nils-herrmann/clean_scirepeval huggingface dataset:
A Search for EFL College Students' Culture Related Rhetorical Templates of Argumentative Writing
Venue: ENGLISH TEACHING
Year: 2019

This study investigated EFL college students' culture related templates of written texts along the possibility of inter cultural transfer. We designed a case study to explore how certain cultural assumptions contribute to EFL students' rhetorical decisions while writing an argumentative writing. The participants were four EFL college students. Multiple data sources include background questionnaires, argumentative essays, and in depth retrospective interviews. To analyze rhetorical choices in the participants' writing, we identified choices of argumentation subtypes, and introduction and conclusion components. We also categorized the location of the writer's main claim and thesis statement. The interview data were qualitatively analyzed to see what rhetorical resources participants draw from the cultural/educational contexts, and which factors had influenced the participants' rhetorical strategy. Data analyses indicate that each participant manipulated different rhetorical structures to strengthen the rhetorical impact of their writing. Indeed, the complex constellation of individual participants' cultural resources was at play in their L2 writing. This study contributes to our understanding of the rhetorical templates of L2 texts as constructs that are always in process, and therefore adaptable and negotiable.
Three distinct optical switching states in phase change materials containing impurities: From physical origin to material design
Year: 2021

Ge2Sb2Te5 is the most widely utilized chalcogenide phase change material for non volatile photonic applications, which undergoes amorphous cubic and cubic hexagonal phase transition under external excitations. However, the cubic hexagonal optical contrast is negligible, only the amorphous cubic phase transition of Ge2Sb2Te5 is available. This limits the optical switching states of traditional active displays and absorbers to two. We find that increasing structural disorder difference of cubic hexagonal can increase optical contrast close to the level of amorphous cubic. Therefore, an amorphous cubic hexagonal phase transition with high optical contrast is realized. Using this phase transition, we have developed display and absorber with three distinct switching states, improving the switching performance by 50 Through the combination of first principle calculations and experiments, we reveal that the key to increasing structural disorder difference of amorphous, cubic and hexagonal phases is to introduce small interstitial impurities (like N) in Ge2Sb2Te5, rather than large substitutional impurities (like Ag) previously thought. This is explained by the formation energy and lattice distortion. Based on the impurity atomic radius, interstitial site radius and formation energy, C and B are also potential suitable impurities. In addition, introducing interstitial impurities into phase change materials with van der Waals gaps in stable phase such as GeSb4Te7, GeSb2Te4, Ge3Sb2Te6, Sb2Te3 will produce high optical contrast amorphous metastable stable phase transition. This research not only reveals the important role of interstitial impurities in increasing the optical contrast between metastable stable phases, but also proposes varieties of candidate matrices and impurities. This provides new phase change materials and design methods for non volatile optical devices with multi switching states.
A natural killer dendritic cell axis defines checkpoint therapy responsive tumor microenvironments
Venue: Nature Medicine
Year: 2018

Intratumoral stimulatory dendritic cells (SDCs) play an important role in stimulating cytotoxic T cells and driving immune responses against cancer. Understanding the mechanisms that regulate their abundance in the tumor microenvironment (TME) could unveil new therapeutic opportunities. We find that in human melanoma, SDC abundance is associated with intratumoral expression of the gene encoding the cytokine FLT3LG. FLT3LG is predominantly produced by lymphocytes, notably natural killer (NK) cells in mouse and human tumors. NK cells stably form conjugates with SDCs in the mouse TME, and genetic and cellular ablation of NK cells in mice demonstrates their importance in positively regulating SDC abundance in tumor through production of FLT3L. Although anti PD 1 'checkpoint' immunotherapy for cancer largely targets T cells, we find that NK cell frequency correlates with protective SDCs in human cancers, with patient responsiveness to anti PD 1 immunotherapy, and with increased overall survival. Our studies reveal that innate immune SDCs and NK cells cluster together as an excellent prognostic tool for T cell directed immunotherapy and that these innate cells are necessary for enhanced T cell tumor responses, suggesting this axis as a target for new therapies.Cross talk between innate immune cells helps to enhance the antitumor T cell response during checkpoint blockade therapy.
Sistem Informasi Pelayanan Surat Keterangan pada Kantor Desa (SI SUKET)
Venue: Indonesian Journal of Technology, Informatics and Science (IJTIS)
Year: 2021

