Miracle-dz/UniFAR-FTUs huggingface dataset:
Mapping and Resynthesis for LUT-based FPGAs with an Efficient SAT-Based Boolean Matching

To support FPGA synthesis in the OAGear package, we have implemented the following new components: (i) a cut-based technology mapper for LUT-based FPGA with delay/area optimization options, (ii) an efficient SAT-based Boolean matcher (SAT-BM) for both single-output and multipleoutput Boolean functions, and (iii) an area-aware resynthesis algorithm using this SAT-BM. The SAT-BM incorporates the recent improvements presented in [1], which shows over 200x speedup compared to the original SAT-BM algorithm [2]. The resynthesis considers both single-output and multiple-output logic blocks [3] and reduces the number of LUTs by up to 1.4%, compared to Berkeley ABC mapper.
Partisanship , Voting , and the Dopamine D 2 Receptor Gene

Previous studies have found that both political orientations (Alford, Funk, and Hibbing 2005) and voting behavior (Fowler, Baker, and Dawes 2008; Fowler and Dawes 2008) are significantly heritable. In this article we study genetic variation in another important political behavior: partisan attachment. Using the National Longitudinal Study of Adolescent Health, we show that individuals with the A2 allele of the D2 dopamine receptor gene are significantly more likely to identify as a partisan than those with the A1 allele. Further, we find that this gene’s association with partisanship also mediates an indirect association between the A2 allele and voter turnout. These results are the first to identify a specific gene that may be partly responsible for the tendency to join political groups, and they may help to explain correlation in parent and child partisanship and the persistence of partisan behavior over time.
Brightness- and motion-based blink detection for head-mounted eye trackers

Blinks are an indicator for fatigue or drowsiness and can assist in the diagnose of mental disorders, such as schizophrenia. Additionally, a blink that obstructs the pupil impairs the performance of other eye-tracking algorithms, such as pupil detection, and often results in noise to the gaze estimation. In this paper, we present a blink detection algorithm that is tailored towards head-mounted eye trackers and is robust to calibration-based variations like translation or rotation of the eye. The proposed approach reached 96,35% accuracy for a realistic and challenging data set and in real-time even on low-end devices, rendering the proposed method suited for pervasive eye tracking.
Leptoquark Production and Identification in High Energy μ + μ − , e + e − and eγ Collisions ∗

We study single leptoquark production in ee, eγ, and μμ collisions due to the quark content of the photon. Leptoquarks can be produced in substantial numbers for masses ver y close to the centre of mass energy of the collider which resul ts in equivalently high discovery limits. Using polarization as ymmetries in aneγ collider the ten different types of leptoquarks listed by Buchmüller, Rückl and Wyler can be distinquished from o ne another for leptoquark masses essentially up to the kinemat ic limit. Thus, if a leptoquark were discovered an eγ collider could play a crucial role in determining its origins.
An Operation Scheme for T Hroughput Maximization and Fairness in CDMA Cellular Systems with AMC

In this paper, the throughput maximization and fairness problems in the downlink of a sectored CDMA cellular system with AMC techniques are studied. We focus on maximizing the data rate for users on the cell border. An optimum data transmission with power control allocates the maximum allowable rate to only one user with the highest SINR. However, this throughput maximization rate allocation strategy causes high unfairness. On the other hand, if more service time or slots are assigned to the lower SINR users for fairness, system throughput will be decreased. Thus, we propose the operation of the system in a four time interval duty cycle that increases system throughput and fairness at the same time. In the first interval, users close to the base stations are served, one at a time in every sector. In the rest of the time intervals, for users close to the cell border, an On-Off Synchronous sectored operation is achieved. In this operation only one sector of each cell is allowed to transmit per each interval to only one user. Optimum durations of the time intervals are obtained. The results show that the average data rate at the cell border is increased 75% and the average data rate over the sector area is increased 9.7% relative to the traditional one-by-one transmission in each sector.
Offered load control in IEEE 802.11 multi-hop ad-hoc networks

In a multi-hop ad-hoc network, stations may pump more traffic into it than can be supported, resulting in high packet-loss rate, rerouting instability and unfairness problems. The paper shows that controlling the offered load at the sources can eliminate these problems. In addition, we provide an analysis to estimate the optimal offered load that maximizes the throughput of a multi-hop traffic flow. We use this result to devise schemes that can achieve fairness when there are multiple flows from different sources to different destinations. We believe this is the first paper in the literature to provide a quantitative analysis (as opposed to simulation) for the impact of hidden nodes, exposed nodes, and signal capture on sustainable throughput. The analysis is based on the observation that a large-scale 802.11 network with hidden nodes is a network in which the carrier-sensing capability breaks down partially. Its performance is therefore somewhere between a carrier-sensing network and an ALOHA network. Indeed, our analytical closed-form solution has the appearance of the throughput equation of the ALOHA network. Our approach allows one to identify whether the performance of an 802.11 network is hidden-node limited or spatial-reuse limited.
Robust Independence-Based Causal Structure Learning in Absence of Adjacency Faithfulness

