nils-herrmann/clean_scirepeval huggingface dataset:
Competition and the Welfare Gains from Transportation Infrastructure: Evidence from the Golden Quadrilateral of India

Cada ano se invierte una significativa cantidad de recursos en mejorar las infraestructuras de transporte de los paises en desarrollo. En este articulo investigamos los efectos de un gran proyecto de este tipo: el Golden Quadrilateral de la India. Para ello, utilizamos un modelo de comercio interno con margenes variables. En contraste con la literatura previa, el modelo incorpora diversos canales a traves de los cuales la infraestructura de transporte afecta al bienestar. En particular, el modelo tiene en cuenta las ganancias provenientes de la eficiencia en la asignacion de recursos en la economia. Calibramos el modelo para el sector manufacturero de la India y encontramos que las ganancias reales del producto ascienden al 2,7 Ademas, la mejora en la asignacion explica el 7,4 de dichas ganancias. La importancia de este canal varia en gran medida por Estados, pudiendo explicar hasta el 18 de las ganancias en algunos de ellos. El resto de la mejora en el bienestar se explica por cambios en los ingresos laborales, la eficiencia productiva y los margenes medios, que afectan a los terminos de intercambio de los Estados.
Single Stage Three Phase Differential Mode Buck Boost Inverters With Continuous Input Current for PV Applications
Venue: IEEE Transactions on Power Electronics

Differential mode buck boost inverters have merits such as reduced switch number, ability to provide voltages higher or lower than the input voltage magnitude, improved efficiency, reduced cost and size, and increased power density, especially in low power applications. There are five buck boost inverters that can provide flexible output voltage without the need of a large electrolytic input side capacitor, which degrades the reliability of inverters. The continuous input current of these inverters is appropriate for maximum power point tracking operation in photovoltaic and fuel cells applications. Three of the five inverters can be isolated with high frequency link transformers where the common mode leakage current can be mitigated. However, the performance and control of such converters have not been discussed in detail. In this paper, the five possible single stage three phase differential mode buck boost inverters with continuous input current are investigated and compared in terms of total losses, maximum ripple current, total harmonic distortion, and device and passive element ratings. In addition, the possible methods are presented for eliminating the input third order harmonic current, resulting from the stored energy in the passive elements, as well as the output second order harmonic currents. The ability for isolating the input and output sides of the inverters with a small high frequency transformers is discussed. A changeable terminal 2.5 kW bidirectional inverter is used to validate the design flexibility of the inverter topologies, when digital signal processor controlled.
Recovery of Bio Oil from Industrial Food Waste by Liquefied Dimethyl Ether for Biodiesel Production

The development of new energy sources has become particularly important from the perspective of energy security and environmental protection. Therefore, the utilization of waste resources such as industrial food wastes (IFWs) in energy production is expected. The central research institute of electric power industry (CRIEPI, Tokyo, Japan) has recently developed an energy saving oil extraction technique involving the use of liquefied dimethyl ether (DME) which is an environmentally friendly solvent. In this study, three common IFWs (spent coffee grounds, soybean, and rapeseed cakes) were evaluated with respect to oil yield for biodiesel fuel (BDF) production by the DME extraction method. The coffee grounds were found to contain 16.8% bio oil, whereas the soybean and rapeseed cakes contained only approximately 0.97% and 2.6% bio oil, respectively. The recovered oils were qualitatively analysed by gas chromatography mass spectrometry. The properties of fatty acid methyl esters derived from coffee oil, such as kinematic viscosity, pour point, and higher heating value (HHV) were also determined. Coffee grounds had the highest oil content and could be used as biofuel. In addition, the robust oil extraction capability of DME indicates that it may be a favourable alternative to conventional oil extraction solvents.
Bidirectional linguistic change in rural child and adolescent language in Syria

Investigating the spread of the urban feature the glottal stop in place of the rural voiceless uvular stop [q] in the speech of rural children and adolescents in the Syrian village, Oyoun Al Wadi, a bidirectional linguistic change is observed. Girls retain their mothers' urban feature in preadolescence and adolescence; boys who initially acquire the urban feature start switching to the rural feature around age eight and increase their use of this feature with age. Thus, the observed variation a nd changes are gender and age related and result from different meanings associated with urban and rural sounds. Preadolescence emerges as the period in which kids are emotionally involved in building a social identity, indicating early development of soc iolinguistic competence.
Audio Visual Speech Recognition Using Bimodal Trained Bottleneck Features for a Person with Severe Hearing Loss
Venue: INTERSPEECH

