nils-herrmann/clean_scirepeval huggingface dataset:
Demographically adjusted norms for the WAIS R Block Design and Arithmetic subtests: Results from the Neuropsychological Norms for the US Mexico Border Region in Spanish (NP NUMBRS) project
Venue: The Clinical neuropsychologist
Year: 2020

Adult Intelligence Scale (WAIS) Block Design and Arithmetic subtests are frequently used as measures of visuospatial construction and verbal working memory, respectively. As part of a larger test adaptation and norming effort for this population, we generated and investigated demographically adjusted interpretive norms for WAIS R Block Design and Arithmetic in Spanish speaking adults living in the US Mexico border region.  Participants included 183 community dwelling adults ages 20 55 (education range: 0 20 years; 58% women) from the NeuroPsychological Norms for the US Mexico Border Region in Spanish (NP NUMBRS) Project. They completed the WAIS R Block Design and Arithmetic subtests in Spanish. Demographically adjusted T scores were calculated for these subtests using fractional polynomial equations adjusting for linear and non linear effects of age, education (continuous) and sex. We compared our rates of impairment (i.e. T 40) against rates calculated using published English speaking WAIS R standardization sample norms adjusted for age, education, and sex.  Education was positively associated with performance on Block Design and Arithmetic subtests, and men outperformed women on both subtests. The present Spanish speaker norms for these subtests yielded expected rates of "impairment" (i.e. 15 16% impaired, a 1 SD cutoff) while existing norms for English speakers underestimated impairment (i.e. 5 6% impaired) when applied to our Spanish speaking sample.  Regional normative data will improve interpretation of test performance on Block Design and Arithmetic subtests for Spanish speakers living in the US Mexico border region and may aid in bolstering the overall analysis of neuropsychological profile patterns in this population. Cross validation with Spanish speakers in other regions and/or with other national origins is needed.
Learning slosh dynamics by means of data
Venue: Computational Mechanics
Year: 2019

In this work we study several learning strategies for fluid sloshing problems based on data. In essence, a reduced order model of the dynamics of the free surface motion of the fluid is developed under rigorous thermodynamics settings. This model is extracted from data by exploring several strategies. First, a linear one, based on the employ of Proper Orthogonal Decomposition techniques is analyzed. Second, a strategy based on the employ of Locally Linear Embedding is studied. Finally, Topological Data Analysis is employed to the same end. All the three distinct possibilities rely on a numerical integration scheme to advance the dynamics in time. This thermodynamically consistent integrator is developed on the basis of the General Equation for Non Equilibrium Reversible Irreversible Coupling, GENERIC [M. Grmela and H.C Oettinger (1997)  Rev. E. 56 (6) 6620 6632] framework so as to guarantee the satisfaction of first principles (particularly, the laws of thermodynamics) We show how the resulting method employs a few degrees of freedom, while it allows for a realistic reconstruction of the fluid dynamics of sloshing processes under severe real time constraints. The proposed method is shown to run faster than real time in a standard laptop.
MTD Spamguard: a moving target defense based spammer detection system in social network
Venue: Soft Comput.
Year: 2018

Machine learning classifiers are currently the state of the art for spammer detection tasks in SNSs. Note, however, that these classifiers fail to detect adaptive spammers that dynamically change their spamming strategies or behaviors and attempt to pose as legitimate users. In this paper, we propose an efficient spammer detection system (which we call MTD Spamguard) wherein the notion of MTD is applied to increase the robustness of well known machine learning classifiers against the adaptive spammers in SNSs. The system introduces a new method of MTD wherein the concept of differential immunity of different classifiers is employed to detect the spammers. To classify a single user in the test dataset, we pick one of the appropriate trained classifiers from multiple classifiers and then use its classification output. To choose the appropriate classifier, we design an effective classifier switching strategy by formulating the interaction of users (normal users and spammers) and detector (which hosts the machine learning classifier) as a repeated Bayesian Stackelberg game. The classifier switching strategy provides strong Stackelberg equilibrium between users and detector, maximizing the accuracy of classification and reducing the misclassification of spammers. The system achieves 30% gain in classification accuracy over the Facebook dataset (constructed in our recent work)
Portfolio Optimization Without Optimization
Year: 2021

