bluuebunny/crossref_metadata_2025_split huggingface dataset:
Label-free quantitative proteomic analysis of molting-related proteins of Trichinella spiralis intestinal infective larvae
Authors: Ren Hua Nan , Liu Ruo Dan , Song Yan Yan , Zhuo Tong Xu , Guo Kai Xia , Zhang Yao , Jiang Peng , Wang Zhong Quan , Cui Jing 
Published: September 2019

AbstractMolting is a key step for body-size expansion and environmental adaptation of parasitic nematodes, and it is extremely important forTrichinella spiralisgrowth and development, but the molting mechanism is not fully understood. In this work, label-free LC–MS/MS was used to determine the proteome differences betweenT. spiralismuscle larvae (ML) at the encapsulated stage and intestinal infective larvae (IIL) at the molting stage. The results showed that a total of 2885T. spiralisproteins were identified, 323 of which were differentially expressed. These proteins were involved in cuticle structural elements, regulation of cuticle synthesis, remodeling and degradation, and hormonal regulation of molting. These differential proteins were also involved in diverse intracellular pathways, such as fatty acid biosynthesis, arachidonic acid metabolism, and mucin typeO-glycan biosynthesis. qPCR results showed that fiveT. spiralisgenes (cuticle collagen 14, putative DOMON domain-containing protein, glutamine synthetase, cathepsin F and NADP-dependent isocitrate dehydrogenase) had significantly higher transcriptional levels in 10 h IIL than ML (P < 0.05), which were similar to their protein expression levels, suggesting that they might beT. spiralismolting-related genes. Identification and characterization ofT. spiralismolting-related proteins will be helpful for developing vaccines and new drugs against the early enteral stage ofT. spiralis.
Endpoint regularity of discrete multilinear fractional nontangential maximal functions
Authors: Zhang Daiqing 
Published: September 2019

AbstractGiven$m\geq 1$m≥1,$0\leq \lambda \leq 1$0≤λ≤1, and a discrete vector-valued function$\vec{f}=(f_{1},\ldots,f_{m})$f→=(f1,…,fm)with each$f_{j}:\mathbb{Z} ^{d}\rightarrow \mathbb{R}$fj:Zd→R, we consider the discrete multilinear fractional nontangential maximal operator$$ \mathrm{M}_{\alpha,\mathcal{B}}^{\lambda }(\vec{f}) (\vec{n})=\mathop{\sup_{r>0, \vec{x}\in \mathbb{R}^{d}}}_{ \vert \vec{n}-\vec{x} \vert \leq \lambda r}\frac{1}{N(B _{r}(\vec{x}))^{m-\frac{\alpha }{d}}} \prod _{j=1}^{m}\sum_{\vec{k}\in B_{r}(\vec{x})\cap \mathbb{Z}^{d}} \bigl\vert f_{j}(\vec{k}) \bigr\vert , $$Mα,Bλ(f→)(n→)=supr>0,x→∈Rd|n→−x→|≤λr1N(Br(x→))m−αd∏j=1m∑k→∈Br(x→)∩Zd|fj(k→)|,where$\mathcal{B}$Bis the collection of all open balls$B\subset \mathbb{R}^{d}$B⊂Rd,$B_{r}(\vec{x})$Br(x→)is the open ball in$\mathbb{R}^{d}$Rdcentered at$\vec{x}\in \mathbb{R}^{d}$x→∈Rdwith radiusr, and$N(B_{r}(\vec{x}))$N(Br(x→))is the number of lattice points in the set$B_{r}(\vec{x})$Br(x→). We show that the operator$\vec{f}\mapsto |\nabla \mathrm{M}_{\alpha, \mathcal{B}}^{\lambda }(\vec{f})|$f→↦|∇Mα,Bλ(f→)|is bounded and continuous from$\ell ^{1}(\mathbb{Z}^{d})\times \ell ^{1}(\mathbb{Z} ^{d})\times \cdots \times \ell ^{1}(\mathbb{Z}^{d})$ℓ1(Zd)×ℓ1(Zd)×⋯×ℓ1(Zd)to$\ell ^{q}(\mathbb{Z} ^{d})$ℓq(Zd)if$0\leq \alpha < md$0≤α<mdand$q\geq 1$q≥1such that$q>\frac{d}{md- \alpha +1}$q>dmd−α+1. We also prove that the same result also holds for the discrete multilinear fractional nontangential maximal operators associated with cubes. These results we obtained represent significant and natural extensions of what was known previously.
Ethylene-mediated signaling confers thermotolerance and regulates transcript levels of heat shock factors in rice seedlings under heat stress
Authors: Wu Yu-Sian , Yang Chin-Ying 
Published: September 2019

