Miracle-dz/UniFAR-FTUs huggingface dataset:
Safety of advanced airborne self separation under very high en-route traffic demand

Since the "invention" of free flight, an outstanding question is how much traffic demand can safely be accommodated by airborne self separation. In order to answer this question, within the iFly project an advanced airborne self separation concept of operations (ConOps) has been developed. This paper shows the results of an assessment of this ConOps on safety risk under very high en-route traffic demand. The accident risk assessment is conducted using advanced techniques in agent based modelling and rare event Monte Carlo simulation. The results obtained show which en-route traffic demand can safely be accommodated by advanced airborne self separation.
Conventional and new generation models of microstructure evolution during hot forming of steels

The objective of the paper is discussion of various methods of modelling microstructure evolution during hot forming of steels. Commonly used conventional models based on closed form equations are compared with novel approaches based on artificial neural networks (ANN) and on multiscale models. Predictive capabilities of various models are discussed. Basic principles of the ANN and multiscale models developed by the Authors, as well as results regarding digital representation of materials and modelling of recrystallization, are described in the paper. Comparison of numerical results with the experiment is presented.
An Automaton Approach for Waiting Times in DNA Evolution

In a recent article, Behrens and Vingron (J. Comput. Biol. 17/12, 2010) compute waiting times for k-mers to appear during DNA evolution under the assumption that the considered k-mers do not occur in the initial DNA sequence, an issue arising when studying the evolution of regulatory DNA sequences with regard to transcription factor (TF) binding site emergence. The mathematical analysis underlying their computation assumes that occurrences of words under interest do not overlap. We relax here this assumption by use of an automata approach. In an alphabet of size 4 like the DNA alphabet, most words have no or a low autocorrelation; therefore, globally, our results confirm those of Behrens and Vingron. The outcome is quite different when considering highly autocorrelated k-mers; in this case, the autocorrelation pushes down the probability of occurrence of these k-mers at generation 1 and, consequently, increases the waiting time for apparition of these k-mers up to 40%. An analysis of existing TF binding sites unveils a significant proportion of k-mers exhibiting autocorrelation. Thus, our computations based on automata greatly improve the accuracy of predicting waiting times for the emergence of TF binding sites to appear during DNA evolution. We do the computation in the Bernoulli or M0 model; computations in the M1 model, a Markov model of order 1, are more costly in terms of time and memory but should produce similar results. While Behrens and Vingron considered specifically promoters of length 1000, we extend the results to promoters of any size; we exhibit the property that the probability that a k-mer occurs at generation time 1 while being absent at time 0 behaves linearly with respect to the length of the promoter, which induces a hyperbolic behaviour of the waiting time of any k-mer with respect to the length of the promoter. The C code is available at www.lipn. univ-paris13.fr/∼nicodeme/ .
Exploring denitrifying communities in the environment

Denitrifiers are aerobically respiring bacteria that under anoxic conditions have the ability to switch to anaerobic respiration, so that nitrate and nitrite are stepwise reduced to nitric oxide, nitrous oxide and dinitrogen. Denitrifiers are a very diverse functional group with members from almost all phylogenetic bacterial groups. One aim of this thesis was to re-evaluate published primers targeting the functional genes, nirS, nirK and nosZ, encoding different enzymes in the denitrification pathway. New primer combinations for nirS and nosZ were designed, whereas the existing primers for nirK still seemed satisfactory. It was possible to PCR-amplify nirS genotypes from soil samples using the new nirS primer pair. In addition, denaturing gradient gel electrophoresis was introduced as a fingerprinting method for nirK- and nosZ-denitrifiers. The methods developed in this initial project were then used to study denitrifying communities in two environments where denitrification is especially important from a human perspective. In the first, methanol and ethanol were added to a wastewater treatment plant with an activated sludge process to increase the denitrification rate. As a result of the additions of external carbon sources the denitrifying communities altered their metabolic function, and specific nirS- and nirK-denitrifiers developed. In the second project, the nirK-denitrifiers were used as a model community to investigate the toxicity of the heavy metal silver to soil denitrifiers. The use of silver is increasing because of its well-known antimicrobial effects, and this may lead to increased environmental contamination. The addition of silver reduced activity and number of denitrifiers, whereas their diversity increased. Because of this demonstrated sensitivity, it is proposed that denitrifiers are suitable indicator organisms for environmental pollution. In conclusion, this thesis shows that molecular methods show great potential for investigating diversity of denitrifiers in various environments, much of which is yet to be discovered. However, in order to fully understand the ecology of denitrifiers, methods targeting the active organisms must be developed, and more denitrifiers must be isolated and characterised.
Quaternary fault system in the Tularosa and Hueco Basins, southern New Mexico and west Texas

