bluuebunny/crossref_metadata_2025_split huggingface dataset:
Leaf morpho-physiological comparison between native and non-native plant species in a Mediterranean island
Authors: Abdallah Mohamad , Douthe Cyril , Flexas Jaume 
Published: April 2022

AbstractIslands tend to be more prone to plant invasions than mainland regions, with the Mediterranean ones not being an exception. So far, a large number of studies on comparing leaf morphological and physiological traits between native and non-native plants in Mediterranean environments have been performed, although none of them on Mediterranean islands. To fill this gap, this study focuses on 14 plant species grown in a controlled growth chamber in the absence of stress. The goal was (1) to differentiate leaf morpho-physiological traits between native and non-native plants on a Mediterranean island and (2) to deepen in the underlying causes of the differential photosynthetic traits displayed by non-native species. Results showed that in Mediterranean islands, non-native plant species show on average larger values of net CO2 assimilation, stomatal conductance (gm), photosynthetic nitrogen-use efficiency, among others, and lower leaf mass per area (LMA) and leaf thickness, compared to the native species. Among the assessed traits, this study reports for the first time larger gm, and lower mesophyll conductance limitation in non-native species, which seems to be linked to their lower LMA. These novel traits need to be added to the ‘leaf physiological trait invasive syndrome’. It was also found that on a Mediterranean island, native and non-native species are placed on opposite sides of the leaf economics spectrum, with non-native species being placed on the ‘‘fast-return’’ end. In conclusion, this study demonstrates that non-native species inhabiting a Mediterranean island possess distinct leaf morphological and physiological traits compared to co-occurring native species, at least during the favorable growth season, which increases the chances of a successful invasion.
On $$\alpha $$-points of q-analogs of the Fano plane
Authors: Kiermaier Michael 
Published: April 2022

AbstractArguably, the most important open problem in the theory of q-analogs of designs is the question regarding the existence of a q-analog D of the Fano plane. As of today, it remains undecided for every single prime power order q of the base field. A point P is called an $$\alpha $$
α
-point of D if the derived design of D in P is a geometric spread. In 1996, Simon Thomas has shown that there always exists a non-$$\alpha $$
α
-point. For the binary case $$q = 2$$

q
=
2

, Olof Heden and Papa Sissokho have improved this result in 2016 by showing that the non-$$\alpha $$
α
-points must form a blocking set with respect to the hyperplanes. In this article, we show that a hyperplane consisting only of $$\alpha $$
α
-points implies the existence of a partition of the symplectic generalized quadrangle W(q) into spreads. As a consequence, the statement of Heden and Sissokho is generalized to all primes q and all even values of q.
The Latent Structure of Child and Adolescent Psychopathology and its Association with Different Forms of Trauma and Suicidality and Self-Harm
Authors: Hyland Philip , Karatzias Thanos , Ford Julian D. , Fox Robert , Spinazzola Joseph 
Published: April 2022

AbstractThe Hierarchical Taxonomy of Psychopathology (HiTOP) is a multidimensional and hierarchical model of the latent structure of psychopathology. While HiTOP has received much support in child/adolescent community samples, fewer studies have assessed this model in clinical samples of children/adolescents. Here, we modelled the latent structure of 45 symptoms of psychopathology from a clinical sample of children/adolescents and assessed how dimensions of psychopathology were related to specific forms of trauma and suicidality/self-harm. Clinician-derived assessments were obtained from 507 people aged 7–18 years. Confirmatory factor analysis was used to determine the optimal fitting model, and structural equation modelling was used to estimate associations with trauma exposure and suicidality/self-harm. The best fitting model(s) included five first-order factors reflecting Fear, Distress, Externalizing, Thought Disorder, and Traumatic Stress, with a higher-order general factor (p) accounting for the covariation between these factors. Unique associations were identified between specific forms of trauma and each dimension of psychopathology. p was strongly associated with suicidality/self-harm, and of the first-order factors, Distress was most strongly associated with suicidality/self-harm. Findings support the predictions of HiTOP that the latent structure of child/adolescent psychopathology can be effectively described by a multidimensional and hierarchal model. Moreover, we found tentative evidence for a unique dimension of Traumatic Stress psychopathology. Our findings also highlight the unique associations between specific forms of early life trauma and specific dimensions of psychopathology, and the importance of Distress related psychopathology for suicidality/self-harm in children and adolescents.
A boosting first-hitting-time model for survival analysis in high-dimensional settings
Authors: De Bin Riccardo , Stikbakke Vegard Grødem 
Published: April 2022

