Miracle-dz/UniFAR-FTUs huggingface dataset:
Mitigation of Sulfur Dioxide Emission for Utility Expansion: A Long Term Model Incorporating Independent Power Producers

Efforts to reduce levels of sulfur dioxide (SO2) are increasingly emphasized as an effective response to dire environmental circumstances worldwide. In light of the vast number of environmental uncertainties, a utility must analyze the nexus of different alternatives from a broader and long-term perspective with various implications. While attempting to comply with environmental provisions and satisfying privatization trends in the electric industry, this work presents a novel model which includes alternatives such as switching fuels, installing scrubbers, purchasing emission credits, and procuring power for thermal plants. Data from Taiwan’s utility scheme are used to analyze the effectiveness of the proposed model. Implementation results demonstrate that purchasing credits or procuring power from independent power producers (IPPs) is more beneficial than other alternatives. By using the proposed model, Taipower will be able to evaluate the effect of the newly issues and the governments could review the related regulations.
Brain Dendritic Cells and Macrophages/Microglia in Central Nervous System Inflammation1

Microglia subpopulations were studied in mouse experimental autoimmune encephalomyelitis and toxoplasmic encephalitis. CNS inflammation was associated with the proliferation of CD11b+ brain cells that exhibited the dendritic cell (DC) marker CD11c. These cells constituted up to 30% of the total CD11b+ brain cell population. In both diseases CD11c+ brain cells displayed the surface phenotype of myeloid DC and resided at perivascular and intraparenchymatic inflammatory sites. By lacking prominent phagocytic organelles, CD11c+ cells from inflamed brain proved distinct from other microglia, but strikingly resembled bone marrow-derived DC and thus were identified as DC. This brain DC population comprised cells strongly secreting IL-12p70, whereas coisolated CD11c− microglia/brain macrophages predominantly produced TNF-α, GM-CSF, and NO. In comparison, the DC were more potent stimulators of naive or allogeneic T cell proliferation. Both DC and CD11c− microglia/macrophages from inflamed brain primed naive T cells from DO11.10 TCR transgenic mice for production of Th1 cytokines IFN-γ and IL-2. Resting microglia that had been purified from normal adult brain generated immature DC upon exposure to GM-CSF, while CD40 ligation triggered terminal maturation. Consistently, a functional maturation of brain DC was observed to occur following the onset of encephalitis. In conclusion, these findings indicate that in addition to inflammatory macrophage-like brain cells, intraparenchymatical DC exist in autoimmune and infectious encephalitis. These DC functionally mature upon disease onset and can differentiate from resident microglia. Their emergence, maturation, and prolonged activity within the brain might contribute to the chronicity of intracerebral Th1 responses.
Early-onset alcoholism with conduct disorder: go/no go learning deficits, working memory capacity, and personality.

BACKGROUND Two studies were conducted to investigate the disinhibitory mechanisms that (1) discriminate early-onset alcoholism (EOA) with conduct disorder (CD; antisocial EOA) from a non-antisocial subtype of EOA and (2) are associated with novelty-seeking and low harm avoidance. METHODS Young adults with antisocial EOA (n = 96), with non-antisocial EOA (without CD; n = 80), with CD alone (n = 50), and controls (n = 125) were given two go/no go tasks (one with monetary loss and the other with shock punishment), the Digit Span test (working memory capacity), and personality measures of harm avoidance, novelty-seeking/impulsivity, excitement-seeking, and negative affectivity. RESULTS Study 1 revealed that antisocial EOA subjects had poor behavioral inhibition compared with non-antisocial EOAs and controls on both go/no go tasks and with the CD-alone group on the monetary-loss task. Low Digit Span scores accentuated poor inhibition in antisocial EOAs on the monetary loss, but not the shock task. EOA with low Digit Span was associated with higher hit rates on the shock task. Study 2 revealed that antisocial EOAs had high novelty-seeking/impulsivity and low harm avoidance compared with both non-antisocial EOAs and controls. Low harm avoidance was associated with poor inhibition with shock punishment, and this association was mediated by CD. For subjects with low Digit Span scores, novelty-seeking/impulsivity was associated with poor inhibition to monetary-loss punishment and higher hit rates to shock punishment. CONCLUSIONS The results suggest two disinhibitory mechanisms that distinguish antisocial from non-antisocial EOA: an increased sensitivity to reward in nonaversive contexts associated with novelty-seeking/impulsivity and a decreased sensitivity to punishment in aversive contexts associated with low harm avoidance. Results also suggest that EOA and novelty-seeking/impulsivity are associated with a greater response to rewards in those with low working memory capacity.
Properties of a baculovirus mutant defective in the protein phosphatase gene

