nils-herrmann/clean_scirepeval huggingface dataset:
Development of a Nomogram to Predict the Recurrence Score of 21 Gene Prediction Assay in Hormone Receptor Positive Early Breast Cancer.
Venue: Clinical breast cancer
Year: 2019

A 21 gene prediction assay (Oncotype DX) is helpful to estimate benefit from adjuvant chemotherapy in patients with hormone receptor positive, lymph node negative early breast cancer. This study was conducted to develop a model to estimate high recurrence score (RS) using easily available clinicopathologic parameters in limited resource countries.  Hormone receptor positive, lymph node negative early breast cancer patients who underwent Oncotype DX were enrolled onto the training set (n 192) The risk category range of the RS was the same as in the TAILORx study. The multivariable logistic regression model was used to identify significant variables associated with high RS. The independent validation set (n 264) was established from patients of a different time period.  The median age in the training set was 47 years, and 78.0% were premenopausal. The number of patients with low RS 11) intermediate RS (11 25) and high RS 25) were 42 (22.0% 122 (63.9% and 27 (14.1% respectively. High nuclear grade, no progesterone receptor expression, and high Ki 67 were associated with high RS, and these variables were used to construct the nomogram. It had significant discriminatory power in internal validation (area under the curve 0.856) and in the validation set (area under the curve 0.828) The calibration plot showed optimal agreement between predicted and actual probabilities in both sets.  A nomogram was successfully developed with 3 simple parameters. The probability of high RS can be easily and conveniently estimated using our nomogram. It might be useful to determine whether or not Oncotype DX is conducted in the TAILORx era. Future large scale prospective studies are warranted.
Safety assurance mechanisms of collaborative robotic systems in manufacturing
Venue: Robotics Comput. Integr. Manuf.
Year: 2021

Collaborative robots (cobots) are robots that are designed to collaborate with humans in an open workspace. In contrast to industrial robots in an enclosed environment, cobots need additional mechanisms to assure humans' safety in collaborations. It is especially true when a cobot is used in manufacturing environment; since the workload or moving mass is usually large enough to hurt human when a contact occurs. In this article, we are interested in understanding the existing studies on cobots, and especially, the safety requirements, and the methods and challenges of safety assurance. The state of the art of safety assurance of cobots is discussed at the aspects of key functional requirements (FRs) collaboration variants, standardizations, and safety mechanisms. The identified technological bottlenecks are (1) acquiring, processing, and fusing diversified data for risk classification, (2) effectively updating the control to avoid any interference in a real time mode, (3) developing new technologies for the improvement of HMI performances, especially, workloads and speeds, and (4) reducing the overall cost of safety assurance features. To promote cobots in manufacturing applications, the future researches are expected for (1) the systematic theory and methods to design and build cobots with the integration of ergonomic structures, sensing, real time controls, and human robot interfaces, (2) intuitive programming, task driven programming, and skill based programming which incorporate the risk management and the evaluations of biomechanical load and stopping distance, and (3) advanced instrumentations and algorithms for effective sensing, processing, and fusing of diversified data, and machine learning for high level complexity and uncertainty. The needs of the safety assurance of integrated robotic systems are specially discussed with two development examples.
Improved picture naming in aphasia patients treated with cathodal tDCS to inhibit the right Broca's homologue area.
Venue: Restorative neurology and neuroscience
Year: 2011

Previous reports have suggested that noninvasive cortical stimulation could influence speech production in patients with chronic stroke. Here, we evaluated the hypothesis that cathodal transcranial DC stimulation (ctDCS) a technique that decreases excitability of stimulated cortical sites, applied over a healthy right Broca's homologue area could improve picture naming in patients with post stroke aphasia.  Ten right handed patients with post stroke aphasia were enrolled in this double blind, counterbalanced sham controlled, crossover study. Each patient received an intervention of ctDCS (2 mA for 20 min) and of sham tDCS (2 mA for 1 min) daily for 5 consecutive days in a randomized crossover manner with a minimum interval of one week between interventions, over a healthy right Broca's homologue area using a left supraorbital anode and simultaneous daily sessions of conventional word retrieval training. The primary endpoint measure of this study was a standardized, validated Korean version of the Boston Naming Test, which is a measure of picture naming skills.  ctDCS was not found to have any adverse effects. Furthermore, significantly improved picture naming (p 0.02) was observed at 1 hour following the last (5th) ctDCS treatment session, but no changes were observed after sham tDCS.  These results demonstrate that cathodal tDCS over the right healthy Broca's homologue area with a left supraorbital anodal location can improve picture naming task performance in post stroke aphasia.
Figures du lien social chez les adolescents mineurs de justice clinique de l'echange et construction paritaire
Year: 2009