Abstract

Background
Agriculture is highly dependent on climate. Increases in temperature caused by global warming pose challenges for crop production. Heat stress induces oxidative damage to cell membranes and then causes cell death. Plants have developed various responses to elevated temperatures, including hormone signaling pathways and heat shock factors that elevate their thermotolerance. In response to heat stress, the gaseous hormone ethylene is produced through regulation of the expression of signaling-related genes to modulate resource allocation dynamics. For comprehensive understanding of the role of ethylene, this study used an ethylene precursor to analyze the ethylene signaling pathway involved in adjustment of the homeostasis of the antioxidant system and to evaluate heat shock factor expression in rice seedlings under heat stress.

Results
Levels of cell membrane oxidation and ion leakage were reduced in rice seedlings under heat treatment combined with ethylene precursor treatment, conferring enhanced thermotolerance. Reduction of the fresh weight and chlorophyll a/b ratio in rice seedlings was lower in rice seedlings under heat stress with ethylene precursor treatment than in those under heat stress only. Moreover, reduction of antioxidant response caused by heat stress was ameliorated by treatment with ethylene precursors such as catalase and total peroxidase. Quantitative reverse transcriptase-polymerase chain reaction showed higher expression levels of heat shock factors such as HSFA1a and HSFA2a, c, d, e, and f and ethylene-signaling-related genes such as ethylene insensitive 2, ethylene insensitive-like 1, and ethylene insensitive-like 2 in rice seedlings under heat stress with ethylene precursor treatment than in rice seedlings under heat stress only.

Conclusion
Ethylene-mediated signaling was involved in the reduction of oxidative damage, maintenance of chlorophyll content, and enhancement of thermotolerance in rice seedlings under heat stress. Furthermore, this study revealed heat shock factors and ethylene-signaling-related genes involved in complex network regulation that confers thermotolerance to rice seedlings.
Augmented intelligence in educational data mining
Authors: Toivonen Tapani , Jormanainen Ilkka , Tukiainen Markku 
Published: September 2019

AbstractEducational data mining (EDM) processes have shifted towards open-ended processes with visualizations and parameter and predictive model adjusting. Data and models in hyperdimensions can be visualized for end-users with popular data mining platforms such as Weka and RapidMiner. Multiple studies have shown how the adjusting and even creating the decision tree classifiers help EDM end-users to better comprehend the dataset and the context where the data has been collected. To harness the power of such open-ended approach in EDM, we introduce a novelAugmented Intelligencemethod and a cluster analysis algorithmNeural N-Tree. These contributions allow EDM end-users to analyze educational data in an iterative process where the knowledge discovery and the accuracy of the predictive model generated by the algorithm increases over time through the interactions between the models and the end-users. In contrast to other similar approaches, the key in our method is in the model adjusting and not in parameter tuning. We report a study where the potential EDM end-users clustered data from an education setting and interacted with Neural N-Tree models by following Augmented Intelligence method. The findings of the study suggest that the accuracy of the models evolve over time and especially the end-users who have a adequate level of knowledge from data mining benefit from the method. Moreover, the study indicates that the knowledge discovery is possible through AUI.
A new weighted injury severity scoring system: better predictive power for adult trauma mortality
Authors: Shi Junxin , Shen Jiabin , Zhu Motao , Wheeler Krista K. , Lu Bo , Kenney Brian , Nuss Kathryn E. , Xiang Henry 
Published: September 2019

Abstract

Background
An accurate injury severity measurement is essential in the evaluation of trauma care and in outcome research. The traditional Injury Severity Score (ISS) does not consider the differential risks of the Abbreviated Injury Scale (AIS) from different body regions, and the three AIS involved in the calculation of ISS are given equal weights. The objective of this study was to develop a weighted injury severity scoring (wISS) system for adult trauma patients with better predictive power than the traditional Injury Severity Score (ISS).

