nils-herrmann/clean_scirepeval huggingface dataset:
Design of Two Channel Infusion Pump Analyzer Using Photo Diode Detector
Year: 2021

April 5, 2021  April 15,2021 Accepted: May 10, 2021 In the medical world, patient safety is a top priority. The large number of workloads and the frequency of using the devices in the long run will affect the accuracy and accuracy of the tool. If the flow rate and volume of the syringe pump or infusion pump given to the patient are not controlled (overdose or the fluid flow rate is too high) it can cause hypertension, heart failure or pulmonary edema. Therefore, it is necessary to have a calibration, which is an application activity to determine the correctness of the designation of the measuring instrument or measuring material. The purpose of this research is to make a two channel infusion device analyzer using a photodiode sensor. The contribution of this research is that the system can display three calibration results in one measurement at the same setting and can calibrate 2 tools simultaneously. The design of the module is in the form of an infrared photodiode sensor for reading the flowrate value. This study uses an infrared photodiode sensor for channels 1 and 2 installed in the chamber. This study uses a flow rate formula that is applied to the water level system to obtain 3 calibration results. Infrared photodiode sensor will detect the presence of water flowing in the chamber from an infusion or syringe pump. Then the sensor output will be processed by STM32 and 3 calibration results will be displayed on the 20x4 LCD. This tool has an average error value on channel 1 of 3.50% and on channel 2 of 3.39% It can be concluded that the whole system can work well, the placement and distance between the infrared photodiodes also affects the sensor readings.
Detection of Fake and Provokative Comments in Social Network Using Machine Learning
Venue: 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus)
Year: 2020

Nowadays internet trolls have big impact on other users, it interferes with comfortable use. Objective of the project is creating model for identifying provocative and fake comments. Science articles about detection of trolls by hand were searched for making the criteria of relevant comments selection. To achieve the goal there were created two artificial neural networks: definition of sarcasm and definition of sentiment analysis. The program result is datasets of troll comments and fake comments, statistic and diagrams of definition.
Coffee and the Countryside: Small Farmers and Sustainable Development in Las Segovias de Nicaragua
Year: 2012

Las Segovias de Nicaragua is a highland tropical region along the Rio Coco and the Honduran border in the northern part of the country. Over the past decade and a half, efforts to introduce and establish organic coffee production methods and cooperative organization models have focused on the impoverished rural inhabitants of this region. This approach represents a significant shift in international development policies toward Third World producer nations. I engaged in this context to question the viability of organic coffee farming given the legacy of deceit, violence, and natural disasters that have plagued this region since the Spanish Conquest. The historical and cultural antecedents to this development mode inform the pace and direction in which presumably 'sustainable' innovations to this traditionally exploitative, century old coffee industry take form. I conducted ethnographic research over two years with the small scale coffee farmer community of Las Grietas within the municipality of San Juan del Rio Coco to understand how these innovations are received and embraced by the inhabitants of this
On the mechanism of the Skraup Doebner Von Miller quinoline synthesis.
Venue: The Journal of organic chemistry
Year: 2006

The mechanism of the formation of substituted quinolines from anilines and alpha,beta unsaturated ketones has been studied by the use of 13C labeled ketones in cross over experiments. In the reaction of doubly labeled 13C(2,4) mesityl oxide, a 100% scrambling of the label in the quinoline product was observed, whereas only a small (5 10% amount of the starting mesityl oxide showed scrambling of the label. Similarly, the reaction of triply labeled pulegone clearly shows that the label in the product is 100% scrambled, whereas the label in the starting pulegone is retained. On the basis of these studies, a mechanistic pathway for the Skraup quinoline synthesis is proposed that involves a fragmentation recombination mechanism. The aniline component condenses with the alpha,beta unsaturated ketone initially in a conjugate fashion, followed by a fragmentation to the corresponding imine and the ketone itself. These fragments recombine to form the quinoline product.
The Relationship among Reading Interest, Vocabulary Mastery, and Short Story Writing Skills of Indonesian Language and Literature Education Study Program Students of Tridinanti University Palembang
Year: 2019

