nils-herrmann/clean_scirepeval huggingface dataset:
Correlations of the liquefaction resistance of sands in spreader dumps of lignite opencast mines with CPT tip resistance and shear wave velocity
Year: 2019

Correlations between the liquefaction resistance of sands in spreader dumps of lignite opencast mines on one side and the CPT tip resistance or the shear wave velocity on the other side have been developed based on an extensive experimental study on 10 different sands. The cyclic resistance ratio CRR N 10) f for a failure in 10 cycles, defined as the liquefaction resistance herein, was determined from undrained cyclic triaxial tests for all materials. The CPT tip resistance qc was measured in soundings performed in a calibration chamber. The shear wave velocity vS was obtained from measurements in a triaxial cell by means of bender elements. All three quantities CRR N 10) f qc and vS were determined for different relative densities Dr In case of qc and vS also the pressure dependence was examined in order to derive suitable equations for a pressure normalization being necessary for the interpretation of field test data, giving values qc1 and vS1 for a mean effective stress of p 100 kPa. The procedure for the development of the CRR N 10) f qc1 and CRR N 10) f vS1 correlations based on the experimental data is explained. The correlations derived for the various sands in the present study are analyzed with respect to the influence of the grain size distribution curve and compared to respective relationships for natural soils or uncompacted recent artificial fills from the literature.
General Dynamic Scene Reconstruction from Multiple View Video
Venue: 2015 IEEE International Conference on Computer Vision (ICCV)
Year: 2015

This paper introduces a general approach to dynamic scene reconstruction from multiple moving cameras without prior knowledge or limiting constraints on the scene structure, appearance, or illumination. Existing techniques or dynamic scene reconstruction from multiple wide baseline camera views primarily focus on accurate reconstruction in controlled environments, where the cameras are fixed and calibrated and background is known. These approaches are not robust for general dynamic scenes captured with sparse moving cameras. Previous approaches for outdoor dynamic scene reconstruction assume prior knowledge of the static background appearance and structure. The primary contributions of this paper are twofold: an automatic method for initial coarse dynamic scene segmentation and reconstruction without prior knowledge of background appearance or structure, and a general robust approach for joint segmentation refinement and dense reconstruction of dynamic scenes from multiple wide baseline static or moving cameras. Evaluation is performed on a variety of indoor and outdoor scenes with cluttered backgrounds and multiple dynamic non rigid objects such as people. Comparison with state of the art approaches demonstrates improved accuracy in both multiple view segmentation and dense reconstruction. The proposed approach also eliminates the requirement for prior knowledge of scene structure and appearance.
PENGARUH STRATEGI PROMOSI MELALUI SOCIAL MEDIA, WORD OF MOUTH MARKETING DAN DISCOUNT TERHADAP KEPUTUSAN PEMBELIAN PRODUK HERBAL TIENS( Studi Pada Konsumen Produk Herbal Tiens Dalam Komunitas TRC JABODETABEK
Year: 2020

Penelitian ini bertujuan untuk mengetahui Pengaruh Strategi Promosi melalui Social media, Word of Mouth marketing, dan Discount Terhadap Keputusan pembelian Produk Herbal Tiens (Studi Pada Konsumen Produk Herbal Tiens Dalam Komunitas TRC JABODETABEK) Penelitian ini bertujuan untuk menganalisa pengaruh variabel independent (social media, word of mouth marketing, dan discount) terhadap variabel dependen (keputusan pembelian) Populasi pada penelitian ini adalah konsumen produk herbal tiens dalam komunitas TRC JABODETABEK sebanyak 200 orang dengan mengambil sampel sebanyak 60 responden. Adapun metode penelitian yang digunakan adalah metode kualitatif dan kuantitatif. Instrument pengumpulan data menggunakan studi pustaka dan kuesioner melalui penyebaran link kuesioner online pada responden. Metode analisis data yang digunakan dalam penelitian ini adalah uji kualitas data (uji validitas dan uji reliabilitas) analisis regresi linier berganda, uji hipotesis dan koefisien determinasi dengan menggunakan SPSS versi 20. Hasil penelitian diketahui semua item pertanyaan dinyatakan valid dan reliabel, sedangkan berdasarkan persamaan regresi linier berganda diperoleh Y 6,094 0,562X1 0,107X2 0,138X3. Dalam pengujian hipotesis secara parsial (uji t) ada pengaruh antara social media terhadap keputusan pembelian, sedangkan word of mouth marketing, dan discount tidak ada pengaruh terhadap keputusan pembelian. Dan simultan (uji f) secara Bersama sama Social Media, Word Of Mouth marketing, dan Discount berpengaruh terhadap keputusan pembelian produk herbal tiens dalam komunitas TRC JABODETABEK. Untuk uji koefisien determinasi (Adjust R2) sebesar 0,415 hal ini berarti 41,5% koefisien determinasi ini digunakan untuk mengetahui seberapa besar presentase pengaruh variabel bebas social media (X1) WOM (X2) dan discount (X3) terhadap keputusan pembelian (Y) dan besarnya pengaruh variabel bebas terhadap variabel terikat dalam penelitian ini adalah 41,5% sedangkan sisanya 58,5% dipengaruhi oleh faktor lain yang belum diteliti. Kata Kunci Social Media, Word Of Mouth marketing, Discount dan Keputusan Pembelian
Point Cloud Segmentation and Recognition Deep Learning Dataset for Ornamental trees and Shrubs Environment
Year: 2019

