nils-herrmann/clean_scirepeval huggingface dataset:
Effect of cutting and storage temperature on sucrose and organic acids metabolism in postharvest melon fruit
Year: 2020

In order to reveal the molecular information of soluble sugars and organic acids both in stored fresh cut and whole melon fruits, the enzymes and genes involved in the metabolism of sucrose and organic acids in melon fruit (cv. Xizhoumi 17) were investigated. Cutting of fruit and storage temperature significantly affected the content of sugars, citric acid (CA) and malic acid (MA) and the change was controlled by enzymes involved in the metabolism of sucrose and organic acids. Fresh cut melon had higher content of hexose (fructose and glucose) and organic acids when stored at 15 degC for a short period of time, and this was correlated with higher activities of acid invertase (AI) neutral invertase (NI) sucrose synthase cleavage (SS c) phosphoenolpyruvate carboxylase (PEPC) citrate synthase (CS) aconitase (ACO) malate dehydrogenase (MDH) and malic enzyme (ME) and lower activity of isocitrate dehydrogenase (IDH) These patterns were due to the up regulation of CmAI1/2, CmNI3, CmPEPC3, CmCS1, CmACO1/2, CmMDH1/3 and CmME3/4 and down regulation of CmIDH1 in fresh cut melon. Compared with fresh cut melon stored at 15 degC, lower temperature (5 degC) significantly extended the shelf life and reduced the quality loss as indicated by higher content of sucrose, CA and MA in fresh cut fruit stored at 5 degC. These differences resulted from the up regulation of CmPEPC2/3 and down regulation of CmAI1/2, CmNI3, CmCS1, CmACO1/2 and CmME3/4 during the storage period.
Depressive symptoms in the context of Chinese grandparents caring for grandchildren.
Venue: Aging mental health
Year: 2021

This study examined the longitudinal association of depressive symptoms with grandchild care intensity and whether the association varies by household structure, residential area, and gender for Chinese grandparents.  Using data from three waves of the China Health and Retirement Longitudinal Study (CHARLS, 2011 2015) we applied multilevel mixed effects models to examine changes in depressive symptoms and the associations with caregiving intensity and to test the moderation effects of residence, living arrangement, and gender.  After controlling for sociodemographic and health covariates, we found that providing a medium level of grandchild care was associated with fewer baseline depressive symptoms compared with non caregivers. Providing low level care among those living with spouse/partner and among those living with child(ren)/others was associated with fewer depressive symptoms relative to non caregivers with similar living arrangements.  Findings indicate that a medium level of involvement in childcare was associated with better mental wellness and low levels of caregiving may benefit nonresidential caregivers. More prospective longitudinal studies are needed to improve the operationalization of grandparent caregiving, validate the associated health outcomes, and apply a contextual approach to examine socioeconomic, cultural, and policy related contexts of caregiving in the changing world of China.
ML Based Social Media Data Emotion Analyzer and Sentiment Classifier with Enriched Preprocessor
Year: 2021

Sentiment Analysis or opinion mining is NLP's method to computationally identify and categorize user opinions expressed in textual data. Mainly it is used to determine the user's opinions, emotions, appraisals, or judgments towards a specific event, topic, product, etc. is positive, negative, or neutral. In this approach, a huge amount of digital data generated online from blogs and social media websites is gathered and analyzed to discover the insights and help make business decisions. Social media is web based applications that are designed and developed to allow people to share digital content in real time quickly and efficiently. Many people define social media as apps on their Smartphone or tablet, but the truth is, this communication tool started with computers. It became an essential and inseparable part of human life. Most business uses social media to market products, promote brands, and connect to current customers and foster new business. Online social media data is pervasive. It allows people to post their opinions and sentiments about products, events, and other people in the form of short text messages. For example, Twitter is an online social networking service where users post and interact with short messages, called "tweets." Hence, currently, social media has become a prospective source for businesses to discover people's sentiments and opinions about a particular event or product. This paper focuses on the development of a Multinomial Naive Bayes Based social media data emotion analyzer and sentiment classifier. This paper also explains various enriched methods used in pre processing techniques. This paper also focuses on various Machine Learning Techniques and steps to use the text classifier and different types of language models.
Non invasive measurements based model predictive control of pulsatile flow in an implantable rotary blood pump for heart failure patients
Venue: 2011 19th Mediterranean Conference on Control Automation (MED)
Year: 2011