This study aimed to examine the relationship among reading interest, vocabulary mastery, and short story writing skill of Indonesian language and Literature Education Study Program students of Tridinanti University Palembang. A correlational research was used as the design of this study. 20 students participated as the sample of the study. To obtain the data, tests and questionnaire were administered. Based on the data analyses, it was found that there was a low correlation between student's reading interest and their vocabulary mastery (r value =0.278 and r value 0.234) Student's reading interest and their writing skill of short story were weakly correlated (r value 0.053 and rvalue 0.82) However, student's vocabulary mastery and their short story writing skill signified strong correlation (r value 0.803 and r value 0.000) Meanwhile, the result of partial correlation analysis indicated that there was a moderate positive correlation (r value 0.540 and r value 0,017) among student's reading interest, vocabulary mastery, and writing skill of short story.  reading, vocabulary mastery and short story writing
Feedback motion planning of legged robots by composing orbital Lyapunov functions using rapidly exploring random trees
Venue: 2019 International Conference on Robotics and Automation (ICRA)
Year: 2019

We present a sampling based framework for feedback motion planning of legged robots. Our framework is based on switching between limit cycles at a fixed instance of motion, the Poincare section (e.g. apex or touchdown) by finding overlaps between the regions of attraction (ROA) of two limit cycles. First, we assume a candidate orbital Lyapunov function (OLF) and define a ROA at the Poincare section. Next, we solve multiple trajectory optimization problems, one for each sampled initial condition on the ROA to minimize an energy metric and subject to the exponential convergence of the OLF between two steps. The result is a table of control actions and the corresponding initial conditions at the Poincare section. Then we develop a control policy for each control action as a function of the initial condition using deep learning neural networks. The control policy is validated by testing on initial conditions sampled on ROA of randomly chosen limit cycles. Finally, the rapidly exploring random tree algorithm is adopted to plan transitions between the limit cycles using the ROAs. The approach is demonstrated on a hopper model to achieve velocity and height transitions between steps.
Fabrication of sandwich structured cellulose composite membranes for switchable infrared radiation
Venue: Cellulose
Year: 2019

Developing a feasible and efficient biomass based membrane for energy saving applications is critical for addressing greenhouse effect and energy crises. Herein, a sandwich structured cellulose composite membrane with controllable thermal management properties was fabricated via the assembly of Ag nanoparticles/cellulose (ANPs/C) ultralong MnO2 nanowires (UMNWs) and MnO2 nanosheets/cellulose (MNSs/C) In this strategy, the UMNWs as building blocks were prepared by hydrothermal method. Then, the ANPs/C and MNSs/C were fabricated via magnetron sputtering and in situ growth method, respectively. Finally, the cellulose composite membrane (CCM) was fabricated via vacuum filtration of cotton cellulose (CC) UMNWs and MNSs/C suspension, and subsequently the CC surfaces were covered with the ANPs by magnetron sputtering. The sandwich structured CCM exhibits Janus infrared radiation properties due the asymmetrical surface structure and chemical compositions. The ANPs layer has high infrared reflectivity of 91.6% however, the MNSs/C layer shows the low infrared reflectivity with 62.7% The results indicate that the Janus sandwich CCM not only can efficiently reflect infrared heat back toward the body, in order to achieve highly thermal insulating under low temperature environment, but also can achieve highly passive cooling under high temperature environment. In addition, the CCM exhibits excellent antibacterial properties due to presence of ANPs, which is beneficial to enhance the lifespan of the personal thermal management membrane. The present work may give some insight to prepare sandwich structured membranes with controllable thermal management properties for application in wearable textiles.
How Satisfied are the Self Employed? A Life Domain View
Year: 2016

It is well known in the literature that self employment positively influences job satisfaction, but the effects on other life domains and overall life satisfaction are much less clear. Our study analyzes the welfare effects of self employment apart from its monetary aspects, and focuses on the overall life satisfaction as well as different domain satisfactions of self employed individuals in our German sample from 1997 to 2010. Using matching estimators to create an appropriate control group and differentiating between different types of self employment, we find that voluntary self employment brings with it positive benefits apart from work satisfaction, and leads to higher overall life satisfaction as well as increased health satisfaction, all of which increase in the first three years of self employment. Being forced into self employment to escape unemployment, however, confers no such benefits. Additionally, both types of self employment lead to increasing dissatisfaction with one's leisure time.
New Nanoparticle Formulation for Cyclosporin A: In Vitro Assessment
Venue: Pharmaceutics
Year: 2021

