nils-herrmann/clean_scirepeval huggingface dataset:
An analysis of the open innovation effect on firm performance

The open innovation (OI) paradigm describes how firms innovate by interacting with other organizations. Several authors found that specific OI strategies have a positive effect on economic and industrial innovation performance. Nevertheless, over search and over collaboration phenomena might reduce the OI marginal returns when a firm resorts to additional external innovation partners. This article hypothesizes that the variety of external innovation channels (search breadth) used by a firm, the extent to which a firm draws deeply from them (search depth) and the extent to which a firm collaborates through different external channels (coupled OI) are curvilinearly related with innovation performance. The empirical models are estimated using 84,919 firms from Eurostat's Community Innovation Survey, which was conducted in 2008 across European countries. The results suggest that search breadth is curvilinearly related with all the measures of innovation performance, whereas search depth is not subject to diminishing marginal returns in most cases. Furthermore, this article shows that coupled OI is curvilinearly related with the development and commercialization of radically new products. The findings of this study make several contributions both in a practical perspective, showing how managers can put into practice different OI strategies to influence innovation performance, and in a theoretical perspective, suggesting a number of recommendations for future research.
LSTM, GRU, Highway and a Bit of Attention: An Empirical Overview for Language Modeling in Speech Recognition
Venue: INTERSPEECH

Popularized by the long short term memory (LSTM) multiplicative gates have become a standard means to design artificial neural networks with intentionally organized information flow. Notable examples of such architectures include gated recurrent units (GRU) and highway networks. In this work, we first focus on the evaluation of each of the classical gated architectures for language modeling for large vocabulary speech recognition. Namely, we evaluate the highway network, lateral network, LSTM and GRU. Furthermore, the motivation underlying the highway network also applies to LSTM and GRU. An extension specific to the LSTM has been recently proposed with an additional highway connection between the memory cells of adjacent LSTM layers. In contrast, we investigate an approach which can be used with both LSTM and GRU: a highway network in which the LSTM or GRU is used as the transformation function. We found that the highway connections enable both standalone feedforward and recurrent neural language models to benefit better from the deep structure and provide a slight improvement of recognition accuracy after interpolation with count models. To complete the overview, we include our initial investigations on the use of the attention mechanism for learning word triggers.
How DNA barcoding can be more effective in microalgae identification: a case of cryptic diversity revelation in Scenedesmus (Chlorophyceae)
Venue: Scientific reports

Microalgae identification is extremely difficult. The efficiency of DNA barcoding in microalgae identification involves ideal gene markers and approaches employed, which however, is still under the way. Although Scenedesmus has obtained much research in producing lipids its identification is difficult. Here we present a comprehensive coalescent, distance and character based DNA barcoding for 118 Scenedesmus strains based on rbcL, tufA, ITS and 16S. The four genes, and their combined data rbcL tufA ITS 16S, rbcL tufA and ITS 16S were analyzed by all of GMYC, P ID, PTP, ABGD, and character based barcoding respectively. It was apparent that the three combined gene data showed a higher proportion of resolution success than the single gene. In comparison, the GMYC and PTP analysis produced more taxonomic lineages. The ABGD generated various resolution in discrimination among the single and combined data. The character based barcoding was proved to be the most effective approach for species discrimination in both single and combined data which produced consistent species identification. All the integrated results recovered 11 species, five out of which were revealed as potential cryptic species. We suggest that the character based DNA barcoding together with other approaches based on multiple genes and their combined data could be more effective in microalgae diversity revelation.
Evaluation of antioxidant properties of some naturally isolated microalgae: Identification and characterization of the most efficient strain

Antioxidant capacity and polyphenol content of both intra and extracellular constituents were investigated in five naturally isolated microalgal strains using DPPH and Folin Ciocalteu assays respectively. Three distinct solvents with different polarities including water, ethyl acetate and hexane were employed for extracting the bioactive compounds. Obtained data from DPPH assay suggest that the studied microalgal cells show significant levels of antioxidants and polyphenol compounds ranging from 14.68+ 1.36 (Oocystis pusilla) to 68.68+ 5.95 (Scenedesmus rubescens) umol Trolox g 1 and 9.62+ 1.37 (O. pusilla) to 48.57+ 3.99 (S. rubescens) mg gallic acid equivalent (GAE) g 1 respectively. Considerable connection (R2=0.9316) between two investigated factors prove that a great part of antioxidant activity in the studied microalgae are due to its phenolic compounds. Besides, the results of growth kinetic studies and composition analysis in the most efficient strain (S. rubescens) showed a great potential for antioxidant and polyphenolic compounds production in large scales.
Returns to Education in Criminal Organizations: Did Going to College Help Michael Corleone?