Depuis plusieurs decennies maintenant, le paradigme oedipien joue de ses effets des lors qu'il est question d'apprehender la problematique de la delinquance a l'adolescence. Il se pose regulierement comme point de reference des modeles theoriques et pratiques, animant les politiques de prises en charge tant judiciaires, educatives que therapeutiques. Pourtant, un pan de la clinique nous amene a constater certaines des impasses de ce soubassement chez certains sujets, reiterant les transgressions. L'objectif de cette recherche doctorale est de mettre au jour le glissement de paradigme qu'il est possible d'operer, en reponse a la question suivante comment les adolescents, mineurs de justice, font il emerger le lien social et comment le maintiennent ils ?L'hypothese alors defendue consiste a supposer que ces derniers pourraient ne plus etre homogenes mais heterotopiques. Emerge ainsi, dans l'actualite du pubertaire, une nouvelle geographie du lien aux prises avec une dynamique alteritaire, plus encore paritaire, fondee sur l'echange, ou priment en lieu et place de la genealogie, de la transcendance et de la morale, generation, immanence et ethique. La methodologie de recherche elaboree, conduite aupres de mineurs de justice, nous a permis de degager une construction mythique adolescente organisee autour de quatre axes la position existentielle dans la relation a l'autre, la construction de l'autre comme pluriel, l'echange espace d'inter dits et l'obligo dans son equivocite. Autant de dimensions participant d'un rendez vous manque entre sujet et institutions, et qui nous encouragent a revoir les conditions memes de prises en charge pour des mesures plus efficientes.
XRD, EDX, FTIR and ESR spectroscopic studies of co precipitated Mn substituted Zn ferrite nanoparticles
Venue: Ceramics International
Year: 2019

Co precipitation synthesizing technique was adopted to prepare manganese doped zinc ferrite nanoparticles with varying concentrations 0.5, 0.6, 0.7. EDX proved the consistency of stoichiometry of compositions in the ferrite samples considered under preparation. XRD patterns authenticated the ferrite phase in the investigating samples. The experimental lattice parameter (8.412 8.438 A) is increasing and crystallite size (7.6 6.4 nm) appears to be decreasing with substitution of Mn2+ The grain size (1.1 um) in the sample (x 0.7) with smaller crystallites (6.4 nm) is found to be bigger than that of remaining compositions (x 0.5, 0.6) The vibrational frequencies detected in the FTIR spectra also authorized the obtained spinel phase in the current ferrite systems. The elastic moduli illustrate the mechanical strength of ferrite systems which are dependent on interatomic distances. The variation of line width and Lande's g factor in ESR studies revealed the possibility of core shell morphology of present ferrite nanoparticles.
Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID 19 in the New York City Area.
Venue: JAMA
Year: 2020

