nils-herrmann/clean_scirepeval huggingface dataset:
Remarkably enhanced sulfate radical based photo Fenton like degradation of levofloxacin using the reduced mesoporous MnO@MnOx microspheres
Year: 2020

Sulfate radical based advanced oxidation processes (SR AOPs) are promising alternatives to conventional hydroxyl radical AOPs for recalcitrant contaminants elimination in water treatment. Herein, the efficient and fast degradation of antibiotic levofloxacin (LEV) using mesoporous MnO@MnOx microspheres was successfully achieved with peroxymonosulfate (PMS) as an oxidant under simulated sunlight irradiation. Remarkably, MnO@MnOx catalyst achieves 98.1% degradation and 81.4% mineralization of LEV after being irradiated for 30 min, and SO4 OH, O2 and 1O2 species play the imperative role in the SR photo Fenton like oxidation process. Through the reaction intermediates identification, the LEV degradation pathways are speculated. The deterioration of performance is inconspicuous in the cyclic runs with negligible Mn ions leaching. The excellent catalytic activity and stability of the H2 reduced MnO@MnOx microsphere are ascribed to the mesoporous structure, multivalence and oxygen vacancies, resulting in the large specific area, strong UV vis response, effective charge separation coupling with desirable self redox properties of Mn ions on the catalyst surface. This study offers a useful guideline to efficiently degrade recalcitrant contaminants for water treatment.
Synthese de vecteurs peptidiques non viraux vectorisation et ciblage tumoral
Year: 2013

Dans l'optique de developper de nouveaux agents bio inspires pour la detection et/ou le traitement des cellules cancereuses, nos travaux se sont tournes vers la synthese de macromolecules peptidiques complexes ayant la capacite de reconnaitre les cellules tumorales. Ces travaux visent a developper des molecules permettant de cibler des particularites cellulaires presentes sur les cellules tumorales dans le but d'obtenir un traitement personnalise via une vectorisation active permettant une augmentation de l'efficacite therapeutique et une reduction intrinseque de la toxicite du traitement. Pour cela, ces biomolecules doivent posseder a la fois un site de reconnaissance pour la liaison avec des proteines presentes a la surface de la cellule cible et un ou plusieurs elements utilises pour detecter et/ou detruire la cible. Ces systemes ont ete elabores a partir d'un chassis moleculaire cyclodecapeptidique presentant des proprietes conformationnelles particulieres. Plusieurs approches ont ete envisagees. La premiere a consiste a rechercher de nouveaux ligands de recepteurs tumoraux en s'inspirant du domaine de reconnaissance d'un anticorps monoclonal therapeutique. Dans ce contexte, nous avons propose la conception de mimes du Rituximab ciblant l'antigene CD20 utilise dans le traitement des lymphomes Non Hodgkinien. Dans la seconde approche, nous avons developpe des vecteurs destines a des applications d'imagerie tumorale. Pour cela, des chassis multivalents presentant des ligands peptidiques RGD ciblant l'integrine alpha v beta 3 ont ete conjugues avec differents agents de detection puis evalues par des techniques d'imagerie telles que la TEP, la TEMP et l'imagerie optique. Toujours dans un but de diagnostic des cellules tumorales, nous nous sommes par la suite tournes vers l'application a la capture cellulaire. Pour cela, une surface d'or a ete modifiee via la formation d'une monocouche organisee SAM Self assembled monolayer presentant des cyclodextrines. Un gabarit peptidique adequat a ainsi permis la capture et le relargage selectif de cellules tumorales mesurees par la technique de microbalance a quartz. Ces memes vecteurs, valides pour le diagnostic ont par la suite ete couples a des peptides cytotoxiques issus d'une proteine pro apoptotique Bax Enfin, une derniere partie a ete consacree a la recherche de nouveaux composes comportant plusieurs elements de ciblage tumoraux. Ces molecules presentent deux ligands de ciblage des recepteurs surexprimes sur la membrane et peuvent ainsi permettre une meilleure selectivite vis a vis des tissus tumoraux.
Analysis of Corrugated Coaxial Line with the Use of Body of Revolution and Finite Element Method
Venue: 2020 23rd International Microwave and Radar Conference (MIKON)
Year: 2020

