Miracle-dz/UniFAR-FTUs huggingface dataset:
Fructose‐1,6‐Bisphosphate Stabilizes Brain Intracellular Calcium During Hypoxia in Rats

Background and Purpose: Exogenously administered fructose-l,6-bisphosphate reduces neuronal injury from hypoxic or ischemic brain insults. To test the hypothesis that fructose-l,6-bisphosphate prevents changes in intracellular calcium ([Ca2+])i and high-energy phosphate levels, we measured [Ca2+]1, intracellular pH (pH1), and adenosine triphosphate in cultured rat cortical astrocytes and cortical brain slices during hypoxia. Methods: The fluorescent indicators fura-2 and bis-carboxyethyl-carboxyfluorescein were used to simultaneously measure [Ca2+]1 and pH1 with a fluorometer. Results: Exposure to hypoxia (95% N2,5% CO2) or 100 μM sodium cyanide produced transient increases in [Ca2+]i in astrocytes and sustained increases in [Ca2+]i in brain slices. Adenosine triphosphate levels fell in slices exposed to hypoxia or cyanide. Fructose-l,6-bisphosphate (3.5 mM) blocked increases in [Ca2+]1 and prevented depletion of adenosine triphosphate. Fructose-l,6-bisphosphate also partially prevented adenosine triphosphate depletion in brain slices incubated in glucose-free medium. Iodoacetate (a specific inhibitor of glycolysis) elevated [Ca2+]1 and partially prevented these actions of fructose-1,6-bisphosphate. Changes in pHi during hypoxia were not affected by fructose-l,6-bisphosphate. Conclusions: Fructose-l,6-bisphosphate supports adenosine triphosphate production via stimulation of glycolysis and results in the maintenance of normal [Ca 2+]i during hypoxia or hypoglycemia.
Switch and Tap-Changer Reconfiguration of Distribution Networks Using Evolutionary Algorithms

The reconfiguration of distribution networks is an important combinatorial problem. This work addresses the particular case of reconfiguration after an outage caused by the loss of a single branch of the network. The reconfiguration is carried out over two domains simultaneously: re-switching strategies and transformer tap-changer adjustments. The approach was tested using a real large-scale network within the concession area of Energy Australia. The model considers four operational elements: an AC power flow model, the network's radial topology when operating, voltage limits and load limits. Two evolutionary algorithms were implemented and tested. The first was a genetic algorithm, applied over the space of possible re-switching strategies, and for both re-switching and tap-changer adjustments, simultaneously. The second was a memetic algorithm, applied over the same two variations of the reconfiguration problem. Computational tests consider the evaluation of the loss of every branch, reporting the number of buses affected, and the number of overloaded branches after the reconfiguration.
Performance Analysis of Joint User Scheduling and Antenna Selection Over MIMO Fading Channels

In this letter, a performance analysis is presented for a joint multiuser scheduling and antenna selection in MIMO systems employing orthogonal space-time block coding (OSTBC) over Rayleigh fading channels under a general case of heterogeneous scenario. Using numerical evaluations the performance of different cases of the considered scheme are compared for heterogeneous and homogeneous scenarios.
Online Social Capital: Social Networking Sites' Influence on Civic and Political Engagement

ONLINE SOCIAL CAPITAL: SOCIAL NETWORKING SITES’ INFLUENCE ON CIVIC AND POLITICAL ENGAGEMENT Charles L. Bush Old Dominion University, 2018 Director: Dr. Scott R. Maggard This thesis examines how using social networking sites (SNS) is correlated with levels of civic and political engagement of college students at Old Dominion University. Past research has yielded mixed results on the link between online social capital and civic and political engagement. Major limitations of past research include grouping together social networking sites that are substantially different and not considering these sites’ impact on the different forms of social capital. This thesis first examines how social networking site preference, intensity of use, and motives for use factor into an individual’s online social capital. Secondly, this thesis looks at how online bridging, bonding, and maintained social capital influence an individual’s level of civic and political engagement. Results from an internet-based survey showed Instagram users had the highest level of online social capital. As expected, respondents who used SNS with greater intensity with the purpose to gather information had higher levels of online social capital. Additionally, individuals who had higher levels of online social capital reported being more civically and politically active. These findings contributed to the limited body of research focusing on SNS and online social capital and provide valuable knowledge about the link between using social networking sites and participating in political and civic activities. Future research should build on this research expand the scope of this study by sampling a broader sample, further validating the measures used, and comparing various forms of social networking sites.
Optical fiber refractive index sensor based on peanut flat-end reflection structure