This paper presents an extension to the Conservative PC algorithm which is able to detect violations of adjacency faithfulness under causal sufficiency and triangle faithfulness. Violations can be characterized by pseudo-independent relations and equivalent edges, both generating a pattern of conditional independencies that cannot be modeled faithfully. Both cases lead to uncertainty about specific parts of the skeleton of the causal graph. This is modeled by an f-pattern. We proved that our Very Conservative PC algorithm is able to correctly learn the f-pattern. We argue that the solution also applies for the finite sample case if we accept that only strong edges can be identified. Experiments based on simulations show that the rate of false edge removals is significantly reduced, at the expense of uncertainty on the skeleton and a higher sensitivity for accidental correlations.
Optimization of DSR routing protocol in MANET using passive clustering

Routing algorithms in Mobile Ad hoc Networks like DSR, AODV use flooding as the primary mechanism for discovery of routes in the network. In flooding, each node forwards flood packets to its neighbors so as to ensure that the packets reach the intended destination. Forwarding of redundant flood packets create extra overhead on network bandwidth. However, only a subset of nodes need to forward the packet to make it reach its destination. Clustering has been proven as an efficient mechanism to reduce flooding overhead in MANETs. Active Clustering algorithms use explicit control packets to create and maintain clusters whereas passive clustering piggybacks the control information in the outgoing data packets thus significantly reducing control overhead. The proposed algorithm integrates Passive Clustering with DSR routing protocol. Route Discovery phase of DSR floods the Route Request packets in the entire network. However, the proposed algorithm creates the clusters in the network in the initial phase of Route Discovery process and once the clusters are formed only a subset of nodes will forward the Route Request packets. This approach reduces the overhead on bandwidth by curtailing the flooding of packets and thereby increasing the packet delivery ratio. The simulation results show that optimized DSR algorithm enhances the packet delivery ratio by minimum of 20% and reduces the RREQ flooding by a minimum of 30%.
Design and Analysis for a 60-GHz Low-Noise Amplifier With RF ESD Protection

An RF electrostatic discharge (ESD) protection for millimeter-wave (MMW) regime applied to a 60-GHz low-noise amplifier (LNA) in mixed-signal and RF purpose 0.13-mum CMOS technology is demonstrated in this paper. The measured results show that this chip achieves a small signal gain of 20.4 dB and a noise figure (NF) of 8.7 dB at 60 GHz with 65-mW dc power consumption. Without ESD protection, the LNA exhibits a gain of 20.2 dB and an NF of 7.2 dB at 60 GHz. This ESD protection using an impedance isolation method to minimize the RF performance degradation sustains 6.5-kV voltage level of the human body model on the diode and 1.5 kV on the core circuit, which is much higher than that without ESD protection (< 350 V). To our knowledge, this is the first CMOS LNA with RF ESD protection in the MMW regime and has the highest operation frequency reported to date.
Frayed cell diagrams

Tesselation-based or area-based visual representations are common to many artistic or visualization applications. For example, Voronoi art uses a space-filling tessellation of the image by Voronoi cells. We present frayed cell diagrams as an aesthetic visual representation of the separating border between those space-filling regions. Our approach is based on a simple randomized algorithm that densely draws lines toward the reference points of cells. This algorithm is controlled by a few parameters whose effects are detailed in the paper: the density and size of cells, the degree of fraying, and the color coding. To demonstrate the usefulness of frayed diagrams for algorithmic art, we applied them to pieces of Voronoi art. Finally, we conducted a survey to assess the aesthetics of the frayed cell diagrams. As a result, we found out that the majority of the participants preferred a high degree of fraying, but that a non-negligible subgroup preferred diagrams without any fraying.
More Is Not Necessarily Better: Prozone-Like Effects in Passive Immunization with IgG1

Despite a century of study, the relationship between Ag-specific Ig concentration and protection remains poorly understood for the majority of pathogens. In certain conditions, administration of high Ab doses before challenge with an infectious agent can be less effective than smaller Ab doses, a phenomenon which is consistent with a prozone-like effect. In this study, the relationship between IgG1, IgG2a, IgG2b, and IgG3 dose, infective inocula, and protection was investigated in a mouse model of Cryptococcus neoformans infection. The activity of each IgG subclass ranged from protective to disease-enhancing depending on both the Ab dose and infective inocula used. Enhanced dissemination to the brain was observed in mice given a high IgG2a dose and a relatively low inoculum. Ab administration had immunomodulatory effects, with cytokine expression in lung, brain, and spleen varying as a function of the infective inoculum Ab dose and IgG subclass. In vitro studies did not predict or explain the mechanism of in vivo prozone-like effects, because all isotypes were opsonic and elicited NO release from macrophages. IgG2a was most efficient in inducing a macrophage oxidative burst. These results reveal that an individual Ab can be protective, nonprotective, or disease-enhancing depending on its concentration relative to a challenge inoculum. Our findings have implications for the potential contribution of Ab responses to defense against microbial diseases because Ab-mediated immunity may be protective, nonprotective, or even deleterious to the host.
Dietary germanium biotite supplementation enhances the induction of antibody responses to foot-and-mouth disease virus vaccine in pigs

