shinyReCoR. A shiny application for automatically coding text responses using R

In this paper, we introduce shinyReCoR: a new app that utilizes a cluster-based method for automatically coding open-ended text responses. Reliable coding of text responses from educational or psychological assessments requires substantial organizational and human effort. The coding of natural language in responses to tests depends on the texts\u27 complexity, corresponding coding guides, and the guides\u27 quality. Manual coding is thus not only expensive but also error-prone. With shinyReCoR, we provide a more efficient alternative. The use of natural language processing makes texts utilizable for statistical methods. shinyReCoR is a Shiny app deployed as an R-package that allows users with varying technical affinity to create automatic response classifiers through a graphical user interface based on annotated data. The present paper describes the underlying methodology, including machine learning, as well as peculiarities of the processing of language in the assessment context. The app guides users through the workflow with steps like text corpus compilation, semantic space building, preprocessing of the text data, and clustering. Users can adjust each step according to their needs. Finally, users are provided with an automatic response classifier, which can be evaluated and tested within the process. (DIPF/Orig.

Language Models have a Moral Dimension

Artificial writing is permeating our lives due to recent advances in large-scale, transformer-based language models (LMs) such as BERT, its variants, GPT-2/3, and others. Using them as pretrained models and fine-tuning them for specific tasks, researchers have extended the state of the art for many NLP tasks and shown that they not only capture linguistic knowledge but also retain general knowledge implicitly present in the data. These and other successes are exciting. Unfortunately, LMs trained on unfiltered text corpora suffer from degenerate and biased behaviour. While this is well established, we show that recent improvements of LMs also store ethical and moral values of the society and actually bring a ``moral dimension'' to surface: the values are capture geometrically by a direction in the embedding space, reflecting well the agreement of phrases to social norms implicitly expressed in the training texts. This provides a path for attenuating or even preventing toxic degeneration in LMs. Since one can now rate the (non-)normativity of arbitrary phrases without explicitly training the LM for this task, the moral dimension can be used as ``moral compass'' guiding (even other) LMs towards producing normative text, as we will show

Applying psychometric modeling to aid feature engineering in predictive log-data analytics. The NAEP EDM Competition

The NAEP EDM Competition required participants to predict efficient test-taking behavior based on log data. This paper describes our top-down approach for engineering features by means of psychometric modeling, aiming at machine learning for the predictive classification task. For feature engineering, we employed, among others, the Log-Normal Response Time Model for estimating latent person speed, and the Generalized Partial Credit Model for estimating latent person ability. Additionally, we adopted an n-gram feature approach for event sequences. Furthermore, instead of using the provided binary target label, we distinguished inefficient test takers who were going too fast and those who were going too slow for training a multi-label classifier. Our best-performing ensemble classifier comprised three sets of low-dimensional classifiers, dominated by test-taker speed. While our classifier reached moderate performance, relative to the competition leaderboard, our approach makes two important contributions. First, we show how classifiers that contain features engineered through literature-derived domain knowledge can provide meaningful predictions if results can be contextualized to test administrators who wish to intervene or take action. Second, our re-engineering of test scores enabled us to incorporate person ability into the models. However, ability was hardly predictive of efficient behavior, leading to the conclusion that the target label\u27s validity needs to be questioned. Beyond competition-related findings, we furthermore report a state sequence analysis for demonstrating the viability of the employed tools. The latter yielded four different test-taking types that described distinctive differences between test takers, providing relevant implications for assessment practice. (DIPF/Orig.

A Patient-Specific Musculoskeletal Model of Total Knee Arthroplasty to Predict In Vivo Knee Biomechanics

Musculoskeletal(MS) models are useful to gain information on in vivo biomechanics that would be otherwise very difficult to obtain.However, before entering the clinical routine MS models must be thoroughlyvalidated. This study presents a novel MS modelling framework capable ofintegrating the patient-specific MS architecture in a very detailed way, andsimultaneously simulating body level dynamics and secondary knee kinematics.The model predictions were further validated against publicly available in vivo experimental data. The bonegeometries were segmented from CT images of a patient with an instrumentedTotal Knee Arthroplasty (TKA) from the “Grand Challenge Competition to Predict In Vivo Knee Loads” dataset. These were inputtedinto an advanced morphing technique in order to scale the MS architecture of thenew TLEM 2.0 model1 to the specific patient. A detailed 11-DOF modelof the knee joint was constructed that included ligaments and rigid contact. Aninverse kinematic and a force-dependent kinematic technique2 wereutilized to simulate one gait cycle and one right-turn trial. Tibiofemoral (TF)joint contact force predictions were evaluated against experimental TF forcesrecorded by the TKA prosthesis, and secondary knee kinematics againstexperimental fluoroscopy data. The coefficientof determination and the root-mean-square error between predicted andexperimental tibiofemoral forces were larger than 0.9 and smaller than 0.3body-weights, respectively, for both gait and right-turn trials. Secondary kneekinematics were estimated with an average Sprague and Geers’ combined error assmall as 0.06. Themodelling strategy proposed permits a high level of patient-specificpersonalization and does not require any non-physiological parameter tuning.The very good agreement between predictions and experimental in vivo data is promising for the futureintroduction of the model into clinical applications

