bluuebunny/crossref_metadata_2025 huggingface dataset:
Progesterone receptor membrane component 2 regulates the neuronal activity and participates in epileptic seizures in experimental mice
Authors: Yang Xiaoyan , Lv Wenbo , Yang Yong , Yang Juan , Zhang Haiqing , Xu Zucai
Published: January 2023

It was found the expression of progesterone receptor membrane component 2 (PGRMC2) in the histone of epileptic mice was lower than that of normal mice. In this study, we found by the immunofluorescence technique, PGRMC2 was expressed in both astrocytes and neurons of the mouse hippocampus. In addition, the seizure latency and seizure grade of mice in each group were observed after stereotactic injection of the PGRMC2 knockdown virus, PGRMC2 overexpression lentivirus, and related null virus into the hippocampus of mice. It was found that the seizure latency of mice in the PTZ + siPGRMC2 group was prolonged compared with the null virus group. The seizure latency was shortened in the PTZ + PGRMC2 group. The number of grade IV and above seizures in the PTZ + siPGRMC2 group was significantly reduced, while the number of grade IV and above seizures in the PTZ + PGRMC2 group was significantly increased. It was found that the nerve cells in the PTZ + siPGRMC2 group were still intact. In the PTZ + PGRMC2 group, the neural cells were damaged, the intercellular space was widened, and the number of cells was reduced. These findings support that PGRMC2 may be involved in epileptic seizures.
Use of artificial intelligence models for the reduction of nanoparticle size in the synthesis of ZnO
Authors: Martínez‐Vargas Blanca L , González Rodríguez Luis M , Pacheco‐Álvarez Martín , Peralta‐Hernández Juan M , Picos Alain
Published: January 2023

BACKGROUND

This study evaluates the effectiveness of an artificial intelligence (AI) model for predicting the best experimental conditions to reduce particle size during the synthesis of ZnO nanoparticles. Firstly, an artificial neural networks (ANN) was trained using 52 experimental data from the synthesis of ZnO nanoparticles. The selected input variables were temperature, experimental time, and NaOH concentration, and the output variable was nanoparticle size. The performance of the ANN was measured with the root mean square error and mean absolute percentage error, and the obtained values for the selected ANN were 0.67% and 9.87%, respectively. These values were calculated by using real and predicted values.

RESULTS

A genetic algorithm (GA) model was coupled with the ANN to find the best operational conditions for the reduced size of ZnO nanoparticles. According to the AI model, a temperature of 59 °C, an experimental time of 56 min, and a concentration of NaOH of 0.08 should be tested to obtain ZnO nanoparticles with 5.67 nm of diameter. After applying the conditions predicted by the model, ZnO nanoparticles with a mean diameter of 5.3 ± 0.4 nm were obtained. The results were confirmed by using several characterization methods, such as approximation of effective masses (5.3 nm), equation Debye–Scherrer (5.2 nm), and high‐resolution transmission electron microscope (HR‐TEM) selected micrograph (5.5 nm). The photocatalytic activity of the synthesized nanoparticles was evaluated using the synthetic dye thymol blue. The best discoloration efficiency was reached by the synthesized ZnO nanoparticles at 74%, while the commercial ZnO only achieved 58%.

CONCLUSION

According to the ANN‐GA model, it was possible to predict the experimental conditions needed to obtain ZnO nanoparticles with reduced sizes and excellent photocatalytic activity. © 2023 Society of Chemical Industry (SCI).
Diverging snowfall trends across months and elevation in the northeastern Italian Alps
Authors: Bertoldi Giacomo , Bozzoli Michele , Crespi Alice , Matiu Michael , Giovannini Lorenzo , Zardi Dino , Majone Bruno
Published: January 2023

Snowfall and snow accumulation play a crucial role in shaping ecosystems and human activities in the Alpine region. This resource is under threat as a consequence of the visible effects of global warming, and, therefore, it appears urgent to understand how snowfall trends have changed in time and space. In this context, we recovered data from over a hundred snowfall (HN) time series covering the period 1980–2020 over the mountain region of Trentino‐South Tyrol in the northeastern Italian Alps and analysed them to understand snowfall climatology in the region, recent trends and their dependence on elevation and timing of the season. Negative, although not always statistically significant, trends were found in the lowest elevation range (0–1,000 m a.s.l.) over the whole winter season, while some positive and even significant trends were found from January to March above 2,000 m a.s.l. The intermediate elevation range (1,000–2,000 m a.s.l.) exhibits a strong variability with no clear trend. Negative and statistically significant trends were found in April for all elevations. An attribution analysis was performed using precipitation (P), mean air temperature (TMEAN), and large‐scale synoptic descriptors, such as the North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO) indices. The analysis shows that, overall, P is the driver that best explains the snowfall trends, but, for low elevations, especially during mid‐winter, TMEAN is more relevant. Low elevations are facing a clear decrease in HN due to a significant increase in mean temperatures, while high elevations during mid‐winter display a slight increase in HN, associated with a general increase in precipitation. NAO and AO indices exhibit no significant correlations with HN, except at the lowest elevations and at the beginning of the season.
SeroTracker‐RoB: A decision rule‐based algorithm for reproducible risk of bias assessment of seroprevalence studies
Authors: Bobrovitz Niklas , Noël Kim , Li Zihan , Cao Christian , Deveaux Gabriel , Selemon Anabel , Clifton David A. , Yanes‐Lane Mercedes , Yan Tingting , Arora Rahul K.
Published: January 2023