In this paper, we propose an audio visual speech recognition system for a person with an articulation disorder resulting from severe hearing loss. In the case of a person with this type of articulation disorder, the speech style is quite different from those of people without hearing loss that a speaker independent acoustic model for unimpaired persons is hardly useful for recognizing it. The audio visual speech recognition system we present in this paper is for a person with severe hearing loss in noisy environments. Although feature integration is an important factor in multimodal speech recognition, it is difficult to integrate efficiently because those features are different intrinsically. We propose a novel visual feature extraction approach that connects the lip image to audio features efficiently, and the use of convolutive bottleneck networks (CBNs) increases robustness with respect to speech fluctuations caused by hearing loss. The effectiveness of this approach was confirmed through word recognition experiments in noisy environments, where the CBN based feature extraction method outperformed the conventional methods.
Double machine learning for treatment and causal parameters

Most modern supervised statistical/machine learning (ML) methods are explicitly designed to solve prediction problems very well. Achieving this goal does not imply that these methods automatically deliver good estimators of causal parameters. Examples of such parameters include individual regression coffiecients, average treatment e ffects, average lifts, and demand or supply elasticities. In fact, estimators of such causal parameters obtained via naively plugging ML estimators into estimating equations for such parameters can behave very poorly. For example, the resulting estimators may formally have inferior rates of convergence with respect to the sample size n caused by regularization bias. Fortunately, this regularization bias can be removed by solving auxiliary prediction problems via ML tools. Speci ficially, we can form an efficient score for the target low dimensional parameter by combining auxiliary and main ML predictions. The efficient score may then be used to build an efficient estimator of the target parameter which typically will converge at the fastest possible 1/v n rate and be approximately unbiased and normal, allowing simple construction of valid con fidence intervals for parameters of interest. The resulting method thus could be called a "double ML" method because it relies on estimating primary and auxiliary predictive models. Such double ML estimators achieve the fastest rates of convergence and exhibit robust good behavior with respect to a broader class of probability distributions than naive "single" ML estimators. In order to avoid overfi tting, following  our construction also makes use of the K fold sample splitting, which we call cross fitting. The use of sample splitting allows us to use a very broad set of ML predictive methods in solving the auxiliary and main prediction problems, such as random forests, lasso, ridge, deep neural nets, boosted trees, as well as various hybrids and aggregates of these methods (e.g. a hybrid of a random forest and lasso) We illustrate the application of the general theory through application to the leading cases of estimation and inference on the main parameter in a partially linear regression model and estimation and inference on average treatment eff ects and average treatment e ffects on the treated under conditional random assignment of the treatment. These applications cover randomized control trials as a special case. We then use the methods in an empirical application which estimates the e ffect of 401(k) eligibility on accumulated financial assets.
Robust Pose Recognition Using Deep Learning
Venue: CVIP

Current pose estimation methods make unrealistic assumptions regarding the body postures. Here, we seek to propose a general scheme which does not make assumptions regarding the relative position of body parts. Practitioners of Indian classical dances such as Bharatnatyam often enact several dramatic postures called Karanas. However, several challenges such as long flowing dresses of dancers, occlusions, change of camera viewpoint, poor lighting etc. affect the performance of state of the art pose estimation algorithms [1, 2] adversely. Body postures enacted by practitioners performing Yoga also violate the assumptions used in current techniques for estimating pose. In this work, we adopt an image recognition approach to tackle this problem. We propose a dataset consisting of 864 images of 12 Karanas captured under controlled laboratory conditions and 1260 real world images of 14 Karanas obtained from Youtube videos for Bharatnatyam. We also created a new dataset consisting of 400 real world images of 8 Yoga postures. We use two deep learning methodologies, namely, convolutional neural network (CNN) and stacked auto encoder (SAE) and demonstrate that both these techniques achieve high recognition rates on the proposed datasets.
Annexure

Sir/Madam, I am a research scholar at the Faculty of Commerce and Management, Jiwaji University and conducting a research on "Antecedents of Impulse Purchase with special reference to Trade Fairs" This questionnaire is the tool for measurement of research work being conducted and is purely for research purpose; hence all the information given will be kept confidential. You are gently requested to present information as absolute as possible and help it to be of high validity. Thank you very much for your cooperation.
Combined gestures and auditory verbal training for comprehension and production of verbs in deaf children