The rapid collection and real time detection of forest resources information is the key to improving the efficiency of forestry survey and realizing the intelligent cultivation and harvesting of under forest resources. In recent years, tremendous amount of progress is being made in the field of 3D Machine Learning, which is an interdisciplinary field that fuses computer vision, computer graphics and machine learning. Few prior works study deep learning on point sets. The 3D point cloud classification in urban scenes has been widely applied in the fields of automatic driving, map updating, change detection, etc. Accurate and effective classification of mobile laser scanning (MLS) point clouds remains a big challenge for these applications. The existing point cloud processing algorithms have poor generalization ability, weak robustness, low precision, and poor real time performance, which are urgent scientific problems to be solved. PointNet is a pioneer in this direction. In this paper a dataset produced by FARO 3D laser scanner was generated to test its ability to recognize fine grained patterns like artificial pruning Ornamental trees and shrubs. As the result, the typical spherical bush segmentation in a big scene could be precisely acquire throughout the Pointnet method. It shows a great potential in identify and segment complex forest environment point clouds in the future.
The m6A methyltransferase METTL3 promotes bladder cancer progression via AFF4/NF kB/MYC signaling network
Venue: Oncogene
Year: 2019

N6 methyladenosine (m6A) is the most abundant modification in eukaryotic messenger RNAs (mRNAs) and plays important roles in many bioprocesses. However, its functions in bladder cancer (BCa) remain elusive. Here, we discovered that methyltransferase like 3 (METTL3) a major RNA N6 adenosine methyltransferase, was significantly up regulated in human BCa. Knockdown of METTL3 drastically reduced BCa cell proliferation, invasion, and survival in vitro and tumorigenicity in vivo. On the other hand, overexpression of METTL3 significantly promoted BCa cell growth and invasion. Through transcriptome sequencing, m6A sequencing and m6A methylated RNA immuno precipitation quantitative reverse transcription polymerase chain reaction, we revealed the profile of METTL3 mediated m6A modification in BCa cells for the first time. AF4/FMR2 family member 4 (AFF4) two key regulators of NF kB pathway (IKBKB and RELA) and MYC were further identified as direct targets of METTL3 mediated m6A modification. In addition, we showed that besides NF kB, AFF4 binds to the promoter of MYC and promotes its expression, implying a novel multilevel regulatory network downstream of METTL3. Our results uncovered an AFF4/NF kB/MYC signaling network operated by METTL3 mediated m6A modification and provided insight into the mechanisms of BCa progression.
[Rehabilitation after total knee and hip arthroplasty]
Venue: Casopis lekaru ceskych
Year: 2018

The main purpose of total hip replacement is to relieve hip pain and recover the lost mobility of the joint. The postoperative functionality of the hip endoprosthesis is closely related to proper physiotherapy. A good range of motion, sufficient pain reduction and minimum disruption to the muscle tissues are conditions allowing the patients to perform individualized muscle strengthening exercises and to exercise the newly gained mobility, following practice sessions during the early postoperative period still in hospital. The authors describe the individual fazes of the physiotherapy and summarize the principles, which lead to a successful rehabilitation of the patient and his early recovery as well as return to normal life activities.
The Cityscapes Dataset for Semantic Urban Scene Understanding
Venue: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2016

