Miracle-dz/UniFAR-FTUs huggingface dataset:
N 96-14907 Self-Attitude Awareness Training : An Aid To Effective Performance In Microgravity and Virtual Environments ? '

This paper describes ongoing development of training procedures to enhance selfattitude awareness in astronaut trainees. The procedures are based on observations regarding self-attitude (perceived self-orientation and self-motion) reported by astronauts. Self-attitude awareness training is implemented on a personal computer system and consists of lesson stacks programmed using Hypertalk with Macromind Director movie imports. Training evaluation will be accomplished by an active search task using the virtual Spacelab environment produced by the Device for Orientation and Motion Environments Preflight Adaptation Trainer (DOME-PAT) as well as by assessment of astronauts' performance and sense of well-being during orbital flight. The general purpose of self-attitude awareness training is to use as efficiently as possible tine limited DOME-PAT training time available to astronauts prior to a space mission. We suggest that similar training procedures may enhance the performance of virtual environment operators.
Potential of digital beamforming in bi- and multistatic SAR

Digital beamforming on receive is an innovative concept to gather additional information about the direction of scattered radar echoes during the acquisition of synthetic aperture radar (SAR) images. This additional information can be used to suppress range and azimuth ambiguities, to improve geometric and/or radiometric resolution, and to increase the unambiguous swath width. It is shown that this technique is especially promising in combination with bistatic SAR constellations, where digital beamforming on the receive will allow for more compact antenna structures. Furthermore, an extension of digital beamforming to multistatic SAR formations will enable a reduced antenna aperture for each receiver, thereby allowing cost-effective and powerful SAR missions with wide swath coverage in the future.
BEHAVIOR OF THE MAIN WHARF IN SAN PEDRITO PORT IN MANZANILLO, MEXICO

The earthquake of 9 October, 1995 (Ms=7.3, Mw=8.0) in the Mexican port of Manzanillo damaged a Container Terminal at the San Pedrito harbor. This is a descriptive paper which reviews succinctly the damages observed in Manzanillo during this earthquake and then presents a discussion of the behavior of the docking facilities at the Container Terminal. The authors conclude that constructive methods influenced detrimentally the performance of the piles in that wharf, that more research is required to specify design spectra for docks in Manzanillo and that further studies must also be undertaken to account properly for pile-soil interaction effects in these structures.
Identification and characterization of candidate Rlm 4 blackleg resistance genes in Brassica napus using next-generation sequencing

next generation sequencing. Summary A thorough understanding of the relationships between plants and pathogens is essential if we are to continue to meet the agricultural needs of the world’s growing population. The identification of genes underlying important quantitative trait loci is extremely challenging in complex genomes such as Brassica napus (canola, oilseed rape or rapeseed). However, recent advances in next-generation sequencing (NGS) enable much quicker identification of candidate genes for traits of interest. Here, we demonstrate this with the identification of candidate disease resistance genes from B. napus for its most devastating fungal pathogen, Leptosphaeria maculans (blackleg fungus). These two species are locked in an evolutionary arms race whereby a gene-for-gene interaction confers either resistance or susceptibility in the plant depending on the genotype of the plant and pathogen. Preliminary analysis of the complete genome sequence of Brassica rapa, the diploid progenitor of B. napus, identified numerous candidate genes with disease resistance characteristics, several of which were clustered around a region syntenic with a major locus (Rlm4) for blackleg resistance on A7 of B. napus. Molecular analyses of the candidate genes using B. napus NGS data are presented, and the difficulties associated with identifying functional gene copies within the highly duplicated Brassica genome are discussed.
Muscle Contraction Duration and Fibre Recruitment Influence Blood Flow and VO 2 Independent of Contractile Work during Steady-State Exercise in Humans

