Unnatural Temporalities and Projected Places in Sam Shepard’s Cowboys #2

Sam Shepard’s Cowboys #2 (1967) belongs to his first period of play writing. In this phase, his works exhibit experimental, remote, impossible narrative/fictional worlds that are overwhelmingly abstract, exhibiting “abrupt shifts of focus and tone” (Wetzsteon 1984, 4). Shepard’s unusual theatrical literary cartography is commensurate with his depiction of unnatural temporalities, in that, although the stage is bare, with almost no props, the postmodernist/metatheatrical conflated timelines and projected (impossible) places in the characters’ imagination mutually reflect and inflect each other. Employing Jan Alber’s reading strategies in his theorization of unnatural narratology and Barbara Piatti’s concept of projected places, this essay proposes a synthetic approach so as to naturalize the unnatural narratives and storyworlds in Shepard’s play.

Landscape dynamics promoted the evolution of mega-diversity in South American freshwater fishes

Landscape dynamics and river network rearrangements are widely thought to shape the diversity of Neotropical freshwater fishes, the most species-rich continental vertebrate fauna on Earth. Yet the effects of hydrogeographic changes on fish dispersal and diversification remain poorly understood. Here we integrate an unprecedented occurrence dataset of 4,967 South American freshwater fish species with a species-dense phylogeny to track the evolutionary processes associated with hydrogeographic events over 100 Ma. Net lineage diversification was heterogeneous through time, across space, and among clades. Three abrupt shifts in diversification rates occurred during the Paleogene (between 63 and 23 Ma) in association with major landscape evolution events, and net diversification accelerated from the Miocene to the Recent (c. 20 - 0 Ma). The Western Amazon exhibited the highest rates of in situ diversification and was also the most important source of species dispersing to other regions. All regional biotic interchanges were associated with documented hydrogeographic events and the formation of biogeographic corridors, including Early Miocene (c. 20 Ma) uplift of the Serra do Mar, and Late Miocene (c. 10 Ma) uplift of the Northern Andes and formation of the modern transcontinental Amazon River. Reciprocal mass dispersal of fishes between the Western and Eastern Amazon coincided with this phase of Andean uplift. The Western Amazon has the highest contemporary levels of species richness and phylogenetic endemism. Our results support the hypothesis that landscape dynamics were constrained by the history of drainage basin connections, strongly affecting the assembly and diversification of basin-wide fish faunas.

Narratiiv ja topos Heino Elleri “Sümfoonilises legendis”

This article focuses on the narrative analysis of late-romantic instrumental music. Having adopted the structuralist-semiotic conception of musical narrative as proposed by Byron Almén (2008) as the transvaluation of an opposing hierarchy, and the concept of the musical topic as musical elements with specific stylistic-cultural associations, I analyse the expressive form of Heino Eller’s early symphonic poem “Symphonic Legend” (1923). Narrative logic was found to permeate the musical work despite its collage or suite-like form, as the composer introduces characteristic musical actors that re-appear in different musical contexts. These actors are largely distinguished by musical topics, the conventional stylistic associations related with their musical characteristics as Eller’s piece presents a wide synthesis of styles – from musical impressionism and expressionism to lyrical or chromatic late-romantic; and various topics, such as fantastic, ombra, apassionata, pianto, heroic, and pastoral. Further, I propose a layered narrative structure for the “Symphonic Legend”, as the jarring and abrupt changes in musical material, affect and topic between different movements of the piece suggest shifts in the level of musical discourse and a framed narrative, as proposed by Hatten (1994). The primary order-imposing hierarchy is identified as the pastoral-impressionist topic that acts as the introduction and coda to the entire piece while the transgressive hierarchy is carried by antagonistic musical material associated with fantastical and dysphoric topics (whole-tone scale, chromaticism, fanfare-like brass and ombra) and with the main theme-actor of the piece (a theme strongly resembling the main theme of the first part of Rimsky-Korsakov’s “Scheherezade”). While the pastoral beginning and end of the piece (1st and 11th sections) suggest a narrative trajectory of a romance or “the victory of the order-imposing hierarchy over the transgression”, the abrupt shifts that occur between those sections and the middle-sections of the piece suggest that these take place at a different level of discourse, placing the narrative weight in sections 2–10, where the primary conflict seems to be between the antagonistic material and the theme-actor. In the middle sections Eller seems to problematize the typical narrative trajectory of dysphoric to euphoric in 19th-century symphonic poems, as the theme-actor’s heroic apotheosis in the 9th section is undermined by its reprise in section 10 and ultimate inability to be united with the order-imposing hierarchy in the coda, suggesting an ironic narrative. This reading is hopefully the first of many narrative analyses of Eller’s and other Estonian composers’ unique late-romantic and early modern symphonic poems.

