Miracle-dz/UniFAR-FTUs huggingface dataset:
Extracting Exact Answers to Questions Based on Structural Links

This paper presents a novel approach to extracting phrase-level answers in a question answering system. This approach uses structural support provided by an integrated Natural Language Processing (NLP) and Information Extraction (IE) system. Both questions and the sentence-level candidate answer strings are parsed by this NLP/IE system into binary dependency structures. Phrase-level answer extraction is modelled by comparing the structural similarity involving the question-phrase and the candidate answer-phrase.There are two types of structural support. The first type involves predefined, specific entity associations such as Affiliation, Position, Age for a person entity. If a question asks about one of these associations, the answer-phrase can be determined as long as the system decodes such pre-defined dependency links correctly, despite the syntactic difference used in expressions between the question and used in expressions between the question and the candidate answer string. The second type involves generic grammatical relationships such as V-S (verb-subject), V-O (verb-object). Preliminary experimental results show an improvement in both precision and recall in extracting phrase-level answers, compared with a baseline system which only uses Named Entity constraints. The proposed methods are particularly effective in cases where the question-phrase does not correspond to a known named entity type and in cases where there are multiple candidate answer-phrases satisfying the named entity constraints.
Correction of Spatially Varying Image and Video Motion Blur Using a Hybrid Camera

We describe a novel approach to reduce spatially varying motion blur in video and images using a hybrid camera system. A hybrid camera is a standard video camera that is coupled with an auxiliary low-resolution camera sharing the same optical path but capturing at a significantly higher frame rate. The auxiliary video is temporally sharper but at a lower resolution, while the lower frame-rate video has higher spatial resolution but is susceptible to motion blur. Our deblurring approach uses the data from these two video streams to reduce spatially varying motion blur in the high-resolution camera with a technique that combines both deconvolution and super-resolution. Our algorithm also incorporates a refinement of the spatially varying blur kernels to further improve results. Our approach can reduce motion blur from the high-resolution video as well as estimate new high-resolution frames at a higher frame rate. Experimental results on a variety of inputs demonstrate notable improvement over current state-of-the-art methods in image/video deblurring.
Abnormalities in Bone Mineral Density and Bone Histology in Thalassemia

This study demonstrated that there was extensive iron staining on trabecular surface and marked reduction in trabecular bone volume without significant alteration in bone formation and bone resorption rates as well as significant reduction in bone mineral density in 18 thalassemic patients. Serum IGF‐I was reduced and may modulate the reduction of bone mass.
A Modified DVB-T System Architecture with Multi-Carrier Multi-Code Transmission and MPIC Based Reception

In this paper, we propose a modified DVB-T system architecture with a multi-carrier multi-code transmission format. The main techniques we use in the system include the orthogonal Walsh code spreading and soft multipath interference cancellation (soft MPIC). Both techniques are used to combat the system degradation caused by the multipath effect. With the spreading gain and the path diversity gain achievable from the used techniques, the proposed system architecture shows much better performance compared with the original DVB-T system.
Synchrony and Stability of Food Webs in Metacommunities

Synchrony has fundamental but conflicting implications for the persistence and stability of food webs at local and regional scales. In a constant environment, compensatory dynamics between species can maintain food web stability, but factors that synchronize population fluctuations within and between communities are expected to be destabilizing. We studied the dynamics of a food web in a metacommunity to determine how environmental variability and dispersal affect stability by altering compensatory dynamics and average species abundance. When dispersal rate is high, weak correlated environmental fluctuations promote food web stability by reducing the amplitude of compensatory dynamics. However, when dispersal rate is low, weak environmental fluctuations reduce food web stability by inducing intraspecific synchrony across communities. Irrespective of dispersal rate, strong environmental fluctuations disrupt compensatory dynamics and decrease stability by inducing intermittent correlated fluctuations between consumers in local food webs, which reduce both total consumer abundance and predator abundance. Strong correlated environmental fluctuations lead to (i) spatially asynchronous and highly correlated local consumer dynamics when dispersal is low and (ii) spatially synchronous but intermediate local consumer correlation when dispersal is high. By controlling intraspecific synchrony, dispersal mediates the capacity of strong environmental fluctuations to disrupt compensatory dynamics at both local and metacommunity scales.
How does the information capacity of ad hoc networks scale

n source and destination pairs randomly located in an area want to communicate with each other. Signals transmitted from one user to another at distance r apart is subject to a power attenuation of r as well as a random phase. We identify exactly the scaling laws of the information theoretic capacity of the network. In the case of dense networks, where the area is fixed and the density of nodes increasing, we show that the total capacity of the network scales linearly with n. In the case of extended networks, where the density of nodes is fixed and the area increasing linearly with n, we show that the sum capacity scales as n for α < 3 and √ n for α ≥ 3. Thus, much better scaling than multihop can be achieved in dense networks, as well as in extended networks with low attenuation. The performance gain is achieved by intelligent node cooperation and distributed MIMO communication. The key ingredient is a hierarchical and digital architecture for nodal exchange of information for realizing the cooperation.
Variational sequences on finite order jets of submanifolds

