bluuebunny/crossref_metadata_2025 huggingface dataset:
Robustness of carbon‐ion radiotherapy against DNA damage repair associated radiosensitivity variation based on a biophysical model
Authors: Liew Hans , Tessonnier Thomas , Mein Stewart , Magro Giuseppe , Glimelius Lars , Coniavitis Elias , Held Thomas , Haberer Thomas , Abdollahi Amir , Debus Jürgen , Dokic Ivana , Mairani Andrea
Published: April 2024

Background

Interpatient variation of tumor radiosensitivity is rarely considered during the treatment planning process despite its known significance for the therapeutic outcome.

Purpose

To apply our mechanistic biophysical model to investigate the biological robustness of carbon ion radiotherapy (CIRT) against DNA damage repair interference (DDRi) associated patient‐to‐patient variability in radiosensitivity and its potential clinical advantages against conventional radiotherapy approaches.

Methods and Materials

The “UNIfied and VERSatile bio response Engine” (UNIVERSE) was extended by carbon ions and its predictions were compared to a panel of in vitro and in vivo data including various endpoints and DDRi settings within clinically relevant dose and linear energy transfer (LET) ranges. The implications of UNIVERSE predictions were then assessed in a clinical patient scenario considering DDRi variance.

Results

UNIVERSE tests well against the applied benchmarks. While in vitro survival curves were predicted with an R2 > 0.92, deviations from in vivo RBE data were less than 5.6% The conducted paradigmatic patient plan study implies a markedly reduced significance of DDRi based radiosensitivity variability in CIRT (13% change of in target) compared to conventional radiotherapy (62%) and that boosting the LET within the target further amplifies this robustness of CIRT (8%). In the case of heightened tumor radiosensitivity, a dose de‐escalation strategy for photons allows a reduction of the maximum effective dose within the normal tissue (NT) from a of 2.65 to 1.64 Gy, which lies below the level found for CIRT ( = 2.41 Gy) for the analyzed plan and parameters. However, even after de‐escalation, the integral effective dose in the NT is found to be substantially higher for conventional radiotherapy in comparison to CIRT ( of 0.75, 0.46, and 0.24 Gy for the conventional plan, its de‐escalation and CIRT, respectively).

Conclusions

The framework offers adequate predictions of in vitro and in vivo radiation effects of CIRT while allowing the consideration of DRRi based solely on parameters derived from photon data. The results of the patient planning study underline the potential of CIRT to minimize important sources of interpatient divergence in therapy outcome, especially when combined with techniques that allow to maximize the LET within the tumor. Despite the potential of de‐escalation strategies for conventional radiotherapy to reduce the maximum effective dose in the NT, CIRT appears to remain a more favorable option due to its ability to reduce the integral effective dose within the NT.
Enhancing adaptive proton therapy through CBCT images: Synthetic head and neck CT generation based on 3D vision transformers
Authors: Viar‐Hernandez David , Molina‐Maza Juan Manuel , Vera‐Sánchez Juan Antonio , Perez‐Moreno Juan Maria , Mazal Alejandro , Rodriguez‐Vila Borja , Malpica Norberto , Torrado‐Carvajal Angel
Published: April 2024

Background

Proton therapy is a form of radiotherapy commonly used to treat various cancers. Due to its high conformality, minor variations in patient anatomy can lead to significant alterations in dose distribution, making adaptation crucial. While cone‐beam computed tomography (CBCT) is a well‐established technique for adaptive radiation therapy (ART), it cannot be directly used for adaptive proton therapy (APT) treatments because the stopping power ratio (SPR) cannot be estimated from CBCT images.

Purpose

To address this limitation, Deep Learning methods have been suggested for converting pseudo‐CT (pCT) images from CBCT images. In spite of convolutional neural networks (CNNs) have shown consistent improvement in pCT literature, there is still a need for further enhancements to make them suitable for clinical applications.

Methods

The authors introduce the 3D vision transformer (ViT) block, studying its performance at various stages of the proposed architectures. Additionally, they conduct a retrospective analysis of a dataset that includes 259 image pairs from 59 patients who underwent treatment for head and neck cancer. The dataset is partitioned into 80% for training, 10% for validation, and 10% for testing purposes.

Results

The SPR maps obtained from the pCT using the proposed method present an absolute relative error of less than 5% from those computed from the planning CT, thus improving the results of CBCT.

Conclusions

We introduce an enhanced ViT3D architecture for pCT image generation from CBCT images, reducing SPR error within clinical margins for APT workflows. The new method minimizes bias compared to CT‐based SPR estimation and dose calculation, signaling a promising direction for future research in this field. However, further research is needed to assess the robustness and generalizability across different medical imaging applications.
Deep learning‐based extraction of surface wave dispersion curves from seismic shot gathers
Authors: Chamorro Danilo , Zhao Jiahua , Birnie Claire , Staring Myrna , Fliedner Moritz , Ravasi Matteo
Published: April 2024

