nils-herrmann/clean_scirepeval huggingface dataset:
Preliminary characterization of the mechanical and durability properties of lightweight concrete from Colombian expanded clay aggregates
Venue: 2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria (CONIITI)
Year: 2020

Nowadays, lightweight aggregate concrete (LWAC) made from expanded clay aggregates has become a widely used material around the world. However, the use of this type of concrete has not been implemented on a long scale in Colombia, because expanded clay aggregates have not been fully characterized and tested. For this reason, the objective of this study is to characterize some mechanical and durability properties of lightweight aggregate concrete from Colombian expanded clay. For this purpose, samples of normal weight aggregate concrete (NWAC) and samples of lightweight aggregate concrete (LWAC) with four different contents of expanded clay aggregates (12.5% 25.0% 37.5% and 50.0% by volume of aggregates) were casted. Subsequently, the workability of the fresh concrete, bulk density, compressive strength, and the chloride penetration resistance of hardened concrete samples were characterized. The results showed the inclusion of clay aggregates modifies some properties of the concrete; replacement of 50% of the clay aggregate causes the compressive strength of concrete to decrease by up to 36% However, the chloride penetration resistance was reduced by 33.8% Likewise the concrete bulk density decreased by 22.4% Accordingly, it is preliminarily concluded that expanded clays from Colombian sources have great potential for implementation as aggregates in the manufacture of structural lightweight concrete with allowable mechanical strength but enhanced durability properties.
Recycling combustion ash for sustainable cement production: A critical review with data mining and time series predictive models
Year: 2016

Combustion is a complex process that produces energy as the goal and ashes as by products. The ash of coal, biomass and solid waste combustion can be used as pozzolans in blended cement due to the similarity of their physiochemical properties to conventional pozzolans (e.g. silica fume) This strategy effectively recycles pozzolanic active combustion ash and replaces a significant proportion of Portland cement, which potentially reduces the greenhouse gas (GHG) emissions from cement production. However, cement producers wishing to substitute pozzolanic active ash for conventional pozzolans lack information on the pozzolanic activity (PA) of ash from diverse combustible materials. A data mining model that can extract key information for predicting the PA of combustion ash is envisioned as a screening tool to assess the pozzolanic potential of candidate combustible materials prior to experimental work. Hence, the objectives of this chapter are, 1) to critically review the recent research progress in using various combustion ashes as pozzolans, including the mechanism of the pozzolanic reaction, sources of eligible materials, and methods of PA improvement, 2) to create a data mining artificial neural network (ANN) model for PA prediction built upon data reported in the scientific literature from 1998 to 2015, and 3) to describe the effect of cement curing period on PA, based on a time series model. The ANN and time series models developed in this study can accurately forecast the PA of combustion ashes during 3 90 d curing (R 2 0.8479 0.9914) We recommend these screening tools as rapid indicators of the pozzolanic potential of combustion ash prior to undertaking strength tests and other experimental testing.
Selection Strategies for Atlas Based Mosaicing of Left Atrial 3 D Transesophageal Echocardiography Data.
Venue: Ultrasound in medicine biology
Year: 2018

Three dimensional transesophageal echocardiography (TEE) provides real time soft tissue information, but its use is hampered by its limited field of view. The mosaicing of multiple TEE views makes it possible to visualize a large structure, like the left atrium, in a single volume. To this end, an automatic registration method is required. Similarly to atlas based segmentation approaches, atlas based mosaicing (ABM) uses a full volume atlas set to moderate the onerous registration of the individual TEE views. The performance of ABM depends both on the quality of the involved registrations and on the selection of the optimal transformation from the candidate transformations that result from the various atlases. The study described here explored the performance of different selection strategies on multiview TEE data of the left atrium. We found that by incorporating two stages of transformation selection, using the image similarity and the conformity between the candidate transformations as selection criteria, the average registration error dropped below 3 mm with respect to manual registration of these data. Finally, we used this method for the automatic construction of a wide view TEE volume of the left atrium.
Blockchain Based Edge Computing Resource Allocation in IoT: A Deep Reinforcement Learning Approach
Venue: IEEE Internet of Things Journal
Year: 2021