Cyclosporin A (CsA) is a molecule with well known immunosuppressive properties. As it also acts on the opening of mitochondrial permeability transition pore (mPTP) CsA has been evaluated for ischemic heart diseases (IHD) However, its distribution throughout the body and its physicochemical characteristics strongly limit the use of CsA for intravenous administration. In this context, nanoparticles (NPs) have emerged as an opportunity to circumvent the above mentioned limitations. We have developed in our laboratory an innovative nanoformulation based on the covalent bond between squalene (Sq) and cyclosporin A to avoid burst release phenomena and increase drug loading. After a thorough characterization of the bioconjugate, we proceeded with a nanoprecipitation in aqueous medium in order to obtain SqCsA NPs of well defined size. The SqCsA NPs were further characterized using dynamic light scattering (DLS) cryogenic transmission electron microscopy (cryoTEM) and high performance liquid chromatography (HPLC) and their cytotoxicity was evaluated. As the goal is to employ them for IHD, we evaluated the cardioprotective capacity on two cardiac cell lines. A strong cardioprotective effect was observed on cardiomyoblasts subjected to experimental hypoxia/reoxygenation. Further research is needed in order to understand the mechanisms of action of SqCsA NPs in cells. This new formulation of CsA could pave the way for possible medical application.
A spatial SEIRS reaction diffusion model in heterogeneous environment
Venue: Journal of Differential Equations
Year: 2019

We propose a susceptible exposed infected recovered susceptible (SEIRS) reaction diffusion model, where the disease transmission and recovery rates can be spatially heterogeneous. The basic reproduction number R 0 is connected with the principal eigenvalue of a linear cooperative elliptic system. Threshold type results on the global dynamics in terms of R 0 are established. The monotonicity of R 0 with respect to the diffusion rates of the exposed and infected individuals, which does not hold in general, is established in several cases. Finally, the asymptotic profile of the endemic equilibrium is investigated when the diffusion rate of the susceptible individuals is small. Our results reveal the importance of the movement of the exposed and recovered individuals in disease dynamics, as opposed to most of previous works which solely focused on the movement of the susceptible and infected individuals.
A Distributed Deep Learning System for Web Attack Detection on Edge Devices
Venue: IEEE Transactions on Industrial Informatics
Year: 2020

With the development of Internet of Things (IoT) and cloud technologies, numerous IoT devices and sensors transmit huge amounts of data to cloud data centers for further processing. While providing us considerable convenience, cloud based computing and storage also bring us many security problems, such as the abuse of information collection and concentrated web servers in the cloud. Traditional intrusion detection systems and web application firewalls are becoming incompatible with the new network environment, and related systems with machine learning or deep learning are emerging. However, cloud IoT systems increase attacks against web servers, since data centralization carries a more attractive reward. In this article, based on distributed deep learning, we propose a web attack detection system that takes advantage of analyzing URLs. The system is designed to detect web attacks and is deployed on edge devices. The cloud handles the above challenges in the paradigm of the Edge of Things. Multiple concurrent deep models are used to enhance the stability of the system and the convenience in updating. We implemented experiments on the system with two concurrent deep models and compared the system with existing systems by using several datasets. The experimental results with 99.410% in accuracy, 98.91% in true positive rate (TPR) and 99.55% in detection rate of normal requests (DRN) demonstrate the system is competitive in detecting web attacks.
Characterization and anti diabetic effects of the oligosaccharide fraction isolated from Rosa canina in STZ Induced diabetic rats.
Venue: Carbohydrate research
Year: 2020