Importance There is limited information describing the presenting characteristics and outcomes of US patients requiring hospitalization for coronavirus disease 2019  To describe the clinical characteristics and outcomes of patients with COVID 19 hospitalized in a US health care system.  The study included all sequentially hospitalized patients between March 1, 2020, and April 4, 2020, inclusive of these dates.  Confirmed severe acute respiratory syndrome coronavirus 2 (SARS CoV 2) infection by positive result on polymerase chain reaction testing of a nasopharyngeal sample among patients requiring admission.  Clinical outcomes during hospitalization, such as invasive mechanical ventilation, kidney replacement therapy, and death. Demographics, baseline comorbidities, presenting vital signs, and test results were also collected.  A total of 5700 patients were included (median age, 63 years [interquartile range {IQR} 52 75; range, 0 107 years] 39.7% female) The most common comorbidities were hypertension (3026; 56.6% obesity (1737; 41.7% and diabetes (1808; 33.8% At triage, 30.7% of patients were febrile, 17.3% had a respiratory rate greater than 24 breaths/minute, and 27.8% received supplemental oxygen. The rate of respiratory virus co infection was 2.1% Outcomes were assessed for 2634 patients who were discharged or had died at the study end point. During hospitalization, 373 patients (14.2% (median age, 68 years [IQR, 56 78] 33.5% female) were treated in the intensive care unit care, 320 (12.2% received invasive mechanical ventilation, 81 (3.2% were treated with kidney replacement therapy, and 553 (21% died. Mortality for those requiring mechanical ventilation was 88.1% The median postdischarge follow up time was 4.4 days (IQR, 2.2 9.3) A total of 45 patients (2.2% were readmitted during the study period. The median time to readmission was 3 days (IQR, 1.0 4.5) for readmitted patients. Among the 3066 patients who remained hospitalized at the final study follow up date (median age, 65 years [IQR, 54 75] the median follow up at time of censoring was 4.5 days (IQR, 2.4 8.1)  This case series provides characteristics and early outcomes of sequentially hospitalized patients with confirmed COVID 19 in the New York City area.
The persistence of air pollution in four mega cities of China
Year: 2016

This paper analyses long range fractional dependence of China pollution in four major cities, namely Beijing, Shangai, Guangzhou and Shenzhen from September 28 of 2013 to December 12 of 2015. Unit roots hypotheses are tested by using fractional integration methods using both uncorrelated and autocorrelated errors. The results reveal that the pollution is persistent, meaning that it will continue until strong anti pollution measures are adopted. Policy implication is derived.
Thermal Plasma Treatment of Medical Waste
Venue: Plasma Chemistry and Plasma Processing
Year: 2020

The harmless treatments of medical waste have significantly drawn people's attention owing to their risks to health care staff, the public, and the environment. The traditional thermal technology for processing medical waste may cause indispensable secondary pollution such as dioxin, furan, and heavy metals, and infectious materials that may remain in the solid residual. Thermal plasma technologies offer advantages of effectively treating medical waste due to its high temperature and energy density, lower pollutant emissions, rapid start up and shut down, and smaller size of the installation. These benefits play roles in the treatment of medical waste on site or off site, especially when somewhere encounters an abnormally sharp increase in medical waste. This paper mainly introduces the typical thermal plasma processes of medical waste and its central component, plasma furnace. Meanwhile, how process parameters influence the formed gaseous and solid products, the performances of mass and volume reduction, pathogen destruction, and energy recovery, are discussed in detail. Finally, the mechanism of the thermal plasma process is also analyzed.
Evaluating the performance of the most important Lexicons used to Sentiment analysis and opinions Mining
Year: 2020

With the emergence of social media that includes billions of people from around of the world interacting and sharing data, information, feelings and opinions among themselves on various topics, there is a huge amount of social media data generated by users to explore opinions and analyze emotions. Sentiment analysis aims to classify the polarity of a text based on the writer's opinion, by revealing the positive, negative or neutral sentiments about a particular subject. It is used in marketing, customer service and other fields. State of art approaches for Sentiment analysis are classified in two categories: the first one depends on Machine learning techniques and data mining by training a model on a set of labeled data. Whereas, the second category lexicon based ones give specific weights for each word according to polarity of the word which it belongs, and thus identify the sentiments by comparing text words with preprepared lexicons. This study relies on the methodology of sentiment analysis based on the lexicon based, it focuses on five of the most important and well known lexicons used in the field of sentiment analysis on Twitter data, such as(VADER, SentiWordNet, SentiStrength, Liu and Hu opinion lexicon and AFINN 111) It provides an assessment of the performance of these lexicons in Twitter polarity classification by comparing the overall classification accuracy and the F1 measure The Results show that the accuracy of classification using Vader lexicon were higher for positive and negative sentiments.
MODEM: an UML profile for MODEling and Predicting software Maintenance before implementation
Venue: 2019 International Conference on Computer and Information Sciences (ICCIS)
Year: 2019

