In the area of electronically-mediated communication, real-time online
text commentaries (OTCs) as a new specialised register have become popular as an
alternative to traditional broadcasting. OTCs have been recognised as “mediated
quasi-interaction” (Chovanec 2010) and a hybrid genre showing characteristics
of spoken discourse within a written mode (Jucker 2006), as well as a characteristic
combination of simultaneous information and entertainment (“infotainment”),
where familiarity or “pseudo-intimacy” (O’Keeffe 2006; cf. Chovanec
2008) between commentator and the audience is created. This contribution helps
to situate this emerging register from a cross-cultural perspective. I use OTCs by
English and German media outlets from the EURO 2012 football championship to
tackle the following issues with the help of a corpus-linguistic approach: (i) What
are register-specific structural features of OTCs? (ii) Are there any culture-specific
aspects along language boundaries or the dimension “intended readership”? I
also consider the interaction of layout and content, production circumstances,
and the influence of recent developments (such as the incorporation of Twitter
messages) on reporting styles.
This study provides an analysis of the Present Perfect (PrPf; have + V-en) in World Englishes. To this end, I extract occurrences of the PrPf from the International Corpus of English and annotate them manually for various factors (such as semantics, Aktionsart, temporal adverbials). I analyze the distributions of these factors and define a central PrPf context, while I also explore a multidimensional aggregative approach as a means to establish measures of similarity between the different varieties. In addition, I present a measure of PrPf-friendliness and examine alternative surface forms appearing in perfect contexts. Eventually I relate the findings to existing models of World Englishes, whose applicability I critically review in the light of the findings for the feature under investigation.
Following decades of stability and comfortable margins, utility companies today face
strong pressure from regulatory bodies and competitors. As a response to the market
dynamics, many have initiated a transformation from a “provider” to a service
company, yet realize that their customer insights that would be necessary to
successfully develop and market new services are sparse. We argue that the required
information is contained in consumption data that is available to utility companies. We
demonstrate how data analytics and machine learning make sense out of such data and
add value to organizations. Using datasets containing annual electricity consumption
information of private households, we apply and test in field experiments a Support
Vector Machines algorithm that predicts probabilities of individual costumers to sign up
on an energy efficiency portal. We show that signup rates can be doubled and argue
that classification tools provide customer insights at low cost and at scale.
Power systems require a continuous balance of supply and demand. In Europe, this task is shared between Balance Responsible Parties (BRPs) and Transmission System Operators (TSOs). For this purpose, the European electricity sector consists of several markets. Objective of this paper is to investigate distorted incentives that stem from loopholes in the market design which BRPs can use to undermine electricity balancing principles in favour of gaming opportunities between the domestic imbalance energy pricing and international wholesale markets. These incentives are evaluated using historical data from the Swiss power system which features a typical European imbalance pricing mechanism. The results imply that little effort would have been needed to make a good profit at the expense of system security. The major loophole arises from the interdependence between cross-border trading and national imbalance energy pricing. Bearing in mind the European Union's Third Energy Package, the importance of national balancing mechanisms will increase strongly. In this context, national remedies to cope with distorted incentives are outlined and the importance of harmonising balancing markets on an international level is elaborated.
The limited driving range of electric vehicles (EV) is one of the
biggest deployment challenges for electromobility. We use GPS driving data
from a fleet of about 1,000 conventional private vehicles collected over two
years to simulate energy consumption of electric cars. We estimate how much
energy is required for EV charging at home and at a secondary parking location
(e.g., at work) and to what extent energy from solar panels during sunlight hours
can be used for charging.
This paper presents a supervised classification model, where the indicators of correlation
between dependent and independent variables within each class are utilized
for a transformation of the large-scale input data to a lower dimension without loss
of recognition relevant information. In the case study, we use the consumption data
recorded by smart electricity meters of 4200 Irish dwellings along with half-hourly
outdoor temperature to derive 12 household properties (such as type of heating, floor
area, age of house, number of inhabitants, etc.). Survey data containing characteristics
of 3500 households enables algorithm training. The results show that the presented
model outperforms ordinary classifiers with regard to the accuracy and temporal characteristics.