Is there any return to education in criminal activities? This paper is one of the first to investigate whether education has not only a positive impact on legitimate, but also on illegitimate activities. We use as a case study one of the longest running criminal corporations in history: the Italian American mafia. Its most successful members were capable businessmen, orchestrating crimes that required abilities that might be learned at school: extracting the optimal rent when setting up a racket, weighting interests against default risk when starting a loan sharking business or organizing supply chains, logistics and distribution when setting up a drug dealing system. We address this question by comparing mobsters to a variety of samples drawn from the United States 1940 Population Census, including a sample of their closest (non mobster) neighbors. We document that mobsters have one year less education than their neighbors on average. We find that mobsters have significant returns to education of 7.5 8.5 percent, which is only slightly smaller than their neighbors and 2 5 percentage points smaller than for U.S. born men or male citizens. Mobster returns were consistently about twice as large as a sample of Italian immigrants or immigrants from all origin countries. Within that, those charged with complex crimes including embezzlement and bookmaking have the highest returns. We conclude that private returns to education exist even in the illegal activities characterized by a certain degree of complexity as in the case of organized crime in mid twentieth century United States.
Large scale profiling of signalling pathways reveals an asthma specific signature in bronchial smooth muscle cells
Venue: Oncotarget

Bronchial smooth muscle (BSM) cells from asthmatic patients maintain in vitro a distinct hyper reactive "primed" phenotype, characterized by increased release of pro inflammatory factors and mediators, as well as hyperplasia and/or hypertrophy. This "primed" phenotype helps to understand pathogenesis of asthma, as changes in BSM function are essential for manifestation of allergic and inflammatory responses and airway wall remodelling.  To identify signalling pathways in cultured primary BSMs of asthma patients and non asthmatic subjects by genome wide profiling of differentially expressed mRNAs and activated intracellular signalling pathways (ISPs)  Transcriptome profiling by cap analysis of gene expression (CAGE) which permits selection of preferentially capped mRNAs most likely to be translated into proteins, was performed in human BSM cells from asthmatic (n=8) and non asthmatic (n=6) subjects and OncoFinder tool were then exploited for identification of ISP deregulations.  CAGE revealed >600 RNAs differentially expressed in asthma vs control cells (p<=0.005) with asthma samples showing a high degree of similarity among them. Comprehensive ISP activation analysis revealed that among 269 pathways analysed, 145 (p<0.05) or 103 (p<0.01) are differentially active in asthma, with profiles that clearly characterize BSM cells of asthmatic individuals. Notably, we identified 7 clusters of coherently acting pathways functionally related to the disease, with ISPs down regulated in asthma mostly targeting cell death promoting pathways and up regulated ones affecting cell growth and proliferation, inflammatory response, control of smooth muscle contraction and hypoxia related signalization.  These first time results can now be exploited toward development of novel therapeutic strategies targeting ISP signatures linked to asthma pathophysiology.
Demonstration of Protein Based Human Identification Using the Hair Shaft Proteome
Venue: PloS one

Human identification from biological material is largely dependent on the ability to characterize genetic polymorphisms in DNA. Unfortunately, DNA can degrade in the environment, sometimes below the level at which it can be amplified by PCR. Protein however is chemically more robust than DNA and can persist for longer periods. Protein also contains genetic variation in the form of single amino acid polymorphisms. These can be used to infer the status of non synonymous single nucleotide polymorphism alleles. To demonstrate this, we used mass spectrometry based shotgun proteomics to characterize hair shaft proteins in 66 European American subjects. A total of 596 single nucleotide polymorphism alleles were correctly imputed in 32 loci from 22 genes of subjects' DNA and directly validated using Sanger sequencing. Estimates of the probability of resulting individual non synonymous single nucleotide polymorphism allelic profiles in the European population, using the product rule, resulted in a maximum power of discrimination of 1 in 12,500. Imputed non synonymous single nucleotide polymorphism profiles from European American subjects were considerably less frequent in the African population (maximum likelihood ratio 11,000) The converse was true for hair shafts collected from an additional 10 subjects with African ancestry, where some profiles were more frequent in the African population. Genetically variant peptides were also identified in hair shaft datasets from six archaeological skeletal remains (up to 260 years old) This study demonstrates that quantifiable measures of identity discrimination and biogeographic background can be obtained from detecting genetically variant peptides in hair shaft protein, including hair from bioarchaeological contexts.
Tryptophan rich basic protein (WRB) mediates insertion of the tail anchored protein otoferlin and is required for hair cell exocytosis and hearing
Venue: The EMBO journal

