nils-herrmann/clean_scirepeval huggingface dataset:
Seasonal responses of terrestrial ecosystem water use efficiency to climate change.
Venue: Global change biology

Ecosystem water use efficiency (EWUE) is an indicator of carbon water interactions and is defined as the ratio of carbon assimilation (GPP) to evapotranspiration (ET) Previous research suggests an increasing long term trend in annual EWUE over many regions and is largely attributed to the physiological effects of rising CO2 The seasonal trends in EWUE, however, have not yet been analyzed. In this study, we investigate seasonal EWUE trends and responses to various drivers during 1982 2008. The seasonal cycle for two variants of EWUE, water use efficiency (WUE, GPP/ET) and transpiration based WUE (WUEt the ratio of GPP and transpiration) is analyzed from 0.5deg gridded fields from four process based models and satellite based products, as well as a network of 63 local flux tower observations. WUE derived from flux tower observations shows moderate seasonal variation for most latitude bands, which is in agreement with satellite based products. In contrast, the seasonal EWUE trends are not well captured by the same satellite based products. Trend analysis, based on process model factorial simulations separating effects of climate, CO2 and nitrogen deposition (NDEP) further suggests that the seasonal EWUE trends are mainly associated with seasonal trends of climate, whereas CO2 and NDEP do not show obvious seasonal difference in EWUE trends. About 66% grid cells show positive annual WUE trends, mainly over mid and high northern latitudes. In these regions, spring climate change has amplified the effect of CO2 in increasing WUE by more than 0.005 gC m( 2) mm( 1) yr( 1) for 41% pixels. Multiple regression analysis further shows that the increase in springtime WUE in the northern hemisphere is the result of GPP increasing faster than ET because of the higher temperature sensitivity of GPP relative to ET. The partitioning of annual EWUE to seasonal components provides new insight into the relative sensitivities of GPP and ET to climate, CO2, and NDEP.
K nearest neighbors optimized clustering algorithm by fast search and finding the density peaks of a dataset

In order to overcome the de ciencies of the clustering algorithm published in Science in June 2014 for performing fast searches and nding density peaks, a new K nearest neighbors based clustering algorithm is pro posed in this paper. The proposed algorithm de nes the local density of a point based on its K nearest neighbors, and thus the density peaks can be found accurately. Then, two new assignment strategies for points are developed based on the K nearest neighbors theory. The density peaks are regarded as the initial centers for clusters, and the two new assignment strategies are, in turn, used to assign points to the density peaks in order to construct the clusters of a dataset. The theory analyzes the principles of the new algorithm, and thorough experiments on several popular test cases that include both synthetic and real world datasets from the UCI machine learning repository and Olivetti face database, we demonstrate that the proposed K nearest neighbors based clustering algorithm can detect the right cluster centers by searching for density peaks. Furthermore, we show that the proposed algorithm can recognize clusters regardless of their shape and the dimensionality of the space where the clusters are embedded, independently from the size of the dataset. The algorithm is also robust to outliers, and it outperforms the original algorithm published in Science and other popular clustering algorithms, including AP, DBSCAN, and K means. The new algorithm is a powerful clustering algorithm that can be used to discover the patterns and rules hidden in real world datasets.
Evolution And Modification Of Behavior

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Industrial policy and technology in Italy

After the crisis started in 2008 Italy's industry has lost close to one quarter of its industrial production. The article documents the decline of Italy's industry and technology, setting it in the context of the demise of post war government intervention and of the current European debate on industrial policies. An analysis of the current tools used in Italy's industrial and innovation policy is carried out, showing its 'horizontal' approach, limited resources and fragmented measures. Current initiatives appear unable to support a revival of production and investment and to reduce Italy's gap in technological activities. The conclusions argue that the possibility to reconstruct the country's production capacity largely depends on the development of a new industrial policy combining Italian and European initiatives.
Smart specialization in a centralized state: strengthening the regional contribution in North East Romania

Regional Innovation Strategies 3 (RIS3) are intended to promote the economic transformation of European Union (EU) regions, particularly those that are lagging in development. The introduction of RIS3 has not been without its critics. This is not unexpected given its rapid, and, for some, rather hasty, move from conceptual idea to mainstream EU policy. This paper explores the introduction of the RIS3 approach in North East Romania, one of the EU's least developed regions. Whilst Romania has launched a national RIS3, the Regional Development Agency for North East Romania also voluntarily embarked upon a process of developing a regional RIS3 for the North East region. This provides a valuable opportunity to explore different spatial dimensions of the smart specialization approach and offers the opportunity to consider the extent to which active and well regarded research actors can act as anchors to a RIS3 approach in a less developed region. The paper argues that whilst the experience of developing a regional RIS3 offers strong learning benefits, the effectiveness of this will be dependent on supporting institutional structures.
Modularization strategy: analysis of published articles on production and operations management (1999 to 2013)