Risk of bias (RoB) assessments are a core element of evidence synthesis but can be time consuming and subjective. We aimed to develop a decision rule‐based algorithm for RoB assessment of seroprevalence studies. We developed the SeroTracker‐RoB algorithm. The algorithm derives seven objective and two subjective critical appraisal items from the Joanna Briggs Institute Critical Appraisal Checklist for Prevalence studies and implements decision rules that determine study risk of bias based on the items. Decision rules were validated using the SeroTracker seroprevalence study database, which included non‐algorithmic RoB judgments from two reviewers. We quantified efficiency as the mean difference in time for the algorithmic and non‐algorithmic assessments of 80 randomly selected articles, coverage as the proportion of studies where the decision rules yielded an assessment, and reliability using intraclass correlations comparing algorithmic and non‐algorithmic assessments for 2070 articles. A set of decision rules with 61 branches was developed using responses to the nine critical appraisal items. The algorithmic approach was faster than non‐algorithmic assessment (mean reduction 2.32 min [SD 1.09] per article), classified 100% (n = 2070) of studies, and had good reliability compared to non‐algorithmic assessment (ICC 0.77, 95% CI 0.74–0.80). We built the SeroTracker‐RoB Excel Tool, which embeds this algorithm for use by other researchers. The SeroTracker‐RoB decision‐rule based algorithm was faster than non‐algorithmic assessment with complete coverage and good reliability. This algorithm enabled rapid, transparent, and reproducible RoB evaluations of seroprevalence studies and may support evidence synthesis efforts during future disease outbreaks. This decision rule‐based approach could be applied to other types of prevalence studies.
Long‐Term Follow‐Up of Non‐Enhancing Renal Masses on CEUS
Authors: Barr Richard G. , Cestone Angelo , Peterson Cynthia , De Silvestri Annalisa
Published: January 2023

Purpose

To determine the natural history and necessity of long‐term follow‐up of renal masses that do not demonstrate enhancement on contrast‐enhanced ultrasound (CEUS).

Methods

This retrospective single‐center study was approved by our local IRB and is HIPAA compliant. Exactly 405 patients with 620 non‐enhancing renal masses on CEUS from a previously reported study were followed for up to 10 years. Techniques and equipment are described in the original manuscript. Patient charts and imaging studies were reviewed for the change in features. There were 117 (18.6%) patients lost to follow‐up leading to 341 patients with 512 lesions. The lesion size, patient age, number of lesions per patient, and Bosniak class assigned at the initial examination was recorded.

Results

Mean patient age was 66 ± 12.6 years (range 17–95 years). Average time of follow‐up was 58.9 ± 41.7 months (range 1–207 months). There was a mean of 1.5 ± 1.0 lesions per patient (range 1–7 lesions). Lesion size was 24.9 ± 18.2 mm (range 3–161 mm). There were 276 (53.9%) patients with >5‐year follow‐up and 78 (15.2%) patients with >10‐year follow‐up. The probability of change within 5 years was 0% (95% CI: 0–0.37 per 100PY) and 10 years 0% (95% CI: 0.0–0.18 per 100PY). Two lesions (0.4%) resolved by 60 months. Five lesions (1.0%) decreased in size. Four lesions (0.8%) increased in size >20% during the follow‐up period but remained benign on subsequent imaging.

Conclusion

Any non‐enhancing renal mass on CEUS can be classified as benign.
Double‐anticorrosion ability of in‐situ superhydrophobic MgAl‐LDH coating with excellent stability of the corrosion resistance on magnesium alloy AZ31
Authors: Han Xing , Wang Yongqin , Hu Jia , Xiao Tianbing , Li Jianjun
Published: January 2023

We reported the realization of superhydrophobic layered double hydroxide (LDH) coating with the double‐anticorrosion mechanism on magnesium alloys. This coating was prepared via in‐situ growth of LDHs on the etched AZ31 alloy and the modification was caused by 1H, 1H, 2H, 2H‐perfluorooctyltrimethoxysilane. The water contact angle on the coating was as large as 161°, possessing the two‐scale rough structure consisting of microislands and LDH crystal nanosheets. The excellent corrosion resistance properties of the superhydrophobic LDH coating can be attributed to the double‐anticorrosion mechanism associated with LDH coating and superhydrophobic structure. In addition to the active protection of LDH coating, the passive protection of superhydrophobic coating can suppress the occurrence of ion‐exchange reactions, leading to excellent corrosion resistance stability.
Ecosystem Microbiome Science
Authors: Zhu Yong‐Guan , Zhu Dong , Rillig Matthias C. , Yang Yunfeng , Chu Haiyan , Chen Qing‐Lin , Penuelas Josep , Cui Hui‐Ling , Gillings Michael
Published: January 2023