In this paper we introduce a simple, yet flexible approach to construct (enhanced) index tracking portfolios. PADME (Portfolio Allocation via Density MatchEs) uses the density function of returns as a robust means of capturing investor preferences, and identifies suitable portfolios through a measure of closeness. Recognizing model uncertainty, PADME avoids optimization and instead relies upon the behavioral concept of revealed preferences by offering the investor a palette of options from which to choose. In a case study we consider an EIT manager with an SP500 benchmark. We illustrate PADME's flexibility by imposing several types of Bayesian beliefs simultaneously. Using far fewer assets than the SP500, we are able to generate numerous portfolios whose out of sample risk and return were superior to the benchmark during the turbulent COVID Crisis of 2020.
Decoding movement direction from cortical microelectrode recordings using an LSTM based neural network
Venue: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine Biology Society (EMBC)
Year: 2020

Brain machine interfaces (BMIs) allow individuals to communicate with computers using neural signals, and Kalman Filter (KF) are prevailingly used to decode movement directions from these neural signals. In this paper, we implemented a multi layer long short term memory (LSTM)based artificial neural network (ANN) for decoding BMI neural signals. We collected motor cortical neural signals from a nonhuman primate (NHP) implanted with microelectrode array (MEA) while performing a directional joystick task. Next, we compared the LSTM model in decoding the joystick trajectories from the neural signals against the prevailing KF model. The results showed that the LSTM model yielded significantly improved decoding accuracy measured by mean correlation coefficient (0.84, p 10 7) than the KF model (0.72) In addition, using a principal component analysis (PCA) based dimensionality reduction technique yielded slightly deteriorated accuracies for both the LSTM (0.80) and KF (0.70) models, but greatly reduced the computational complexity. The results showed that the LSTM decoding model holds promise to improve decoding in BMIs for paralyzed humans.
Exploring the Relationship Between ICT Use, Mental Health Symptoms and Well Being of the Historically Disadvantaged Open Distance Learning Student: A Case Study
Venue: Turkish Online Journal of Distance Education
Year: 2019

Whereas there exists a complex pattern of interrelated factors that act as determinants of the successful implementation of ODL in developing countries, most point at differences in access, use of, or impact of ICT. In addressing an area of research that has not received any attention, this study reports on an investigation into the relationship between ICT use patterns, selected mental health symptoms and the emotional, social and psychological well being of the historically disadvantaged ODL student in the South African context of disparities. Data collected from 315 students in online survey revealed medium ICT use, higher computer use by working students compared to full time students, a low prevalence of computer overuse symptoms, medium loss of sleep and a preference for individualized and non collaborative activities that require minimalistic use of ICT. Differences between the ICT use scores of students who reported symptoms of stress and sleep disturbances and those who did not report symptoms were not significant, while the majority of students were diagnosed as moderately mentally healthy or flourishing. A significant relationship was found between working students' ICT use scores and reduced performance, as well as between their ICT use scores and their social, emotional and psychological well being scores. The strengths of the well being relationships, however, ranged from weak to very weak. No significant relationships were reported for full time students, nor for both groups between their ICT use scores and total mental health scores. The study concluded that in the context studied, ICT use patterns hold no risk factors for the mental health and well being of the historically disadvantaged ODL student.
Phenotype, donor age and gender affect function of human bone marrow derived mesenchymal stromal cells
Venue: BMC Medicine
Year: 2013