We tested the hypothesis that, among conditions of matched contractile work, shorter contraction durations and greater muscle fibre recruitment result in augmented skeletal muscle blood flow and oxygen consumption (V̇O2) during steady-state exercise in humans. To do so, we measured forearm blood flow (FBF; Doppler ultrasound) during 4 minutes of rhythmic handgrip exercise in 24 healthy young adults and calculated forearm V̇O2 via blood samples obtained from a catheter placed in retrograde fashion into a deep vein draining the forearm muscle. In Protocol 1 (n = 11), subjects performed rhythmic isometric handgrip exercise at mild and moderate intensities under conditions in which tension time index (TTI; isometric analog of work) was held constant but contraction duration was manipulated. In this protocol, shorter contraction durations led to greater FBF (184 ± 25 vs. 164 ± 25 ml·min-1) and V ̇O2 (23 ± 3 vs. 17 ± 2 ml·min-1; both P <0.05) among mild workloads, whereas this was not the case for moderate intensity exercise. In Protocol 2 (n = 13), subjects performed rhythmic dynamic handgrip exercise at mild and moderate intensities under conditions of matched total work, but muscle fibre recruitment was manipulated. In this protocol, greater muscle fibre recruitment led to significantly greater FBF (152 ± 15 vs. 127 ±13 ml·min-1) and V ̇O2 (20 ± 2 vs. 17 ± 2 ml·min-1; both P<0.05) at mild workloads and there was a trend for similar responses at the moderate intensity but this was not statistically significant. In both protocols, the ratio of the change in FBF to change in V̇O2 was similar across all exercise intensities and manipulations, and the strongest correlation among all variables was between V̇O2 and blood flow. Our collective data indicate that, among matched workloads, shorter contraction duration and greater muscle fibre recruitment augment FBF and V̇O2 during mild intensity forearm exercise, and that muscle blood flow is more closely related to metabolic cost (V̇O2) rather than contractile work per se during steady-state exercise in humans.
A 1.9 GHz low-voltage silicon bipolar receiver front-end for wireless personal communications systems

A 1.9 GHz wireless receiver front-end (low-noise preamplifier and mixer) is described that incorporates monolithic microstrip transformers for significant improvements in performance compared to silicon broadband designs. Reactive feedback and coupling elements are used in place of resistors to lower the front-end noise figure through the reduction of resistor thermal noise, and this also allows both circuits to operate at supply voltages below 2 V. These circuits have been fabricated in a production 0.8 /spl mu/m BiCMOS process that has a peak npn transistor transit frequency (f/sub T/) of 11 GHz. At a supply voltage of 1.9 V, the measured mixer input third-order intercept point is +2.3 dBm with a 10.9 dB single-sideband noise figure. Power dissipated by the mixer is less than 5 mW. The low-noise amplifier input intercept is -3 dBm with a 2.8 dB noise figure and 9.5 dB gain. Power dissipation of the preamplifier is less than 4 mW, again from a 1.9 V supply.
Real-time implementation of a low delay low bit rate vocoder with a single ADAP-21020

This paper presents a low delay vocoder operating at 4.8 kb/s with a modified code excited linear prediction (CELP) algorithm. The total speech coding delay is only 2.5 msec. The coder has also been real-time implemented using a single ADSP-21020 chip and provided a good output speech quality. In this low delay vocoder, backward LPC analysis is used to obtain the short term filter coefficients and a new approach based on a "dual-decision" scheme is adopted to calculate the long term prediction (LTP) coefficients. At the excitation part, a new excited model is exploited which contains a sinusoidal codebook and a stochastic codebook to excite the whole speech system. The synthesized speech of this vocoder has a comparable quality to that of the conventional CELP coder, i.e., the FS-1016, while having a delay constraint more than an order of magnitude smaller than that of the conventional coder.
Trajectory tracking of underactuated underwater vehicles

This paper deals with a control strategies for underactuated underwater vehicles whose target is the tracking of a space trajectory. A cascade control strategy is employed which brings to a control law consisting of: 1) a kinematic control law, derived from the vehicle kinematic model, which forces this model to track the reference trajectory; and 2) a dynamic control law which forces the system to track the reference signals given by the kinematic control law. Conditions for asymptotic tracking of the trajectory are given with reference to the standard dynamical model of the above vehicle. An observer of the marine current is also added in order to process the control law. Simulation tests illustrate the proposed approach.
It's new, but is it good? How generalization and uncertainty guide the exploration of novel options.

