nils-herrmann/clean_scirepeval huggingface dataset:
Longitudinal trajectories of sensation seeking, risk taking propensity, and impulsivity across early to middle adolescence.
Venue: Addictive behaviors
Year: 2014

Adolescent substance use and abuse show associations with increases in disinhibitory constructs, including sensation seeking, risk taking propensity, and impulsivity. However, the longitudinal trajectories of these constructs from early to middle adolescence remain largely unknown. Thus, the current study examined these developmental trajectories in 277 adolescents (Mage=11.00 at Wave 1) over five consecutive yearly waves. Controlling for age, Hierarchical Linear Modeling analyses showed that sensation seeking increased linearly, whereas risk taking propensity and impulsivity demonstrated curvilinear changes. Specifically, risk taking propensity increased in the first four waves of assessment but did not evidence changes at the last assessment wave. Impulsivity, on the other hand peaked at wave four before subsequently declining. A comparison between females and males and Black and White adolescents suggested that these groups' trajectories were similar. Black adolescents' sensation seeking trajectory differed from adolescents who belonged to the "Other" racial group (i.e. adolescents who neither self identified as Black or White) Generally, the study findings replicate and extend earlier work indicating that these risk factors increase across early adolescence and begin to level off during middle adolescence. The importance of understanding the natural course of these core constructs is of great importance for directing future relevant prevention and intervention work.
Novel Equalization Techniques for Space Division Multiplexing Based on Stokes Space Update Rule
Year: 2017

Space division multiplexing (SDM) is a promising technology that aims to overcome the capacity crunch of optical communications. In this paper, we introduce the multiple input multiple output (MIMO) Stokes Space Algorithm (SSA) implemented in frequency domain, a novel equalization technique for space division multiplexing (SDM) Although different papers have been published about the SSA and its MIMO implementation, we provide for the first time an analysis of the of the convergence speed and frequency offset of the SSA compared to the least mean square (LMS) SSA algorithm can deal with higher frequency offsets and linewidths than LMS, being suitable for optical communications with higher phase noise. SSA does not need pre compensation of frequency offset, which can be compensated after equalization without penalties. On the other hand, due to reduced convergence speed, SSA requires longer training sequences than LMS.
2011 ESC/EAS Guidelines for the Management of Dyslipidaemias
Year: 2012

2011 ESC/EAS guidelines for the management of dyslipidaemias has been released.The 2011 guidelines include many updates including total cardiovascular risk estimation,treatment target,statins treatment,treatment of hypercholesterolaemia and hypertriglyceridaemia,treatment of high density lipoprotein,and the management of dyslipidaemias in different clinical settings.This article summarizes the updated information.
Neural Style Transfer Replication Project
Year: 2018

There are three major advancements in the area of neural style transfer. In 2015, the paper, A neural algorithm of artistic style [2] proposes an iterative algorithm for neural style transfer. In 2016, the paper, Perceptual losses for real time style transfer and super resolution  proposes a real time neural style transfer algorithm. However, for this algorithm, we have to train a seperate neural network for each style. In 2017, the paper, A learned representation for artistic style  proposes a real time neural style transfer algorithm that can transfer a variety of styles with one neural network.
Depression and loneliness during COVID 19 restrictions in the United States, and their associations with frequency of social and sexual connections
Venue: medRxiv
Year: 2020

To estimate the prevalence of depression and loneliness during the US COVID 19 response, and examine their associations with frequency of social and sexual connections.  We conducted an online cross sectional survey of a nationally representative sample of American adults (n=1010) aged 18 94, running from April 10 20, 2020. We assessed depressive symptoms (CES D 10 scale) loneliness (UCLA 3 Item Loneliness scale) and frequency of in person and remote social connections (4 items, e.g. hugging family member, video chats) and sexual connections (4 items, e.g. partnered sexual activity, dating app use)  One third of participants (32% reported depressive symptoms, and loneliness was high [mean (SD) 4.4 (1.7) Those with depressive symptoms were more likely to be women, age 20 29, unmarried, and low income. Frequent in person connections were associated with lower depression and loneliness; frequent remote connections were not.  Depression and loneliness were elevated during the early US COVID 19 response. Those who maintained frequent in person, but not remote, social and sexual connections had better mental health outcomes. While COVID 19 social restrictions remain necessary, it will be critical to expand mental health services to serve those most at risk and identify effective ways of maintaining social and sexual connections from a distance.
Foundation for transdisciplinary education at Cape Peninsula University of Technology
Year: 2020