Multi‐channel analysis of surface waves is a seismic method employed to obtain useful information about shear‐wave velocities in the near surface. A fundamental step in this methodology is the extraction of dispersion curves from dispersion spectra, with the latter usually obtained by applying specific processing algorithms onto the recorded shot gathers. Although the extraction process can be automated to some extent, it usually requires extensive quality control, which can be arduous for large datasets. We present a novel approach that leverages deep learning to identify a direct mapping between seismic shot gathers and their associated dispersion curves (both fundamental and first higher order modes), therefore by‐passing the need to compute dispersion spectra. Given a site of interest, a set of 1D compressional and shear velocities and density models are created using prior knowledge of the local geology; pairs of seismic shot gathers and Rayleigh‐wave phase dispersion curves are then numerically modelled and used to train a simplified residual network. The proposed approach is shown to achieve high‐quality predictions of dispersion curves on a synthetic test dataset and is, ultimately, successfully deployed on a field dataset. Various uncertainty quantification and convolutional neural network visualization techniques are also presented to assess the quality of the inference process and better understand the underlying learning process of the network. The predicted dispersion curves are inverted for both the synthetic and field data; in the latter case, the resulting shear‐wave velocity model is plausible and consistent with prior geological knowledge of the area. Finally, a comparison between the manually picked fundamental modes with the predictions from our model allows for a benchmark of the performance of the proposed workflow.
Government expenditure and unemployment nexus in Nigeria: Does institutional quality matter?
Authors: Raifu Isiaka Akande , Aminu Alarudeen , Afolabi Joshua Adeyemi , Obijole Emmanuel Olubowale
Published: April 2024

This study investigates the role of institutional quality in the government expenditure‐unemployment nexus in Nigeria using different components of government expenditures (total, recurrent, and capital expenditures). Causality tests and the autoregressive distributed lag estimation methods are used to analyse data spanning the period from 1984 to 2019. The key findings are as follows: (i) unidirectional causality runs from unemployment to total and capital expenditure and a partial unidirectional causality runs from recurrent expenditure to unemployment; (ii) total and capital expenditures are pro‐employment in the long run, while the recurrent expenditure is only pro‐employment in the short run; (iii) institutional quality is detrimental to employment in the long run; and (iv) institutional quality significantly moderates the impact of government expenditure on unemployment in Nigeria. The Nigerian government need to increase pro‐employment expenditure and make concerted efforts at improving the institutional quality in Nigeria.
Validity of inpatient electronic health record‐based measures of oxygen‐related therapy in the United States: Lessons applicable for studying COVID‐19 endpoints
Authors: Fuller Candace C. , Rosen Edward , Rai Ashish , Cosgrove Austin , Miller Karla , Bright Patricia , Haffenreffer Katherine , Poland Russell E. , Pratt Natasha , Sands Kenneth , Shinde Mayura U. , Platt Richard , Cocoros Noelle M. , Klompas Michael , Dutcher Sarah K.
Published: April 2024

Introduction

During the COVID‐19 pandemic, inpatient electronic health records (EHRs) have been used to conduct public health surveillance and assess treatments and outcomes. Invasive mechanical ventilation (MV) and supplemental oxygen (O2) use are markers of severe illness in hospitalized COVID‐19 patients. In a large US system (n = 142 hospitals), we assessed documentation of MV and O2 use during COVID‐19 hospitalization in administrative data versus nursing documentation.

Methods

We identified 319 553 adult hospitalizations with a COVID‐19 diagnosis, February 2020–October 2022, and extracted coded, administrative data for MV or O2. Separately, we developed classification rules for MV or O2 supplementation from semi‐structured nursing documentation. We assessed MV and O2 supplementation in administrative data versus nursing documentation and calculated ordinal endpoints of decreasing COVID‐19 disease severity. Nursing documentation was considered the gold standard in sensitivity and positive predictive value (PPV) analyses.

Results

In nursing documentation, the prevalence of MV and O2 supplementation among COVID‐19 hospitalizations was 14% and 75%, respectively. The sensitivity of administrative data was 83% for MV and 41% for O2, with both PPVs above 91%. Concordance between sources was 97% for MV (κ = 0.85), and 54% for O2 (κ = 0.21). For ordinal endpoints, administrative data accurately identified intensive care and MV but underestimated hospitalizations with O2 requirements (42% vs. 18%).

Conclusions

In comparison to nursing documentation, administrative data under‐ascertained O2 supplementation but accurately estimated severe endpoints such as MV. Nursing documentation improved ascertainment of O2 among COVID‐19 hospitalizations and can capture oxygen requirements in adults hospitalized with COVID‐19 or other respiratory illnesses.
Prevalence of self‐medication practices among pregnant women in India: A systematic review and meta‐analysis
Authors: Chaudhary Vaibhav , Kumari Sweta , Khurana Navneet , Azharuddin Mohammad , Singh Aditya Pratap , Devi Varsha , Dhir Deepali , Pal Biplab
Published: April 2024

Background

Self‐medication practice among pregnant women is a global concern. However, its understanding in the Indian context is limited due to a lack of comprehensive studies.

Purpose

This study aimed to comprehensively assess the prevalence of self‐medication, the medications used for self‐medication, diseases/conditions associated with self‐medication, and the reasons for self‐medication among Indian pregnant women.

Methods

This study was carried out following the guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA). A thorough search was done in PubMed, Embase, and Google Scholar to find articles that were published up until May 2023. Inclusion criteria comprised observational studies reporting self‐medication prevalence among pregnant women in India. Data were extracted using a standardized sheet, and a random‐effects model was applied to determine the overall prevalence of self‐medication using R software. The I2 statistic was employed to assess the heterogeneity among the studies.