Econometrics for Modelling Climate Change

Shared features of economic and climate time series imply that tools for empirically modeling nonstationary economic outcomes are also appropriate for studying many aspects of observational climate-change data. Greenhouse gas emissions, such as carbon dioxide, nitrous oxide, and methane, are a major cause of climate change as they cumulate in the atmosphere and reradiate the sun’s energy. As these emissions are currently mainly due to economic activity, economic and climate time series have commonalities, including considerable inertia, stochastic trends, and distributional shifts, and hence the same econometric modeling approaches can be applied to analyze both phenomena. Moreover, both disciplines lack complete knowledge of their respective data-generating processes (DGPs), so model search retaining viable theory but allowing for shifting distributions is important. Reliable modeling of both climate and economic-related time series requires finding an unknown DGP (or close approximation thereto) to represent multivariate evolving processes subject to abrupt shifts. Consequently, to ensure that DGP is nested within a much larger set of candidate determinants, model formulations to search over should comprise all potentially relevant variables, their dynamics, indicators for perturbing outliers, shifts, trend breaks, and nonlinear functions, while retaining well-established theoretical insights. Econometric modeling of climate-change data requires a sufficiently general model selection approach to handle all these aspects. Machine learning with multipath block searches commencing from very general specifications, usually with more candidate explanatory variables than observations, to discover well-specified and undominated models of the nonstationary processes under analysis, offers a rigorous route to analyzing such complex data. To do so requires applying appropriate indicator saturation estimators (ISEs), a class that includes impulse indicators for outliers, step indicators for location shifts, multiplicative indicators for parameter changes, and trend indicators for trend breaks. All ISEs entail more candidate variables than observations, often by a large margin when implementing combinations, yet can detect the impacts of shifts and policy interventions to avoid nonconstant parameters in models, as well as improve forecasts. To characterize nonstationary observational data, one must handle all substantively relevant features jointly: A failure to do so leads to nonconstant and mis-specified models and hence incorrect theory evaluation and policy analyses.

Challenges Faced in Teaching and Learning during Clinical Years of Dentistry amidst the Covid-19 Pandemic

Background: COVID-19 has had unprecedented effects in all disciplines of life, across the world. Nationwide shutdowns and uncertainty of reopening educational institutes have raised concerns about the smooth continuity of the education system. Sudden and abrupt shifts to online learning poses significant challenges for dental and medical schools everywhere. Aim: This cross-sectional study explores the challenges faces by students and faculty of Undergraduate Dentistry in clinical years. Methods: This cross-sectional study was conducted from 6th April to 5th May 2020. Two structured questionnaires (for faculty and third, final year BDS students respectively) were designed and validated. Data analysis was performed using SPSS 21, descriptive statistics were applied and frequencies were calculated for various responses Results : Thirty-three (94.3%) faculty members and 161 (95.3%) students expressed that COVID-19 was disrupting the teaching and learning of the clinical years of dentistry, while 16 (45.7%) said clinical teaching had been disturbed more than knowledge-based teaching. According to the students and faculty members, applications like WhatsApp and Zoom were inadequate for developing clinical skills. Conclusion: Clinical teaching and learning of Dentistry have been considerably disrupted by the Corona Virus. Social media applications such as WhatsApp and Zoom are the most commonly used mode for knowledge transfer but are not adequate platforms for clinical skills needed to gain competence in clinical dentistry. The ability of teaching and accessing mandatory clinical skills using online forums is a major concern and needs to be addressed as soon as possible. Keywords: E-learning, COVID-19 and dental teaching, social media teaching

Rapid Assessment of the COVID-19 Impacts on the Galician (NW Spain) Seafood Sector

This paper aims to develop a rapid assessment of the COVID-19 impact on the Galician (NW Spain) seafood sector, one of the most important maritime regions in the world. Here, we focus not only on the immediate COVID-19 impacts on the extractive fisheries sector, but also on the capacity of the aquaculture and the canned industries to supply seafood markets before and during the pandemic. We synthesize multiple data sources from across the seafood supply chain to show the relative initial responses and variables of recovery during a pre-COVID-19 period (2015–2019) and during the pandemic (2020). Our study shows that seafood sectors and trade were disrupted by abrupt shifts in demand, supply and limitations on the movement of people and goods, with a wide range of impacts and consequences for the seafood sectors. We find that domestic landings, Galician aquaculture production and imports and exports of seafood products (fresh, live and frozen) in 2020 showed an important decrease. In contrast, the canned production and the imports and exports of prepared and preserved seafood products followed an increasing trend during the COVID-19 pandemic. We record a change in the consumption behavior of the Galician population, which significantly increased expenditure in fresh and canned seafood products during the first confinement. Overall, the Galician seafood sectors were able to ensure the supply of seafood products to the population during the period of confinement decreed as a result of the COVID-19 crisis. Proximity to markets, investment in domestic or nearby supply chains and the development of new technological innovations helped to avoid food shortages and loss of livelihoods in Galicia. Fishers and fishing enterprises have also acted collectively to reassert their rights to provide essential and high quality seafood products to the Galician population, their livelihoods and safe working conditions, and have leveraged relationships and collaborations with their government counterparts to continue fishing.

Severe Testing and Characterization of Change Points in Climate Time Series

This paper applies misspecification (M-S) testing to the detection of abrupt changes in climate regimes as part of undertaking severe testing of climate shifts versus trends. Severe testing, proposed by Mayo and Spanos, provides severity criteria for evaluating statistical inference using probative criteria, requiring tests that would find any flaws present. Applying M-S testing increases the severity of hypothesis testing. We utilize a systematic approach, based on well-founded principles that combines the development of probative criteria with error statistical testing. Given the widespread acceptance of trend-like change in climate, especially temperature, tests that produce counter-examples need proper specification. Reasoning about abrupt shifts embedded within a complex times series requires detection methods sensitive to level changes, accurate in timing, and tolerant of simultaneous changes of trend, variance, autocorrelation, and red-drift, given that many of these measures may shift together. Our preference is to analyse the raw data to avoid pre-emptive assumptions and test the results for robustness. We use a simple detection method, based on the Maronna-Yohai (MY) test, then re-assess nominated shift-points using tests with varied null hypotheses guided by M-S testing. Doing so sharpens conclusions while avoiding an over-reliance on data manipulation, which carries its own assumptions.