Limited effects of preterm birth and the first enteral nutrition on cerebellum morphology and gene expression in piglets

Preterm pigs show many signs of immaturity that are characteristic of preterm infants. In preterm infants, the cerebellum grows particularly rapid and hypoplasia and cellular lesions are associated with motor dysfunction and cognitive deficits. We hypothesized that functional brain delays observed in preterm pigs would be paralleled by both structural and molecular differences in the cerebellum relative to term born piglets. Cerebella were collected from term (n=56) and preterm (90% gestation, n=112) pigs at 0, 5, and 26days after birth for stereological volume estimations, large-scale qPCR gene expression analyses (selected neurodevelopmental genes) and western blot protein expression analysis (Sonic Hedgehog pathway). Memory and learning was tested using a T-maze, documenting that preterm pigs showed delayed learning. Preterm pigs also showed reduced volume of both white and gray matter at all three ages but the proportion of white matter increased postnatally, relative to term pigs. Early initiation of enteral nutrition had limited structural or molecular effects. The Sonic Hedgehog pathway was unaffected by preterm birth. Few differences in expression of the selected genes were found, except consistently higher mRNA levels of Midkine, p75, and Neurotrophic factor 3 in the preterm cerebellum postnatally, probably reflecting an adaptive response to preterm birth. Pig cerebellar development appears more affected by postconceptional age than by environmental factors at birth or postnatally. Compensatory mechanisms following preterm birth may include faster white matter growth and increased expression of selected genes for neurotrophic factors and regulation of angiogenesis. While the pig cerebellum is immature in 90% gestation preterm pigs, it appears relatively mature and resilient toward environmental factor

Comparison between light scattering and gravimetric samplers for PM10 mass concentration in poultry and pig houses

The objective of this study was to compare co-located real-time light scattering devices and equivalent gravimetric samplers in poultry and pig houses for PM10 mass concentration, and to develop animal-specific calibration factors for light scattering samplers. These results will contribute to evaluate the comparability of different sampling instruments for PM10, concentrations. Paired DustTrak light scattering device (DustTrak aerosol monitor, TSI, U.S.) and PM10 gravimetric cyclone sampler were used for measuring PM10 mass concentrations during 24 h periods (from noon to noon) inside animal houses. Sampling was conducted in 32 animal houses in the Netherlands, including broilers, broiler breeders, layers in floor and in aviary system, turkeys, piglets, growing-finishing pigs in traditional and low emission housing with dry and liquid feed, and sows in individual and group housing. A total of 119 pairs of 24 h measurements (55 for poultry and 64 for pigs) were recorded and analyzed using linear regression analysis. Deviations between samplers were calculated and discussed. In poultry, cyclone sampler and DustTrak data fitted well to a linear regression, with a regression coefficient equal to 0.41, an intercept of 0.16 mg m(-3) and a correlation coefficient of 0.91 (excluding turkeys). Results in turkeys showed a regression coefficient equal to 1.1 (P = 0.49), an intercept of 0.06 mg m(-3) (P < 0.0001) and a correlation coefficient of 0.98. In pigs, we found a regression coefficient equal to 0.61, an intercept of 0.05 mg m(-3) and a correlation coefficient of 0.84. Measured PM10 concentrations using DustTraks were clearly underestimated (approx. by a factor 2) in both poultry and pig housing systems compared with cyclone pre-separators. Absolute, relative, and random deviations increased with concentration. DustTrak light scattering devices should be self-calibrated to investigate PM10 mass concentrations accurately in animal houses. We recommend linear regression equations as animal-specific calibration factors for DustTraks instead of manufacturer calibration factors, especially in heavily dusty environments such as animal houses. (C) 2015 Elsevier Ltd. All rights reserved.The study was financed by the Dutch Ministry of Economic affairs, Agriculture and Innovation. Authors wish to thank the Campus de Excelencia Internacional of the Universitat Politecnica de Valencia (Spain) for funding Dr. Cambra-Lopez's postdoc contract.Cambra López, M.; Winkel, A.; Mosquera, J.; Ogink, NW.; Aarnink, AJA. (2015). Comparison between light scattering and gravimetric samplers for PM10 mass concentration in poultry and pig houses. Atmospheric Environment. 111:20-27. doi:10.1016/j.atmosenv.2015.03.051S202711