Results

This study analyzed eight studies with a collective sample size of 2208 pregnant women. The pooled prevalence of self‐medication among pregnant Indian women was 19.3% (95% CI: 7.5%–41.3%; I2 = 99%; p < 0.01). Common self‐treated conditions were cold, cough, fever, headache, and stomach disorders. Antipyretics, analgesics, antihistamines, and antacids were frequently used for self‐medication. The perception of mild ailment, immediate alleviation, convenience, time savings, and advice from family, friends, or the media were all reasons for self‐medication. Local pharmacies were the most usual source for obtaining drugs, and pharmacists, family, friends, and past prescriptions were common sources of medicine information.

Conclusions

A low yet substantial number of pregnant women in India are engaged in self‐medication practices. Appropriate strategies need to be planned to reduce self‐medication practices to attain sustainable developmental goals for maternal health in India.
Design, characterization, and performance evaluation of novel PVA/CS/CNF/MOP TN ionic conductive hydrogels for flexible sensors
Authors: Xu Wenjun , Newton Md All Amin , Chen Zhuoming , Xin Binjie
Published: April 2024

Flexible hydrogel polymers with excellent stretchability, high conductivity, and biocompatibility are widely used to prepare flexible sensing devices. However, it remains difficult to simultaneously combine excellent tensile capacity and high ion conducting ability into a simple hydrogel material. While PVA‐based hydrogels have been developed before, this work focuses on a unique preparation method. It solves the engineering problem of making hydrogels that have both high elongation at break and high ionic conductivity. In the study, we introduced cellulose nanofibers (CNFs) into polyvinyl alcohol (PVA)/chitosan (CS) cross‐linked polymer networks to form triple network (TN) composite hydrogel. The labyrinthine three‐dimensional (3D) honeycomb through‐hole network nanostructure generated by the addition of CNF provides the hydrogel with excellent mechanical properties. Then, the simple salting‐out strategy of muriate of potash (MOP) solution gives the hydrogel superior mechanical properties and high ionic conductivity. The prepared PVA/CS/CNF/MOP TN ionic conductive hydrogel not only exhibits excellent mechanical properties (toughness up to 2.39 MJ m−3, fracture strength up to 1.78 MPa, fracture strain up to 350%) but also has impressive ionic conductivity (highest to 8.4 S m−1). The flexible hydrogel strain sensor assembled from the PVA/CS/CNF/MOP TN ionic conductive hydrogel showed remarkable sensitivity (gauge factor for 6.9) and the ability to detect human motions reliably. Besides, the hydrogel also has maintained long‐term antimicrobial and antioxidant properties. The study provided a new perspective on designing multifunctional materials featuring strong mechanical properties and high ionic conductivity, contributing to the advancement of flexible sensor technologies.
Impact of glycan nature on structure and viscoelastic properties of glycopeptide hydrogels
Authors: Proksch Jonas , Dal Colle Marlene C. S. , Heinz Frederick , Schmidt Robert F. , Gottwald Jacqueline , Delbianco Martina , Keller Bettina G. , Gradzielski Michael , Alexiev Ulrike , Koksch Beate
Published: April 2024

Mucus is a complex biological hydrogel that acts as a barrier for almost everything entering or exiting the body. It is therefore of emerging interest for biomedical and pharmaceutical applications. Besides water, the most abundant components are the large and densely glycosylated mucins, glycoproteins of up to 20 MDa and carbohydrate content of up to 80 wt%. Here, we designed and explored a library of glycosylated peptides to deconstruct the complexity of mucus. Using the well‐characterized hFF03 coiled‐coil system as a hydrogel‐forming peptide scaffold, we systematically probed the contribution of single glycans to the secondary structure as well as the formation and viscoelastic properties of the resulting hydrogels. We show that glycan‐decoration does not affect α‐helix and coiled‐coil formation while it alters gel stiffness. By using oscillatory macrorheology, dynamic light scattering microrheology, and fluorescence lifetime‐based nanorheology, we characterized the glycopeptide materials over several length scales. Molecular simulations revealed that the glycosylated linker may extend into the solvent, but more frequently interacts with the peptide, thereby likely modifying the stability of the self‐assembled fibers. This systematic study highlights the interplay between glycan structure and hydrogel properties and may guide the development of synthetic mucus mimetics.
Molecular crosstalk between insulin‐like growth factors and follicle‐stimulating hormone in the regulation of granulosa cell function
Authors: Hayes Emily , Winston Nicola , Stocco Carlos
Published: April 2024

Background

The last phase of folliculogenesis is driven by follicle‐stimulating hormone (FSH) and locally produced insulin‐like growth factors (IGFs), both essential for forming preovulatory follicles.

Methods

This review discusses the molecular crosstalk of the FSH and IGF signaling pathways in regulating follicular granulosa cells (GCs) during the antral‐to‐preovulatory phase.

Main findings

IGFs were considered co‐gonadotropins since they amplify FSH actions in GCs. However, this view is not compatible with data showing that FSH requires IGFs to stimulate GCs, that FSH renders GCs sensitive to IGFs, and that FSH signaling interacts with factors downstream of AKT to stimulate GCs. New evidence suggests that FSH and IGF signaling pathways intersect at several levels to regulate gene expression and GC function.

