MT Models Research Articles

Multi-trait genomic selection improves the prediction accuracy of end-use quality traits in hard winter wheat.

Improvement of end-use quality remains one of the most important goals in hard winter wheat (HWW) breeding. Nevertheless, the evaluation of end-use quality traits is confined to later development generations owing to resource-intensive phenotyping. Genomic selection (GS) has shown promise in facilitating selection for end-use quality; however, lower prediction accuracy (PA) for complex traits remains a challenge in GS implementation. Multi-trait genomic prediction (MTGP) models can improve PA for complex traits by incorporating information on correlated secondary traits, but these models remain to be optimized in HWW. A set of advanced breeding lines from 2015 to 2021 were genotyped with 8725 single-nucleotide polymorphisms and was used to evaluate MTGP to predict various end-use quality traits that are otherwise difficult to phenotype in earlier generations. The MTGP model outperformed the ST model with up to a twofold increase in PA. For instance, PA was improved from 0.38 to 0.75 for bake absorption and from 0.32 to 0.52 for loaf volume. Further, we compared MTGP models by including different combinations of easy-to-score traits as covariates to predict end-use quality traits. Incorporation of simple traits, such as flour protein (FLRPRO) and sedimentation weight value (FLRSDS), substantially improved the PA of MT models. Thus, the rapid low-cost measurement of traits like FLRPRO and FLRSDS can facilitate the use of GP to predict mixograph and baking traits in earlier generations and provide breeders an opportunity for selection on end-use quality traits by culling inferior lines to increase selection accuracy and genetic gains.

Deep electrical structure of the northern UAE: An investigation along the Dibba zone and the foreland basin using magnetotellurics

Recent geophysical studies are focused on imaging the present-day architecture of the subsurface structures in the northern United Arab Emirates. Previous geophysical data have not fully investigated the deep structures in the middle and lower crust. The foreland basin flanking the UAE-Oman mountains to its west has been investigated by oil companies, mainly using seismic techniques. These studies have been vital in providing a constraint on the subsurface structure of the northern Emirates. This paper reports the results of using broad-band magnetotelluric (BBMT) data acquired for the first time in the UAE to map deep electrical crustal structures. The study aims at determining the geometry of the Semail Ophiolite, the underlying thrust sheets, and the basement structure beneath the allochthonous units and the foreland basin. The MT data were collected from 15 stations along an E-W profile across the Semail Ophiolite and the Dibba zone in the east and the foreland basin in the west. The MT data achieve greater crustal penetration, revealing electrical structures within the upper, mid, and lower crust. 2D and 3D inversion of the data map the high resistivity Ophiolite structure and the associated conductive Hwasina-Haybi thrust sheets in the mountain ranges and in the Dibba zone. In the foreland basin, the Quaternary and Tertiary sediments in the Pabdeh basin are characterized by low resistivity. Furthermore, the MT models detect a high resistivity zone related to the basement structure of the northern UAE in the middle and lower crust. The Ophiolite near the Dibba zone has >7 km thickness as shown in the 2D MT model, and the Hawasina-Haybi sheets have a maximum thickness of ⁓10 km beneath the Ophiolite. The allochthonous units indicate an oceanward dipping as similarly reported in the previous geophysical and geologic studies.

What do post-editors correct? A fine-grained analysis of SMT and NMT errors

The recent improvements in neural MT (NMT) have driven a shift from statistical MT (SMT) to NMT. However, to assess the usefulness of MT models for post-editing (PE) and have a detailed insight of the output they produce, we need to analyse the most frequent errors and how they affect the task. We present a pilot study of a fine-grained analysis of MT errors based on post-editors corrections for an English to Spanish medical text translated with SMT and NMT. We use the MQM taxonomy to compare the two MT models and have a categorized classification of the errors produced. Even though results show a great variation among post-editors’ corrections, for this language combination fewer errors are corrected by post-editors in the NMT output. NMT also produces fewer accuracy errors and errors that are less critical.

