nils-herrmann/clean_scirepeval huggingface dataset:
NCU IISR/AS GIS: Results of Various Pre trained Biomedical Language Models and Linear Regression Model in BioASQ Task 9b Phase B
Venue: CLEF
Year: 2021

Transformer has been widely applied in Natural Language Processing (NLP) field, and it also results in an amount of pre trained language models like BioBERT, SciBERT, NCBI_Bluebert, and PubMedBERT. In this paper, we introduce our system for the BioASQ Task 9b Phase B. We employed various pre trained biomedical language models, including BioBERT, BioBERT MNLI, and PubMedBERT, to generate "exact" answers for the questions, and a linear regression model with our sentence embedding to construct the top n sentences as a prediction for "ideal" answers.
Preventability of maternal near miss and mortality in Rwanda: A case series from the University Teaching Hospital of Kigali (CHUK)
Venue: PloS one
Year: 2018

Assess the primary causes and preventability of maternal near misses (MNM) and mortalities (MM) at the largest tertiary referral hospital in Rwanda, Kigali University Teaching Hospital (CHUK)  We reviewed records for all women admitted to CHUK with pregnancy related complications between January 1st, 2015 and December 31st, 2015. All maternal deaths and near misses, based on WHO near miss criteria were reviewed ( A committee of physicians actively involved in the care of pregnant women in the obstetric gynecology department reviewed all maternal near misses/ pregnancy related deaths to determine the preventability of these outcomes. Preventability was assessed using the Three Delays Model.[1] Descriptive statistics were used to show qualitative and quantitative outcomes of the maternal near miss and mortality.  We identified 121 maternal near miss (MNM) and maternal deaths. The most common causes of maternal near miss and maternal death were sepsis/severe systemic infection (33.9% postpartum hemorrhage (28.1% and complications from eclampsia (18.2%/severe preeclampsia (5.8% In our obstetric population, MNM and deaths occurred in 87.6% and 12.4% respectively. Facility level delays (diagnostic and therapeutic) through human error or mismanagement (provider issues) were the most common preventable factors accounting for 65.3% of preventable maternal near miss and 10.7% maternal deaths, respectively. Lack of supplies, blood, medicines, ICU space, and equipment (system issues) were responsible for 5.8% of preventable maternal near misses and 2.5% of preventable maternal deaths. Delays in seeking care contributed to 22.3% of cases and delays in arrival from home to care facilities resulted in 9.1% of near misses and mortalities. Cesarean delivery was the most common procedure associated with sepsis/death in our population. Previous cesarean delivery (24% and obstructed/prolonged labor (13.2% contributed to maternal near miss and mortalities.  The most common preventable causes of MNM and deaths were medical errors, shortage of medical supplies, and lack of patient education/understanding of obstetric emergencies. Reduction in medical errors, improved supply/equipment availability and patient education in early recognition of pregnancy related danger signs will reduce the majority of delays associated with MNM and mortality in our population.
A Direct Dense Visual Servoing Approach Using Photometric Moments
Venue: IEEE Transactions on Robotics
Year: 2018

In this paper, visual servoing based on photometric moments is advocated. A direct approach is chosen by which the extraction of geometric primitives, visual tracking and image matching steps of a conventional visual servoing pipeline can be bypassed. A vital challenge in photometric methods is the change in the image resulting from the appearance and disappearance of portions of the scene from the camera field of view during the servo. To tackle this issue, a general model for the photometric moments enhanced with spatial weighting is proposed. The interaction matrix for these spatially weighted photometric moments is derived in an analytical form. The correctness of the modeling, effectiveness of the proposed strategy in handling the exogenous regions, and improved convergence domain are demonstrated with a combination of simulation and the experimental results.
Young children's understanding of ownership rights for newly made objects
Year: 2014