The model allows incorporating any kind of data affecting energy consumption
time series, or in a more general case, the data affecting class-dependent variable,
while minimizing the risk of the curse of dimensionality. The gained information on
household characteristics renders targeted energy-efficiency measures of utility companies
and public bodies possible.
Over two decades have passed since the federal policy on environmental justice (EO 12898) was issued. However, empirical evidence indicates that injustice persists and that US states vary in their adoption of the terms of the environmental justice (EJ) policy. Moreover, studies of the explanations for the variation in states’ adoption of EJ policy are rare and have yielded puzzling ﬁndings - e.g., environmental interest groups are not associated with states’ EJ policy adoption, or the severity of problems is associated inversely with their adoption. We examined the progress and variation in states’ EJ policy adoption as of 2005 using fuzzy-set qualitative comparative analysis. Our analysis showed ﬁrst that a strong environmental interest group presence, combined with high racial diversity and low problem severity, is sufﬁcient for a high level of EJ policy adoption, especially in Western states. Second, when environmental interest group presence is weak, if it is combined, again, with high racial diversity and the presence of a more liberal state government, a high level of EJ policy adoption also occurs. This is observed in the East coast, Midwestern, and Southern regions of the USA. Environmental politics and policy research can beneﬁt from a conﬁgurational approach, especially when there is no guiding theory on the conjunctional effects of key factors.
This study compared the long-term efficacy of a diabetes-specific cognitive behavioral
group therapy (CBT) with sertraline in patients with diabetes and depression
who initially responded to short-term depression treatment.
RESEARCH DESIGN AND METHODS
A randomized controlled single-blind trial was conducted in 70 secondary care
centers across Germany comparing 12 weeks of CBT with sertraline in 251 patients
with type 1 or 2 diabetes (mean HbA1c 9.3%, 78 mmol/mol) and major depression
(Structured Clinical Interview for DSM-IV [SCID]). After 12 weeks, treatment responders
(‡50% reduction Hamilton Depression Rating Scale [HAMD-17]) were
included in the 1-year study phase where CBT patients were encouraged to use
bibliotherapy and sertraline patients received continuous treatment. We analyzed
differences for HbA1c (primary outcome) and reduction (HAMD-17) or remission
(SCID) of depression from baseline to the 1-year follow-up using ANCOVA
or logistic regression analysis.
After 12 weeks, 45.8% of patients responded to antidepressant treatment and
were included in the 1-year study phase. Adjusted HbA1c mean score changes from
baseline to the end of the long-term phase (20.27, 95% CI 20.62 to 0.08) revealed
no significant difference between interventions. Depression improved in both
groups, with a significant advantage for sertraline (HAMD-17 change: 22.59,
95% CI 1.15–4.04, P < 0.05).
Depression improved under CBT and sertraline in patients with diabetes and depression,
with a significant advantage for sertraline, but glycemic control
remained unchanged. CBT and sertraline as single treatment are insufficient to treat secondary care diabetes patients with depression and poor glycemic control.
This paper presents an experimental study investigating the interplay of individuals’ other-regarding preferences and individuals’ risk attitude. Participants (N = 120) had to make choices between a certain and risky payoff only for themselves (individual context) and choices in which the participants were paired with another randomly assigned participant who functioned as a passive recipient (interpersonal context). In the interpersonal context the risky option was beneficial for the other person while the certain option was not. Thus, the interpersonal choice context was an abstract representation of the incentive structure in helping situations, which yield risk only for the helper. Risky options in the interpersonal context yielded different payoff distributions, which allowed us to identify how considerations of fairness affect interpersonal risky choices. To assess other-regarding preferences, a dictator game was played. First we found that participants were generally less risk averse in the interpersonal choices; however, the degree of risk aversion was affected by the distribution of payoffs between decider and recipient. Furthermore, we found that changes of risk aversion in an interpersonal context could be predicted with the proposed splits in the dictator game.