Methods
The 2007–2014 National Trauma Data Bank (NTDB) Research Datasets were used. We identified adult trauma patients from the NTDB and then randomly split it into a study sample and a test sample. Based on the association between mortality and the Abbreviated Injury Scale (AIS) from each of the six ISS body regions in the study sample, we evaluated 12 different sets of weights for the component AIS scores used in the calculation of ISS and selected one best set of weights. Discrimination (areas under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, concordance) and calibration were compared between the wISS and ISS.

Results
The areas under the receiver operating characteristic curves from the wISS and ISS are all 0.83, and 0.76 vs. 0.73 for patients with ISS = 16–74 and 0.68 vs. 0.53 for patients with ISS = 25–74. The wISS showed higher specificity, positive predictive value, negative predictive value, and concordance when they were compared at similar levels of sensitivity. The wISS had better calibration than the ISS.

Conclusions
By weighting the AIS from different body regions, the wISS had significantly better predictive power for mortality than the ISS, especially in critically injured adults.
Development of a kinematic GNSS-Acoustic positioning method based on a state-space model
Authors: Tomita Fumiaki , Kido Motoyuki , Honsho Chie , Matsui Ryo 
Published: September 2019

Abstract
GNSS-A (combination of Global Navigation Satellite System and Acoustic ranging) observations have provided important geophysical results, typically based on static GNSS-Acoustic positioning methods. Recently, continuous GNSS-Acoustic observations using a moored buoy have been attempted. Precise kinematic GNSS-Acoustic positioning is essential for these approaches. In this study, we developed a new kinematic GNSS-A positioning method using the extended Kalman filter (EKF). As for the observation model, parameters expressing underwater sound speed structure [nadir total delay (NTD) and underwater delay gradients] are defined in a similar manner to the satellite geodetic positioning. We then investigated the performance of the new method using both the synthetic and observational data. We also investigated the utility of a GNSS-Acoustic array geometry composed of multi-angled transponders for detection of vertical displacements. The synthetic tests successfully demonstrated that (1) the EKF-based GNSS-Acoustic positioning method can resolve the GNSS-Acoustic array displacements, as well as NTDs and underwater delay gradients, more precisely than those estimated by the conventional kinematic positioning methods and (2) precise detection of vertical displacements can be achieved using multi-angled transponders and EKF-based GNSS-Acoustic positioning. Analyses of the observational data also demonstrated superior performance of the EKF-based GNSS-Acoustic positioning method, when assuming a laterally stratified sound speed structure. Further, we found three superior aspects to the EKF-based array positioning method when using observational data: (1) robustness of the solutions when some transponders fail to respond, (2) precise detection for an abrupt vertical displacement, and (3) applicability to real-time positioning when sampling interval of the acoustic ranging is shorter than 30 min. The precision of the detection of abrupt steps, such as those caused by coseismic slips, is ~ 5 cm (1σ) using this method, an improvement on the precision of ~ 10 cm of conventional methods. Using the observational data, the underwater delay gradients and the horizontal array displacements could not be accurately solved even using the new method. This suggests that short-wavelength spatial heterogeneity exists in the actual ocean sound speed structure, which cannot be approximated using a simple horizontally graded sound speed structure.
Enhancing the thermostability and activity of uronate dehydrogenase from Agrobacterium tumefaciens LBA4404 by semi-rational engineering
Authors: Su Hui-Hui , Peng Fei , Xu Pei , Wu Xiao-Ling , Zong Min-Hua , Yang Ji-Guo , Lou Wen-Yong 
Published: September 2019

Abstract

Background
Glucaric acid, one of the aldaric acids, has been declared a “top value-added chemical from biomass”, and is especially important in the food and pharmaceutical industries. Biocatalytic production of glucaric acid from glucuronic acid is more environmentally friendly, efficient and economical than chemical synthesis. Uronate dehydrogenases (UDHs) are the key enzymes for the preparation of glucaric acid in this way, but the poor thermostability and low activity of UDH limit its industrial application. Therefore, improving the thermostability and activity of UDH, for example by semi-rational design, is a major research goal.