The microbiome contributes to multiple ecosystem functions and services through its interactions with a complex environment and other organisms. To date, however, most microbiome studies have been carried out on individual hosts or particular environmental compartments. This greatly limits a comprehensive understanding of the processes and functions performed by the microbiome and its dynamics at an ecosystem level. We propose that the theory and tools of ecosystem ecology be used to investigate the connectivity of microorganisms and their interactions with the biotic and abiotic environment within entire ecosystems and to examine their contributions to ecosystem services. Impacts of natural and anthropogenic stressors on ecosystems will likely cause cascading effects on the microbiome and lead to unpredictable outcomes, such as outbreaks of emerging infectious diseases or changes in mutualistic interactions. Despite enormous advances in microbial ecology, we are yet to study microbiomes of ecosystems as a whole. Doing so would establish a new framework for microbiome study: Ecosystem Microbiome Science. The advent and application of molecular and genomic technologies, together with data science and modeling, will accelerate progress in this field.
Vinblastine pharmacokinetics in mouse, dog, and human in the context of a physiologically based model incorporating tissue‐specific drug binding, transport, and metabolism
Authors: Witta Sandra , Collins Keagan P. , Ramirez Dominique A. , Mannheimer Joshua D. , Wittenburg Luke A. , Gustafson Daniel L.
Published: January 2023

Vinblastine (VBL) is a vinca alkaloid‐class cytotoxic chemotherapeutic that causes microtubule disruption and is typically used to treat hematologic malignancies. VBL is characterized by a narrow therapeutic index, with key dose‐limiting toxicities being myelosuppression and neurotoxicity. Pharmacokinetics (PK) of VBL is primarily driven by ABCB1‐mediated efflux and CYP3A4 metabolism, creating potential for drug–drug interaction. To characterize sources of variability in VBL PK, we developed a physiologically based pharmacokinetic (PBPK) model in Mdr1a/b(−/−) knockout and wild‐type mice by incorporating key drivers of PK, including ABCB1 efflux, CYP3A4 metabolism, and tissue‐specific tubulin binding, and scaled this model to accurately simulate VBL PK in humans and pet dogs. To investigate the capability of the model to capture interindividual variability in clinical data, virtual populations of humans and pet dogs were generated through Monte Carlo simulation of physiologic and biochemical parameters and compared to the clinical PK data. This model provides a foundation for predictive modeling of VBL PK. The base PBPK model can be further improved with supplemental experimental data identifying drug–drug interactions, ABCB1 polymorphisms and expression, and other sources of physiologic or metabolic variability.
COVID‐19 vaccine wastage: A challenge to achieving herd immunity in Nigeria
Authors: Musa Shuaibu Saidu , Ibrahim Adamu Muhammad , Hamid Muhammad Rahima , Obia Hope Jonah , Buwa Garba Mohammed
Published: January 2023

The emergence of the COVID‐19 pandemic has overburdened many health‐care systems in the world, particularly in Nigeria and other African countries with fragile public health system. Since the emergence of the pandemic, Nigeria has been struggling to restore the impact on its health‐care system as the country keeps recording a growing number of cases and deaths. Vaccination has been the most efficient strategy towards curbing the COVID‐19 pandemic, particularly in countries like Nigeria where preventive measures were poorly strategised or implemented. The country was able to secure some doses of the COVID‐19 vaccine through donations, but concerns have been raised as up to 1 million doses of the vaccine were wasted due to delays in importations and poor cold chain management system. This wastage can pose a challenge to achieving COVID‐19 herd immunity in Nigeria. The causative factors of the vaccine wastage in Nigeria must therefore be tackled in order to effectively curb the COVID‐19 outbreak and consequently achieve herd immunity through massive vaccination. The government in collaboration with World Health Organisation and Africa Centre for Disease Control should facilitate and fast track the safe delivery of the vaccines to Nigeria. Misconceptions about COVID‐19 and its vaccine should be tackled to encourage the vaccine acceptance. The challenges faced by the vaccine supply chain system should be properly addressed by providing adequate funding and security, improved power supply, good vaccine infrastructure and improved vaccine data management in order to facilitate the safe and timely distribution of adequate vaccines across the country.
Ensemble based methods for leapfrog integration in the simplified parameterizations, primitive‐equation dynamics model
Authors: Nino‐Ruiz Elias D. , Consuegra Ortega Randy S. , Lucini Magdalena
Published: January 2023