Young children often use simple rules of thumb to infer ownership of objects, but do they also understand ownership rights? We investigated whether 2 and 3 year olds would react to violations of ownership rights in the context of newly made objects. In Experiment 1, children protested and made spontaneous reference to ownership when a puppet took away the child's object, but protested little when a third party's objects were at stake. Yet, 3 year olds attributed ownership to the third party when asked ownership questions. Children's ownership claims were due to the effort invested in making new things, as they rarely used ownership protest after having handled raw materials (Experiment 2) Two and 3 year olds thus showed an appreciation of ownership rights for their own newly made objects. While 3 year olds understood third party ownership, they may have lacked the motivation to intervene in ownership rights violations involving a third party.
PROPUESTA PARA ORDENAR LA GESTION AMBIENTAL EN UNA EMPRESA DE PRODUCCION O SERVICIOS
Year: 2016

Se presentan los resultados de un trabajo realizado en la localidad de Machala, con el objetivo de elaborar una propuesta para ordenar la Gestion Ambiental en empresas de produccion o servicios. Se utiliza como metodo la revision documental, lo que permite desde la interpretacion de la Norma ISO 14 000, identificar los elementos a tomar en consideracion para el diseno de los procedimientos, que conforman la arquitectura del sistema y fundamentar el como o, el porque y el para que de cada uno de los elementos que de caracter voluntario establece esta norma. Como resultado se logra una propuesta que hace mas entendible el proceder a nivel organizacional en el proceso de ordenar su gestion ambiental y con ello, el control de los desechos peligrosos, se orienta mejor los esfuerzos en la reduccion de sus impactos ambientales. Palabras clave: Arquitectura del sistema, desechos peligrosos, gestion ambiental, impactos ambientales, Norma ISO 14 000.  The results of a work done in the city of Machala, with the aim of developing a proposal to order the Environmental Management in production or services companies are presented. As a method it was used document review which allows from the interpretation of ISO 14 000, identifying the elements to be taken into consideration in designing procedures which make up the base system architecture and how or why and for what each of the elements which set the voluntary nature of the standard. As a result it is achieved a proposal which makes more understandable the proceeding at the organizational level in the process of ordering their environmental management and with it, the control of hazardous wastes, guiding efforts better in reducing their environmental.  System architecture, hazardous waste, environmental management, environmental impacts, ISO 14 000.
Detecting Adversarial Perturbations Through Spatial Behavior in Activation Spaces
Venue: 2019 International Joint Conference on Neural Networks (IJCNN)
Year: 2019

Although neural network based classifiers outperform humans in a range of tasks, they are still prone to manipulation through adversarial perturbations. Prior research has resulted in the identification of effective defense mechanisms for many reported attack methods, however a defense against the C&W attack, as well as a holistic defense mechanism capable of countering multiple different attack methods, are still missing.All attack methods reported so far share a common goal. They aim to avoid detection by limiting the allowed perturbation magnitude, and still trigger incorrect classification. As a result, small perturbations cause classification to shift from one class to another.We coined the term activation spaces to refer to the hyperspaces formed by the activation values of the different network layers. We then use activation spaces to capture the differences in spatial dynamics between normal and adversarial examples, and form a novel adversarial example detector. We induce a set of k nearest neighbor (k NN) classifiers, one per activation space, and leverage those classifiers to assign a sequence of class labels to each input of the neural network. We then calculate the likelihood of each observed label sequence and show that sequences associated with adversarial examples are far less likely than those of normal examples.We demonstrate the efficiency of our proposed detector against the C&W attack using two image classification datasets (MNIST, CIFAR 10) achieving an AUC of 0.97 for the CIFAR 10 dataset. We further show how our detector can be easily augmented with previously suggested defense methods to form a holistic multi purpose defense mechanism.
Notice of Retraction Numberical simulation of low specific speed centrifugal pump cavitation influence of pressure pulsation under different conditions
Year: 2010