We evaluated the potential ability of germanium biotite (GB) to stimulate the production of antibodies specific for foot-and-mouth disease virus (FMDV). To this aim, we measured the total FMDV-specific antibody responses and IgM production after vaccination against FMD both experimentally and in the field. GB supplementation with FMDV vaccination stimulated the production of anti-FMDV antibodies, and effectively increased IFN-γ and TNF-α levels. These results suggest that GB may be a novel alternative feed supplement that can serve as a boosting agent and an immunostimulator for increasing the efficacy of FMDV vaccination in pigs.
Feedback Selecting of Manually Acquired Rules Using Automatic Evaluation

As the number of manually acquired rules in a patent translation system increases, conflicts between rules inevitably exist. Meanwhile, lacking the matched cases of manually acquired rules in real bilingual corpus, people may conceive rules which cause implausible impact on machine translation quality. In this paper, we propose a feedback selecting algorithm for manually acquired rules in patent translation using automatic evaluation, which picks out manually acquired rules that benefit machine translation quality. Experiments show that we achieve significant improvement in terms of BLEU (+5.23 points over baseline).
Introducing Linggle: From Concordance to Linguistic Search Engine

We introduce a Web-scale linguistics search engine, Linggle, that retrieves lexical bundles in response to a given query. Unlike a typical concordance, Linggle accepts queries with keywords, wildcard, wild part of speech (PoS), synonymous words, and additional regular expression (RE) operators, and returns bundles with frequency counts. In our approach, we argument Google Web 1T corpus with inverted file indexing, PoS information from BNC, and semantic indexing based on Latent Dirichlet Allocation. The method involves parsing the query to transforming the query to several keyword retrieval commands, retrieving word chunks with counts, filtering the chunks again the query as a RE, and finally displaying the results according the count, similarity, and topic. Clusters of synonymous or conceptually related words are also provided. In addition, Linggle provide example sentences from The New York Times on demand. The current implementation of Linggle is the most comprehensive functionally, and is in principle language and dataset independent. We plan to extend Linggle to provide a fast and convenient access to a wealth of linguistic information embodied in Web scale datasets including Google Web 1T and Google Books Ngram for many major languages in the World. For non-native speakers, doubts concerning the usage of a preposition, the mandatory presence of a determiner, the correctness of the association of a verb with an object or the need for synonyms of a term in a given context are problems that arise frequently when writing in English. Printed collocation dictionaries and reference tools based on compiled corpora offer limited coverage of word usage while knowledge of collocations is vital for the competent use of a language. We propose to address these limitations with a comprehensive system that truly aims at letting learners “know a word by the company it keeps”. Linggle (linggle.com) is a broad coverage language reference tool for English as Second Language learners (ESL). The system is designed to access words in context under various forms. First, we build inverted file index for the Google Web 1T Ngram to support queries with RE-like patterns including PoS and synonym matches. For example, for the query “$V $D +important role”, Linggle retrieve 4-gram chunks that start with a PACLIC-27
Planning of large rural low-voltage networks using evolution strategies

This paper presents a method based on evolution strategies for designing large rural low-voltage (LV) distribution networks. Planning rural LV distribution networks involves radial configuration design, location of medium-voltage/low-voltage substations, and minimum cost. In this work, these goals are considered by taking into account different conductors, voltage drop and conductor capacity constraints, power losses in lines, and deterministic loads. The algorithms developed in this paper are based on evolution strategies (ES) and were implemented on large-scale rural LV distribution networks, but they could also be used in general network optimization.
A Lightweight Key Management Protocol for Hierarchical Sensor Networks

Key Management is a fundamental security service in distributed sensor networks. The focus of this paper is to design a lightweight group key management scheme to safeguard the data packet passing on the sensor networks under different types of attacks. We propose an energy efficient level-based hierarchical system and build the secure route from the source node to sink node . We compromise between the energy consumption and the shortest path by utilizing the number of neighbors of a sensor when renewing a cluster head or choosing the next hop in the hierarchical clusters. In addition, our protocol contains group communication policies, group membership require-ments and an algorithm for generating a distributed group key for secure communication.
Evidence that 4-Hydroxynonenal Mediates Oxidative Stress-Induced Neuronal Apoptosis