This paper presents efficient and practical implementations of sequential data assimilation methods for the Simplified Parameterizations, primitive‐Equation DYnamics (SPEEDY) Model, a well‐known numerical model, into the data assimilation community for climate prediction. In the SPEEDY model, the time evolution of dynamics is performed via the second‐order Leapfrog integration scheme; this time integrator relies on two steps: the position and the velocity. The computational implementation of SPEEDY blends the time integrator and the spatial discretization of dynamics to accelerate algebraic computations. Thus, there is no access to the right‐hand side function of the ordinary differential equations governing the time evolution of model dynamics. Consequently, the SPEEDY model is often treated as a black box wherein positions and velocities work as inputs and outputs. Since observations in operational data assimilation only match position states, we can exploit augmented vector states to propagate analysis innovations from positions to velocities. For this purpose, we formulate three variants of ensemble‐based filters and perform numerical experiments to assess their accuracies. We consider two scenarios for the experiments: an ideal case wherein positions and velocities can be observed and a more realistic one wherein measurements are only accessible for position states. Besides, we discuss the effects of the ensemble size on the accuracies of our formulations and, even more, the typical case in which velocities are not updated across assimilation steps. The results reveal that all filter formulations' accuracies remain the same in terms of Root‐Mean‐Square‐Error by neglecting observations from velocities (a realistic scenario) even for cases wherein the number of measurements decreases to 6% of model components. Furthermore, for all discussed filter implementations, the propagation of analysis increments from position to velocities improves up to 100% the performance of filter implementations wherein velocities are not updated, a typical operational scenario.
Event‐triggered asynchronous distributed model predictive control with variable prediction horizon for nonlinear systems
Authors: Wang Pengbiao , Ren Xuemei , Zheng Dongdong
Published: January 2023

In this article, we develop an event‐triggered asynchronous distributed model predictive control (ETADMPC) algorithm with the adaptive prediction horizon for distributed nonlinear systems with weakly dynamics couplings, bounded disturbances, and system constraints. First, we focus on designing a novel adaptive event‐triggered mechanism with Zeno‐free phenomenons in order to reduce computational burdens, whose triggering threshold can adapt to the real‐time changes of the system and make necessary adjustments. Then, a robust time‐varying tightened state constraint is tailored for the optimization problem with respect to distributed model predictive control, and it can provide robustness to external disturbances and system coupling parts. And an adaptive prediction horizon update scheme is deliberately designed to decrease the length of the prediction horizon when the system state is close to the terminal set, reducing the computational complexity in the optimization problem. Furthermore, we strictly prove that under the given sufficient conditions, the proposed ETADMPC algorithm is recursively feasible and the closed‐loop system is stable. Finally, a numerical example is provided to show that our scheme can achieve satisfactory control performances with less calculation and a shorter calculation time than the existing results.
Unveiling the Complex Evolution in Mixed Br–Cl Perovskite Precursors for High‐Efficiency Deep‐Blue Light‐Emitting Diodes
Authors: Jia Yongheng , Li Ruichen , Zhou Yang , Zhao Shenghe , Yu Hui , Wang Jianpu , Lin Zhenyang , Su Haibin , Zhao Ni
Published: January 2023

Perovskite light‐emitting diodes (PeLEDs) based on 3D mixed Br‐Cl compositions have shown good color stability and efficiency in the sky‐blue color range. However, when the Cl/Br ratio increases to reach deep‐blue emission, the performance of the PeLEDs decreases drastically, with the external quantum efficiency (EQE) typically below 1%. Such performance decay is due largely to the poor morphology of the emissive layer. Herein, theoretical and experimental approach is combined to investigate the evolution of solvated lead complexes in the precursor solution of mixed Br–Cl perovskites. It is found that the energetically favorable exchange of halide ions in the lead complexes drives the precipitation of CsCl, leading to extremely low precursor solubility at high Cl/Br ratios and consequently poor perovskite film coverage. Based on the findings, a metastable dissolution strategy for perovskite film preparation is proposed and deep‐blue PeLEDs with a record high EQE of 4% in 3D‐based PeLEDs and excellent spectral stability is achieved.
The emerging roles of circRNAs in traits associated with livestock breeding
Authors: Sun Ping , Chen Mengjie , Sooranna Suren R. , Shi Deshun , Liu Qingyou , Li Hui
Published: January 2023

Many indicators can be used to evaluate the productivity and quality of livestock, such as meat and milk production as well as fat deposition. Meat and milk production are measures of livestock performance, while fat deposition affects the taste and flavor of the meat. The circRNAs, are non‐coding RNAs, that are involved in the regulation of all these three traits. We review the functions and mechanisms of circRNAs in muscle and fat development as well as lactation to provide a theoretical basis for circRNA research in animal husbandry. Various phenotypic changes presented in livestock may be produced by different circRNAs. Our current concern is how to use the roles played by circRNAs to our advantage to produce the best possible livestock. Hence, we describe the advantages and disadvantages of knockout techniques for circRNAs. In addition, we also put forward our thoughts regarding the mechanism and network of circRNAs to provide researchers with novel ideas of how molecular biology can help us advance our goals in animal farming.