Diabetes mellitus is the most common metabolic disorder characterized by chronic hyperglycemia. There has been a surge of research studies aiming to use natural products in the management of diabetes. The objective of this study was to isolate and characterize the structure and anti diabetic mechanisms of the main ingredient from Rosa canina. The oligosaccharide was isolated from Rosa canina fruits and characterized by a combination of FTIR, NMR and Mass spectrometry. Wistar rats were divided into negative control, diabetic (type 2) isolated oligosaccharide (IO) treated diabetic and positive diabetic controls. Oral glucose tolerance, gluconeogenesis and a glucosidase inhibitory tests as well as immunohistochemistry and quantitative real time PCR were performed to elucidate the molecular anti diabetic mechanisms of IO. Structural analyses confirmed the oligosaccharide structure of isolated fraction. Gluconeogenesis and a glucosidase activity were inhibited by IO in diabetic rats. The oral glucose tolerance test was improved significantly in the group treated with the IO (P 0.05) Pancreatic b cells and tissue pathological examination showed a significant improvement after the treatment period. In addition, the expression of Ngn3, Nkx6.1 and insulin increased in oligosaccharide treated compared to untreated diabetic rats. Owing to the verified anti diabetic effects and regenerative potential, isolated oligosaccharide could be considered as the promising drug in the management of diabetes.
Hybrid real time tracking of non rigid objects under occlusions
Venue: Electronic Imaging
Year: 2009

A mean shift algorithm has gained special attention in recent years due to its simplicity to enable real time tracking. However, the traditional mean shift tracking algorithm can fail to track target under occlusions. In this paper we propose a novel technique which alleviates the limitation of mean shift tracking. Our algorithm employs the Kalman filter to estimate the target dynamics information. Moreover, the proposed algorithm performs the background check process to calculate the similarity which expresses how similar to target the background is. We then find the exact target position combining the motion estimation by Kalman filter and the color based estimation by the mean shift algorithm based on the similarity value. Therefore, the proposed algorithm can robustly track targets under several types of occlusion, while the mean shift and mean shift Kalman filter algorithms fail.
Shakespeare sob o olhar sul africano: Macbeth na adaptacao uMabatha, de Welcome Msomi
Year: 2017

ix INTRODUCAO Tentando romper as barreiras..1 CAPITULO 1 Da natureza a arte: a presenca da adaptacao..7 1.1.  Do teatro para o teatro: a transculturacao na adaptacao..19 1.3. O pos colonialismo e os estudos culturais na adaptacao..23 CAPITULO 2 A vida e um palco: o limiar da arte..28 2.1. Shakespeare: o grande adaptador..30 2.2.As origens de Macbeth..35 2.3. O poder em Macbeth..41 CAPITULO 3 A arte rompendo fronteiras: o encontro de culturas atraves da adaptacao..47 3.1. O apartheid na Africa do Sul: um breve contexto historico..48 3.1.1. O Teatro no periodo do apartheid..53 3.2 Welcome Msomi e a peca uMabatha: a cultura Zulu em foco..57 3.3 Macbeth versus uMabatha: a arte como libertacao .66 CONSIDERACOES FINAIS Em defesa da arte: desatando os nos coloniais..74 REFERENCIAS..82 ANEXOS..89
Adjustment From Temperature Annual Dynamics for Reconstructing Land Surface Temperature Based on Downscaled Microwave Observations
Venue: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Year: 2020

Land surface temperature (LST) is crucial to wide varieties of environmental issues, whereas its low tolerance to cloud contamination greatly challenges its applications. Passive microwave (PMW) measurements are employed to retrieve LST due to its great capability of penetrating clouds. Despite great efforts from previous studies, their further applications are limited by coarse resolution of PMW, uncertainty from cloudy coverage, and less attention on large scale applications. To address these problems, this article proposes a method combining adjustment from annual temperature circle to reconstruct LST based on downscaled microwave observations over mainland China. In order to conduct a comprehensive and solid accuracy evaluation, the proposed method is validated according to three strategies namely comparing with moderate resolution imaging spectroradiometer (MODIS) LST, ground surface temperature, and in situ observations from the Heihe Watershed Allied Telemetry Experimental Research, respectively. In the strategy 1, mean root mean square error (RMSE) of predicted LST is 2.39 K and 1.33 K at day and night. According to the strategy 2, mean RMSE of MODIS, predicted and merged LST is 4.97 K, 5.07 K, and 4.93 K at daytime, and 2.32 K, 4.57 K, and 3.39 K at nighttime. In the strategy 3, they are 3.75 K, 3.90 K, and 2.87 K at day, and 2.80 K, 3.61 K, and 2.79 K at night. Furthermore, adjustments from annual temperature cycle are discussed. The proposed method is promising in future research for reconstructing LST with high spatiotemporal resolution at large scales thanks to its simple process, high accuracy, and seamless reconstruction.
Deep Learning Based Joint Detection and Decoding of Non Orthogonal Multiple Access Systems
Venue: 2018 IEEE Globecom Workshops (GC Wkshps)
Year: 2018

