nils-herrmann/clean_scirepeval huggingface dataset:
Hungry for inclusion: Exposure to peer victimization and heightened social monitoring in adolescent girls
Venue: Development and Psychopathology
Year: 2020

Belonging to a social group is one of the most important factors contributing to well being. The Belonging Regulation model proposes that humans possess a social monitoring system (SMS) that evaluates social inclusion and monitors belonging needs. Here, we used a prospective longitudinal design to examine links between peer victimization experienced across 7 years and social monitoring at the behavioral and neural level in adolescent girls (n 38, Mage 15.43 years, SD .33) Participants completed a social evaluation task during a functional magnetic resonance imaging (fMRI) scan. More severe peer victimization was associated with increased activation to in group versus out group peers in the amygdala, ventral striatum, fusiform gyrus, and temporoparietal junction. Moreover, participants who displayed increased activation in these regions reported lower social self esteem and higher levels of internalizing and externalizing symptoms. These results suggest that exposure to peer victimization across the school years is associated with heightened social monitoring at the neural level during adolescence, which has potential adverse implications for girls' adjustment and well being.
Chemical vapor deposition of layered two dimensional MoSi2N4 materials
Venue: Science
Year: 2020

Stabilizing monolayer nitrides with silicon Transition metal carbides and nitrides are nonlayered materials that in monolayer form have potentially useful electronic and chemical properties. These monolayers are usually made by chemical etching that produces flakes with surface defects that have poor air and water stability. Hong et al. report that introducing silicon during chemical vapor deposition growth of molybdenum nitride passivates the surface and prevents island formation. Centimeter scale monolayer films of the semiconductor MoSi2N4 form as a MoN2 layer sandwiched by two Si N bilayers. These layers possess high mechanical strength and ambient stability. Science, this issue p. 670 Addition of silicon during film growth stabilized a molybdenum nitride monolayer by sandwiching it between two Si N bilayers. Identifying two dimensional layered materials in the monolayer limit has led to discoveries of numerous new phenomena and unusual properties. We introduced elemental silicon during chemical vapor deposition growth of nonlayered molybdenum nitride to passivate its surface, which enabled the growth of centimeter scale monolayer films of MoSi2N4. This monolayer was built up by septuple atomic layers of N Si N Mo N Si N, which can be viewed as a MoN2 layer sandwiched between two Si N bilayers. This material exhibited semiconducting behavior (bandgap ~1.94 electron volts) high strength ~66 gigapascals) and excellent ambient stability. Density functional theory calculations predict a large family of such monolayer structured two dimensional layered materials, including semiconductors, metals, and magnetic half metals.
Impact of Downpours on Fluvial Processes in the Polish Carpathians as Exemplified by the Bystrzanka Stream
Year: 2012

This paper present the results of the geomorphological mapping of transformations in the Bystrzanka channel after the rainfall in May and June 2010. Mapping data from June 2010 were compared to observations from April 2010. Total rainfall in the 20 day period from 15 May to 3 June was 320.4 mm, which constituted the highest two decade value in the last 40 years. Research of concentration of suspended sediments showed that sediments concentration in the main tributary (Gerucha) during the flood on June was up to 4.5 times higher than the concentration in the Bystrzanka. High discharge (57.7 m s) have caused significant transformations of the Bystrzanka channel (main stream 7,1 km, area 13 km) Numerous cut banks occurred at an irregular fashion along the whole length of the stream. Cut banks of the channel most often reached the height of 2 m. Point bars and central bars of varied size and shape, depending on channel morphology, were observed along the whole length of the study channel and consisted mainly of sand, gravel, and boulders both abraded (in varying degrees) and non abraded. Also observed was the activation of rotational landslides at the stream banks, the fronts of which almost entirely blocked the bottom of the stream. High discharge during the flood caused damage to the road, resulting in the riverbank receding by about 10 m.
MINI SEED 2 (MIS2) Encodes a Receptor like Kinase that Controls Grain Size and Shape in Rice
Venue: Rice
Year: 2020