AbstractIn this paper we propose a boosting algorithm to extend the applicability of a first hitting time model to high-dimensional frameworks. Based on an underlying stochastic process, first hitting time models do not require the proportional hazards assumption, hardly verifiable in the high-dimensional context, and represent a valid parametric alternative to the Cox model for modelling time-to-event responses. First hitting time models also offer a natural way to integrate low-dimensional clinical and high-dimensional molecular information in a prediction model, that avoids complicated weighting schemes typical of current methods. The performance of our novel boosting algorithm is illustrated in three real data examples.
Insights from the national maternal and Child Health Workforce Development Center on Title V Teams’ collaborative readiness and goal accomplishment
Authors: Wells Rebecca , Coffey Alexandria M. , Mullenix Amy , Simon Jessica , Lich Kristen Hassmiller 
Published: April 2022

Abstract
Purpose
State Title V programs collaborate with diverse partners to improve maternal and child health. Since 2014, the National Maternal and Child Health Workforce Development Center has trained Title V leaders in facilitating system change. This article describes aspects of initial collaborative readiness differentiating state and jurisdiction teams that later reported meeting their goals to greater or lesser degrees.

Description
We used quantitative data from initial team leader reports to characterize readiness to collaborate with external partners, and their responses twelve months later to a prompt about how fully they had accomplished their goals. In addition, we coded excerpts from team leader accounts six and twelve months into their work with the Center, and retrospective coach perspectives, to identify collaborative readiness patterns.

Assessment
Teams whose leaders reported higher goal accomplishment twelve months after beginning work with the Center had initially reported higher levels of collaboration with key partners. Our analyses suggest that such teams were also better able to use their cohort experience with the Center to improve collaboration, including information sharing with external stakeholders. Challenges working with Medicaid were reported both by teams with more and less goal accomplishment.

Conclusions
Title V teams with lower levels of initial collaborative readiness may benefit from additional support in skill development, connections to key partners, and convening power. Given the crucial and increasing role of Medicaid in maternal and child health systems, more attention may be warranted to supporting all Title V programs in partnering with this funder.
Identifying health-related quality of life cut-off scores that indicate the need for supportive care in young adults with cancer
Authors: Lidington Emma , Giesinger Johannes M. , Janssen Silvie H. M. , Tang Suzanne , Beardsworth Sam , Darlington Anne-Sophie , Starling Naureen , Szucs Zoltan , Gonzalez Michael , Sharma Anand , Sirohi Bhawna , van der Graaf Winette T. A. , Husson Olga 
Published: April 2022

Abstract
Purpose
Using patient-reported outcomes in routine cancer care may improve health outcomes. However, a lack of information about which scores are problematic in specific populations can impede use. To facilitate interpretation of the European Organisation for Research and Treatment of Cancer Core Questionnaire (EORTC QLQ-C30), we identified cut-off scores that indicate need for support by comparing each scale to relevant items from the Supportive Care Needs Survey (SCNS-LF59) in a young adult (YA) population.

Methods
We conducted a cross-sectional survey amongst YAs with cancer ages 25–39 at diagnosis. Participants completed the EORTC QLQ-C30 and SCNS-LF59. Patient, clinician and research experts matched supportive care needs from the SCNS-LF59 to quality of life domains of the EORTC QLQ-C30. We evaluated the EORTC QLQ-C30 domain score’s ability to detect patients with need using receiver operator characteristic (ROC) analysis, calculating the area under the ROC curve and sensitivity and specificity for selected cut-offs. Cut-offs were chosen by maximising Youden’s J statistic and ensuring sensitivity passed 0.70. Sensitivity analyses were conducted to examine the variability of the cut-off scores by treatment status.