Every fall since 1950, the New Mexico Geological Society (NMGS) has held an annual Fall Field Conference that explores some region of New Mexico (or surrounding states). Always well attended, these conferences provide a guidebook to participants. Besides detailed road logs, the guidebooks contain many well written, edited, and peer-reviewed geoscience papers. These books have set the national standard for geologic guidebooks and are an essential geologic reference for anyone working in or around New Mexico.
L1 and L2 role assignment in L3 learning. Is there a pattern?

ABSTRACT This study investigates lexical transfer in four German learners’ oral production of L3 Swedish. They have already learned English as an L2. The point of departure is Williams and Hammarberg’s [1998. Language switches in L3 production: implications for a polyglot speaking model. Applied Linguistics, 19, 295–333] case study in which Swedish was also the L3, but the learner had English as an L1 and German as an L2. Williams and Hammarberg convincingly showed that the background languages played different roles in L3 oral production: L1 English had an instrumental role, while L2 German was assigned a supplier role. The determining factor for the assignment of supplier role was L2 status and of instrumental role common access and established practice. In the present study the model is tested on the same involved languages; but English is the L2 and German the L1. The model would predict that English L2 will be used in both the supplier and the instrumental role. However, the results indicate that this is not the case. Possible explanations are discussed.
Explicit simulation of aerosol physics in a cloud-resolving model

The role of convection in introducing aerosols and promoting the formation of new particles to the upper troposphere has been examined using a cloud-resolving model coupled with an interactive explicit aerosol module. A baseline simulation suggests good agreement in the upper troposphere between modeled and observed results including concentrations of aerosols in different size ranges, mole fractions of key chemical species, and concentrations of ice particles. In addition, a set of 34 sensitivity simulations has been carried out to investigate the sensitivity of modeled results to the treatment of various aerosol physical and chemical processes in the model. The size distribution of aerosols is proved to be an important factor in determining the aerosols' fate within the convective cloud. Nucleation mode aerosols (0 2 SO 4 . Accumulation mode aerosols (d>? 31.0 nm) are almost completely removed by nucleation (activation of cloud droplets) and impact scavenging. However, a substantial part (up to 10% of the boundary layer concentration) of the Aitken mode aerosol population (5.84 nm<? d<? 31.0 nm) reaches the top of the cloud and the free troposphere. These particles may continually survive in the upper troposphere, or over time form ice crystals, both that could impact the atmospheric radiative budget. The sensitivity simulations performed indicate that critical processes in the model causing a substantial change in the upper tropospheric Aitken mode number concentration are coagulation, condensation, nucleation scavenging, nucleation of aerosols and the transfer of aerosol mass and number between different aerosol bins. In particular, for aerosols in the Aitken mode to grow to CCN size, coagulation appears to be more important than condensation. Less important processes are dry deposition, impact scavenging and the initial vertical distribution and concentration of aerosols. It is interesting to note that in order to sustain a vigorous storm cloud, the supply of CCN must be continuous over a considerably long time period of the simulation. Hence, the treatment of the growth of particles is in general much more important than the initial aerosol concentration itself.
Computing the Entropy of User Navigation in the Web

