bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fetal growth restriction exhibits various mTOR signaling in different regions of mouse placentas with altered lipid metabolism
Authors: Dong Jie , Xu Qian , Qian Chenxi , Wang Lu , DiSciullo Alison , Lei Jun , Lei Hui , Yan Song , Wang Jingjing , Jin Ni , Xiong Yujing , Zhang Jianhua , Burd Irina , Wang Xiaohong 
Published: March 2024

AbstractFetal growth restriction (FGR) is a common complication of pregnancy and can have significant impact on obstetric and neonatal outcomes. Increasing evidence has shown that the inhibited mechanistic target of rapamycin (mTOR) signaling in placenta is associated with FGR. However, interpretation of existing research is limited due to inconsistent methodologies and varying understanding of the mechanism by which mTOR activity contributes to FGR. Hereby, we have demonstrated that different anatomic regions of human and mouse placentas exhibited different levels of mTOR activity in normal compared to FGR pregnancies. When using the rapamycin-induced FGR mouse model, we found that placentas of FGR pregnancies exhibited abnormal morphological changes and reduced mTOR activity in the decidual-junctional layer. Using transcriptomics and lipidomics, we revealed that lipid and energy metabolism was significantly disrupted in the placentas of FGR mice. Finally, we demonstrated that maternal physical exercise during gestation in our FGR mouse model was associated with increased fetal and placental weight as well as increased placental mTOR activity and lipid metabolism. Collectively, our data indicate that the inhibited placental mTOR signaling contributes to FGR with altered lipid metabolism in mouse placentas, and maternal exercise could be an effective method to reduce the occurrence of FGR or alleviate the adverse outcomes associated with FGR.
Graphical Abstract

Human and mouse placentas have different mTOR signaling activities in different anatomic regions in normal and FGR pregnancies.

Pregnant mice with FGR induced by rapamycin show smaller placentas, decreased mTOR activity in DJ layer of placenta and altered lipid metabolism.

Maternal exercise partially alleviates the abnormal outcomes of FGR model.
Modeling the effects of power efficient approximate multipliers in radio astronomy correlators
Authors: Kokkeler A. B. J. , Gillani G. A. , Boonstra A. J. 
Published: March 2024

AbstractLarge scale Radio Telescopes for Radio Astronomy highly depend on the availability of large (digital) processing capacities for imaging. Estimates concerning power efficiency for future Radio Telescopes lead to anticipated power consumption numbers beyond feasibility. To reduce the power budget, the use of approximate multipliers within the correlator is explored. A baseband equivalent executable model of a radio synthesis telescope is constructed to assess the effects of approximate multipliers. Besides ideal multipliers with floating point accuracy, the use of accurate 8-bit multipliers and 4 different types of approximate multipliers is explored. For each of these multipliers, the energy efficiency of an individual multiplier is known and used to determine the energy efficiency improvement of a correlator when using approximate multipliers. The effects of approximation are quantified by 3 metrics (Signal-to-Noise-Ratio (SNR), Spurious-Free-Dynamic-Range (SFDR) and Root-Mean-Square (RMS) level) derived from maps constructed by the executable model based on an empty sky with only a single point source. This is considered to be the worst case scenario. For illustration purposes, a more realistic input is processed by the model as well. The metrics have been determined based on different SNR levels at the input of each antenna element. For input SNR levels up to 10 dB, all types of approximate multipliers used in this paper can be exploited to improve energy efficiency of correlators, leading to a maximum energy reduction of 19 %. For input SNR values up to 30 dB an energy improvement up to 12 % can be achieved. These percentages are based on implementations in a 40nm low power IC technology at 1 GHz.
The Impact of EFL Learners’ Negative Emotional Orientations on (Un)Willingness to Communicate in In-person and Online L2 Learning Contexts
Authors: Solhi Mehdi 
Published: March 2024

