Regulation - the movie:a semiotic study of the periodic review of UK regulated industry

This paper explores the regulatory process of UK privatised utilities as manifest in the periodic review of prices. Two separate review processes are identified, operating concurrently - a covert dialogue between the regulator and the regulated and an overt dialogue taking place in the public arena. Using a semiotic analysis of the review the authors argue that the overt event is the real review. Furthermore they argue that the unfolding of each review is so similar that it can be likened to a film script which is constantly re-enacted. The purpose of the review as a legitimating vehicle for the regulator and regulated, who exist in a symbiotic relationship, is explored in terms of the semiotics involved and the myth creation role of legitimation in order to explain the significance of the regulatory process.

Constant shear along a boundary of a flume

'I'he accurate rreasurement of bed shear stress has been extremely difficult due to its changing values until white propunded a theory which would give constant shear along the bed of a flume. In this investigation a flume has been designed according to White's theory and by two separate methods proven to give constant shearing force along the bed. The first method applied the Hydrogen Bubble Technique to obtain accurate values of velocity thus allowing the velocity profile to be plotted and the momentum at the various test sections to be calculated. The use of a 16 mm Beaulieu movie camera allowed the exact velocity profiles created by the hydrogen bubbles to be recorded whilst an analysing projector gave the means of calculating the exact velocities at the various test sections. Simultaneously Preston's technique of measuring skin friction using Pitot tubes was applied. Twc banks of open ended water manometer were used for recording the static and velocity head pressure drop along the flume. This tvpe of manometer eliminated air locks in the tubes and was found to be sufficiently accurate. Readings of pressure and velocity were taken for various types and diameters of bed material both natural sands and glass spheres and the results tabulated. Graphs of particle Reynolds Number against bed shear stress were plotted and gave a linear relationship which dropped off at high values of Reynolds number. It was found that bed movement occurred instantaneously along the bed of the flume once critical velocity had been reached. On completion of this test a roof curve inappropriate to the bed material was used and then the test repeated. The bed shearing stress was now no longer constant and yet bed movement started instantaneously along the bed of the flume, showing that there are more parameters than critical shear stress to bed movement. It is concluded from the two separate methods applied that the bed shear stress is constant along the bed of the flume.

May the contact lens force be with you

FULL TEXT: Like many people one of my favourite pastimes over the holiday season is to watch the great movies that are offered on the television channels and new releases in the movie theatres or catching up on those DVDs that you have been wanting to watch all year. Recently we had the new ‘Star Wars’ movie, ‘The Force Awakens’, which is reckoned to become the highest grossing movie of all time, and the latest offering from James Bond, ‘Spectre’ (which included, for the car aficionados amongst you, the gorgeous new Aston Martin DB10). It is always amusing to see how vision correction or eye injury is dealt with by movie makers. Spy movies and science fiction movies have a freehand to design aliens with multiples eyes on stalks or retina scanning door locks or goggles that can see through walls. Eye surgery is usually shown in some kind of day case simplified laser treatment that gives instant results, apart from the great scene in the original ‘Terminator’ movie where Arnold Schwarzenegger's android character encounters an injury to one eye and then proceeds to remove the humanoid covering to this mechanical eye over a bathroom sink. I suppose it is much more difficult to try and include contact lenses in such movies. Although you may recall the film ‘Charlie's Angels’, which did have a scene where one of the Angels wore a contact lens that had a retinal image imprinted on it so she could by-pass a retinal scan door lock and an Eddy Murphy spy movie ‘I-Spy’, where he wore contact lenses that had electronic gadgetry that allowed whatever he was looking at to be beamed back to someone else, a kind of remote video camera device. Maybe we aren’t quite there in terms of devices available but these things are probably not the behest of science fiction anymore as the technology does exist to put these things together. The technology to incorporate electronics into contact lenses is being developed and I am sure we will be reporting on it in the near future. In the meantime we can continue to enjoy the unrealistic scenes of eye swapping as in the film ‘Minority Report’ (with Tom Cruise). Much more closely to home, than in a galaxy far far away, in this issue you can find articles on topics much nearer to the closer future. More and more optometrists in the UK are becoming registered for therapeutic work as independent prescribers and the number is likely to rise in the near future. These practitioners will be interested in the review paper by Michael Doughty, who is a member of the CLAE editorial panel (soon to be renamed the Jedi Council!), on prescribing drugs as part of the management of chronic meibomian gland dysfunction. Contact lenses play an active role in myopia control and orthokeratology has been used not only to help provide refractive correction but also in the retardation of myopia. In this issue there are three articles related to this topic. Firstly, an excellent paper looking at the link between higher spherical equivalent refractive errors and the association with slower axial elongation. Secondly, a paper that discusses the effectiveness and safety of overnight orthokeratology with high-permeability lens material. Finally, a paper that looks at the stabilisation of early adult-onset myopia. Whilst we are always eager for new and exciting developments in contact lenses and related instrumentation in this issue of CLAE there is a demonstration of a novel and practical use of a smartphone to assisted anterior segment imaging and suggestions of this may be used in telemedicine. It is not hard to imagine someone taking an image remotely and transmitting that back to a central diagnostic centre with the relevant expertise housed in one place where the information can be interpreted and instruction given back to the remote site. Back to ‘Star Wars’ and you will recall in the film ‘The Phantom Menace’ when Qui-Gon Jinn first meets Anakin Skywalker on Tatooine he takes a sample of his blood and sends a scan of it back to Obi-Wan Kenobi to send for analysis and they find that the boy has the highest midichlorian count ever seen. On behalf of the CLAE Editorial board (or Jedi Council) and the BCLA Council (the Senate of the Republic) we wish for you a great 2016 and ‘may the contact lens force be with you’. Or let me put that another way ‘the CLAE Editorial Board and BCLA Council, on behalf of, a great 2016, we wish for you!’