With the exponential growth in the number of Internet of Things (IoT) devices, the cloud centric computing paradigm can hardly meet the increasingly high requirements for low latency, high bandwidth, ease of availability, and more intelligent services. Therefore, a distributed and decentralized computing architecture is imperative, where edge centric computing, such as fog computing and mist computing, has been recently proposed. Edge centric computing resources can be managed locally and personally rather than being administered by a remote centralized third party. However, security and privacy issues are the main challenges due to the absence of trust between the IoT devices and edge computing nodes (ECNs) A blockchain, as a decentralized, trustless, and immutable public ledger, can well solve the trust absence issue. In this article, we first elaborate on the security and privacy issues of edge computing enabled IoT, and then present the key characteristics of blockchains, which make blockchains well suited for the edge centric IoT scenarios. Furthermore, we propose a general framework for blockchain based edge computing enabled IoT scenarios that specifies the step by step procedure of a single transaction between an IoT end and an ECN. In addition, we design a smart contract within a private blockchain network that exploits the state of the art machine learning algorithm, asynchronous advantage actor critic (A3C) to allocate the edge computing resources, which exemplifies how artificial intelligence (AI) can be combined with blockchains. We further discuss the benefits of the convergence of AI and blockchains. Finally, simulation results are presented.
Differences in Levodopa Response for Progressive and Non Progressive Micrographia in Parkinson's Disease
Venue: Frontiers in Neurology
Year: 2021

Micrographia, one element of the dysgraphia of Parkinson's disease (PD) may be classified according to the presence or absence of a decremental pattern. The decremental form, progressive micrographia, is an expression of the sequence effect seen generally in bradykinesia. Its responsiveness to levodopa has not been evaluated kinematically.  Aim of this study is to investigate the difference in levodopa response for progressive and non progressive micrographia.  Twenty four PD patients and 24 age matched repeatedly wrote the letter e on a computerized digital tablet. PD patients performed the task two times, in a defined off state and again after levodopa. Scripts were classified as progressive micrographia (PDPM) or non progressive micrographia (PDNPM) depending on whether a 10% decrement was seen between the first and final characters of a line of lettering.  While levodopa produced a similar response on the MDS UPDRS motor scale for the two groups, the effect on the two types of micrographia was different. While writing speed improved significantly in both groups after levodopa, the responses were over twofold greater for PDNPM. Moreover, the decremental features of PDPM in size, speed, and pen pressure were largely unaltered by a levodopa dose.  Progressive micrographia is less responsive to levodopa. Our findings agree with research showing that the sequence effect of bradykinesia is relatively resistant to medication. Yet we did not find a weaker overall levodopa motor benefit. Caution is needed in the interpretation of such micrographia measurements for estimating drug responses.
Quantitative evaluation of the matrix effect in bioanalytical methods based on LC MS: A comparison of two approaches
Venue: Journal of pharmaceutical and biomedical analysis
Year: 2018

HIGHLIGHTSNine analytes of different structure were studied.Lack of relevant differences between both calculation methods.CV( of IS norm matrix factor was 0.5% higher than IS norm relative matrix effect.Method adopted by European Medicines Agency seems to be slightly more conservative.  Liquid chromatography coupled to mass spectrometry (LC MS) is a powerful tool for studying pharmacokinetics and toxicokinetics. Reliable bioanalysis requires the characterization of the matrix effect, i.e. influence of the endogenous or exogenous compounds on the analyte signal intensity. We have compared two methods for the quantitation of matrix effect. The CVs( of internal standard normalized matrix factors recommended by the European Medicines Agency were evaluated against internal standard normalized relative matrix effects derived from Matuszewski et al. (2003) Both methods use post extraction spiked samples, but matrix factors require also neat solutions. We have tested both approaches using analytes of diverse chemical structures. The study did not reveal relevant differences in the results obtained with both calculation methods. After normalization with the internal standard, the CV( of the matrix factor was on average 0.5% higher than the corresponding relative matrix effect. The method adopted by the European Medicines Agency seems to be slightly more conservative in the analyzed datasets. Nine analytes of different structures enabled a general overview of the problem, still, further studies are encouraged to confirm our observations.
Cross scene crowd counting via deep convolutional neural networks
Venue: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2015

