Miracle-dz/UniFAR-FTUs huggingface dataset:
Velocity change of the Amery Ice Shelf, East Antarctica, during the period 1968-1999

Historic velocity measurements of Antarctica's ice sheet represent vital baseline values that allow ice flow velocity variations to be observed over multidecadal timescales, such as those due to climate change. Using velocity values derived from geodetic quality measurements made in the 1960s and from more recent GPS and remote sensing studies during the 1990s, we examine the variability of ice flow velocities of the northern Amery Ice Shelf, East Antarctica, over the 30-year period, 1968-1999. The historic ice shelf velocities are reexamined using original field notes and the previous data analyses are shown to be erroneous, yielding positional and velocity errors of up to 4 km and 150 m/yr respectively. Once corrected, these historic measurements are shown to be in close (1-5 m/yr) general agreement with GPS-derived velocities from the 1990s at similar geographical locations, providing one of the first precise constraints on multidecadal ice shelf velocity variations on a large Antarctic ice shelf. Comparison of the terrestrial and GPS velocities with spatially dense velocity measurements from remote sensing imagery reveals a systematic bias in the latter of up to ±30 m/yr, mostly due to propagation of unmodeled vertical ice shelf motion due to tides and atmospheric pressure variations. We therefore excluded the remote sensing velocities from further comparison and suggest caution in the interpretation of similarly derived ice shelf velocities. Velocity differences between the GPS and terrestrial surveys were compared at nine geographical locations suggesting a small (∼2.2 m/yr or ∼0.6%), but statistically significant, slowdown of the ice shelf. Copyright 2007 by the American Geophysical Union.
Dendritic magnetite crystals in rapid quenched fine spherules produced by falling experiments through the high temperature furnace with controlled gas flow

Magnetite is a common accessory mineral in various rocks. Crystal shapes and habits of magnetite show diversity depending on crystallization conditions, especially cooling rate. Characteristic dendritic or skeletal magnetite crystals occur in quench rims of effusive rocks. The dendritic magnetite also occur in micrometeorites undergone quick heating and quenching at atmospheric entry. In this study, we constructed a fine particle free fall apparatus in a high temperature furnace to carry out crystallization experiments with controlled rapid heating and quenching. Experiments were carried out in a high-temperature vertical tube furnace with H2, CO2 and Ar mass flow controllers to control oxygen partial pressure and total gas flow rate. At the top of the furnace, a silica glass tube with an orifice with approximately 0.5 mm in diameter was set to keep falling rate of particles. Particles were retrieved in an alumina crucible at the bottom of the furnace tube. Terminal velocity of silicate particles with 100 μm in diameter in the static Ar gas at 1200 °C is approximately 0.18 m/s. Gas ascent rate at 1200 °C is approximately 0.11 m/s in the furnace tube when gas flow rate is approximately 1 l/min at standard condition. The falling velocity of the particles with 100 μm in diameter, therefore, is reduced to approximately 0.07 m/s. When the highest temperature in the furnace tube set to 1520 °C, the falling particles reach 1400 °C within 2 s, keep above 1400 °C more than 1 s, and are quenched within 1 s. For the fine particles with 100 μm in diameter, time scale of thermal equilibrium by radiation can be achieved within 0.1 s. In the experiments with volcanic ash particles, we found quite characteristic dendritic magnetite crystals in rapid-quenched spherules. From particles with high volume fraction of magnetite, we can see quite characteristic texture in which dendritic magnetite cover almost whole surface of the spherule. Magnetite dendrite crystals with particular crystallographic orientation also occur. The rapid quenching experiments for fine particles can be applied to reproduce atmospheric entry heating processes of micrometeorites.
Adaptive sampling with strict energy constraints