Results
Three hundred and forty-seven YAs took part in the survey. Six experts matched SCNS-LF59 items to ten EORTC QLQ-C30 domains. The AUC ranged from 0.78 to 0.87. Cut-offs selected ranged from 8 (Nausea and Vomiting and Pain) to 97 (Physical Functioning). All had adequate sensitivity (above 0.70) except the Financial Difficulties scale (0.64). Specificity ranged from 0.61 to 0.88. Four of the cut-off scores differed by treatment status.

Conclusion
Cut-offs with adequate sensitivity were calculated for nine EORTC QLQ-C30 scales for use with YAs with cancer. Cut-offs are key to interpretability and use of the EORTC QLQ-C30 in routine care to identify patients with supportive care need.
Xamã : Optical character recognition for multi-domain model management
Authors: Torres Weslley , van den Brand Mark G. J. , Serebrenik Alexander 
Published: April 2022

AbstractThe development of systems following model-driven engineering can include models from different domains. For example, to develop a mechatronic component one might need to combine expertise about mechanics, electronics, and software. Although these models belong to different domains, the changes in one model can affect other models causing inconsistencies in the entire system. Only few tools, however, support management of models from different domains. Indeed, these models are created using different modeling notations and it is not plausible to use a multitude of parsers geared toward each and every modeling notation. Therefore, to ensure maintenance of multi-domain systems, we need a uniform approach that would be independent from the peculiarities of the notation. Notation independence implies that such a uniform approach can only be based on elements commonly present in models of different domains, i.e., text, boxes, and lines. In this study, we investigate the suitability of optical character recognition (OCR) as a basis for such a uniformed approach. We select graphical models from various domains that typically combine textual and graphical elements. We start by analyzing the performance of Google Cloud Vision and Microsoft Cognitive Services, two off-the-shelf OCR services. Google Cloud Vision performed better than Microsoft Cognitive Services being able to detect text of 70% of model elements. Errors made by Google Cloud Vision are due to absence of support for text common in engineering formulas, e.g., Greek letters, equations, and subscripts. We identified the multi-line text error as one of the main issues of using OCR to recognize textual elements in models from different domains. This error happens when OCR misinterprets one textual element as two separate elements. To address the multi-line text error, we build Xamã on top of Google Cloud Vision. Xamã includes two approaches to identify whether the elements are positioned on a single line or multiple lines, and merge those identified as positioned on multiples lines. With and without shape detection, Xamã correctly identified 956 and 905 elements, respectively, out of 1171. Additionally, we compared the accuracy of Xamã and state-of-the-art tool img2UML, and we observe that Xamã outperformed img2UML in both precision and recall, being able to recognize 433 out of 614 textual elements as opposed to 171 by img2UML.
Facile synthesis of mesoporous nano Ni/NiO and its synergistic role as super adsorbent and photocatalyst under sunlight irradiation
Authors: Mohamed Sahar K. , Elhgrasi Amira M. , Ali Omnia I. 
Published: April 2022

AbstractTailoring a material that has a synergistic role as an adsorbent and a photocatalyst for environmental application is an attractive field for research. This article presents a study of facile synthesis of NiO and Ni/NiO with a synergistic role as super adsorbents in the lake of light and photocatalysts under light irradiation. Nano flower-like mesoporous NiO and Ni/NiO were synthesized by the co-precipitation method. XRD, SEM, EDAX, XPS, BET, and DR/UV–Vis spectroscopy techniques were employed for samples’ analysis. The point of zero surface charge of prepared samples was detected by the batch equilibrium method. The adsorption efficiency was investigated in the absence of light using aniline blue as a pollutant model dye. The synergistic effect as an adsorbent and a photocatalyst was investigated under UV and sunlight irradiation. Different parameters affecting the adsorption in the dark have been optimized. The results showed that in the absence of light, the prepared samples are super adsorbents with a maximum adsorption capacity ranging from 210 to 230 mg g−1 and a removal % ranging from 95 to 100% within 2 h. Under UV or sunlight irradiation, the adsorbent/photocatalyst attained a dye removal % of 99.8% within 30 min. The adsorption data matched the pseudo-second-order model, and the equilibrium adsorption data showed compatibility with Langmuir model. The findings of experiments revealed that the adsorption is spontaneous, exothermic, and results in less entropy. Under sunlight irradiation, the dye removal efficiency increased by 19% in the case of Ni/NiO hybrid; it showed a removal efficiency of 99.5% within 30 min under sunlight irradiation versus 80% after 120 min in the dark.
Levothyroxine treatment and gastric juice pH in humans: the proof of concept
Authors: Virili Camilla , Bruno Giovanni , Santaguida Maria Giulia , Gargano Lucilla , Stramazzo Ilaria , De Vito Corrado , Cicenia Alessia , Scalese Giulia , Porowska Barbara , Severi Carola , Centanni Marco 
Published: April 2022