Navigation through the web, colloquially known as "surfing", is one of the main activities of users during web interaction. When users follow a navigation trail they often tend to get disoriented in terms of the goals of their original query and thus the discovery of typical user trails could be useful in providing navigation assistance. Herein, we give a theoretical underpinning of user navigation in terms of the entropy of an underlying Markov chain modelling the web topology. We present a novel method for online incremental computation of the entropy and a large deviation result regarding the length of a trail to realize the said entropy. We provide an error analysis for our estimation of the entropy in terms of the divergence between the empirical and actual probabilities. We then indicate applications of our algorithm in the area of web data mining. Finally, we present an extension of our technique to higher-order Markov chains by a suitable reduction of a higher-order Markov chain model to a first-order one.
Intra-Articular Injection of Cross-Linked Hyaluronic Acid-Dexamethasone Hydrogel Attenuates Osteoarthritis: An Experimental Study in a Rat Model of Osteoarthritis

Cross-linked hyaluronic acid hydrogel (cHA gel) and dexamethasone (Dex) have been used to treat knee osteoarthritis (OA) in clinical practice owing to their chondroprotective and anti-inflammatory effects, respectively. The aim of the present study was to compare the treatment effects of the cHA gel pre-mixed with/without Dex in a surgery-induced osteoarthritis model in rats. Anterior cruciate ligament transection (ACLT) surgery was performed on the right knee of rats to induce OA. Male 2-month-old Sprague-Dawley rats were randomly divided into five groups (n = 10/per group): (1) ACLT + saline; (2) ACLT + cHA gel; (3) ACLT + cHA-Dex (0.2 mg/mL) gel; (4) ACLT + cHA-Dex (0.5 mg/mL) gel; (5) Sham + saline. Intra-joint injections were performed four weeks after ACLT in the right knee. All animals were euthanized at 12 weeks post-surgery. Cartilage damage and changes in the synovial membrane were assessed by micro X-ray, Indian ink articular surface staining, Safranin-O/Fast Green staining, immunohistochemistry, hematoxylin and eosin staining of the synovial membrane, and quantitative reverse transcription-polymerase chain reaction for changes in gene expression. Micro X-ray revealed that the knee joint treated with the cHA-Dex gel was wider than those treated with cHA gel alone or saline. The cHA-Dex gel group had less Indian ink staining (indicator of cartilage fibrillation) than the cHA gel or saline injection groups. Safranin-O/Fast Green staining indicated that increased proteoglycan staining and less cartilage damage were found in the cHA-Dex gel group compared with the cHA gel or saline injection groups. Quantification of histology findings from saline, cHA gel, cHA-Dex (0.2 mg/mL) gel, cHA-Dex (0.5 mg/mL) gel, and sham groups were 5.84 ± 0.29, 4.50 ± 0.87, 3.00 ± 1.00, 2.00 ± 0.48, and 0.30 ± 0.58 (p < 0.05), respectively. A strong staining of type II collagen was found in both the cHA-Dex gel groups compared with saline group or cHA alone group. Similar result was found for the mRNA level of aggrecan and opposite result for type X collagen. Hematoxylin and eosin staining in the synovial membrane showed less synovial lining cell layers and reduced inflammatory cell infiltration in cHA-Dex gel-treated animals compared with saline or cHA only groups. Altogether, cHA-Dex gel has better chondroprotective and anti-inflammatory effects in rat surgery-induced osteoarthritis than cHA alone.
Clustering Genes of Common Evolutionary History

