Miracle-dz/UniFAR-FTUs huggingface dataset:
Price Discrimination with Experience Goods: a Structural Econometric Analysis

Firms often offer menus of two-part tariffs to price discriminate among consumers with heterogeneous preferences. In this paper we study the effectiveness of this screening mechanism when consumers are uncertain about the quality of the good and resolve this uncertainty through consumption experiences. We use consumer-level data to estimate a dynamic structural model of forward-looking consumers with heterogeneous demands, both ex-ante and ex-post, for an experience good sold by a monopolist offering a fixed menu of two-part tariffs. Our analysis highlights four elements that influence consumer behavior and affect pricing strategies: beliefs, switching costs, experiential learning, and (ex-ante) mistakes in tariff choice. Since elements of our data contradict the rational expectations assumption, we impose a slightly weaker beliefs assumption. Despite consumers having, on average, unbiased priors, their beliefs conditional on tariff choice are biased. Consumers on flat fee tariffs tend to have optimistic priors whereas consumers on per-use tariffs tend to have pessimistic priors. Combined with high switching costs, this sorting-induced bias implies that flat fee tariffs can yield high profits for the firm even after optimistic consumers revise their beliefs. Biased priors also lead to biased expectations of consumer surplus. Realized surplus is on average negative, despite expectations of surplus of \$118 per consumer. Regarding the use of menus, we find they are ineffective, yielding almost no gain over the optimal single two-part tariff
Lycopersicon esculentum Extract Enhances Cognitive Function and Hippocampal Neurogenesis in Aged Mice

A decrease in adult neurogenesis is associated with the aging process, and this decrease is closely related to memory impairment. Tomato (Lycopersicon esculentum) is a fruit with diverse bioactive nutrients that is consumed worldwide. In this study, we investigated the cognition-enhancing effect of tomato ethanolic extracts (TEE) in aged mice. Six weeks of oral TEE administration in 12-month-old aged mice significantly increased their exploration time of novel objects when compared to vehicle-treated mice. The TEE supplement increased doublecortin (DCX)-positive cells and postsynaptic density-95 (PSD95) expression in mice hippocampus. Moreover, we found an increased expression of brain-derived neurotrophic factor (BDNF) and subsequently-activated extracellular-signal-regulated kinase (ERK)/cAMP response element binding (CREB) signaling pathway in the TEE-supplemented mice hippocampus. In conclusion, the oral administration of TEE exhibits a cognition-enhancing effect, and the putative underlying mechanism is the induction of BDNF signaling-mediated proliferation and synapse formation in the hippocampus. These findings indicate that TEE could be a candidate for treatment of age-related memory impairment and neurodegenerative disorders.
Demonstrating Low-Power Distributed Queuing for active RFID communications at 433 MHz

This paper presents a demonstrator of Low-Power Distributed Queuing (LPDQ), a MAC protocol targeted at active RFID systems operating at 433 MHz. LPDQ is based on a packet-based Preamble Sampling for network synchronization and Distributed Queuing for channel access. Compared to the MAC protocol defined in the ISO 18000-7 standard, based on an analog Preamble Sampling and Frame Slotted ALOHA, LPDQ represents a major breakthrough in terms of system performance and energy consumption. At the MAC layer system performance is close to the optimal, e.g., no collisions during data packet transmission, and tag energy consumption can be reduced by more than 10% compared to FSA.
Processing Group Reverse kNN in Spatial Databases

In Reverse Nearest Neighbour (RNN) Query, every single object in the space has a certain region where all objects inside this region will think of the query object as their nearest neighbour. Other objects that are outside the region will not consider the query object as their nearest neighbour. In many cases, we might encounter a situation where we want to find this kind of region for several objects altogether, instead of a single object. Current RNN region approach cannot be used for this problem. Therefore we propose Group Reverse kNN as a solution, which we will find a specific region based on multiple query objects. So any objects located inside this region will always consider all of the query objects as the nearest compare to the non-query objects. Our experiments demonstrate the performance efficiency of the proposed Group Reverse kNN algorithm.
A Multi-Site Evaluation of Innovative Approaches to Increase Tuberculosis Case Notification: Summary Results