Abstract
Purpose
Despite the absorption of oral thyroxine (T4) occurs in the small bowel, several patients with gastric disorders show an increased need for T4. In vitro evidence suggested that medium pH variations interfere with T4 dissolution. This study was aimed at finding the proof of concept of a direct relationship between the minimal effective dose of T4 and the actual gastric juice pH.

Patients and methods
Among 311 consecutively thyroxine-treated patients, 61 bearing Hashimoto’s thyroiditis (52 F/9 M; median age = 51 years) who complained persistent dyspepsia and/or upper abdominal symptoms following a noninvasive workup for gastrointestinal disorders, underwent EGDS with multiple biopsies and gastric juice pH measurement. All patients accepted to take thyroxine in fasting conditions, abstaining from eating or drinking for one hour.

Results
Thyroxine requirement increased along with the rising gastric pH (ρ = 0.4229; p = 0.0007). A multivariate analysis revealed that gastric pH was, beside body mass index, the far more important independent variable in determining the effective dose of T4 (p = 0.001). The ROC curve revealed that the pH threshold for an increased thyroxine requirement was at 2.28, being the AUC by 78%. Subdividing patients by the histologic findings, it appeared a significant increase (p = 0.0025) along with the progressive damage of gastric mucosa.

Conclusion
The in vivo measurement of gastric pH highlighted its key role in determining the minimal effective dose of oral T4 and may explain the interference of food, of some drugs and gut disorders on levothyroxine treatment
On control measures of multimeasures
Authors: Rodríguez José 
Published: April 2022

AbstractLet M be a multimeasure defined on a $$\sigma $$
σ
-algebra and taking values in the family of bounded non-empty subsets of a Banach space X. We prove that M admits a control measure whenever X contains no subspace isomorphic to $$c_0(\omega _1)$$

c
0

(

ω
1

)

. The additional assumption on X is shown to be essential.
A new method for image processing using generalized linguistic neutrosophic cubic aggregation operator
Authors: Kaur Gagandeep , Garg Harish 
Published: April 2022

AbstractImage processing is a technique of scrutinizing an image and extricating important information. Indecisive situations are generally undergone when the picture processes with profuse noise. Neutrosophic set (NS), a part of neutrosophy theory, studies the scope of neutralities and is essential to reasoning with incomplete and uncertain information. However, the linguistic neutrosophic cubic set (LNCS) is one of the extensions of the NS. In LNCS, each element is characterized by the interval-valued and single-valued neutrosophic numbers to handle the data uncertainties. Keeping these features in mind, we apply LNCS for image processing after defining their aggregation operators and operations. In this study, noisy grey-scale images were transformed into the LNCS domain using three membership degrees, then aggregated using aggregation operators. The proposed method clarifies the noise in the Lena image and three other test images. It has justified the utilization of operators based on visual clarity obtained. Suitable comparison analysis and efficiency testing is performed on the proposed theory by considering noise types, such as Gaussian, Poisson, and Speckle. In addition, we have also compared the computational efficiency of our proposed method with existing ones. The results show that our approach consumes less memory and executes quicker than the existing methods. A decision-maker can select a more effective operator to segment the images more effectively using the obtained results.
Impact of Cryopreservation and Freeze-Thawing on Therapeutic Properties of Mesenchymal Stromal/Stem Cells and Other Common Cellular Therapeutics
Authors: Cottle Chasen , Porter Amanda Paige , Lipat Ariel , Turner-Lyles Caitlin , Nguyen Jimmy , Moll Guido , Chinnadurai Raghavan 
Published: April 2022

Abstract

Purpose of Review

Cryopreservation and its associated freezing and thawing procedures–short “freeze-thawing”–are among the final steps in economically viable manufacturing and clinical application of diverse cellular therapeutics. Translation from preclinical proof-of-concept studies to larger clinical trials has indicated that these processes may potentially present an Achilles heel to optimal cell product safety and particularly efficacy in clinical trials and routine use.