The transmembrane recognition complex (TRC40) pathway mediates the insertion of tail anchored (TA) proteins into membranes. Here, we demonstrate that otoferlin, a TA protein essential for hair cell exocytosis, is inserted into the endoplasmic reticulum (ER) via the TRC40 pathway. We mutated the TRC40 receptor tryptophan rich basic protein (Wrb) in hair cells of zebrafish and mice and studied the impact of defective TA protein insertion. Wrb disruption reduced otoferlin levels in hair cells and impaired hearing, which could be restored in zebrafish by transgenic Wrb rescue and otoferlin overexpression. Wrb deficient mouse inner hair cells (IHCs) displayed normal numbers of afferent synapses, Ca2+ channels, and membrane proximal vesicles, but contained fewer ribbon associated vesicles. Patch clamp of IHCs revealed impaired synaptic vesicle replenishment. In vivo recordings from postsynaptic spiral ganglion neurons showed a use dependent reduction in sound evoked spiking, corroborating the notion of impaired IHC vesicle replenishment. A human mutation affecting the transmembrane domain of otoferlin impaired its ER targeting and caused an auditory synaptopathy. We conclude that the TRC40 pathway is critical for hearing and propose that otoferlin is an essential substrate of this pathway in hair cells.
Emotion malleability beliefs, emotion regulation, and psychopathology: Integrating affective and clinical science.
Venue: Clinical psychology review

Beliefs that individuals hold about whether emotions are malleable or fixed, also referred to as emotion malleability beliefs, may play a crucial role in individuals' emotional experiences and their engagement in changing their emotions. The current review integrates affective science and clinical science perspectives to provide a comprehensive review of how emotion malleability beliefs relate to emotionality, emotion regulation, and specific clinical disorders and treatment. Specifically, we discuss how holding more malleable views of emotion could be associated with more active emotion regulation efforts, greater motivation to engage in active regulatory efforts, more effort expended regulating emotions, and lower levels of pathological distress. In addition, we explain how extending emotion malleability beliefs into the clinical domain can complement and extend current conceptualizations of major depressive disorder, social anxiety disorder, and generalized anxiety disorder. This may prove important given the increasingly central role emotion dysregulation has been given in conceptualization and intervention for these psychiatric conditions. Additionally, discussion focuses on how emotion beliefs could be more explicitly addressed in existing cognitive therapies. Promising future directions for research are identified throughout the review.
Affect Aware Student Models for Robot Tutors
Venue: AAMAS

Computational tutoring systems, such as educational software or interactive robots, have the potential for great societal benefit. Such systems track and assess students' knowledge via inferential methods, such as the popular Bayesian Knowledge Tracing (BKT) algorithm. However, these methods do not typically draw on the affective signals that human teachers use to assess knowledge, such as indications of discomfort, engagement, or frustration. In this paper we present a novel extension to the BKT model that uses affective data, derived autonomously from video records of children playing an interactive story telling game with a robot, to infer student knowledge of reading skills. We find that, compared to a control group of children who played the game with only a tablet, children who interacted with an embodied social robot generated stronger affective data signals of engagement and enjoyment during the interaction. We then show that incorporating this affective data into model training improves the quality of the learned knowledge inference models. These results suggest that physically embodied, affect aware robot tutors can provide more effective and empathic educational experiences for children, and advance both algorithmic and human centered motivations for further development of systems that tightly integrate affect understanding and complex models of inference with interactive, educational robots.
Affective Computing and Sentiment Analysis
Venue: IEEE Intelligent Systems

Understanding emotions is an important aspect of personal development and growth, and as such it is a key tile for the emulation of human intelligence. Besides being important for the advancement of AI, emotion processing is also important for the closely related task of polarity detection. The opportunity to automatically capture the general public's sentiments about social events, political movements, marketing campaigns, and product preferences has raised interest in both the scientific community, for the exciting open challenges, and the business world, for the remarkable fallouts in marketing and financial market prediction. This has led to the emerging fields of affective computing and sentiment analysis, which leverage human computer interaction, information retrieval, and multimodal signal processing for distilling people's sentiments from the ever growing amount of online social data.
Emotion recognition using wireless signals
Venue: MobiCom

