nils-herrmann/clean_scirepeval huggingface dataset:
Que significa ser profesional docente en la actualidad
Year: 2011

La profesionalidad en el campo educativo plantea cuestiones especificas diferentes de otros campos, dado que la responsabilidad de la educacion es compartida con otros agentes personales y sociales. No obstante, los profesionales de la educacion comparten con los demas profesionales una serie de notas caracteristicas, aunque algunas tomar dimensiones especificas. De su analisis se pueden desprender conclusiones interesantes para el presente y futuro de la profesionalizacion pedagogica. En el articulo se analizan tambien la especificidad de las competencias profesionales de los docentes en tanto que grupo mas representativo de los profesionales de la educacion.
Blockchain in construction logistics: state of art, constructability, and the advent of a new digital business model in Sweden
Venue: Proceedings of the 2019 European Conference on Computing in Construction
Year: 2019

Research on blockchain technology implementation within civil engineering has mainly focused on smart contracts, and interfaces with information systems. However, the use of blockchain for the integration of the material and economic flows within construction supply chain thus creating a new business model to enhance a construction project's production, logistics management, and constructability, has not been investigated. In this paper, this shortage is documented through a comprehensive literature review. Then, the potential of Swedish independent third party logistics consultants as a fertile ground for such a business model, is examined. Finally, conclusions about the pursuance of this potential paradigm shift are drawn.
Systemic Risk Assessment in Complex Supply Networks
Venue: IEEE Systems Journal
Year: 2018

The growth in size and complexity of supply chains has led to compounded risk exposure, which is hard to measure with existing risk management approaches. In this study, we apply the concept of systemic risk to show that centrality metrics can be used for complex supply network risk assessment. We review and select metrics, and set up an exemplary case applied to the material flow and contractual networks of Honda Acura. In the exemplary case study, geographical risk information is incorporated to selected systemic risk assessment metrics and results are compared to assessment without risk indicators in order to draw conclusions on how additional information can enhance systemic risk assessment in supply networks. Katz centrality is used to measure the node's risk spread using the World Risk Index. Authority and hub centralities are applied to measure the link risk spread using distances between geographical locations. Closeness is used to measure speed of disruption spread. Betweenness centrality is used to identify high risk middlemen. Our results indicate that these metrics are successful in identifying vulnerabilities in network structure even in simplified cases, which risk practitioners can use to extend with historical data to gain more accurate insights into systemic risk exposure.
Learning to Sense Sparse Signals: Simultaneous Sensing Matrix and Sparsifying Dictionary Optimization
Venue: IEEE Transactions on Image Processing
Year: 2009

Sparse signal representation, analysis, and sensing have received a lot of attention in recent years from the signal processing, optimization, and learning communities. On one hand, learning overcomplete dictionaries that facilitate a sparse representation of the data as a liner combination of a few atoms from such dictionary leads to state of the art results in image and video restoration and classification. On the other hand, the framework of compressed sensing (CS) has shown that sparse signals can be recovered from far less samples than those required by the classical Shannon Nyquist Theorem. The samples used in CS correspond to linear projections obtained by a sensing projection matrix. It has been shown that, for example, a nonadaptive random sampling matrix satisfies the fundamental theoretical requirements of CS, enjoying the additional benefit of universality. On the other hand, a projection sensing matrix that is optimally designed for a certain class of signals can further improve the reconstruction accuracy or further reduce the necessary number of samples. In this paper, we introduce a framework for the joint design and optimization, from a set of training images, of the nonparametric dictionary and the sensing matrix. We show that this joint optimization outperforms both the use of random sensing matrices and those matrices that are optimized independently of the learning of the dictionary. Particular cases of the proposed framework include the optimization of the sensing matrix for a given dictionary as well as the optimization of the dictionary for a predefined sensing environment. The presentation of the framework and its efficient numerical optimization is complemented with numerous examples on classical image datasets.
An Overview of Methods and Applications to Value Informal Care in Economic Evaluations of Healthcare
Venue: PharmacoEconomics
Year: 2012