How do people decide whether to try out novel options as opposed to tried-and-tested ones? We argue that they infer a novel option's reward from contextual information learned from functional relations and take uncertainty into account when making a decision. We propose a Bayesian optimization model to describe their learning and decision making. This model relies on similarity-based learning of functional relationships between features and rewards, and a choice rule that balances exploration and exploitation by combining predicted rewards and the uncertainty of these predictions. Our model makes 2 main predictions. First, decision makers who learn functional relationships will generalize based on the learned reward function, choosing novel options only if their predicted reward is high. Second, they will take uncertainty about the function into account, and prefer novel options that can reduce this uncertainty. We test these predictions in 3 preregistered experiments in which we examine participants' preferences for novel options using a feature-based multiarmed bandit task in which rewards are a noisy function of observable features. Our results reveal strong evidence for functional exploration and moderate evidence for uncertainty-guided exploration. However, whether or not participants chose a novel option also depended on their attention, as well as reflecting on the value of the options. These results advance our understanding of people's reactions in the face of novelty. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
ICONE19-43067 Application of data mining in three-dimensional space time reactor model

A high-fidelity three-dimensional space time nodal method has been developed to simulate the dynamics of the reactor core for real time simulation. This three-dimensional reactor core mathematical model can be composed of six sub-models, neutron kinetics model, cay heat model, fuel conduction model, thermal hydraulics model, lower plenum model, and core flow distribution model. During simulation of each sub-model some operation data will be produced and lots of valuable, important information reflecting the reactor core operation status could be hidden in, so how to discovery these information becomes the primary mission people concern. Under this background, data mining (DM) is just created and developed to solve this problem, no matter what engineering aspects or business fields. Generally speaking, data mining is a process of finding some useful and interested information from huge data pool. Support Vector Machine (SVM) is a new technique of data mining appeared in recent years, and SVR is a transformed method of SVM which is applied in regression cases. This paper presents only two significant sub-models of three-dimensional reactor core mathematical model, the nodal space time neutron kinetics model and the thermal hydraulics model, based on which the neutron flux and enthalpy distributions of the core are obtained by solving the three-dimensional nodal space time kinetics equations and energy equations for both single and two-phase flows respectively.Moreover, it describes that the three-dimensional reactor core model can also be used to calculate and determine the reactivity effects of the moderator temperature, boron concentration, fuel temperature, coolant void, xenon worth, samarium worth, control element positions (CEAs) and core burnup status. Besides these, the main mathematic theory of SVR is introduced briefly next, on the basis of which SVR is applied to dealing with the data generated by two sample calculation, rod ejection transient and axial flux offset. Comparing with the traditional data analysis method, the main character of SVR is not enforcing a priori information or judgment before analysis begins, but obtaining the fitting result from inner relationship of data completely, which represents the main principle of data mining, letting the data speak themselves, and the result is more accurate and believable than traditional methods.
The dynamics of staphylococcus epidermis biofilm formaTion in relaTion To nuTriTion , TemperaTure , and Time