Perception while watching movies:effects of physical screen size and scene type

Over the last decade, television screens and display monitors have increased in size considerably, but has this improved our televisual experience? Our working hypothesis was that the audiences adopt a general strategy that “bigger is better.” However, as our visual perceptions do not tap directly into basic retinal image properties such as retinal image size (C. A. Burbeck, 1987), we wondered whether object size itself might be an important factor. To test this, we needed a task that would tap into the subjective experiences of participants watching a movie on different-sized displays with the same retinal subtense. Our participants used a line bisection task to self-report their level of “presence” (i.e., their involvement with the movie) at several target locations that were probed in a 45-min section of the movie “The Good, The Bad, and The Ugly.” Measures of pupil dilation and reaction time to the probes were also obtained. In Experiment 1, we found that subjective ratings of presence increased with physical screen size, supporting our hypothesis. Face scenes also produced higher presence scores than landscape scenes for both screen sizes. In Experiment 2, reaction time and pupil dilation results showed the same trends as the presence ratings and pupil dilation correlated with presence ratings, providing some validation of the method. Overall, the results suggest that real-time measures of subjective presence might be a valuable tool for measuring audience experience for different types of (i) display and (ii) audiovisual material.

Self-training from labeled features for sentiment analysis

Sentiment analysis concerns about automatically identifying sentiment or opinion expressed in a given piece of text. Most prior work either use prior lexical knowledge defined as sentiment polarity of words or view the task as a text classification problem and rely on labeled corpora to train a sentiment classifier. While lexicon-based approaches do not adapt well to different domains, corpus-based approaches require expensive manual annotation effort. In this paper, we propose a novel framework where an initial classifier is learned by incorporating prior information extracted from an existing sentiment lexicon with preferences on expectations of sentiment labels of those lexicon words being expressed using generalized expectation criteria. Documents classified with high confidence are then used as pseudo-labeled examples for automatical domain-specific feature acquisition. The word-class distributions of such self-learned features are estimated from the pseudo-labeled examples and are used to train another classifier by constraining the model's predictions on unlabeled instances. Experiments on both the movie-review data and the multi-domain sentiment dataset show that our approach attains comparable or better performance than existing weakly-supervised sentiment classification methods despite using no labeled documents.

Incorporating sentiment prior knowledge for weakly supervised sentiment analysis

This article presents two novel approaches for incorporating sentiment prior knowledge into the topic model for weakly supervised sentiment analysis where sentiment labels are considered as topics. One is by modifying the Dirichlet prior for topic-word distribution (LDA-DP), the other is by augmenting the model objective function through adding terms that express preferences on expectations of sentiment labels of the lexicon words using generalized expectation criteria (LDA-GE). We conducted extensive experiments on English movie review data and multi-domain sentiment dataset as well as Chinese product reviews about mobile phones, digital cameras, MP3 players, and monitors. The results show that while both LDA-DP and LDAGE perform comparably to existing weakly supervised sentiment classification algorithms, they are much simpler and computationally efficient, rendering themmore suitable for online and real-time sentiment classification on the Web. We observed that LDA-GE is more effective than LDA-DP, suggesting that it should be preferred when considering employing the topic model for sentiment analysis. Moreover, both models are able to extract highly domain-salient polarity words from text.

A comparative study of bayesian models for unsupervised sentiment detection

This paper presents a comparative study of three closely related Bayesian models for unsupervised document level sentiment classification, namely, the latent sentiment model (LSM), the joint sentiment-topic (JST) model, and the Reverse-JST model. Extensive experiments have been conducted on two corpora, the movie review dataset and the multi-domain sentiment dataset. It has been found that while all the three models achieve either better or comparable performance on these two corpora when compared to the existing unsupervised sentiment classification approaches, both JST and Reverse-JST are able to extract sentiment-oriented topics. In addition, Reverse-JST always performs worse than JST suggesting that the JST model is more appropriate for joint sentiment topic detection.