This paper compares several applied valuation methods for including informal care in economic evaluations of healthcare programmes: the proxy good method; the opportunity cost method; the contingent valuation method (CVM) conjoint measurement (CM) and valuation of health effects in terms of health related quality of life (HR QOL) and well being. The comparison focuses on three questions: what outcome measures are available for including informal care in economic evaluations of healthcare programmes; whether these measures are compatible with the common types of economic evaluation; and, when applying these measures, whether all relevant aspects of informal care are incorporated.All types of economic evaluation can incorporate a monetary value of informal care (using the opportunity cost method, the proxy good method, CVM and CM) on the cost side of an analysis, but only when the relevant aspects of time costs have been valued. On the effect side of a cost effectiveness or cost utility analysis, the health effects (for the patient and/or caregiver) measured in natural units or QALYs can be combined with cost estimates based on the opportunity cost method or the proxy good method. One should be careful when incorporating CVM and CM in cost minimization, cost effectiveness and cost utility analyses, as the health effects of patients receiving informal care and the carers themselves may also have been valued separately. One should determine whether the caregiver valuation exercise allows combination with other valuation techniques.In cost benefit analyses, CVM and CM appear to be the best tools for the valuation of informal care. When researchers decide to use the well being method, we recommend applying it in a cost benefit analysis framework. This method values overall QOL (happiness) hence it is broader than just HR QOL, which complicates inclusion in traditional health economic evaluations that normally define outcomes more narrowly. Using broader, non monetary valuation techniques, such as the CarerQol instrument, requires a broader evaluation framework than cost effectiveness/cost utility analysis, such as cost consequence or multi criteria analysis.
Lifelong Machine Learning for Regional Based Image Classification in Open Datasets
Venue: Symmetry
Year: 2020

Deep Learning algorithms are becoming common in solving different supervised and unsupervised learning problems. Different deep learning algorithms were developed in last decade to solve different learning problems in different domains such as computer vision, speech recognition, machine translation, etc. In the research field of computer vision, it is observed that deep learning has become overwhelmingly popular. In solving computer vision related problems, we first take a CNN (Convolutional Neural Network) which is trained from scratch or some times a pre trained model is taken and further fine tuned based on the dataset that is available. The problem of training the model from scratch on new datasets suffers from catastrophic forgetting. Which means that when a new dataset is used to train the model, it forgets the knowledge it has obtained from an existing dataset. In other words different datasets does not help the model to increase its knowledge. The problem with the pre trained models is that mostly CNN models are trained on open datasets, where the data set contains instances from specific regions. This results into predicting disturbing labels when the same model is used for instances of datasets collected in a different region. Therefore, there is a need to find a solution on how to reduce the gap of Geo diversity in different computer vision problems in developing world. In this paper, we explore the problems of models that were trained from scratch along with models which are pre trained on a large dataset, using a dataset specifically developed to understand the geo diversity issues in open datasets. The dataset contains images of different wedding scenarios in South Asian countries. We developed a Lifelong CNN that can incrementally increase knowledge i.e. the CNN learns labels from the new dataset but includes the existing knowledge of open data sets. The proposed model demonstrates highest accuracy compared to models trained from scratch or pre trained model.
HUBUNGAN BEBERAPA FAKTOR DENGAN STUNTING PADA BALITA BERAT BADAN LAHIR RENDAH
Year: 2018