The ability to form biofilm is one of the most important virulence factors occurring in microbes. The biofilm-forming bacteria are difficult to eradicate with antibiotics and often cause chronic infections. The aim of this study was to correlate the dynamics of biofilm formation with nutrition and temperature conditions during the cultivation in biofilm-positive Staphylococcus epidermidis isolates. The cultivation was performed on standard microtitre plates and the wells were examined for the production of biofilm every 1 hr up to 48 hrs. All the tested strains showed better growth of the biofilm at a temperature of 37 °C in a nutrient-richer environment. The first signs of bacterial adhesion were visible after 2–4 hours of cultivation, the first homogenous but a very thin layer was visible after 5 hours; after 7 hours the biofilm layer was circa three times thicker. After 10 hours the biofilm layer seemed to be mature – the changes in thickness were not so evident after this time. After a cultivation longer than 34–42 hours, parts of the biofilm layer started to detach, and consequently the biofilm became non-homogeneous. For biofilm studies, a biofilm cultivation for 12–16 hours should be sufficient.
Design and implementation of a low cost computer vision system for sorting of closed-shell pistachio nuts

Iran is one of the most important producers and exporters of pistachio nuts in the world. Certainly, the quality of pistachio is very important for customers. Sorting of pistachio nuts is a post-harvesting process which is currently performed using a mechanical apparatus called “pin picker”. Due to the possibility of kernel damage by the pin picker, mechanical methods of closed-shell pistachio removal are gradually being replaced by other appropriate systems. Low cost systems for post-harvesting processes such as computer vision-based sorting systems are experiencing rapid growth. In this paper, a low cost intelligent system is implemented for pistachio sorting using computer vision. The system uses a combination of two flat mirrors and one low cost camera to obtain suitable 3 dimensional images from pistachios which are processed to detect closed-shell nuts. The experimental results for the three varieties of pistachios nuts shows 92.7 and 86.7% average removal accuracy, respectively for open and closed shell pistachio nuts. Key words: Pistachio, closed shell, sorting, computer vision.
A Kernel Canonical Correlation Analysis Based Idle-State Detection Method for SSVEP-Based Brain-Computer Interfaces

In this paper, we propose a kernel canonical correlation analysis (KCCA) based idle-state detection method for asynchronous steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) systems. KCCA method can offer a flexible nonlinear solution to adequately extract nonlinear features of multi-electrode electroencephalogram signals. Based on this method, an ensemble KCCA coefficients feature model is proposed by weighting effectively multi-harmonic information and afterwards a threshold classification strategy for idle-state detection is presented. The weights of the model and optimal threshold are trained by the presented parameters learning scheme. Using our method, offline analysis was performed on 10 subjects with 8 fixed common electrodes. The results showed that the idle state could be detected with 95.9% average accuracy when SSVEP could be determined with 93.8% average accuracy. Further, the analysis verified the effectiveness and significant superiority of our method over other widely used ones.
CRARP 2503 RELATIONSHIPS OF VARIOUS SOUNDING PARAMETERS DURING HAIL EVENTS IN THE CHICAGO COUNTY WARNING AREA

Between 1990 and 1999, there were nine days per year, on average, with reports of hail (0.75 in diameter or greater) within the County Warning Area (CWA) of the National Weather Service’s Chicago office. When making warning decisions it is critical that forecasters are able to recognize pre-storm environments that favor hail production. One of the more common variables forecasters tend to use when diagnosing pre-storm environment is the height of the wet bulb zero. In general, when the height of the wet bulb zero is high (greater than 12,000 ft, for instance), the threat of severe hail is significantly lower as the hail will have more time to melt as it descends toward the surface. Previous studies have found that more than 90% of reported hail events in the Midwest occur when the wet bulb zero height is between 5,000 and 12,000 ft (Miller 1972). The initial intent of this study was to develop a local climatology of wet bulb zero heights during severe hail occurrences in the NWS Chicago’s CWA. The results led to more questions than answers. With more than 40% of the severe hail events in the CWA having occurred in environments with wet bulb zero heights above 12,000 ft, it appears that wet bulb zero heights are a poor indicator, at best, for anticipating hail producing thunderstorms. Given the inconclusive nature of wet bulb zero heights as a predictor of hail, other sounding parameters were examined in an attempt to locate other variables that may be more useful than wet bulb zero in assessing pre storm environment and the threat of severe hail. Parameters such as environmental freezing level, lapse rates, and 500mb wind speed were created to look for possible connections with hail events. The results in this study were very much in line with what Edwards and Thompson (1998) found on a national basis, that is, singular parameters tend to be poor predictors of severe hail.
Medical Image Segmentation using local classifiers Atlas Supervisors :

