Alien Registration- Secord, E Maud (Portland, Cumberland County)

https://digitalmaine.com/alien_docs/21987/thumbnail.jp

A new taeniolabidoid multituberculate (Mammalia) from the middle Puercan of the Nacimiento Formation, New Mexico, and a revision of taeniolabidoid systematics and phylogeny

Multituberculates were amongst the most abundant and taxonomically diverse mammals of the late Mesozoic and the Paleocene, reaching their zenith in diversity and body size in the Paleocene. Taeniolabidoidea, the topic of this paper, includes the largest known multituberculates, which possess highly complex cheek teeth adapted for herbivory. A new specimen from the early Paleocene (middle Puercan; biochron Pu2) of the Nacimiento Formation, New Mexico represents a new large-bodied taeniolabidoid genus and species, Kimbetopsalis simmonsae. A phylogenetic analysis to examine the relationships within Taeniolabidoidea that includes new information from Kimbetopsalis gen. et sp. nov. and gen. nov. and from new specimens of Catopsalis fissidens, first described here, and data from all other described North American and Asian taeniolabidoids. This analysis indicates that Catopsalis is nonmonophyletic and justifies our transfer of the basal-most taeniolabidoid ‘Catopsalis’ joyneri to a new genus, Valenopsalis. Kimbetopsalis and Taeniolabis form a clade (Taeniolabididae), as do the Asian Lambdopsalis, Sphenopsalis, and possibly also Prionessus (Lambdopsalidae). Taeniolabidoids underwent a modest taxonomic radiation during the early Paleocene of North America and underwent a dramatic increase in body size, with Taeniolabis taoensis possibly exceeding 100 kg. Taeniolabidoids appear to have gone extinct in North America by the late Paleocene but the appearance of lambdopsalids in the late Paleocene of Asia suggests that they dispersed from North America in the early to middle Paleocene

Terrestrial carbon isotope stratigraphy and mammal turnover during post-PETM hyperthermals in the Bighorn Basin, Wyoming, USA

Paleogene hyperthermals, including the Paleocene–Eocene Thermal Maximum (PETM) and several other smaller events, represent global perturbations to Earth’s climate system and are characterized by warmer temperatures, changes in floral and faunal communities, and hydrologic changes. These events are identified in the geologic record globally by negative carbon isotope excursions (CIEs), resulting from the input of isotopically light carbon into Earth’s atmosphere. Much about the causes and effects of hyperthermals remains uncertain, including whether all hyperthermals were caused by the same underlying processes, how biotic effects scale with the magnitude of hyperthermals, and why CIEs are larger in paleosol carbonates relative to marine records. Resolving these questions is crucial for a full understanding of the causes of hyperthermals and their application to future climate scenarios. The primary purpose of this study was to identify early Eocene hyperthermals in the Fifteenmile Creek area of the south-central Bighorn Basin, Wyoming, USA. This area preserves a sequence of fluvial floodplain sedimentary rocks containing paleosol carbonates and an extensive record of fossil mammals. Previous analysis of faunal assemblages in this area revealed two pulses of mammal turnover and changes in diversity interpreted to correlate with the ETM2 and H2 hyperthermals that follow the PETM. This was, however, based on long-distance correlation of the fossil record in this area with chemostratigraphic records from elsewhere in the basin. We present new carbon isotope stratigraphies using micrite δ13C values from paleosol carbonate nodules preserved in and between richly fossiliferous mammal localities at Fifteenmile Creek to identify the stratigraphic positions of ETM2 and H2. Carbon isotope results show that the ETM2 and H2 hyperthermals, and possibly the subsequent I1 hyperthermal, are recorded at Fifteenmile Creek. ETM2 and H2 overlap with the two previously recognized pulses of mammal turnover. The CIEs for these hyperthermals are also somewhat smaller in magnitude than in more northerly Bighorn Basin records. We suggest that basin-wide differences in soil moisture and/or vegetation could contribute to variable CIE amplitudes in this and other terrestrial records

Male mastodon landscape use changed with maturation (late Pleistocene, North America)