Phylogenetic inference can potentially result in a more accurate tree using data from multiple loci. However, if the loci are incongruent—due to events such as incomplete lineage sorting or horizontal gene transfer—it can be misleading to infer a single tree. To address this, many previous contributions have taken a mechanistic approach, by modeling specific processes. Alternatively, one can cluster loci without assuming how these incongruencies might arise. Such “process-agnostic” approaches typically infer a tree for each locus and cluster these. There are, however, many possible combinations of tree distance and clustering methods; their comparative performance in the context of tree incongruence is largely unknown. Furthermore, because standard model selection criteria such as AIC cannot be applied to problems with a variable number of topologies, the issue of inferring the optimal number of clusters is poorly understood. Here, we perform a large-scale simulation study of phylogenetic distances and clustering methods to infer loci of common evolutionary history. We observe that the best-performing combinations are distances accounting for branch lengths followed by spectral clustering or Ward’s method. We also introduce two statistical tests to infer the optimal number of clusters and show that they strongly outperform the silhouette criterion, a general-purpose heuristic. We illustrate the usefulness of the approach by 1) identifying errors in a previous phylogenetic analysis of yeast species and 2) identifying topological incongruence among newly sequenced loci of the globeflower fly genus Chiastocheta. We release treeCl, a new program to cluster genes of common evolutionary history (http://git.io/treeCl).
Attitudes of University of Botswana Faculty of Humanities students towards minority languages

Abstract Some twenty-four odd years ago, The Revised National Policy on Education intimated that Botswana should incorporate local languages other than Setswana in the education system, although this has still not come to fruition. We administered a questionnaire to undergraduate students at the University of Botswana to find out the languages the students speak, and their attitudes towards minority languages spoken in their country as well as to determine what their views were towards including the said languages in the curriculum. We found out that (1) the students speak a variety of local languages: Setswana, Ikalanga, Shekhalahari, Setswapong, Ndebele and Shona, (2) we also determined that while overall the attitudes of the students towards the country’s minority languages were positive, there were nonetheless differences in the students’ responses towards incorporating minority languages in education between Setswana L1 speakers and minority language L1 speakers, an outcome which likely depicts the language ideology portrayed in the nation’s language policy.
An energy harvesting AWGN channel with a finite battery

In energy harvesting communication systems, the transmitter is adapted to harvest energy per time slot. The harvested energy is either used right away or is stored in a battery to facilitate future transmissions. We consider the problem of determining the Shannon capacity of an energy harvesting transmitter communicating over an additive white Gaussian noise (AWGN) channel, where the amount of energy harvested per time slot is a constant ρ and the battery has capacity σ. This imposes a new kind of power constraint on the transmitted codewords, and we call the resulting constrained channel a (σ, ρ) power constrained AWGN channel. When σ is 0 or ∞, the capacity of this channel is known. For the finite battery case, we obtain an expression for the channel capacity. We obtain bounds on capacity by considering the volume of S<sub>n</sub>(σ, ρ) ⊆ ℝ<sup>n</sup>, which is the set of all length n sequences satisfying the (σ, ρ) constraints.
On the validity of Chapman-Enskog expansions for shock waves with small strength.

We justify a Chapman{Enskog expansion for discontinuous solutions of hyperbolic conservation laws containing shock waves with small strength. Precisely, we establish pointwise uniform estimates for the difierence between the traveling waves of a relaxation model and the traveling waves of the corresponding difiusive equations determined by a Chapman{Enskog expansion procedure to flrst- or second-order.
Using computer vision to simulate the motion of virtual agents

In this paper, we propose a new model to simulate the movement of virtual humans based on trajectories captured automatically from filmed video sequences. These trajectories are grouped into similar classes using an unsupervised clustering algorithm, and an extrapolated velocity field is generated for each class. A physically‐based simulator is then used to animate virtual humans, aiming to reproduce the trajectories fed to the algorithm and at the same time avoiding collisions with other agents. The proposed approach provides an automatic way to reproduce the motion of real people in a virtual environment, allowing the user to change the number of simulated agents while keeping the same goals observed in the filmed video. Copyright © 2007 John Wiley & Sons, Ltd.
KeyGraph: automatic indexing by co-occurrence graph based on building construction metaphor