Cross scene crowd counting is a challenging task where no laborious data annotation is required for counting people in new target surveillance crowd scenes unseen in the training set. The performance of most existing crowd counting methods drops significantly when they are applied to an unseen scene. To address this problem, we propose a deep convolutional neural network (CNN) for crowd counting, and it is trained alternatively with two related learning objectives, crowd density and crowd count. This proposed switchable learning approach is able to obtain better local optimum for both objectives. To handle an unseen target crowd scene, we present a data driven method to fine tune the trained CNN model for the target scene. A new dataset including 108 crowd scenes with nearly 200,000 head annotations is introduced to better evaluate the accuracy of cross scene crowd counting methods. Extensive experiments on the proposed and another two existing datasets demonstrate the effectiveness and reliability of our approach.
What are the factors affecting the progression of kidney failure, mortality and morbidity after cardiac surgery in patients with chronic kidney disease?
Venue: Journal of cardiac surgery
Year: 2021

Acute kidney injury occurs in as many as 40% of patients after cardiac surgery and requires dialysis in 1% of cases and associated with an increased risk of mortality and morbidity, predisposes patients to a longer hospitalization, requires additional treatments, and increases the hospital costs. We aimed to investigate the factors affecting the progression of kidney disease during cardiac surgery in preoperative chronic kidney disease patients (CKD)
Team Effectiveness 1997 2007: A Review of Recent Advancements and a Glimpse Into the Future
Year: 2008

The authors review team research that has been conducted over the past 10 years. They discuss the nature of work teams in context and note the substantive differences underlying different types of teams. They then review representative studies that have appeared in the past decade in the context of an enhanced input process outcome framework that has evolved into an inputs mediators outcome time sensitive approach. They note what has been learned along the way and identify fruitful directions for future research. They close with a reconsideration of the typical team research investigation and call for scholars to embrace the complexity that surrounds modern team based organizational designs as we move forward.
Le financement des universites, les experiences Algeriennes et Quebecoises misent sous les projecteurs
Year: 2019

Pour tout etat l'education et l'enseignement sont des priorites, ils representent le fondement meme sur lequel se base une societe, de part sa transformation, son evolution et son demarquage. Il faut note que le financement des universites differe d'un etat a un autre, et d'un pays a un autre, l'objectif est de faire de l'enseignement superieur et la recherche ainsi que de l'universite le lieu le plus attractif le plus competitif et le plus efficace possible. L'universite n'est pas seulement un contenant (batiment) mais elle represente aussi un contenu (Enseignement Superieur et Recherche ESR) et le defi auquel feront face les universites de demain est de taille et consequent. Il faut donc savoir ecouter et entendre l'universite, et developper ses sens, afin de mieux cerner les besoins de l'universite du futur. Dans ce travail nous allons parler de l'experience inedite quebecoise en matiere d'enseignement superieur et de recherche (ESR) le Quebec a mis en action une nouvelle politique de financement des universites en 2018 2019, l'idee etait de revoir la politique de financement trace en l'an 2000, cette nouvelle politique de financement au Quebec represente le resultat de la concertation et de la cohesion entre les chefs d'etablissements universitaires quebecois et le gouvernement. Une experience inedite est riche en donnees que nous avons decide de vous presenter, pour lever le voile sur cette nouvelle politique de financement des universites quebecoises. Nous tenterons aussi de dresser un etat des lieux du financement de l'enseignement superieur algerien, afin de degager en quoi consiste la strategie algerienne dans ce domaine Et quelles sont ses atouts et ses faiblesses en comparaison avec l'experience quebecoise. Mots cles Universite, politique, financement, Algerie, Quebec, ESR,
Orofacial findings and dental care management in a patient with Robinow Syndrome
Year: 2019

