennas is an efficient method to realize the space-time transmission which can make full use of the rich scattering channel and can greatly increase the spectral efficiency. It has been observed that the detecting ordering is crucial for good performance to alleviate the effort of error propagation. However, the optimal ordering needs a higher computational complexity. To avoid this difficulty, we proposed a double-directional BLAST detection algorithm. It utilizes the improved square-root algorithm without the optimal ordering to detect signals in double direction, and the diversity technique to improve its BER performance. It is shown that the double-directional algorithm can achieve better bit error performance with lower complexity compared to the original V-BLAST algorithm.
Plasma DNA as a prognostic marker in trauma patients.

BACKGROUND Recently, much interest has developed in the potential use of plasma DNA as a diagnostic and monitoring tool. We hypothesized that plasma DNA is increased in patients with trauma and may be prognostic in such patients. METHODS We studied 84 patients who had sustained an acute blunt traumatic injury. We measured plasma DNA by a real-time quantitative PCR assay for the beta-globin gene. Blood samples were collected at a median time of 60 min following injury. Blood samples were also obtained from 27 control subjects. RESULTS The median plasma DNA concentrations in the control, minor/moderate trauma (Injury Severity Score <16; n = 47), and major trauma (Injury Severity Score > or =16; n = 37) groups were 3154 kilogenome-equivalents/L, 13 818 kilogenome-equivalents/L, and 181 303 kilogenome-equivalents/L, respectively. Plasma DNA concentrations in patients with adverse outcomes, including acute lung injury, acute respiratory distress syndrome, and death, had 11. 6- to 12-fold higher plasma DNA concentrations than those who did not develop these complications. At a cutoff of 232 719 kilogenome-equivalents/L, the sensitivities of plasma DNA analysis for the prediction of acute lung injury, acute respiratory distress syndrome, and death were 100% (95% confidence interval, 100-100%), 100% (95% confidence interval, 100-100%), and 78% (95% confidence interval, 40-97%), respectively. The respective specificities were 81% (95% confidence interval, 71-89%), 80% (95% confidence interval, 70-88%), and 82% (95% confidence interval, 71-90%). CONCLUSIONS Plasma DNA is increased after trauma and may be a potentially valuable prognostic marker for these patients.
What Should be Taught in Intermediate Macroeconomics?

A lack of consensus remains on what should form the theoretical core of the undergraduate intermediate macroeconomic course. In determining how to deal with the Keynesian/classical divide, instructors must decide whether to follow the modern approach of building macroeconomic relationships from micro foundations, or to use the traditional approach based on aggregate models of the macroeconomy. In this article, the authors discuss the advantages and shortcomings of each approach in the context of course objectives. Because there is significant heterogeneity in textbook coverage, the authors summarize some of the approaches taken in current intermediate-level textbooks, which should serve as a useful starting point for new instructors. The authors also discuss how each approach can be extended to analyze the recent recession in the United States.
A State Transition Model for Anti-Interference on the Embedded System

Microprogrammed control unit (MCU) and embedded systems are widely used in all kinds of industrial, communication devices and household appliances. However, for the embedded system, even with well hardware protection, the stability are often impacted by the complicated electro magnetic interference (EMI) and the others interference. To get a better system stability ratio, this paper introduces a potent state transition model for the anti-interference intention instead of the empiristic methods. The states of the embedded system are classified into three types: I/O, computing, and error. By the state transition diagram, we deduced a set of anti-interference probability model, which guide the software measures for the anti-interference intention and reduce the unstable probability of the embedded system.
Clinical Potential of Neurosteroids for CNS

Neurosteroids are key endogenous molecules in the brain that affect many neural functions. We describe here recent advances in US National Institutes of Health (NIH)-sponsored and other clinical studies of neurosteroids for CNS disorders. The neuronal GABA-A receptor chloride channel is one of the prime molecular targets of neurosteroids. Allopregnanolone-like neurosteroids are potent allosteric agonists as well as direct activators of both synaptic and extrasynaptic GABA-A receptors. Hence, neurosteroids can maximally enhance synaptic phasic and extrasynaptic tonic inhibition. The resulting chloride current conductance generates a form of shunting inhibition that controls network excitability, seizures, and behavior. Such mechanisms of neurosteroids are providing innovative therapies for epilepsy, status epilepticus (SE), traumatic brain injury (TBI), fragile X syndrome (FXS), and chemical neurotoxicity. The neurosteroid field has entered a new era, and many compounds have reached advanced clinical trials. Synthetic analogs have several advantages over natural neurosteroids for clinical use because of their superior bioavailability and safety trends.
Large-Area Patterning by Vacuum-Assisted Micromolding

