Miracle-dz/UniFAR-FTUs huggingface dataset:
Cost Pass-Through in Differentiated Product Markets: The Case of U.S. Processed Cheese

In this paper, we estimate a mixed logit model for demand in the U.S. processed cheese market. The estimates are used to determine pass-through rates of cost changes under different behavioral regimes. We find that, under collusion, the pass-through rates for all brands fall between 21% and 31% while, under Nash-Bertrand price competition, the range of pass-through rates is between 73% and 103%. The mixed logit model provides a more flexible framework for studying pass-through rates than the logit model since the curvature of the demand functions depends upon the empirical distribution of consumer types.
An Efficient Distributed Routing Algorithm for Delay Constrained Multicast

For dynamic QoS multicast routing, efficient handling of node’s join and leave is an important problem. This paper addresses the problem of optimally connecting a new node to an existing multicast tree under sourceto-destination delay and inter-destination delay variation constraints (MRDC-JOIN). We assume a QoS framework where a delay dependent cost function is associated with each network link. After showing that MRDC-JOIN is NPcomplete, we present centralized and distributed versions of the algorithm MRDC-JOIN. By means of simulation, we show that the algorithm is capable of handling join requests efficiently in terms of success rate and tree cost in comparison with a centralized static multicast routing algorithm [1].
DNA Damage Response Is Involved in the Developmental Toxicity of Mebendazole in Zebrafish Retina

Intestinal helminths cause iron-deficiency anemia in pregnant women, associated with premature delivery, low birth weight, maternal ill health, and maternal death. Although benzimidazole compounds such as mebendazole (MBZ) are highly efficacious against helminths, there are limited data on its use during pregnancy. In this study, we performed in vivo imaging of the retinas of zebrafish larvae exposed to MBZ, and found that exposure to MBZ during 2 and 3 days post-fertilization caused malformation of the retinal layers. To identify the molecular mechanism underlying the developmental toxicity of MBZ, we performed transcriptome analysis of zebrafish eyes. The analysis revealed that the DNA damage response was involved in the developmental toxicity of MBZ. We were also able to demonstrate that inhibition of ATM significantly attenuated the apoptosis induced by MBZ in the zebrafish retina. These results suggest that MBZ causes developmental toxicity in the zebrafish retina at least partly by activating the DNA damage response, including ATM signaling, providing a potential adverse outcome pathway in the developmental toxicity of MBZ in mammals.
Sensitivity analysis and tuning for active safety systems

Active safety systems utilize information about the vehicle's state and possibly the surrounding environment to assist the driver if a traffic situation is considered hazardous. The decision to assist the driver is based on sensors that are more or less subjected to errors. In this paper, we study the influence of input perturbations on decision functions in active safety systems. We present a framework for evaluation of system performance, specification of input requirements and decision function tuning. By introducing a robustness measure, describing the robustness to error for the decision function, we derive efficient methods for analyzing the system performance. The framework is demonstrated on experimental data.
Identification of informative reviews enhanced by dependency parsing and sentiment analysis

The processing and analysis of the customer reviews have been received increasing attention recently. Filtering the noise and useless sentences from the reviews is the first step for this work. In this paper a new informative review identification method is proposed based on dependency parsing and sentiment analysis. These two linguistic concepts can be used to extract effective features from the sentences in the reviews. The framework for identifying informative reviews is set up, which include two stages: feature extraction and classifier learning. The experiment results on the Amazon product reviews show that the performance of the classification has been improved significantly. The method proposed in this paper can be used as a preprocessing in various review analysis and information extraction.
Dual Pricing and the Information Deficit in Electronic Markets

We model the availability of product information in Internet-based markets, and explain the underlying causes for the phenomenon of less than perfect information available to consumers of products and services in these markets. We use Salop’s model of product differentiation and explore the conditions under which sellers make horizontal information available to buyers. We demonstrate that under broad conditions, if sellers are unable to charge buyers for product information, in the presence of even very small costs associated with the dissemination of information they will choose to provide just enough information to distinguish their products from their competitors’ and no more than that. Furthermore, we show that a market for product information can partly correct this inefficiency and predict that product information will begin to be traded once an appropriate micro-transaction payment scheme becomes available. It follows from our analysis that allowing sellers to charge an information rent leads to more efficient markets.
Twitter Hash Tag Prediction Algorithm