This article is categorized under:

RNA in Disease and Development > RNA in Disease

RNA Interactions with Proteins and Other Molecules > Protein‐RNA Interactions: Functional Implications

RNA Interactions with Proteins and Other Molecules > Protein‐RNA Recognition

RNA Interactions with Proteins and Other Molecules > RNA‐Protein Complexes
Machine Learning Weather Analogs for Near-Surface Variables
Authors: Hu Weiming , Cervone Guido , Young George , Delle Monache Luca
Published: January 2023

Numerical weather prediction models and high-performance computing have significantly improved our ability to model near-surface variables, but their uncertainty quantification still remains a challenging task. Ensembles are usually produced to depict a series of possible future states of the atmosphere, as a means to quantify the prediction uncertainty, but this requires multiple instantiation of the model, leading to an increased computational cost. Weather analogs, alternatively, can be used to generate ensembles without repeated model runs. The analog ensemble (AnEn) is a technique to identify similar weather patterns for near-surface variables and quantify forecast uncertainty. Analogs are chosen based on a similarity metric that calculates the weighted multivariate Euclidean distance. However, identifying optimal weights for similarity metric becomes a bottleneck because it involves performing a constrained exhaustive search. As a result, only a few predictors were selected and optimized in previous AnEn studies. A new machine learning similarity metric is proposed to improve the theoretical framework on how weather analogs are identified. First, a deep learning network is trained to generate latent features using all the temporal multivariate input predictors. Analogs are then selected in this latent space, rather than the original predictor space. The proposed method does not require prior predictor selection and an exhaustive search, thus presenting a significant computational benefit and scalability. It is tested for surface wind speed and solar irradiance forecasts in Pennsylvania from 2017 to 2019. Results show that the proposed method is capable of handling a large number of predictors, and it outperforms the original similarity metric in RMSE, bias, and CRPS. Since the data-driven transformation network is trained using the historical record, the proposed method has been found to be more flexible for searching through a longer record.
Understanding the Impact of Home Confinement on Children and Young People with ADHD and ASD During the COVID-19 Pandemic
Authors: Hall Charlotte L. , Partlett Christopher , Valentine Althea Z. , Pearcey Samantha , Sayal Kapil
Published: January 2023

To understand whether the mental health of children and young people (CYP) with and without attention-deficit/hyperactivity disorder (ADHD) and/or autism spectrum disorder (ASD) were differentially affected by COVID-19. We analysed data (n = 6507) from the Co-Space study, a UK web-based longitudinal survey. CYP with ADHD (n = 160;2.5%), ASD (n = 465;7%), and ADHD + ASD (n = 155;2.4%) were compared with a reference group (n = 5727;88%) using parent-completed questionnaires [Strengths and Difficulties Questionnaire (SDQ) & Pandemic Anxiety Scale (PAS)]. Baseline to 1-month follow-up differences were compared using linear regression models. CYP with ADHD and/or ASD had higher scores at baseline than other CYP. At follow-up, CYP with ASD showed small but significant improvements in symptoms (SDQ), compared with the reference group. CYP with ASD experienced a worsening of disease anxiety (PAS) and CYP with ADHD a deterioration in functional impairment. These findings indicate a mixed pattern of pandemic-related impact for CYP with ADHD and/or ASD.
The influence of using video media on basic movement skills in kindergarten
Authors: Mohammad Mona , Boushehry Heyam Reda
Published: January 2023

This study aimed to measure the effects of video media on kindergarten children basic movement skills. Educators use many strategies to assist their children in acquiring basic movement skills in kindergartens; The style of teaching encompasses the style of guided discovery, with a component and entire method approach supported by visual medias. This research used an experimental design with convenience sampling of 40 children from two classes in kindergarten. The experimental study is an investigation into the effects of video media in children’s and other supervised subjects on fundamental movement abilities. Twenty children assigned to an experimental treatment, in which the researchers studied findings on children development on basic movement skills. Other children (N = 20) were assigned to a control group. Instrumentation for the Research-based on observation to gather data, the observation made by a researcher to find items that are needed. Moreover, The Bruininks-Oseretsky Second Edition Motor Capability Test ((Bruiniks and Bruiniks, Bruininks-Oseretsky Test of Motor Proficiency> Second (Edition manual), Pearson Assessment, 2005)) and The Test of Gross Motor Development (TGMD) used in this research. Blinding teaching methods in kindergarten physical education using visual media showed increase the basic mobility skills of the kindergarten sample. Physical Education teachers using blinding methods in classroom provide their special children with more effective learning skills in the Basic Movement Skills in the kindergarten. In addition, video media tools showed improvement in basic movement skills of school lay-up children. The outcome of this research provided advice to practitioners and researchers on how to incorporate video in their teaching with a view to promoting the development of important motor skills in children.
On predicting school dropouts in Egypt: A machine learning approach
Authors: Selim Kamal Samy , Rezk Sahar Saeed
Published: January 2023