ABSTRAK Stunting merupakan salah satu masalah gizi yang utama pada anak di Indonesia. Stunting menjadi masalah yang serius karena dikaitkan dengan kualitas sumberdaya manusia di kemudian hari. Anak dengan BBLR(Berat Badan Lahir Rendah) beresiko lebih tinggi menjadi stunting. Tujuan untuk mengetahui hubungan antara IMD (Inisiasi Menyusu Dini) dan BBLR dengan stunting pada anak usia 12 24 bulan dengan berat badan lahir rendah. Jenis penelitian adalah observasional analitik dengan menggunakan desain penelitian cross sectional. Subjek penelitian ditentukan dengan purposive sampling. Subjek terdiri dari 82 balita yang berusia 12 24 bulan dengan BBLR di 2 kecamatan di Kota Surakarta. Pengumpulan data dilakukan dengan wawancara langsung dan pengukuran antropometri. Uji statistik Chi square digunakan untuk menganalisis hubungan antara variabel IMD dengan stunting dan uji Anova digunakan untuk menganalisis hubungan antara variabel BBLR dengan stunting. Hasil: IMD tidak berhubungan signifikan dengan kejadian stunting (X2 0,286, p 0,593) berat badan lahir rendah (BBLR) berhubungan signifikan dengan kejadian stunting pada a 10 F 1,561, p 0,087) Kesimpulan: ada hubungan antara Berat Badan Lahir Rendah dengan Kejadian Stunting.  Stunting, IMD, BBLR ABSTRACT Stunting is one of the main nutritional problems in children in Indonesia. Stunting becomes a serious problem because it is associated with the quality of human resources in the future. Children with LBW (Low Birth Weight) are at higher risk of becoming stunting.  To know the relationship between IMD, and LBW with stunting in children aged 12 24 months with low birth weight. The type of research is observational analytic by using cross sectional research design. Research subject is determined by purposive sampling. Subject consisted of 82 children aged 12 24 months with LBW in 2 districts in Surakarta. Data collection is done by direct interview and anthropometry measurement. Chi square statistical test is used to analyze the relationship between IMD variable with stunting and Anova test is used to analyze the relationship between LBW variable with stunting. The result: IMD was not significantly associated with stunting incidence (X2 0.286, p 0,593) low birth weight (LBW) was significantly associated with stunting incidence at a 10% (F 1.561, p 0.087)  there is a relationship between Low Birth Weight with Stunting Event.  Stunting, IMD, BBLR
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Year: 2015

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Power system reconfiguration in a radial distribution network for reducing losses and to improve voltage profile using modified plant growth simulation algorithm with Distributed Generation (DG)
Year: 2015

Network reconfiguration which is constrained non linear optimization problem has been solved for loss minimization, load balancing, etc. for last two decades using various heuristic search evolutionary algorithms like binary particle swarm optimization, neuro fuzzy techniques, etc. The contribution of this paper lies in considering distributed generation which are smaller power sources like solar photovoltaic cells or wind turbines connected in the customer roof top. This new connection in the radial network has made unidirectional current flow to become bidirectional there by increasing the efficiency but sometimes reducing stability of the system. Modified plant growth simulation algorithm has been applied here successfully to minimize real power loss because it does not require barrier factors or cross over rates because the objectives and constraints are dealt separately. The main advantage of this algorithm is continuous guiding search along with changing objective function because power from distributed generation is continuously varying so this can be applied for real time applications with required modifications. This algorithm here is tested for a standard 33 bus radial distribution system for loss minimization and test results here shows that this algorithm is efficient and suitable for real time applications.
EFEKTIVITAS MEDIA PETAKONSEP DALAM PENGAJARAN BIOKIMIA DASAR TERHADAP PENINGKATAN PRESTASI BELAJAR MAHASISWA
Year: 2013