Surat menyurat merupakan salah satu jenis pelayanan yang terpenting yang ada di setiap kantor desa. Terdapat sejumlah jenis surat yang biasanya dilayani oleh desa seperti surat pernyataan, surat keterangan kelahiran, surat keterangan kematian, surat keterangan tidak mampu, surat keterangan serbaguna, surat keterangan domisili surat keterangan berkelakuan baik, surat keterangan usaha dan beberapa surat surat lainnya. dalam pelaksanaannya terdapat kendala yaitu para Kaur Umum harus mengetik isi surat secara manual. Hal ini bisa menghambat kinerja pelayanan surat keterangan di balai Desa dan menyebabkan penumpukan antrian warga yang akan membuat surat keterangan. Selain itu, pengarsipan yang masih manual menggunakan buku menjadi masalah tersendiri. Pengarsipan secara manual dengan buku beresiko terjadi kehilangan data, misalnya apabila terjadi kebakaran, buku terselip, hilang dan sebagainya. Dari permasalahan tersebut perlu dikembangkan sistem informasi berbasis web yang dapat memberikan solusi untuk mengatasi permasalahan tersebut, utamanya pada kegiatan pelayanan surat menyurat pada kantor desa. Metode pengembangan yang diterapkan pada penelitian ini adalah dengan pengembangan metode SDLC (System Development Life Cycle) Dengan tahapan investigate, analyze, desain, implementasi dan perawatan. Dengan adanya aplikasi SI SUKET ini diharapkan bisa membantu pihak kantor desa dalam menyediakan pelayanan pembuatan surat keterangan secara mandiri dan berbasis web (online)
Iterated Integrals and Population Time Series Analysis
Year: 2020

One of the core advantages topological methods for data analysis provide is that the language of (co)chains can be mapped onto the semantics of the data, providing a natural avenue for human understanding of the results. Here, we describe such a semantic structure on Chen's classical iterated integral cochain model for paths in Euclidean space. Specifically, in the context of population time series data, we observe that iterated integrals provide a model free measure of pairwise influence that can be used for causality inference. Along the way, we survey recent results and applications, review the current standard methods for causality inference, and briefly provide our outlook on generalizations to go beyond time series data.
The Effect of Acid Sanitizers on the Microbiome of Re use Water
Venue: Frontiers in Sustainable Food Systems
Year: 2020

Due to global climate change, water is becoming increasingly scarce. The poultry industry is a major consumer of fresh water; therefore, in order to reduce their environmental footprint, companies are in the beginning stages of evaluating water for re use. Re use water is classified as water from the poultry plant that has been collected, sanitized, and used again during poultry processing. Necessarily, this water must be potable as it otherwise produces a significant risk to the poultry industry. One of the most commonly used sanitizers in processing water is peracetic acid (PAA) At high concentrations, PAA is corrosive to the metal equipment in the plant and introduces a significant occupational hazard to plant workers. Inorganic sanitizers, such as sodium bisulfate (SBS) have documented antimicrobial and sanitation effects on a variety of surfaces. In this study, SBS and PAA were compared for their ability to sanitize re use water collected from a local poultry plant. Fresh, commercial poultry processing plant re use water was collected at the end of a processing shift and used within 1 h of the collection. Microcosms were created to simulate the sanitation environment and a time course collection of live microorganisms were collected and evaluated for aerobic plate counts, total Enterobacteriaceae, and Salmonella load. The microcosms contained either SBS (1, 2, or 3% or 200 ppm PAA throughout the course of the study. Water samples were collected at 0, 15, 30, and 60 min post sanitation. The water was evaluated for total Enterobacteriaceae and microbial load using traditional plating methods and the total DNA was extracted and sequenced using the 16S rDNA Illumina MiSeq v3 Platform targeting the V4 region of the prokaryote rDNA molecule. All sanitation methods resulted in nearly undetectable XLD and APC counts by 60 m (P 0.05) with 1 and 2% SBS having a slight rebounding of APC counts by 60 m. The sequences were analyzed using the QIIME2.2018.08 pipeline. Changes in alpha diversity and beta diversity were indicated across time and by treatment group, which may reflect the cumulative effects of the sanitation treatment (killing, delayed killing, and the emergence of resistant populations) Overall, based on the ANCOM results, SBS groups had less Pseudmonas and more Bacteroides while PAA groups had greater Actiobacter and Gallinobacterium (Q 0.05) The results of this study indicate that SBS is as efficacious as PAA for decreasing bacterial loads in poultry re use water, but it may favor different populations of bacteria in that water. Therefore, while more studies are needed to evaluate the changes in the microbiome when re use water is applied to carcasses, evidence presented herein suggest that the choice of sanitizer in water re use sanitation may impact downstream microbial loads.
Image semantic segmentation with an improved fully convolutional network
Venue: Soft Comput.
Year: 2020