Under harsh Pleistocene climates, migration and other forms of seasonally patterned landscape use were likely critical for reproductive success of mastodons (Mammut americanum) and other megafauna. However, little is known about how their geographic ranges and mobility fluctuated seasonally or changed with sexual maturity. We used a spatially explicit movement model that coupled strontium and oxygen isotopes from two serially sampled intervals (5+ adolescent years and 3+ adult years) in a male mastodon tusk to test for changes in landscape use associated with maturation and reproductive phenology. The mastodon’s early adolescent home range was geographically restricted, with no evidence of seasonal preferences. Following inferred separation from the matriarchal herd (starting age 12 y), the adolescent male’s mobility increased as landscape use expanded away from his natal home range (likely central Indiana). As an adult, the mastodon’s monthly movements increased further. Landscape use also became seasonally structured, with some areas, including northeast Indiana, used only during the inferred mastodon mating season (spring/summer). The mastodon died in this area (\u3e150 km from his core, nonsummer range) after sustaining a craniofacial injury consistent with a fatal blow from a competing male’s tusk during a battle over access to mates. Northeast Indiana was likely a preferred mating area for this individual and may have been regionally significant for late Pleistocene mastodons. Similarities between mammutids and elephantids in herd structure, tusk dimorphism, tusk function, and the geographic component of male maturation indicate that these traits were likely inherited from a common ancestor

Elevated CAIX Expression is Associated with an Increased Risk of Distant Failure in Early-Stage Cervical Cancer

Tumor hypoxia is associated with adverse outcome in many malignancies. The goal of this study was to determine if elevated expression of carbonic anhydrase IX (CAIX), a biomarker of hypoxia, predicts for recurrence in early-stage cervical cancer. The charts of all patients with early-stage cervical cancer, primarily FIGO IB, treated by radical hysterectomy at our institution from 1988–2001 were reviewed. Adequate pathologic specimens from patients who recurred or who had at least three years follow-up and remained disease-free were stained for CAIX. An immunohistochemical score (IHC) was generated from the extent/intensity of staining. Outcome, as measured by freedom from recurrence (FFR), distant metastases (FFDM) and local recurrence (FFLR), was analyzed as a function of age, IHC, lymph node status (LN) and histology. Forty-two relapsing patients and 76 non-relapsing patients were evaluated. In univariate analysis, +LN, though not IHC or histology, was a significant predictor of any recurrence. Both +LN and higher IHC were associated with decreased FFDM but not FFLR. Patients with both +LN and elevated IHC more frequently exhibited distant metastases as first site of failure (5-year FFDM 50%) than patients with only +LN, elevated IHC or neither feature (70, 85 and 95%, respectively, p = 0.0004). In multivariable analysis, only +LN was significantly associated with poorer FFDM (hazard ratio 4.6, p = 0.0015) though there was a strong trend with elevated CAIX expression (p = 0.069). Elevated CAIX expression is associated with more frequent distant metastases in early-stage cervical cancer, suggesting that patients with this characteristic may benefit from more aggressive treatment

A novel business strategies framework of do-it-yourself practices in logistics to minimise environmental waste and improve performance

The transportation sector is consuming a high quantity of oil and producing air pollution, CO2 and allergies, as well as promoting the storage of goods in traditional warehouses. It is not only creating waste and environmental pollution but also increasing temperature, air pollution and low rainfall. The present study intends to uncover and understand the challenges of logistic infrastructure as well as how the adoption of do-it-yourself (DIY) business strategies is useful to encourage those practices and technology which are useful in transforming the logistic infrastructure into an eco-friendly environment. The DIY focuses on purposely utilising digital technologies to increase the engagement and involvement of customers in businesses. Moreover, DIY enables organisations to produce products and services that are highly demanded and have high acceptability. After doing an extensive literature review, the enablers of DIY are identified, and empirical investigation has been conducted. The analysis of the study provides a business strategies framework of DIY which would help the logistics managers in the proper implementation of the DIY practices to minimise negative environmental impact and improve business performance

Enabling Viewpoint Learning through Dynamic Label Generation

Optimal viewpoint prediction is an essential task in many computer graphics applications. Unfortunately, common viewpoint qualities suffer from two major drawbacks: dependency on clean surface meshes, which are not always available, and the lack of closed-form expressions, which requires a costly search involving rendering. To overcome these limitations we propose to separate viewpoint selection from rendering through an end-to-end learning approach, whereby we reduce the influence of the mesh quality by predicting viewpoints from unstructured point clouds instead of polygonal meshes. While this makes our approach insensitive to the mesh discretization during evaluation, it only becomes possible when resolving label ambiguities that arise in this context. Therefore, we additionally propose to incorporate the label generation into the training procedure, making the label decision adaptive to the current network predictions. We show how our proposed approach allows for learning viewpoint predictions for models from different object categories and for different viewpoint qualities. Additionally, we show that prediction times are reduced from several minutes to a fraction of a second, as compared to state-of-the-art (SOTA) viewpoint quality evaluation. We will further release the code and training data, which will to our knowledge be the biggest viewpoint quality dataset available