In this paper, firstly, we propose a linear time variant (LTV) model to estimate the mean pulsatile flow (Qp) in an implantable rotary blood pump (RBP) Non invasive measurement of mean pulse width modulation (PWM) signal acquired from the pump controller was used as an input to estimate the mean pulsatility index of pump rotational speed (PIo) with this subsequently used to estimate the mean Qp. Secondly, the proposed LTV model was used to develop a controller to regulate and track the variations in the mean Qp and PIo. We used a model predictive control (MPC) approach to develop the controller where this allowed us to explicitly apply pre defined practical constraints to control input PWM as well as the output and the states of the system including; Qp and PIo. The model and the controller were tested using a parameter optimized model of the cardiovascular system rotary blood pump under wide ranges of speed ramp experiments carried out under different operating conditions such as variations in afterload, preload and heart contractility.
Fault Diagnosis for Wind Turbine Systems
Year: 2018

This chapter presents a tutorial treatment on the basis principles of model based and data driven fault detection and isolation strategies with application to dynamic processes. The FDI problem has been formalized in a uniform framework by presenting a mathematical description and definition. Within this framework, the residual generation has been identified as a central issue in both model based and data driven FDI. By choosing the proper design approach, the FDI task can be performed. The residual generator is summarized in different residual generation structures. The ways of designing residuals for fault isolation are also discussed. The most commonly used residual generation strategies are recalled by presenting related problems and discussing the applicability of model based and data driven FDI methods to dynamic processes such as wind turbine systems. The success of fault diagnosis depends on the quality of the residuals. Successful diagnosis requires residual signals, which should be robust with respect to modeling uncertainty. The robust FDI problem is also discussed in this chapter, and the implementation of robust residual generators will be shown in the following chapters of the book.
Maria Antonia Canals y la Didactica de las Matematicas
Year: 2018

El articulo presenta parte de una investigacion de doctorado sobre la historia de vida de Maria Antonia Canals, matematica, maestra, formadora de maestras/os e investigadora en la ensenanza de las matematicas en Educacion Infantil y Primaria. Se estudia su proceso de formacion en Didactica de las Matematicas y su posicion en este campo cientifico. La Didactica de las Matematicas se consolida en el ambito universitario, especialmente dedicado a la carrera academica del profesorado, mientras que los movimientos de renovacion pedagogica se dedican a la mejora de la ensenanza escolar. El caso de M. A. Canals sirve para analizar el papel de la Didactica de las Matematicas y sus limitaciones actuales.
Distance based Protein Folding Powered by Deep Learning
Venue: RECOMB
Year: 2019

Contact assisted protein folding has made very good progress, but two challenges remain. One is accurate contact prediction for proteins lack of many sequence homologs and the other is that time consuming folding simulation is often needed to predict good 3D models from predicted contacts. We show that protein distance matrix can be predicted well by deep learning and then directly used to construct 3D models without folding simulation at all. Using distance geometry to construct 3D models from our predicted distance matrices, we successfully folded 21 of the 37 CASP12 hard targets with a median family size of 58 effective sequence homologs within 4 hours on a Linux computer of 20 CPUs. In contrast, contacts predicted by direct coupling analysis (DCA) cannot fold any of them in the absence of folding simulation and the best CASP12 group folded 11 of them by integrating predicted contacts into complex, fragment based folding simulation. The rigorous experimental validation on 15 CASP13 targets show that among the 3 hardest targets of new fold our distance based folding servers successfully folded 2 large ones with <150 sequence homologs while the other servers failed on all three, and that our ab initio folding server also predicted the best, high quality 3D model for a large homology modeling target. Further experimental validation in CAMEO shows that our ab initio folding server predicted correct fold for a membrane protein of new fold with 200 residues and 229 sequence homologs while all the other servers failed. These results imply that deep learning offers an efficient and accurate solution for ab initio folding on a personal computer.
Near optimal search and rescue path planning for a moving target
Venue: J. Oper. Res. Soc.
Year: 2021

Discrete search and rescue path planning for a moving target problem is computationally hard. Despite heuristic methods proposed so far, for which efficiency is further plagued by random episodic target kinematic behavior, qualifying real solution goodness and specifying optimality gap still remain elusive. In this paper a new alternate formulation is proposed to solve the search path planning problem for a moving target. Rather than tackling explicitly the original problem model, a remarkable property is exploited to solve a conjugate mixed integer linear programming problem. The approach lies on a compact open loop search path planning problem model with anticipated feedback to efficiently minimize probability of detection failure as opposed to traditionally maximize cumulative probability of success. Preserving path solution optimality, solving the conjugate problem proves very valuable in significantly reducing computational complexity. This is mainly achievable by virtue of the resulting problem objective property which concisely defines the function to be minimized in terms of terminal belief contributions only. For the first time optimal or upper bound solution computation are made possible in reasonable time for practical size problems. A network representation is further utilized to simplify modeling and facilitate constraint specification. Computational results show the strength of the approach for one and two searching agent problem instances.
From Polar to Reed Muller Codes: A Technique to Improve the Finite Length Performance
Venue: IEEE Transactions on Communications
Year: 2014