A combination of the body of revolution and finite element methods is utilized to the analysis of coaxial lines with corrugated rod and wall. Both periodic and non periodic structures can be investigated. As the structure is axially symmetrical the two dimensional scalar vector finite element method can be used, which allows for the investigation of complex geometries and is computationally efficient. A generalized impedance matrix at the line ports is calculated from which the scattering parameters are derived. A few examples of corrugated coaxial lines have been analyzed and the results were compared to those obtained from commercial software.
Nei Neng [Huo Yong ]Heng Wei Zheng Zhi De Tu Shi Zheng Ming
Year: 2006

Gen Ju Nei Neng [Huo Yong ]De Ding Yi ,Cai Yong Zheng Ming Feng Bi Xi Tong Zai p vTu Zhong Gou Cheng De Ke Ni Xun Huan Shi Shun Shi Zhen Fang Xiang Yu Qi Nei Neng [Huo Yong ]Ju You Zheng Zhi Deng Jie De Si Lu , Chu Liao Nei Neng [Huo Yong ]Heng Wei Zheng De Yi Ban Xing Zheng Ming Zhe Shuo Ming Zhi Yao Ti Xi Yu Huan Jing Cun Zai Qiang Du Liang De Chai Yi ,Dang Ti Xi Bian Hua Dao Qi Ji Tai Shi ,Xiang Guan Wai Jie Jiu Ke Huo De You Yong Gong
Purkinje Cells Directly Inhibit Granule Cells in Specialized Regions of the Cerebellar Cortex
Venue: Neuron
Year: 2016

Inhibition of granule cells plays a key role in gating the flow of signals into the cerebellum, and it is thought that Golgi cells are the only interneurons that inhibit granule cells. Here we show that Purkinje cells, the sole output neurons of the cerebellar cortex, also directly inhibit granule cells via their axon collaterals. Anatomical and optogenetic studies indicate that this non canonical feedback is region specific: it is most prominent in lobules that regulate eye movement and process vestibular information. Collaterals provide fast, slow, and tonic inhibition to granule cells, and thus allow Purkinje cells to regulate granule cell excitability on multiple timescales. We propose that this feedback mechanism could regulate excitability of the input layer, contribute to sparse coding, and mediate temporal integration.
Climate driven changes to ocean circulation and their inferred impacts on marine dispersal patterns
Year: 2016

The dispersal and distribution patterns of many marine organisms are driven by oceanographic conditions, which are influenced by global climate. Climate driven oceanographic changes are thus likely to result in biogeographical changes. We assess how recent and predicted oceanographic changes affect the dispersal capacities and distributions of ecologically important (especially habitat forming) marine organisms.  We include studies from tropical, temperate and sub polar regions to draw globally relevant conclusions.  We review biogeographical, biological and oceanographic studies to critically evaluate emerging trends in biogeographical responses to climate driven oceanographic changes, and predict how future changes will affect marine ecosystems.  Many oceanic dispersal pathways are being altered by climate change. These changes will affect marine ecosystems by differentially affecting the replenishment potential and connectivity of key habitat forming species. In particular, the length of propagule pre competency periods, propagule behaviour and the geographical distance between areas of suitable habitat will be critical in determining how oceanographic changes affect the pattern and success of dispersal events, including the likelihood of species experiencing poleward range shifts in response to a warming climate.  Future climate driven oceanographic changes are likely to strengthen or weaken different oceanic dispersal pathways, which will either increase or decrease the potential for dispersal and connectivity in various marine taxa according to the interaction between the local oceanographic, geographical and taxon specific biological factors. A key focus for future work should be the development of fine scale near shore ocean circulation models that can be used to assess the dispersal response of key marine taxa under various marine climate change scenarios.
Exploring Creativity Expectation in CS1 Students' View of Programming
Venue: 2020 IEEE Frontiers in Education Conference (FIE)
Year: 2020