Robinow syndrome is a rare genetic disorder of skeletal development. It is characterized by short stature, facial dysmorphisms and orodental anomalies, underdeveloped genitalia, mesomelic brachymelia.  A 6 year old girl with Robinow Syndrome was referred in the Center for Formation of Human Resources Specialized in Dental Care to Special Needs Patients (Ribeirao Preto, Sao Paulo, Brazil) for evaluation. Medical history investigation and clinical examination were observed in short stature, facial dimorphism and hypoplastic genitalia. Orofacial findings showed retrognathism, a mid line hemangiomaapproximately 1 cm wide with upturned borders, bifid tongue, ankyloglossia, general gingival hypertrophy, deep bite and mild tooth crowding. Cardiac abnormality and neuromotor developmental delay consisted of systemic manifestations present which demanded individualized dental care. The dental treatment consisted of preventive and restoratives procedures to adequate the oral health condition of the patient and orthodontic treatmentwas planned. The patient has been in follow up for six years.  Orofacial anomalies and other alterations found in the present case contributed to complement the orofacialfindings described in the literature and to assist in diagnosis of the syndrome. In this case, amultiprofessional team and integral treatment were essential to rescue oral health and improvelife quality of the patient.
Detection of Compromised Smart Grid Devices with Machine Learning and Convolution Techniques
Venue: 2018 IEEE International Conference on Communications (ICC)
Year: 2018

The smart grid concept has transformed the traditional power grid into a massive cyber physical system that depends on advanced two way communication infrastructure to integrate a myriad of different smart devices. While the introduction of the cyber component has made the grid much more flexible and efficient with so many smart devices, it also broadened the attack surface of the power grid. Particularly, compromised devices pose great danger to the healthy operations of the smart grid. For instance, the attackers can control the devices to change the behaviour of the grid and can impact the measurements. In this paper, to detect such misbehaving malicious smart grid devices, we propose a machine learning and convolution based classification framework. Our framework specifically utilizes system and library call lists at the kernel level of the operating system on both resource limited and resource rich smart grid devices such as RTUs, PLCs, PMUs, and IEDs. Focusing on the types and other valuable features extracted from the system calls, the framework can successfully identify malicious smart grid devices. In order to test the efficacy of the proposed framework, we built a representative testbed conforming to the IEC 61850 protocol suite and evaluated its performance with different system calls. The proposed framework in different evaluation scenarios yields very high accuracy (avg. 91% which reveals that the framework is effective to overcome compromised smart grid devices problem.
Collaborative video blended learning for exercising higher order thinking evaluation using community of inquiry framework
Venue: Int. J. Soc. Media Interact. Learn. Environ.
Year: 2015

This paper presents findings from an examination of different learning experiences in students engaged in intercultural learning activities in a collaborative blended learning environment using video sharing, within a university foreign language course. Learning experience in the video collaborative blended learning environment was evaluated using community of inquiry framework, focusing on cognitive presence in students with different cultural backgrounds. It was hypothesised that multicultural experience would enhance cognitive presence, as profound life experience could fuel higher order thinking. The results of an in depth analysis of diaries kept by six students (two international students, two local students with Asian background, and two local students with a relatively monocultural background) indicated that while prior intercultural experience of individual students plays a key role, both teaching presence and social presence also affect the exercise of higher order thinking.
Estimation of Crown Temperature of Winter Wheat and the Effect on Simulation of Frost Tolerance
Year: 2017