Learning sentiment classification model from labeled features

We propose a novel framework where an initial classifier is learned by incorporating prior information extracted from an existing sentiment lexicon. Preferences on expectations of sentiment labels of those lexicon words are expressed using generalized expectation criteria. Documents classified with high confidence are then used as pseudo-labeled examples for automatical domain-specific feature acquisition. The word-class distributions of such self-learned features are estimated from the pseudo-labeled examples and are used to train another classifier by constraining the model's predictions on unlabeled instances. Experiments on both the movie review data and the multi-domain sentiment dataset show that our approach attains comparable or better performance than exiting weakly-supervised sentiment classification methods despite using no labeled documents.

Automatically extracting polarity-bearing topics for cross-domain sentiment classification

Joint sentiment-topic (JST) model was previously proposed to detect sentiment and topic simultaneously from text. The only supervision required by JST model learning is domain-independent polarity word priors. In this paper, we modify the JST model by incorporating word polarity priors through modifying the topic-word Dirichlet priors. We study the polarity-bearing topics extracted by JST and show that by augmenting the original feature space with polarity-bearing topics, the in-domain supervised classifiers learned from augmented feature representation achieve the state-of-the-art performance of 95% on the movie review data and an average of 90% on the multi-domain sentiment dataset. Furthermore, using feature augmentation and selection according to the information gain criteria for cross-domain sentiment classification, our proposed approach performs either better or comparably compared to previous approaches. Nevertheless, our approach is much simpler and does not require difficult parameter tuning.

Androiden und (Anti)feminismus in The Stepford Wives

Since the early days of cinema the creation of artificial life with its various implications has been a popular topic on screen. Amongst the large number of films that deal with the theme of androids Bryan Forbes’ "The Stepford Wives" (1975) is noticeable for its focus on questions of gender and the relationship between the sexes. The film is set in a contemporary small suburban town where frustrated husbands have found a special way of dealing with their emancipated wives by replacing them with docile life-like robots. Mixing elements of the thriller and horror genres with farce and comedy "The Stepford Wives" was the first American mainstream film to deal explicitly with Women’s Lib. Unlike Ira Levin in his much more ambivalent novel that the film was based on, Forbes and his actors deliberately set out to make a feminist satire, and according to some critics succeeded in producing an important document of second wave feminism which soon acquired cult status. However, it also provoked a number of negative reactions from feminists who were very uncomfortable with a film in which men get away with murdering the female population of an entire town. A closer inspection reveals that the satirical element of the film is indeed not prominent and frequently counteracted, at times facilitating a misogynist rather than a feminist interpretation. This is mainly due to the ending of the film which implies the murderous elimination of the female protagonist. Unlike all other cinematic and literary works that feature androids "The Stepford Wives" shows the successful creation of artificial life which does not backfire. In addition, the film which clearly categorises itself as a thriller and horror movie, and specifically alludes to the tradition of threatened yet strong female characters in these genres, at the same time defies this convention in favour of a seemingly misogynist ending. Thus the way in which "The Stepford Wives" refuses to comply with the traditions of both the android theme and the horror genre, involuntarily serves to undermine its intention as a feminist social satire.

Joint sentiment/topic model for sentiment analysis

Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes a novel probabilistic modeling framework based on Latent Dirichlet Allocation (LDA), called joint sentiment/topic model (JST), which detects sentiment and topic simultaneously from text. Unlike other machine learning approaches to sentiment classification which often require labeled corpora for classifier training, the proposed JST model is fully unsupervised. The model has been evaluated on the movie review dataset to classify the review sentiment polarity and minimum prior information have also been explored to further improve the sentiment classification accuracy. Preliminary experiments have shown promising results achieved by JST.

All-optical binary counter

We experimentally demonstrate an all-optical binary counter composed of four semiconductor optical amplifier based all-optical switching gates. The time-of-flight optical circuit operates with bit-differential delays between the exclusive-OR gate used for modulo-2 binary addition and the AND gate used for binary carry detection. A movie of the counter operating in real time is presented.