Literature provides creativity definitions that are applicable to educational settings. For example, the definition by Plucker et al. emphasizes the 'social context' in which the usefulness and novelty of a creative outcome is evaluated, and notes that this emphasis allows students' coursework to be deemed creative without extraordinary characteristics. Computing educators tend to assume that incoming CS course populations welcome creativity, and utilize application contexts (e.g. games, media, arts, and robots) in which creativity is a central attribute. Previous research also suggests that beginner CS students may initially possess versatile identities regarding what computing will entail. This article seeks to provide further evidence for creativity expectation among students starting a CS1 course, looking at how and to what extent creativity is acknowledged. This agenda was observed to be possible using a large data set (N=1,946, eight year period) in which students at the very beginning of their computing studies characterized what programming is. Qualitatively different creativity related categories were identified and frequencies for these categories were counted in a sample of 240 respondents. Further content analysis was applied to the remaining data by using word searches. The categories identified were: freedom to create and express, creativity needed in problem solving, programming as a circumstance for personalized activity, associations with arts, creative innovations, tolerance to open ended situations, aesthetics and elegance of programming, and programming as a flow like activity. In the sample of 240, 59% of the data was interpreted to refer to creativity, and among the word searched portion of the data, nearly one third was interpreted to indicate it. The illustrations and the numbers of references support educators' assumptions as they consider introducing creativity related education.
PENGEMBANGAN MEDIA PEMBELAJARAN BERDASARKAN KONSEP TPACK PADA MATERI GARIS DAN SUDUT MENGGUNAKAN HAWGENT DYNAMIC MATHEMATICS SOFTWARE
Year: 2020

At every level of education, one of the most important lessons is mathematics. Mathematics becomes a very important learning because it is always used in everyday life. Therefore mathematics learning must be centered on the basic concepts of mathematics. So students can apply the basic concepts of mathematics to everyday life. At this time the development of technology is very rapid and can be utilized to develop based on the TPACK concept of learning media that is in accordance with the model or learning approach to explain a mathematical concept. So that learning mathematics can be more interesting and can help students to understand the basic concepts of mathematics. Hawgent is one of the software developed in accordance with the needs of teaching mathematics. In this study learning media will be developed based on the TPACK concept on line and angle material using hawgent dynamic mathematics software. The results of this study are learning media declared valid by media experts and material experts and can be implemented in schools.
Deep Generative Adversarial Networks for Compressed Sensing Automates MRI
Venue: ArXiv
Year: 2017

Magnetic resonance image (MRI) reconstruction is a severely ill posed linear inverse task demanding time and resource intensive computations that can substantially trade off \it accuracy} for \it speed} in real time imaging. In addition, state of the art compressed sensing (CS) analytics are not cognizant of the image \it diagnostic quality} To cope with these challenges we put forth a novel CS framework that permeates benefits from generative adversarial networks (GAN) to train a (low dimensional) manifold of diagnostic quality MR images from historical patients. Leveraging a mixture of least squares (LS) GANs and pixel wise \ell_1$ cost, a deep residual network with skip connections is trained as the generator that learns to remove the \it aliasing} artifacts by projecting onto the manifold. LSGAN learns the texture details, while \ell_1$ controls the high frequency noise. A multilayer convolutional neural network is then jointly trained based on diagnostic quality images to discriminate the projection quality. The test phase performs feed forward propagation over the generator network that demands a very low computational overhead. Extensive evaluations are performed on a large contrast enhanced MR dataset of pediatric patients. In particular, images rated based on expert radiologists corroborate that GANCS retrieves high contrast images with detailed texture relative to conventional CS, and pixel wise schemes. In addition, it offers reconstruction under a few milliseconds, two orders of magnitude faster than state of the art CS MRI schemes.
Trust and online consumer health service success
Year: 2017

We examine consumers' early stage trust beliefs for effects on perceptions of information and system quality, later stage trust, satisfaction and usage intentions in the context of online health services. Using a longitudinal research design, data was collected from a sample of undergraduates during two time periods, approximately five weeks apart. Results show that trust in the website influences trust in the e service provider at both early and later stages. Perceptions of system and information quality depend on trust, while trust and satisfaction are important to continued usage intentions. Results are important for understanding how trust interacts with IS success factors.
A General Procedure for Improving Language Models in Low Resource Speech Recognition
Venue: 2019 International Conference on Asian Language Processing (IALP)
Year: 2019