This paper demonstrates a new technology that can infer a person's emotions from RF signals reflected off his body. EQ Radio transmits an RF signal and analyzes its reflections off a person's body to recognize his emotional state (happy, sad, etc. The key enabler underlying EQ Radio is a new algorithm for extracting the individual heartbeats from the wireless signal at an accuracy comparable to on body ECG monitors. The resulting beats are then used to compute emotion dependent features which feed a machine learning emotion classifier. We describe the design and implementation of EQ Radio, and demonstrate through a user study that its emotion recognition accuracy is on par with state of the art emotion recognition systems that require a person to be hooked to an ECG monitor.
Cognitive control and word recognition speed influence the Stroop effect in bilinguals.
Venue: International journal of psychology Journal international de psychologie

Bilinguals have been shown to be less susceptible to Stroop interference in their first language than monolinguals, though the cause is currently being debated. In two experiments, we explored how cognitive control and word recognition contribute to the Stroop effect by contrasting cognitive control (via a Simon arrow task) word recognition speed (via a Chinese/English word recognition task) and Stroop susceptibility (via a verbal Stroop task) between proficient and non proficient Chinese English bilinguals. Compared to non proficient bilinguals, proficient bilinguals showed better cognitive control at inhibiting irrelevant information, and they were slower at recognising Chinese words but quicker at recognising English words. Critically, we also showed that proficient bilinguals showed a smaller Stroop effect than non proficient bilinguals in Chinese but a comparable Stroop effect as non proficient bilinguals in English. The results cannot be accounted for by cognitive control or word recognition speed alone; instead, they are best accommodated by assuming that cognitive control and word recognition speed jointly determine the Stroop effect. Thus, we conclude that enhanced cognitive control and delayed word recognition combine to reduce Stroop effect in bilinguals as compared to monolinguals.
The semantic Stroop effect: An ex Gaussian analysis
Venue: CogSci

Previous analyses of the standard Stroop effect (which typically uses color words that form part of the response set) have documented effects on mean reaction times in hundreds of experiments in the literature. Less well known is the fact that ex Gaussian analyses reveal that such effects are seen in (a) the mean of the normal distribution (mu) as well as in (b) the standard deviation of the normal distribution (sigma) and (c) the tail (tau) No ex Gaussian analysis exists in the literature with respect to the semantically based Stroop effect (which contrasts incongruent color associated words with, e.g. neutral controls) In the present experiments, we investigated whether the semantically based Stroop effect is also seen in the three ex Gaussian parameters. Replicating previous reports, color naming was slower when the color was carried by an irrelevant (but incongruent) color associated word (e.g. sky, tomato) than when the control items consisted of neutral words (e.g. keg, palace) in each of four experiments. An ex Gaussian analysis revealed that this semantically based Stroop effect was restricted to the arithmetic mean and mu; no semantic Stroop effect was observed in tau. These data are consistent with the views (1) that there is a clear difference in the source of the semantic Stroop effect, as compared to the standard Stroop effect (evidenced by the presence vs. absence of an effect on tau) and (2) that interference associated with response competition on incongruent trials in tau is absent in the semantic Stroop effect.
A novel analysis of consumption based carbon footprints in China: Unpacking the effects of urban settlement and rural to urban migration

Urbanization in developing countries greatly contributes to growing carbon emissions. Although studies have documented the urbanization effect, the science of consumption based footprint assessments has yet to unpack various effects during the process of urbanization. Based on household expenditure data, this study innovatively proposes a methodology to conceptually and statistically deconstruct the observed urbanization effects on carbon footprint into selection effects and migration effects, which consist of human settlement effects and purposeful changes of migration (such as income and residential location) Applying propensity score matching and regression on the 2010 China Family Panel Study, we find that the apparent carbon footprint difference between rural residents and migrants is about 1.5 t CO2e per capita. The migration effects account for about 2/3 of the apparent difference and the remaining 1/3 is due to selection effects. Urban settlement effects and the purposeful changes account for 73% and 27% of the migration effects, respectively. Transport sector is the key driver of carbon footprint growth: it accounts for 60% of the migration effects. We conclude that travel behavior of rural migrants, currently in scarcity in the lite rature, merits further investigation, and policies should emphasize transit oriented land use and transportation to achieve low carbon urbanization.