The theory of finite order variational sequences has been recently developed trough Krupka’s finite order variational bicomplex and Vinogradov’s C-spectral sequence. Such theories are formulated on finite order jets of fibred manifolds. In this paper we shall provide a formulation on finite order jets of submanifolds using Vinogradov’s C-spectral sequence approach. New insight on the geometry of jets of submanifolds is obtained as a by-product of our research. Intrinsic and coordinate expressions of relevant objects are given.
An Algorithm for Secure Key Distribution and Data Transfer in MANETS

a mobile ad hoc network (MANET) is self-organizing, dynamic topology network, which is formed by a collection of mobile nodes through radio links. MANETs enable wireless communication between mobile devices without relying on a fixed infrastructure. Hence, routing in dynamic network is a new challenge. We used various routing algorithms for smooth exchange of information between mobile nodes. Generally we imply security on all the nodes of the network. But this causes wastage of time and cost. This paper proposes that first we have to find out the shortest path and then imply the security in multicast routing. The routing is done with the help of GDH. We use the Key obtained by GDH to transfer data from source to destination. But there can be a malicious node that can change the key so that it can change the data sent to the destination node. So we have to find out these intruders (malicious nodes) that i have proposed in this paper. This proposed scheme will improve the performance of the network such as delay and packet delivery ratio than traditional routing algorithms.
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

When considering human neuroimaging data, an appreciation of signal variability represents a fundamental innovation in the way we think about brain signal. Typically, researchers represent the brain's response as the mean across repeated experimental trials and disregard signal fluctuations over time as "noise". However, it is becoming clear that brain signal variability conveys meaningful functional information about neural network dynamics. This article describes the novel method of multiscale entropy (MSE) for quantifying brain signal variability. MSE may be particularly informative of neural network dynamics because it shows timescale dependence and sensitivity to linear and nonlinear dynamics in the data.
A Preference-Aware Service Recommendation Method on Map-Reduce

Service recommender systems have shown to be valuable tools to provide appropriate recommendations to the users. However, in most of existing service recommender systems, the ratings and rankings of services presented to different users are the same, which didn't consider users' preferences and therefore could not meet users' personalized requirements. Moreover, the number of customers, alternative services and other online information grows rapidly. Thus, the improvement of scalability and efficiency of recommender systems is also necessary and urgent. In view of these challenges, a preference-aware service recommendation method on Map-Reduce, named PASR, is proposed in this paper. It aims at presenting a personalized ranking list and recommending the most appropriate services to the users from big data environment. In this method, keywords are used to indicate users' preferences, and a user based Collaborative Filtering algorithm is adopted to generate appropriate recommendations. To improve the scalability and efficiency of PASR, we implement it on a distributed computing platform, Hadoop, which uses Map-Reduce as its computing framework. Finally, experimental results show that our approach performs well both in accuracy and scalability.
Correlated gamma frailty models for bivariate survival data

ABSTRACT Frailty models are used in the survival analysis to account for the unobserved heterogeneity in individual risks to disease and death. To analyze the bivariate data on related survival times (e.g., matched pairs experiments, twin or family data) the shared frailty models were suggested. Shared frailty models are used despite their limitations. To overcome their disadvantages correlated frailty models may be used. In this article, we introduce the gamma correlated frailty models with two different baseline distributions namely, the generalized log logistic, and the generalized Weibull. We introduce the Bayesian estimation procedure using Markov chain Monte Carlo (MCMC) technique to estimate the parameters involved in these models. We present a simulation study to compare the true values of the parameters with the estimated values. Also we apply these models to a real life bivariate survival dataset related to the kidney infection data and a better model is suggested for the data.
Performance improvement of MHN-enhanced uplink with frequency offset compensation

This paper proposes an uplink frequency offset compensation scheme for the millimeter-wave (mmWave) based mobile hotspot network that provides a wireless backhaul link of high-speed railway communications. We designed new uplink control and shared channels to mitigate Doppler effects and also proved that the proposed automatic frequency control (AFC) scheme employing the newly designed uplink channels showes better block error rate performances than the original channel structures.
Simplified stimuli generation for scenario and assertion based verification