Oxidative stress is believed to play important roles in neuronal cell death associated with many different neurodegenerative conditions (e.g., Alzheimer’s disease, Parkinson’s disease, and cerebral ischemia), and it is believed also that apoptosis is an important mode of cell death in these disorders. Membrane lipid peroxidation has been documented in the brain regions affected in these disorders as well as in cell culture and in vivo models. We now provide evidence that 4-hydroxynonenal (HNE), an aldehydic product of membrane lipid peroxidation, is a key mediator of neuronal apoptosis induced by oxidative stress. HNE induced apoptosis in PC12 cells and primary rat hippocampal neurons. Oxidative insults (FeSO4 and amyloid β-peptide) induced lipid peroxidation, cellular accumulation of HNE, and apoptosis. Bcl-2 prevented apoptosis of PC12 cells induced by oxidative stress and HNE. Antioxidants that suppress lipid peroxidation protected against apoptosis induced by oxidative insults, but not that induced by HNE. Glutathione, which binds HNE, protected neurons against apoptosis induced by oxidative stress and HNE. PC12 cells expressing Bcl-2 exhibited higher levels of glutathione and lower levels of HNE after oxidative stress. Collectively, the data identify that HNE is a novel nonprotein mediator of oxidative stress-induced neuronal apoptosis and suggest that the antiapoptotic action of glutathione may involve detoxification of HNE.
Implementation of multikernel sparse representation on remote sensing image classification

This paper presents a novel multikernel based Sparse representation for the classification of Remotely sensed images. The sparse representation based feature extraction are in a run which is a signal dependent feature extraction and thus more accurate. Multikernel Sparse representation was also had proved to be more accurate and less computationally complex while implemented in other applications like the video object tracking. Affine transform based templates are extracted from the image which has to be trained and the kernel matrix is generated which is used for comparison with the templates extracted from the test images. Kernel Coordinate Descent (KCD) algorithm. The weight values updated using the observation likelihood calculation from the proposed algorithm is used to train the SVM for the image classification in remote sensing images. The template with the highest weight values would be taken as the classified portion of the query image. Matlab based implementation is carried out on the image classification using the Multikernel Sparse Represenation (MKSR) and the results are observed and tabulated.
On Massive Conflict: Macro-Micro Link

Micro and macro properties of social system should be taken as relative poles of a two dimensional continuum since every debate on social system will however shift to the discussion on the two levels of description. This is consistently used as perspective to see massive social conflict. We propose analysis of the emerging conflict on its micro-causations by using computer simulations. We construct a dynamical model based on some propositions on massive conflict based upon the individual’s degree of membership to collective identity she has whether to mobilize or not. The simulations result the possibilities to see the linkage of the macro-micro properties in the case of massive conflict and suggestions on how to cope with massive conflict or even to resolve it. The paper is an endeavor to a more comprehensive methodology on how to cope with conflict on research and theory development.
Neurobiology of Disease Evolution of Synchrony Dynamics across Brain Structures in Limbic Epilepsy Varies Between the Initiation and Termination Phase of Seizures Abbreviated title : Synchrony dynamics during seizure phases

a Illinois Institute of Technology, Department of Biomedical Engineering, 3255 South Dearborn Street, Wishnick Hall, Room 314, Chicago, IL 60616-3793, United States b University of Illinois, Department of Bioengineering, Medical Scientist Training Program, Chicago, IL, United States c University of Illinois, Department of Mathematics, Statistics & Computer Science, Chicago, IL, United States * Both authors contributed equally to this research.
The United States as a debtor nation

The United States has once again entered into a period of large external imbalances. This time the current account deficit, at nearly 6 percent of GDP in 2004, is much larger than in the last episode, when the deficit peaked at about 3.5 percent of GDP in 1987. Moreover, the deficit is on track to become substantially larger over the next several years. This study examines whether the large and growing current account deficit is a problem, and if so, how the problem can be solved. A central policy conclusion of this study is that it is increasingly important that the United States reduce its external current account deficit. This deficit is no longer benign as it arguably was in the late 1990s when it was financing high investment instead of high consumption and large government dissaving.
Credit Spread Changes Under Switching Regimes

Many empirical studies on credit spread determinants consider a single regime model over the entire sample period and …nd limited explanatory power for theoretical deter- minants of credit spreads. In this paper, we show that accounting for dierent regimes enhances the explanatory power of these determinants. We also obtain that credit spreads have their own cycle which is dierent from the economic cycle. Then, we model the credit cycle independently from macroeconomic fundamentals using a Markov regime switching model. We …nd that, in contrast to the economic cycle, the introduction of the credit cycle increases the model's adjusted R-squared to up to 60% on average for the 10-year AA to BB credit spread changes.