Background Globally, TB notifications have stagnated since 2007, and sputum smear positive notifications have been declining despite policies to improve case detection. We evaluate results of 28 interventions focused on improving TB case detection. Methods We measured additional sputum smear positive cases treated, defined as the intervention area's increase in case notification during the project compared to the previous year. Projects were encouraged to select control areas and collect historical notification data. We used time series negative binomial regression for over-dispersed cross-sectional data accounting for fixed and random effects to test the individual projects' effects on TB notification while controlling for trend and control populations. Results Twenty-eight projects, 19 with control populations, completed at least four quarters of case finding activities, covering a population of 89.2 million. Among all projects sputum smear positive (SS+) TB notifications increased 24.9% and annualized notification rates increased from 69.1 to 86.2/100,000 (p = 0.0209) during interventions. Among the 19 projects with control populations, SS+TB case notifications increased 36.9% increase while in the control populations a 3.6% decrease was observed. Fourteen (74%) of the 19 projects' SS+TB notification rates in intervention areas increased from the baseline to intervention period when controlling for historical trends and notifications in control areas. Conclusions Interventions were associated with large increases in TB notifications across many settings, using an array of interventions. Many people with TB are not reached using current approaches. Different methods and interventions tailored to local realities are urgently needed.
Hysterosalpingo-foam sonography: patient selection and perspectives

We present an overview of the common types of tubal patency tests, with a focus on hysterosalpingo-foam sonography (HyFoSy). Current evidence suggests that HyFoSy is an accurate alternative to X-ray hysterosalpingography (HSG) for outpatient tubal evaluation in women who are at low risk for tubal disease. It may be superior to saline hysterosalpingo-contrast sonography (HyCoSy) in excluding tubal occlusion. A hyperechogenic medium may enhance contrast visualization and enable clearer delineation of tubal anatomy. This may enhance confidence in the diagnosis of tubal patency, reduce false occlusion results, and improve the diagnostic yield of the test. It would be reasonable to deduce that HyFoSy would have similar performance characteristics as HyCoSy with other positive contrast agents. The available evidence supports the accuracy of HyFoSy compared to other forms of tubal investigation. We suggest a decision-making pathway based on the most current professional recommendations and available evidence. However, in this article, we do not provide a definitive exposition of the methods used for investigating tubal patency. Rather, we explore the contexts in which the various investigations are most and least suitable, and identify their strengths and limitations. Finally, we also discuss challenges encountered when performing tubal contrast sonography in clinical practice, including the problem of false occlusion results.
Antinociceptive Activity of Methanolic Stem Bark Extracts of Harrisonia Abyssinica Oliv and Landolphia Buchananii (Hallier F.) Stapf in Mice Model

Pain is an unpleasant sensation attributed to an interplay of sensory and cognitive mechanisms and thus a source of burden to the individual and society. Since pain acts as a source of discomfort, it requires medical suppression. There is a growing interest in the use of herbal remedies as an attractive healthcare alternative to synthetic drugs. This is due to conventional medications being expensive and arguably associated with various adverse effects, hence the necessity for herbal agents that are effective, safe and relatively cheap. Harrisonia abyssinica and Landolphia buchananii are herbs that have been utilized to manage various ailments afflicting people especially in tropical Africa. However, despite their wide folklore use, extensive literature research reveals limited evaluation on the pharmacological activities of their described effects on pain. Thus, the aim of the current study was to evaluate the antinociceptive effects of their methanolic extracts. Experimental mice were divided into a normal control group, a negative control group, a reference group and three dosage groups. The dosage groups were treated with stem bark extracts at concentration of 50 mg/kg, 100 mg/kg and 150 mg/kg. The formalin paw licking test was used to determine the antinociceptive potential. Evaluation of the antinociceptive activities was compared with diclofenac as the reference drug. The H. abyssinica extract reduced pain by 39.73%-81.13% (in the early phase) and 15.92%-69.84% (in the late phase) while L. buchananii extract reduced it by between 35.35%-47.72% (in the early phase) and 20.57-55.17% (in the late phase). In the early phase, reduction of pain by diclofenac was by 19.97%-46.50% and 76.77-74.80% (in the late phase). Several phytochemicals were observed to be present. The traditional medicinal use of the aforementioned plants in the suppression of pain has thus been confirmed by the study results.
Accumulation of AGEs and VEGF in Eyes of SDT Rats