Urzeit, Traumzeit, Endzeit:Versuch über Heiner Müller

Dieser Essay von Uwe Schütte unternimmt eine so unorthodoxe wie überfällige Annäherung an das komplexe Werk Heiner Müllers. Unter kulturanthropologischem Vorzeichen werden zentrale Dramen wie Mauser, Bildbeschreibung oder Verkommenes Ufer Medeamaterial Landschaft mit Argonauten diskutiert, aber auch Gedichte und weithin unbekannte Kurzprosa. Die assoziativ vorgehende Analyse kreist dabei um Stichworte wie Mantik und Kannibalismus oder Opfer und Verausgabung sowie um das Traumzeitdenken der australischen Aborigines, Ritus und Mythos am Beispiel entpersonalisierter Postdramatik, das Schweigen als Urgrund des Theaters, das Kainsmal als Urschrift, schamanistische Jenseitsreisen, prophetische Rede und traumatischer Wiederholungszwang in der Prosa. Abseits gängiger Interpretationsansätze eröffnet sich dadurch ein tiefgreifendes Verständnis für die kulturanthropologische Basis von Heiner Müllers Schreiben.

Preeclampsia : an accelerator–brake defect disorder

Life's perfect partnership starts with the placenta. If we get this right, we have the best chance of healthy life. In preeclampsia, we have a failing placenta. Preeclampsia kills one pregnant woman every minute and the life expectancy of those who survive is greatly reduced. Preeclampsia is treated roughly the same way it was when Thomas Edison was making the first silent movie. Globally, millions of women risk death to give birth each year and almost 300,000 lose their lives in this process. Over half a million babies around the world die each year as a consequence of preeclampsia. Despite decades of research, we lack pharmacological agents to treat it. Maternal endothelial dysfunction is a central phenomenon responsible for the clinical signs of preeclampsia. In the late nineties, we discovered that vascular endothelial growth factor (VEGF) stimulated nitric oxide release. This led us to suggest that preeclampsia arises due to the loss of VEGF activity, possibly due to a rise in soluble Flt-1 (sFlt-1), the natural antagonist of VEGF. Researchers have shown that high sFlt-1 elicits preeclampsia-like signs in pregnant rats and sFlt-1 increases before the clinical signs of preeclampsia in pregnant women. We demonstrated that removing or reducing this culprit protein from preeclamptic placenta restored the angiogenic balance. Heme oxygenase-1 (HO-1 or Hmox1) that generates carbon monoxide (CO), biliverdin (rapidly converted to bilirubin) and iron is cytoprotective. We showed that the Hmox1/CO pathway prevents human placental injury caused by pro-inflammatory cytokines and suppresses sFlt-1 and soluble endoglin release, factors responsible for preeclampsia phenotypes. The other key enzyme we identified is the hydrogen sulfide generating cystathionine-gamma-lyase (CSE or Cth). These are the only two enzyme systems shown to suppress sFlt-1 and to act as protective pathways against preeclampsia phenotypes in animal models. We also showed that when hydrogen sulfide restores placental vasculature, it also improves lagging fetal growth. These molecules act as the inhibitor systems in pregnancy and when they fail, this triggers preeclampsia. Discovering that statins induce these enzymes led us to an RCT to develop a low-cost therapy (StAmP Trial) to prevent or treat preeclampsia. If you think of pregnancy as a car then preeclampsia is an accelerator–brake defect disorder. Inflammation, oxidative stress and an imbalance in the angiogenic milieu fuel the ‘accelerator’. It is the failure in the braking systems (the endogenous protective pathway) that results in the ‘accelerator’ going out of control until the system crashes, manifesting itself as preeclampsia.

Collaborative filtering and deep learning based recommendation system for cold start items

Recommender system is a specific type of intelligent systems, which exploits historical user ratings on items and/or auxiliary information to make recommendations on items to the users. It plays a critical role in a wide range of online shopping, e-commercial services and social networking applications. Collaborative filtering (CF) is the most popular approaches used for recommender systems, but it suffers from complete cold start (CCS) problem where no rating record are available and incomplete cold start (ICS) problem where only a small number of rating records are available for some new items or users in the system. In this paper, we propose two recommendation models to solve the CCS and ICS problems for new items, which are based on a framework of tightly coupled CF approach and deep learning neural network. A specific deep neural network SADE is used to extract the content features of the items. The state of the art CF model, timeSVD++, which models and utilizes temporal dynamics of user preferences and item features, is modified to take the content features into prediction of ratings for cold start items. Extensive experiments on a large Netflix rating dataset of movies are performed, which show that our proposed recommendation models largely outperform the baseline models for rating prediction of cold start items. The two proposed recommendation models are also evaluated and compared on ICS items, and a flexible scheme of model retraining and switching is proposed to deal with the transition of items from cold start to non-cold start status. The experiment results on Netflix movie recommendation show the tight coupling of CF approach and deep learning neural network is feasible and very effective for cold start item recommendation. The design is general and can be applied to many other recommender systems for online shopping and social networking applications. The solution of cold start item problem can largely improve user experience and trust of recommender systems, and effectively promote cold start items.