With more and more battery-operated devices equiped with sensors, it is becoming increasingly relevant to focus not only on energy efficiency, but also on ensuring that the available energy is not spent before the battery will be recharged. In this thesis a strategy for adaptive sampling is proposed that adapts the sample rate while respecting a predefined limit on the number of samples per discharge period. The proposed sample strategy aims to sample with uniform prediction errors, as opposed to uniform intervals. This signalagnostic strategy is tested upon data from traffic flow, a wireless sensor node, and a position trace obtained with a mobile phone. A reduction in the root mean squared error ranging from 0 to 50 percent compared to uniform sampling was achieved.
McKay ’ s Canonical Graph Labeling Algorithm

The problem of deciding whether two graphs are isomorphic is fundamental in graph theory. Moreover, the flexibility with which other combinatorial objects can be modeled by graphs has meant that efficient programs for deciding whether graphs are isomorphic have also been used to study a variety of other combinatorial structures. Not only is the graph isomorphism problem a very practical one, it is also fascinating from a complexity-theoretic point of view. Graph isomorphism is one of the few problems that are clearly in NP but not known either to be solvable in polynomial time, or to be NPcomplete. Various people have worked to create algorithms for graph isomorphism which are “practical in practice”. One of the most powerful and best known of these algorithms is due to Brendan McKay. It is known that his algorithm has exponential running time on some inputs, but it performs exceptionally well under most circumstances. In this article we aim to provide an introduction to the essential ideas of McKay’s algorithm.
A Comparison of Prognostic Factors and Surgical Results in 1,786 Patients with Localized (Stage I) Melanoma Treated in Alabama, USA, and New South Wales, Australia

Twelve clinical and pathologic parameters were compared in two series of Stage I melanoma patients treated at the University of Alabama in Birmingham, USA (676 patients) and at the University of Sydney in New South Wales, Australia (1,110 patients). Actuarial survival rates were virtually the same at the two institutions over a 25-year follow-up period. The incidence of thin melanomas (<0.76 mm) was also similar at both geographic locations (25% vs. 26%). Other similarities of these two patient populations included the following: 1) tumor thickness (Breslow Microstaging), 2) level of invasion (Clark Microstaging), 3) surgical results, 4) sex distribution, and 5) age distribution. The greatest differences between the two patient populations were their 1) anatomic distribution, 2) growth pattern, and 3) incidence of ulceration. The trunk was the most common site of melanoma, and occurred more frequently among Australian patients (37% vs. 28%). A multifactorial analysis (Cox's regression model) was then performed that included a comparison of the two institutions as a variable (Alabama vs. Australia). The dominant prognostic factors (p < 0.0001) were 1) ulceration, 2) tumor thickness, 3) initial surgical management (wide excision ± node dissection), 4) anatomic location, 5) pathologic stage (I vs. II), and 6) level of invasion. The benefit of elective lymph node dissection was demonstrated in both series for patients with intermediate thickness melanoma (0.76 to 3.99 mm). For melanomas ranging from 0.76 to 1.5 mm in thickness, the benefit of node dissection was primarily in male patients. Survival rates for melanoma at the two institutions were not significantly different in the multifactorial analysis, even after adjusting for all other variables. Thus, the biologic behavior of melanoma in these two different parts of the world was virtually the same, with only minor differences that did not significantly influence survival rates. Long-term follow-up exceeding eight to ten years after surgery is critical in the interpretation of these prognostic factors and the surgical results.
Characterizing Episodic Memory Retrieval: Electrophysiological Evidence for Diminished Familiarity following Unitization

Episodic memory relies on both recollection and familiarity; why these processes are differentially engaged during retrieval remains unclear. Traditionally, recollection has been considered necessary for tasks requiring associative retrieval, whereas familiarity supports recognition of items. Recently, however, familiarity has been shown to contribute to associative recognition if stimuli are “unitized” at encoding (a single representation is created from multiple elements)—the “benefit” of unitization. Here, we ask if there is also a “cost” of unitization; are the elements of unitized representations less accessible via familiarity? We manipulated unitization during encoding and used ERPs to index familiarity and recollection at retrieval. The data revealed a selective reduction in the neural correlate of familiarity for individual words originally encoded in unitized compared with nonunitized word pairs. This finding reveals a measurable cost of unitization, suggesting that the nature of to-be-remembered stimuli is critical in determining whether familiarity contributes to episodic memory.
Estimating generalized soil-water characteristics from texture