Results
In the present work, three UDHs were obtained from different Agrobacterium tumefaciens strains. The three UDHs have an approximate molecular weight of 32 kDa and all contain typically conserved UDH motifs. All three UDHs showed optimal activity within a pH range of 6.0–8.5 and at a temperature of 30 °C, but the UDH from A. tumefaciens (At) LBA4404 had a better catalytic efficiency than the other two UDHs (800 vs 600 and 530 s−1 mM−1). To further boost the catalytic performance of the UDH from AtLBA4404, site-directed mutagenesis based on semi-rational design was carried out. An A39P/H99Y/H234K triple mutant showed a 400-fold improvement in half-life at 59 °C, a 5 °C improvement in $$ {\text{T}}_{ 5 0}^{ 1 0} $$

T

50

10

value and a 2.5-fold improvement in specific activity at 30 °C compared to wild-type UDH.

Conclusions
In this study, we successfully obtained a triple mutant (A39P/H99Y/H234K) with simultaneously enhanced activity and thermostability, which provides a novel alternative for the industrial production of glucaric acid from glucuronic acid.
A EEG-based emotion recognition model with rhythm and time characteristics
Authors: Yan Jianzhuo , Chen Shangbin , Deng Sinuo 
Published: September 2019

Abstract
As an advanced function of the human brain, emotion has a significant influence on human studies, works, and other aspects of life. Artificial Intelligence has played an important role in recognizing human emotion correctly. EEG-based emotion recognition (ER), one application of Brain Computer Interface (BCI), is becoming more popular in recent years. However, due to the ambiguity of human emotions and the complexity of EEG signals, the EEG-ER system which can recognize emotions with high accuracy is not easy to achieve. Based on the time scale, this paper chooses the recurrent neural network as the breakthrough point of the screening model. According to the rhythmic characteristics and temporal memory characteristics of EEG, this research proposes a Rhythmic Time EEG Emotion Recognition Model (RT-ERM) based on the valence and arousal of Long–Short-Term Memory Network (LSTM). By applying this model, the classification results of different rhythms and time scales are different. The optimal rhythm and time scale of the RT-ERM model are obtained through the results of the classification accuracy of different rhythms and different time scales. Then, the classification of emotional EEG is carried out by the best time scales corresponding to different rhythms. Finally, by comparing with other existing emotional EEG classification methods, it is found that the rhythm and time scale of the model can contribute to the accuracy of RT-ERM.
“Who’s got the power?”: A critical examination of the anti-bias curriculum
Authors: Escayg Kerry-Ann 
Published: September 2019

Abstract
Ample research data indicate that young children recognize racial characteristics and subsequently exhibit both positive and negative racial attitudes toward their own and other racial groups. In the early childhood field, educators commonly adopt an anti-bias/multicultural curriculum to address such issues with young children and—with rare exceptions—such methods are subject to ongoing endorsement in the scholarly literature. This article, however, offers a more comprehensive critique of the anti-bias curriculum, including an analysis of the conceptual frameworks underpinning several of the associated teaching strategies. In addition, the present article illustrates how the anti-bias curriculum, though presented as congruent with the empirical evidence with respect to the education of young children and race, departs considerably from these data. Furthermore, the curricula under scrutiny fail to engage young children in critical discussions and classroom practices centering on: (i) power relations; (ii) racism; (iii) whiteness; and (iv) white privilege. This critique concludes with a preliminary conceptualization of anti-racism in early childhood education.
The indicative meaning calculator – quantification of paleo sea-level relationships by using global wave and tide datasets
Authors: Lorscheid Thomas , Rovere Alessio 
Published: September 2019