Simulation-based approaches that require to drive the design under verification (DUV) to specific conditions, like for example, scenario-based testing and dynamic assertion-based verification (ABV), cannot rely on generic coverage-driven stimuli generators. On the contrary, constraint-based generation must be adopted. In this context, among several solutions, the Universal Verification Methodology (UVM) and the SystemC Verification Library (SCV) represent the main alternatives. However, their powerfulness is paid in term of easiness of use. In fact, their application generally requires to write complex pieces of code to specify the constraints that must be satisfied by the stimuli generator to produce the desired sequences of values. More is the complexity of setting up an effective stimuli generator, more is the risk of failing to capture the right behaviour and/or having a longer verification time. To overcome these problems, the paper presents a framework and a corresponding language for the automatic generation of stimuli that requires to write intuitive and compact directives representing the desired constraints. The approach is independent from the language adopted for the DUV implementation and it works for both embedded hardware as well as embedded software.
Calcium measurement in the periphery of an axon

Aequorin was microinjected into squid giant axons, the axons were stimulated, and the change in light emission was followed. This response was compared with that found when the axon, in addition to being microinjected with aequorin, is also injected with the dye phenol red. Large concentrations of phenol red injected into axons result in a high probability that photons emitted by aequorin, when it reacts with Ca in the core of the axoplasm, will be absorbed before they escape from the axon; photons produced by the aequorin reaction at the periphery of the axoplasm are much less likely to be absorbed. This technique thus favors observing changes in Cai taking place in the periphery of the axon. Stimulation in 50 mM Ca seawater of an aequorin- phenol red-injected axon at 180 s-1 for 1 min produces a scarcely detectable change in Cai; the addition of 2 mM cyanide (CN) to the seawater produces an easily measureable increase in Cai, suggesting that mitochondrial buffering in the periphery is substantial. Making the pH of the axoplasm of a normal axon alkaline with 30 mM NH4+ -50 mM Ca seawater, reduces the resting glow of the axon but results in an even more rapid increase in Cai with stimulation. In a phenol red- injected axon, this treatment results in a measureable response to stimulation in the absence of CN.
Query-sensitive embeddings

A common problem in many types of databases is retrieving the most similar matches to a query object. Finding those matches in a large database can be too slow to be practical, especially in domains where objects are compared using computationally expensive similarity (or distance) measures. This paper proposes a novel method for approximate nearest neighbor retrieval in such spaces. Our method is embedding-based, meaning that it constructs a function that maps objects into a real vector space. The mapping preserves a large amount of the proximity structure of the original space, and it can be used to rapidly obtain a short list of likely matches to the query. The main novelty of our method is that it constructs, together with the embedding, a query-sensitive distance measure that should be used when measuring distances in the vector space. The term "query-sensitive" means that the distance measure changes depending on the current query object. We report experiments with an image database of handwritten digits, and a time-series database. In both cases, the proposed method outperforms existing state-of-the-art embedding methods, meaning that it provides significantly better trade-offs between efficiency and retrieval accuracy.
Decreased Contractile and Metabolic Reserve in Peroxisome Proliferator–Activated Receptor-&agr;–Null Hearts Can Be Rescued by Increasing Glucose Transport and Utilization

Background— Downregulation of peroxisome proliferator–activated receptor-&agr; (PPAR&agr;) in hypertrophied and failing hearts leads to the reappearance of the fetal metabolic pattern, ie, decreased fatty acid oxidation and increased reliance on carbohydrates. Here, we sought to elucidate the functional significance of this shift in substrate preference. Methods and Results— We assessed contractile function and substrate utilization using 13C nuclear magnetic resonance spectroscopy and high-energy phosphate metabolism using 31P nuclear magnetic resonance spectroscopy in perfused hearts isolated from genetically modified mice (PPAR&agr;−/−) that mimic the metabolic profile in myocardial hypertrophy. We found that the substrate switch from fatty acid to glucose (3-fold down) and lactate (3-fold up) in PPAR&agr;−/− hearts was sufficient for sustaining normal energy metabolism and contractile function at baseline but depleted the metabolic reserve for supporting high workload. Decreased ATP synthesis (measured by 31P magnetization transfer) during high workload challenge resulted in progressive depletion of high-energy phosphate content and failure to sustain high contractile performance. Interestingly, the metabolic and functional defects in PPAR&agr;−/− hearts could be corrected by overexpressing the insulin-independent glucose transporter GLUT1, which increased the capacity for glucose utilization beyond the intrinsic response to PPAR&agr; deficiency. Conclusions— These findings demonstrate that metabolic remodeling in hearts deficient in PPAR&agr; increases the susceptibility to functional deterioration during hemodynamic overload. Moreover, our results suggest that normalization of myocardial energetics by further enhancing myocardial glucose utilization is an effective strategy for preventing the progression of cardiac dysfunction in hearts with impaired PPAR&agr; activity such as hearts with pathological hypertrophy.
Paliperidone: the evidence of its therapeutic value in schizophrenia