Visual understanding of complex urban street scenes is an enabling factor for a wide range of applications. Object detection has benefited enormously from large scale datasets, especially in the context of deep learning. For semantic urban scene understanding, however, no current dataset adequately captures the complexity of real world urban scenes. To address this, we introduce Cityscapes, a benchmark suite and large scale dataset to train and test approaches for pixel level and instance level semantic labeling. Cityscapes is comprised of a large, diverse set of stereo video sequences recorded in streets from 50 different cities. 5000 of these images have high quality pixel level annotations, 20 000 additional images have coarse annotations to enable methods that leverage large volumes of weakly labeled data. Crucially, our effort exceeds previous attempts in terms of dataset size, annotation richness, scene variability, and complexity. Our accompanying empirical study provides an in depth analysis of the dataset characteristics, as well as a performance evaluation of several state of the art approaches based on our benchmark.
An empirical study on the importance of source code entities for requirements traceability
Venue: Empirical Software Engineering
Year: 2014

Requirements Traceability (RT) links help developers during program comprehension and maintenance tasks. However, creating RT links is a laborious and resource consuming task. Information Retrieval (IR) techniques are useful to automatically create traceability links. However, IR based techniques typically have low accuracy (precision, recall, or both) and thus, creating RT links remains a human intensive process. We conjecture that understanding how developers verify RT links could help improve the accuracy of IR based RT techniques to create RT links. Consequently, we perform an empirical study consisting of four case studies. First, we use an eye tracking system to capture developers' eye movements while they verify RT links. We analyse the obtained data to identify and rank developers' preferred types of Source Code Entities (SCEs) e.g. domain vs. implementation level source code terms and class names vs. method names. Second, we perform another eye tracking case study to confirm that it is the semantic content of the developers' preferred types of SCEs and not their locations that attract developers' attention and help them in their task to verify RT links. Third, we propose an improved term weighting scheme, i.e. Developers Preferred Term Frequency/Inverse Document Frequency (D P T F I D F) that uses the knowledge of the developers' preferred types of SCEs to give more importance to these SCEs into the term weighting scheme. We integrate thisweighting scheme with an IR technique, i.e. Latent Semantic Indexing (LSI) to create a new technique to RT link recovery. Using three systems (iTrust, Lucene, and Pooka) we show that the proposed technique statistically improves the accuracy of the recovered RT links over a technique based on LSI and the usual Term Frequency/Inverse Document Frequency (T F I D F) weighting scheme. Finally, we compare the newly proposed D P T F I D F with our original Domain Or Implementation/Inverse Document Frequency (D O I I D F) weighting scheme.
State Entropy Maximization with Random Encoders for Efficient Exploration
Venue: ICML
Year: 2021

Recent exploration methods have proven to be a recipe for improving sample efficiency in deep reinforcement learning (RL) However, efficient exploration in high dimensional observation spaces still remains a challenge. This paper presents Random Encoders for Efficient Exploration (RE3) an exploration method that utilizes state entropy as an intrinsic reward. In order to estimate state entropy in environments with high dimensional observations, we utilize a k nearest neighbor entropy estimator in the low dimensional representation space of a convolutional encoder. In particular, we find that the state entropy can be estimated in a stable and compute efficient manner by utilizing a randomly initialized encoder, which is fixed throughout training. Our experiments show that RE3 significantly improves the sample efficiency of both model free and model based RL methods on locomotion and navigation tasks from DeepMind Control Suite and MiniGrid benchmarks. We also show that RE3 allows learning diverse behaviors without extrinsic rewards, effectively improving sample efficiency in downstream tasks. Source code and videos are available at https: /sites.google.com/view/re3 rl.
Antioxidant Content of Frozen, Convective Air Dried, Freeze Dried, and Swell Dried Chokecherries (Prunus virginiana L.
Venue: Molecules
Year: 2020