Background/Aims: The Spontaneously Diabetic Torii (SDT) rat develops advanced diabetic retinopathy (DR). The aim of this study was to identify advanced glycation end products (AGEs) related to vascular endothelial growth factor (VEGF) expression, a cause of DR in SDT rats. Methods: One eye was obtained from six SDT rats (blood glucose, >250 mg/dl) and 10 nondiabetic normal Sprague- Dawley (SD) rats and prepared for immunohistochemical study of VEGF and AGEs (pyrraline, pentosidine, carboxy methyl lysine (CML)). Immunostaining was described as minimal, moderate, and severe. Results: In diabetic rats, for CML, five eyes had severe and one moderate immunostaining. For pyrraline, one eye had moderate and five eyes minimal immunostaining. For pentosidine, one eye had moderate and five eyes minimal immunostaining. For VEGF, three eyes each had moderate and severe immunostaining. In nondiabetic rats, for CML one eye had minimal, seven had moderate, and two had severe immunostaining. For pyrraline, four eyes had moderate and six eyes minimal immunostaining. For pentosidine, 10 eyes had minimal immunostaining. For VEGF, one eye had moderate and nine had minimal immunostaining. The prevalence rates of CML and VEGF were significantly (P<0.05, P<0.001, respectively) greater in diabetic than in nondiabetic rats. The prevalence rates of pyrraline and pentosidine were not significantly (P=0.35, P=0.38) different between diabetic and nondiabetic rats. Conclusion: CML coexists with VEGF and may be involved in the pathogenesis of severe ocular complications in SDT rats.
5 . 4 Emotion and Achievement in the Classroom

With the exception of extensive research on test anxiety since the 1950s (Sarason & Mandler, 1952; Zeidner, 2007) and on emotions in achievement settings based on attribution theory (Weiner, 1985), empirical educational research has largely neglected students' emotions. Over the past decade, however, a discernible increase in theoretical and empirical contributions on emotions in education is reflected in numerous special issues and edited volumes (Efklides & Volet, 2005; Linnenbrink, 2006; Linnenbrink-Garcia & Pekrun, 2011; Lipnevich & Roberts, 2012; Schutz & Lanehart, 2002; Schutz & Pekrun, 2007). Nonetheless, with the exception of research on anxiety/achievement relations (e.g., Hembree, 1988; Ma, 1999; Seipp, 1991), there exist only scattered empirical findings on relations between other emotions and academic achievement (Pekrun, 2006). This lack of emphasis is reflected in arecent PsychINFO search (January 2011) for manuscript titles inc1uding "achievement" and "anxiety" (532) as compared to "enjoyment" (10), "hope" (14), "pride" (7), "anger" (8), "shame" (8), or "boredom" (3). In contrast to 1,015 titles inc1uding "achievement" and "self-concept," the relatively small number of publications in the field of emotions as compared to self-concept research is c1early evident.
Spatio-Temporal Access Methods

The rapid increase in spatio-temporal applications calls for new auxiliary indexing structures. A typical spatio-temporal application is one that tracks the behavior of moving objects through location-aware devices (e.g., GPS). Through the last decade, many spatio-temporal access methods are developed. Spatio-temporal access methods focus on two orthogonal directions: (1) Indexing the past, (2) Indexing the current and predicted future positions. In this short survey, we classify spatio-temporal access methods for each direction based on their underlying structure with a brief discussion of future research directions.
Discovery of Trending Topics in Microblog Streams Based on Contextual Search