946 Ó WILEY-VCH Verlag GmbH, D-69469 Weinheim, 1999 0935-9648/99/1108-0946 $ 17.50+. 50/0 Adv. Mater. 1999, 11, No. 11 layers we achieved were very compact films, i.e. the grains were densely arranged with a large number of inter-grain contacts. Moreover, the electrical measurements showed that Nb addition only had a negligible influence on the intergrain barrier. For these two reasons, magnification of surface effects for gas sensing may reasonably be expected to be bound up with the surface-to-volume ratio of the grains in the films, i.e. with the average size of the grains. Indeed, it is clear from the table that the smaller the grain size, the more sensitive the films. However, in order to achieve a quantitative relationship, further work needs to be done which takes into account the details of CO adsorption at the surface. Finally, by comparing the measurements of Nb-doped TiO2 samples annealed at 650 C (anatase) to the ones at 850 C (rutile), the measured response of the sensors exhibited no significant dependence on the structure of the lattice. This work has demonstrated a way to produce nanosized TiO2 films through the thick-film technique, a method which could be applied to extensive and low-cost production. On the basis of the experience we have gained whilst carrying out these experiments, we conclude that preparation of stable nanostructured thick films of titania can be reproducibly achieved. We attribute such a performance to numerically controlled screen printing, for which accurate control of empirical parameters is possible. Control of grain size was achieved by varying temperature and/or dopant addition. Also highlighted here is the way a nanophase magnifies the property of a material through the practical example of gas sensing. The performance as a sensing layer is interesting because of the high degree of reproducibility by which the sensors can be produced and the negligible influence from humidity in CO detection. Qualitative agreement between structural features and electrical response was also inferred.
GPC-LPV: a predictive LPV controller based on BMIs

In this paper the authors present a predictive linear parameter varying (LPV) controller based on the GPC controller [1]–[3], for nonlinear systems. The resulting controller is denoted as GPC-LPV. This one has the same structure as a general LPV controller [4]–[7], which has a lineal fractional dependence on the process signal measurements. Therefore, this controller has the ability of modifying its dynamics depending on measurements leading to a possibly nonlinear controller. That controller is designed in two steps. First, for a given steady state point is obtained a linear GPC using a local model of the nonlinear system around that operating point. And second, using bilinear matrix inequalities (BMIs) the remaining matrices of GPC-LPV are selected in order to achieve some closed loop properties: stability in some operation zone, norm bounding of some input/output channels, maximum settling time, maximum overshoot, etc. This methodology of design can be applied to nonlinear systems which can be embedded in a LPV system using differential inclusion techniques. Finally, the GPC-LPV is applied to the nonlinear model of a liquid-gas separation process.
Leisure Time Activities, Parental Monitoring and Drunkenness in Adolescents

Background: The aim of this cross-sectional study was to explore the association between adolescent drunkenness and participation in risky leisure time activities and parental monitoring. Methods: A sample of 3,694 Slovak elementary school students (mean age 14.5 years; 49.0% males) was assessed for drunkenness in the previous month, participation in risky leisure activities and parental monitoring. Results: Participation in risky leisure time activities increased the probability of drunkenness among adolescents, while parental monitoring decreased it. The effect did not change after adding the mother’s and father’s monitoring into the models. Conclusion: Our results imply that adolescents involved in going out with friends, having parties with friends and/or visiting sporting events every day or several times a week are at a higher risk of drunkenness, as are those less monitored by their parents. These less monitored adolescents and their parents should become a target group in prevention.
What it means to be “under-connected” in lower-income families