AbstractThe present study explored how negative emotional orientations (i.e., anxiety, boredom, and demotivation) may contribute to English as a foreign language (EFL) learners’ willingness to communicate (WTC) in in-person and online classes. In doing so, a total of 290 university students majoring in English were recruited to fill in a set of scales. The structural equation modeling analysis indicated that foreign language classroom anxiety (FLA) and L2 demotivation have a direct impact on EFL learners’ in-person and online L2WTC. While L2 demotivation was the strongest significant predictor of learners’ in-person L2WTC, FLA was the strongest predictor of online L2WTC. Additionally, there was a positive correlation among FLA, L2 demotivation, and foreign language classroom boredom (FLB). While FLA demonstrated no direct impact on communication willingness, it exhibited significant indirect paths to in-person L2WTC via the full mediation of L2 demotivation and FLA . Although the result did not show any significant direct impact of FLB on online L2WTC, it had a small yet significant indirect path to online L2WTC through the full mediation of FLA. FLA also revealed indirect significant paths to online L2WTC through FLB and L2 demotivation. The implications for L2 teachers and teacher educators will be further discussed.
Homogenization of a Multivariate Diffusion with Semipermeable Interfaces
Authors: Aryasova Olga , Pavlyukevich Ilya , Pilipenko Andrey 
Published: March 2024

AbstractWe study the homogenization problem for a system of stochastic differential equations with local time terms that models a multivariate diffusion in the presence of semipermeable hyperplane interfaces with oblique penetration. We show that this system has a unique weak solution and determine its weak limit as the distances between the interfaces converge to zero. In the limit, the singular local times terms vanish and give rise to an additional regular interface-induced drift.
Alternative finance in bank-firm relationship: how does board structure affect the cost of debt?
Authors: Palmieri Egidio , Geretto Enrico F. , Polato Maurizio , Miani Stefano 
Published: March 2024

AbstractIn this paper, we examine the relationship between alternative finance and board structure on the cost of debt for firms, focusing on the unique effects of differing board characteristics. Using a dataset of 176 European listed companies observed annually from 2013 to 2022, we dissect this relationship through several hypotheses considering factors such as the supply of alternative finance, board gender composition, age, expertise, and board turnover. Our findings reveal that increased alternative finance credit supply escalates the cost of debt, especially for firms with lower ESG scores. Firms with young boards, boards specialized in economics or low, and board turnover also experience a rise in borrowing costs with increasing of alternative finance. Through a pooling 2SLS model, we provide robust evidence about the interplay of alternative finance and varying board structures on the cost of debt. This research clarifies the intricacies of bank-firm relationships in alternative finance and holds significant implications for supervisory authorities, banks, and policymakers. It underscores the necessity of good corporate governance in managing the cost implications of alternative finance. It calls for tailored risk assessment strategies, conducive regulatory frameworks, and vigilant supervisory approaches to create a resilient financial ecosystem where alternative finance can thrive without inordinately inflating the cost of debt.
New Insights on Bidirectional Associative Memory Neural Networks with Leakage Delay Components and Time-Varying Delays Using Sampled-Data Control
Authors: Chandra S. Ravi , Padmanabhan S. , Umesha V. , Ali M. Syed , Rajchakit Grienggrai , Jirawattanpanit Anuwat 
Published: March 2024

AbstractThe sampling data control of bidirectional associative memory (BAM) neural network with leakage delay is considered in this article. The BAM model is viewed as a mixed delay that combines a distributed delay, a discrete delay that varies over time, and a delay in the leaking period. The sampling system is then converted to a continuous time-delay system using an input delay method. In order to get adequate conditions in the form of linear matrix inequalities(LMIs), we build a new Lyapunov-Krasovskii Functional (LKF) in conjunction with the free weight matrix approach. Finally, a simulation results are given to show the efficiency of the theoretical approach.
Rethinking Zero-DCE for Low-Light Image Enhancement
Authors: Mi Aizhong , Luo Wenhui , Qiao Yingxu , Huo Zhanqiang 
Published: March 2024