Efektivitas media petakonsep dalam pengajaran biokimia dasar terhadap peningkatan prestasi belajar mahasiswa. Penggunakan media petakonsep dalam pembelajaran dapat meningkatkan kinerja mahasiswa dan kemampuan untuk memecahkan masalah dalam subjek kimia. Penelitian ini bertujuan untuk mengetahui efektivitas media petakonsep dalam meningkatkan prestasi belajar mahasiswa dalam pembelajaran kimia. Penelitian ini merupakan penelitian eksperimen dengan menggunakan metode pembelajaran media petakonsep yang kemudian dibandingkan dengan metode pengajaran konvensional ceramah. Hasil penelitian menunjukkan bahwa metode pengajaran dengan menggunakan media petakonsep sangat efektif dalam meningkatkan kemampuan mahasiswa untuk memahami konsep biokimia dasar dibanding konvensional ceramah. Rata rata prestasi mahasiswa dalam pengajaran kimia dengan media petakonsep M=53,16+ 65,25 pada pre test menjadi M=79,83+ 4,93 pada post test1, dan M=82,83+ 4,59 pada post test2 lebih tinggi disbanding rata rata kelas kontrol menggunakan konvensional ceramah yaitu M=54,99+ 6,39 pada pre test menjadi M=65,99+ 8,56 pada post test1, dan M=66,33 7,15 pada post test2. Dapat disimpulkan bahwa metode pengajaran dengan media petakonsep sangat efektif dalam pengajaran biokimia dasar.
Porous NiCo 2 O 4 nanowires supported on carbon cloth for flexible asymmetric supercapacitor with high energy density
Year: 2018

Recently, binary metal oxides have been considerably researched for energy storage since it can provide higher electrical conductivity and electrochemical activity than single components. Besides, rational arrays structure design can effectively enhance the utilization of active material. In this article, we synthesis a porous NiCo2O4 nanowires arrays, which were intimate contact with flexible carbon cloth (CC) by a facile hydrothermal reaction and calcination treatment. The rational array structures of NiCo2O4 facilitate the diffusion of electrolyte and effectively increase the utilization of active material. The as obtained NiCo2O4@CC electrode exhibits a high capacitance of 1183 mF cm 2 and an outstanding capacitance retention of 90.4% after 3000 cycles. Furthermore, a flexible asymmetric supercapacitor (ASC) using NiCo2O4@CC as positive electrode and activated carbon cloth (ACC) as negative electrode was fabricated, which delivers a large capacitance of 750 mF cm 2 (12.5 F cm 3) a high energy density of 0.24 mWh cm 2 (3.91 mWh cm 3) as well as excellent cycle stability under different bending states. These remarkable results suggest that as assembled NiCo2O4@CC//ACC ASC is a promising candidate in flexible energy storage applications.
Management of pediatric patients with DSD and ambiguous genitalia: Balancing the child's moral claims to self determination with parental values and preferences.
Venue: Journal of pediatric urology
Year: 2018

A central ethical dilemma in management of the patient with a disorder of sex development (DSD) is the potential conflict between respect for the fundamental right of the child for physical and emotional integrity and self determination, and the right of parents to serve as surrogate decision makers and act in their child's best interest.  Over the past 2 years we have encountered three complex DSD cases on the spectrum of mixed gonadal dysgenesis to ovotesticular DSD in which gender assignment and therefore optimal surgical management was uncertain. All patients had mosaic karyotypes with Y chromosome, dysgenetic ovary and dysgenetic testis, a urogenital sinus, and prominent phallus. In all three cases a team approach was taken to assess functional potential and risks along either gender pathway and to develop a spectrum of treatment options for parental consideration, including: 1. masculinization with removal of dysgenetic ovary; 2. initial vaginoplasty but with retention of the phallus bilateral gonadectomy) 3. initial vaginoplasty with "burial" of corporal bodies (Pippi Salle procedure) bilateral gonadectomy) 4. full feminization: vaginoplasty and clitoroplasty (with bilateral gonadectomy) 5. no surgical intervention.  In all three cases, after consideration of risks and benefits of all options, parents selected option 2: gonadectomy to eliminate tumor risk and vaginoplasty, taking advantage of the child's young age to exteriorize urinary and reproductive tracts to avoid incontinence and infection and supporting parental bias toward female gender, but preservation of phallic structures to ensure a male option should the patient later declare a male gender identity. Parents of the three patients were contacted post operatively (at 7, 17, and 22 months) for follow up. All (3/3) regarded their child's development and wellbeing positively, and their own decisions regarding gender assignment and surgical plan favorably. All (3/3) regarded the team advisory process as balanced and supportive.  In the setting of exposure of the neonatal brain to testosterone, vaginoplasty and phallic preservation afforded a balance between parental preferences and preservation of anatomic options, allowing potential reconstruction of male or female phenotype as gender identity is ascertained thereby respecting both parent and patient rights. Parents valued a spectrum of options, transparency, and the team decision making process.
Trained Immunity Characteristics Are Associated With Progressive Cerebral Small Vessel Disease
Venue: Stroke
Year: 2018