Compulsory school-dropout is a serious problem affecting not only the education systems, but also the developmental progress of any country as a whole. Identifying the risk of dropping out, and characterizing its main determinants, could help the decision-makers to draw eradicating policies for this persisting problem and reducing its social and economic negativities over time. Based on a substantially imbalanced Egyptian survey dataset, this paper aims to develop a Logistic classifier capable of early predicting students at-risk of dropping out. Training any classifier with an imbalanced dataset, usually weaken its performance especially when it comes to false negative classification. Due to this fact, an extensive comparative analysis is conducted to investigate a variety of resampling techniques. More specifically, based on eight under-sampling techniques and four over-sampling ones, and their mutually exclusive mixed pairs, forty-five resampling experiments on the dataset are conducted to build the best possible Logistic classifier. The main contribution of this paper is to provide an explicit predictive model for school dropouts in Egypt which could be employed for identifying vulnerable students who are continuously feeding this chronic problem. The key factors of vulnerability the suggested classifier identified are student chronic diseases, co-educational, parents' illiteracy, educational performance, and teacher caring. These factors are matching with those found by many of the research previously conducted in similar countries. Accordingly, educational authorities could confidently monitor these factors and tailor suitable actions for early intervention.
You Don’t Have to Re-invent the Wheel to Implement Technology Activities in Early Childhood Education
Authors: Eliasson Sara , Peterson Louise , Lantz-Andersson Annika
Published: January 2023

This study on technology education in preschool aims to explore how technology activities in preschool are enacted and what knowledge, related to the five dimensions of the nature of technology, is made possible for the children to learn when intersubjectivity is established in the interaction between the participants. The empirical data encompass three video-documented technology activities, involving five children and one preschool teacher. Drawing on the five dimensions of the nature of technology by DiGironimo, the participants’ interactions were analysed using interaction analysis. The results showed that the teacher, through well-defined and sensitive orchestration, enacted goal-oriented activities by allowing a play-oriented approach, and that intersubjectivity on technology was established related to four of the five dimensions of technology. The lack of knowledge related to the historical dimension of technology suggests further scrutiny and is discussed as essential in ECE technology education for contemporary children, growing up in high-tech societies.
On the Phase Space of Fourth-Order Fiber-Orientation Tensors
Authors: Bauer Julian Karl , Schneider Matti , Böhlke Thomas
Published: January 2023

Fiber-orientation tensors describe the relevant features of the fiber-orientation distribution compactly and are thus ubiquitous in injection-molding simulations and subsequent mechanical analyses. In engineering applications to date, the second-order fiber-orientation tensor is the basic quantity of interest, and the fourth-order fiber-orientation tensor is obtained via a closure approximation. Unfortunately, such a description limits the predictive capabilities of the modeling process significantly, because the wealth of possible fourth-order fiber-orientation tensors is not exploited by such closures, and the restriction to second-order fiber-orientation tensors implies artifacts. Closures based on the second-order fiber-orientation tensor face a fundamental problem – which fourth-order fiber-orientation tensors can be realized? In the literature, only necessary conditions for a fiber-orientation tensor to be connected to a fiber-orientation distribution are found. In this article, we show that the typically considered necessary conditions, positive semidefiniteness and a trace condition, are also sufficient for being a fourth-order fiber-orientation tensor in the physically relevant case of two and three spatial dimensions. Moreover, we show that these conditions are not sufficient in higher dimensions. The argument is based on convex duality and a celebrated theorem of D. Hilbert (1888) on the decomposability of positive and homogeneous polynomials of degree four. The result has numerous implications for modeling the flow and the resulting microstructures of fiber-reinforced composites, in particular for the effective elastic constants of such materials. Based on our findings, we show how to connect optimization problems on fourth-order fiber-orientation tensors to semi-definite programming. The proposed formulation permits to encode symmetries of the fiber-orientation tensor naturally. As an application, we look at the differences between orthotropic and general, i.e., triclinic, fiber-orientation tensors of fourth order in two and three spatial dimensions, revealing the severe limitations inherent to orthotropic closure approximations.
The nutrition-environment nexus assessment of Thai Riceberry product for supporting environmental product declaration
Authors: Mungkung Rattanawan , Dangsiri Sarocha , Satmalee Prajongwate , Surojanametakul Vipa , Saejew Katreeya , Gheewala Shabbir H.
Published: January 2023

Riceberry rice has a special characteristic of being specially bred with high nutrients. High-value added products from riceberry are being promoted targeting health-conscious consumers. To provide supporting information for sustainable food systems, environmental footprinting was applied for evaluating the environmental performance of a ready-to-eat product of riceberry rice mixed with kidney red bean called “Riceberry + KU”, developed by Kasetsart University in Thailand. Based on sold unit as the unit of analysis, the carbon footprint of Riceberry + KU was 5.24 gCO2e per 300 g. Interestingly, white rice had the highest carbon footprint and riceberry rice as well as the riceberry product had at least 30% lower values. However, using nutrient-based scores, although white rice still had the highest carbon footprint, Riceberry + KU had 80% lower and the riceberry rice had 65% lower values. This resulted from the highest nutritional levels found in Riceberry + KU along with the lower greenhouse gas emissions from riceberry field during the cultivation stage. Similar trends were found in the other impact categories assessed by using life cycle assessment as well. To provide appropriate information to consumers for making more sustainable food choices, the environmental performance based on nutrient quality resulting from different farming systems and processing methods should be used to derive recommendations for moving toward sustainable food systems. The nutrition-environment nexus assessment could be very useful for supporting consumers toward making more sustainable food choices.
Enhancement of thermoelectric power factor in Cu2Se superionic conductor via high energy electron beam irradiation
Authors: Mangavati Suraj , Gurukrishna K , Rao Ashok , Petwal Vikash Chandra , Verma Vijay Pal , Dwivedi Jishnu
Published: January 2023