Soil-water potential and hydraulic conductivity relationships with soil-water content are needed for many plant and soil-water studies. Measurement of these relationships is costly, difficult, and often impractical. For many purposes, general estimates based on more readily available information such as soil texture are sufficient. Recent studies have developed statistical correlations between soil texture and selected soil potentials using a large data base, and also between selected soil textures and hydraulic conductivity. The objective of this study was to extend these results by providing mathematical equations for continuous estimates over broad ranges of soil texture, water potentials, and hydraulic conductivities. Results from the recent statistical analyses were used to calculate water potentials for a wide range of soil textures, then these were fit by multivariate analyses to provide continuous potential estimates for all inclusive textures. Similarly, equations were developed for unsaturated hydraulic conductivities for all inclusive textures. While the developed equations only represent a statistical estimate and only the textural influence, they provide quite useful estimates for many usual soil-water cases. The equations provide excellent computational efficiency for model applications and the textures can be used as calibration parameters where field or laboratory soil water characteristic data are available. Predicted values were successfully compared with several independent measurements of soil-water potential.
Versatile building blocks for multirate processing of bandpass signals

In this paper we develop a special down-converting bandpass decimator structure which can be used for reducing the sampling rate by a factor two without causing any disturbing aliasing effects for a bandpass signal located originally around quarter of the sampling rate (π/2). Based on this special bandpass filter design and usual halfband lowpass and highpass decimation filters, an efficient stepwise decimation and mixing approach is developed for filtering out and down-converting a narrowband signal located in frequency domain anywhere within a wideband digitized signal. This kind of down-conversion and decimation approach finds applications in communications receivers where the role of DSP-based solutions is becoming more and more important.
Harnessing naturally occurring data to measure the response of spending to income

Balancing your incomings and outgoings Economic theory predicts that when someone receives money should have little effect on their spending patterns. Gelman et al. constructed a data set of 60 million transactions made by 75,000 people to test this theory. People do seem to go on a mini–spending spree after they get their paychecks or pensions. However, closer inspection reveals that that's mostly explained by the convenience of linking regular payments, such as rent and utilities, to regular income. Unsurprisingly, cash-strapped people are more likely to increase their spending in response to receiving income. Science, this issue p. 212 How do theoretical predictions of individual fiscal behaviors match up against real-world, real-time data? This paper presents a new data infrastructure for measuring economic activity. The infrastructure records transactions and account balances, yielding measurements with scope and accuracy that have little precedent in economics. The data are drawn from a diverse population that overrepresents males and younger adults but contains large numbers of underrepresented groups. The data infrastructure permits evaluation of a benchmark theory in economics that predicts that individuals should use a combination of cash management, saving, and borrowing to make the timing of income irrelevant for the timing of spending. As in previous studies and in contrast to the predictions of the theory, there is a response of spending to the arrival of anticipated income. The data also show, however, that this apparent excess sensitivity of spending results largely from the coincident timing of regular income and regular spending. The remaining excess sensitivity is concentrated among individuals with less liquidity.
Aging Affects Hemispheric Asymmetry in the Neural Representation of Speech Sounds