Autographa california nuclear polyhedrosis virus (AcMNPV) contains a gene, ptp, encoding a protein tyrosine/serine phosphatase, BV-PTP. To investigate the biological function of ptp in the baculoviral replication cycle, we constructed a recombinant baculovirus, vPTPdel, in which the catalytically active site of BV-PTP was deleted. Although the vPTPdel mutant was viable in cell culture, it was partially defective in occluded virus production in SF-21 but not TN-368 cell lines. SF-21 cells infected with vPTPdel were heterogeneous in their ability to support occluded virus production. These results suggest that BV-PTP functions in a cell line-specific and possibly a cell cycle-specific fashion. The yield of occlusion bodies, infectivity (concentration of virus causing 50% mortality) and virulence (the time at which 50% of the cells died) of vPTPdel appeared to be normal in insect larvae. We identified a 35-kDa phosphoprotein as a potential target of the BV-PTP in SF-21 cells.
Analytical Drain Current Model for Fully Depleted Surrounding Gate TFET

In this paper, we propose the analytical modeling for fully depleted surrounding gate TFET surrounding gate tunneling field effect transistor with single metal gate. This model comprises the surface potential using 2-D Poisson’s equation and drain current with the effects of oxide thickness, silicon thickness as radius, drain voltage, gate metal work function, and assuming channel is fully depleted. The model is tested using TCAD Simulation Tool.
A Global Optimisation Algorithm for 802.11 WLAN Radio Resource Management

The wireless link is still the bottleneck in 802.11 WLAN systems, especially in a public WLAN deployment with high-demand users. The most common way of improving the system performance is by accurate site planning, but this still does not cope with dynamic demand from users, such as in hotspots at an airport where travellers with WLAN laptops tend to gather at different gates at different times. In this paper, a novel intelligent radio resource management system for WLANs with low-cost semi-smart antennas is proposed and evaluated. The access points can re-configure their radio coverage patterns to balance hot-spot traffic. Using a global optimisation algorithm, significant performance improvement is discovered over traditional configurations by simulations.
UWB for Robust Indoor Tracking: Weighting of Multipath Components for Efficient Estimation

In a radio propagation channel, deterministic reflections carry important position-related information. With the help of prior knowledge such as a floor plan, this information can be exploited for indoor localization. This letter presents the improvement of a multipath-assisted tracking approach using information about the relevance of deterministic multipath components in an environment. This information is fed to a tracking filter as an observation noise model. It is estimated from a few training signals between anchors and an agent at known positions. Tracking results are presented for measurements in a partial non-line-of-sight environment. At a bandwidth of 2 GHz, an accuracy of 4 cm can be achieved for over 90% of the positions if additional channel information is available. Otherwise, this accuracy is only possible for about 45% of the positions. The covariance of the estimation matches closely to the corresponding Cramèr-Rao lower bound.
Cytoplasmic glycogen inclusions in cells of anaerobic gram-negative rumen bacteria.