With the rapid growing of microblog, the need to discover the trending topics in microblogs becomes more and more pressing. Although topic detection has long been a hotspot research, it is difficult to discover the trending topics with high contextual meaning because the microblogs are small elements of content, such as short sentences, individual images, or video links. This paper proposes a novel approach to detect trending topics in microblog streams based on contextual search. First, burst keywords from microblog segment will be detected by calculating their frequencies and average growth rates; then related tweets are clustered as a document based on a contextual search method; finally, top-k keywords in the document are regarded as the trending topic based on a TF-IDF method. The experiment results show that the proposed approach can detect trending topics with high contextual meaning and accuracy.
Communicating Processes with Data for Supervisory Coordination

We employ supervisory controllers to safely coordinate high-level discrete(-event) behavior of distributed components of complex systems. Supervisory controllers observe discrete-event system behavior, make a decision on allowed activities, and communicate the control signals to the involved parties. Models of the supervisory controllers can be automatically synthesized based on formal models of the system components and a formalization of the safe coordination (control) requirements. Based on the obtained models, code generation can be used to implement the supervisory controllers in software, on a PLC, or an embedded (micro)processor. In this article, we develop a process theory with data that supports a model-based systems engineering framework for supervisory coordination. We employ communication to distinguish between the different flows of information, i.e., observation and supervision, whereas we employ data to specify the coordination requirements more compactly, and to increase the expressivity of the framework. To illustrate the framework, we remodel an industrial case study involving coordination of maintenance procedures of a printing process of a high-tech Oc´e printer.
Improved PNIPAAm-Hydrogel Photopatterning by Process Optimisation with Respect to UV Light Sources and Oxygen Content

Poly-N-isopropylacrylamide (PNIPAAm) hydrogels, known for their sensor and actuator capabilities, can be photolithographically structured for microsystem applications. For usage in microsystems, the preparation, and hence the characteristics, of these hydrogels (e.g., degree of swelling, size, cooperative diffusion coefficient) are key features, and have to be as reproducible as possible. A common method of hydrogel fabrication is free radical polymerisation using a thermally-initiated system or a photoinitiator system. Due to the reaction quenching by oxygen, the polymer solution has to be rinsed with protective inert gases like nitrogen or argon before the polymerisation process. In this paper, we focus on the preparation reproducibility of PNIPAAm hydrogels under different conditions, and investigate the influence of oxygen and the UV light source during the photopolymerisation process. The flushing of the polymer solution with inert gas is not sufficient for photostructuring approaches, so a glove box preparation resulting in better quality. Moreover, the usage of a wide-band UV light source yields higher reproducibility to the photostructuring process compared to a narrow-band UV source.
Partially reversible data hiding with pure message communications over state-dependent channels ∗

In this paper, we analyze the reversibility of data hiding techniques based on random binning as a by-product of pure message communications. We demonstrate the capabilities of unauthorized users to perform hidden data removal using solely a signal processing approach based on optimal estimation as well as consider reversibility on the side of authorized users who have knowledge of the key used for the message hiding. In fact, we show that knowledge of the auxiliary random variable, used in the codebook construction of random binning techniques, is sufficient to perform the optimal reversibility procedure. We compare the optimal rate-distortion region results obtained using more involved coding strategies based on hybrid random binning with those utilizing uncoded transmission. This analysis is performed for the generalized Gel’fand-Pinsker formulation, Gaussian Costa setup and particular practical schemes based on structured codebooks. Finally, we consider some related open issues and possible future extensions. 1 Further information: Send correspondence to S. Voloshynovskiy ∗ Part of this paper appeared as S. Voloshynovskiy, O. Koval, E. Topak, J.E. Vila-Forcen, P. Comesana, and T. Pun. On reversibility of random binning techniques: multimedia perspectives. In 9th Conference on Communications and Multimedia Security, CMS 2005, Lecture Notes in Computer Science. SpringerVerlag Heidelberg, September 2005.
Multiple Aesthetic Attribute Assessment by Exploiting Relations Among Aesthetic Attributes

