Trends, periodicities and ENSO relationship of New Zealand rainfall

The rainfall series for six homogeneous regions of New Zealand for 1901-1996 were not well intercorrelated (maximum correlation +0.6). Rainfalls were almost equally spread in all months. Trends (total changes over about 90 years) were ~0, +11, +2, -6, +1, +8 (±~4)% for the six regions. For seasonal rainfall, large trends were -19% for DJF and +16% for MAM of region 1. Spectral analysis showed peaks in QBO (Quasi-biennial oscillations, 2-3 years) range and near 3, 4-5, 6-9, 10-11 years and higher periodicities. ENSO relationships were not clear-cut. In individual El Niño events, only the very strong events of 1972-73, 1982-83 and 1997-98 were associated with widespread droughts in New Zealand, while the 1940-41 El Niño event was associated with excess rainfall. During the durations of all other El Niño events, New Zealand rainfalls were excess or deficit for a few months, followed by deficit or excess for the next few months (oscillatory nature), similar in all regions in some events, dissimilar in others, with no preference for any season. During La Niña (anti-El Niño) events also, oscillations were observed.

Trends, periodicities and ENSO relationships of the annual precipitation over the contiguous United States and Southern Canada

The century-long (1891-1990) time series of Groisman and Easterling (1994a,b) representing estimates of annual precipitation amounts over five homogeneous regions of the United States and Southern Canada (south of 55° N) were examined for trends, periodicities and ENSO relationships. The trends were not uniformly up or down during the 100-year interval, for any region. From 1891 to about 1930, the trends were downward or negligible. Thereafter, the trends were mostly upward, with cyclic variations superposed. A spectral analysis revealed significant periodicities in the QBO and QTO regions (2-3 years and 3-4 years) as also higher periodicities, some common to all regions and hence seen in the series for the entire region. To study the ENSO relationship, a finer classification of El Nino events was used. Each year was examined to check whether it had an El Nino (EN) and/or a Southern Oscillation Index SOI minimum (SO) and/or warm (W) or cold (C) equatorial eastern Pacific sea surface temperatures SST. Several years were ENSOW, which were further subdivided into two groups viz. Unambiguous ENSOW where El Nino existed and SOI minima and SST maxima were in the middle of the calendar year (May-Aug) and, Ambiguous ENSOW where El Nino existed but the SOI minima and SST maxima were in the early or late part of the calendar year, not in the middle. Other El Nino events were of the type ENSO, ENW, ENC, EN. For the All India summer monsoon rainfall, Unambiguous ENSOW were overwhelmingly associated with droughts. For the rainfall in USA and Canada, relationships were not clear-cut except in the Gulf-Mexico region and some other parts. For these regions, excess rains were associated better with the Unambiguous ENSOW.

To New Beginnings: Riboproteogenomics Discovery of N-Terminal Proteoforms in Arabidopsis Thaliana

Alternative translation initiation is a widespread event in biology that can shape multiple protein forms or proteoforms from a single gene. However, the respective contribution of alternative translation to protein complexity remains largely enigmatic. By complementary ribosome profiling and N-terminal proteomics (i.e., riboproteogenomics), we provide clear-cut evidence for ~90 N-terminal proteoform pairs shaped by (alternative) translation initiation in Arabidopsis thaliana. Next to several cases additionally confirmed by directed mutagenesis, identified alternative protein N-termini follow the enzymatic rules of co-translational N-terminal protein acetylation and initiator methionine removal. In contrast to other eukaryotic models, N-terminal acetylation in plants cannot generally be considered as a proxy of translation initiation because of its posttranslational occurrence on mature proteolytic neo-termini (N-termini) localized in the chloroplast stroma. Quantification of N-terminal acetylation revealed differing co- vs. posttranslational N-terminal acetylation patterns. Intriguingly, our data additionally hints to alternative translation initiation serving as a common mechanism to supply protein copies in multiple cellular compartments, as alternative translation sites are often in close proximity to cleavage sites of N-terminal transit sequences of nuclear-encoded chloroplastic and mitochondrial proteins. Overall, riboproteogenomics screening enables the identification of (differential localized) N-terminal proteoforms raised upon alternative translation.

Multi-surveyor detection-mark-redetection as a powerful tool for butterfly population monitoring in the pre-imaginal stage

1. For many elusive insect species, which are difficult to cover by standard monitoring schemes, innovative monitoring methods are needed to gain robust data on population trends. We suggest a monitoring of overwintering larvae for the endangered nymphalid butterfly Limenitis reducta. 2. We tested one removal and three detection-mark-redetection (DMR) approaches in a field study in the “Alb-Donau” region, Germany. We replaced movement of the study organisms by random movement of multiple different surveyors, and we examined the model assumption of equal detectability using simulations. 3. Our results indicate that multi-surveyor removal/DMR techniques are suitable for estimating abundance of overwintering L. reducta larvae. Detection probabilities varied with surveyor experience and the uncertainty of population estimates increased with a decrease in personnel expenditure. Estimated larval densities on a spruce clear-cut ranged between one and three individuals per 100 m². 4. We suggest a detection-mark-redetection (DMR) approach with three trained surveyors for the monitoring of L. reducta populations in the pre-imaginal stage. Besides L. reducta, the proposed method is likely to be suitable for other insect taxa with specific immobile life-stages and some sessile organisms, e.g. corals, elusive plants, or fungi.

