nils-herrmann/clean_scirepeval huggingface dataset:
Quantification of maize water uptake from different layers and root zones under alternate furrow irrigation using stable oxygen isotope

How to quantify the root water uptake from different soil layers under alternate furrow irrigation (AFI) condition accurately, is still of great challenge. In this study, the stable hydrogen and oxygen (dD and d18O) isotopes of soil water, stem water, rainfall and irrigation water (groundwater) in the maize field system under AFI condition were measured during 2013 2014. The root water uptake was estimated by the multi source mass balance method (IsoSource model) Results showed that d18O distribution varied significantly between the ridge (R) and furrow (F) near soil surface, and between ridge surface and wet furrow under AFI. d18O in stem water had better response to soil water variation at wet side, and soil water in wet side was firstly absorbed by maize root and then transported to the dry side. Maize water uptake was mainly from the depths of 20 40cm at the late jointing stage, 40 60cm at the late heading stage and 40 80cm at the filling stage, with relative contribution of 84, 80 and 66% respectively. Maize water uptake from different soil zones varied remarkably at AFI. For example, at the filling stage, 16 52% of maize water uptake was from the depth of 60 80cm below the ridge (dry side) before irrigation, 32 78 and 14 64% from the surface soil (0 20cm) of wet furrow and the ridge at 1 day after irrigation, 14 60 and 8 54% from the depths of 20 40cm below the ridge side and 40 60cm below wet furrow at 3 day after irrigation, and 6 80 and 30 60% from the depths of 60 80cm below the ridge and 40 60cm below the ridge side at 7 day after irrigation. Thus maize root water uptake was from deeper soil with the advance of growth stage, and it was mainly from the deeper soil in dry side and the shallow soil in wet side under AFI.
Determining the importance of Hospital Information System adoption factors using Fuzzy Analytic Network Process (ANP)

The Hospital Information System (HIS) is a computer system aimed at providing a paperless environment that covers all aspects of the hospital's operation such as clinical, administrative, and financial systems. The aim of this study is to provide more insight within the context of Malaysia to understand the potential factors that importantly driving or inhibiting the decision of HIS adoption from non adopters' perspective. This study mainly integrates the diffusion of innovation theory, technology organization environment framework, institutional theory along with human organization technology fit model that can be tailored in understanding of the HIS adoption by Malaysian public hospitals. In this regard, the initial model is designed by considering four main dimensions (Technology, Environment, Human, Organization) with seventeen variables based on reviewing of the existing extensive literature of information system in particular information technology adoption in line with prior HIS adoption studies. Accordingly, a Fuzzy Analytic Network Process (ANP) one of the Multi Criteria Decision Making (MCDM) techniques, model is developed to determine the most important factors among the four categories for the HIS adoption in the context of Malaysian public hospitals. These factors are identified and compared by 20 hospital experts and decision makers, who are fully familiar of HIS technology with also professional management and decision making experience in hospitals. Then fuzzy ANP is applied to compute the weights of incorporated factors in the HIS adoption. The results reveal that hospitals with compatibility, complexity, mimetic pressure and vendor support are more likely to adopt HIS. Hence, the decision to adopt HIS is mainly determined by technological and environmental context. The study and its findings have resulted in theoretical contributions and research implications where the integrated theoretical model serves as a tool for healthcare industry to gain insight into the process of HIS adoption.
Chronic exposure to soil salinity in terrestrial species: Does plasticity and underlying physiology differ among specialized ground dwelling spiders?
Venue: Journal of insect physiology

In salt marshes, the alternation of low and high tides entails rapid shifts of submersion and aerial exposure for terrestrial communities. In these intertidal environments, terrestrial species have to deal with an osmotic loss in body water content and an increase in sodium chloride concentration when salt load increases. In salt marshes, spiders represent an abundant arthropod group, whose physiological ecology in response to variations of soil salinity must be further investigated. In this study, we compared the effect of salinity on the survival and physiology of three species of Lycosidae; two salt marsh species (Arctosa fulvolineata and Pardosa purbeckensis) and one forest species (P. saltans) Spiders were individually exposed at three salinity conditions (0%0, 35%0 and 70%0) and survival, changes in body water content, hemolymph ions (Na( Ca(2+ Mg(2+ K( ICP MS technique) and metabolites (mainly amino acids, polyols, sugars; LC and GC techniques) were assessed. The survival of the forest species P. saltans was very quickly hampered at moderate and high salinities. In this spider, variations of hemolymph ions and metabolites revealed a quick loss of physiological homeostasis and a rapid salt induced dehydration of the specimens. Conversely, high survival durations were measured in the two salt marsh spiders, and more particularly in A. fulvolineata. In both P. purbeckensis and A. fulvolineata, the proportion of Na( Ca(2+ Mg(2+ K( remained constant at the three experimental conditions. Accumulation of hemolymph Na( and amino acids (mainly glutamine and proline) demonstrated stronger osmoregulatory capacities in these salt marsh resident spiders. To conclude, even if phylogenetically close (belonging to the same, monophyletic, family) we found different physiological capacities to cope with salt load among the three tested spider species. Nevertheless, physiological responses to salinity were highly consistent with the realized ecological niches of the spiders.
KREATIVITAS SUPRIYADI PUJA WIYATA DALAM KARYA TARI TOPENG DEGERAN

