POS Tagging and its Applications for Mathematics

Content analysis of scientific publications is a nontrivial task, but a useful and important one for scientific information services. In the Gutenberg era it was a domain of human experts; in the digital age many machine-based methods, e.g., graph analysis tools and machine-learning techniques, have been developed for it. Natural Language Processing (NLP) is a powerful machine-learning approach to semiautomatic speech and language processing, which is also applicable to mathematics. The well established methods of NLP have to be adjusted for the special needs of mathematics, in particular for handling mathematical formulae. We demonstrate a mathematics-aware part of speech tagger and give a short overview about our adaptation of NLP methods for mathematical publications. We show the use of the tools developed for key phrase extraction and classification in the database zbMATH

Serially Concatenated Luby Transform Coding and Bit-Interleaved Coded Modulation Using Iterative Decoding for the Wireless Internet

In Bit-Interleaved Coded Modulation (BICM) the coding and modulation schemes were jointly optimized for the sake of attaining the best possible performance when communicating over fading wireless communication channels. The iterative decoding scheme of BICM (BICM-ID) invoking an appropriate bit-to-symbol mapping strategy enhances its achievable performance in both AWGN and Rayleigh channels. BICM-ID may be conveniently combined with Luby Transform (LT) codes, which were designed for handling packetized wireless Internet data traffic in erasure channels without retransmitting the corrupted packets. By jointly designing a serially concatenated LT-BICM-ID code, an infinitesimally low Bit Error Rate (BER) is achieved for Signal to Noise Ratios (SNR) in excess of 7.5dB over wireless Internet type erasure channels contaminated by AWGN

Factors influencing farmers' forestland-use changes over 15 years (2005–2020) in Thua Thien Hue province, Vietnam

Over the last decades, Vietnam has seen substantial shifts in forest landscape uses and associated livelihoods. We document the livelihood transformations in Nam Dong, a mountainous district of Central Vietnam, where land uses have changed from the utilisation of products from natural forests and shifting cultivation (swidden agriculture) to acacia tree-dominated plantation forestry. Forestry policies (forestland allocation, plantation development agendas), the increase in the economic value of acacia, and household livelihood assets are the primary factors driving these changes. We also found that there are differences in the access to and ownership of forestland with regard to households of different communities and between poor vs wealthy households. Therefore, careful attention needs to be paid to guide future land use policies in the area to foster social and ecological sustainability. HIGHLIGHTS • Major livelihood and forestland-use changes have taken place in central Vietnam over the last two decades. • There has been widespread conversion of forestland (degraded natural forests, swidden land) and cropland to acacia plantations. • Household-scale forestland use changes were primarily driven by forestry policies, the market for woodchips, and land resource access. • There is inequality in access to and ownership of forestland between poor and wealthier households in the mountain district of Vietnam. • Cases of illegal forestland conversions pose challenges to ensuring sustainable forest landscapes

Electrochemical copper recovery from galvanic sludge

The feasibility of recovering copper from electronic industrial waste mud (galvanic sludge) using a combination of leaching and electrowinning has been examined. Leaching with sulfuric acid was found to be the most efficient and cost-effective way of extracting the copper from the sludge, and the optimum acid concentration and time were determined. The copper was then extracted by electrowinning in a batch recirculation electrochemical reactor (Porocell™) employing a three-dimensional carbon felt cathode. The influence of applied current, flow rate and the presence of other metal ion contaminates on the rate and current efficiency of copper electrowinning was investigated. An analysis of the experimental data showed that the current efficiency was lower than unity even though the limiting current for copper deposition was not exceeded. This low current efficiency was attributed to the occurrence of a side reaction, most likely the reduction of dissolved oxygen or oxygen-induced corrosion. The influence of this side reaction can be minimized by operating at relatively high currents and low flow rates

Number--conserving model for boson pairing

An independent pair ansatz is developed for the many body wavefunction of dilute Bose systems. The pair correlation is optimized by minimizing the expectation value of the full hamiltonian (rather than the truncated Bogoliubov one) providing a rigorous energy upper bound. In contrast with the Jastrow model, hypernetted chain theory provides closed-form exactly solvable equations for the optimized pair correlation. The model involves both condensate and coherent pairing with number conservation and kinetic energy sum rules satisfied exactly and the compressibility sum rule obeyed at low density. We compute, for bulk boson matter at a given density and zero temperature, (i) the two--body distribution function, (ii) the energy per particle, (iii) the sound velocity, (iv) the chemical potential, (v) the momentum distribution and its condensate fraction and (vi) the pairing function, which quantifies the ODLRO resulting from the structural properties of the two--particle density matrix. The connections with the low--density expansion and Bogoliubov theory are analyzed at different density values, including the density and scattering length regime of interest of trapped-atoms Bose--Einstein condensates. Comparison with the available Diffusion Monte Carlo results is also made.Comment: 21 pages, 12 figure

A Syngeneic Orthotopic Murine Model of Pancreatic Adenocarcinoma in the C57/BL6 Mouse Using the Panc02 and 6606PDA Cell Lines