Current research of aesthetic assessment for images assumes one aesthetic score or one aesthetic label for an image, ignoring the relations of multiple aesthetic-related attributes. However, most images can be described by multiple aesthetic attributes simultaneously. Therefore, in this paper, we propose multiple aesthetic attribute prediction and classification by modeling relations among aesthetic attributes through Bayesian Networks (BN). In order to realize continuous aesthetic attribute prediction, each aesthetic attribute is represented by a three-node BN, including the discretized aesthetic attribute label, the predicted aesthetic attribute score, and the measurement of the aesthetic attribute score. In addition, the relations among multiple aesthetic attributes are modeled by another discrete BN, whose structure and conditional probabilities are learned from the training data. The attribute measurements are obtained by an existing image-driven regression method. With the learned BN, we infer the true discrete label and continuous score for each attribute by combining the relations among attributes with the previously obtained measurements. Experiments on the Memorability dataset show the superiority of our proposed approach to current image-driven methods for both multiple continuous aesthetic attribute score prediction and multiple discrete aesthetic attribute label classification, indicating the effectiveness of the captured relations for aesthetic quality assessment.
Thyroid Hormone and the Neuroglia: Both Source and Target

Thyroid hormone plays a crucial role in the development and function of the nervous system. In order to bind to its nuclear receptor and regulate gene transcription thyroxine needs to be activated in the brain. This activation occurs via conversion of thyroxine to T3, which is catalyzed by the type 2 iodothyronine deiodinase (D2) in glial cells, in astrocytes, and tanycytes in the mediobasal hypothalamus. We discuss how thyroid hormone affects glial cell function followed by an overview on the fine-tuned regulation of T3 generation by D2 in different glial subtypes. Recent evidence on the direct paracrine impact of glial D2 on neuronal gene expression underlines the importance of glial-neuronal interaction in thyroid hormone regulation as a major regulatory pathway in the brain in health and disease.
Recovering Latent Signals From a Mixture of Measurements Using a Gaussian Process Prior

In sensing applications, sensors cannot always measure the latent quantity of interest at the required resolution, sometimes they can only acquire a blurred version of it due the sensor's transfer function. To recover latent signals when only noisy mixed measurements of the signal are available, we propose the Gaussian process mixture of measurements (GPMM), which models the latent signal as a Gaussian process (GP) and allows us to perform Bayesian inference on such signal conditional to a set of noisy mixture of measurements. We describe how to train GPMM, that is, to find the hyperparameters of the GP and the mixing weights, and how to perform inference on the latent signal under GPMM; additionally, we identify the solution to the underdetermined linear system resulting from a sensing application as a particular case of GPMM. The proposed model is validated in the recovery of three signals: A smooth synthetic signal, a real-world heart-rate time series and a step function, where GPMM outperformed the standard GP in terms of estimation error, uncertainty representation, and recovery of the spectral content of the latent signal.
Enhancing sun safety in young women: The relative impact of format and temporal framing on beliefs and behaviour

Abstract Malignant melanoma (MM) is mainly attributable to UV exposure and research indicates that maladaptive sun safe beliefs and behaviour need to be changed in order to help reduce MM prevalence in the most at-risk subset of the UK population; fair-skinned young women. Sun safety interventions which are personalised and appearance-based have been found effective at improving sun safe beliefs and behaviour. To date, no research has explored whether the effectiveness of these interventions can be improved by varying both their format of presentation and temporal framing. In this experimental study, UK fair-skinned young women (n = 65) aged between 16 and 25 rated their sun safe beliefs and behavioural cognitions after being exposed to personalised appearance-based information which varied in terms of format (text vs visual) and temporal framing (immediate vs future). Their sun safe behaviour was also observed. The visual format used the Aprilage® digital sun ageing programme. The results showed that following the visual format intervention participants had significantly lower perceptions of the skin’s ability to heal, and higher levels of observed sun safe behaviour in the form of taking a sunscreen sample and a sun safety educational leaflet compared to those who received the text intervention. No significant effect of temporal framing was found. The results suggest that a visual, personalised, appearance-based intervention may be an effective form of sun safety promotion for young women in the UK.