BackgroundMesenchymal stromal cells (MSCs) are attractive for cell based therapies ranging from regenerative medicine and tissue engineering to immunomodulation. However, clinical efficacy is variable and it is unclear how the phenotypes defining bone marrow (BM) derived MSCs as well as donor characteristics affect their functional properties.MethodsBM MSCs were isolated from 53 (25 female, 28 male; age: 13 to 80 years) donors and analyzed by: (1) phenotype using flow cytometry and cell size measurement; (2) in vitro growth kinetics using population doubling time; (3) colony formation capacity and telomerase activity; and (4) function by in vitro differentiation capacity, suppression of T cell proliferation, cytokines and trophic factors secretion, and hormone and growth factor receptor expression. Additionally, expression of Oct4, Nanog, Prdm14 and SOX2 mRNA was compared to pluripotent stem cells.ResultsBM MSCs from younger donors showed increased expression of MCAM, VCAM 1, ALCAM, PDGFRb, PDL 1, Thy1 and CD71, and led to lower IL 6 production when co cultured with activated T cells. Female BM MSCs showed increased expression of IFN gR1 and IL 6b, and were more potent in T cell proliferation suppression. High clonogenic BM MSCs were smaller, divided more rapidly and were more frequent in BM MSC preparations from younger female donors. CD10, b1integrin, HCAM, CD71, VCAM 1, IFN gR1, MCAM, ALCAM, LNGFR and HLA ABC were correlated to BM MSC preparations with high clonogenic potential and expression of IFN gR1, MCAM and HLA ABC was associated with rapid growth of BM MSCs. The mesodermal differentiation capacity of BM MSCs was unaffected by donor age or gender but was affected by phenotype (CD10, IFN gR1, GD2) BM MSCs from female and male donors expressed androgen receptor and FGFR3, and secreted VEGF A, HGF, LIF, Angiopoietin 1, basic fibroblast growth factor (bFGF) and NGFB. HGF secretion correlated negatively to the expression of CD71, CD140b and Galectin 1. The expression of Oct4, Nanog and Prdm14 mRNA in BM MSCs was much lower compared to pluripotent stem cells and was not related to donor age or gender. Prdm14 mRNA expression correlated positively to the clonogenic potential of BM MSCs.ConclusionsBy identifying donor related effects and assigning phenotypes of BM MSC preparations to functional properties, we provide useful tools for assay development and production for clinical applications of BM MSC preparations.
Out of Africa: origins and evolution of the human malaria parasites Plasmodium falciparum and Plasmodium vivax.
Venue: International journal for parasitology
Year: 2017

Plasmodium falciparum and Plasmodium vivax account for more than 95% of all human malaria infections, and thus pose a serious public health challenge. To control and potentially eliminate these pathogens, it is important to understand their origins and evolutionary history. Until recently, it was widely believed that P. falciparum had co evolved with humans (and our ancestors) over millions of years, whilst P. vivax was assumed to have emerged in southeastern Asia following the cross species transmission of a parasite from a macaque. However, the discovery of a multitude of Plasmodium spp. in chimpanzees and gorillas has refuted these theories and instead revealed that both P. falciparum and P. vivax evolved from parasites infecting wild living African apes. It is now clear that P. falciparum resulted from a recent cross species transmission of a parasite from a gorilla, whilst P. vivax emerged from an ancestral stock of parasites that infected chimpanzees, gorillas and humans in Africa, until the spread of the protective Duffy negative mutation eliminated P. vivax from human populations there. Although many questions remain concerning the biology and zoonotic potential of the P. falciparum and P. vivax like parasites infecting apes, comparative genomics, coupled with functional parasite and vector studies, are likely to yield new insights into ape Plasmodium transmission and pathogenesis that are relevant to the treatment and prevention of human malaria.
The impact of being bullied at school on psychological distress and work engagement in a community sample of adult workers in Japan
Venue: PloS one
Year: 2018