We explore the relationship between polar and RM codes and we describe a coding scheme which improves upon the performance of the standard polar code at practical block lengths. Our starting point is the experimental observation that RM codes have a smaller error probability than polar codes under MAP decoding. This motivates us to introduce a family of codes that "interpolates" between RM and polar codes, call this family Cinter {Ca a [0, 1j} where Ca|a=1 is the original polar code, and Ca|a=0 is an RM code. Based on numerical observations, we remark that the error probability under MAP decoding is an increasing function of a. MAP decoding has in general exponential complexity, but empirically the performance of polar codes at finite block lengths is boosted by moving along the family Cinter even under low complexity decoding schemes such as, for instance, belief propagation or successive cancellation list decoder. We demonstrate the performance gain via numerical simulations for transmission over the erasure channel as well as the Gaussian channel.
A Smooth Double Proximal Primal Dual Algorithm for a Class of Distributed Nonsmooth Optimization Problems
Venue: IEEE Transactions on Automatic Control
Year: 2020

This technical note studies a class of distributed nonsmooth convex consensus optimization problems. The cost function is a summation of local cost functions which are convex but nonsmooth. Each of the local cost functions consists of a twice differentiable (smooth) convex function and two lower semi continuous (nonsmooth) convex functions. We call these problems as single smooth plus double nonsmooth (SSDN) problems. Under mild conditions, we propose a distributed double proximal primal dual optimization algorithm. Double proximal splitting is designed to deal with the difficulty caused by the unproximable property of the summation of those two nonsmooth functions. Besides, it can also guarantee that the proposed algorithm is locally Lipschitz continuous. An auxiliary variable in the double proximal splitting is introduced to estimate the subgradient of the second nonsmooth function. Theoretically, we conduct the convergence analysis by employing Lyapunov stability theory. It shows that the proposed algorithm can make the states achieve consensus at the optimal point. In the end, nontrivial simulations are presented and the results demonstrate the effectiveness of the proposed algorithm.
Interpolasi Cubic Spline untuk Memetakan Distribusi Panas pada Permukaan Panel Sel Surya
Year: 2020

ABSTRAK Penelitian ini bertujuan untuk mengetahui sebaran atau distribusi panas yang terjadi pada permukaan panel surya atau photo voltaic (PV) dengan dengan data sebaran sensor yang diolah dengan metode interpolasi cubic spline, sehingga dapat digunakan untuk mengetahui posisi panel surya yang efektif dan ideal menerima cahaya matahari. Selain informasi panas pada panel surya juga informasi mengenai daya yang dikeluarkan oleh panel surya tersebut. Pemetaan distribusi panas pada panel PV menggunakan metode interpolasi cubic spline yang selanjutnya divisualisasikan dalam heatmap 2D. Berdasarkan heatmap hasil interpolasi dan hasil eksperimen menunjukkan panel PV pada posisi vertikal dengan kemiringin 0o pukul 12.00 14.00 menghasilkan arus tertinggi yaitu 449.2mA dengan tegangan yang dihasilkan sebesar 1.03V sehingga menghasilkan daya sebesar 0.46W. Hal ini lebih optimal dari suhu permukaan PV yang lebih panas pada pada posisi vertikal dengan kemiringin 45 o ataupun posisi horizontal 0 o dan 45 o pada jam yang sama. Kata kunci: panel surya, heatmap, cubic spline, interpolasi  This research aims to determine the distribution of heat that is exposed on the surface of solar panels or photo voltaic (PV) where the data from distributed sensor is processed by means of cubic spline interpolation method, so that it can be used to determine the ideal and effective position of solar panel to receive sunlight radiation. In addition to heat information on the solar panel, information about the power generated by PV is also measured. Based on the heatmap generated from the interpolation method and the experimental results, it shows that the PV panel in a vertical position with 0o inclination at 12.00 14.00 produces the highest current which is 449.2mA with the output voltage of 1.03V, thus the generated power is about 0.46W. This is more optimal than the surface temperature of the PV which is hotter in the vertical position with a 4 5 o or horizontal position with 0 o and 45 o at the same time.  solar panel, heatmap, cubic spline, interpolation
Turning rice meiosis into mitosis
Venue: Cell Research
Year: 2016