Grain size is a key agronomic trait that is directly associated with grain yield in rice. Although several genes related to grain size in rice have been identified, our understanding of the mechanism of grain development is still limited. In this study, we reported the characterization of a novel seed size mutant mini seed 2 (mis2) in which the grain showed reduced length, width and thickness along with wrinkled surface. Microscopic analysis revealed that the spikelet epidermal cell size was reduced but the cell number was increased in the mis2 mutant, suggesting that MIS2 controls grain size by coordinately regulating epidermal cell size and cell number. Map based cloning revealed that MIS2 encodes a receptor like kinase CRINKLY4 (CR4) which showed the highest expression in developing panicles. The MIS2 protein is localized primarily on the plasma membrane along with the endosome. However, the Arg258Gln mutation located in extracellular domain in the mis2 mutant disturbed its subcellular localization. Additionally, three major haplotypes of MIS2 were identified in the japonica, indica and aus rice cultivars. The 18 bp InDel (insertion and deletion) in the 5' UTR (untranslated region) caused different expression level of MIS2 in haplotypes. We reported a key role of OsCR4 in controlling grain size and shape by coordinately regulating epidermal cell size and cell number. The Arg258 in the extracellular seven repeat domain is essential for the correct subcellular behavior and function of the OsCR4 protein.
Predicting the Effects of Language Learning on Cognition and Well being in Late Life Depression A systematic review and future directions [cancelled/postponed due to COVID 19]
Year: 2019

Late life depression (LLD) is often overshadowed by other age related illnesses such as Alzheimer's disease. Studies estimate, however, that approximately a quarter of community dwelling older adults, and nearly half of those in nursing homes experience depressive symptoms to varying degrees. This is problematic, as LLD and cognitive dysfunction are closely linked, which has even led some to consider LLD a prodromal form of dementia. Unsurprisingly, social well being is negatively impacted in those with LLD, too, with loneliness and small social networks being characteristic of LLD patients. The effectiveness of antidepressants in LLD patients is not supported by meta analyses, and many avoid seeking mental health professionals due to stigmas surrounding LLD. A proposed solution that is inherently social, while simultaneously targeting brain structures affected in LLD, is foreign language learning. It has been suggested that lifelong bilingualism boosts cognitive reserve, which significantly delays the onset of cognitive impairment symptoms. Recent research has suggested that even late life foreign language learning can be beneficial in training cognitive flexibility, a useful skill in staving off rumination in LLD patients. Simultaneously, the classroom based nature of a language intervention may reduce feelings of loneliness associated with depression in older adulthood. The present review, therefore, aims to systematically compare the cognitive domains that are weakened in LLD to those that are strengthened by foreign language training. Additionally, findings regarding changes in well being as a result of group based interventions will be discussed. Based on this systematic review, future directions for language training in relation to LLD will be presented.
Online Drone Education, a Mapping Review
Venue: 2020 IEEE Global Engineering Education Conference (EDUCON)
Year: 2020

As Unmanned Aerial Vehicles (UAV) increase in popularity, legislation, use and applications education becomes a paramount objective for safety reasons and correct usage of this technology. Online education is becoming one of the main sources of knowledge, especially thanks to the wider geographical and social reach. Online education regarding UAVs has become a crucial mean to transfer and spread this knowledge. This work presents a mapping review of the state of such education with the aim of finding knowledge gaps and areas of improvement.
Semi Supervised Graph Embedding Scheme with Active Learning (SSGEAL) Classifying High Dimensional Biomedical Data
Venue: PRIB
Year: 2010