The objective of this study was to analyze the main topics studied on the subject of modularization in 81 academic articles published between 1999 and 2013 in international and Brazilian journals that include research related to production and operations management. This analysis proposes a general framework of studies that serves as support for future research on modularization strategy. To fulfill the proposed objective, a systematic literature review was conducted using 10 international academic journals and two Brazilian academic journals that publish studies on the study topic. The main results include identifying the lack of studies on the background that leads to modularization, the lack of empirical and quantitative studies on its effects, and the use of modularization in the organizational, service, and environmental contexts. The present study also organizes modularization studies in the proposed conceptual structure and classifies the articles analyzed into a specific modularization taxonomy and in terms of the study's objective.
Distributed compressive sensing in heterogeneous sensor network
Venue: Signal Process.

In this paper, we apply distributed compressive sensing (DCS) in heterogeneous sensor network (HSN) Combining different types of measurement matrices and different numbers of measurements, we firstly investigate three different scenarios in which HSN is used for signal acquisition. In the first scenario, there are two different types of measurement matrices. One is Gaussian measurement and the other is Fourier measurement, and each sensor applies the same numbers of measurements. In the second scenario, all sensors use the same type of measurement matrices but the number of measurements are different with each other. The third scenario combines different types of measurement matrix and distinct numbers of measurements. Our simulation results show that in Scenario I, when the common sparsity is considerable, the DCS scheme can reduce the number of measurements. In Scenario II, the reconstruction situation becomes better with the increase of the number of measurements. In both Scenarios I and III, joint decoding that use different types of measurement matrices performs better than that of all Gaussian measurement matrices, but it performs worse than that of all Fourier measurement matrices. Therefore, DCS is a good compromise between reconstruction percentage and the number of measurements in HSN.
Signals Reconstruction in Heterogeneous Sensor Network with Distributed Compressive Sensing

In this paper, we reconstruct signals in heterogeneous sensor network (HSN) with distributed compressive sensing (DCS) Combining different types of measurement matrices and different numbers of measurements, we investigate three different scenarios in which HSN is used to acquiring signals for the first time. In the first scenario, there are two different types of measurement matrices. One is Gaussian measurement and the other is Fourier measurement, and each sensor applies the same numbers of measurements. In the second scenario, all sensors use the same type of measurement matrices but the number of measurements are different from each other. The third scenario combines different types of measurement matrix and distinct numbers of measurements. Our simulation results show that in Scenario I, when the common sparsity is considerable, the DCS scheme can reduce the number of measurements. In Scenario II, the reconstruction situation becomes better with the increase of the number of measurements. In both Scenario I and III, joint decoding that use different types of measurement matrices performs better than that of all Gaussian measurement matrices, but it performs worse than that of all Fourier measurement matrices. Therefore, DSC is a good compromise between reconstruction percentage and the number of measurements in HSN.
Diversity in the Economics Profession: A New Attack on an Old Problem

The economics profession includes disproportionately few women and members of historically underrepresented racial and ethnic minority groups, relative both to the overall population and to other academic disciplines. The relative lack of women, African Americans, Hispanics, and Native Americans within economics is present at the undergraduate level, continues throughout the academy, and is barely improving over time. In this paper, we present data on the presence of women and minority groups in the profession and offer an overview of current research on the reasons for the imbalance, highlighting that implicit attitudes and institutional practices may be contributing at all stages of the pipeline. We review evidence on how diversity affects productivity and conclude that the underrepresentation likely hampers the discipline, constraining the range of issues addressed and limiting our collective ability to understand familiar issues from new and innovative perspectives. Broadening the pool from which professional economists are drawn is not just about fairness; it is necessary to ensure the profession produces robust and relevant knowledge. We propose remedial interventions along with evidence on effectiveness, identifying several promising practices, programs, and areas for future research.
IT Konsumerisierung: Strategien und Massnahmen in mittelstandischen Unternehmen
Venue: HMD Praxis der Wirtschaftsinformatik