Social media has demonstrated quick growth, in both directions of becoming the most popular activities in internet and of attracting scientific researchers to get better insights into the understanding into the underlying sociology. Real time micro-blogging sites such as Twitter, Flickr and Delicious use tags as an alternative to traditional forms of navigation and hypertext browsing. The tag system of those micro-blogging sites has unique features in that they change so frequently that it is hard to identify the number of clusters and so effectively carry out classification when new tags can come out at any time. In this paper, we propose to use Euclidean distance between points as the measurement of their similarity. Our method has advantages in easy data storage and easy accommodation to personal settings. In experiment, we compare our model with other classification functions and show that our model maintains a false positive rate lower than 15%. Our work is relevant for researchers interested in navigating of emergent hypertext structures, and for engineers seeking to improve the navigability of social tagging systems.
The Net for the Graphs : Towards Webgenre Representation for Corpus Linguistic Studies

In recent years, the Web has become increasingly significant for corpus linguistic research (Baroni and Bernardini 2004; Keller and Lapata 2003; Kilgarriff and Grefenstette 2003; Resnik and Smith 2003; Santamaŕıa et al. 2003). On the one hand, it contains a vast amount of hypertext documents of newly emerging document types (e.g., conference websites, corporate sites, electronic encyclopedias, hotlists, sites of online shops, (personal, academic) home pages, weblogs etc.). On the other hand, the Web has become accepted as a common platform for information exchange so that one can find instances of almost any type of electronic text imaginable. This, in theory, makes the Web the source of choice when large corpora for studying language varieties are needed. But it also makes it the source of choice when studying the emergence and evolvement of hypertext types. The reason for this assessment is also the main source of difficulties one has to face following this line of research: Web-based hypertext authoring mostly utilizes languages, as for example HTML, CSS and related “standards”, in spite of their well-known deficits regarding the separation of structure, content and form. Moreover, these languages do not at all standardize the content-based, functional structuring of websites, neither with respect to the internal structuring of constitu-
DECOMPOSITION OF INFLECTED WORDS IN A SECOND LANGUAGE

German participles offer a distinction between regular forms that are suffixed with –t and do not exhibit any stem changes and irregular forms that all have the ending –n and sometimes undergo (largely unpredictable) stem changes. This article reports the results from a series of psycholinguistic experiments (acceptability judgments, lexical decision, and masked priming) that investigate regular and irregular participle forms in adult native speakers of German in comparison to advanced adult second language (L2) learners of German with Polish as their first language (L1). The most striking L1-L2 contrasts were found for regular participles. Although the L1 group’s performance was influenced by the combinatorial structure of regular participle forms, this was not the case for the L2 group. These findings suggest that adult L2 learners are less sensitive to morphological structure than native speakers and rely more on lexical storage than on morphological parsing during processing.
The effect of pegylated human recombinant leptin (PEG-OB) on neuroendocrine adaptations to semi-starvation in overweight men.

OBJECTIVE Starvation induces a complex neuroendocrine response in humans thought to have evolved to defend against reduced energy intake. The drop in leptin levels observed during fasting has been implicated as a factor that triggers this adaptive response. To explore this hypothesis, we executed a randomized, double-blind, placebo-controlled study to investigate whether elevated leptin levels using long-acting pegylated human recombinant leptin (PEG-OB) influenced the neuroendocrine responses to semi-starvation in human subjects. DESIGN Twenty-four overweight male subjects (mean+/-s.e.m.; 34.8+/-1.3 yrs; 28.8+/-0.5 kg/m(2)) were prescribed a very low energy diet (2.1 MJ/day) to induce a state of semi-starvation for the next 46 days. In addition, all subjects received a weekly treatment of 80 mg PEG-OB or matching placebo. Hormone measurements were performed throughout the study period and included 5-h frequent hormone samplings and 24-h urine collections. RESULTS Weekly subcutaneous administration of PEG-OB led to significant additional weight loss (2.8 kg) but it did not reverse the fasting-induced changes in the thyroid, corticotropic, somatotropic axes and sympathetic nervous system activity. However, after adjustment for weight loss, the drop in mean luteinizing hormone levels was attenuated in the PEG-OB group compared with the placebo group. CONCLUSIONS These results suggest that a reduced level of leptin accompanying food restriction might be a component of the fasting-induced neuroendocrine inhibition of the human reproductive axis.
A Matlab toolbox for optimization over symmetric cones

SeDuMi is an add-on for MATLAB, which lets you solve optimization problems with linear, quadratic and semidefiniteness constraints. It is possible to have complex valued data and variables in SeDuMi. Moreover, large scale optimization problems are solved efficiently, by exploiting sparsity. This paper describes how to work with this toolbox.
Progress on model checking robot behaviour