Introduction of clonal reproduction through seeds (apomixis) in crops has the potential to revolutionize agriculture by allowing self propagation of any elite variety, in particular F1 hybrids. In the sexual model plant Arabidopsis thaliana synthetic clonal reproduction through seeds can be artificially implemented by (i) combining three mutations to turn meiosis into mitosis (MiMe) and (ii) crossing the obtained clonal gametes with a line expressing modified CENH3 and whose genome is eliminated in the zygote. Here we show that additional combinations of mutations can turn Arabidopsis meiosis into mitosis and that a combination of three mutations in rice (Oryza sativa) efficiently turns meiosis into mitosis, leading to the production of male and female clonal diploid gametes in this major crop. Successful implementation of the MiMe technology in the phylogenetically distant eudicot Arabidopsis and monocot rice opens doors for its application to any flowering plant and paves the way for introducing apomixis in crop species.
Natural Language Metaphors Covertly Influence Reasoning
Venue: PloS one
Year: 2013

Metaphors pervade discussions of social issues like climate change, the economy, and crime. We ask how natural language metaphors shape the way people reason about such social issues. In previous work, we showed that describing crime metaphorically as a beast or a virus, led people to generate different solutions to a city's crime problem. In the current series of studies, instead of asking people to generate a solution on their own, we provided them with a selection of possible solutions and asked them to choose the best ones. We found that metaphors influenced people's reasoning even when they had a set of options available to compare and select among. These findings suggest that metaphors can influence not just what solution comes to mind first, but also which solution people think is best, even when given the opportunity to explicitly compare alternatives. Further, we tested whether participants were aware of the metaphor. We found that very few participants thought the metaphor played an important part in their decision. Further, participants who had no explicit memory of the metaphor were just as much affected by the metaphor as participants who were able to remember the metaphorical frame. These findings suggest that metaphors can act covertly in reasoning. Finally, we examined the role of political affiliation on reasoning about crime. The results confirm our previous findings that Republicans are more likely to generate enforcement and punishment solutions for dealing with crime, and are less swayed by metaphor than are Democrats or Independents.
Apreciacion artistica y devocion a cinco imagenes crucificadas del norte de Mexico
Year: 2017

El proceso de evangelizacion, y posterior inculturacion  en Mexico, trajo consigo no solo la suplantacion iconica devocional como trivialmente se ha querido explicar, sino un proceso complejamente entretejido, mezclado de fe, religiosidad, devocion, arte y cultura, en general. Asi, las imagenes en particular jugaron un rol de inculturacion e implementacion de una nueva cosmovision religiosa, porque aparte de ser utilizadas en los procesos de evangelizacion, entre muchas otras formas y figuras, tambien tuvieron un impacto en la sensibilidad artistica del pueblo mexicano; una verdadera aportacion del arte cristiano a las culturas del nuevo mundo, misma que se prolonga hasta nuestros dias en las culturas visuales contemporaneas  Especificamente, las imagenes de Cristo crucificado constituyen una verdadera expresion artistico devocional. El presente trabajo intenta resaltar la mutua correspondencia entre una profunda intuicion artistica y la devocion religiosa hacia cinco imagenes de Cristo crucificado del norte de Mexico. El "Divino Pastor" 1596, en Canatlan, Dgo; el "Senor de Tizonazo o Senor de los guerreros" lo datan aproximadamente en 1603, Inde, Dgo; el "Senor de Santo Entierro" en Santiago Papasquiaro, en 1625 "llego" la imagen al templo; el "Senor de Mapimi" en Cuencame, Dgo. 1715 (todas en el estado de Durango) y el "Santo Cristo de la Capilla" en Saltillo, Coahuila, con 408 anos de haber llegado a la ciudad. Imagenes artisticamente bellas y antiguas, que forman parte del patrimonio cultural del norte de Mexico.  proceso de integracion de una cultura en otra.  Aportes del arte cristiano a las culturas visuales contemporaneas IV Congreso Internacional de Cultura Visual. Roma.
LOFAR observations of X ray cavity systems
Year: 2020

We present LOFAR observations at 120 168 MHz of 42 systems with possible X ray cavities in their hot atmosphere, of which 17 are groups or ellipticals, 19 are nearby clusters (z 0.3) The X ray cavities, formed by the radio lobes of the central active galactic nucleus (AGN) are evidence of radio mode AGN feedback. In the groups and ellipticals sample, half of the systems have X ray cavities for which no associated lobe emission was detected. Conversely, we report the discovery of large radio lobes in NGC 6338, extending far beyond the emission reported previously in the literature. In the case of the nearby clusters, our observations show that there is little low frequency radio emission that extends beyond the cavities (e.g. MS 0735.6+7421, A2052) For the first time, we report secure cavity radio associations in 2A 0335+096, ZwCl 2701, and ZwCl 8276 that strengthens their interpretation as AGN created cavities. However, in some known cavity systems (e.g. A1795 and ZwCl 3146) we report the lack of detectable low frequency radio emission associated with the cavities. Our sample of higher redshifts systems is small, and unfortunately the present LOFAR observations are not able to resolve the lobes in many of them. Nevertheless, our sample represents one of the best available for investigating the connection between radio and jet power in radio mode AGN feedback.