The Demand Side of Democratic Backsliding: How Divergent Understandings of Democracy Shape Political Choice

Why do citizens in democracies fail to punish political candidates who openly violate democratic standards at the ballot box? The bulk of existing research assumes that a common understanding of democracy underpins citizens’ evaluations of different candidates, resulting in a trade-off between undemocratic practices and partisan or economic considerations. We shed doubt on this assumption by showing that divergent understandings of democracy coexist among citizens and affect vote choice. We leverage a novel approach to estimate individual-level citizen commitment to democracy by means of a candidate choice conjoint experiment in Poland, a country experiencing democratic backsliding in a context of deep polarization. We find support for our claim that respondents with less clear-cut liberal democratic attitudes not only tolerate democratic violations more readily, but do so irrespective of a given candidate’s partisan affiliation. Thus, we contend that a lack of attitudinal consolidation around liberal democratic norms explains continued voter support for authoritarian-leaning leaders.

Assessment of glomerular morphological patterns by deep learning algorithms

Background Compilation of different morphological lesion signatures is characteristic of renal pathology. Previous studies have documented the potential value of artificial intelligence (AI) in recognizing relatively clear-cut glomerular structures and patterns, such as segmental or global sclerosis or mesangial hypercellularity. This study aimed to test the capacity of deep learning algorithms to recognize complex glomerular structural changes that reflect common diagnostic dilemmas in nephropathology. Methods For this purpose, we defined nine classes of glomerular morphological patterns and trained twelve convolutional neuronal network (CNN) models on these. The two-step training process was done on a first dataset defined by an expert nephropathologist (12,253 images) and a second consensus dataset (11,142 images) defined by three experts in the field. Results The efficacy of CNN training was evaluated using another set with 180 consensus images, showing convincingly good classification results (kappa-values 0.838–0.938). Furthermore, we elucidated the image areas decisive for CNN-based decision making by class activation maps. Finally, we demonstrated that the algorithm could decipher glomerular disease patterns coinciding in a single glomerulus (e.g. necrosis along with mesangial and endocapillary hypercellularity). Conclusions In summary, our model, focusing on glomerular lesions detectable by conventional microscopy, is the first sui generis to deploy deep learning as a reliable and promising tool in recognition of even discrete and/or overlapping morphological changes. Our results provide a stimulus for ongoing projects that integrate further input levels next to morphology (such as immunohistochemistry, electron microscopy, and clinical information) to develop a novel tool applicable for routine diagnostic nephropathology.

Hardwired to attack. Candidates’ personality traits and negative campaigning in three European countries

A growing body of studies shows that the reasons for competing candidates to “go negative” on their opponents during elections—that is, attacking their opponents instead of promoting their own programs or ideas stem from strategic considerations. Yet, existing research has, at this stage, failed to assess whether candidates’ personality traits also play a role. In this article, we bridge the gap between existing work in political psychology and political communication and study to what extent the personality traits of competing candidates are linked with their use of negative campaigning strategies. We rely on candidate survey data for recent elections in three countries—Germany (2017), Switzerland (2019), and Finland (2019). The data includes self-reported measures for candidates’ “Big Five” personality traits (extraversion, agreeableness, conscientiousness, neuroticism, openness) and the the use of attacks towards their opponents during the campaign. Controlling for the usual suspects driving the use of negative campaigning we show that this latter is associated with low agreeableness and (marginally) with high extraversion and low conscientiousness. The role of personality for the focus of an attack (issue vs. character attacks) is somewhat less clear-cut. All in all, kinder and more stable candidates tend to go less negative; when they do, they tend to stay away from character-based attacks and somehow focus on issues.

Tracking Hunter-Gatherer Impact on Vegetation in Last Interglacial and Holocene Europe: Proxies and Challenges

We review palaeoenvironmental proxies and combinations of these relevant for understanding hunter-gatherer niche construction activities in pre-agricultural Europe. Our approach consists of two steps: (1) identify the possible range of hunter-gatherer impacts on landscapes based on ethnographic studies; (2) evaluate proxies possibly reflecting these impacts for both the Eemian (Last Interglacial, Middle Palaeolithic) and the Early–Middle Holocene (Mesolithic). We found these paleoenvironmental proxies were not able to unequivocally establish clear-cut differences between specific anthropogenic, climatic and megafaunal impacts for either time period in this area. We discuss case studies for both periods and show that published evidence for Mesolithic manipulation of landscapes is based on the interpretation of comparable data as available for the Last Interglacial. If one applies the ‘Mesolithic’ interpretation schemes to the Neanderthal record, three common niche construction activities can be hypothesised: vegetation burning, plant manipulation and impact on animal species presence and abundance. Our review suggests that as strong a case can be made for a Neanderthal impact on landscapes as for anthropogenic landscape changes during the Mesolithic, even though the Neanderthal evidence comes from only one high-resolution site complex. Further research should include attempts (e.g. by means of modelling studies) to establish whether hunter-gatherer impact on landscapes played out at a local level only versus at a larger scale during both time periods, while we also need to obtain comparative data on the population sizes of Last Interglacial and Holocene hunter-gatherers, as these are usually inferred to have differed significantly.

Approaches and Applications for Sentiment Analysis

With the increasing penetration of the internet, an ever-growing number of people are voicing their opinions in the numerous blogs, tweets, forums, social networking, and consumer review websites. Each such opinion has a sentiment (positive, negative, or neutral) associated with it. But the problem is that the amount of data is simply overwhelming. Methods like supervised machine learning and lexical-based approaches are available for measuring sentiments that have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis has been used in several applications including analysis of the repercussions of events in social networks, analysis of opinions about products and services. This chapter presents sentiment analysis applications and challenges with their approaches and tools. The techniques and applications discussed in this chapter will provide a clear-cut idea to the sentiment analysis researchers to carry out their work in this field.