An important factor determining the efficacy of speech therapy for children with severe hearing loss is the type and the method of educating children in the use of speech language items. Given the shortage of golden time for language learning, it is necessary to use efficient speech therapy approaches for improving the language of the child. The aim of this study was to investigate the effect of adding gestures to auditory verbal training (AVT) in speech therapy for children with severe hearing loss.  In this double blinded clinical trial, 66 children with severe hearing loss were randomly assigned to two groups of 33 subjects. Receptive and expressive language competence for some simple Persian verbs was evaluated by the Newsha test. The AVT was accompanied by gesture for the intervention group and no accompanying gesture for the control group. Simple verbs include fifty early action words such as sit, run, hold, and go.  In both the experimental and control groups, a significant difference was observed for receptive language of simple verbs before and after the intervention (P 0.001, P 0.045) However, no significant difference was found before the intervention (P 0.532) there was a significant difference between mean receptive score of the two groups after the intervention (P 0.032)  Adding gestures to AVT significantly changed the mean expressive score in 2 3 year old children with severe hearing loss. But, both the synthetic approach and the AVT had the same degree of positive effect for education of receptive language of simple verbs for these children.
INFLUENCE OF PRODUCT PLACEMENT ON CONSUMER BEHAVIOR: THE MEDIATING ROLES OF CONSUMER RECOGNITION WITH PROGRAM CELEBRITY AND ETHICAL PERCEPTIONS TOWARDS PRODUCT PLACEMENT THAT LEADS TO CONSUMER PURCHASE INTENTION

Product Placement is nowadays popular tool of advertisement. It is very difficult to place the product and synchronize it with the natural environment so that consumer is acknowledged and has positive vibes towards the placed products brand.  Perception towards ethics of Product Placement, Consumer Recognition with Program Celebrity that leads to Consumer Purchase Intention.  The study is based on 600 consumers who take part in the study and Quantitative Research methods are used to analyze the results. SPSS 20.0 is used for the purpose of data analysis in this study.  The results showed that there is a positive relationship between these variables Product Placement, Consumer Perception towards ethics of Product Placement, Consumer Recognition with Program Celebrity that leads to Consumer Purchase Intention and Consumer Purchase Intention.  This study recommends Brands and their Product Placement strategists to follow the ethical approach in Placing their Product in the movie or Television series use the Celebrity attachment with the Product in a way that there is a Positive affect on the Consumer and our goalto enhance Consumer Purchase Intention is accomplished Keywords: Product placement, Program Celebrity, Ethical Perceptions, Purchase intention
Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology
Venue: Comput. Hum. Behav.

Mobile payment is receiving growing attention globally, from consumers to merchants, as an alternative to using cash, check, or credit cards. The potential of this technology is enormous. This study aims to identify the main determinants of mobile payment adoption and the intention to recommend this technology. We advance the body of knowledge on this subject by proposing an innovative research model that combines the strengths of two well known theories; the extended unified theory of acceptance and use of technology (UTAUT2) with the innovation characteristics of the diffusion of innovations (DOI) with perceived security and intention to recommend the technology constructs. The research model was empirically tested using 301 responses from an online survey conducted in a European country, Portugal. Data was analyzed using the structured equation modeling (SEM) We found compatibility, perceived technology security, performance expectations, innovativeness, and social influence to have significant direct and indirect effects over the adoption of mobile payment and the intention to recommend this technology. The relevance of customer's intention to recommend mobile payment technology in social networks and other means of communication was also confirmed, supporting the recommendation to include it in social marketing campaigns and in future technology adoption studies. For researchers this study provides a basis for further refinement of individual models of acceptance. For practitioners, understanding the key constructs is crucial to design, refine, and implement mobile payment services, applications, and products that achieve high consumer acceptance, value, and high rates of positive recommendations in social networks.
Extracting Actions with Improved Part of Speech Tagging for Social Networking Texts
Venue: 2016 IEEE International Conference on Computer and Information Technology (CIT)

With the growing interests in social networking, the interaction of social actors evolved to a source of knowledge in which it become possible to perform context aware reasoning. The information extraction from social networking specially Twitter and Facebook is on of the problem in this area. To extract text from social networking, we need several lexical features and large scale word clustering. We attempt to expand existing tokenizer and to develop our own tagger in order to support the incorrect words currently in existence in Facebook and Twitter. Our goal in this work is to benefit of the lexical features developed for Twitter and online conversational text in previous works, to design and to develop an extraction model for constructing a huge knowledge based on actions.
Use of trimetasphere metallofullerene MRI contrast agent for the non invasive longitudinal tracking of stem cells in the lung.
Venue: Methods

Magnetic Resonance Imaging (MRI) is a commonly used, non invasive imaging technique that provides visualization of soft tissues with high spatial resolution. In both a research and clinical setting, the major challenge has been identifying a non invasive and safe method for longitudinal tracking of delivered cells in vivo. The labeling and tracking of contrast agent labeled cells using MRI has the potential to fulfill this need. Contrast agents are often used to enhance the image contrast between the tissue of interest and surrounding tissues with MRI. The most commonly used MRI contrast agents contain Gd(III) ions. However, Gd(III) ions are highly toxic in their ionic form, as they tend to accumulate in the liver, spleen, kidney and bones and block calcium channels. Endohedral metallofullerenes such as trimetallic nitride endohedral metallofullerenes (Trimetasphere(r) are one unique class of fullerene molecules where a Gd3N cluster is encapsulated inside a C80 carbon cage referred to as Gd3N@C80. These endohedral metallofullerenes have several advantages over small chelated Gd(III) complexes such as increased stability of the Gd(III) ion, minimal toxic effects, high solubility in water and high proton relativity. In this study, we describe the evaluation of gadolinium based Trimetasphere(r) positive contrast agent for the in vitro labeling and in vivo tracking of human amniotic fluid derived stem cells within lung tissue. In addition, we conducted a 'proof of concept' experiment demonstrating that this methodology can be used to track the homing of stem cells to injured lung tissue and provide longitudinal analysis of cell localization over an extended time course.
Taking Stock of the Comparative Literature on the Role of Blame Avoidance Strategies in Social Policy Reform