Accurate estimation of winter wheat frost kill in cold temperate agricultural regions is limited by lack of data on soil temperature at wheat crown depth, which determines winter survival. We compared the ability of four models of differing complexity to predict observed soil temperature at 2 cm depth during two winter seasons (2013 14 and 2014 15) at Ultuna, Sweden, and at 1 cm depth at Ilseng and As, Norway. Predicted and observed soil temperature at 2 cm depth was then used in FROSTOL model simulations of the frost tolerance of winter wheat at Ultuna. Compared with the observed soil temperature at 2 cm depth, soil temperature was better predicted by detailed models than simpler models for both seasons at Ultuna. The LT50 (temperature at which 50 of plants die) predictions from FROSTOL model simulations using input from the most detailed soil temperature model agreed better with LT50 FROSTOL outputs from observed soil temperature than what LT50 FROSTOL predictions using temperature from simpler models did. These results highlight the need for simpler temperature prediction tools to be further improved when used to evaluate winter wheat frost kill.
Spatial calibration of large volume photogrammetry based metrology systems
Year: 2015

Photogrammetry systems are used extensively as volumetric measurement tools in a diverse range of applications including gait analysis, robotics and computer generated animation. For precision applications the spatial inaccuracies of these systems are of interest. In this paper, an experimental characterisation of a six camera Vicon T160 photogrammetry system using a high accuracy laser tracker is presented. The study was motivated by empirical observations of the accuracy of the photogrammetry system varying as a function of location within a measurement volume of approximately 100 m3. Error quantification was implemented through simultaneously tracking a target scanned through a sub volume (27 m3) using both systems. The position of the target was measured at each point of a grid in four planes at different heights. In addition, the effect of the use of passive and active calibration artefacts upon system accuracy was investigated. A convex surface was obtained when considering error as a function of position for a fixed height setting confirming the empirical observations when using either calibration artefact. Average errors of 1.48 mm and 3.95 mm were obtained for the active and passive calibration artefacts respectively. However, it was found that through estimating and applying an unknown scale factor relating measurements, the overall accuracy could be improved with average errors reducing to 0.51 mm and 0.59 mm for the active and passive datasets respectively. The precision in the measurements was found to be less than 10 mm for each axis.
Overexpression of microRNA 29b inhibits epithelial mesenchymal transition and angiogenesis of colorectal cancer through the ETV4/ERK/EGFR axis
Venue: Cancer cell international
Year: 2021

Recent studies have reported the involvement of microRNA 29 (miR 29) family members in human cancers through their ability to regulate cellular functions. The present study investigated biological function of miR 29b in colorectal cancer (CRC) Methods CRC tissues and adjacent normal tissues were collected and the expression of ETV4 and miR 29b in the tissues were identified. The relationship between ETV4 and miR 29b or ETV4 expression and the EGFR promoter was identified using dual luciferase reporter gene and CHIP assays. The proliferation, invasion, migration, and apoptosis of CRC HCT116 cells were assayed using MTT assay, Scratch test, Transwell assay, and flow cytometry, respectively. Also, expression of epithelial mesenchymal transition (EMT) markers, angiogenic factors, and vasculogenic mimicry formation were evaluated using RT qPCR and Western blot. Results ETV4 was upregulated, while miR 29b expression was decreased in CRC tissues. ETV4 was identified as a target gene of miR 29b, which in turn inactivated the ERK signaling pathway by targeting ETV4 and inhibiting EGFR transcription. Transfection with miR 29b mimic, siRNA ETV4, or ERK signaling pathway inhibitor U0126 increased expression of E cadherin and TSP 1, and CRC cell apoptosis, yet reduced expression of ERK1/2, MMP 2, MMP 9, Vimentin, and VEGF, as well as inhibiting EMT, angiogenesis, and CRC cell migration and invasion. The EMT, angiogenesis and cancer progression induced by miR 29b inhibitor were reversed by siRNA mediated ETV4 silencing.  29b suppresses angiogenesis and EMT in CRC via the ETV4/ERK/EGFR axis.