Topeng Degeran merupakan karya tari yang diciptakan Supriyadi Puja Wiyata berdasarkan fenomena adanya tari topeng di Banyumas. Penelitian ini bertujuan mengetahui kreativitas Supriyadi Puja Wiyata dalam tari Topeng Degeran yang di dalamnya dijelaskan mengenai kesenimanan Supriyadi Puja Wiyata yang berpengaruh terhadap kreativitasnya dalam menciptakan tari Topeng Degeran. Tujuan lain pada penelitian ini adalah untuk mengetahui bentuk tari Topeng Degeran yang dijelaskan menggunakan elemen elemen dasar koreografi berdasarkan pendapat dari Sumandiyo Hadi. Kreativitas Supriyadi Puja Wiyata dijelaskan menggunakan konsep 4P yang dikemukakan oleh Utami Munandar yaitu pribadi (person) pendorong (press) proses (process) produk (product) Pada kreativitas ini terdapat pembentukan gerak tari Topeng Degeran yang di dalamnya merupakan suatu aksi dan usaha ketubuhan (effort shape) yang dilakukan penari. Penelitian ini menggunakan metode penelitian kualitatif dengan bentuk deskriptif analitik yaitu dengan memberikan deskripsi atau gambaran dengan cara memaparkan data yang diperoleh di lapangan mengenai Topeng Degeran, koreografi Topeng Degeran, dan kreativitas Supriyadi Puja Wiyata dalam menciptakan tari Topeng Degeran. Hasil penelitian yang diperoleh yaitu kreativitas Supriyadi dalam tari Topeng Degeran banyak dipengaruhi oleh pengalamannya sebagai penari maupun koreografer. Kreativitas tersebut diwujudkan dalam motif gerak sembahan, lampah miring, lembeyan, dan singgetan selut. Gerak gerak tersebut terinspirasi dari gerak tari Yogyakarta, Sunda, Surakarta, dan Jawa Timur, kemudian digarap menggunakan musik tari Banyumas sehingga muncul rasa Banyumasan yang khas. Kesimpulan pada penelitian ini yaitu hasil kreativitas Supriyadi yang mengadopsi beberapa vokabuler gerak ditata dengan nuansa Banyumas.
Effects of adjustment devices on the fore and aft mode of an automobile seat system: headrest, height adjuster, recliner and track slide

The automobile seat is an important and unique device in the automobile system, which directly contacts the human body. The dynamic characteristics of the automobile seat are the key parameters for its vibration security and dynamic performance. Both experiments and finite element simulations are conducted to analyse the fore and aft operating modes of a new type of automobile seat system in this paper. The results and their correlation analysis between the experimental data and the computational models are given. By using finite element simulations, the computational results of the modes with the first 12 orders for the automobile seat are in the range 0 100 Hz, including the integral modes and the local modes of the automobile seat. An experimental method was designed to measure the seat frame mode using an impact hammer, a triaxial accelerometer, uniaxial accelerometers and a 24 channel LMS vibration test system. The experimental data were analysed by estimating the frequency response function and the modal parameters and validated using LMS Test.Lab software. The experimental results for five integral modal parameters of the automobile seat between 0 Hz and 100 Hz are given. The orthogonal experimental method is used to design nine different working states of the automobile seat with variations in the positions of different adjustable devices (the headrest, the height adjuster, the recliner and the track slide) Finally, the influences of the above mentioned adjustable devices on the fore and aft operating mode are analysed by the single factor analysis method using finite element simulations.
Leaf Disease Detection and Prevention Using Image Processing using Matlab

Nowadays many of the farmers and agro help center use the different new technology to enhance the agriculture production. Plants have become important source of energy. There are several diseases that affect plants with the potential to cause economic and social losses. Many of disease are most popular where disease spots occur on the sugar cane plant leaves. If the disease are not detected at first stage than it is more harm full to production. To find out particular disease using Digital image processing helps to find disease and provide prevention for particular disease which types pesticide need to prevent disease. Firstly take Input image in RGB form then the green pixels are removed then the image is segmented useful segment used for extraction finally texture statistics is completed and according to analysis disease prevention is provided.  Digital image processing; segmentation; Extraction;  Spots; Sugarcane.
Unsupervised Word and Dependency Path Embeddings for Aspect Term Extraction
Venue: IJCAI