We model systems that involve a learning robot which interacts with obstacles in a static environment. Our models are speciﬁed in Promela with a view to verifying them using SPIN [2]. Because of the complex nature of these systems our initial models have intractable state-spaces: we aren’t able to model check them. Last year [4] we introduced an abstraction technique to greatly reduce the state-space of our models. One of the challenges we now face is to prove that our abstraction technique is correct i.e., it preserves the properties of concern.
Extended chirp scaling algorithm for air- and spaceborne SAR data processing in stripmap and ScanSAR imaging modes

Presents a generalized formulation of the extended chirp scaling (ECS) approach for high precision processing of air- and spaceborne SAR data. Based on the original chirp scaling function, the ECS algorithm incorporates a new azimuth scaling function and a subaperture approach, which allow an effective phase-preserving processing of ScanSAR data without interpolation for azimuth geometric correction. The azimuth scaling can also be used for automatic azimuth coregistration of interferometric image pairs which are acquired with different sampling distances. Additionally, a novel range scaling formulation is proposed for automatic range coregistration of interferometric image pairs or for improved robustness for the processing of highly squinted data. Several simulation and processing results of air- and spaceborne SAR data are presented to demonstrate the validity of the proposed algorithms.
Philadelphia-negative chronic myeloproliferative neoplasms

Chronic myeloproliferative diseases without the Philadelphia chromosome marker (Ph-), although first described 60 years ago, only became the subject of interest after the turn of the millennium. In 2001, the World Health Organization (WHO) defined the classification of this group of diseases and in 2008 they were renamed myeloproliferative neoplasms based on morphological, cytogenetic and molecular features. In 2005, the identification of a recurrent molecular abnormality characterized by a gain of function with a mutation in the gene encoding Janus kinase 2 (JAK2) paved the way for greater knowledge of the pathophysiology of myeloproliferative neoplasms. The JAK2 mutation is found in 90-98% of polycythemia vera and in about 50% essential thrombocytosis and primary myelofibrosis. In addition to the JAK2 mutation, other mutations involving TET2 (ten-eleven translocation), LNK (a membrane-bound adaptor protein); IDH1/2 (isocitrate dehydrogenase 1/2 enzyme); ASXL1 (additional sex combs-like 1) genes were found in myeloproliferative neoplasms thus showing the importance of identifying molecular genetic alterations to confirm diagnosis, guide treatment and improve our understanding of the biology of these diseases. Currently, polycythemia vera, essential thrombocytosis, myelofibrosis, chronic neutrophilic leukemia, chronic eosinophilic leukemia and mastocytosis are included in this group of myeloproliferative neoplasms, but are considered different situations with individualized diagnostic methods and treatment. This review updates pathogenic aspects, molecular genetic alterations, the fundamental criteria for diagnosis and the best approach for each of these entities.
Cross-lingual lexical language discovery from audio data using multiple translations

Zero-resource Automatic Speech Recognition (ZR ASR) addresses target languages without given pronunciation dictionary, transcribed speech, and language model. Lexical discovery for ZR ASR aims to extract word-like chunks from speech. Lexical discovery benefits from the availability of written translations in another source language. In this paper, we improve lexical discovery even more by combining multiple source languages. We present a novel method for combining noisy word segmentations resulting in up to 11.2% relative F-score gain. When we extract word pronunciations from the combined segmentations to bootstrap an ASR system, we improve accuracy by 9.1% relative compared to the best system with only one translation, and by 50.1% compared to monolingual lexical discovery.
Decoding the Content of Delayed Intentions

Rostrolateral prefrontal cortex (RLPFC) plays a key role in our ability to postpone the execution of intended behaviors until after another activity has been performed. However, it is poorly understood in computational terms. One crucial question is whether RLPFC represents the content of delayed intentions or plays a nonspecific role. In this human functional magnetic resonance imaging study (n = 32), RLPFC was active while participants stored delayed intentions during a distracting ongoing task. Multivariate analysis showed that the intended cue for future action and the intended behavior could be decoded from distinct posterior brain regions. However, the content of intentions could not be decoded from RLPFC itself. Functional connectivity analysis showed that RLPFC increased its coupling with content-representing regions during intention storage. Furthermore, trials with relatively high RLPFC activity were associated with enhanced decoding. Thus, RLPFC may enable realization of delayed intentions via interactions with posterior brain regions, which represent their content.
Global Registration of Subway Tunnel Point Clouds Using an Augmented Extended Kalman Filter and Central-Axis Constraint

