Arapahoe Community College

This research introduces a charge-enhanced encoding module within the AisNet multifeature fusion framework, demonstrating superior force error accuracy and cross-model transferability, and achieving in state-of-the-art performance on the SN2 dataset. Compared with the original AisNet, the addition of the Coulomb matrix enables AisNet-C with ternary features to maintain its leading performance in all feature dimensions. Through t-SNE and PCA analysis, long-range Coulomb interaction effectively enhances global environmental resolution, forming a synergistic relationship with other features. The performance of the AisNet-C is optimal at a dimension larger than 60, which is related to the accuracy of the ACSF fitting. Particularly, the PAINN model demonstrated the best compatibility with the enhanced module, resulting in the SOTA result of 0.00423 eV/Å and reducing the mean error over by 41.8% compared to PhysNet's benchmark. The key to PaiNN's success lies in the multimodule cooperation, which maintains intraclass atomic resolution while bringing different atom types closer together, thus forming a more compact feature space. Our plug-and-play encoding module can not only efficiently utilize multiple descriptors through feature decoupling, but also has the potential to be applied to a wider range of model architectures, providing new ideas for realizing physically informed machine learning force fields.

ABSTRACT One way in which philosophers have often sought to distinguish moral judgments from non-moral judgments is by using the “moral-conventional” distinction. I seek to raise serious questions about the significance of the moral-conventional distinction, at least for philosophers interested in moral judgment. I survey recent developments in the fields of philosophy, psychology, and cognitive science that have led many to the conclusion that moral judgment is not a distinctive kind of judgment or the result of a specific, identifiable cognitive process. I argue that if this conclusion is largely correct, the moral-conventional distinction loses significance. If moral judgment does not correspond to a distinctive cognitive process, it is unclear how distinguishing between types of norms tracks anything of significance to human judgment formation. I then discuss the implications of abandoning the distinction for research in the field of moral psychology and tentatively propose a more modest way of conceiving of norm significance.

I argue that the debate concerning the nature of first-person moral judgment, namely, whether such moral judgments are inherently motivating (internalism) or whether moral judgments can be made in the absence of motivation (externalism), may be founded on a faulty assumption: that moral judgments form a distinct kind that must have some shared, essential features in regards to motivation to act. I argue that there is little reason to suppose that first-person moral judgments form a homogenous class in this respect by considering an ordinary case: student readers of Peter Singer’s “Famine, Affluence, and Morality”. Neither internalists nor externalists can provide a satisfying account as to why our students fail to act in this particular case, but are motivated to act by their moral judgments in most cases. I argue that the inability to provide a satisfying account is rooted in this shared assumption about the nature of moral judgments. Once we consider rejecting the notion that first-person moral decision- making forms a distinct kind in the way it is typically assumed, the internalist/externalist debate may be rendered moot.

ABSTRACT The Sopris archaeological culture in southeastern Colorado was first identified as Puebloan and then later as local hunter-gatherers influenced by trade with the Northern Rio Grande area. By applying Eastern Pueblo ethnography, we show that the earlier interpretation is better. Physical emphases on such profound cultural features as dualism, cardinal directions, and kiva equivalents cannot be explained by trade, but instead point to Eastern Pueblo origins. Furthermore, a Tanoan model, incorporating a Tewa origin myth as well as Tiwa ethnography, provides a framework for understanding associated rock art. Concentric activity zones essential to a Tanoan worldview help to explain an agricultural shrine near fields (zone 2), hunting shrines in surrounding hills (zone 3), and a rain shrine in the headwaters of the Purgatoire valley (zone 4). The rain shrine included unusual and unique images.

The Permian Basin of west Texas spans two major subbasins — the Midland Basin and the Delaware Basin. Both basins contain Wolfcampian- to Leonardian-age turbidites that form thick sections of prolific unconventional reservoirs. For the past several years, the most active drilling targets in the United States have been the Wolfberry turbidite interval of the Midland Basin and the Wolfbone turbidite interval in the Delaware Basin. We have used two new technologies to examine the internal architecture and fabric of a thick interval of these unconventional drilling targets with seismic reflection seismology. First, we used seismic interpretation software that uses unsupervised machine learning (ML), so that a higher level of detail could be extracted from seismic images. Second, we complemented our P-P imaging of Wolfberry turbidites with a new seismic imaging option, that being SV-P (or converted-P) imaging. Because vertical vibrators, particularly arrays of vertical vibrators, produce downgoing P and downgoing SV illuminating wavefields, SV-P reflections can usually be extracted from the same vertical-geophone responses as are P-P reflections. The combination of these two images essentially doubles the amount of information that can be extracted from data generated by P sources and recorded with vertical geophones. SV-P imaging with P sources has been ignored by reflection seismologists for decades, so we felt an obligation to illustrate the value of this ignored seismic mode. These two new tools — SV-P imaging and interpreting P-P and SV-P images via unsupervised ML — expanded our insights into the internal architecture and fabric of Wolfberry turbidites. Our work provides interpreters a much-needed example of applying unsupervised ML technology in a joint interpretation of P- and S-wave data.

Plant design parameters for gold extraction, leach residence time and cyanide consumption are generally determined from standard bench-scale bottle roll or agitation leach tests. The application of laboratory data to process design has essentially evolved from the testing of oxide or low cyanide-consuming ores. Such scale-up factors may not be appropriate for ores that deplete cyanide and oxygen since this interferes with gold extraction kinetics. High cyanide-consuming ores also exacerbate the differences between the conditions applicable to small batch tests and large continuous operations. Testing a reactive high-sulfide South American ore deposit necessitated the re-evaluation of conventional bench-scale cyanidation procedures. Pulp density can be a major factor affecting the results for plant design purposes and should be treated as a test work variable. As with high clay-bearing ore, where pulp viscosity can hinder mass transfer, minimizing the influence of test equipment on gold extraction kinetics may require low pulp densities. This introduces interpretative complexity since cyanide consumption changes as a function of pulp density. Activated carbon also consumes cyanide, so its effect has to be accounted for in the case of carbon-in-leach (CIL) or carbon-in-pulp (CIP) plant flowsheets. Since cyanide is an expensive reagent, often a major component of plant operating costs, it is important that the scale-up of cyanide consumption from laboratory to plant be representative. The traditional method of reporting cyanide consumption in bench-scale testing is questioned since it takes credit for residual free cyanide in leach tails. The projected plant consumption may be better estimated by using the total cyanide addition in a laboratory test. We propose a test work protocol that categorizes the cyanide consumption into its components but requires more extensive testing to generate design data. The ultimate validation of scale-up factors used by project engineers requires rigorous bench-scale versus commercial plant comparative data. Such data are not readily available.