Towards Fully Automated Manga Translation

We tackle the problem of machine translation of manga, Japanese comics. Manga translation involves two important problems in machine translation: context-aware and multimodal translation. Since text and images are mixed up in an unstructured fashion in Manga, obtaining context from the image is essential for manga translation. However, it is still an open problem how to extract context from image and integrate into MT models. In addition, corpus and benchmarks to train and evaluate such model is currently unavailable. In this paper, we make the following four contributions that establishes the foundation of manga translation research. First, we propose multimodal context-aware translation framework. We are the first to incorporate context information obtained from manga image. It enables us to translate texts in speech bubbles that cannot be translated without using context information (e.g., texts in other speech bubbles, gender of speakers, etc.). Second, for training the model, we propose the approach to automatic corpus construction from pairs of original manga and their translations, by which large parallel corpus can be constructed without any manual labeling. Third, we created a new benchmark to evaluate manga translation. Finally, on top of our proposed methods, we devised a first compleheisive system for fully automated manga translation.

The Alteration of L-Carnitine Transport and Pretreatment Effect under Glutamate Cytotoxicity on Motor Neuron-Like NSC-34 Lines.

L-Carnitine (LC) is essential for transporting fatty acids to the mitochondria for β-oxidation. This study was performed to examine the alteration of the LC transport system in wild type (WT, NSC-34/hSOD1WT) and mutant type (MT, NSC-34/hSOD1G93A) amyotrophic lateral sclerosis (ALS) models. The uptake of [3H]L-carnitine was dependent on time, temperature, concentration, sodium, pH, and energy in both cell lines. The Michaelis–Menten constant (Km) value as well as maximum transport velocity (Vmax) indicated that the MT cell lines showed the higher affinity and lower capacity transport system, compared to that of the WT cell lines. Additionally, LC uptake was inhibited by organic cationic compounds but unaffected by organic anions. OCTN1/slc22a4 and OCTN2/slc22a5 siRNA transfection study revealed both transporters are involved in LC transport in NSC-34 cell lines. Additionally, slc22a4 and slc22a5 was significantly decreased in mouse MT models compared with that in ALS WT littermate models in the immune-reactivity study. [3H]L-Carnitine uptake and mRNA expression pattern showed the pretreatment of LC and acetyl L-carnitine (ALC) attenuated glutamate induced neurotoxicity in NSC-34 cell lines. These findings indicate that LC and ALC supplementation can prevent the neurotoxicity and neuro-inflammation induced by glutamate in motor neurons.

The Usefulness of Bibles in Low-Resource Machine Translation

Bibles are available in a wide range of languages, which provides valuable parallel text between languages since verses can be aligned accurately between all the different translations. How well can such data be utilized to train good neural machine translation (NMT) models? We are particularly interested in low-resource languages of high morphological complexity, and attempt to answer this question in the current work by training and evaluating Basque-English and Navajo-English MT models with the Transformer architecture. Different tokenization methods are applied, among which syllabification turns out to be most effective for Navajo and it is also good for Basque. Another additional data resource which can be potentially available for endangered languages is a dictionary of either word or phrase translations, thanks to linguists’ work on language documentation. Could this data be leveraged to augment Bible data for better performance? We experiment with different ways to utilize dictionary data, and find that word-to-word mapping translation with a word-pair dictionary is more effective than low-resource techniques such as backtranslation or adding dictionary data directly into the training set, though neither backtranslation nor word-to-word mapping translation produce improvements over using Bible data alone in our experiments.

Micro-mechanical model for predicting the elasto-plastic behavior of composites based on secant formulation method

To predict the Elasto-Plastic Behaviors (EPBs) of aligned inclusions reinforced composites, this paper develops an interpolative Mori-Tanaka/Double-Inclusion (MT-DI) homogenization model with the secant formulation, and gives the numerical implementation algorithms of the developed MT-DI model with the secant formulation. The Finite Element (FE) homogenization method is implemented to provide the “exact” EPBs of the composites and thus validate the MT-DI model with the secant formulation. The MT-DI model with the 2nd-order secant formulation is validated to provide the more accurate predictions, while the MT-DI model with the 1st-order secant formulation always gives the stiffer predictions. The results show that using the macro-stress and macro-strain as the inputs, the MT-DI model with the secant formulation gives the identical predictions. The predictions of the MT-DI model with the secant formulation vary between those of the MT and DI models with the secant formulation. Meanwhile, the MT-DI model with the secant formulation does not predict the accurate EPBs for the phases of the composites.