In recent years, many studies have applied deep learning techniques to the field of communication. Many of them have achieved reduced complexity or improved performance. In this paper, we apply deep learning techniques to joint multiuser detection and decoding of non orthogonal multiple access system. We construct the neural network detector and decoder based on message passing algorithm (MPA) and belief propagation (BP) algorithm, respectively. And the decoder is cascaded with the detector to form a larger neural network. To achieve this, we assign weights to the edges of the respective factor graphs and then use deep learning approaches to train these weights to get better performance. Compared with the conventional method (i.e. MPA for multiuser detection and BP for decoding) the proposed method improves the joint detection and decoding performance, while the computational complexity is not greatly increased.
Pre cardiopulmonary bypass administration of dexmedetomidine decreases cardiac troponin I level following cardiac surgery with sevoflurane postconditioning
Venue: The Journal of international medical research
Year: 2019

This study was performed to determine the effect of dexmedetomidine (DEX) administration on myocardial damage in cardiac surgery with sevoflurane postconditioning.  We retrospectively examined all cardiac valve replacement surgeries from 1 April 2016 to 30 April 2017. Eligible patients were divided into two groups based on whether DEX was infused. DEX infusion was permitted only between intubation and the beginning of cardiopulmonary bypass (CPB) Sevoflurane was inhaled via the standard postconditioning procedure starting at aortic declamping. The cardiac troponin I (cTnI) level was measured at different time points. The postoperative outcomes and complications were also analyzed.  One hundred patients were included in the study (DEX group, n 53; non DEX group, n 47) Increased cTnI levels were significantly correlated with the New York Heart Association classification, CPB time, and DEX use. DEX use and the CPB time were potential independent factors contributing to changes in the cTnI level. The cTnI level at 6, 12, and 24 hours postoperatively was remarkably lower in the DEX than non DEX group by 1.14, 7.83, and 5.86 ng/mL, respectively.  DEX decreased the cTnI level after CPB when sevoflurane postconditioning was used, especially at 6, 12, and 24 hours postoperatively.
A Multi task Learning Approach to Adapting Bilingual Word Embeddings for Cross lingual Named Entity Recognition
Venue: IJCNLP
Year: 2017

We show how to adapt bilingual word embeddings (BWE's) to bootstrap a cross lingual name entity recognition (NER) system in a language with no labeled data. We assume a setting where we are given a comparable corpus with NER labels for the source language only; our goal is to build a NER model for the target language. The proposed multi task model jointly trains bilingual word embeddings while optimizing a NER objective. This creates word embeddings that are both shared between languages and fine tuned for the NER task.
On the Improvement of the Identification Procedure of the Occupational Injury in China
Year: 2017

The identification procedure of the occupational injury in China is so complicated that it impedes the preconceived effect of the occupational injury insurance severely. This thesis collected 2774 judicial documents of Chinese courts from the Pkulaw database. On the foundation of the present system of the identification procedure and the analysis of the judicial documents, it's found that both the time cost and the evidences in the cases of the occupational injury are not reasonable. We should simplify the procedure to improve Chinese occupational injury insurance system. On one hand, we should cancel the identification as the pre procedure of the application of industrial injury insurance. On the other hand, the injured worker should be allowed to file an incidental civil action in the administrative suit.