Cerebral small vessel disease (cSVD) is the major vascular cause of cognitive decline and dementia. The pathogenesis of cSVD remains largely unknown, although several studies suggest a role for systemic inflammation. In certain pathophysiological situations, monocytes can reprogram toward a long term proinflammatory phenotype, which has been termed trained immunity. We hypothesize that trained immunity contributes to the progression of cSVD.  Individuals with mild to severe cSVD participated in the study. Severity of cSVD was determined by the white matter hyperintensities (WMH) volume (mL) on magnetic resonance imaging in 2006, 2015, and the progression between 2006 and 2015 &Dgr;WMH) Cytokine production was assessed after ex vivo stimulation of peripheral blood mononuclear cells and monocytes. Additionally, monocyte subsets were identified by flow cytometry.  Fifty one subjects (70+ 6 years, 60% men, 5.1+ 6.4 mL &Dgr;WMH) were included. Circulating hsIL (high sensitivity interleukin) 6 correlated with cSVD (P=0.005, rs=0.40) Cytokine production capacity by monocytes was associated with cSVD progression. Basal IL 8 and IL 17 production (P=0.08, rs=0.25; P=0.03, rs=0.30) and IL 6 production after Pam3Cys stimulation in monocytes was associated with cSVD (n=35: P=0.008, rs=0.44) Conversely, interferon (IFN) &ggr; production in Candida albicans stimulated peripheral blood mononuclear cells was negatively correlated with cSVD (P=0.009, rs= 0.36) Flow cytometry revealed a correlation of the intermediate monocyte subset with cSVD (P=0.01, rs=0.36) Conclusions Severity and progression of cSVD are not only correlated with systemic inflammation (hsIL 6) but also with trained immunity characteristics of circulating monocytes, in terms of an altered cytokine production capacity and a shift toward the proinflammatory intermediate monocyte subset.
K beauty SNS inpeulrueonseoga junggug sobijayi sinjepum suyongyidoe micineun yeonghyang jeonggyohwa ganeungseong model(ELM)eul jungsimeuro
Year: 2019

The acceleration of digital transformation (DX) has resulted in SNS influencer marketing trends becoming the mainstream of the new market. SNS influencers act as early adopters in the process of new products being accepted. Chinese consumers are most affected by Hallyu, which increases interest in K beauty products. This study analyzes how K beauty SNS influencers are related to Chinese consumers. A survey was conducted among Chinese millennial consumers after watching videos provided by K beauty SNS influencer; subsequently, 456 responses were used for data analysis. As a result, the analysis based on the Elaboration Likelihood Model (ELM) distinguishes the central route and the peripheral route in the process of Chinese consumers accepting new SNS products. The study findings suggested that information quality, credibility, accuracy, and usefulness had significant effects on acceptance intention for new products among central route factors, and similarity, trustworthiness, pleasure, expertise, and attractiveness also had significant effects on the acceptance intention of new product among peripheral route factors. It was found that variables of the central route, rather than those of peripheral route, had stronger effects on the acceptance intention for new products. Consequently, the central route of K beauty SNS influencer is more important to Chinese consumers' acceptance of new products. It is expected that this study will offer beauty influencer marketing based cosmetics brands efficient consumer management suggestions.