Conclusion

FSH and locally produced IGFs form a positive feedback loop essential for preovulatory follicle formation in all species. Understanding the mechanisms by which FSH and IGFs interact to control GC function will help design new interventions to optimize follicle maturation, perfect treatment of ovulatory defects, improve in vitro fertilization, and develop new contraceptive approaches.
Assessing experimental silvicultural treatments enhancing structural complexity in a central European forest – BEAST time‐series analysis based on Sentinel‐1 and Sentinel‐2
Authors: Kacic Patrick , Gessner Ursula , Holzwarth Stefanie , Thonfeld Frank , Kuenzer Claudia
Published: April 2024

Assessing the dynamics of forest structure complexity is a critical task in times of global warming, biodiversity loss and increasing disturbances in order to ensure the resilience of forests. Recent studies on forest biodiversity and forest structure emphasize the essential functions of deadwood accumulation and diversification of light conditions for the enhancement of structural complexity. The implementation of an experimental patch‐network in managed broad‐leaved forests within Germany enables the standardized analysis of various aggregated and distributed treatments characterized through diverse deadwood and light structures. To monitor the dynamics of enhanced forest structure complexity as seasonal and trend components, dense time‐series from high spatial resolution imagery of Sentinel‐1 (Synthetic‐Aperture Radar, SAR) and Sentinel‐2 (multispectral) are analyzed in time‐series decomposition models (BEAST, Bayesian Estimator of Abrupt change, Seasonal change and Trend). Based on several spatial statistics and a comprehensive catalog on spectral indices, metrics from Sentinel‐1 (n = 84) and Sentinel‐2 (n = 903) are calculated at patch‐level. Metrics best identifying the treatment implementation event are assessed by change point dates and probability scores. Heterogeneity metrics of Sentinel‐1 VH and Sentinel‐2 NMDI (Normalized Multi‐band Drought Index) capture the treatment implementation event most accurately, with clear advantages for the identification of aggregated treatments. In addition, aggregated structures of downed or no deadwood can be characterized, as well as more complex standing structures, such as snags or habitat trees. To conclude, dense time‐series of complementary high spatial resolution sensors have the potential to assess various aggregated forest structure complexities, thus supporting the continuous monitoring of forest habitats and functioning over time.
Functionalizing Yeast Lipid Droplets as Versatile Biomaterials
Authors: Suri Ankita , Hu Kevin K.Y. , Younas Tayyaba , Dumsday Geoff , Haritos Victoria S.
Published: April 2024

Lipid droplets (LD) are dynamic cellular organelles of ≈1 µm diameter in yeast where a neutral lipid core is surrounded by a phospholipid monolayer and attendant proteins. Beyond the storage of lipids, opportunities for LD engineering remain underdeveloped but they show excellent potential as new biomaterials. In this research, LD from yeast Saccharomyces cerevisiae is engineered to display mCherry fluorescent protein, Halotag ligand binding protein, plasma membrane binding v‐SNARE protein, and carbonic anhydrase enzyme via linkage to oleosin, an LD anchoring protein. Each protein‐oleosin fusion is coded via a single gene construct. The expressed fusion proteins are specifically displayed on LD and their functions can be assessed within cells by fluorescence confocal microscopy, TEM, and as isolated materials via AFM, flow cytometry, spectrophotometry, and by enzyme activity assay. LD isolated from the cell are shown to be robust and stabilize proteins anchored into them. These engineered LD function as reporters, bind specific ligands, guide LD and their attendant proteins into union with the plasma membrane, and catalyze reactions. Here, engineered LD functions are extended well beyond traditional lipid storage toward new material applications aided by a versatile oleosin platform anchored into LD and displaying linked proteins.
Metal Valence State Modulation Strategy to Design Core@shell Hollow Carbon Microspheres@MoSe2/MoOx Multicomponent Composites for Anti‐Corrosion and Microwave Absorption
Authors: Xiao Junxiong , Zhan Beibei , Qi Xiaosi , Ding Junfei , Qu Yunpeng , Gong Xiu , Yang Jing‐Liang , Wang Lei , Zhong Wei , Che Renchao
Published: April 2024

The exploitation of multicomponent composites (MCCs) has become the main pathway for obtaining advanced microwave absorption materials (MAMs). Herein, a metal valence state modulation strategy is proposed to tune the electromagnetic (EM) parameters and improve microwave absorption performances. Core@shell hollow carbon microspheres@MoSe2 and hollow carbon microspheres@MoSe2/MoOx MCCs with various mixed‐valence states content are well‐designed and produced by a simple hydrothermal reaction or/and heat treatment process. The results reveal that the thermal treatment of hollow carbon microspheres@MoSe2 in Ar and Ar/H2 leads to the in situ formation of MoOx and multivalence state, respectively, and the enhanced content of Mo4+ in the designed MCCs greatly boosts their impedance matching characteristics, polarization, and conduction loss capacities, which lead to their evidently improved EM wave absorption properties. Amongst, the as‐prepared hollow carbon microspheres@MoSe2/MoOx MCCs achieve an effective absorption bandwidth of 5.80 GHz under a matching thickness of 1.97 mm and minimum reflection loss of −21.49 dB. Therefore, this work offers a simple and universal method to fabricate core@shell hollow carbon microspheres@MoSe2/MoOx MCCs, and a novel and feasible metal valence state modulation strategy is proposed to develop high‐efficiency MAMs.
Tunable Structured 2D Nanobiocatalysts: Synthesis, Catalytic Properties and New Horizons in Biomedical Applications
Authors: Cui Qiqi , Gao Yang , Wen Qinlong , Wang Ting , Ren Xiancheng , Cheng Liang , Bai Mingru , Cheng Chong
Published: April 2024