South Africa faces a multitude of social, economic and environmental challenges, which require well considered planning efforts. However, the efficacy of the built environment professions to adequately plan for the current and future populations can to some extent be questioned. Factors that are arguably responsible for the failure of the professions to achieve the desired outcomes include the following: (1) the inability of professionals to comprehensively analyse community problems and (2) although the various professions might work on the same issues, they largely fail to transcend disciplinary boundaries. This state of affairs can in part be linked to the role of higher education, which is in a good position to equip future professionals with the skills required for the analysis of diverse societal problems. In spite of the importance of education and training, there is a paucity of literature that explore ways in which the South African higher education sector instils transdisciplinary thinking and, accordingly, imparts the requisite soft skills to students. Using the case study of Cape Peninsula University of Technology in Cape Town, the aim of this article was to present efforts that are pursued towards instilling transdisciplinarity in students. The efforts revolve around community service learning pedagogy, which grants students a platform to work in close collaboration with communities. In the process, students and community members develop an in depth understanding of the community's problems and how they could be collectively resolved.
Human capital challenges in the food and beverage service industry of Canada: Finding innovative solutions
Year: 2017

Challenged by a clear shortfall of available employees to be long term members of the food service industry, this paper aims to establish reasons for the shortage of available employees and curate a number of strategies to improve the situation.  This paper draws on the perspectives of many industry stakeholders. These professionals collaborated to identify a number of contributing factors to the shortage of employees in the Canadian food and beverage industry. Corresponding solutions were assessed, prioritized and categorized by groups responsible for taking action.  There are many strategies that can be implemented in both the short and long term that can increase the draw for potential employees to join this industry.  Industry members, educators and government policymakers can all play a role in improving the worker shortage in the food service industry. The recommendations range from industry collaboration to redefinition of jobs and to redistribution of wages.  The co authors of this paper include the President and CEO of Ontario Restaurant, Hotel and Motel Association and educators with strong industry experiences gained in the positions of food and beverage director, restaurant manager and executive chef. Given the diverse experiences of the author team, this paper creates a more holistic view of the recommendations to consider for this industry to see positive change.
How Organizational Capacity Can Improve Electoral Accountability
Year: 2021

The organizational structure of the bureaucracy is a key determinant of policy outcomes. Bureaucratic agencies exhibit wide variation in their organizational capacity, which allows politicians to strategically shape policy implementation. This paper examines what bureaucratic structure implies for the ability of voters to hold politicians electorally accountable. It explicitly models differences in organizational capacity across bureaucratic agencies and considers a problem where a politician must decide not only which policy to choose but which agency, or combination of agencies, will implement it. The choice of implementation feeds back into the choice of policy and this, in turn, affects how voters perceive the performance of the incumbent. This creates a chain of interdependence from agency structure to policy choice and political accountability. The formal model shows that the variation in organizational capacity serves the interests of voters by improving electoral control of politicians.
Multi objective Neural Architecture Search via Predictive Network Performance Optimization
Venue: ArXiv
Year: 2019

Neural Architecture Search (NAS) has shown great potentials in finding a better neural network design than human design. Sample based NAS is the most fundamental method aiming at exploring the search space and evaluating the most promising architecture. However, few works have focused on improving the sampling efficiency for a multi objective NAS. Inspired by the nature of the graph structure of a neural network, we propose BOGCN NAS, a NAS algorithm using Bayesian Optimization with Graph Convolutional Network (GCN) predictor. Specifically, we apply GCN as a surrogate model to adaptively discover and incorporate nodes structure to approximate the performance of the architecture. For NAS oriented tasks, we also design a weighted loss focusing on architectures with high performance. Our method further considers an efficient multi objective search which can be flexibly injected into any sample based NAS pipelines to efficiently find the best speed/accuracy trade off. Extensive experiments are conducted to verify the effectiveness of our method over many competing methods, e.g. 128.4xmore efficient than Random Search and 7.8xmore efficient than previous SOTA LaNAS for finding the best architecture on the largest NAS dataset NASBench 101.
Multi subject analyses with dynamic causal modeling
Venue: NeuroImage
Year: 2010