Recent Findings

We review the current state of the literature on how cryopreservation of cellular therapies has evolved and how the application of this technique to different cell types is interlinked with their ability to engraft and function upon transfer in vivo, in particular for hematopoietic stem and progenitor cells (HSPCs), their progeny, and therapeutic cell products derived thereof. We also discuss pros and cons how this may differ for non-hematopoietic mesenchymal stromal/stem cell (MSC) therapeutics. We present different avenues that may be crucial for cell therapy optimization, both, for hematopoietic (e.g., effector, regulatory, and chimeric antigen receptor (CAR)-modified T and NK cell based products) and for non-hematopoietic products, such as MSCs and induced pluripotent stem cells (iPSCs), to achieve optimal viability, recovery, effective cell dose, and functionality of the cryorecovered cells.

Summary

Targeted research into optimizing the cryopreservation and freeze-thawing routines and the adjunct manufacturing process design may provide crucial advantages to increase both the safety and efficacy of cellular therapeutics in clinical use and to enable effective market deployment strategies to become economically viable and sustainable medicines.
Bayesian Inference on the Bimodality of the Generalized von Mises Distribution
Authors: Gatto Riccardo , Salvador Sara 
Published: April 2022

AbstractThis article introduces Bayesian inference on the bimodality of the generalized von Mises (GvM) distribution for planar directions (Gatto and Jammalamadaka in Stat Methodol 4(3):341–353, 2007). The GvM distribution is a flexible model that can be axial symmetric or asymmetric, unimodal or bimodal. Two inferential approaches are analysed. The first is the test of null hypothesis of bimodality and Bayes factors are obtained. The second approach provides a two-dimensional highest posterior density (HPD) credible set for two parameters relevant to bimodality. Based on the identification of the two-dimensional parametric region associated with bimodality, the inclusion of the HPD credible set in that region allows us to infer on the bimodality of the underlying GvM distribution. A particular implementation of the Metropolis–Hastings algorithm allows for the computation of the Bayes factors and the HPD credible sets. A Monte Carlo study reveals that, whenever the samples are generated under a bimodal GvM, the Bayes factors and the HPD credible sets do clearly confirm the underlying bimodality.
Deep Optimisation: Transitioning the Scale of Evolutionary Search by Inducing and Searching in Deep Representations
Authors: Caldwell Jamie , Knowles Joshua , Thies Christoph , Kubacki Filip , Watson Richard 
Published: April 2022

AbstractWe investigate the optimisation capabilities of an algorithm inspired by the Evolutionary Transitions in Individuality. In these transitions, the natural evolutionary process is repeatedly rescaled through successive levels of biological organisation. Each transition creates new higher-level evolutionary units that combine multiple units from the level below. We call the algorithm Deep Optimisation (DO) to recognise both its use of deep learning methods and the multi-level rescaling of biological evolutionary processes. The evolutionary model used in DO is a simple hill-climber, but, as higher-level representations are learned, the hill-climbing process is repeatedly rescaled to operate in successively higher-level representations. The transition process is based on a deep learning neural network (NN), specifically a deep auto-encoder. Our experiments with DO start with a study using the NP-hard problem, multiple knapsack (MKP). Comparing with state-of-the-art model-building optimisation algorithms (MBOAs), we show that DO finds better solutions to MKP instances and does so without using a problem-specific repair operator. A second, much more in-depth investigation uses a class of configurable problems to understand more precisely the distinct problem characteristics that DO can solve that other MBOAs cannot. Specifically, we observe a polynomial vs exponential scaling distinction where DO is the only algorithm to show polynomial scaling for all problems. We also demonstrate that some problem characteristics need a deep network in DO. In sum, our findings suggest that the use of deep learning principles have significant untapped potential in combinatorial optimisation. Moreover, we argue that natural evolution could be implementing something like DO, and the evolutionary transitions in individuality are the observable result.