Background/Aims: To develop a clinically relevant immunocompetent murine model to study pancreatic cancer using two different syngeneic pancreatic cancer cell lines and to assess MRI for its applicability in this model. Methods: Two cell lines, 6606PDA and Panc02, were employed for the experiments. Cell proliferation and migration were monitored in vitro. Matrigel™ was tested for its role in tumor induction. Tumor cell growth was assessed after orthotopic injection of tumor cells into the pancreatic head of C57/BL6 mice by MRI and histology. Results: Proliferation and migration of Panc02 were significantly faster than those of 6606PDA. Matrigel did not affect tumor growth/migration but prevented tumor cell spread after injection thus avoiding undesired peritoneal tumor growth. MRI could reliably monitor longitudinal tumor growth in both cell lines: Panc02 had a more irregular finger-like growth, and 6606PDA grew more spherically. Both tumors showed local invasiveness. Histologically, Panc02 showed a sarcoma-like undifferentiated growth pattern, whereas 6606PDA displayed a moderately differentiated glandular tumor growth. Panc02 mice had a significantly shorter (28 days) survival than 6606PDA mice (50 days). Conclusion: This model closely mimics human pancreatic cancer. MRI was invaluable for longitudinal monitoring of tumor growth thus reducing the number of mice required. Employing two different cell lines, this model can be used for various treatment and imaging studies

Sequencing the USDA core soybean collection reveals gene loss during domestication and breeding

The gene content of plants varies between individuals of the same species due to gene presence/absence variation, and selection can alter the frequency of specific genes in a population. Selection during domestication and breeding will modify the genomic landscape, though the nature of these modifications is only understood for specific genes or on a more general level (e.g., by a loss of genetic diversity). Here we have assembled and analyzed a soybean (Glycine spp.) pangenome representing more than 1,000 soybean accessions derived from the USDA Soybean Germplasm Collection, including both wild and cultivated lineages, to assess genomewide changes in gene and allele frequency during domestication and breeding. We identified 3,765 genes that are absent from the Lee reference genome assembly and assessed the presence/absence of all genes across this population. In addition to a loss of genetic diversity, we found a significant reduction in the average number of protein-coding genes per individual during domestication and subsequent breeding, though with some genes and allelic variants increasing in frequency associated with selection for agronomic traits. This analysis provides a genomic perspective of domestication and breeding in this important oilseed crop

GAMER MRI: Gated-attention mechanism ranking of multi-contrast MRI in brain pathology.

During the last decade, a multitude of novel quantitative and semiquantitative MRI techniques have provided new information about the pathophysiology of neurological diseases. Yet, selection of the most relevant contrasts for a given pathology remains challenging. In this work, we developed and validated a method, Gated-Attention MEchanism Ranking of multi-contrast MRI in brain pathology (GAMER MRI), to rank the relative importance of MR measures in the classification of well understood ischemic stroke lesions. Subsequently, we applied this method to the classification of multiple sclerosis (MS) lesions, where the relative importance of MR measures is less understood. GAMER MRI was developed based on the gated attention mechanism, which computes attention weights (AWs) as proxies of importance of hidden features in the classification. In the first two experiments, we used Trace-weighted (Trace), apparent diffusion coefficient (ADC), Fluid-Attenuated Inversion Recovery (FLAIR), and T1-weighted (T1w) images acquired in 904 acute/subacute ischemic stroke patients and in 6,230 healthy controls and patients with other brain pathologies to assess if GAMER MRI could produce clinically meaningful importance orders in two different classification scenarios. In the first experiment, GAMER MRI with a pretrained convolutional neural network (CNN) was used in conjunction with Trace, ADC, and FLAIR to distinguish patients with ischemic stroke from those with other pathologies and healthy controls. In the second experiment, GAMER MRI with a patch-based CNN used Trace, ADC and T1w to differentiate acute ischemic stroke lesions from healthy tissue. The last experiment explored the performance of patch-based CNN with GAMER MRI in ranking the importance of quantitative MRI measures to distinguish two groups of lesions with different pathological characteristics and unknown quantitative MR features. Specifically, GAMER MRI was applied to assess the relative importance of the myelin water fraction (MWF), quantitative susceptibility mapping (QSM), T1 relaxometry map (qT1), and neurite density index (NDI) in distinguishing 750 juxtacortical lesions from 242 periventricular lesions in 47 MS patients. Pair-wise permutation t-tests were used to evaluate the differences between the AWs obtained for each quantitative measure. In the first experiment, we achieved a mean test AUC of 0.881 and the obtained AWs of FLAIR and the sum of AWs of Trace and ADC were 0.11 and 0.89, respectively, as expected based on previous knowledge. In the second experiment, we achieved a mean test F1 score of 0.895 and a mean AW of Trace = 0.49, of ADC = 0.28, and of T1w = 0.23, thereby confirming the findings of the first experiment. In the third experiment, MS lesion classification achieved test balanced accuracy = 0.777, sensitivity = 0.739, and specificity = 0.814. The mean AWs of T1map, MWF, NDI, and QSM were 0.29, 0.26, 0.24, and 0.22 (p < 0.001), respectively. This work demonstrates that the proposed GAMER MRI might be a useful method to assess the relative importance of MRI measures in neurological diseases with focal pathology. Moreover, the obtained AWs may in fact help to choose the best combination of MR contrasts for a specific classification problem