With the development of deep learning and the emergence of unmanned driving, fully convolutional networks are a feasible and effective for image semantic segmentation. DeepLab is an algorithm based on the fully convolutional networks. However, DeepLab algorithm still has room for improvement, and we design three improved methods: (1) the global context structure module, (2) highly efficient decoder module, and (3) multi scale feature fusion module. The experimental results show that the three improved methods that we proposed in this paper can make the model obtain more expressive features and improve the accuracy of the algorithm. At the same time, we do some experiments on the Cityscapes dataset to further verify robustness and effectiveness of the improved algorithm. Finally, the improved algorithm is applied to the actual scene and has certain practical value.
Basic efficiency measurement of Hungarian logistics centres using data envelopment analysis
Year: 2011

Data envelopment analysis (DEA) is a non parametric linear programming method capable of evaluating the efficiency of decision making units (DMUs) of various kinds. It is widely utilised for the ranking of companies operating in the transport sector. It is, however, not very often applied for the analysis of logistics centres, although its characteristics make it perfectly suitable for this purpose. The present article investigates how DEA can be used for the evaluation of Hungarian logistics centres. The statistic data of 26 DMUs have been collected and the sample has been corrected so as to include only the firms with sufficient data available for an extensive efficiency rating, leaving 12 logistics centres in the pool. Their efficiency was examined as based on the following inputs: surface size of offices, number of employees, surface of available storage space (excluding external storage facilities) The output considered was the volume of total sales revenue and in a second test, the tons of freight hand led. Aggregate, pure technical and scale efficiencies have also been determined.
End to End Airplane Detection Using Transfer Learning in Remote Sensing Images
Venue: Remote. Sens.
Year: 2018

Airplane detection in remote sensing images remains a challenging problem due to the complexity of backgrounds. In recent years, with the development of deep learning, object detection has also obtained great breakthroughs. For object detection tasks in natural images, such as the PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning) VOC (Visual Object Classes) Challenge, the major trend of current development is to use a large amount of labeled classification data to pre train the deep neural network as a base network, and then use a small amount of annotated detection data to fine tune the network for detection. In this paper, we use object detection technology based on deep learning for airplane detection in remote sensing images. In addition to using some characteristics of remote sensing images, some new data augmentation techniques have been proposed. We also use transfer learning and adopt a single deep convolutional neural network and limited training samples to implement end to end trainable airplane detection. Classification and positioning are no longer divided into multistage tasks; end to end detection attempts to combine them for optimization, which ensures an optimal solution for the final stage. In our experiment, we use remote sensing images of airports collected from Google Earth. The experimental results show that the proposed algorithm is highly accurate and meaningful for remote sensing object detection.
Lizzy's Struggles with Attaining Fluency in Multiplication Tables.
Year: 2013

Many learners struggle to make the transition from addition and subtraction to multiplication and division, which hampers further progress in mathematics. In this article, I present a case study of one learner who struggled to attain fluency in multiplication by seven. The purpose of this study was to identify and explain how previous non encapsulations related to addition and subtraction number bonds hampered her efforts in attaining fluency in the multiplication tables. Data for the study were generated from observations and interactions with the child, Lizzy, over a period of two years. The study employed a narrative analysis technique, while drawing upon the APOS (action, process, object, schema) framework together with the notion of conceptual embodiment. The findings suggest that Lizzy's struggles were due to a non encapsulation of the various number bond strings, which did not allow her to see patterns in addition by seven. By using an alternative intervention, Lizzy was able to use this strategy as a conceptual embodiment leading her to greater fluency in the seven times table.
P8.12 Effects of neurofeedback on EEG alpha power and attention span
Venue: Clinical Neurophysiology
Year: 2011