In this paper, we present a new dimensionality reduction (DR) method (SSGEAL) which integrates Graph Embedding (GE) with semi supervised and active learning to provide a low dimensional data representation that allows for better class separation. Unsupervised DR methods such as Principal Component Analysis and GE have previously been applied to the classification of high dimensional biomedical datasets (e.g. DNA microarrays and digitized histopathology) in the reduced dimensional space. However, these methods do not incorporate class label information, often leading to embeddings with significant overlap between the data classes. Semi supervised dimensionality reduction (SSDR) methods have recently been proposed which utilize both labeled and unlabeled instances for learning the optimal low dimensional embedding. However, in several problems involving biomedical data, obtaining class labels may be difficult and/or expensive. SSGEAL utilizes labels from instances, identified as "hard to classify" by a support vector machine based active learning algorithm, to drive an updated SSDR scheme while reducing labeling cost. Real world biomedical data from 7 gene expression studies and 3900 digitized images of prostate cancer needle biopsies were used to show the superior performance of SSGEAL compared to both GE and SSAGE (a recently popular SSDR method) in terms of both the Silhouette Index (SI) (SI 0.35 for GE, SI 0.31 for SSAGE, and SI 0.50 for SSGEAL) and the Area Under the Receiver Operating Characteristic Curve (AUC) for a Random Forest classifier (AUC 0.85 for GE, AUC 0.93 for SSAGE, AUC 0.94 for SSGEAL)
Improving Aeromagnetic Calibration Using Artificial Neural Networks
Year: 2020

The Global Positioning System (GPS) has proven itself to be the single most accurate positioning system available, and no navigation suite is found without a GPS receiver. Even basic GPS receivers found in most smartphones can easily provide high quality positioning information at any time. Even with its superb performance, GPS is prone to jamming and spoofing, and many platforms requiring accurate positioning information are in dire need of other navigation solutions to compensate in the event of an outage, be the cause hostile or natural. Indeed, there has been a large push to achieve an alternative navigation capability which performs nearly as well as GPS. One navigation method which has shown promise to increase navigation performance of aircraft utilizes magnetic anomalies[1] local variations in the Earth's crust to discern position. One significant drawback to this approach is the magnetic disturbance generated by the aircraft itself, which must be accounted for and eliminated. Current calibration procedures involve placing the magnetometer on a long stinger far from the aircraft body to minimize interference with the magnetic anomaly signal. While some aircraft permit the addition of stingers, many do not. No calibration procedure exists which satisfies potential location restraints of the magnetometer and the calibration problem for these less ideal aircraft, especially potentially magnetically noisy platforms such as an F16. Current linear models which attempt to correct mild disturbance fields on more ideal aircraft exist. We propose that a more sophisticated model is necessary to make magnetic navigation platform agnostic. Specifically, we show that a deep learning approach and the utilization of more inputs than the current de facto calibration procedure known in the literature as Tolles Lawson can achieve a 90% reduction in platform based magnetic disturbance signals.
A Weighted Aggregating SGD for Scalable Parallelization in Deep Learning
Venue: 2019 IEEE International Conference on Data Mining (ICDM)
Year: 2019

We investigate the stochastic optimization problem and develop a scalable parallel computing algorithm for deep learning tasks. The key of our study involves a reformation of the objective function for the stochastic optimization in neural network models. We propose a novel update rule, named weighted aggregating stochastic gradient decent, after theoretically analyzing the characteristics of the newly formalized objective function. The new rule introduces a weighted aggregation scheme based on the performance of local workers and does not require a center variable. It assesses the relative importance of local workers and accepts them according to their contributions. Our new rule also allows the implementation of both synchronous and asynchronous parallelization and can result in varying convergence rates. For method evaluation, we benchmark our schemes against the mainstream algorithms, including the elastic averaging SGD in training deep neural networks for classification tasks. We conduct extensive experiments on several classic datasets, and the results confirm the strength of our scheme in accelerating the training of deep architecture and scalable parallelization.
Acknowledgment of Reviewers
Venue: American journal of critical care an official publication, American Association of Critical Care Nurses
Year: 2020