The modification in the Cu2Se thermoelectric system by electron beam irradiation has been carried out in this work. Samples were prepared using the solid-state reaction technique. The prepared samples were irradiated with various energy dosages viz. 50, 100, and 150 kGy. XRD studies reveal that the synthesized samples crystallized in a monoclinic structure. The micro-hardness of the samples decreased with an increase in irradiation dosage. The sample irradiated at 100 kGy dose exhibits the lowest electrical resistivity, moderate Seebeck coefficient, and highest power factor.
Bumble Bee Avoidance of Argentine Ants and Associated Chemical Cues
Authors: Miner Michelle Constanza , Wilson Rankin Erin E.
Published: January 2023

Bees provide pollination services in both agricultural and natural ecosystems. However, invasive ants that exploit floral nectar in these landscapes can compete with bees for resources, with implications for pollinator resource acquisition, plant fitness, and, ultimately, ecosystem function. While interference competition has been described between bees and nectivorous, non-pollinator antagonists, the behaviors and sensory mechanisms involved remain largely unresolved. Here, we studied the mechanisms by which invasive Argentine ants influence bee nectar foraging behavior. In a series of laboratory assays, we assessed the foraging behavior of bumble bees (Bombus impatiens) in response to live Argentine ants (Linepithema humile) or to a subset of ant chemical cues. Bees were clearly deterred by live ants at a nectar source: they consumed less, fed less frequently, and fed for a shorter duration when live ants were present. Bees were also deterred by a combination of olfactory and gustatory ant chemical cues, consistent with both innate and learned avoidance behavior. Naïve and ant-experienced bees were deterred through chemosensation of ants, feeding less from nectar infused with ant chemicals as compared to nectar lacking ants or their associated cues. Some ant-experienced bees showed a unique behavior, displaying aggression toward ants as well as in response to ant chemicals. The marked effects of this invasive ant on bee foraging behavior—through physical interaction and chemical cues—highlights Argentine ants as a serious pest whose control should be considered when developing pollinator conservation and management strategies.
Towards trust-based governance of health data research
Authors: Bak Marieke A. R. , Ploem M. Corrette , Tan Hanno L. , Blom M. T. , Willems Dick L.
Published: January 2023

Developments in medical big data analytics may bring societal benefits but are also challenging privacy and other ethical values. At the same time, an overly restrictive data protection regime can form a serious threat to valuable observational studies. Discussions about whether data privacy or data solidarity should be the foundational value of research policies, have remained unresolved. We add to this debate with an empirically informed ethical analysis. First, experiences with the implementation of the General Data Protection Regulation (GDPR) within a European research consortium demonstrate a gap between the aims of the regulation and its effects in practice. Namely, strictly formalised data protection requirements may cause routinisation among researchers instead of substantive ethical reflection, and may crowd out trust between actors in the health data research ecosystem; while harmonisation across Europe and data sharing between countries is hampered by different interpretations of the law, which partly stem from different views about ethical values. Then, building on these observations, we use theory to argue that the concept of trust provides an escape from the privacy-solidarity debate. Lastly, the paper details three aspects of trust that can help to create a responsible research environment and to mitigate the encountered challenges: trust as multi-agent concept; trust as a rational and democratic value; and trust as method for priority setting. Mutual cooperation in research—among researchers and with data subjects—is grounded in trust, which should be more explicitly recognised in the governance of health data research.
The cascading failure of check dam systems during the 28 July 2022 Emamzadeh Davood flood in Iran
Authors: Motagh Mahdi , Akhani Hossein
Published: January 2023

On July 18, 2022, an unexpected rainfall and flash flood struck the Emamzadeh Davood village in northwestern Tehran, the capital city of Iran, claiming the life of at least 23 people. In this brief communication, we report results from a recent investigation carried out by field surveys and remote sensing data, highlighting the role of anthropogenic factors and catastrophic failures in a series of check dams in intensifying the impacts of the 2022 Emamzadeh Davood event.
Mucopenetrating Janus Nanoparticles For Field-Coverage Oral Cancer Chemoprevention
Authors: Habibi Nahal , Bissonnette Caroline , Pei Ping , Wang Daren , Chang Albert , Raymond Jeffery E. , Lahann Joerg , Mallery Susan R.
Published: January 2023

Introduction

Oral squamous cell carcinoma (OSCC), is associated with high morbidity and mortality. Preemptive interventions have been postulated to provide superior therapeutic options, but their implementation has been restricted by the availability of broadly applicable local delivery systems.

Methods

We address this challenge by engineering a delivery vehicle, Janus nanoparticles (JNP), that combine the dual mucoadhesive properties of a first cationic chitosan compartment with a second hydrophobic poly(lactide-co-glycolide) release compartment. JNP are designed to avoid rapid mucus clearance while ensuring stable loading and controlled release of the IL-6 receptor antagonist, tocilizumab (TCZ).