Hemispheric asymmetries in the processing of elemental speech sounds appear to be critical for normal speech perception. This study investigated the effects of age on hemispheric asymmetry observed in the neurophysiological responses to speech stimuli in three groups of normal hearing, right-handed subjects: children (ages, 8–11 years), young adults (ages, 20–25 years), and older adults (ages > 55 years). Peak-to-peak response amplitudes of the auditory cortical P1–N1 complex obtained over right and left temporal lobes were examined to determine the degree of left/right asymmetry in the neurophysiological responses elicited by synthetic speech syllables in each of the three subject groups. In addition, mismatch negativity (MMN) responses, which are elicited by acoustic change, were obtained. Whereas children and young adults demonstrated larger P1–N1-evoked response amplitudes over the left temporal lobe than over the right, responses from elderly subjects were symmetrical. In contrast, MMN responses, which reflect an echoic memory process, were symmetrical in all subject groups. The differences observed in the neurophysiological responses were accompanied by a finding of significantly poorer ability to discriminate speech syllables involving rapid spectrotemporal changes in the older adult group. This study demonstrates a biological, age-related change in the neural representation of basic speech sounds and suggests one possible underlying mechanism for the speech perception difficulties exhibited by aging adults. Furthermore, results of this study support previous findings suggesting a dissociation between neural mechanisms underlying those processes that reflect the basic representation of sound structure and those that represent auditory echoic memory and stimulus change.
Gral: An Extensible Relational Database System for Geometric Applications

We describe the architecture of a relational database system that is extensible by user-defined data types and operations, including relation operations. The central concept is to use languages based on many-sorted algebra to represent queries as well as query execution plans. This leads to a simple and clean extensible system architecture, eases the task of an application developer by providing a uniform framework, and also simplifies rule-based optimization. As a case study the extensions needed for a geometric database system are considered.
Classification Algorithm Based on Weighted SVMs and Locally Tuning kNN

This paper presents a new classification algorithm consisting of a Weighted SVMs approach (WSVM) to identify data class, and a locally Tuning kNN (TkNN) to address the rejected case. Basic SVM of WSVM is equipped with weights derived from SVM output distribution to demonstrate decision confidence. These weights influence label assignment. TkNN handles the difficult cases rejected by WSVM. It works in the neighborhood that is developed by a locally informative metric. SVM decision interfaces helps to define the new metric. Hyper parameters of basic SVM are learned context dependently. We present experimental evidence of classification performance improved by our schema over state of the arts.
Visually-Grounded Bayesian Word Learning

Learning the meaning of a novel noun from a few labeled objects is one of the simplest aspects of learning a language, but approximating human performance on this task is still a significant challenge for current machine learning systems. Current methods typically fail to find the appropriate level of generalization in a concept hierarchy for a given visual stimulus. Recent work in cognitive science on Bayesian models of word learning partially addresses this challenge, but it assumes that the labels of objects are given (hence no object recognition) and it has only been evaluated in small domains. We present a system for learning nouns directly from images, using probabilistic predictions generated by visual classifiers as the input to Bayesian word learning, and compare this system to human performance in an automated, large-scale experiment. The system captures a significant proportion of the variance in human responses. Combining the uncertain outputs of the visual classifiers with the ability to identify an appropriate level of abstraction that comes from Bayesian word learning allows the system to outperform alternatives that either cannot deal with visual stimuli or use a more conventional computer vision approach.
On the Estimation of Lagrangian Diffusivity: Influence of Nonstationary Mean Flow

Eddy mean flow decomposition is crucial to the estimation of Lagrangian diffusivity based on drifter data. Previous studies have shown that inhomogeneous mean flow induces shear dispersion that increases the estimated diffusivity with time. In the present study, the influences of nonstationary mean flows on the estimation of Lagrangian diffusivity, especially the asymptotic behavior, are investigated using a first-order stochastic model, with both idealized and satellite-based oceanic mean flows. Results from both experiments show that, in addition to inhomogeneity, nonstationarity of mean flows that contain slowly varying signals, such as a seasonal cycle, also cause large biases in the estimates of diffusivity within a time lag of 2 months if a traditional binning method is used. Therefore, when assessing Lagrangian diffusivity over regions where a seasonal cycle is significant [e.g., the Indian Ocean (IO) dominated by monsoon winds], inhomogeneity and nonstationarity of the mean flow should be simultaneously taken into account in eddy mean flow decomposition. A temporally and spatially continuous fit through the Gauss Markov (GM) estimator turns out to be very efficient in isolating the effects of inhomogeneity and nonstationarity of the mean flow, resulting in estimates that are closest to the true diffusivity, especially in regions where strong seasonal cycles exist such as the eastern coast of Somalia and the equatorial IO.
A Tableau Calculus for Temporal Description Logic: the Expanding Domain Case