Megasphaera elsdenii, an anaerobic rumen bacterium, produced intracellular polysaccharide granules varying in size from 0.05 to 0.15 μm during growth in batch culture. This polysaccharide material was purified and was found to contain D-glucose as the only reducing sugar. The polyglucose polymer was highly opalescent in aqueous solution and formed a strong reddish-brown iodine complex with a maximum absorbance at 493 nm. Its infrared spectrum had characteristic absorption bands at 8.70, 9.25, and 9.75 μm and was identical with that of the glycogen of enteric bacteria and beef liver. When these polysaccharide granules were observed with an electron microscope, they resembled the glycogen granules produced by Arthrobacter globiformis and Escherichia coli. These properties indicate that the polysaccharide was a type of glycogen. The yield of crude glycogen was 16.82% of the dry weight of late log-phase cells (14-h). The lysis of cells of M. elsdenii and other rumen bacteria that store polysaccharide granules .
Energy Efficiency Maximization Framework in Cognitive Downlink Two-Tier Networks

To support the surge in wireless data traffic, the spectrum and energy efficiencies of cellular networks should be largely increased. Heterogeneous two-tier architecture has been identified as one key solution. However, small-cell deployment raises questions about the resulting energy efficiency and interference mitigation. Therefore, we propose an energy-efficient and cognitive spectrum sharing scheme between primary macrocell and secondary small cells. Specifically, the small cells allocate their transmission power to maximize their total energy efficiency while respecting some interference constraints imposed by macrocell users. We solve this centralized optimization in two steps. First, assuming that the small-cell transmissions are noninterfering, the solution of this nonconvex optimization is characterized using a convex parametric approach. Using this characterization, we derive an algorithm based on Newton method, which converges to a global optimal solution. Second, when the small-cell transmissions are not necessarily orthogonal, we derive an algorithm, which converges at least to a local optimum, using the minorization-maximization principle and Newton method. Through simulations, we validate the convergence of these algorithms and compare their performance with existing schemes. We also analyze the effects of the interference and of the number of users on the energy efficiency.
The spectrum of power from wind turbines

The power spectral density of the output of wind turbines provides information on the character of fluctuations in turbine output. Here both 1-second and 1-hour samples are used to estimate the power spectrum of several wind farms. The measured output power is found to follow a Kolmogorov spectrum over more than four orders of magnitude, from 30 s to 2.6 days. This result is in sharp contrast to the only previous study covering long time periods, published 50 years ago. The spectrum defines the character of fill-in power that must be provided to compensate for wind’s fluctuations when wind is deployed at large scale. Installing enough linear ramp rate generation (such as a gas generator) to fill in fast fluctuations with amplitudes of 1% of the maximum fluctuation would oversize the fill-in generation capacity by a factor of two for slower fluctuations, greatly increasing capital costs. A wind system that incorporates batteries, fuel cells, supercapacitors, or other fast-ramp-rate energy storage systems would match fluctuations much better, and can provide an economic route for deployment of energy storage systems when renewable portfolio standards require large amounts of intermittent renewable generating sources. © 2007 Elsevier B.V. All rights reserved.
Implementation and Characterization of a Physical Unclonable Function for IoT: A Case Study With the TERO-PUF

Today, life is becoming increasingly connected. From TVs to smartphones, including vehicles, buildings, and household appliances, everything is interconnected in what we call the “Internet of Things” (IoT). IoT is now part of our life and we have to deal with it. More than ten billion devices are already connected and five times more are expected to be deployed in the next five years. While deployment and integration of IoT is expanding, one of the main challenge is to provide practical solutions to security, privacy, and trust issues in IoT. Protection and security mechanisms need to include features such as interoperability and scalability but also traceability, authentication, and access control while remaining lightweight. Among the most promising approaches to such security mechanisms, physical unclonable functions (PUFs) provide a unique identifier for similar but different integrated circuits using some of their physical characteristics. These types of functions can thus be used to authenticate integrated circuits, provide traceability and access control. This paper presents a comprehensive case study of the transient effect ring oscillator (RO) PUF from its implementation on FPGAs to its complete characterization. The implementation of the PUF is detailed for two different families of FPGAs: 1) Xilinx Spartan 6 and 2) Altera Cyclone V. All the metrics used for the characterization are explained in detail and the results of the characterization include robustness to environmental parameters including variations in temperature and voltage. Finally, we compare our results with those obtained for another PUF: the RO PUF. All the design files are available online to ensure repeatability and enable comparison of our contribution with other studies.
Acc: generic on-demand accelerations for neighbor discovery in mobile applications