We used online interference by repetitive transcranial magnetic stimulation (rTMS) to evaluate whether the lateral parietal cortex (PC) is involved in Eureka effect, as suggested by neuroimaging data.  Thirty nine healthy volunteers were included in the study. Ten Hz rTMS of the right and left PC was delivered at the intrapatietal sulcus using an optically tracked neuronavigational system. An intensity of 90% resting motor threshold was employed. RTMS of the PC did not affect recognition of degraded pictures representing objects and animals when displayed 2 s after the presentation of their undegraded version (learning phase) However, rTMS delivered over either right or left PC simultaneously to the undegraded image presentation, disrupted identification of the degraded version of the same pictures when displayed 30 minutes after the learning phase. In contrast, recognition of degraded images was unaffected by rTMS over the vertex or by sham rTMS, or when rTMS of either PC was delivered 2 s after the presentation of the undegraded image. In a control experiment aiming to investigate whether the effect of rTMS of the right PC was related to the semantic nature of the visual stimuli, we found that delayed identification of degraded pictures was affected to the same extent when images representing animals or faces were used.  Findings strongly support the hypothesis that both PC at the level of the intraparietal sulcus play a pivotal role in the Eureka effect particularly in consolidation processes. This involvement was likely supracategorial. Data contribute to elucidate the neural network underlying rapid perceptual learning.
Aspect Based Sentiment Analysis of Online Marketplace Reviews Using Convolutional Neural Network
Year: 2020

Most online stores provide product review facilities that contain responses to a product. The number of reviews makes it difficult for potential customers to make conclusions, so that sentiment analysis is needed to extract information from these reviews. Most sentiment analysis is done at the document level, so the results were still lacking in detail because the classification is based on the entire sentence or document and does not identify the specific aspect discussed. This research aims to classify aspect based sentiments from online store reviews using the convolutional neural network (CNN) method with the extraction of features using Word2Vec. The dataset used is Indonesian review data from the site bukalapak.com. The test results on the built system showed that CNN's method of Word2Vec feature extraction has a better score than the naive bayes method with an accuracy value of 85.54% 96.12% precision, 88.39% recall, and f measure 92.02% Classification without using stemming preprocessing on the dataset increases the accuracy by 2.77%
Composite Graph Based Sparse Subspace Clustering for Machine Fault Diagnosis
Venue: IEEE Transactions on Instrumentation and Measurement
Year: 2020

Sparse subspace clustering (SSC) is an effective method to cluster sensing signal for fault diagnosis in mechanical systems. SSC is based on a global expression strategy describing each data point by other data points from all the potential clusters. A drawback of this strategy is that it generates nonzero elements in the nondiagonal blocks of the similarity matrix, thereby reducing the performance of the matrix for data discrimination. To improve SSC's performance, a composite graph based SSC (CG SSC) method is developed by introducing distance among the data points into SSC, where the L1 norm of the sparse coefficients is replaced by the product of the data distance and the sparse coefficients. The distance serves as a constraint to the amplitude of the sparse coefficients. A sparse coefficient with small amplitude is assigned if the distance between the expressed data and the expressing data is large, and vice versa. This method supports the construction of a compact cluster. The effectiveness of the presented method is experimentally verified by data measured on several bearings and gearboxes with different types of faults. The method is also compared with classical clustering methods, and the results indicate its advantage for data sorting and clustering.
Papillomatosis of breast
Year: 2018

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L'enseignement/apprentissage de l'oral en francais dans les universites iraniennes le cas de l'Universite de Tabriz
Year: 2016

Dans cet article, notre objectif consiste a donner quelques pistes de reflexion sur l'enseignement/apprentissage de l'oral dans les universites iraniennes, car la place de l'oral n'y est pas nettement definie dans l'enseignement du FLE. Pour verifier cette reflexion, nous nous interesserons specialement aux productions orales des etudiants des cours de la licence en langue et litterature francaises de 2012 2015 a l'Universite de Tabriz, ou le probleme du discours oral et de communiquer oralement en francais affecte un assez grand nombre d'apprenants. Notre regard s'orientera sur une etude analytique et approfondie des problemes consistant a en connaitre les causes, a etablir des moyens ainsi bien qu'a suggerer des propositions cles qui aboutiront a l'acquisition des competences de comprehension et d'expression orales. Notre intention est de participer a la mise en oeuvre de l'enseignement de l'oral en francais, fonde sur une approche communicative qui vise le developpement de la competence de communication devenue necessaire pour faire progresser la communication orale des apprenants de la langue francaise. Enfin, nous souhaitons que cette approche fasse partie du systeme educatif et pedagogique de l'enseignement du FLE en Iran.
On Curriculum Reform of Teacher Education in Normal Colleges Based on the Background of the National Teacher Certification Examination
Year: 2015

Teacher Certification is a necessary condition of the teacher certificates.Some of the new provisions of the National Teacher Examination qualification will help regulate the access standards,improve the teachers' quality.The Normal Colleges for training teachers should integrate the course structure,improve the course content,integrate the pre vocational curriculum and establish the concept of lifelong education to meet the challenges of the National Teacher Certification Examination for training qualified teachers.