Constrained access to the internet and devices that connect to it, or digital inequality, is more complex than the binary framing of a “digital divide” can possibly capture. If connectivity is a continuum along which all technology users are placed (Livingstone & Helsper, 2007), then it stands to reason that some users are “under-connected,” (Rideout & Katz, 2016), relative to how connected they would like to be. I argue that scholars need to prioritize understanding the realities of being under-connected, adjusting their research methods accordingly, if we are to fully account for how digital inequality impacts both children and adults. I will also argue that scholars need to consider digital inequality in context of social relationships, not as individualized experiences. In the case of children, family context is especially crucial to how digital inequality is experienced. Children’s constrained access to technology is never entirely independent; after all, they rely on parents to purchase devices, prioritize monthly payments for internet access, or get them to libraries if the family doesn’t have internet at home. Less obviously, children depend on parents and siblings as sources of support for learning with technology. As a result, family interactions are fundamental to understanding digital inequalities among children, and to identifying potential pathways for resolving these social disparities. I primarily base my comments on a study I led between 2013 and 2016 to investigate how low-income U.S. parents and their school-age children make decisions about adopting the internet and related devices, and how they integrate those technologies into everyday routines. I was particularly interested in how families responded to national, state, and local policy initiatives that target them with subsidized technology offers to empirically assess how well those digital equity programs are addressing families’ needs.1 My team and I began by conducting in-depth, qualitative interviews with 170 Mexicanheritage parents and their focal child in grades K to 8 (N = 336) who qualified for reduced-cost school meals2 in three school districts in Arizona, California, and Colorado (see Katz & Gonzalez, 2016a, 2016b). With the Joan Ganz Cooney Center at Sesame Workshop and Vicky Rideout, we developed questions for a national survey informed by the interview findings, thereby ensuring that we covered key issues for families and not just what we as researchers thought was important. In early 2015, we deployed a nationally representative telephone
Comparative Ultrastructure of the Sinus Node in Man and Dog

Ultrastructure of the sinus node was studied in human and canine hearts and found to be similar. The principal cell of the sinus node is a small round pale cell with randomly distributed sarcosomes and sparse myofibrils. These cells have been designated as P cells. They occur in elongated clusters and make contact with each other in all directions but do not make direct contact with ordinary working myocardium. Transitional cells, which have features intermediate between P cells and working myocardium, serve as the connections between P cells and the rest of the heart. Each P cell is surrounded by a plasma membrane and groups of them are bound by a basement membrane. The only specialized junction between P cells is the desmosome, which occurs singly and seldom, with most contact being between apposing plasma membranes. P cells exhibit unusually active pinocytosis but have only a sparsely developed sarcoplasmic reticulum. The sarcosomes of P cells are much simpler in internal structure than are those of adjacent working myocardium obtained at the same time in the same heart in the same way, by direct perfusion with glutaraldehyde into the beating sinus node. Correlation of the electron microscopic appearance of the sinus node with that based on light microscopy is discussed, and some of the possible functional significances of the fine structure are considered.
Towards a web tracking profiling algorithm

Accurate tracking of web attackers can be used to identify and monitor repeat offenders, and to allow defenders to deter and/or retaliate against the attackers. Tracking of web clients has been difficult since HTTP is a stateless protocol. Existing methods are limited to the current session and are not designed to track a client long-term or through different environments. This paper evaluates and rates the most popular methods of tracking web users in terms of the uniqueness of the information provided by them, and how well they preserve information when a client attempts to remove them. The tracking methods are then combined using a profiling algorithm to correlate all of the available information into a single profile. The algorithm is designed with different weights for each method. Test results demonstrate that this approach accurately determines the correct profile for a client in situations where the individual methods alone could not.
The Role of Optical Radiations in Skin Cancer

Purpose. Electromagnetic radiation with wavelength in the range 100 nm to 1 mm is known as optical radiation and includes ultraviolet radiation, the visible spectrum, and infrared radiation. The deleterious short- and long-term biological effects of ultraviolet radiation, including melanoma and other skin cancers, are well recognized. Infrared radiation may also have damaging biological effects. Methods. The objective of this review was to assess the literature over the last 15 years and to summarize correlations between exposure to optical radiation and the risk of melanoma and other cancers. Results. There is a clear correlation between exposure to UV radiation and the development of skin cancer. Most importantly, a strong association between artificial UV radiation exposure, for example, tanning devices, and the risk of melanoma and squamous cell carcinoma has been clearly demonstrated. There is no clear evidence that exposure to IR and laser radiation may increase the risk of skin cancer, although negative health effects have been observed. Conclusions. Preventative strategies that involve provision of public information highlighting the risks associated with exposure to sunlight remain important. In addition, precautionary measures that discourage exposure to tanning appliances are required, as is legislation to prevent their use during childhood.
Contextual dynamics of group-based sharing decisions