AbstractZero-Reference Deep Curve Estimation (Zero-DCE) is currently one of the most popular low-light image enhancement methods. Through extensive experimentation, we observe that: (i) the excellent performance of Zero-DCE depends on the training data with multiple exposure levels, (ii) it cannot effectively handle uneven light, extremely low light, or overexposed images in natural environments. Therefore, we propose an improved zero-reference dual-illumination deep curve estimation method for low-light image enhancement named Zero-DiDCE, which can enhance, suppress, or maintain light levels for images. The adaptive light enhancement curve was designed to handle images with different exposure levels. An iterator and amplitude controller are designed to control the curve enhancement intensity by calculating the gap between the input image and the optimal light level. Furthermore, instead of the DCE-Net in Zero-DCE only taking the input image as network input, our DiDCE-Net in Zero-DiDCE takes the input image and the inverted input image simultaneously as network input to ensure that the training set contains samples with multiple exposure levels. A piecewise non-reference loss function is designed to guide the training of DiDCE-Net from the perspective of information loss. Qualitative and quantitative experiments show that our method can handle images with different levels of exposure well and outperforms state-of-the-art methods. In addition, the proposed curve and iterator can be integrated into other methods to improve their enhancement effects. The code is available at https://github.com/Wenhui-Luo/Zero-DiDCE.
Variation of peripheral blood-based biomarkers for response of anti-PD-1 immunotherapy in non-small-cell lung cancer
Authors: Wang Xiaoming , Chen Dayu , Ma Yuyan , Mo Dongping , Yan Feng 
Published: March 2024

Abstract
Purpose
Immune checkpoint inhibitors (ICIs) for non-small-cell lung cancer (NSCLC) are on the rise, but unfortunately, only a small percentage of patients benefit from them in the long term. Thus, it is crucial to identify biomarkers that can forecast the efficacy of immunotherapy.

Methods
We retrospectively studied 224 patients with NSCLC who underwent anti-PD-1 therapy. The role of biomarkers and clinical characteristics were assessed in a prognostic model.

Results
Only 14.3% of patients had both programmed death ligand 1 (PD-L1) and tumor mutational burden (TMB) outcomes, highlighting the need to investigate more available biomarkers. Our analysis found a correlation between histological PD-L1 TPS and hematological PD-1 expression. Analysis of hematological biomarkers revealed that elevated expression of CD4/CD8 and LYM% are positively associated with effective immunotherapy, while PD-1+ on T cells, NLR, and MLR have a negative impact. Moreover, high level of ΔCEA%, CYFRA21-1 and LDH may suggest ineffective ICIs. We also observed that disparate immunotherapy drugs didn’t significantly impact prognosis. Lastly, by comparing squamous carcinoma and adenocarcinoma cohorts, ΔCEA%, CD3+PD-1+, CD4+PD-1+, and CD4/CD8 are more important in predicting the prognosis of adenocarcinoma patients, while age is more significant for squamous carcinoma patients.

Conclusion
Our research has yielded encouraging results in identifying a correlation between immunotherapy’s response and clinical characteristics, peripheral immune cell subsets, and biochemical and immunological biomarkers. The screened hematological detection panel could be used to forecast an NSCLC patient’s response to anti-PD-1 immunotherapy with an accuracy rate of 76.3%, which could help customize suitable therapeutic decision-making.
NMR study of the structure and dynamics of the BRCT domain from the kinetochore protein KKT4
Authors: Ludzia Patryk , Hayashi Hanako , Robinson Timothy , Akiyoshi Bungo , Redfield Christina 
Published: March 2024