Competition can lead to unexpected patterns in tropical ant communities

Ecological communities are structured by competitive, predatory, mutualistic and parasitic interactions combined with chance events. Separating deterministic from stochastic processes is possible, but finding statistical evidence for specific biological interactions is challenging. We attempt to solve this problem for ant communities nesting in epiphytic bird's nest ferns (Asplenium nidus) in Borneo's lowland rainforest. By recording the frequencies with which each and every single ant species occurred together, we were able to test statistically for patterns associated with interspecific competition. We found evidence for competition, but the resulting co-occurrence pattern was the opposite of what we expected. Rather than detecting species segregation—the classical hallmark of competition—we found species aggregation. Moreover, our approach of testing individual pairwise interactions mostly revealed spatially positive rather than negative associations. Significant negative interactions were only detected among large ants, and among species of the subfamily Ponerinae. Remarkably, the results from this study, and from a corroborating analysis of ant communities known to be structured by competition, suggest that competition within the ants leads to species aggregation rather than segregation. We believe this unexpected result is linked with the displacement of species following asymmetric competition. We conclude that analysing co-occurrence frequencies across complete species assemblages, separately for each species, and for each unique pairwise combination of species, represents a subtle yet powerful way of detecting structure and compartmentalisation in ecological communities

MiDAS 4: A global catalogue of full-length 16S rRNA gene sequences and taxonomy for studies of bacterial communities in wastewater treatment plants

Microbial communities are responsible for biological wastewater treatment, but our knowledge of their diversity and function is still poor. Here, we sequence more than 5 million high-quality, full-length 16S rRNA gene sequences from 740 wastewater treatment plants (WWTPs) across the world and use the sequences to construct the ‘MiDAS 4’ database. MiDAS 4 is an amplicon sequence variant resolved, full-length 16S rRNA gene reference database with a comprehensive taxonomy from domain to species level for all sequences. We use an independent dataset (269 WWTPs) to show that MiDAS 4, compared to commonly used universal reference databases, provides a better coverage for WWTP bacteria and an improved rate of genus and species level classification. Taking advantage of MiDAS 4, we carry out an amplicon-based, global-scale microbial community profiling of activated sludge plants using two common sets of primers targeting regions of the 16S rRNA gene, revealing how environmental conditions and biogeography shape the activated sludge microbiota. We also identify core and conditionally rare or abundant taxa, encompassing 966 genera and 1530 species that represent approximately 80% and 50% of the accumulated read abundance, respectively. Finally, we show that for well-studied functional guilds, such as nitrifiers or polyphosphate-accumulating organisms, the same genera are prevalent worldwide, with only a few abundant species in each genus.Fil: Dueholm, Morten Kam Dahl. Aalborg University; DinamarcaFil: Nierychlo, Marta. Aalborg University; DinamarcaFil: Andersen, Kasper Skytte. Aalborg University; DinamarcaFil: Rudkjøbing, Vibeke. Aalborg University; DinamarcaFil: Knutsson, Simon. Aalborg University; DinamarcaFil: Arriaga, Sonia. Instituto Potosino de Investigación Científica y Tecnológica; MéxicoFil: Bakke, Rune. University College of Southeast Norway; NoruegaFil: Boon, Nico. University of Ghent; BélgicaFil: Bux, Faizal. Durban University of Technology; SudáfricaFil: Christensson, Magnus. Veolia Water Technologies Ab; SueciaFil: Chua, Adeline Seak May. University Malaya; MalasiaFil: Curtis, Thomas P.. University of Newcastle; Reino UnidoFil: Cytryn, Eddie. Agricultural Research Organization Of Israel; IsraelFil: Erijman, Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentina. Universidad de Buenos Aires; ArgentinaFil: Etchebehere, Claudia. Instituto de Investigaciones Biológicas "Clemente Estable"; UruguayFil: Fatta Kassinos, Despo. University of Cyprus; ChipreFil: Frigon, Dominic. McGill University; CanadáFil: Garcia Chaves, Maria Carolina. Universidad de Antioquia; ColombiaFil: Gu, April Z.. Cornell University; Estados UnidosFil: Horn, Harald. Karlsruher Institut Für Technologie; AlemaniaFil: Jenkins, David. David Jenkins & Associates Inc; Estados UnidosFil: Kreuzinger, Norbert. Tu Wien; AustriaFil: Kumari, Sheena. Durban University of Technology; SudáfricaFil: Lanham, Ana. University of Bath; Reino UnidoFil: Law, Yingyu. Singapore Centre For Environmental Life Sciences Engineering; SingapurFil: Leiknes, TorOve. King Abdullah University of Science and Technology; Arabia SauditaFil: Morgenroth, Eberhard. Eth Zürich; SuizaFil: Muszyński, Adam. Politechnika Warszawska; PoloniaFil: Petrovski, Steve. La Trobe University; AustraliaFil: Pijuan, Maite. Catalan Institute For Water Research; EspañaFil: Pillai, Suraj Babu. Va Tech Wabag Ltd; IndiaFil: Reis, Maria A. M.. Universidade Nova de Lisboa; PortugalFil: Rong, Qi. Chinese Academy of Sciences; ChinaFil: Rossetti, Simona. Istituto Di Ricerca Sulle Acque (irsa) ; Consiglio Nazionale Delle Ricerche;Fil: Seviour, Robert. La Trobe University; AustraliaFil: Tooker, Nick. University of Massachussets; Estados UnidosFil: Vainio, Pirjo. Espoo R&D Center; FinlandiaFil: van Loosdrecht, Mark. Delft University of Technology; Países BajosFil: Vikraman, R.. VA Tech Wabag, Philippines Inc; FilipinasFil: Wanner, Jiří. University of Chemistry And Technology; República ChecaFil: Weissbrodt, David. Delft University of Technology; Países BajosFil: Wen, Xianghua. Tsinghua University; ChinaFil: Zhang, Tong. The University of Hong Kong; Hong KongFil: Nielsen, Per H.. Aalborg University; DinamarcaFil: Albertsen, Mads. Aalborg University; DinamarcaFil: Nielsen, Per Halkjær. Aalborg University; Dinamarc