The aim of this study was to investigate the long term impact of being bullied at school on current psychological distress and work engagement in adulthood among Japanese workers. We hypothesized that workers who had been bullied at school could have higher psychological distress and lower work engagement compared to those who had not been bullied.  We used data from the Japanese Study on Stratification, Health, Income, and Neighborhood (J SHINE) project, conducted from July 2010 to February 2011 in Japan. This survey randomly selected the local residents around a metropolitan area in Japan. Of 13,920 adults originally selected, 4,317 people participated this survey, and the total response rate was 31% The self administered questionnaires assessed current psychological distress (K6) work engagement (UWES) the experiences of being bullied in elementary or junior high school and other covariates. Statistical analyses were conducted only for workers. Hierarchical multiple regression analyses were conducted to determine associations between experiences of being bullied at school and psychological distress/work engagement, with six steps.  Statistical analysis was conducted for 3,111 workers. The number of respondents who reported being bullied in elementary or junior high school was 1,318 (42% We found that the experience of being bullied at school was significantly associated with high psychological distress in adulthood (b .079, p .0001) however, the work engagement scores of respondents who were bullied were significantly higher than for people who were not bullied at school (b .068, p .0001) after adjusting all covariates.  Being bullied at school was positively associated with both psychological distress and work engagement in a sample of workers. Being bullied at school may be a predisposing factor for psychological distress, as previously reported. The higher levels of work engagement among people who experienced being bullied at school may be because some of them might have overcome the experience to gain more psychological resilience.
Dummy molecularly imprinted polymer based microplate chemiluminescence sensor for one step detection of Sudan dyes in egg.
Venue: Food chemistry
Year: 2019

The objective of this study is to report a molecularly imprinted polymer based chemiluminescence method for determination of Sudan dyes. A dummy template molecularly imprinted polymer capable of recognizing seven Sudan dyes was first synthesized and its recognition mechanism was studied by using computation simulation method. The polymer was coated in the wells of conventional microplate to prepare a chemiluminescence sensor and the assay process consisted of only one sample loading step prior to signal acquisition. The optimized sensor was used to determine the seven dyes in egg yolk and the results were confirmed with a high performance liquid chromatography. Results showed that this sensor achieved ultrahigh sensitivity (1.0 5.0 pg/mL) rapid assay process (10 min) and satisfactory recovery (70.5% 92.2% Furthermore, the sensor could be reused for 5 times. Therefore, this sensor could be used as a useful tool for screening the residues of Sudan dyes in egg.
Survey on Ultra Dense Networks for Next Generation Cellular Systems EE 359 Wireless Communications
Year: 2017

Over the past decades, there has been a continuous growing demand for faster, safer, and more intelligent wireless networks. Requirements for next generation cellular networks include higher data rates and scalability, lower latency and energy consumption, and improved connectivity, reliability, and security. Many key enabling technologies have been proposed as solutions to meet these requirements, such as ultra densification, wireless software defined networking, massive MIMO, and millimeter wave technology  This survey will be focused on proposed changes in cellular architecture, specifically Ultra Dense Networks (UDNs) that aim at solving the challenges of future cellular networks.
SIYASAL LIDERLIKTE KARIZMA OLGUSU: RECEP TAYYIP ERDOGAN ORNEGINDE TEORIK VE UYGULAMALI BIR CALISMA
Year: 2006

Insanlar topluluk halinde yasamalarindan oturu her daim lidere ihtiyac duymuslar, lider olarak sectikleri kisilere de mesru olculerde toplumsal duzenin saglanmasinoktasinda bir otorite ve bu otoriteyi kullanma yetkisi vermislerdir. Kullanilan farkliotorite turleri liderleri birbirlerinden farklilastirmis, farklilider cesitlerini ortaya cikarmistir. Bu dogrultuda calismada, bu otorite ve lider cesitlerinden biri olan karizma konusu siyasal liderlik baglaminda Recep Tayyip Erdogan orneginde ele alinmistir. Liderlik, siyasal liderlik, otorite ve karizma kavramlarina kisaca deginildikten sonra, Erdogan'in nasil bir siyasal lider oldugunu ortaya koymak ve onun sahip olduguna inanilan ozelliklerinin deneklerin sosyo demografik ozellikleri dogrultusunda nasil bir degisim gosterdigini saptamak amaciyla bir alan arastirmasigerceklestirilmistir. Sonuc olarak Konya secmeninin Erdogan'idaha cok karizmatik bir lider olarak gordugu, Erdogan'in liderlik ozelliklerine iliskin degerlendirmelerde ise sosyo demografik ozelliklerin etkili oldugu ortaya cikmistir.
International Journal of Scientific Engineering and Research (IJSER)
Year: 2013