An optical fiber peanut flat-end reflection refractive Index sensor based on Michelson interference principle is experimentally demonstrated. It has one peanut structure which makes it easy to fabricate and can implement measurement on the same side. The peanut structure is fabricated by electrical arc discharge. This structure constitutes a Michelson interferometer. Experimental results show that the relationship between the refractive index of the tested solution and the extinction ratio of the interference spectrum is a quadratic function, the fitting degree is 0.9915, and the refractive index measurement range is from 1.34 to 1.43. In the measurement range of refractive index from 1.34 to 1.43, its measurement sensitivity decreases with the increase of the refractive index of tested solution, when refractive index is 1.34, the maximum measurement sensitivity is 197.872 dB while the minimum measurement sensitivity is 9.394 dB when the refractive index is 1.43.
A Microsimulation Model of the Distributional Impacts of Climate Policies

Carbon policies introduce potentially uneven cost burdens. Anticipating these outcomes is important for policymakers seeking to achieve an equitable outcome and can be politically important as well. This paper describes the details of a microsimulation model that utilizes the price and quantity changes predicted by economic models of carbon policies to make an estimation of economic incidence by income quintile or state, and potentially across other dimensions. After taking as inputs the aggregate output from partial or general equilibrium economic modeling, the microsimulation model uses data from the Consumer Expenditure Survey (CE), the State Energy Data System (SEDS), the National Income and Product Accounts (NIPA), estimations from the Congressional Budget Office (CBO), and the Haiku electricity model. These data sources are used to estimate the share of consumer and producer surplus changes that accrue to households in each income quintile and state. The model is unique among existing incidence models in its ability to drill down to the level of state incidence and to plug into a wide range of economic models.
Differential Geometry-Based Adaptive Nonlinear Control Law: Application to an Industrial Refinery Process

In this contribution, an extended generic model control (EGMC) law is proposed based on differential geometry theory. This multivariable nonlinear control system requires the knowledge of the internal state of the process. To cope with this, an adaptive control scheme is formulated here. This adaptive nonlinear control law combines the EGMC with the Luenberger-type nonlinear state estimator (LNSE). Deriving the control law and the state estimator, the stability properties of the EGMC, LNSE and the combined EGMC-LNSE structure are developed. The application and performance of the proposed adaptive EGMC-LNSE control law are finally illustrated by a simulated industrial refinery process (i.e., debutanizer). The representative column has 169 state variables, and it was operated in the province of Alberta, Canada. It is surprising to note that the LNSE scheme aims to estimate a few states that are solely required for the controller based on only two component balance equations. As a consequence, there exists a significant structural discrepancy and despite it, the proposed nonlinear controller shows its superiority over the multivariable dynamic matrix controller.
Smart data synchronization in m-Health monitoring applications

Nowadays, mobile applications/devices have become the trends, especially, when they were gradually shifted from basic communication services to supporting more sophisticated service provisioning. Mobile applications are usually very light, are nowadays likely to be often connected to the Internet, and can be used quite easily. However, these applications exhibit some challenges related to limited resources they have access to, including limited processing power, memory, storage size, battery power, and intermittent network connection. In fact, these considerations have to be taken seriously into consideration when developing mobile applications especially if those applications will be used for critical services, for example, to collect and report vital health data over a long period of time. In this paper, we study the use of mobile applications for monitoring patient's vital. Mobile devices, through an application, are connected to body-strapped biosensors to collect and synchronize these parameters with information systems. This synchronization should be done in such a way that the cost of synchronization is kept low and urgent readings are delivered as soon as possible. To optimize the synchronization process and reduce its cost, we propose and validate cost-oriented algorithms. A case study is developed to illustrate the applicability and effectiveness of our innovative techniques in making continuous monitoring an efficient process.
Requirements for Realistic Remote Education Systems

Telepresence resources are available for at least two decades, but its use is still very low, both in education and industry. There are two main reasons: to save on telecommunication costs, current systems impose restrictions on quality that precludes the transmission of minute details, essential for the transmission the subjective contents of the material, and to save on display equipment, the amount of displayed information is insufficient. This paper proposes minimum standards of quality to overcome these problems, in a remote education context.
Learning the boundary of One-Class-Classifier globally and locally

The one class classification problem aims to distinguish a target class from outliers. Two popular algorithms, one-class SVM (OCSVM) and single-class MPM (SCMPM), solve this problem by finding a hyperplane with the maximum distance to the origin. Their essential difference is that OCSVM focuses on the support vectors (SV) in a local manner while SCMPM emphasizes the whole datapsilas distribution using global information. In fact, these two seemingly different yet complementary characteristics are all important prior knowledge for the one-class-classifier (OCC) design. In this paper, we propose a novel OCC called global & local (GLocal) OCC, which incorporates the global and local information in a unified framework. Through embedding the samplespsila distribution information into the original OCSVM, the GLocal OCC provides a general way to extend the present SVM algorithm to consider global information. Moreover, the optimization problem of the GLocal OCC can be solved using the standard SVM approach similar to OCSVM, and preserves all the advantages of SVM. Experiment results on benchmark data sets show that the GLocal OCC really has better generalization compared with OCSVM and SCMPM.
Power Law of Customers' Expenditures in Convenience Stores