2D materials have offered essential contributions to boosting biocatalytic efficiency in diverse biomedical applications due to the intrinsic enzyme‐mimetic activity and massive specific surface area for loading metal catalytic centers. Since the difficulty of high‐quality synthesis, the varied structure, and the tough choice of efficient surface loading sites with catalytic properties, the artificial building of 2D nanobiocatalysts still faces great challenges. Here, in this review, a timely and comprehensive summarization of the latest progress and future trends in the design and biotherapeutic applications of 2D nanobiocatalysts is provided, which is essential for their development. First, an overview of the synthesis‐structure‐fundamentals and structure‐property relationships of 2D nanobiocatalysts, both metal‐free and metal‐based is provided. After that, the effective design of the active sites of nanobiocatalysts is discussed. Then, the progress of their applied research in recent years, including biomedical analysis, biomedical therapeutics, pharmacokinetics, and toxicology is systematically highlighted. Finally, future research directions of 2D nanobiocatalysts are prospected. Overall, this review to provide cutting‐edge and multidisciplinary guidance for accelerating future developments and biomedical applications of 2D nanobiocatalysts is expected.
Tuning A‐Site Cation Deficiency in Pr0.5La0.5BaCo2O5+δ Perovskite to Realize Large‐Scale Hydrogen Evolution at 2000 mA cm−2
Authors: Li Kaiqian , Xia Tian , Deng Ruiping , Dou Yingnan , Wang Jingping , Li Qiang , Sun Liping , Huo Lihua , Zhao Hui
Published: April 2024

Industrial‐level hydrogen production from the water electrolysis requires reducing the overpotential (η) as much as possible at high current density, which is closely related to intrinsic activity of the electrocatalysts. Herein, A‐site cation deficiency engineering is proposed to screen high‐performance catalysts, demonstrating effective Pr0.5‐xLa0.5BaCo2O5+δ (P0.5‐xLBC) perovskites toward alkaline hydrogen evolution reaction (HER). Among all perovskite compositions, Pr0.4La0.5BaCo2O5+δ (P0.4LBC) exhibits superior HER performance along with unique operating stability at large current densities (J = 500–2000 mA cm−2 geo). The overpotential of ≈636 mV is achieved in P0.4LBC at 2000 mA cm−2 geo, which outperforms commercial Pt/C benchmark (≈974 mV). Furthermore, the Tafel slope of P0.4LBC (34.1 mV dec−1) is close to that of Pt/C (35.6 mV dec−1), reflecting fast HER kinetics on the P0.4LBC catalyst. Combined with experimental and theoretical results, such catalytic activity may benefit from enhanced electrical conductivity, enlarged Co‐O covalency, and decreased desorption energy of H* species. This results highlight effective A‐site cation‐deficient strategy for promoting electrochemical properties of perovskites, highlighting potential water electrolysis at ampere‐level current density.
Enabling High Reversibility of Zn anode via Interfacial Engineering Induced by Amino acid Electrolyte Additive
Authors: Naveed Ahmad , Li Teng , Ali Amjad , Ahmad Farooq , Qureshi Waqar Ahmad , Su Mingru , Li Xiaowei , Zhou Yu , Wu Jian‐Chun , Liu Yunjian
Published: April 2024

Despite possessing substantial benefits of enhanced safety and cost‐effectiveness, the aqueous zinc ion batteries (AZIBs) still suffers with the critical challenges induced by inherent instability of Zn metal in aqueous electrolytes. Zn dendrites, surface passivation, and corrosion are some of the key challenges governed by water‐driven side reactions in Zn anodes. Herein, a highly reversible Zn anode is demonstrated via interfacial engineering of Zn/electrolyte driven by amino acid D‐Phenylalanine (DPA) additions. The preferential adsorption of DPA and the development of compact SEI on the Zn anode suppressed the side reactions, leading to controlled and uniform Zn deposition. As a result, DPA added aqueous electrolyte stabilized Zn anode under severe test environments of 20.0 mA cm−2 and 10.0 mAh cm−2 along with an average plating/stripping Coulombic efficiency of 99.37%. Under multiple testing conditions, the DPA‐incorporated electrolyte outperforms the control group electrolyte, revealing the critical additive impact on Zn anode stability. This study advances interfacial engineering through versatile electrolyte additive(s) toward development of stable Zn anode, which may lead to its practical implementation in aqueous rechargeable zinc batteries.
Prediction of Macrosegregation in Fe–C–Cr Alloy Casting through Coupling with Thermodynamic Phase Transformation Path
Authors: Sun Leqin , Zhang Hongwei , Feng Miaomiao , Miao Miao , Liu Xiaoming , Xu Guangjun , Wang Qiang
Published: April 2024