Results

The JNP featured defined and monodispersed sizes with an average diameter of 327 nm and a PDI of 0.245, high circularities above 0.90 and supported controlled release of TCZ and effective internalization by oral keratinocytes. TCZ released from JNP retained its biological activity and effectively reduced both, soluble and membrane-bound IL-6Rα (71% and 50%). In full-thickness oral mucosal explants, 76% of the JNP breached the stratum corneum and in 41% were observed in the basal cell layer indicating excellent mucopenetrating properties. When tested in an aggressive OSCC xenograft model, TCZ-loaded JNP showed high levels of xenograft inhibition and outperformed all control groups with respect to inhibition of tumor cell proliferation, reduction in tumor size and reduced expression of the proto-oncogene ERG.

Conclusion

By combining critically required, yet orthogonal properties within the same nanoparticle design, the JNP in this study, demonstrate promise as precision delivery platforms for intraoral field-coverage chemoprevention, a vastly under-researched area of high clinical importance.
Langue and Parole of Investment Law
Authors: Vargiu Paolo
Published: January 2023

This article identifies the principal signs forming the language of investment law and arbitration, isolating for each of them its signifier and its signified in light of how such signs are used by arbitrators, practitioners and scholars. In light of this analysis, investment arbitration is assessed from a semiotic standpoint in order to verify whether it is possible, under this perspective, to consider international investment law as a multilateralised branch of international law, with a common language, customs and rules rightly referred to by international arbitral tribunals, or if the term “international investment law” is merely a conventional expression that simply groups together a plurality of micro-systems with no significant link among each other to justify the arbitrators' establishment of a de facto system of precedent and the constant reference to a non-existent body of international law rules on foreign investment.
Philosophical Reflections on Child Poverty and Education
Authors: Terzi Lorella , Unterhalter Elaine , Suissa Judith
Published: January 2023

The harmful effects of Covid 19 on children living in poverty have refocused attention on the complex nature of child poverty and the vexed question of its relationship to education. The paper examines a tension at the heart of much discussion of child poverty and education. On the one hand, education is often regarded as essential for children’s flourishing and a means by which children can “escape” poverty; yet on the other hand, education systems, institutions, and practices, often reflect and entrench the disadvantages associated with poverty. Narratives concerning education as an escape from poverty tend not to deal in any depth with the injustices associated with poverty, stressing instead the transformative potential of education. By contrast, largely sociological analyses of the ways in which schooling reproduces inequalities tend to stop short of developing a normative account of how education can contribute to transforming the structural injustices related to poverty and its effects on children’s lives. In working to move beyond this analytic impasse, the paper shows how the cluster of concepts, which Robeyns (2018) locates as central to the capability approach, give insights which help to address these two different lacunae. The notion of conversion factors highlights the significance of taking account of existing relationships in education, while the distinction between capabilities and functionings helps guide practices regarding the education of children living in poverty. Drawing on literature on the heightened inequalities associated with poor children’s experience of lack of schooling during the COVID pandemic, the paper sketches some of the ways in which sociological analysis and normative evaluation can be linked in taking forward an “ethically engaged political philosophy” (Wolff, 2018) to discuss child poverty and education in real schools.
The metaphysical underdetermination of time-reversal invariance
Authors: López Cristian
Published: January 2023

In this paper I argue that the concept of time-reversal invariance in physics suffers from metaphysical underdetermination, that is, that the concept may be understood differently depending on one’s metaphysics about time, laws, and a theory’s basic properties. This metaphysical under-determinacy also affects subsidiary debates in philosophy of physics that rely on the concept of time-reversal invariance, paradigmatically the problem of the arrow of time. I bring up three cases that, I believe, fairly illustrate my point. I conclude, on the one hand, that any formal representation of time reversal should be explicit about the metaphysical assumptions of the concept that it intends to represent; on the other, that philosophical arguments that rely on time reversal to argue against a direction of time require additional premises.
Phosphorus Deactivation on Co-based Catalysts for Fischer-Tropsch
Authors: Ivanez Oscar , Groven Anette S. , Rout Kumar R. , Blekkan Edd A.
Published: January 2023

The effect of phosphorus on a cobalt-based catalyst for Fischer-Tropsch Synthesis (FTS) has been investigated. Phosphorus is an impurity present in biomass and, in this work, its deposition on the catalyst during biomass to liquid (BTL) operation, based on gasification and FTS, has been mimicked. For this purpose, four different cobalt-manganese-rhenium catalysts supported on alumina were prepared by incipient wetness impregnation with different phosphorus loadings. The results showed that below 800 ppm of phosphorus, the catalysts performance was not significantly affected, possibly because the interaction of phosphorus mainly was with the alumina support. However, above this threshold, the effect of phosphorus was noticeable with a decrease in intrinsic activity. The reduced performance can be attributed to a physical blocking of cobalt sites. But, in all poisoned catalysts, the product distribution was affected and shifted towards less valuable products as methane and light paraffins. The electronegativity of phosphorus might be the cause for this effect, as the effective H2/CO ratio on the catalyst surface may be increased due to a weakened metal-CO bonding and consequently, the selectivity of the hydrogenated products increased.