In this paper, we develop a novel approach to aspect term extraction based on unsupervised learning of distributed representations of words and dependency paths. The basic idea is to connect two words (w1 and w2) with the dependency path (r) between them in the embedding space. Specifically, our method optimizes the objective w1 r w2 in the low dimensional space, where the multi hop dependency paths are treated as a sequence of grammatical relations and modeled by a recurrent neural network. Then, we design the embedding features that consider linear context and dependency context information, for the conditional random field (CRF) based aspect term extraction. Experimental results on the SemEval datasets show that, (1) with only embedding features, we can achieve state of the art results; (2) our embedding method which incorporates the syntactic information among words yields better performance than other representative ones in aspect term extraction.
Un estudio multidisciplinario interinstitucional de necesidades sociocomunicativas linguisticas: hacia una propuesta curricular para la ingenieria agroindustrial, 2014, CURVA ELCE UNAH

In the interest of responding to the demand of the Career of Engineering in Agribusiness of the Centro Universitario Regional del Valle de Aguan (CURVA) in the city of Olanchito, Honduras, a scientific study was conducted on a quantitative and qualititive based approach, at the Foreign Languages Department of the UNAH, late 2014; such research collected data from 4 appropriately selected populations, with the aim of designing and developing a curriculum for the English for Specific Purposes (ESP) program of this regional center of the National Autonomous University of Honduras (UNAH) This research project was aimed, first, to diagnosing and determining, through 5 instruments for data collection, the training needs in English (the needs of education in English) and then, after the analysis of these data, to establishing and technically validating a more intensive program that will respond to profession orientated communicative and linguistic needs, subjective needs and intercultural needs of students and graduates of the Engineering in Agribusiness. The new program will eventually lead to acquire better language and communicative skills for optimal academic and professional achievement in this concrete area. In short, this study determined the students' insufficient level of English, the demand, motivation and actual study habits to learning the language, also the needed content, sociolinguistic competence, teaching strategies and assessment methodology. Moreover, the research determined how these students should read, listen, write and speak in English in a more profession orientated way. In conclusion, the following question was answered: "Who needs what language, which operation to perform, according to what party, in what circumstances and for what purpose with regard to which object using what means and in what language forms? " Cabre (2010).These components shaped the curriculum proposal that was formulated. Consequently, the management of this new curriculum reform attempts to promote the socioeconomic development of the families in the community, and to respond to the demand of hiring skilled professionals because of the huge number of national and international companies in the area of Valle del Aguan, engaged in the field of agriculture and industry.
Deep learning approach for active classification of electrocardiogram signals
Venue: Inf. Sci.

In this paper, we propose a novel approach based on deep learning for active classification of electrocardiogram (ECG) signals. To this end, we learn a suitable feature representation from the raw ECG data in an unsupervised way using stacked denoising autoencoders (SDAEs) with sparsity constraint. After this feature learning phase, we add a softmax regression layer on the top of the resulting hidden representation layer yielding the so called deep neural network (DNN) During the interaction phase, we allow the expert at each iteration to label the most relevant and uncertain ECG beats in the test record, which are then used for updating the DNN weights. As ranking criteria, the method relies on the DNN posterior probabilities to associate confidence measures such as entropy and Breaking Ties (BT) to each test beat in the ECG record under analysis. In the experiments, we validate the method on the well known MIT BIH arrhythmia database as well as two other databases called INCART, and SVDB, respectively. Furthermore, we follow the recommendations of the Association for the Advancement of Medical Instrumentation (AAMI) for class labeling and results presentation. The results obtained show that the newly proposed approach provides significant accuracy improvements with less expert interaction and faster online retraining compared to state of the art methods.
Attending to Characters in Neural Sequence Labeling Models
Venue: COLING

Sequence labeling architectures use word embeddings for capturing similarity, but suffer when handling previously unseen or rare words. We investigate character level extensions to such models and propose a novel architecture for combining alternative word representations. By using an attention mechanism, the model is able to dynamically decide how much information to use from a word or character level component. We evaluated different architectures on a range of sequence labeling datasets, and character level extensions were found to improve performance on every benchmark. In addition, the proposed attention based architecture delivered the best results even with a smaller number of trainable parameters.
Listen, attend and spell: A neural network for large vocabulary conversational speech recognition
Venue: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

We present Listen, Attend and Spell (LAS) a neural speech recognizer that transcribes speech utterances directly to characters without pronunciation models, HMMs or other components of traditional speech recognizers. In LAS, the neural network architecture subsumes the acoustic, pronunciation and language models making it not only an end to end trained system but an end to end model. In contrast to DNN HMM, CTC and most other models, LAS makes no independence assumptions about the probability distribution of the output character sequences given the acoustic sequence. Our system has two components: a listener and a speller. The listener is a pyramidal recurrent network encoder that accepts filter bank spectra as inputs. The speller is an attention based recurrent network decoder that emits each character conditioned on all previous characters, and the entire acoustic sequence. On a Google voice search task, LAS achieves a WER of 14.1% without a dictionary or an external language model and 10.3% with language model rescoring over the top 32 beams. In comparison, the state of the art CLDNN HMM model achieves a WER of 8.0% on the same set.
A population approach to analyze the effectiveness of a back extension exercise "One Stretch" in patients with low back pain: A replication study.
Venue: Journal of orthopaedic science official journal of the Japanese Orthopaedic Association