It is difficult for a language model (LM) to perform well with limited in domain transcripts in low resource speech recognition. In this paper, we mainly summarize and extend some effective methods to make the most of the out of domain data to improve LMs. These methods include data selection, vocabulary expansion, lexicon augmentation, multi model fusion and so on. The methods are integrated into a systematic procedure, which proves to be effective for improving both n gram and neural network LMs. Additionally, pre trained word vectors using out of domain data are utilized to improve the performance of RNN/LSTM LMs for rescoring first pass decoding results. Experiments on five Asian languages from Babel Build Packs show that, after improving LMs, 5.4 7.6% relative reduction of word error rate (WER) is generally achieved compared to the baseline ASR systems. For some languages, we achieve lower WER than newly published results on the same data sets.
CuCo2O4 flowers/Ni foam architecture as a battery type positive electrode for high performance hybrid supercapacitor applications
Year: 2017

The battery type CuCo 2 O 4 electrode was evaluated as a positive electrode material for its hybrid supercapacitor applications. CuCo 2 O 4 flowers were prepared on Ni foam through a simple hydrothermal process and post calcination treatment. The structure and morphology of the CuCo 2 O 4 flowers/Ni foam was characterized by X ray diffraction (XRD) field emission scanning electron microscopy (FESEM) and high resolution transmission electron microscopy. FESEM clearly revealed the flower like morphology, which was composed of large number of petals. The length and width of the petals ranged from approximately 5 8 mm and approximately 50 150 nm, respectively. The CuCo 2 O 4 flowers/Ni foam electrode was employed for electrochemical characterization for hybrid supercapacitor applications. The specific capacity of the CuCo 2 O 4 flower like electrode was 692.4C g 1 (192.3 mA h g 1 at a scan rate of 5 mV s 1 The flower like CuCo 2 O 4 electrode exhibited a maximum specific capacity of 645.1C g 1 (179.2 mA h g 1 at a specific current of 1 A g 1 and good long term cyclic stability. The high specific capacity, good cyclic stability, and low internal and charge transfer resistance of the CuCo 2 O 4 flowers/Ni foam electrode confirmed the suitability of the prepared material as a positive electrode for hybrid supercapacitor applications.
Braiding via geometric Lie algebra actions
Venue: Compositio Mathematica
Year: 2012

We introduce the idea of a geometric categorical Lie algebra action on derived categories of coherent sheaves. The main result is that such an action induces an action of the braid group associated to the Lie algebra. The same proof shows that strong categorical actions in the sense of Khovanov Lauda and Rouquier also lead to braid group actions. As an example, we construct an action of Artin's braid group on derived categories of coherent sheaves on cotangent bundles to partial flag varieties.
Chassis Assembly Detection and Identification Based on Deep Learning Component Instance Segmentation
Venue: Symmetry
Year: 2019

Chassis assembly quality is a necessary step to improve product quality and yield. In recent years, with the continuous expansion of deep learning method, its application in product quality detection is increasingly extensive. The current limitations and shortcomings of existing quality detection methods and the feasibility of improving the deep learning method in quality detection are presented and discussed in this paper. According to the characteristics of numerous parts and complex types of chassis assembly components, a method for chassis assembly detection and identification based on deep learning component segmentation is proposed. In the proposed method, assembly quality detection is first performed using the Mask regional convolutional neural network component instance segmentation method, which reduces the influence of complex illumination conditions and background detection. Next, a standard dictionary of chassis assembly is built, which is connected with Mask R CNN in a cascading way. The component mask is obtained through the detection result, and the component category and assembly quality information is extracted to realize chassis assembly detection and identification. To evaluate the proposed method, an industrial assembly chassis was used to create datasets, and the method is effective in limited data sets of industrial assembly chassis. The experimental results indicate that the accuracy of the proposed method can reach 93.7% Overall, the deep learning method realizes complete automation of chassis assembly detection.
Efektifitas HKI Sebagai Pelindung Industri Kreatif dan UMKM Di Tengah Pandemi Covid 19
Year: 2020