Gender classification is an important matter for Human Computer Interaction devices. A new methodology for gender classification is examined in this study where the facial feature is extracted from local region of a face using gray color intensity. The facial area is divided into eighty one equal sized square sub regions and Local Minima Pattern (LMnP) method is applied to each pixel. LMnP histograms extracted from those regions are concatenated into a single vector to represent that particular face. The classification accuracy obtained using Local Minima Pattern (LMnP) along with support vector machine as a classifier has outperformed all traditional feature descriptors for gender classification. It is evaluated on the images collected from popular FERET database
Reverse Docking, Molecular Docking, Absorption, Distribution, and Toxicity Prediction of Artemisinin as an Anti diabetic Candidate
Year: 2020

Aldose reductase is an enzyme that catalyzes one of the steps in the sorbitol (polyol) pathway that is responsible for fructose formation from glucose. In diabetes, aldose reductase activity increases as the glucose concentration increases. The purpose of this research was to identify and develop the use of artemisinin as an anti diabetic candidate through in silico studies, including reverse docking, receptor analysis, molecular docking, drug scan, absorption, and distributions and toxicity prediction of artemisinin. Based on the results, we conclude that artemisinin can be used as an anti diabetic candidate through inhibition of aldose reductase
Scene recognition algorithm based on multi feature and weighted minimum distance classifier for digital hearing aids
Venue: 2016 International Conference on Audio, Language and Image Processing (ICALIP)
Year: 2016

The recognition precision of the existing auditory scene recognition algorithms is relatively satisfactory, but they can only be applied to several noise scenarios, and it can't meet the performance requirements of digital hearing aids in complex environment. In order to solve the above problems, scene recognition algorithm based on multi feature and weighted minimum distance classifier is proposed in this paper. In this algorithm, the speech endpoint detection algorithm based on the band partitioning spectral entropy and spectral energy is used to divide the noisy speech into speech segment and noise segment. Then the characteristics such as Critical Band Ratio and band partitioning spectral entropy as well as adaptive short time zero crossing rate of each segment are extracted for the weighted minimum distance classifier to recognize the noise scenario. The experiments result shows that the proposed algorithm has strong robustness and high accuracy. It's suitable to be applied in digital hearing aids.
The Cambridge Dictionary of Psychology
Year: 2009

The Cambridge Dictionary of Psychology is the fi rst and only dictionary that surveys the broad discipline of psychology from an international, crosscultural, and interdisciplinary focus. This focus was achieved in several ways. The managing and consulting editorial boards comprise worldrenowned scholars in psychology from many different countries, not just the United States. They reviewed and edited all of the keyword entries to make them lively and applicable across cultural contexts, incorporating the latest knowledge in contemporary international psychology. Thus entries related to culture, as well as those from all domains of psychology, are written with the broadest possible audience in mind. Also, many keywords central to contemporary psychology were incorporated that are not included by many competitors, including the Oxford and American Psychological Association dictionaries.
Precision measurement and analysis of CMM for runout
Year: 2015

Around the process and measurement problems of the gear parts with a short stepped as the reference encountered in the actual production,processing programs are described in detail. Use CMM to measure the geometric elements of the process characteristics,analyze two measurement methods and the results are compared,provide effective date support to processing program. The defects of characteristic properties caused the reason of unstable measurement. By normal principles of"dense sampling point"can be positive or negative offset error in the measurement. And because the measuring span is big,making the measurement results are proportional to enlarge relations,need to determine the amplification times of the state of actual parts. Shorter reference hole geometric elements characteristic date collection provides an effective measurement method,and conducts numerous experiments and demonstration,suitable for a variety of precision measuring short reference hole.