As a supporting primitive of many mobile device applications, neighbor discovery identifies nearby devices so that they can exchange information and collaborate in a peer-to-peer manner. To date, discovery schemes trade a long latency for energy efficiency and require a collaborative duty cycle pattern, and thus they are not suitable for interactive mobile applications where a user is unable to configure others' devices. In this paper, we propose Acc, which serves as an on-demand generic discovery accelerating middleware for many existing neighbor discovery schemes. Acc leverages the discovery capabilities of neighbor devices, supporting both direct and indirect neighbor discoveries. Our evaluations show that Acc-assisted discovery schemes reduce latency by a maximum of 51.8%, compared with the schemes consuming the same amount of energy. We further present and evaluate a Crowd-Alert application where Acc can be employed by taxi drivers to accelerate selection of a direction with fewer competing taxis and more potential passengers, based on a 10 GB dataset of more than 15,000 taxis in a metropolitan area.
Solving Combinatorial Auctions Using Stochastic Local Search

Combinatorial auctions (CAs) have emerged as an important model in economics and show promise as a useful tool for tackling resource allocation in AI. Unfortunately, winner determination for CAs is NP-hard and recent algorithms have difficulty with problems involving goods and bids beyond the hundreds. We apply a new stochastic local search algorithm, Casanova, to this problem, and demonstrate that it finds high quality (even optimal) solutions much faster than recently proposed methods (up to several orders of magnitude), particularly for large problems. We also propose a logical language for naturally expressing combinatorial bids in which a single logical bid corresponds to a large (often exponential) number of explicit bids. We show that Casanova performs much better than systematic methods on such problems.
Inflation and Stock Prices: No Illusion

Campbell and Vuolteenaho (2004) use VAR results to advocate inflation illusion as the explanation for the positive association between inflation and the dividend yield. Contrary to their results, we find that a fully rational dynamic general equilibrium model can generate a positive correlation between the dividend yield and inflation of comparable size to its data counterpart. The model results support a proxy hypothesis, according to which, a third factor, which in our model represents technology shocks, moves both inflation and the dividend yield in the same direction, resulting in a positive correlation between the two. The VAR structure of our model solutions makes it possible to decompose the dividend yield into the long-run expected dividend growth rate and the discount rate components, so that their relative importance can be studied.
Scaffolding as an Organizing Principle in Trans-translation

A eubacterial ribosome stalled on a defective mRNA can be released through a quality control mechanism referred to as trans-translation, which depends on the coordinating binding actions of transfer-messenger RNA, small protein B, and ribosome protein S1. By means of cryo-electron microscopy, we obtained a map of the complex composed of a stalled ribosome and small protein B, which appears near the decoding center. This result suggests that, when lacking a codon, the A-site on the small subunit is a target for small protein B. To investigate the role of S1 played in trans-translation, we obtained a cryo-electron microscopic map, including a stalled ribosome, transfer-messenger RNA, and small protein Bs but in the absence of S1. In this complex, several connections between the 30 S subunit and transfer-messenger RNA that appear in the +S1 complex are no longer found. We propose the unifying concept of scaffolding for the roles of small protein B and S1 in binding of transfer-messenger RNA to the ribosome during trans-translation, and we infer a pathway of sequential binding events in the initial phase of trans-translation.
Learning Optimal Dialogue Management Rules by Using Reinforcement Learning and Inductive Logic Programming