The free trade system requires business players to be able to continue to survive in global competition. Through various international conventions ratified, Indonesia has implemented legal protection for Intellectual Property Rights (IPR) Creative industries are closely related to intellectual property in their products services. The economic constraint urges every business actor to continue to innovate in order to survive. Many local products that contribute to the economy in Indonesia still do not have legal protection for their IPRs, making them vulnerable to disputes in the future. The impact of Covid 19 provides opportunities and challenges for businesses to participate in and develop their businesses in the industrial era 4.0.  IPR; Creative Industries; MSME; Covid 19. Abstrak Sistem perdagangan bebas menuntut para pelaku usaha untuk dapat terus bertahan dalam persaingan global. Melalui berbagai konvensi internasional yang diratifikasi, maka Indonesia telah menerapkan perlindungan hukum terhadap Hak Kekayaan Intelektual (HKI) Industri kreatif berkaitan erat dengan kekayaan intelektual dalam produk/jasanya. Keterhimpitan ekonomi mendesak setiap pelaku usaha untuk terus berinovasi agar dapat bertahan hidup. Banyaknya produk lokal yang memberikan kontribusi terhadap perekonomian di Indonesia yang masih belum memiliki perlindungan hukum terhadap HKInya, sehingga rentan akan adanya sengketa dikemudian hari. Dampak Covid 19 memberikan peluang dan tantangan bagi pelaku usaha untuk ikut berperan dan mengembangkan usahanya di era industri 4.0.  HKI; Industri Kreatif; UMKM; Covid 19
Next Generation Firewall for Network Security: A Survey
Venue: SoutheastCon 2018
Year: 2018

In today's world, with the advent of internet, the network security has become a necessity to protect the usability and integrity of network and data. Traditional firewalls are incapable of coping with emerging threats such as targeted and data focused attacks. In this paper, a survey of the different types of current and next generation firewalls are discussed in details highlighting their potential functionalities. The different technologies implemented in Next Generation Firewall (NGFW) for network security are highlighted. Additionally, the advantages of the next generation firewalls were compared against the traditional firewalls. Also in this paper, the primary network security goals, their recent emerging security threats, and their potential solutions to protect the network are discussed.
Condensed forms for the symmetric eigenvalue problem on multi threaded architectures
Venue: Concurr. Comput. Pract. Exp.
Year: 2011

We investigate the performance of the routines in LAPACK and the Successive Band Reduction (SBR) toolbox for the reduction of a dense matrix to tridiagonal form, a crucial preprocessing stage in the solution of the symmetric eigenvalue problem, on general purpose multi core processors. In response to the advances of hardware accelerators, we also modify the code in the SBR toolbox to accelerate the computation by off loading a significant part of the operations to a graphics processor (GPU) The performance results illustrate the parallelism and scalability of these algorithms on current high performance multi core and many core architectures.
Activation of surface lattice oxygen in single atom Pt/CeO2 for low temperature CO oxidation
Venue: Science
Year: 2017

Stable catalysts through steaming The lifetime of catalysts that convert automotive exhaust pollutants can be increased by lowering their operating temperature, which helps to prevent deactivation caused by the active metal atoms agglomerating into larger, less active particles. Nie et al. show that a thermally stable catalyst, atomically dispersed Pt2+ on CeO2, can become active for CO oxidation at 150degC after steam treatment at 750degC. In studies with simulated vehicle exhaust, this catalyst treatment also improves its oxidation activity for other exhaust components such as hydrocarbons. Science, this issue p. 1419 Steam treatment at 750degC transforms single Pt2+ ions on CeO2 into a CO oxidation catalyst active at low temperatures. To improve fuel efficiency, advanced combustion engines are being designed to minimize the amount of heat wasted in the exhaust. Hence, future generations of catalysts must perform at temperatures that are 100degC lower than current exhaust treatment catalysts. Achieving low temperature activity, while surviving the harsh conditions encountered at high engine loads, remains a formidable challenge. In this study, we demonstrate how atomically dispersed ionic platinum (Pt2+ on ceria (CeO2) which is already thermally stable, can be activated via steam treatment (at 750degC) to simultaneously achieve the goals of low temperature carbon monoxide (CO) oxidation activity while providing outstanding hydrothermal stability. A new type of active site is created on CeO2 in the vicinity of Pt2+ which provides the improved reactivity. These active sites are stable up to 800degC in oxidizing environments.