Ines Anjula Pandey Cordeiro Elfriede Poll Ramiro Cruz Duran Richard K. Rabeler Gerrit Davidse Jose Eduardo L. da Silva Ribeiro Laurence J. Dorr Jon Ricketson Christian Feuillet Zachary S. Rogers Pedro Fiaschi George E. Schatz Christopher R. Fraser Jenkins Luiz Jose Soares Pinto Susy Fuentes Bazan Maria de las Mercedes Sosa Antonio Galan de Mera W. D. Stevens Javier Garzon Venegas Antenor A. Sulekic Roy Gereau Susan Swensen Witherup David Glenny Charlotte Taylor Favio Gonzalez Garavito Warren L. Wagner Alisa E. Grabovskaya Borodina Wen Tsai Wang Jason R. Grant Alan Weakley Elsie Franklin Guimaraes J. J. F. E. de Wilde Richard Halse Norris H. Williams Margaret Hanes Ann Willyard Luis G. Hernandez Sandoval Robert E. Wyatt R. James Hickey Yoon Hwan Su Mark Hughes Zhang Li John Huisman Li bing Zhang Jaime Jimenez Ramirez Votis gratias agamus.
Cumulative release characteristics of controlled release nitrogen and potassium fertilizers and their effects on soil fertility, and cotton growth
Venue: Scientific reports
Year: 2016

To investigate the interacting effects of polymer coated urea (PCU) and polymer coated potassium chloride (PCPC) on cotton growth, an experiment was conducted with containerized plants in 2014 and 2015. There were two kinds of nitrogen fertilizer, PCU and urea, which were combined with PCPC at three application rates (40, 80 and 120 kg ha 1) The kinds of nitrogen fertilizer formed the main plot, while individual rates of PCPC were the subplots. The results suggested N and K release patterns for PCU and PCPC in the soil were closely matched to the N and K requirements by cotton. Soil inorganic nitrogen contents significantly increased by using PCU instead of urea, and the same trend was observed with soil available potassium contents, which also had increased rates. Meanwhile, the number of bolls and lint yields of cotton in the PCU treatments were 4.9 35.3% and 2.9 40.7% higher than from urea treatments. Lint yields also increased by 9.1 12.7% with PCPC80 and PCPC120 treatments compared with PCPC40 treatment at the same nitrogen type. Hence, application of PCU combined with 80 kg ha 1 of PCPC fertilizer on cotton increased the yields and fertilizer use efficiencies in addition to improving fiber quality and delaying leaf senescence.
Correction: MOF derived PtCo/Co3O4 nanocomposites in carbonaceous matrices as high performance ORR electrocatalysts synthesized via laser ablation techniques
Year: 2021

Rapidly expanding global energy demands due to fast paced human technology interfaces have propelled fuel cell technology as a sustainable energy conversion alternative. Nonetheless, the rational development of such technology demands the engineering of low cost durable materials that can exhibit and retain specific electrocatalytic activities to sustain the electrochemical energy conversions. Herein, we present our recently patented tandem laser ablation synthesis in solution galvanic replacement reaction (LASiS GRR) as a facile technique for the synthesis of Pt Co bimetallic nanoparticles encapsulated in the simultaneously formed metal organic frameworks (MOF) phases of ZIF 67 out of the laser ablation process. Upon pyrolytic post treatments, these structures are found to be partially altered, giving rise to the formation of graphitic shell coated Pt Co bimetallic nanocomposites (NCs) that are spatially framed onto Co3O4 decorated carbonaceous matrices. We investigate the effect of the Pt precursor (K2PtCl4) concentrations during the LASiS GRR technique in facilitating a higher degree of Pt Co alloying in the phases as the K2PtCl4 initial concentrations are increased from 65 to 125 mg L 1. Our results from subsequent electrochemical characterizations reveal the ability of the as manufactured NCs in the carbonaceous matrix to exhibit superior electrocatalytic activities towards oxygen reduction reaction (ORR) while maintaining their long term stabilities in a highly concentrated alkaline media (KOH 1 M) Specifically, the NCs synthesized from a 125 mg L 1 K2PtCl4 solution demonstrated an extraordinary 5 fold enhancement in their specific mass activities as compared to state of the art commercial Pt catalysts. These outstanding performances are attributed to the unique configurations arising from cooperative catalytic activities (spill over effects) between the graphitic shell coated bimetallic Pt Co nanoparticles and the electrochemically active Co3O4 decorated carbon matrix support.
Information and communication technology overload and social networking service fatigue: A stress perspective
Venue: Comput. Hum. Behav.
Year: 2016