This article takes stock of and reviews the comparative literature on blame avoidance strategies in social policy reform to identify the conditions under which blame avoidance strategies are necessary (or not) This helps to solve the seemingly contradictory findings that blame avoidance strategies may not (always) be necessary while they are often employed. Moreover, it proposes that experimental designs help to establish the effect of blame avoidance strategies and presents an approach for assessing systematically the employment and success of blame avoidance strategies. Hereby, the article outlines a research agenda for comparative theory development.
The pedunculopontine tegmental nucleus A functional hypothesis from the comparative literature
Venue: Movement disorders official journal of the Movement Disorder Society

We present data from animal studies showing that the pedunculopontine tegmental nucleus conserved through evolution, compartmentalized, and with a complex pattern of inputs and outputs has functions that involve formation and updates of action outcome associations, attention, and rapid decision making. This is in contrast to previous hypotheses about pedunculopontine function, which has served as a basis for clinical interest in the pedunculopontine in movement disorders. Current animal literature points to it being neither a specifically motor structure nor a master switch for sleep regulation. The pedunculopontine is connected to basal ganglia circuitry but also has primary sensory input across modalities and descending connections to pontomedullary, cerebellar, and spinal motor and autonomic control systems. Functional and anatomical studies in animals suggest strongly that, in addition to the pedunculopontine being an input and output station for the basal ganglia and key regulator of thalamic (and consequently cortical) activity, an additional major function is participation in the generation of actions on the basis of a first pass analysis of incoming sensory data. Such a function rapid decision making has very high adaptive value for any vertebrate. We argue that in developing clinical strategies for treating basal ganglia disorders, it is necessary to take an account of the normal functions of the pedunculopontine. We believe that it is possible to use our hypothesis to explain why pedunculopontine deep brain stimulation used clinically has had variable outcomes in the treatment of parkinsonism motor symptoms and effects on cognitive processing.
Takotsubo Cardiomyopathy: What we have Learned in the Last 25 Years? (A Comparative Literature Review)
Venue: Current cardiology reviews

We performed a comparative literature review, to elucidate the major features of the Takotsubo (stress) cardiomyopathy (TCM) collected in last 25 years. TCM is characterized by left or biventricular apical ballooning with a clinical presentation, electrocardiographic abnormalities, and biomarker profils similar to those seen in acute myocardial infarction. Epidemiological studies have shown that TCM is more common in postmenopausal women; however exact figures are not available. The underlying aetiology is still largely undetermined. Elevated catecholamine levels, lack of estrogen, disturbed myocardial fatty acid metabolism and plaque rupture with spontaneous thrombolysis are potentially discussed mechanisms responsible for inducing a prolonged stunned myocardium. Strong emotional or physical stress is the most frequently described trigger in the literature. Therapy recommendations include appropriate antiplatelet treatment, b blockers and ACE inhibitors. The abnormal kinetics usually resolve or improve within a month and carry a favorable prognosis in most cases. However, all the suspected complications of an acute myocardial infarction, including cardiogenic shock or lethal arrhythmias, may still occur.
Expanding Comparative Literature into Comparative Sciences Clusters with Neutrosophy and Quad stage Method

By using Neutrosophy and Quad stage Method, the expansions of comparative literature include: comparative social sciences clusters, comparative natural sciences clusters, comparative interdisciplinary sciences clusters, and so on. Among them, comparative social sciences clusters include: comparative literature, comparative history, comparative philosophy, and so on; comparative natural sciences clusters include: comparative mathematics, comparative physics, comparative chemistry, comparative medicine, comparative biology, and so on. In addition, comparative literature itself can also be expanded. Under the two main categories of research and practice, comparative literature can be expanded into: comparative literature research, comparative literature practice (including comparative essay, comparative fiction, comparative poetry, comparative drama, and so on) comparative literature research and practice, and so on. This paper discusses the applications of comparative method in comparative sciences clusters and their various branches. Point out that in the existing fields of social sciences and natural sciences, many sprouts of comparative sciences clusters can be found, but a wide range of the achievements of comparative sciences clusters, still are the virgin lands to be developed.