In this paper we present a tableau calculus for a temporal extension of the description logic ALC, called T L ALC. This logic is based on the temporal language with`Until' interpreted over the natural numbers with expanding ALC-domains. The tableau calculus forms an elaborated combination of Wolper's tableau calculus for propositional linear temporal logic, the standard tableau-algorithm for ALC, and the method of quasi-models as it has been introduced by Wolter and Zakharyaschev. Based on those three ingredients the paper provides a new method of how tableau-based decision procedures can be constructed for many-dimensional logics which lack the nite model property. The method can be applied to deal with other temporalized formalisms as well.
Visual data association in narrow-bandwidth networks

The performance of any cooperative task that involves two or more robots will be determined by their capacity to recognize common information of the environment. Vision sensors are very effective for this particular goal, but the cost of transmitting the visual information represents a real issue, even more if communication must be performed in narrow bandwidth networks and/or over a multi-hop path. Visual vocabularies provide a dimensionality reduction that has been effectively used in computer vision to reduce the computational load of performing searches in large volumes of data. In this paper we propose to exploit the same technique to decrease the volume of information that is exchanged in the network. This way, robots do not need to send the full descriptors associated to the features they observe, but only the word indices of the corresponding features in the vocabulary. Experiments with a wide variety of vocabularies are used to evaluate the quality of the association given by the algorithm. Finally, real experiments in a wireless network with a limited bandwidth are reported, showing the advantages of the proposed method compared to the communication of full images or feature descriptors.
Ability of Remnant Riparian Forests, With and Without Grass Filters, to Buffer Concentrated Surface Runoff 1

Knight, Kris W. , Richard C. Schultz, Cathy M. Mabry, and Thomas M. Isenhart, 2010. Ability of Remnant Riparian Forests, With and Without Grass Filters, to Buffer Concentrated Surface Runoff. Journal of the American Water Resources Association (JAWRA) 46(2):311‐322. DOI: 10.1111/j.1752‐1688.2010. 00422.x
Insight into cordycepin biosynthesis of Cordyceps militaris: Comparison between a liquid surface culture and a submerged culture through transcriptomic analysis

Cordyceps militaris produces cordycepin, which is known to be a bioactive compound. Currently, cordycepin hyperproduction of C. militaris was carried out in a liquid surface culture because of its low productivity in a submerged culture, however the reason was not known. In this study, 4.92 g/L of cordycepin was produced at the 15th day of C. militaris NBRC 103752 liquid surface culture, but only 1 mg/L was produced in the submerged culture. RNA-Seq was used to clarify the gene expression profiles of the cordycepin biosynthetic pathways of the submerged culture and the liquid surface culture. From this analysis, 1036 genes were shown to be upregulated and 557 genes were downregulated in the liquid surface culture compared with the submerged culture. Specifically, adenylosuccinate synthetase and phosphoribosylaminoimidazole-succinocarboxamide (SAICAR) synthase in purine nucleotide metabolism were significantly upregulated in the liquid surface culture. Thick mycelia formation in the liquid surface culture was found to induce the expression of hypoxia-related genes (GABA shunt, glutamate synthetase precursor, and succinate-semialdehyde dehydrogenase). Cytochrome P450 oxidoreductases containing heme were also found to be significantly enriched, suggesting that a hypoxic condition might be created in the liquid surface culture. These results suggest that hypoxic conditions are more suitable for cordycepin production in the liquid surface culture compared with the submerged culture. Our analysis paves the way for unraveling the cordycepin biosynthesis pathway and for improving cordycepin production in C. militaris.