Chokecherry (Prunus virginiana L. is rich in bioactive molecules as phenolics, which can act as antioxidants, anti inflammatory, anticancer, among others; however, due to its high perishability, most of this fruit is wasted. Freezing and sun drying have been the most adopted techniques to avoid its postharvest deterioration. Nevertheless, both processes have presented some drawbacks as high storage costs and losses of bioactive molecules. Therefore, to preserve these molecules, this study compared the impact of convective airflow drying (CAD) freezing (FR) freeze drying (FD) and swell drying (SD) Total phenolics content (TPC) total flavonoids content (TFC) kuromanin concentration (KC) and antioxidant activity (antiradical activity (ARA) and Trolox equivalent antioxidant capacity assay (TEAC) of chokecherries were measured. "Swell drying" is a drying process coupling convective airflow drying to the Instant Controlled Pressure Drop (DIC) expansion. A central composite rotatable design was applied to optimize the DIC variables and responses. Results showed that both freezing and swell drying effectively preserve the TPC, TFC, KC, and ARA. Moreover, SD samples also presented the highest TEAC. Contrary, in the case of CAD, it caused the highest losses of both antioxidant content and activity. Swell drying remedies the shrinkage and collapsing of dried food structure, which results in a better antioxidants extraction.
Seeing the Dao: conceptual metaphors and the philosophy of religion
Venue: Religious Studies
Year: 2015

This article suggests that different philosophical traditions have developed and matured around particular conceptual metaphors. It proposes that conceptual metaphor theory provides a useful tool with which to think about different world philosophical traditions, as it can reveal the deep structure of networks of ideas. Conceptual metaphors are not just linguistic devices; rather they organize whole networks of thought, experience, and activity. This idea is explored and special attention paid to the role of those conceptual metaphors that structure ways of thinking about knowledge within Western, Indian, and East Asian traditions. The article concludes with some reflections on the implications of this approach for inter cultural philosophy of religion.
ANALISE DA DOR MUSCULOESQUELETICA EM MOTORISTAS DE ONIBUS ESCOLAR
Year: 2017

Essa pesquisa tem como objetivo analisar a localizacao das principais dores musculoesqueleticas relacionadas ao trabalho. Alem de relacionar a carga horaria e o tempo de profissao com as dores relatadas, quantificar o nivel de dor sentida pelos motoristas de onibus urbano. Para isso, foi aplicado um questionario aos motoristas de onibus escolar. Dos entrevistados, 35% tinham entre 21 a 30 anos, enquanto 5% dos entrevistados tinham de 41 a 50 anos e acima de 60. Dos motoristas participantes da pesquisa 40% sentiram dor e 60% nao sentem dor. Os locais com mais queixa foram costas dorsais 40% costas lombares 35% Com isso, observou se que as posicoes improprias sao fatores que contribuem para os desgastes musculoesqueleticos nos motoristas que propiciam o aumento na incidencia das dores relacionadas ao trabalho.
JUST at ImageCLEF 2019 Visual Question Answering in the Medical Domain
Venue: CLEF
Year: 2019

This paper describes our method for the Medical Domain Visual Question Answering (VQA Med) Task of ImageCLEF 2019. The aim is to build a model that is able to answer questions about medical images. Our proposed model consists of sub models, each specializing in answering a specific type of questions. Specifically, the sub models we have are: "plane" model, "organ systems" model, "modality" models, and "abnormality" models. All of these models are basically image classification models based on pre trained VGG16 network. We do not rely on the questions for the answers prediction since the questions on each type are repetitive. However, we do rely on them to determine the suitable model to be used for producing the answers and determine the suitable answer format. Our best model achieves 57% accuracy and 0.591 BLEU score.
Existence and Uniqueness of an Inverse Memory Kernel for an Integro Differential Parabolic Equation with Free Boundary
Year: 2018

We consider an inverse problem for an integro differential parabolic equation with free boundary. This inverse problem aims to identify the memory kernel function from a global measurement data. Based on a fixed point argument, we derive the local in time existence and uniqueness of our inverse problem. Additionally, we present a numerical experiment.
Obtention theorique et experimentale des lois de diffusion thermique de l'eau legere
Year: 2018