Because tunnels generally have tubular shapes, the distribution of tie points between adjacent scans is usually limited to a narrow region, which makes the problem of registration error accumulation inevitable. In this paper, a global registration method is proposed based on an augmented extended Kalman filter and a central-axis constraint. The point cloud registration is regarded as a stochastic system, and the global registration is considered to be a process that recursively estimates the rigid transformation parameters between each pair of adjacent scans. Therefore, the augmented extended Kalman filter (AEKF) is used to accurately estimate the rigid transformation parameters by eliminating the error accumulation caused by the pair-wise registration. Moreover, because the scanning range of a terrestrial laser scanner can reach hundreds of meters, a single scan can cover a tunnel segment with a length of more than one hundred meters, which means that the central axis extracted from the scan can be employed to control the registration of multiple scans. Therefore, the central axis of the subway tunnel is first determined through the 2D projection of the tunnel point cloud and curve fitting using the RANSAC (RANdom SAmple Consensus) algorithm. Because the extraction of the central axis by quadratic curve fitting may suffer from noise in the tunnel points and from variations in the tunnel, we present a global extraction algorithm that is based on segment-wise quadratic curve fitting. We then derive the central-axis constraint as an additional observation model of AEKF to optimize the registration parameters between each pair of adjacent scans. The proposed approach is tested on terrestrial point clouds that were acquired in a subway tunnel. The results show that the proposed algorithm is capable of improving the accuracy of aligning multiple scans by 48%.
Stereo-polarimetric measurement of pair of mueller images for three dimensional partial reconstruction

Stereoscopy is well adapted for performing three dimensional partial reconstruction. Classical stereoscopy uses conventional scalar images for representing three dimensional objects. Thus all the necessary tasks (segmentation, classification, edge detection, correspondence matching) are performed on the classical scalar images. For some particular cases like improperly illuminated scenes, camera blindness by a bright edge response and for transparent objects detection, scalar images do not provide us with the reliable foundation from which precise three dimensional partial reconstruction can be performed (bad segmentation, hidden contour, undetected region, false classification). The object of this paper is to show how, very simply, by controlling the polarization state of the imaging system we can overcome the above mentioned problems. On the conceptual level, the contribution of polarimetry to the stereoscopy will be high-lighted by a quantitative analysis of the precision of three-dimensional reconstruction of objects.
Intergenerational Equity, Social Discount Rates and Global Warming

Abstract This article is about the logic underlying social discount rates. We argue thatthese rates are not ethical raw material, but are derived from the more fundamentalnotion of justice among generations. A number of approaches to the concept ofintergenerational justice are discussed, and it is argued that the most compellingformulation available to us is the one long been in use among economists, namely, theRamsey-Koopmans theory. This theory advocates that investment projects having long-run effects should be subjected to the same conceptual treatment as those that affectonly the near future. We show that social discount rates depend on the numeraire, andthat methods of estimating them depend on the institutional setting within which socialcost benefit analysis is assumed to be undertaken. We also show that it is incorrect toadvocate project-specific discount rates as a way of conserving environmentalresources.Social discount rates have universally been taken to be positive, on grounds thatthe rate of return on investment is positive. But if consumption and productionactivities give rise to environmental pollution as a by-product, the social rate of returnon investment could be zero even when the private rate is positive; at the very least, thesocial rate would be lower than the private rate. The current practice among most globalenergy modellers of relying exclusively on (risk-free) market rates of return forestimating optimal carbon taxes is conceptually faulty. In the context of a formal modelof environmental pollution we show how, even along an optimal programme, socialrates of discount can be zero. We also demonstrate that in certain institutional settings,social discount rates can be negative.
Application of Regenerating Codes for Fault Tolerance in Distributed Storage Systems

Recently, regenerating codes, a special network coding technique, were discovered for fault-tolerant storage systems with the promising advantage of efficient data recovery in the case of a single node failure and replacement (regeneration case). From the perspective of coding theory, regenerating codes are extensively studied, but there exists no reference on how to implement these codes in storage systems. We provide a comparison of Reed-Solomon codes and regenerating codes from an implementation point of view. The comparison includes the experimental evaluation of the encoding and the regeneration data throughput.
A Process of Continuous Innovation: Centralizing Analytics at Caesars

With more than 70,000 employees and casino resorts on four continents the company primarily operates under the Harrahs, Caesars and Horseshoe brands, in addition to owning the London Clubs casinos and the World Series of Poker Caesars has built its reputation on knowing its customer base. It builds this knowledge by using analytics to create a rich customer experience, marketing to customers based not only on their preferences but their actions while at a Caesars property, including whether they've had a winning day or a losing one. Over the past several years, Caesars has undergone a reorganization, in part to centralize its analytics functions. The goal: to build a deeper understanding not only of customers, but also of operations everything from food and beverage analytics to labor analytics. Ruben Sigala, chief analytics officer at Caesars, talks with MIT Sloan Management Review contributing editor Renee Boucher Ferguson about that process, some valuable lessons learned, and where innovation and intuition play a role.