Introduction: Paliperidone, the 9-hydroxy metabolite of risperidone, is a second-generation antipsychotic that was recently approved for the treatment of schizophrenia. It is marketed as an improvement over risperidone, but is likely to be considerably more costly when risperidone is no longer protected by patent. Aims: To review the evidence for the clinical impact of paliperidone in the treatment of patients with schizophrenia, particularly in contrast to risperidone. Evidence review: Paliperidone is primarily metabolized and excreted renally, and thus may be of particular utility for patients with hepatic impairment. There is clear evidence that paliperidone is more efficacious than placebo in reducing the positive and negative symptoms of schizophrenia. In patients with schizophrenia, paliperidone has been shown to stabilize acute psychotic symptoms. There is some evidence that it can prevent relapse in stabilized patients. Studies on the cost effectiveness of paliperidone are needed. Most importantly, there are no trials comparing paliperidone directly with other second-generation antipsychotics. Place in therapy: Until direct efficacy and cost effectiveness comparisons are made with risperidone, it is difficult to justify paliperidone use over risperidone. It will become even harder to justify when risperidone becomes available as a less expensive generic medication.
Compensation of IQ Imbalance and DC Offset for OFDM Transmission over Frequency Selective Channels

In this paper a time-domain method for joint estimation of in-phase and quadrature-phase (IQ) imbalance, direct current (DC) offset and channel response for orthogonal frequency division multiplexing (OFDM) system is proposed. Using the fact that in an OFDM system the block size is usually much larger than the cyclic prefix length, we show that without knowing the channel impulse response, we are able to accurately estimate the IQ mismatch and DC offset, from which the channel response can be obtained. Only one OFDM block is needed for training. Simulation results demonstrate that the performance of the proposed method is very close to the ideal case when IQ mismatch, DC offset and channel response are perfectly known at the receiver.
Guaranteeing the topology of an implicit surface polygonization for interactive modeling

Morse theory shows how the topology of an implicit surface is affected by its function’s critical points, whereas catastrophe theory shows how these critical points behave as the function’s parameters change. Interval analysis ﬁnds the critical points, and they can also be tracked efﬁciently during parameter changes. Changes in the function value at these critical points cause changes in the topology. Techniques for modifying the polygonization to accommodate such changes in topology are given. These techniques are robust enough to guarantee the topology of an implicit surface polygonization, and are efﬁcient enough to maintain this guarantee during interactive modeling. The impact of this work is a topologically-guaranteed polygonization technique, and the ability to directly and accurately manipulate polygonized implicit surfaces in real time.
Neural Network Based Online Simultaneous Policy Update Algorithm for Solving the HJI Equation in Nonlinear $H_{\infty}$ Control

It is well known that the nonlinear H∞ state feedback control problem relies on the solution of the Hamilton-Jacobi-Isaacs (HJI) equation, which is a nonlinear partial differential equation that has proven to be impossible to solve analytically. In this paper, a neural network (NN)-based online simultaneous policy update algorithm (SPUA) is developed to solve the HJI equation, in which knowledge of internal system dynamics is not required. First, we propose an online SPUA which can be viewed as a reinforcement learning technique for two players to learn their optimal actions in an unknown environment. The proposed online SPUA updates control and disturbance policies simultaneously; thus, only one iterative loop is needed. Second, the convergence of the online SPUA is established by proving that it is mathematically equivalent to Newton's method for finding a fixed point in a Banach space. Third, we develop an actor-critic structure for the implementation of the online SPUA, in which only one critic NN is needed for approximating the cost function, and a least-square method is given for estimating the NN weight parameters. Finally, simulation studies are provided to demonstrate the effectiveness of the proposed algorithm.
Southern Hemispheric Westerlies control sedimentary processes of Laguna Azul (south-eastern Patagonia, Argentina)

Multiproxy investigations of lacustrine sediments from Laguna Azul (52 °S) document multi-millennial Holocene influences of Southern Hemispheric Westerlies (SHW) on the hydroclimatic variability of south-eastern Patagonia. During the last 4000 years, this hydroclimatic variability is overprinted by centennial warm/dry periods. A cool/wet period from 11,600 to 10,100 cal. BP is succeeded by an early Holocene dry period (10,100–8300 cal. BP) with a shallow lake, strong anoxia, methanogenesis and high salinity. Between 8300 and 4000 cal. BP the influence of SHW weakened, resulting in a freshwater lake considered to be related to less arid conditions. Since 4000 cal. BP, regional temperature decreased accompanied by re-intensification of SHW reaching full strength since 3000 cal. BP. Centred around 2200, 1000 cal. BP and in the 20th century, Laguna Azul experienced century-long warm/dry spells. Between these dry periods, two pronounced moist periods are suggested to be contemporaneous to the ‘Dark Age Cold Period’ and the ‘Little Ice Age’. Different from millennial SHW variations, centennial fluctuations appear to be synchronous for South America and the Northern Hemisphere. Changes in solar activity, large volcanic eruptions and/or modulations of ocean circulation are potential triggers for this synchronicity.