Une bonne connaissance des sections efficaces de l'eau legere est importante, car l'eau est le moderateur le plus employe dans les reacteurs a eau pressurisee (REP) qui fonctionnent a des temperatures et des pressions avoisinant 550 K et 150 bar. Les sections efficaces neutroniques dans le domaine d'energie thermique dependent de la structure et de la dynamique du materiau diffusant, decrites par des lois de diffusion thermiques (TSL) Les evaluations des TSL existantes n'ont pas ete validees aux hautes temperatures et pressions, et doivent etre revues. Pour produire de nouvelles TSL, des mesures de la diffusion inelastique des neutrons sur l'eau ont ete effectuees a l'Institut Laue Langevin (ILL) a l'aide de deux spectrometres IN4c et IN6. Afin de completer ces mesures, des simulations de dynamique moleculaire (MD) ont ete realisees en s'appuyant sur deux modeles classiques d'interaction moleculaire, le modele non polarisable TIP4P/2005f et le modele polarisable TCPE. Les spectres de frequence a differentes pressions et temperatures obtenus grace aux mesures de temps de vol et aux simulations MD ont ete exploites pour developper de nouvelles TSL. Les performances de ces nouvelles bibliotheques ont ete testees sur une serie de mesures de sections efficaces differentielles, double differentielles et totales disponibles dans la litterature. Des benchmarks critiques (ICSBEP benchmarks) ont egalement ete utilises. Les resultats de ces etudes permettent une meilleure comprehension de l'impact de la temperature et de la pression sur les TSL dans les applications liees a l'exploitation des REP.
Optimisation of data reliability in UASN using adaptive Buffalo algorithm
Venue: J. Ambient Intell. Humaniz. Comput.
Year: 2021

Underwater acoustic network is introduced in recent times to explore the resources available in an underwater environment. The scientific data are collected, and the data packets are transmitted to the onshore base station through the acoustic network. The underwater acoustic network faces several challenges like higher propagation delay, increased energy consumption and limited bandwidth availability due to harsh environmental condition. The most notable limitation is to forward the data packets efficiently from the underwater sensor node to the onshore sink node. Identifying energy efficient path is not enough to achieve maximum efficiency. The Routing protocol developed for the underwater environment must overcome link failure due to congestion, harsh environment or due to energy drop out. A new optimisation protocol is developed based on biological inspiration over the characteristics of African Buffalo, and it is named as Buffalo optimisation algorithm (BOA) In underwater acoustic network, most of the energy is wasted due to the occurrence of collision in the intermediate routing nodes. And uneven traffic generation is also increasing the possibilities of occurrence of early dead nodes. To overcome all these limitations, BOA utilises lookup table based multipath communication. The algorithm is implemented in NS2 simulator, and the performance was compared with the conventional algorithms like vector based flooding protocol, depth based forwarding protocol and channel aware routing protocol. The simulation results show throughput, packet delivery ratio increased by 10% and 12% respectively. The end to end delay and overhead reduced by 8% and 4% respectively. Furthermore, the test bed is developed to identify the performance of the buffalo optimisation protocol in a hardware environment. Comparative analysis of BOA with fore mentioned algorithms shows, energy consumption reduced by13% and response time improved by 3%
Using the Cooperative Learning for Teaching Idioms on French Foreign Language Students.
Year: 2018

The objective of this study is to detect the effect of using cooperative learning for teaching idioms to first grade students, learning French as a foreign language. The study was carried out on two groups experimental group and control group during the academic year of 2017 2018 in the lesson "Reading in French" The lesson was taught using traditional teaching methods with the control group, while using Jigsaw II technique with the experimental group. According to the findings obtained from this research, the experimental group students, on whom the Jigsaw II technique was applied, became more successful within the scope of learning idioms in French language.
HUBUNGAN DIAGNOSIS KLINIS DENGAN DIAGNOSIS BIOPSI ASPIRASI JARUM HALUS PADA STRUMA DI RSUD DR. H. ABDUL MOELOEK PROVINSI LAMPUNG TAHUN 2016
Year: 2016

To determine the relationship of clinical diagnosis and diagnosis of Fine Needle Aspiration Biopsy in Struma In Hospital Dr. H. Abdul Moeloek Lampung Province 2016.The research method used in this research is the method of analytic research with cross sectional study. The samples used were 72 cases in dr. H Abdul Moeloek Lampung Province.The results obtained with the results BAJAH ST malign as many as 18 cases (25. lower compared with the results BAJAH benign as many as 15 cases (20.8% with the result BAJAH SNT malign as many as 6 cases (8.3% higher than the result of benig BAJAH as 33 cases (43.8% Based on the statistical test obtained by value p 0.001 (OR 3.545, 95% CI 1.594 to 7.884) It can be concluded that there is a significant relationship between the clinical diagnosis with the diagnosis BAJAH