ZusammenfassungDurch die zunehmende Konsumerisierung im Bereich der Informationstechnologie (IT) stehen IT Abteilungen vor der Herausforderung, den Wunsch der Mitarbeiter, dieselben mobilen Endgerate sowohl zu privaten als auch zu beruflichen Zwecken nutzen zu konnen, mit den Vorgaben und Moglichkeiten der Unternehmens IT zu vereinbaren. Typischerweise wird zur Bewaltigung dieser Anforderung das Konzept des ,Bring Your Own Device" (BYOD) genannt, obwohl sich in den letzten Jahren auch alternative Ausgestaltungsformen herausgebildet haben. Unter der Annahme, dass mittelstandische Unternehmen im Vergleich zu Grossunternehmen signifikante Unterschiede in der Unternehmensorganisation im Allgemeinen als auch in der IT Organisation im Speziellen aufweisen, sind bei der Strategiewahl die Anforderungen dieser Unternehmen berucksichtigen.
Revision of Outcomes and Complications Following Open Reduction, and Zigzag Osteotomy Combined with Fibular Allograft for Developmental Dysplasia of the Hip in Children

Reports of the efficacy of open reduction and Zigzag Osteotomy combined Fibular Allograft (ZOFA) for developmental dysplasia of the hip. The purposes of this study were to evaluate the long term outcomes and complications after surgery.  We performed a retrospective match controlled study in which 158 patients had 181 hips with developmental dysplasia of the hip. Radiographs were found of acetabular index, height of dislocation, Tonnis grade, abduction angle in the spica cast, and Severin grade. At final follow up, deformity of femoral head or neck or acetabulum was evaluated according to the Severin. Avascular necrosis was rated according to Kalamchi. Clinical evaluation was made according to modified McKay criteria.  Between 2009 and 2012, 133 girls (84.2% and 25 boys (15.8% with developmental dysplasia of the hip underwent open reduction and ZOFA; 135 (85.4% were unilateral, and 23 (14.6% were bilateral. Patients were divided into 2 groups: group 1 included 54 patients (62 hips) aged 12 months =18 months and group 2 included 84 patients (119 hips) aged >18 months =36 months. According to Tonnis system: type 3 appeared in 127 hips (70.2% and Type 4 in 54 hip (29.8% The anterior approach was used to expose inner table of the ilium and ZOFA in all cases. Acetabular index was improved; preoperation was 42.95deg, and latest follow up 17.26deg. The Kirschner Wires (KW) were not used to fix the fibular allograft at the pelvic osteotomy site. All of the fibular allografts were completely incorporated in mean time of 14 weeks (range, 12 weeks 17 weeks) post surgery. Clinical evaluation according to modified McKay criteria: satisfactory result (excellent and good) was achieved in 141 hips (77.9% Avascular Necrosis (AVN) happened in 61 hips (33.7% redislocation in 18 hips (9.9% coxa vara in 4 hips (2.2% trendelenburg gait in 4 hips (2.2% and supracondylar femoral fractures in 2 hips (1.1%  On the basis of this study, ZOFA was strength and graft was not resorption, graft problems; without medial displacement of the distal fragment. Acetabular index was improved, without KW problem. Surgical technique with ZOFA did not expose outer table of the illium, limiting abductor muscle injury with negative trendelenburg gait; on the other hand, the blood loss from this procedure is acceptable. Some complications have been seen in this study: AVN, redislocation, coxa magna, coxa vara, trendelenburg gait, and distal femoral fracture.
Literary translation and conceptual metaphors: From movement to performance

Literary translators and translation, when noticed at all, have a poor public image inconsistent with the evidence of skill and effort shown in translators' essays, postscripts and interviews, and with the respect shown to literary translation practice in translation studies in general. This article suggests that much of this negativity results from the entailments, or logical implications, of the dominant conceptual metaphors of translation: movement and replacement. Conceptual metaphors powerfully shape perceptions and expectations, but unlike consciously applied metaphors their effects go largely unnoticed. By comparing the current dominant metaphors of translation to an alternative of "translation as performance" we can see that many of the common concepts of translation are entailments of metaphor rather than intrinsic features of translation. The performance metaphor is used as a contrast because it has very different entailments, thus highlighting the effects of the current metaphors and also providing a possible alternative for translators and students of translation.
A Model of Representational Spaces in Human Cortex
Venue: Cerebral cortex

Current models of the functional architecture of human cortex emphasize areas that capture coarse scale features of cortical topography but provide no account for population responses that encode information in fine scale patterns of activity. Here, we present a linear model of shared representational spaces in human cortex that captures fine scale distinctions among population responses with response tuning basis functions that are common across brains and models cortical patterns of neural responses with individual specific topographic basis functions. We derive a common model space for the whole cortex using a new algorithm, searchlight hyperalignment, and complex, dynamic stimuli that provide a broad sampling of visual, auditory, and social percepts. The model aligns representations across brains in occipital, temporal, parietal, and prefrontal cortices, as shown by between subject multivariate pattern classification and intersubject correlation of representational geometry, indicating that structural principles for shared neural representations apply across widely divergent domains of information. The model provides a rigorous account for individual variability of well known coarse scale topographies, such as retinotopy and category selectivity, and goes further to account for fine scale patterns that are multiplexed with coarse scale topographies and carry finer distinctions.
Biovalorisation of okara (soybean residue) for food and nutrition