A software is developed to satisfy some requirements that could change with respect to technology progress or new clients needs. That is why a software evolves continually in order to fit with occurring requirements. Software evolution or maintenance represents a non trivial issue that should be treated seriously. In fact, according to some studies software maintenance could consume about 80% of software development total cost. In most of works, such issue was treated in a source code level by proposing new techniques and tools that could optimize maintenance cost. In this paper, we treat the same issue but in an earlier phase of software development and exactly in software design. We propose here an UML profile that allows to software developers and designers to carry about maintenance tasks at the design phase in order to predict handling maintenance tasks before happening, to get an historical trace of these tasks and to express explicitly on models some design patterns helping to resolve software maintenance problems in order to make maintenance easier and cheaper.
Enhancement of charge transport in porous carbon nanofiber networks via ZIF 8 enabled welding for flexible supercapacitors
Year: 2020

Lightweight, self supporting, and flexible carbon nanofiber membranes are desirable electrode candidates for flexible supercapacitors. At present, inadequate electrical contact between adjacent nanofibers, poor wettability with electrolyte, and limited specific surface area are still challenges for further improving the capacitive property. In this work, a novel porous N doped carbon nanofiber network membrane in which continuous ZIF 8 derived carbon layers "welding" adjacent carbon nanofibers is synthesized through bifunctional ZnO nanoparticles contained in the nanofibers. Here, ZnO nanoparticles not only serve as the pore forming agent to create multiscale pores, but also provide zinc sources for in situ growth of ZIF 8 nanoparticle layer. Because of highly interconnected networks, special spider web like surface nanostructure, and hierarchical pores, the as prepared carbon membrane reveals superior electrical conductivity, high specific surface area and excellent wettability. An excellent rate performance with 75.5% capacitance retention even with 70 times current density increase and extraordinary cycling stability (98.8% capacitance retention after 100,000 cycles at 10 A g 1) could be found, when the optimized hierarchically porous N doped welded carbon network membrane is used as the electrode. The quantitatively electrochemical kinetic analysis of the electrode indicates that fast double layer capacitive behavior is dominant at high current densities. Meanwhile, the flexible quasi solid state devices display excellent electrochemical stability in severely bending states.
Effects of Orthokeratology on Choroidal Thickness and Axial Length
Venue: Optometry and vision science official publication of the American Academy of Optometry
Year: 2016

To investigate the effect of orthokeratology (ortho k) treatment on choroidal thickness and its relationship with axial length change.  Seventy seven myopic subjects aged between 7 and 17 years were treated with ortho k lenses (n 39) or single vision spectacle lenses (SVL, n 38) Choroidal thickness and axial length measurements were taken at baseline and repeated 1 week and 3 weeks after lens wear for the ortho k group and at 3 weeks for the SVL group. Parafoveal choroidal thickness was assessed using optical coherence tomography and segmented into nine regions according to the Early Treatment Diabetic Retinopathy Study (ETDRS) within a 6 x 6 mm circular zone centered on the fovea. Axial length was measured using partial coherence interferometry. The changes in subfoveal choroidal thickness were compared to the changes in axial length in both study groups.  The change in axial length was significantly correlated with the change in choroidal thickness in both groups at 3 weeks (ortho k, r 0.351, p 0.028 vs. SVL, r 0.408, p 0.011) Parafoveal choroidal thickness increased after 3 weeks of lens wear in the ortho k group (mean, 21.8 25.2 &mgr;m) but did not change in the SVL group (mean, 0.1 19.7 &mgr;m) Choroidal thickness significantly varied across the posterior retinal regions (F 82.14, p 0.001) with the temporal regions being thickest and nasal regions being thinnest. After 3 weeks of ortho k treatment, the magnitude of change (range, 14.1 27.6 &mgr;m) in choroidal thickness of the nine ETDRS regions was proportional to the baseline choroidal thickness in those regions (r 0.88, p 0.002) Axial length did not significantly change over time (F 0.001, p 0.975) and did not differ between the two treatment modalities (F 0.305, p 0.582) Conclusions Choroidal thickness increases after short term ortho k treatment. Regional choroidal thickening after ortho k treatment may be attributable to the altered retinal defocus profile associated with ortho k lens wear.
Language Models with RNNs for Rescoring Hypotheses of Russian ASR
Venue: ISNN
Year: 2016