Developing dialogue systems is a complex process. In particular, designing efficient dialogue management strategies is often difficult as there are no precise guidelines to develop them and no sure test to validate them. Several suggestions have been made recently to use reinforcement learning to search for the optimal management strategy for specific dialogue situations. These approaches have produced interesting results, including applications involving real world dialogue systems. However, reinforcement learning suffers from the fact that it is state based. In other words, the optimal strategy is expressed as a decision table specifying which action to take in each specific state. It is therefore difficult to see whether there is any generality across states. This limits the analysis of the optimal strategy and its potential for re-use in other dialogue situations. In this paper we tackle this problem by learning rules that generalize the state-based strategy. These rules are more readable than the underlying strategy and therefore easier to explain and re-use. We also investigate the capability of these rules in directing the search for the optimal strategy by looking for generalization whilst the search proceeds.
Analysis of the hand effect on head SAR with generic and CAD phone models using FDTD

The assessment methodology and procedures of the peak-spatial SAR in the head are defined in IEEE 1528 [1]. In the current version of the standard, the user's hand is not included for obtaining conservative SAR results. However, recent studies have demonstrated that the hand can increase the SAR in the head in some cases [2]. In other words, the SAR measurement without considering the effect of the user's hand may not always be the most conservative estimation. It is a great challenge to study the effect of the hand in terms of SAR, since mobile phones and the hand have very complicated geometries and are in the reactive near-field of the antenna. The objective of this paper is to conduct a multi-variable study of the effect of the hand on the SAR in the head with generic phone models and generic hand and head phantoms.
Wyner-Ziv source coding with feedback and uncertain side information

In this paper, the problem of lossy source coding with side information at the decoder is considered when the dependency between the source and the side information (SI) is quasi-stationary and unknown to the encoder. This dependency is modeled using a (virtual) block fading channel. In order to help the decoder estimate the dependency, a part of the transmitted source in each block is coded at high rate (disregarding the SI) to be decoded error-free at the decoder. The estimate of the virtual block fading channel is imperfect and its quality depends on the length of the estimation block. The decoder's estimate is then quantized and communicated back to the encoder using a limited rate feedback. The encoder encodes the rest of the source block with this knowledge of the SI dependency model. A source coding scheme that uses the estimated dependency structure is proposed and the appropriate length of the source assigned for the estimation phase is characterized so as to minimize the mean distortion. The effect of the feedback rate, the quantization step size and the dependency estimation error are also investigated.
Constructing a Model-based Optimum Currency Area Index

The EU acceding countries are supposed to adopt the Euro as soon as economic convergence is achieved. This paper offers a methodology to quantify the economic consequences of an acceding country’s EMU entrance. A small macroeconomic two-country model is specified and combined with two different monetary policy regimes: (i) national monetary policy, (ii) monetary union. The performance of the two regimes is analyzed in terms of inflation and output variability. A model-based optimum currency area index is obtained by computing the relative loss in terms of output gap and inflation rate variability in the two monetary policy regimes.
Relevance feedback learning with feature selection in region-based image retrieval

Region-based image retrieval and relevance feedback are two important methods to bridge the gap between the low-level visual features and the high-level semantic concepts in content-based image retrieval. In this paper, we address the issue of introducing the relevance feedback mechanism into the region-based image retrieval with online feature selection during each feedback round. Our contribution is two-fold. (1) A novel region-based image representation is proposed. Based on a generative model, a fuzzy codebook is extracted from the original region-based features, which represents the images in a uniform real-value feature space. (2) A feature selection criterion is developed and an effective relevance feedback algorithm is implemented in a boosting manner to simultaneously select the optimal features from the fuzzy codebook, and generate a strong ensemble classifier over the selected features. Experimental results show that the proposed scheme can substantially improve the retrieval performance of the region-based image retrieval system.