AbstractKKT4 is a multi-domain kinetochore protein specific to kinetoplastids, such as Trypanosoma brucei. It lacks significant sequence similarity to known kinetochore proteins in other eukaryotes. Our recent X-ray structure of the C-terminal region of KKT4 shows that it has a tandem BRCT (BRCA1 C Terminus) domain fold with a sulfate ion bound in a typical binding site for a phosphorylated serine or threonine. Here we present the 1H, 13C and 15N resonance assignments for the BRCT domain of KKT4 (KKT4463–645) from T. brucei. We show that the BRCT domain can bind phosphate ions in solution using residues involved in sulfate ion binding in the X-ray structure. We have used these assignments to characterise the secondary structure and backbone dynamics of the BRCT domain in solution. Mutating the residues involved in phosphate ion binding in T. brucei KKT4 BRCT results in growth defects confirming the importance of the BRCT phosphopeptide-binding activity in vivo. These results may facilitate rational drug design efforts in the future to combat diseases caused by kinetoplastid parasites.
The Voice of the People: Populism and Donald Trump’s Use of Informal Voice
Authors: Kjeldgaard-Christiansen Jens 
Published: March 2024

AbstractMany studies have examined characteristic verbal aspects of Donald J. Trump’s political communication, from his authoritarian rhetoric to his preference for short words and simple sentences, as expressions of his populism. This article focuses on his use of non-verbal voice quality. In analyzing the “Trump rallies” and other materials from his successful campaigning before the 2016 United States presidential election, I argue that Trump’s evocative and meaningful uses of pitch, amplitude, speech rate, rhythm, and other vocal measures combine to make his paralanguage exceptionally and counter-normatively informal, and that this informality amplifies his explicitly populist messaging. I conclude by suggesting that Trump’s informal voice solves an important problem for him: It allows him to express his populism with a deeply personal undertone, and thereby potentially to make his claims to popular identification ring intuitively true.
Well-being in late childhood and early adolescence: evolution and explanatory factors
Authors: González-Carrasco Mònica , Casas Ferran 
Published: March 2024

AbstractThis paper has three objectives (1) to test whether a decrease in well-being scores is observed from one year to the next in the period between 10 and 16 years of age when measured using indicators of subjective well-being (SWB) (including the OLS as a global measure) and psychological well-being (PWB); (2) to explore the contribution of the primary/secondary school, gender and age in explaining global SWB; and (3) to identify potential non-linear relationships between SWB, measured globally, and other indicators of SWB and PWB. To this end, data were analysed from 994 Spanish students, who responded to the same self-administered questionnaire over two consecutive school years and were recruited through a process of non-random sampling. The results obtained using Student’s t-test for repeated measures and generalized additive models (GAM) showed a statistically significant decrease in 10 out of the 20 indicators considered (more of which assess PWB than SWB), and that the indicators measuring the SWB affective component made a more relevant and less linear contribution to a global SWB measure than those measuring the cognitive component or the PWB.
Vocational Teachers’ Craft Knowledge and Working-life Experiences in Building and Construction: a Narrative Study of Embodied and Tacit Learning
Authors: Lensjø Marit 
Published: March 2024

AbstractVocational teachers in building and construction in upper secondary school deal with complex situations of an organisational, vocational, and social kind. Recent research has shown that the teacher is the single most important factor for students’ learning in school. Teacher-student relationships and the teacher’s repertoire of teaching practices can be more important for the student’s learning than class size, the classroom environment, and the student’s socio-economic background. Beyond passing the journeyman’s test, we know little about the craft knowledge and working life experiences vocational teachers in the building and construction trades have acquired over many years in the construction industry, and thus, what knowledge and experiences they bring into the vocational teacher role. Learning in working life often takes place as an integrated part of work, and it is difficult to observe how learning happens. Craft knowledge is often tacit and personal. In this narrative, phenomenologically inspired study, learning is investigated as a bodily, internal process that simultaneously depends on the interaction with the material and social environment. Through narrative interviews with eleven vocational teachers in plumbing and carpentry, this study explores the teachers’ backgrounds as vocational students and apprentices, and their extensive experience as craftsmen on different construction sites. The analysis shows that the building site drives craft-related actions and situations that generate a strong craft identity, professional working life experiences, and personal growth. Craftsmen at the construction site work under constant pressure in a social, physically, and mentally demanding work environment and consecutively solve problems. As professional craftsmen in the complex working environment, the teachers also acquired social and organisational expertise, which they intuitively transferred to their role as vocational teachers.
Processing Challenges and Delamination Prevention Methods in Titanium-Steel DED 3D Printing
Authors: Andreu Alberto , Kim Sanglae , Kim Insup , Kim Jeong-Hwan , Noh Jinhong , Lee Suhan , Lee Wonhee , Su Pei-Chen , Yoon Yong-Jin 
Published: March 2024