The principle of atlas-based segmentation is to segment an image using the registration to another image with known segmentation. This tool that has many applications in clinical studies. It can be used to measure the size or the atrophy of specific anatomical structures (hippocampus, .), it also allows to identify the structures for radiotherapy treatment planning or for measuring physiological parameters (fraction anisotropy, T1, T2, . bone density) in specific structures. The atlas approach has been successfully used to segment a wide variety of organs, on different species and different modalities.
Optimal Persuasion in First-price Auctions with Stochastic Entry ∗

In this paper, we adopt a Bayesian persuasion approach to study the seller’s optimal policy for disclosing the actual number of bidders in first-price auctions with stochastic entry. We assume that the bidders’preference exhibits constant absolute risk aversion or risk loving. After entry, a participating bidder forms own posterior belief upon the public information released by the seller and his own entry status. We find that when bidders are risk averse (resp. risk loving), the revenue-maximizing policy is to fully conceal (resp. fully disclose) the actual number of participating bidders. When bidders are risk neutral, the induced expected revenue is invariant to the disclosure policy. We further show that the ex ante utility of each potential bidder does not depend on the disclosure policy. The seller-optimal policy is thus Pareto dominant. Our analytical procedure applies to alternative first-price and all-pay auction environments in which bidders are risk neutral and their disutility of payment is nonlinear, and similar results are shown to hold for the alternative auction environments. JEL Classification Numbers: C72; D72; D82.
The Impact of Autocorrelation on Queuing Systems

The performance of single-server queues with independent interarrival intervals and service demands is well understood, and often analytically tractable. In particular, the M/M/1 queue has been thoroughly studied, due to its analytical tractability. Little is known, though, when autocorrelation is introduced into interarrival times or service demands, resulting in loss of analytical tractability. Even the simple case of an M/M/1 queue with autocorrelations does not appear to be well understood. Such autocorrelations do, in fact, abound in real-life systems, and worse, simplifying independence assumptions can lead to very poor estimates of performance measures. This paper reports the results of a simulation study of the impact of autocorrelation on performance in an FIFO queue. The study used two computer methods for generating autocorrelated random sequences, with different autocorrelation characteristics. The simulation results show that the injection of autocorrelation into interarrival times, and to a lesser extent into service demands, can have a dramatic impact on performance measures. From a performance viewpoint, these effects are generally deleterious, and their magnitude depends on the method used to generate the autocorrelated process. The paper discusses these empirical results and makes some recommendations to practitioners of performance analysis of queuing systems.
Modeling agent-based framework for the automation of sla management lifecycle

Abslmer-In this paper an agent-based framework for the automation of Scrvice Level Agrrement (SLA) management lifecycle i s presented. SLAs are thr cornerstone of this fvamcnork, used to specify various Quality of Service (QoS) rrquiremcnts. Thc multi-agent system (Mas) for QaS management specified by M E S S A G E (hlethodology for Engineering Systems of Software ,\gents) i s used to capturc the market relationships between stakeholders involvcd in the dynamic creation and delivery o f end-user services with QoS guarantees according to the business model defincd in TIN,\ (l'elerommuniration Information Networking Architecture). Ily using D A h I L + O I L (DARPA Agent M a r k u p Lnnguagc and Ontology Inlermre Layer) ontology language, a descriptiun language sufficiently expressive and ncxihle to be used not only in advertisements, but also in matchmaking qucries, negotiation proposals and agrecments i s introduced and analyard. ' Ihc operations which have to be carried out on this dcseription language in order to support autamatrd S L A manngemrnt ai-e also identilied.