We study the statistical laws of the expenditure of a person in convenience stores by analyzing around 100 million receipts. As shown in “T. Mizuno, JPSJ 77 (2008)” and “T. Mizuno et al, Physica A 387 (2008)”, the density function of expenditure exhibits a fat tail that follows a power law. Using the Lorenz curve, the Gini coefficient is estimated to be 0.70; this implies that loyal customers contribute significantly to a store’s sales. We observe the Pareto principle where both the top 25% and 2% of the customers account for 80% and 25% of the store’s sales, respectively.
Named Entity Based Answer Extraction form Hindi Text Corpus Using n-grams

Most existing systems, are constructed for the English language, such as state-of-art system Watson that win the Jeopardy challenge. While working with Indian languages (i.e. Hindi), a richer morphology, greater syntactic variability, and less number of standardized rules availability in the language are just some issues that complicate the construction of systems. It is also considered a resource-poor language since proper gazetteer lists and tagged corpora is not available for it. In this paper, Named Entity (NE) based n-gram approach is used for processing questions written in Hindi language and extract the answer from Hindi documents. Combination of classical information retrieval term weighing model with a linguistic approach mainly based on syntactic analysis is used. We use a corpus of 420 questions and 300 documents containing around 20,000 words as a back-end for closed-domain (World History) Question Answering. A Named Entity Recognizer is employed to identify answer candidates which are then filtered according their usage. Results obtained using this technique outperforms the previously used techniques (e.g. Semantic Based Query Logic).
Objective Types for the Valuation of Secure Business Processes

In today's business environments, the unimpeded execution of corporate business processes is crucial for a company's success. As business processes are permanently exposed to a variety of threats, companies are increasingly forced to pay attention to security issues. Existing approaches for the evaluation of security measures often neglect the consideration of business needs and multiple objectives. This paper gives an overview of the Atana approach that supports decision makers with the elicitation of security safeguards based on corporate business processes and according to multiple objectives. It introduces different objectives types that are needed for measuring the value of security investments.
Heart Rate Variability as Reactivity in Alcoholics an Index of Cue

Background: Autonomic responses fol low exposure to conditioned stimuli such as contextual factors associated with alcohol ingestion. Heart rate variabili O, is under autonomic control and may be a measure o f such response. Methods: Twenty alcoholics and 23 matched social drinkers (all male) were exposed to a neutral cue and then an ah'ohol cue in identical settings, during which the electrocardiogram o f these subjects was recorded. Time and frequency domain parameters o f heart rate variability (HRV) were computed by a blind rater. Resul ts : Coefficient o f variation ~( R-R intervals and absolute powers" o f HRV spectrum (in frequency bands 0 .05-0.15 Hz and 0.01-0.05 Hz) Jbllowing alcohol cue were significantly higher in alcoholics than social drinkers'. The mean heart rate (MHR). f i l i led to reflect this d~[fl, rence. Conclusions: HRV paradigm appears more sensitive than MHR to measure cue reactivity. Biol Psychiatry 1998; 43:544--546 © 1998 Society o f Biological Psychiat O,
Sparse representations in deep learning for noise-robust digit classification

Many sparse regularization methods for encouraging succinct hierarchical features of deep architectures have been proposed, but there is still a lack of studies that compare them. We present a comparison of several sparse regularization methods in deep learning with respect to the performance of a noisy digit classification task under varying size of training samples. We also propose a deep hybrid architecture built from a particular combination of sparse auto-encoders and Restricted Boltzmann Machines. The results show that the sparse architectures can produce better classification performance under noisy test samples than the dense architectures in most cases. In addition, the deep hybrid architectures can solve the digit classification task more effectively with a small size of training samples.
Charge Friedel oscillations in a Mott insulator

When a metal undergoes a transition to an insulator it will lose its electronic Fermi surface. Interestingly in some situations a `ghost' Fermi surface of electrically neutral spin carrying fermions may survive into the insulator. Such a novel ghost Fermi surface has been proposed to underlie the properties of a few different materials but its direct detection has proven elusive. In this paper we show that the ghost Fermi surface leads to slowly decaying spatial oscillations of the electron density near impurities or other defects. These and related oscillations stem from the sharpness of the ghost Fermi surface and are direct analogs of the familiar Friedel oscillations in metals. The oscillation period contains geometric information about the shape of the ghost Fermi surface which can be potentially exploited to detect its existence.
The Halfway Vector Disk for Empirical BRDF Modeling