In this paper we investigate how decisions made while using a granular access control mechanism for sharing photographs are influenced by contextual factors and properties relating to the identities of contacts. We develop analytical models using logistic regression to understand relationships between variables that affect sharing decisions. We also investigate how predefined, static groups for privacy control cope with the challenge of sharing large amounts of content associated with numerous different contexts, and test whether they need to be adjusted to suit particular contexts.
Educational Robots: Three Models for the Research of Learning Theories and Human-Robot Interaction

In the summer of 2006, the Tulane Electrical Engineering and Computer Science department teamed up with UNO graduate students in education and developmental psychology to conduct experiments in the education of young children using robotic agents. Students from the “AI Robotics” class used the Sony AIBO robotic dog to design three different educational systems geared primarily toward young physically and mentally challenged children. We consulted with UNO graduate students concerning prekindergarten education and visited a special education institution, The Chinchuba Institute. The Chinchuba Institute educates hearing- and speech-impaired children, along with children with mental disabilities. We returned with impressive results, designing three systems that focus on methods of communication with the student and usability for the student and teacher. We encountered many challenges in designing for the pre-K and K-12 classroom, such as making the robot interaction robust and intuitive to a child.
A Software System for Anisotropic Diffusion Analysis of Diffusion Tensor Images

A software system of an isotropic diffusion analysis was developed for diffusion index calculation and fiber tractography of diffusion tensor magnetic resonance imaging (DT-MRI) data. The least square method is used to solve tensor calculation. The fractional anisotropy (FA) and color-coded FA mapping were calculated. The paper explain how to calculate diffusion tensor, eigenvalues and other parameters of each voxel and the fiber tracts. The fibers in the whole brain were obtained by the Streamline Tracking Techniques (STT). Matlab code developed the software program for an isotropic diffusion analysis of diffusion tensor images and it will be opened in the sprit of open source. We hope the code will help the researchers who are interested in the DTI images for research of neuron science.
Surface bidirectional reflectance and albedo properties derived using a land cover-based approach with Moderate Resolution Imaging Spectroradiometer observations

[1] Surface bidirectional reflectance distribution function (BRDF) and albedo maps are derived from Moderate Resolution Imaging Spectroradiometer (MODIS) multiday surface reflectance composites with a 500-m spatial resolution (MODIS product MOD09A1/MYD09A1). The proposed method dubbed land cover–based fitting employs the processing of clear-sky reflectance data for similar land cover types and takes into account the magnitude of normalized difference vegetation index (NDVI). The BRDF is derived through the fitting of pixel data sorted into small bins according to the values of angular variables and NDVI. Robust statistical processing is applied to reduce the influence of noise and outliers. This method increases the success rate of the fitting process and enables more accurate monitoring of surface temporal changes during periods of rapid spring vegetation green up and autumn leaf fall, as well as changes due to agricultural practices and snow cover variations. The approach is specifically applied over the Atmospheric Radiation Measurement Program Southern Great Plains area. Results are compared to alternative BRDF/albedo products, such as the MOD43 albedo and Multiangle Imaging Spectroradiometer surface products that are derived through a pixel-based fitting process. A good agreement was generally found between different data sets. For example, the average biases in the visible and near-infrared bands are usually less than 0.01 and 0.02, respectively, and correlation coefficients are typically larger than 0.80. An analysis of these differences identifies some unique advantages of the proposed method, such as the ability to capture rapidly changing surface properties and an increased performance in the case of reduced number of clear-sky observations because of frequent cloudy conditions. Results suggest that the developed land cover–based methodology is valuable for the purpose of surface BRDF and albedo mapping using MODIS observations.
Kernel Fisher Discriminants as Acoustic Models in HMM-based Speech Recognition

While the temporal dynamic of speech can be handled very efficiently by Hidden Markov Models (HMMs), the classification of the single speech units (phonemes) is usually done with Gaussian probability density functions which are not discriminative. In this paper we use the Kernel Fisher Discriminant (KFD) for classification by integrating this method in a HMM-based speech recognition system. In this structure we translate the outputs of the KFD into class-conditional probabilities and use them as production probabilities in an HMM-based speech decoder. The KFD has already shown good classification results in other fields (e. g. pattern recognition). To obtain good performance also in terms of computational complexity the KFD is implemented iteratively with a sparse greedy approach. We train and test the described hybrid structure on the Resource Management (RM1) task.