Currently, most studies that employ dynamic causal modeling (DCM) use random effects (RFX) analysis to make group inferences, applying a second level frequentist test to subjects' parameter estimates. In some instances, however, fixed effects (FFX) analysis can be more appropriate. Such analyses can be implemented by combining the subjects' posterior densities according to Bayes' theorem either on a multivariate (Bayesian parameter averaging or BPA) or univariate basis (posterior variance weighted averaging or PVWA) or by applying DCM to time series averaged across subjects beforehand (temporal averaging or TA) While all these FFX approaches have the advantage of allowing for Bayesian inferences on parameters a systematic comparison of their statistical properties has been lacking so far. Based on simulated data generated from a two region network we examined the effects of signal to noise ratio (SNR) and population heterogeneity on group level parameter estimates. Data sets were simulated assuming either a homogeneous large population (N=60) with constant connectivities across subjects or a heterogeneous population with varying parameters. TA showed advantages at lower SNR but is limited in its applicability. Because BPA and PVWA take into account posterior (co)variance structure, they can yield non intuitive results when only considering posterior means. This problem is relevant for high SNR data, pronounced parameter interdependencies and when FFX assumptions are violated (i.e. inhomogeneous groups) It diminishes with decreasing SNR and is absent for models with independent parameters or when FFX assumptions are appropriate. Group results obtained with these FFX approaches should therefore be interpreted carefully by considering estimates of dependencies among model parameters.
Developing a spatial analysis framework to guide interoperable urban flood management
Year: 2019

Integrated approaches are needed to make cities resilient to flooding, while aligning with the complex functioning of cities. Central to this integrated thinking is the importance of interfaces and connections, i.e. interoperability, between existing (and new) infrastructure systems to store and transfer stormwater. Yet, it remains challenging to identify how and where connecting different technical solutions and existing infrastructure systems will contribute to flood resilience. There are a lack of approaches to systematically assess flood adaptation options from an interoperable perspective. Nevertheless, the increasing amount of spatial data on urban areas (often publically available) presents an unprecedented opportunity to consider urban areas holistically. The research question addressed in this study is how spatial data can be combined to inform decision making in flood management at the systems level. A spatial analysis framework is presented that aims to synthesize four aspects essential to system oriented urban flood management: (i) flood hazard; (ii) intervention efficiency; (iii) opportunities for interoperability; and (iv) barriers to system integration. By considering these aspects together, further development of the framework into an accessible mapping tool will facilitate engagement among researchers and flood management practitioners in integrating multiple infrastructure systems to increase urban
Study on establishing the power grid advanced metering infrastructure by applying on site working standard
Venue: 2012 International Conference on Systems and Informatics (ICSAI2012)
Year: 2012

This paper discusses the basic scheme for establishing advanced metering infrastructure (AMI) by applying a high voltage electric energy on site calibration apparatus. The apparatus can work as an on site working standard for implementing on site calibration or verification to kinds of meters, electric energy metering cabinet and electric energy device in AMI. Furthermore, this paper provides a technical mean for calculating parameters of power grid, such as transformer loss and wire loss, in accordance with the principle of energy conservation. 10kV high voltage on site calibration apparatus had been developed successfully and has been running in the power grid, on site test results can prove that the scheme is feasible. Establishing a complete AMI system is of great significance for building a strong smart grid.
Light Field Compression of HDCA Images Combining Linear Prediction and JPEG 2000
Venue: 2018 26th European Signal Processing Conference (EUSIPCO)
Year: 2018

We have proposed under JPEG Pleno standardization activities a scheme for lenslet image compression, where the regularities and similarities existing between neighbor angular views were successfully exploited, achieving competitive results in the JPEG Pleno core experiments using lenslet data. This paper proposes improvements on our previous scheme of light field compression, making our approach more suitable for compression of light fields acquired with dense camera arrays, where the disparities between farthest views can reach several hundreds of pixels. We review the functional blocks of the compression algorithm, replacing and modifying some of the functionality with more advanced and efficient solutions. Based on our submission to the JPEG Pleno core experiments, we present and discuss our results obtained on the Fraunhofer HDCA dataset. Additionally, we present a new view merging algorithm which substantially increases the PSNR at all bit rates.
Sentiment based and hashtag based Chinese online bursty event detection
Year: 2018

How to detect bursty events in data streams on social media is a hot research topic in natural language processing. However, current methods for extracting bursty events suffer from poor accuracy and low efficiency. Fortunately, sentiment analysis has been applied to event detection, which has improved the performance greatly. Inspired by this, this paper proposes a new model which utilizes sentiment analysis for Chinese bursty event detection. First, we build a sentiment co occurrence graph offline and apply it to analyze microblog sentiment. Plutchik's emotion wheel is the base for the sentiment classification of the graph. Second, sentiment is used as features to detect bursts in microblog streams online. At last, we exploit regular expressions to extract hashtags in bursty periods and segment hashtags into keywords. By using mutual information and frequent patterns, we fetch words relevant to hashtags as keywords to form events. This approach can detect bursty events online while analyzing the sentiment of microblogs. The experimental results on a large real dataset show that our method can detect bursty events with higher accuracy in a shorter time than traditional methods.
Basic Marketing A Global Managerial Approach
Year: 2016