Application of ensemble empirical mode decomposition based on machine learning methodologies in forecasting monthly pan evaporation

AbstractAccurate prediction of pan evaporation (PE) is one of the crucial factors in water resources management and planning in agriculture. In this research, two hybrid models, self-adaptive time-frequency methodology, ensemble empirical mode decomposition (EEMD) coupled with support vector machine (EEMD-SVM) and EEMD model tree (EEMD-MT), were employed to forecast monthly PE. The EEMD-SVM and EEMD-MT were compared with single SVM and MT models in forecasting monthly PE, measured between 1975 and 2008, at Siirt and Diyarbakir stations in Turkey. The results were evaluated using four assessment criteria, Nash–Sutcliffe Efficiency (NSE), root mean square error (RMSE), performance index (PI), Willmott's index (WI), and Legates–McCabe's index (LMI). The EEMD-MT model respectively improved the accuracy of MT by 36 and 44.7% with respect to NSE and WI in the testing stage for the Siirt station. For the Diyarbakir station, the improvements in results were less spectacular, with improvements in NSE (1.7%) and WI (2.2%), respectively, in the testing stage. The overall results indicate that the proposed pre-processing technique is very promising for complex time series forecasting and further studies incorporating this technique are recommended.

Integrating gravity, seismic, AEM and MT data to investigate crustal architecture and cover thickness: modelling new geophysical data from the Southern Thomson region

New geophysical data, including gravity, airborne electromagnetic (AEM), and both audio frequency and broadband magnetotelluric (AMT, BBMT) were collected along a series of traverses in the southern Thomson Orogen region of north-western New South Wales and southwestern Queensland in 2014 as part of the Southern Thomson Project. Comparing and integrating these data over the same spatial extents aimed to provide a better understanding of the crustal architecture of this region, and help estimate cover thicknesses above basement rocks. When comparing all available datasets, AEM cannot be reliably used when cover thickness is > ~150 m because of limitations in Depth of Investigation (DOI), and BBMT tends to overestimate cover thickness where it is less than 50 m. AMT likely provides the best resolution for estimating cover thicknesses of 0–1000 m on this regional scale. Forward modelling of the gravity data along selected traverses tested the interpreted crustal architecture and cover thicknesses inferred from available seismic images and the new AEM and MT conductivity models. The variable cover thicknesses interpreted from this combined approach produces a closer match with the observed gravity response when compared to a uniform, average cover thickness. The most accurate crustal-scale forward model is a thickened crust north of the Olepoloko Fault (the proposed southern boundary of the southern Thomson), split into simplified lower, middle and upper layers with basement lithologies immediately beneath cover based on the most recent basement interpretation map. Resistive bodies shown in the MT models were included in the gravity modelling, producing a good match between the observed and calculated gravity responses. These results demonstrate the utility in using a combination of different geophysical techniques to understand crustal architecture and estimations of basement depths in regions of Australia with little surface outcrop and thick cover sequences.

Differences in Injury Severity of Accidents on Mountainous Highways and Non-mountainous Highways

Four-year accident data of Colorado Interstate highways is studied to investigate the injury severity of accidents occurring on mountainous highways (MT) and to compare the difference with non-mountainous highways (NM) by using mixed logit models. Injury severity from accidents occurring on MT and NM is modeled separately and their respective critical risk factors are evaluated including vehicle, roadway, environmental, driver and accident characteristics. Considerable differences are found existing between the impacts from a variety of variables on the injury severity in MT and NM accidents. Therefore more comprehensive observations can be made by conducting the injury severity study for MT and NM accidents separately. Estimation findings indicate that one indicator and two indicators will be better modeled as random parameters in MT and NM models respectively. As a result, the complex interactions of various variables and the nature of injury severity are able to be disclosed in a better way.