In an always connected communication environment, users of social networking services (SNSs) need to pay continuous attention to the overwhelming volume of social demands from SNSs. These increased energy requirements may cause SNS fatigue, which can lead to physical and psychological strain. Using the transactional theory of stress and coping as the overarching theory, this study regards overload (i.e. stressors) as a core determinant of SNS fatigue (i.e. strain) and identifies three dimensions of overload information overload, communication overload, and system feature overload. It also includes SNS characteristics as the antecedents of overload.The data used in this study were collected from 201 individuals through online and offline surveys. Our results show that all three dimensions of overload were significant stressors that influence SNS fatigue. Regarding the predictors of overload, the characteristics of the SNS system significantly influenced the features of system overload, while information equivocality positively influences information overload. However, information relevance was not a significant predictor of information overload and information equivocality was not a significant predictor of communication overload. We examine SNS fatigue as an outcome of the stress process.Three dimensions of overload are significant stressors influencing SNS fatigue.Information and system characteristics of SNSs are determinants of overload.
Origins and Pathways of Innovation in the Third Industrial Revolution: Sweden, 1950 2013
Year: 2016

This study examines the factors that have shaped the long term evolution of the ICT industry in Sweden, 1950 2013. Exploiting a new historical micro database on actual innovation output, the driving forces and technological interdependencies in the third industrial revolution are chronicled. The results of this study support some stylized facts about innovational interdependencies in general purpose technologies: a closely knitted set of industries have provided positive and negative driving forces for the development of ICT innovations. The historical evolution of the GPT surrounding microelectronics can in this perspective be described as a sequence of development blocks.
Free Surfaces Overcome Superheating in Simulated Melting of Isotactic Polypropylene
Year: 2015

The equilibrium melting temperature Tm is a challenging experimental benchmark for molecular dynamics (MD) simulations of polymer melting and crystallization. Tm obtained from MD heating scans of a phase isotactic polypropylene (aiPP) can exhibit superheating of over 100 degC. This superheating has been attributed to the combined effects of periodic boundary conditions and ultrafast heating rates, both of which inhibit nucleation of the melt. We have developed a simple method to minimize this superheating; we replace the periodic crystal structure with a periodic array of finite thickness slabs, separated by vacuum gaps. Thermal disorder at the slab surface promotes melting by reducing the melt nucleation barrier. For experimental comparison, we synthesized and measured the melting temperatures of a series of low molecular weight iPP oligomers. In simulations of slab systems, melting initiates at the free surface; as the temperature rises above Tm, the interface advances into the crystal, with a velocity pr.
Design of a Novel Underground Coal Mine 127V Power Supply
Year: 2018

In view of the current disadvantages of the large size, high cost and low power factor of custom transformers in China's coal mine 127V power supply system, a novel type of unit power factor rectifier based on OCC (One Cycle Control) is proposed to supply the underground coal mine lighting system. The power supply consists of three stages, including a Vienna rectifier, a high frequency isolated DC DC converter and an inverter. However, the first two stages of the control circuit use a coordinated control. The circuit is simple to control, unit power factor operation can be realized without the multiplier and input voltage detection and half of the voltage stress of the switching device can be reduced as well. The paper analyses in detail the basic working principle and double closed loop control strategy of the new rectifier circuit. The correctness is fully verified by simulations.
DCT based Robust Steganographic Scheme to Hide a Secret Image
Year: 2012

The steganography research has grown rapidly since last decade. This technique has been used to hide different types of information, such as medical, personal and business information and also in some cases it was used in criminal act. This paper presents a robust steganographic scheme focused on the embedding of a secret image into a cover image in the DCT domain using quantization based embedding algorithm. The experimental results show the robustness of the proposed scheme against the JPEG compression and noise contamination, while keeping an imperceptibility of hidden data. The proposed scheme also is robust to commercial stego analyzers, which cannot detect the presence of the hidden data in the stegoimage generated by the proposed scheme. The better performance of the proposed scheme is shown comparing with a previously reported steganography algorithm with same objective of the proposed one.  Steganography, DCT, JPEG, Quantization based embedding, payload, robustness