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Social effects of poor sanitation and waste management on poor urban communities: a neighborhood specific study of Sabon Zongo, Accra
Year: 2010

This paper provides a neighborhood specific study of the social effects of poor sanitation in a poor neighborhood in a developing country city, Accra. It examines the challenges of rapid urbanization with respect to sanitation and waste management, and the burdens placed on poor urban residents in Sabon Zongo, a poor community in Accra. Like many poor communities in Accra and other large Ghanaian cities, residents of Sabon Zongo unable to queue and pay for sanitation services tend to package their liquid and solid waste in plastic bags and dump them indiscriminately within the community. The paper argues that the inability of city authorities to deal with sanitation and waste management in the poor urban community of Sabon Zongo go beyond the much discussed issue of health. This is because the inadequacy of sanitation and waste management in this particular poor urban settlement also has social implications. The paper concludes that while slums and poor urban communities may exhibit certain similar characteristics, they are not homogenous. Neighborhood specific research such as the present study on Sabon Zongo offers opportunities for analyzing and understanding the internal dynamics, and the key stakeholders at the community level critical conditions for tapping into the energies of residents toward addressing the challenges of sanitation and waste management in poor urban communities in Accra.
Eksplorasi Disain Ventilasi Ruang Kuliah Untuk Mencapai Kenyamanan Termal
Venue: EMARA Indonesian Journal of Architecture
Year: 2019

Kenyamanan termal menjadi faktor penting dalam menunjang efektifitas kinerja di dalam ruang. Untuk memaksimalkan kenyamanan termal tanpa merusak lingkungan, potensi angin dapat dimanfaatkan melalui sistem ventilasi silang. Ventilasi silang dapat menjadi media yang baik sebagai pengalir udara, jika memperhatikan 3 (tiga) aspek, yaitu ukuran, bentuk, dan posisi ventilasi. Tujuan dari penelitian ini adalah mengeksplorasi desain ventilasi terbaik untuk mencapai kenyamanan termal yang dimaksud, khususnya pada ruang ruang perkuliahan. Metode penelitian yang digunakan adalah deskriprif kuantitatif untuk menghasilkan sebuah rekomendasi desain, yang diikuti dengan validasi data menggunakan software ecotect. Ruang ruang perkuliahan di Fakultas Ushuluddin UIN Sunan Ampel dipilih untuk menjadi studi kasus. Hasil penelitian menunjukkan bahwa ventilasi silang melalui jendela besar berjenis vertically pivoted merupakan ventilasi yang paling efektif untuk dipakai di ruang ruang perkuliahan Fakultas Ushuluddin. Model ini dapat memaksimalkan aliran udara hingga 75% dan membuat ruangan 1,4 2,7degC lebih sejuk.
Kepimpinan Pengetua Berdasarkan Atribut Semula Jadi dalam Memartabatkan Profesionalisme Keguruan di SMK St Micheal Penampang, Sabah
Year: 2019

Kepimpinan pengetua diterokai berdasarkan atribut semula jadi yang memfokuskan ketegasan kepimpinan pengetua dalam lapan bidang amalan pengurusan di sekolah. Kerangka teoritikal adalah bersandarkan Teori The Great Man dan model pengetua berkesan diaplikasikan dalam menjalankan kajian secara kualitatif iaitu melalui kajian kes tunggal. Data kualitatif ini diperolehi dengan menemubual pengetua, barisan pentadbir, guru kanan mata pelajaran, dan guru guru. Data kualitatif dianalisa secara manual. Dapatan menunjukkan atribut semula jadi pengetua berdasarkan aspek ketegasan adalah mencerminkan kewibawaan sikap pengetua dalam amalan pengurusannya di sekolah. Aspek ini diteliti berdasarkan tema demografi pengetua dan pandangan guru guru. Temu bual mendalam ini menjelaskan amalan pengurusan kepimpinan pengetua dalam lapan bidang utama di sekolah didapati menyokong dapatan sebagaimana dalam teori dibangunkan serta model pengetua berkesan. Bagaimanapun, dalam menghadapi cabaran impak globalisasi, pengetua juga memerlukan sokongan daripada pelbagai pihak sama ada warga sekolah mahupun pihak luar dalam mengurus sekolah dengan lebih berkesan.