Contrast and stimulus complexity moderate the relationship between spatial frequency and perceived speed: Implications for MT models of speed perception

Area MT in extrastriate visual cortex is widely believed to be responsible for the perception of object speed. Recent physiological data show that many cells in macaque visual area MT change their speed preferences with a change in stimulus spatial frequency (N. J. Priebe, C. R. Cassanello, & S. G. Lisberger, 2003) and that this effect can accurately predict the dependence of perceived speed on spatial frequency demonstrated in a related psychophysical study (N. J. Priebe & S. G. Lisberger, 2004). For more complex compound gratings and high contrast stimuli, MT cell speed preferences show sharper tuning and less dependence on spatial frequency (Priebe et al., 2003), allowing us to predict that such stimuli should produce speed percepts that are less vulnerable to spatial frequency variations. We investigated the perceived speed of simple sine wave gratings and more complex compound gratings (formed from 2 sine wave components) in response to changes in contrast and spatial frequency. In all cases, high contrast stimuli appeared to translate more rapidly. In addition, high spatial frequencies appeared faster-the opposite effect to that predicted by changes in MT cell spatial frequency preferences. Complex grating stimuli were somewhat "protected" from the effect of spatial frequency (compared to simple gratings), as predicted. However, contrary to predictions, the effect of spatial frequency was larger in high (compared to low) contrast gratings. Our data demonstrate that the previously established links between changes in MT cells' speed preferences and human speed perception are more complex than first thought.

Genetic correlations among production, body size, udder, and productive life traits over time in Holsteins.

Genetic correlations among milk, fat, and protein yields; body size composite (BSC); udder composite (UDC); and productive life (PL) in Holsteins were investigated over time. The data set contained 25,280 records of cows born in Wisconsin between 1979 and 1993. The multiple trait random regression (MT-RR) animal model included registration status, herd-year, age group, and stage of lactation as fixed effects; additive genetic effects with random regressions (RR) on year of birth using the first-order Legendre polynomial; and residual effects. Heterogeneous residual variances were considered in the model. Estimates of variance components and genetic correlations among traits from MT-RR were compared with those estimated with a multiple trait interval (MT-I) model, which assumed that every 3-yr interval was a separate trait and included the same effects as in the MT-RR model except for the RR. Genetic correlations estimated with MT-RR and MT-I models over time among all traits were compared with correlations among breeding values predicted with the single trait (ST) model without RR. Correlations among breeding values predicted with MT-RR, ST, and MT models were also calculated. Additive genetic and residual variances for all traits except PL increased over time; those for PL were constant. As a result, heritability estimates had no significant changes during the 15 yr. Genetic correlations of PL with milk, fat, protein, and BSC declined to zero or negative; those with UDC remained positive. Correlations among breeding values predicted with ST, MT, and MT-RR models were relatively high for all traits except PL. Genetic correlations between PL and other traits varied over time, with some correlations changing sign. For accurate indirect prediction of PL from other traits, the genetic correlations among the traits need to be re-estimated periodically.

SINE-GORDON VS. MASSIVE THIRRING

By viewing the sine-Gordon and massive Thirring models as perturbed conformal field theories, one sees that they are different (the difference being observable, for instance, in finite-volume energy levels). The UV limit of the former (SGM) is a Gaussian model, that of the latter (MTM) a so-called fermionic Gaussian model, the compactification radius of the boson underlying both theories depending on the SG/MT coupling. (These two families of conformal field theories are related by a “twist”.) Corresponding SG and MT models contain a subset of fields with identical correlation functions, but each model also has fields the other one does not have; for example, the fermion fields of MTM are not contained in SGM, and the bosonic soliton fields of SGM are not in MTM. Our results imply, in particular, that the SGM at the so-called “free-Dirac point” β2=4π is actually a theory of two interacting bosons with diagonal S-matrix S=−1, and that for arbitrary couplings the overall sign of the accepted SG S-matrix in the soliton sector should be reversed. More generally, we draw attention to the existence of new classes of quantum field theories, analogs of the (perturbed) fermionic Gaussians models, whose partition functions are invariant only under a subgroup of the modular group. One such class comprises “fermionic versions” of the Virasoro minimal models.

Optimum performance of combined flow reactors under adiabatic conditions

AbstractIrreversible first‐ and second‐order reactions are studied for combinations of tubular and CST reactors when endothermal or exothermal adiabatic conditions prevail.Typical results presented for MT and TM models show the variation of either the conversion or the relative residence time as a function of the mixing level of the system.A graphical method, applicable generally to MT reactors, provides a simplification over that of successive approximations required for model TM.For the conditions investigated broad limits are indicated of the optimum reactor combinations.