Storm impacts on phytoplankton community dynamics in lakes

In many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short-term runoff events from watersheds and physical mixing of the water column. In addition, lakes connected to rivers and streams will also experience flushing due to high flow rates. Although we have a well-developed understanding of how wind and precipitation events can alter lake physical processes and some aspects of biogeochemical cycling, our mechanistic understanding of the emergent responses of phytoplankton communities is poor. Here we provide a comprehensive synthesis that identifies how storms interact with lake and watershed attributes and their antecedent conditions to generate changes in lake physical and chemical environments. Such changes can restructure phytoplankton communities and their dynamics, as well as result in altered ecological function (e.g., carbon, nutrient and energy cycling) in the short- and long-term. We summarize the current understanding of storm-induced phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions across a gradient of lake types and environmental conditions.Peer reviewe

A randomised clinical trial on cardiotocography plus fetal blood sampling versus cardiotocography plus ST-analysis of the fetal electrocardiogram (STAN®) for intrapartum monitoring

<p>Abstract</p> <p>Background</p> <p>Cardiotocography (CTG) is worldwide the method for fetal surveillance during labour. However, CTG alone shows many false positive test results and without fetal blood sampling (FBS), it results in an increase in operative deliveries without improvement of fetal outcome. FBS requires additional expertise, is invasive and has often to be repeated during labour. Two clinical trials have shown that a combination of CTG and ST-analysis of the fetal electrocardiogram (ECG) reduces the rates of metabolic acidosis and instrumental delivery. However, in both trials FBS was still performed in the ST-analysis arm, and it is therefore still unknown if the observed results were indeed due to the ST-analysis or to the use of FBS in combination with ST-analysis.</p> <p>Methods/Design</p> <p>We aim to evaluate the effectiveness of non-invasive monitoring (CTG + ST-analysis) as compared to normal care (CTG + FBS), in a multicentre randomised clinical trial setting. Secondary aims are: 1) to judge whether ST-analysis of fetal electrocardiogram can significantly decrease frequency of performance of FBS or even replace it; 2) perform a cost analysis to establish the economic impact of the two treatment options.</p> <p>Women in labour with a gestational age ≥ 36 weeks and an indication for CTG-monitoring can be included in the trial.</p> <p>Eligible women will be randomised for fetal surveillance with CTG and, if necessary, FBS or CTG combined with ST-analysis of the fetal ECG.</p> <p>The primary outcome of the study is the incidence of serious metabolic acidosis (defined as pH < 7.05 and Bd_ecf> 12 mmol/L in the umbilical cord artery). Secondary outcome measures are: instrumental delivery, neonatal outcome (Apgar score, admission to a neonatal ward), incidence of performance of FBS in both arms and cost-effectiveness of both monitoring strategies across hospitals.</p> <p>The analysis will follow the intention to treat principle. The incidence of metabolic acidosis will be compared across both groups. Assuming a reduction of metabolic acidosis from 3.5% to 2.1 %, using a two-sided test with an alpha of 0.05 and a power of 0.80, in favour of CTG plus ST-analysis, about 5100 women have to be randomised. Furthermore, the cost-effectiveness of CTG and ST-analysis as compared to CTG and FBS will be studied.</p> <p>Discussion</p> <p>This study will provide data about the use of intrapartum ST-analysis with a strict protocol for performance of FBS to limit its incidence. We aim to clarify to what extent intrapartum ST-analysis can be used without the performance of FBS and in which cases FBS is still needed.</p> <p>Trial Registration Number</p> <p>ISRCTN95732366</p