According to the cavitation of centrifugal pump which produces in the condition of operating at off design and inhale height exceeds the value of prescribed limit, the cavitation arouse pressure pulsation aggravate, so cause the performance of centrifugal pump that drops. Adopt RNG k e simulated technology model to study the relation between the pressure pulsation and cavitation of centrifugal pump, the researched operating condition includes design and off design operating condition, the design point of operating is specified QBET of rate of flow, the off design points are 0.5 QBET, 0.8 QBET, 1.3 QBET and 1.5 QBET. As the result show, at different operating conditions, duration, location, periodicity and the size of bubble area are changed. At design operation condition the cavitation regional, cavitation duration, pressure pulsation amplitude is minimum; The more deviate the design condition, the cavitation duration grows the more, and in the high rate of flow the cavitation most serious. At low rate of flow of 0.5 QBET cavitation produce mainly in inlet of blade reverse side, pressure pulsation amplitude is the 1.8 times of design operating condition; At high orate of flow of 1.5 QBET, cavitation produce mainly in Inlet of blade pressure side, pressure pulsation amplitude is the 2.6 times of design operating mode.
A passive forensic method for video: Exposing dynamic object removal and frame duplication in the digital video using sensor noise features
Venue: J. Intell. Fuzzy Syst.
Year: 2017

The purpose of this paper is to detect tampering in the video using passive forensic method. With the extensive availability of sophisticated video editing software and tools, it has become easy to forge the video using different tampering techniques. A well known video tampering technique is to duplicate the frames or manipulate the contents of the frames to remove and hide the objects or person in a video. Video forensic is necessary because people tampered the video to get justice from court of law on the basis of video evidence, disgrace the important celebrity and to hide or expose some unwanted object. In this paper, we propose a passive forensic method to expose dynamic object removal and frames duplication by detecting the noise variance between original and tampered video frames. The proposed method exploits sensor noise features, extracted from each frame of the video using Discrete Wavelet Transform (DWT) and nonlinear thresholding such as Hard and Soft with Stein's Unbiased Risk Estimator (SURE) shrinkage. Gaussian Mixture Density (GMD) is used as Bayesian classifier and Expectation Maximization (EM) algorithm set the parameters of the GMD. Implementation results demonstrate that we are getting commendable processing speed, accuracy 97.36 96.26% recall 99.80 98.94% and precision 97.34 87.95% respectively for object removal and frame duplication detection in comparison to existing methods. Proposed method successfully detect and localize forgery in the given video.
New Algorithms for Non Negative Matrix Factorization in Applications to Blind Source Separation
Venue: 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings
Year: 2006

In this paper we develop several algorithms for non negative matrix factorization (NMF) in applications to blind (or semi blind) source separation (BSS) when sources are generally statistically dependent under conditions that additional constraints are imposed such as nonnegativity, sparsity, smoothness, lower complexity or better predictability. We express the non negativity constraints using a wide class of loss (cost) functions, which leads to an extended class of multiplicative algorithms with regularization. The proposed relaxed forms of the NMF algorithms have a higher convergence speed with the desired constraints. Moreover, the effects of various regularization and constraints are clearly shown. The scope of the results is vast since the discussed loss functions include quite a large number of useful cost functions such as weighted Euclidean distance, relative entropy, Kullback Leibler divergence, and generalized Hellinger, Pearson's, Neyman's distances, etc
Cortical neuronal activity determines the dynamics of local sleep homeostasis
Year: 2019