Presents an algorithm for extracting keywords representing the asserted main point in a document, without relying on external devices such as natural-language processing tools or a document corpus. Our algorithm, KeyGraph, is based on the segmentation of a graph, representing the co-occurrence between terms in a document, into clusters. Each cluster corresponds to a concept on which an author's idea is based, and the top-ranked terms are selected as keywords using a statistic based on each term's relationship to these clusters. This strategy comes from considering that a document is constructed like a building for expressing new ideas based on traditional concepts. The experimental results show that the thus-extracted terms match the author's main point quite accurately, even though KeyGraph does not use each term's average frequency in a corpus, i.e. KeyGraph is a content-sensitive, domain-independent indexing device.
Noninvasive Radiofrequency Field Destruction of Pancreatic Adenocarcinoma Xenografts Treated with Targeted Gold Nanoparticles

Purpose: Pancreatic carcinoma is one of the deadliest cancers with few effective treatments. Gold nanoparticles (AuNP) are potentially therapeutic because of the safety demonstrated thus far and their physiochemical characteristics. We used the astounding heating rates of AuNPs in nonionizing radiofrequency (RF) radiation to investigate human pancreatic xenograft destruction in a murine model. Experimental Design: Weekly, Panc-1 and Capan-1 human pancreatic carcinoma xenografts in immunocompromised mice were exposed to an RF field 36 hours after treatment (intraperitoneal) with cetuximab- or PAM4 antibody–conjugated AuNPs, respectively. Tumor sizes were measured weekly, whereas necrosis and cleaved caspase-3 were investigated with hematoxylin–eosin staining and immunofluorescence, respectively. In addition, AuNP internalization and cytotoxicity were investigated in vitro with confocal microscopy and flow cytometry, respectively. Results: Panc-1 cells demonstrated increased apoptosis with decreased viability after treatment with cetuximab-conjugated AuNPs and RF field exposure (P = 0.00005). Differences in xenograft volumes were observed within 2 weeks of initiating therapy. Cetuximab- and PAM4-conjugated AuNPs demonstrated RF field–induced destruction of Panc-1 and Capan-1 pancreatic carcinoma xenografts after 6 weeks of weekly treatment (P = 0.004 and P = 0.035, respectively). There was no evidence of injury to murine organs. Cleaved caspase-3 and necrosis were both increased in treated tumors. Conclusions: This study demonstrates a potentially novel cancer therapy by noninvasively inducing intracellular hyperthermia with targeted AuNPs in an RF field. While the therapy is dependent on the specificity of the targeting antibody, normal tissues were without toxicity despite systemic therapy and whole-body RF field exposure. Clin Cancer Res; 16(23); 5712–21. ©2010 AACR.
Can Infants Map Meaning to Newly Segmented Words?

The present experiments investigated how the process of statistically segmenting words from fluent speech is linked to the process of mapping meanings to words. Seventeen-month-old infants first participated in a statistical word segmentation task, which was immediately followed by an object-label-learning task. Infants presented with labels that were words in the fluent speech used in the segmentation task were able to learn the object labels. However, infants presented with labels consisting of novel syllable sequences (nonwords; Experiment 1) or familiar sequences with low internal probabilities (part-words; Experiment 2) did not learn the labels. Thus, prior segmentation opportunities, but not mere frequency of exposure, facilitated infants∗ learning of object labels. This work provides the first demonstration that exposure to word forms in a statistical word segmentation task facilitates subsequent word learning.
Predicting maximum branch diameter from crown dimensions, stand characteristics and tree species

Forest resource inventories must include wood quality information to support the optimum use of wood fibre. The objective of this study was to develop models relating maximum live branch diameter (MBD), which affects lumber value, to tree and stand characteristics that can be measured through current and emerging remote sensing technologies. Using non-linear mixed effects models for six Canadian conifer species, as well as for three broad-leaved species, MBD was related to crown radius, tree height, crown length, stand basal area, and basal area of trees larger than the subject tree. Models that included only individual tree characteristics (crown radius, tree height, and crown length) did not perform as well as models that additionally included stand characteristics (stand basal area and basal area of larger trees). Models that took into account tree species performed better than models that did not; in particular, broadleaved species had much thicker branches than conifers. The best model did not show b.