The continuum macroscopic transport approach combined with a tabulated thermodynamic phase transformation path is established to predict the macrosegregation in Fe‐1.05 wt% C‐1.65 wt% Cr hypereutectoid steel castings. A combined partial‐equilibrium (PE) and para‐equilibrium (PA) thermodynamic approximation is developed to retrieve the phase transformation path in steels. PA routine is performed on both austenite to stoichiometric cementite transition and austenite to α‐ferrite transition in eutectoid transformation. The approach is also applied to a hypoeutectoid alloy to predict austenite to α‐ferrite transition as well as δ‐ferrite to austenite transition in mushy zone. Thermodynamic properties in macroscopic transport approach are updated by group interpolation from tabulated phase transformation path. Results show that the interaction between substitutional solute Cr and interstitial C weakens the segregation of C and the amount of cementite in the center of casting, making the C distribution more consistent with that obtained by original position statistical distribution analysis in GCr15SiMn alloy castings. This implies that including the contribution of more components can make the estimate more reasonable. The results indicate the potential of macroscopic transport prediction coupled with tabulated phase transformation path through PE + PA approximation.
Establishing European design rules for re‐used steel components
Authors: Feldmann Markus , Bartsch Helen , Eyben Felix , Bours Anna‐Lena , Knobloch Markus
Published: April 2024

In the construction industry, re‐use of components has the potential to play a crucial role in reducing CO2 emissions. The direct re‐use of components is particularly suitable for steel structures because they have a high degree of prefabrication and can be dismantled with a minimum of deterioration. However, for structural applications of re‐used components, there is the need for establishing concepts and rules for evaluation, reclaiming, stockage, placing on the market, structural design and installation. Safety assessment and design of re‐used steel components will be essential for creating a system that fosters the re‐use in the construction market. Against this background, and in order to promote the re‐use of steel components as one of the key measures to reduce carbon emissions of the European construction sector and its contribution to achieving the climate goals, the article outlines key aspects for confidently designing re‐used steel components according to Eurocode 3. This includes defining the scope and implementing a technical action plan.
Investigating the effect of steel micro‐ and macro‐fibers on the bond behavior of steel rebar embedded in ultra‐high performance concrete
Authors: Aghdami Sani Mohammad Reza , Ferdousi Adel , Pourbaba Masoud , Zandi Yousef , Mirrezaei Seyed Saeed
Published: April 2024

In recent years, the use of ultra‐high performance concrete (UHPC) has been widely considered in special structures and retrofitting of existing structures. Since most of the relations proposed by the regulations are based on the behavior of concrete with normal strength concrete, it is necessary to conduct more experimental studies to predict the behavior of UHPC. One of these notable behaviors is the bond and cohesion between rebar and UHPC, which plays a critical role in the design and seismic behavior of structures. In the present study, a series of experimental tests of uniaxial compressive strength, splitting (Brazilian) tensile strength, elastic modulus, and pull‐out of ribbed steel bars from ultra‐high performance fiber‐reinforced concrete (UHPFRC) were performed. The tests were done considering the four‐volume fractions of hooked‐end steel macro‐fibers, straight steel micro‐fibers, a hybrid combination of these two fibers, three different diameters of ribbed steel bars, and several embedded lengths. Moreover, direct tensile and compressive stress–strain curves, Young's modulus, bonding properties of rebar with UHPFRC, and fracture mechanisms were considered. The results indicated that applying micro‐fibers may enhance the bond stress between rebar and UHPC better than macro‐fibers. Also applying hybrid fibers resulted in the concurrent enhancement of bond stress and the optimum point slip of UHPC in the stress–slip diagram. This finding maybe attributed to the satisfactory performance of micro‐fibers in reducing the growth speed of micro‐level cracks and the suitable effect of macro‐fibers in decreasing the progression speed of macro‐level cracks. Furthermore, it was revealed that the increase in rebar diameter and embedding length leads to the reduction of maximum bond stress in UHPFRC.
Data‐driven investigation of compressive strength of FRP‐confined concrete columns using a unified model based on RSM considering interactions between parameters
Authors: Vafaei Ali , Davoudi‐Kia Abdullah , Kutanaei Saman Soleimani , Taslimi Mobina
Published: April 2024

In this study, a data‐driven model was developed to predict compressive strength of concrete columns after confining with Fiber‐Reinforced Polymer (FRP). Through application of Response Surface Method (RSM), interactions of input parameters are investigated in addition to their individual influence. Moreover, RSM is utilized in conjunction with unification to enhance model's accuracy. Furthermore, sensitivity analysis is employed together with RSM, to determine the effect size of statistically significant parameters. It is revealed that the real behavior of FRP confined concrete cannot be predicted by single‐parameter studies. Therefore, interaction terms should be included in the model to yield a more accurate prediction. Moreover, the model shows the highest sensitivity to FRP failure strength which this sensitivity decreases as corner radius increases. Therefore, regarding rounded‐corner sections, high improvements are achievable even by utilizing low strength FRPs. It is also shown that higher improvement may be limited due to premature debonding which elastic modulus mismatch between different phases is supposed to be responsible for it.
Guiding student transduction in elementary school astronomy
Authors: Prain Vaughan , Tytler Russell
Published: April 2024