The homeostatic regulation of sleep manifests as a relative constancy of its total daily amount, and the compensation of sleep loss by an increase in its subsequent duration and intensity. Theoretical descriptions of this phenomenon define "Process S" a variable with dynamics dependent only on sleep wake history and whose levels are reflected in EEG slow wave activity. While numerous hypotheses have been advanced regarding the substrate and role of Process S, such as synaptic or energy homeostasis, it remains unclear whether these dynamics are fundamentally driven by a need to homeostatically regulate specific variables, or by an unknown innate process which enforces that a certain daily sleep quota is obtained. Sleep is typically defined based on brain derived criteria, such as behaviour or EEG power spectra, and variation in brain activity during wakefulness has been linked to variation in Process S accumulation. We therefore hypothesised that Process S dynamics might be related to the quantity and characteristics of spiking activity in cortical neurones. Specifically, we assumed that Process S changes as a function of the deviation of neuronal firing rate from a locally defined set point. To relate these dynamics explicitly to patterns of spiking activity, we incorporated the occurrence of network spiking off periods as both the defining measure of Process S and as the determinant of its rate of decay. This approach was able to describe the time course of Process S, crucially without explicit knowledge of the animal's global sleep wake state. This work provides a conceptual advance in our understanding of the substrate of sleep homeostasis and provides important links between local and global aspects of sleep regulation.
Knowledge Reasoning with Semantic Data for Real Time Data Processing in Smart Factory
Venue: Sensors
Year: 2018

The application of high bandwidth networks and cloud computing in manufacturing systems will be followed by mass data. Industrial data analysis plays important roles in condition monitoring, performance optimization, flexibility, and transparency of the manufacturing system. However, the currently existing architectures are mainly for offline data analysis, not suitable for real time data processing. In this paper, we first define the smart factory as a cloud assisted and self organized manufacturing system in which physical entities such as machines, conveyors, and products organize production through intelligent negotiation and the cloud supervises this self organized process for fault detection and troubleshooting based on data analysis. Then, we propose a scheme to integrate knowledge reasoning and semantic data where the reasoning engine processes the ontology model with real time semantic data coming from the production process. Based on these ideas, we build a benchmarking system for smart candy packing application that supports direct consumer customization and flexible hybrid production, and the data are collected and processed in real time for fault diagnosis and statistical analysis.
Design of Passive Acoustic Wave Shaping Devices and Their Experimental Validation
Year: 2017

We discuss a topology optimization based approach for designing passive acoustic wave shaping devices and demonstrate its application to; directional sound emission  sound focusing and wave splitting. Optimized devices, numerical and experimental results are presented and benchmarked against other designs proposed in the literature. We focus on design problems where the size of the device is on the order of the wavelength, a problematic region for traditional design methods, such as ray tracing. The acoustic optimization problem is formulated in the frequency domain and modeled by the Helmholtz equation. An exterior 2D model domain is used and an array of point sources is considered as sound emitters. The optimization goal is to identify a distribution of solid material in a design sub domain which produces a desired spatial sound field pattern across a frequency band of interest in a target sub domain. The objective is the integral of the deviation in pressure magnitude, between a prescribed sound field and the solution to the model problem for a given design realization over the target sub domain. Filtering is used for regularization and to allow for meaningful optimization for geometric robustness  The Globally Convergent Method of Moving Asymptotes is used to perform the optimization   Rasmus E. Christiansen and Boyan S. Lazarov and Jakob S. Jensen and Ole Sigmund, Creating geometrically robust designs for highly sensitive problems using topology optimization Acoustic Cavity Design. Struct Multidisc Optim 52, p. 737 754, 2015.  Svanberg Krister, A class of globally convergent optimization methods based on conservative convex seperable approximations.  2002.  Nils Koppels Alle 404, DK 2800 Kgs. Lyngby, Denmark
HEp Net: a smaller and better deep learning network for HEp 2 cell classification
Venue: Comput. methods Biomech. Biomed. Eng. Imaging Vis.
Year: 2019