Okara is the soybean residue that remains after the manufacture of soymilk or soybean curd. The high moisture content (70 80% makes it susceptible to spoilage, and so it is often discarded. Yet, okara still holds many nutrients (on a dry weight basis, approximately 50% carbohydrates, 20 30% proteins and 10 20% lipids, as well as minerals and phytochemicals) making it a suitable substrate for biovalorisation. Scope and approach The composition of okara is assessed with respect to its potential for biovalorisation to obtain bioactive substances and food products. Studies on okara fermentation by fungi, bacteria and yeasts are highlighted, with their main drawbacks and challenges critically discussed and the research gaps identified.  Studies to date have demonstrated the feasibility of okara fermentation to produce a variety of functional ingredients and foodstuffs. The health benefits and nutritional quality of okara are often enhanced by fermentation, and the fermented okara is also an inexpensive substrate for extraction of bioactive substances. Present research remains largely at bench scale, and the main challenges are related to scaling up, efficiency and/or yield. There is much scope for further exploration into various aspects of okara biovalorisation, including applying bioprocessing treatments as a pre fermentation step, using combinatorial microbes or enzymes, and evaluating organoleptic property, dietary effects and potential allergenicity of the fermented products.
Relationship between photosynthetic pigments and chlorophyll fluorescence in soybean under varying phosphorus nutrition at ambient and elevated CO2
Venue: Photosynthetica

To assess the relationship between chlorophyll (Chl) fluorescence (CF) and photosynthetic pigments, soybean was grown under varying phosphorus (P) nutrition at ambient and elevated CO2 (EC) The EC stimulated, but P deficiency decreased plant height, node numbers, and leaf area concomitantly with the rates of stem elongation, node addition, and leaf area expansion. Under P deficiency, CF parameters and pigments declined except that carotenoids (Car) were relatively stable indicating its role in photoprotection. The CF parameters were strongly related with Chl concentration but not with Chl a/b or Car. However, total Chl/Car showed the strongest association with CF parameters such as quantum efficiency and yield of photosystem II. This relationship was not affected by CO2 treatment. The high correlation between CF and total Chl/Car underscores the significance of the quantification of both, Chl and Car concentrations, to understand the photochemistry and underlying processes of photoprotection and mechanisms of excess energy dissipation in a given environment.
Sequential Recurrent Neural Networks for Language Modeling
Venue: INTERSPEECH

Feedforward Neural Network (FNN) based language models estimate the probability of the next word based on the history of the last N words, whereas Recurrent Neural Networks (RNN) perform the same task based only on the last word and some context information that cycles in the network. This paper presents a novel approach, which bridges the gap between these two categories of networks. In particular, we propose an architecture which takes advantage of the explicit, sequential enumeration of the word history in FNN structure while enhancing each word representation at the projection layer through recurrent context information that evolves in the network. The context integration is performed using an additional word dependent weight matrix that is also learned during the training. Extensive experiments conducted on the Penn Treebank (PTB) and the Large Text Compression Benchmark (LTCB) corpus showed a significant reduction of the perplexity when compared to state of the art feedforward as well as recurrent neural network architectures.
Novel Accurate and Fast Optic Disc Detection in Retinal Images With Vessel Distribution and Directional Characteristics
Venue: IEEE Journal of Biomedical and Health Informatics

A novel accurate and fast optic disc (OD) detection method is proposed by using vessel distribution and directional characteristics. A feature combining three vessel distribution characteristics, i.e. local vessel density, compactness, and uniformity, is designed to find possible horizontal coordinate of OD. Then, according to the global vessel direction characteristic, a General Hough Transformation is introduced to identify the vertical coordinate of OD. By confining the possible OD vertical range and by simplifying vessel structure with blocks, we greatly decrease the computational cost of the algorithm. Four public datasets have been tested. The OD localization accuracy lies from 93.8% to 99.7% when 8 20% vessel detection results are adopted to achieve OD detection. Average computation times for STARE images are about 3.4 11.5 s, which relate to image size. The proposed method shows satisfactory robustness on both normal and diseased images. It is better than many previous methods with respect to accuracy and efficiency.