We examined the effectiveness of an intervention using a standing back extension exercise called "One Stretch" based on the McKenzie method, in improving or preventing low back pain and disability in Japanese care workers.  We conducted a non randomized controlled trial in Japan. Care workers in the intervention group received an exercise manual and a 30 minute seminar on low back pain and were encouraged to exercise in groups, while care workers in a control group were given only the manual. All care workers answered questionnaires at baseline and after one year on the subjective improvement in low back pain, whether they had had a medical consultation for low back pain, and the exercise compliance. Low back pain with disability was assessed by the Oswestry Disability Index.  Participants included 89 workers in the intervention group and 78 in the control group. Background characteristics did not differ significantly between the two groups. Compared to the control group, a greater number of care workers in the intervention group showed improvements in low back pain or prevented it, did not have a medical consultation for low back pain, and exercised regularly. Furthermore, significantly fewer care workers in the intervention group suffered from low back pain with disability by the end of the study period than in the control group.  The population approach about the exercise "One Stretch" led to better compliance with the exercise, and was effective for improving or preventing low back pain and in decreasing the likelihood of having a medical consultation for low back pain.
Blended Learning as a Potentially Winning Combination of Face to face and Online Learning

Blended learning, in the form of screencasts to be viewed online outside of class, was incorporated into three sections of an introductory sociology course in a liberal arts college setting. The screencasts were used to introduce concepts and theories to provide more time for discussion in class and more opportunity for students to review concepts and theories outside of class. Students' use and their perceptions of the impact of the screencasts were assessed with an in class survey instrument in addition to a web based college administered survey. Although it was not possible to measure the impact of blended learning on students' academic performance and learning outcomes in this exploratory study, student responses indicated high use of the screencasts as well as the perception that the screencasts were helpful, contributed positively to performance on exams, and also led to more positive feelings about the course more generally. Overall, this provides an optimistic initial appraisal of the prospects for blended learning.
Exploiting Heterogeneous Information for Tag Recommendation in API Management
Venue: 2016 IEEE International Conference on Web Services (ICWS)

As web enabled software becomes the standard for business processes, the ways organizations, partners and customers interface with it have become a critical differentiator in the market place, i.e. API Economy. With the rapid proliferation of APIs, it is increasingly important for users to effectively manage objective APIs in kinds of API markets, e.g. ProgramableWeb (PW) Mashape, etc. In this paper, to facilitate the process of API management, we propose a graphbased recommendation approach called ATRec to automatically assign tags to unlabeled APIs by exploiting both graph structure information and semantic similarity. Specifically, ATRec first leverages the multi type relations (i.e. among APIs, mashups, and mashup assigned tags) to construct a heterogeneous network, in which a Random Walk with Restart (RWR) model is applied to alleviate the total cold start problem where no API has ever been tagged. Furthermore, we apply the recommended API tags in two API management scenarios (API search, API recommendation) Comprehensive experiments based on a real dataset crawled from PW demonstrate the effectiveness of the proposed approach.
INVESTIGATION OF PRONIOSOMES GEL AS A PROMISING CARRIER FOR TRANSDERMAL DELIVERY OF GLIMEPIRIDE

The aim of the study was to develop a proniosomal carrier system that is capable of efficiently delivering entrapped glimepiride over an extended period of time for the treatment of type 2 diabetes.  Proniosomal gels were developed based on span 60 with and without cholesterol. The entrapment efficiency of drug inside niosomes developed from hydration of the proniosomes gel was also characterized. The in vitro release and skin permeation of glimepiride from various proniosomes gel formulations were investigated. The stability studies were performed at 4degC and at room temperature.  The maximum entrapment efficiency was obtained when the cholesterol concentration was 10% of total lipid (90.02% In vitro release through mixed cellulose ester membrane showed sustained release of drug from proniosomes gels. In vitro drug permeation across rabbit skin revealed improved drug permeation and higher transdermal flux with proniosomes gels compared to hydro alcoholic gel of drug. Also, good physical stability was also achieved with proniosomes gels. Kinetics of in vitro skin permeation showed diffusion model of drug release from formulations.  The study proved that the concentration of cholesterol had great influence on the properties of proniosomes gels. Hence, proniosomes preparation containing 10% cholesterol can significantly increase trans epidermal flux and prolong the release of glimepiride.