Indirect immunofluorescence of Human Epithelial 2 (HEp 2) cells is a commonly used method for the diagnosis of autoimmune diseases. Traditional approach relies on specialists to observe HEp 2 slides via the fluorescence microscope, which suffers from a number of shortcomings like being subjective and labour intensive. In this paper, we proposed a deep learning network, namely HEp Net, to automatically classify HEp 2 cell images. The proposed HEp Net uses multi scale convolutional component to extract features from Hep 2 cell images and fuses the features extracted by shallow and deep layers for performance improvement. The proposed model is evaluated on publicly available I3A (Indirect Immunofluorescence Image Analysis) and MIVIA data sets. Experimental result demonstrates that, compared to the state of the art approaches, our proposed HEp Net yields better performance with smaller network size.
Complementary Therapies for Symptom Management in Cancer Patients
Venue: Indian journal of palliative care
Year: 2017

Cancer patients are often poly symptomatic which distressingly affects their quality of lives (QOLs) Alhough, conventional management provides adequate symptom control, yet is coupled with some limitations. Complementary therapies (CTs) have shown beneficial effects in cancer patients for symptomatic relief. The aim of this article is to provide evidence based review of commonly used CTs for symptom management in cancer care. Hypnosis has promising evidence to be used for managing symptoms such as pain, chemotherapy induced nausea/vomiting, distress, fatigue, and hot flashes. Guided imagery increases comfort and can be used as a psycho supportive therapy. Meditation substantially improves psychological function, mental health, and QOL. Cognitive behavioral therapies effectively reduce pain, distress, fatigue, anxiety, and depression; and improve subjective sleep outcomes along with mood and QOL. Yoga has short term beneficial effects for anxiety, depression, fatigue, perceived stress, QOL, and well being. T'ai Chi and qigong are beneficial adjunctive therapies for supportive cancer care, but their role in reducing cancer pain is not well proven. Acupuncture is effective for reducing treatment related side effects, pain and fatigue. Other therapies such as massage techniques, energy therapies, and spiritual interventions have also demonstrated positive role in managing cancer related symptoms and improve overall well being. However, the clinical effectiveness of these therapies for symptom management in cancer patients cannot be concluded due to poor strength of evidence. Nonetheless, these are relatively free from risks and hence can be given along with conventional treatments. Only by tailoring these therapies as per patient's beliefs and preferences, optimal patient centered holistic care can be provided.
AHP, Gray Correlation, and TOPSIS Combined Approach to Green Performance Evaluation of Design Alternatives
Venue: IEEE Transactions on Systems, Man, and Cybernetics: Systems
Year: 2018

The green design of electromechanical products is a pivotal link to manufacturing industry. The question on how to design green products must be answered by excellent designers using both advanced design methods and effective assessment techniques of design alternatives. Making an objective and precise assessment of green designs is of increasing importance to ensure sustainable development. This work proposes a framework based on the combination of analytical hierarchy process (AHP) gray correlation (GC) and technique for order performance by similarity to ideal solution (TOPSIS) to evaluate the performance of design alternatives. AHP is used to determine the weights of performance indices and a nonlinear programming model with constraints is proposed to obtain the integrated closeness index based on the similarity closeness index from GC and distance closeness index from TOPSIS. A case study, i.e. three kinds of refrigerators, is illustrated to verify the proposed method. By comparing with existing methods, i.e. AHP TOPSIS and AHP GC, the effectiveness of the proposed method has been confirmed. In addition, sensitivity analysis is also provided in order to assess the robustness of the proposed method. Also, the following implication can be obtained from our results: 1) chloro fluoro carbons (mg/ \text{m}{3} (C1) production noise (dB) (C6) and environmental cost (C16) have a large impact on refrigerator's green design since these factors carry relatively larger weights. Results of the sensitivity analysis from different cases demonstrate that the best alternative may change when different weights are assigned to the evaluation criteria. This finding means the importance of establishing a qualified group of experts/designers in design evaluation and 2) the selection of design alternatives to produce a green product is critical to product development. The main contribution of this paper is the definition and development of an effective evaluation framework to guide managers to assess product design alternatives. The results show that it overcomes the one sidedness of AHP TOPSIS and AHP GC, and makes the evaluation results more objective and realistic. It provides an accurate, effective, and systematic decision support tool for green performance evaluation of product design alternatives.