In this paper, we describe a research of recurrent neural networks (RNNs) for language modeling in large vocabulary continuous speech recognition for Russian. We experimented with recurrent neural networks with different number of units in the hidden layer. RNN based and 3 gram language models (LMs) were trained using the text corpus of 350M words. Obtained RNN based language models were used for N best list rescoring for automatic continuous Russian speech recognition. We tested also a linear interpolation of RNN LMs with the baseline 3 gram LM and achieved 14 relative reduction of the word error rate (WER) with respect to the baseline 3 gram model.
Adsorption behavior of Cr(VI) by magnetically modified Enteromorpha prolifera based biochar and the toxicity analysis.
Venue: Journal of hazardous materials
Year: 2020

Enteromorpha prolifera (EP) biomass collected from a lake in China was employed for biochar production. The EP biochar was magnetically modified by loading g Fe2O3 particles on the surface, and Cr(VI) adsorption behavior and mechanism were evaluated. The magnetic biochar had higher surface polarity, specific surface area and exhibited a higher Cr(VI) adsorption capacity of 95.23 mg/g biochar compared with pristine EP biochar. The pronounced electron spin resonance (ESR) signals showed that the environmental persistent free radicals (EPFRs) preferred to form at lower pyrolysis temperature and lower transition metal concentration. The g factors of BC400, BC800 and BCF400 were 1.8959, 1.7955 and 1.7954, respectively, indicating that the EPFRs mainly used carbon atom as center. In addition, biological toxicity of magnetic EP biochar was tested using the microalga Scenedesmus obliquus. Exposure of S. obliquus cells to magnetic biochar led to the accumulation of reactive oxygen species (ROS) and oxidative stress. The leaching solution toxicity of BCF400 was stronger than BCF800. Thus, the magnetic EP biochar prepared at higher temperature (such as BCF800) provide better Cr (VI) performance with low biologic toxicity. And the EP biomass could be a promising low cost feedstock for biochar production.
Active Knowledge Graph Completion
Venue: SEMWEB
Year: 2020

Knowledge graphs (KGs) proliferating on the Web are known to be incomplete. Much research has been proposed for automatic completion, sometimes by rule learning, that scales well. All existing methods learn closed rules. Here we introduce open path (OP) rules and present a novel algorithm, oprl, for learning them. While closed rules are used to complete a KG by answering given queries, OP rules identify the incompleteness of a KG by inducing such queries to ask. We use adaptations of Freebase, YAGO2, and a synthetic but complete Poker KG to evaluate oprl. We find that oprl mines hundreds of accurate rules from massive KGs with up to 1M facts. The learnt OP rules induce queries with precision up to 98% and recall of 62% on a complete KG, demonstrating the first solution for active knowledge graph completion.
Risk and Return Evaluation of Malaysian Mutual Fund Market
Year: 2019

Mutual funds are growing tremendously in Malaysia. Many investors have no time to select individual stocks or bonds in the market due to limited time, money and knowledge. Hence, mutual fund has to show up as a useful and preferred investment tool in the Malaysian market. Ten portfolios were chosen from two prominent mutual fund companies in Malaysia. Performance evaluation and risk measurements were applied to understand the performance of each portfolio. Paired T test was tested on two portfolios with 45 individual stock in each portfolio. The result was rather intriguing as what was initially expected. There appear to be a difference in terms of decision when applying fundamental measurement using existing concept and measures such as Sharpe and Treynor. To conclude, there is no significant difference in items of risk and return performance in Conventional and Islamic mutual funds. However, further validation can be done with larger sample size or portfolio.