Science educators now broadly recognize the multimodal nature of learning in science, where learners make meanings within modes (linguistic, mathematical, visual, and actional) by using the conventions of different sign systems or grammars in these modes. However, how teachers guide students to link and infer new meanings across modes, called “transduction” (Kress & Van Leeuwen, 2006. Reading images: The grammar of visual design. Routledge, p. 39), is less clear. This mapping of meanings across modes through realizing, generating, aligning, and coordinating meanings in representations is crucial to learning and communicating scientific concepts, inquiry processes, and reasoning. In this paper we propose a pragmatist account of how young students can be guided to achieve cohesion in this process. Drawing mainly on Peirce's (1998, The essential Peirce: Selected philosophical writings. Indiana University Press) theory of sign functions and affordances, we describe how, in practice, transduction entails a sequence of meaning‐making steps across and within sign systems. For Peirce, sign systems in science enable inferential meaning‐making within modes, but signs within these grammars can also prompt, support, and confirm meanings across modes. We analyze student learning in an elementary school astronomy class to identify how transduction is enacted and supported. We draw on micro‐ethnographic analysis of the teacher's interactions with students and their artifacts to identify key transduction enablers. We found that young students can engage successfully in trans‐modal reasoning if multiple conditions are met, with implications for science inquiry design in general and the teacher's key role in transduction guidance.
Performance measurement of international shipping companies before and during COVID‐19: A DEA Malmquist index and window analysis approach
Authors: Wang Chia‐Nan , Quang Bach Xuan , Dang Thanh‐Tuan
Published: April 2024

For the past several decades, the container shipping industry has grown rapidly. As a result, container shipping companies (CSCs) play a vital role in the global cargo transportation market. Thus, measuring the efficiency of CSCs is a primary concern of managers and practitioners. When the COVID‐19 pandemic broke out, the industry was severely disrupted and presented with unprecedented challenges. For this reason, evaluating how CSCs performed and learning the practices they took to achieve successful business results during this period have become necessary. To serve that purpose, this article used a hybrid method that combined data envelopment analysis Malmquist index with window analysis to analyze the world's nine leading CSCs' performance over time and their efficiency relative to each other, using data collected within a 5‐year period from 2016 to 2020. Our findings revealed different characteristics and trends in efficiency among these CSCs in terms of technical efficiency change, technological change, and total productivity change. Then, managerial implications were discussed to understand the best practices of successful CSCs as well as the circumstances in which some of them underperformed during this time. In closing, the study summarized a fact‐based guideline CSCs could take as management reference should a similar crisis occur.
Mitochondria‐associated endoplasmic reticulum membranes involve in oxidative stress‐induced intestinal barrier injury and mitochondrial dysfunction under diquat exposing
Authors: Gou Feiyang , Cai Fengzhou , Li Xin , Lin Qian , Zhu Jiang , Yu Minjie , Chen Shaokui , Lu Jianjun , Hu Caihong
Published: April 2024

Many factors induced by environmental toxicants have made oxidative stress a risk factor for the intestinal barrier injury and growth restriction, which is serious health threat for human and livestock and induces significant economic loss. It is well‐known that diquat‐induced oxidative stress is implicated in the intestinal barrier injury. Although some studies have shown that mitochondria are the primary target organelle of diquat, the underlying mechanism remains incompletely understood. Recently, mitochondria‐associated endoplasmic reticulum membranes (MAMs) have aroused increasing concerns among scholars, which participate in mitochondrial dynamics and signal transduction. In this study, we investigated whether MAMs involved in intestinal barrier injury and mitochondrial dysfunction induced by diquat‐induced oxidative stress in piglets and porcine intestinal epithelial cells (IPEC‐J2 cells). The results showed that diquat induced growth restriction and impaired intestinal barrier. The mitochondrial reactive oxygen species (ROS) was increased and mitochondrial membrane potential was decreased following diquat exposure. The ultrastructure of mitochondria and MAMs was also disturbed. Meanwhile, diquat upregulated endoplasmic reticulum stress marker protein and activated PERK pathway. Furthermore, loosening MAMs alleviated intestinal barrier injury, decrease of antioxidant enzyme activity and mitochondrial dysfunction induced by diquat in IPEC‐J2 cells, while tightening MAMs exacerbated diquat‐induced mitochondrial dysfunction. These results suggested that MAMs may be associated with the intestinal barrier injury and mitochondrial dysfunction induced by diquat in the jejunum of piglets.
Asiatic acid inhibits osteosarcoma cell migration and invasion via the AKT/Sp1/MMP1 axis
Authors: Law Yat‐Yin , Lee Hsiang‐Lin , Lin Chu‐Liang , Chen Pei‐Ni , Wang Pei‐Han , Hsieh Yi‐Hsien , Chen Chien‐Min
Published: April 2024