AbstractDirect Energy Deposition (DED) 3D printing has gained significant importance in various industries due to its ability to fabricate complex and functional parts with reduced material waste, and to repair existing components. Titanium alloys, known for their exceptional mechanical properties and biocompatibility, are widely used in DED 3D printing applications, where they offer benefits such as lightweight design possibilities and high strength-to-weight ratio. However, given the high material cost of titanium alloys, certain applications can benefit from the coating capabilities of DED to achieve the advantages of titanium on a distinct material substrate. Nevertheless, challenges related to material incompatibility and the development of unwanted brittle phases still affect the successful deposition of titanium alloys on steel substrates with DED 3D printing. This paper investigates the processing challenges and reviews delamination prevention methods, specifically targeting titanium-steel interfaces. In particular, the formation of unwanted brittle Ti–Fe intermetallics and methods to circumvent their formation are explored. The findings of this research contribute to a deeper understanding of the processing challenges and delamination prevention methods in DED 3D printing.
A behaviorally validated warm glow questionnaire
Authors: Carpenter Jeffrey , Lyford Alex , Zhang Mingfang 
Published: March 2024

AbstractMeasuring the social preferences of economic agents using experiments has become common place. This process, while incentive compatible, is costly and time consuming, making it infeasible in many settings. We combine standard altruism and warm glow choice experiments with a battery of candidate survey questions to construct behaviorally validated questionnaires. We use machine learning to create parsimonious 3-question modules that reliably replicate existing results on general altruism and provide an alternative method for collecting warm glow preferences.
An open science automatic workflow for multi-model species distribution estimation
Authors: Coro Gianpaolo , Sana Lorenzo , Bove Pasquale 
Published: March 2024

AbstractIntegrated Environmental Assessment systems and ecosystem models study the links between anthropogenic and climatic pressures on marine ecosystems and help understand how to manage the effects of the unsustainable exploitation of ocean resources. However, these models have long implementation times, data and model interoperability issues and require heterogeneous competencies. Therefore, they would benefit from simplification, automatisation, and enhanced integrability of the underlying models. Artificial Intelligence can help overcome several limitations by speeding up the modelling of crucial functional parts, e.g. estimating the environmental conditions fostering a species’ persistence and proliferation in an area (the species’ ecological niche) and, consequently, its geographical distribution. This paper presents a full-automatic workflow to estimate species’ distributions through statistical and machine learning models. It embeds four ecological niche models with complementary approaches, i.e. Artificial Neural Networks, Maximum Entropy, Support Vector Machines, and AquaMaps. It automatically estimates the optimal model parametrisations and decision thresholds to distinguish between suitable- and unsuitable-habitat locations and combines the models within one ensemble model. Finally, it combines several ensemble models to produce a species richness map (biodiversity index). The software is open-source, Open Science compliant, and available as a Web Processing Service-standardised cloud computing service that enhances efficiency, integrability, cross-domain reusability, and experimental reproduction and repetition. We first assess workflow stability and sensitivity and then demonstrate effectiveness by producing a biodiversity index for the Mediterranean based on$$\sim $$∼1500 species data. Moreover, we predict the spread of the invasiveSiganus rivulatusin the Mediterranean and its current and future overlap with the nativeSarpa salpaunder different climate change scenarios.
Green Electricity Prices
Authors: Hannesson Rögnvaldur 
Published: March 2024

AbstractThis paper examines the correlation between end-user electricity prices and the share of solar and wind energy in total electricity production in OECD countries. It is shown (i) that end-user prices in recent years (2020–2022) are positively correlated with the share of solar and wind and (ii) that the price of electricity in the majority of countries has risen with the solar and wind share since these types of energy came on the scene.