We present a mathematical framework for specifying halfway vector distributions in simple two-dimensional domains in such a way that the corresponding BRDF is energy-preserving. Using this framework, we create an energy-preserving empirical BRDF that allows easy specification of diffuse, specular, and retroreflective materials. With the energy conservation constraint, our BRDF produces physically plausible rendered images with accurate behavior, especially near grazing angles. We also present a different BRDF model that is useful for data fitting; although it does not preserve energy, it uses the same halfway vector distribution domains as the first model. We show that this data-fitting BRDF can be used to match measured data extremely well using only a small set of intuitive parameters. We believe that this is an improvement over table-based lookups and factored versions of BRDF data. CR Categories: G.3 [Mathematics of Computing]: Probability and Statistics—Monte Carlo I.3. 7 [Computing Methodologies]: Computer Graphics—Raytracing
Nonrandom chromosome arrangements in germ line nuclei of Sciara coprophila males: the basis for nonrandom chromosome segregation on the meiosis I spindle

Meiosis I in males of the Dipteran Sciara coprophila results in the nonrandom distribution of maternally and paternally derived chromosome sets to the two division products. Based on an earlier study (Kubai, D.F. 1982. J. Cell Biol. 93:655-669), I suggested that the meiosis I spindle does not play a direct role in the nonrandom sorting of chromosomes but that, instead, haploid sets are already separated in prophase nuclei well before the onset of spindle formation. Here I report more direct evidence that this hypothesis is true; this evidence was gained from ultrastructural reconstruction analyses of the arrangement of chromosomes in germ line nuclei (prophase nuclei in spermatogonia and spermatocytes) of males heterozygous for an X- autosome chromosome translocation. Because of this translocation, the maternal and paternal chromosome sets are distinguishable, so it is possible to demonstrate that (a) the two haploid chromosome sets occupy distinct maternal and paternal nuclear compartments and that (b) nuclei are oriented so that the two haploid chromosome sets have consistent relationships to a well-defined cellular axis. The consequences of such nonrandom aspects of nuclear structure for chromosome behavior on premeiotic and meiotic spindles are discussed.
A highly-digitized automotive CAN transceiver in 0.14µm high-voltage SOI CMOS

This paper presents a novel CAN transceiver based on a highly-digitized architecture designed and fabricated in 0. 14μm high-voltage SOI CMOS. This advanced BCD process allows the implementation of this innovative architecture which combines digital and high-voltage analog circuits. Hence, the output stage can be split in multiple unit cells successively enabled or disabled by a shift register. It also allows an advantageous implementation of a dual-clock CAN receiver that combines an architecture optimized for high EM Immunity with a low-power mode where a low-frequency clock is used to reduce the power consumption. EMC performance was evaluated according to automotive industry standards. It shows excellent EME and EMI compliance to car manufacturer requirements without using a common-mode choke.
Limiting the Fall-Out from Fiscal Adjustment

In a review of every major fiscal correction in the OECD since 1975, we find that decisive budgetary adjustments that have focused on reducing government expenditure have (i) been successful in correcting fiscal imbalances; (ii) typically boosted growth; and (iii) resulted in significant bond and equity market outperformance. Tax-driven fiscal adjustments, by contrast, typically fail to correct fiscal imbalances and are damaging for growth.
Chapter 3: Distributed intelligence

In the last chapter we concluded that pattern formation in natural systems occurs as a consequence of simple local rules. We looked at plants, at artificial creatures in the game of life, and at seashells. We now look at emergence of behavioral patterns that can be interpreted by an external observer as some kind of “distributed intelligence”. In this chapter we will proceed by inspecting some examples from robots and natural agents. We start with an experiment in collective robotics. We then discuss self-organizing phenomena in insect societies. Next, we briefly present Craig Reynolds’s famous boids. Finally, we discuss some “guiding heuristics for decentralized thinking”, as outlined by Mitchel Resnick.
An automatic evaluation method of image mattes

In image matting, several algorithms that produce high-quality results have recently been proposed; however, certain parameters have to be manually determined in order to obtain favorable results, which requires significant user effort. In this paper, we propose a method of automatically evaluating alpha mattes based on either of the two criteria: mutual information or correlation coefficient between the matte and the image gradient fields, and selecting optimal parameter values. This drastically reduces the user effort required for tuning parameters in image matting. The experimental results using several matting algorithms for various images show that the automatically selected alpha mattes are similar (or the same) to the manually selected optimal ones.