Osteosarcoma is a malignant bone tumor affecting adolescents and children. No effective treatment is currently available. Asiatic acid (AA), a triterpenoid compound found in Centella asiatica, possesses anti‐tumor, anti‐inflammatory, and anti‐oxidant properties in various types of tumor cells. This study aims to determine whether AA exerts antitumor effects in human osteosarcoma cells. Our results indicate that AA does not influence the viability, proliferative rate, or cell cycle phase of human osteosarcoma cells under non‐toxic conditions. AA suppressed osteosarcoma cell migration and invasion by down‐regulating matrix metalloproteinase 1 (MMP1) expression. Data in the TNMplot database suggested MMP1 expression was higher in osteosarcoma than in normal tissues, with associated clinical significance observed in osteosarcoma patients. Overexpression of MMP1 in osteosarcoma cells reversed the AA‐induced suppression of cell migration and invasion. AA treatment decreased the expression of specificity protein 1 (Sp1), while Sp1 overexpression abolished the effect of AA on MMP1 expression and cell migration and invasion. AA inhibited AKT phosphorylation, and treatment with a PI3K inhibitor (wortmannin) increased the anti‐invasive effect of AA on osteosarcoma cells via the p‐AKT/Sp1/MMP1 axis. Thus, AA exhibits the potential for use as an anticancer drug against human osteosarcoma.
Biological control effect of Trichoderma harzianum (Hypocreales: Hypocreaceae) against phytopathogens
Authors: Swathy Kannan , Nisha Vadesha , Vivekanandhan Perumal
Published: April 2024

Chemical pesticides are synthetic substances created to manage plant pests. Frequent chemical usage causes extensive damage to crops and contributes to pest resistance, leading to environmental contamination, harm to non‐target organisms, the emergence of pesticide‐resistant species, and potential health hazards for humans. The aim of this study is to isolate, identify, and characterize biocontrol agents Trichoderma harzianum and evaluate their effects on various plant phytopathogens. T. harzianum biocontrol effects were tested against various fungal phytopathogens, including Sclerotium rolfsii, Alternaria sp., Pythium aphanidermatum, Macrophomina phaseolina, Fusarium oxysporum, Helminthosporium sativum, and Aspergillus niger. The results clearly showed that, compared to the other Trichoderma species, TVK1 demonstrated the highest ability to suppress phytopathogens, with a growth inhibition rate of 2.48 cm per day. TVK2 grows at a rate of 1.96 cm per day, whereas TVK5 grows at a rate of 1.98 cm per day. The level of antifungal volatile organic compounds produced by TVK1 spores was higher against plant pathogens compared to the other species examined. This compound inhibits the growth of plant pathogens. T. harzianum can eliminate 100% of S. rolfsii pathogens and 100% of Alternaria sp. Pathogens were reduced by 92.02% for A. niger, 94% for F. oxysporum, 100% for P. aphanidermatum, 94.07% for H. sativum, and 100% for M. phaseolina. In a detached leaf assay, TVK1 inhibited the growth of pathogens in various plant leaves, including tomato, mustard, and eggplant, when compared to both the commercially available fungicide and the control. The study confirms that the isolate TVK1 can combat various phytopathogens. Early application of T. harzianum can reduce the risk of phytopathogenic attacks on leaves and promote plant growth.
Supporting Early Biliteracy in English‐Medium Classrooms: Initiatives for Family Engagement and Instructional Innovations
Authors: Stewart Mary Amanda (Mandy) , Abbasher Douha , Jaimes Melanie Aide Aguirre , Hughes Monica
Published: April 2024

Since many bilingual students do not have access to bilingual education, this article illustrates how to collaborate with families and create instructional innovations to support biliteracy for all young bilinguals. The authors implemented a Biliteracy Jumpstart for 6 weeks at the beginning of school year culminating in Family Biliteracy Day with one linguistically diverse Pre‐K classroom.
Evidence‐Based Practices to Enliven Integrated Reading‐to‐Writing Instruction
Authors: Mohr Kathleen A. J. , Jones Cindy D. , Chamberlain Kalie , DeCoursey Kara , Robertson Marla , Summers Catherine , Bagley Megan
Published: April 2024

Despite strong support for integrating reading and writing instruction, writing practice is often crowded out of the schedule in elementary classrooms. To promote increased emphasis on writing, a working group of literacy researchers highlights three writing goals and six research‐based reading‐to‐writing practices to enliven instruction with more integrated opportunities. The three featured goals are maximize reading–writing connections, increase student collaborative writing, and promote a classroom writing community. To achieve these goals, the authors highlight flexible, evidenced‐based writing activities to encourage genre diversity, goal‐setting, peer feedback, and cross‐curricular reading tasks. The collection of recommended practices has the potential to engage students and improve both reading and writing achievement.
Causal learning by infants and young children: From computational theories to language practices
Authors: Basch Samantha , Wang Su‐hua
Published: April 2024

Causal reasoning—the ability to reason about causal relations between events—is fundamental to understanding how the world works. This paper reviews two prominent theories on early causal learning and offers possibilities for theory bridging. Both theories grow out of computational modeling and have significant areas of overlap while differing in several respects. Explanation‐Based Learning (EBL) focuses on young infants' learning about causal concepts of physical objects and events, whereas Bayesian models have been used to describe causal reasoning beyond infancy across various concept domains. Connecting the two models offers a more integrated approach to clarifying the developmental processes in causal reasoning from early infancy through later childhood. We further suggest that everyday language practices offer a promising space for theory bridging. We provide a review of selective work on caregiver–child conversations, in particular, on the use of scaffolding language including causal talk and pedagogical questions. Linking the research on language practices to the two cognitive theories, we point out directions for further research to integrate EBL and Bayesian models and clarify how causal learning unfolds in real life.

This article is categorized under:

Psychology > Learning

Cognitive Biology > Cognitive Development