Abstract
The study of past sea levels relies largely on the interpretation and quantification of sea-level indicators. These are fossil coastal landforms, bioconstructions or deposits that have a quantifiable relation to paleo sea level (called the indicative meaning) and can be assigned an age of formation. The calculation of the indicative meaning should always rely on the quantitative comparison between the paleo sea-level indicator and the elevational range of the same feature in the modern environment with respect to modern sea level. This may prove difficult to quantify when no site-specific data is available, for example when compiling databases with large geographic scope. In this paper, we provide a method to quantify the indicative meaning of sea-level indicators using simple hydro- and morphodynamic equations with inputs from global wave and tide datasets. We apply and compare our approach exemplary to data published in a relative sea-level database on the Marine Isotope Stage 5e highstand and show how this approach can help in estimating the indicative meaning if no site-specific data on the modern analog is available. For the easier usability of the described approach in this paper, we also present a stand-alone Java-app (IMCalc), which can be used as a calculator of the indicative meaning.
How to activate students’ natural desire to test themselves
Authors: Vaughn Kalif E. , Kornell Nate 
Published: September 2019

AbstractTesting oneself (i.e., doing retrieval practice) is an effective way to study. We attempted to make learners choose to test themselves more often. In Experiment 1, participants were asked how they wanted to study and were given four options: retrieval with no hint (e.g., idea: ______), a two-letter hint (e.g., idea: s____r), a four-letter hint (e.g., idea: se__er), or a presentation trial (e.g., idea: seeker). They tested themselves on the majority of trials. In Experiment 2, when the hint options were removed, they chose restudy rather than pure test on the majority of trials. These findings show that people prefer self-testing over restudy as long as they can get the answer right on the test. However, we would not recommend hints if they impaired learning compared to pure testing. Experiment 3 showed that this was not the case; the three retrieval conditions from Experiment 1 led to equivalent amounts of learning, and all three outperformed the pure presentation condition. We used different materials in Experiment 4 and found that the hints made retrieval slightly less beneficial when the hints made it possible to guess the answers without thinking back to the study phase (e.g., whip: pu__sh). In summary, hints catalyzed people’s intuitive desire to self-test, without any downside for learning, thus making their self-regulated study more enjoyable and effective.
The effect of statement type and repetition on deception detection
Authors: Cash Daniella K. , Dianiska Rachel E. , Lane Sean M. 
Published: September 2019

Abstract

Background
Deception is a prevalent component of human interaction. However, meta-analyses suggest that discriminating between truthful and deceptive statements is a very arduous task and accuracy on these judgments is at chance levels. To complicate matters further, individuals tell different types of lies. The current studies examined how an individual’s ability to accurately discriminate between truthful and deceptive statements is affected by the way truths and lies are conveyed. Participants judged the veracity of statements given by speakers who told truths or lies about a performed action by describing that action or denying that it had occurred. Additionally, these statements also differed with regard to how often the lie had been repeated (i.e., practiced), either once or thrice.

Results
The results were largely in line with the prevailing notion that it is difficult to successfully differentiate between truthful and deceptive statements, but also showed that performance was moderated by statement type and repetition. The results revealed that participants were more accurate in discriminating unrepeated descriptions than repeated descriptions, but this difference was not seen for denial statements. Additionally, participants were more likely to believe practiced (repeated) statements, both truthful and deceptive.

Conclusion
The results show that repeated statements as well as shorter denials can increase the difficulty of differentiating truthful from deceptive statements. Additionally, these findings suggest that truthful statements also benefit from repetition with regard to enhancing their believability.
Preconception care in mental health services: planning for a better future
Authors: Catalao Raquel , Mann Sue , Wilson Claire , Howard Louise M. 
Published: September 2019

SummaryIt is increasingly recognised that the preconception period is a window of opportunity to intervene to improve outcomes for women and the next generation. The importance of preconception mental health and comorbidity problems has not traditionally been taken into account by policy makers or mental health service providers. We argue that by addressing preconception physical and mental health in men and women, medical health professionals could improve health outcomes across the whole life course.