bluuebunny/crossref_metadata_2025 huggingface dataset:
Tailoring diamondised nanocarbon-loaded poly(lactic acid) composites for highly electroactive surfaces: extrusion and characterisation of filaments for improved 3D-printed surfaces
Authors: Cieślik Mateusz , Susik Agnieszka , Banasiak Mariusz , Bogdanowicz Robert , Formela Krzysztof , Ryl Jacek
Published: August 2023

A new 3D-printable composite has been developed dedicated to electroanalytical applications. Two types of diamondised nanocarbons - detonation nanodiamonds (DNDs) and boron-doped carbon nanowalls (BCNWs) - were added as fillers in poly(lactic acid) (PLA)-based composites to extrude 3D filaments. Carbon black served as a primary filler to reach high composite conductivity at low diamondised nanocarbon concentrations (0.01 to 0.2 S/cm, depending on the type and amount of filler). The aim was to thoroughly describe and understand the interactions between the composite components and how they affect the rheological, mechanical and thermal properties, and electrochemical characteristics of filaments and material extrusion printouts. The electrocatalytic properties of composite-based electrodes, fabricated with a simple 3D pen, were evaluated using multiple electrochemical techniques (cyclic and differential pulse voltammetry and electrochemical impedance spectroscopy). The results showed that the addition of 5 wt% of any of the diamond-rich nanocarbons fillers significantly enhanced the redox process kinetics, leading to lower redox activation overpotentials compared with carbon black–loaded PLA. The detection of dopamine was successfully achieved through fabricated composite electrodes, exhibiting lower limits of detection (0.12 μM for DND and 0.18 μM for BCNW) compared with the reference CB-PLA electrodes (0.48 μM). The thermogravimetric results demonstrated that both DND and BCNW powders can accelerate thermal degradation. The presence of diamondised nanocarbons, regardless of their type, resulted in a decrease in the decomposition temperature of the composite. The study provides insight into the interactions between composite components and their impact on the electrochemical properties of 3D-printed surfaces, suggesting electroanalytic potential.

Graphical abstract
Integrated planning for a global pharmaceutical supply chain: an ambidexterity perspective
Authors: Yousefi Sarmad Mahsa , Pishvaee Mir Saman , Jahani Hamed , Khaksar Seyed Mohammad Sadegh , Ivanov Dmitry
Published: August 2023

Based on the concept of ambidexterity, we develop a multi-objective, multi-product, and multi-period model to integrate planning for research and development (R&D) and production and distribution (P&D) in a global pharmaceutical supply chain (PSC) considering delays in the entire supply chain. We also propose robust possibilistic programming (RPP) approach to deal with the epistemic uncertainty of some critical input parameters. Applying the ambidexterity approach that emphasizes optimizing a balanced framework based on the R&D and P&D planning, our study reconciles the explorative and exploitative supply chain strategies in the context of global PSCs. The proposed integrated model can manage the inherent delays and uncertainties in the R&D processes and P&D systems via a novel, credibility-based, robust possibilistic programming model. We illustrate the application of our model using a real-world case study of one of the largest and most reputable pharmaceutical companies in Iran. The results affirm the credibility and feasibility of the proposed model when juxtaposed with a non-integrated model. Our study suggests the use of ambidexterity approach in resource allocation planning, risk management, and enhancement of performance in sophisticated settings such as global PSCs.
The Connection Between Sex as Self-Injury and Sexual Violence
Authors: Hedén Ludwig , Jonsson Linda S. , Fredlund Cecilia
Published: August 2023

Nonsuicidal self-injury (NSSI) is a suggested diagnosis recognized by DSM-5 as in need of further research. Recent studies conclude that sex as self-injury (SASI) and NSSI share similar functions, such as being used as emotional regulation. SASI has been associated with earlier sexual abuse, but the understanding of the association between sexual violence and SASI is still limited. The aim of this study was to further investigate the connection between sexual violence and the experience of SASI. How could SASI be related to sexual violence? The study used a qualitative design and was based on an anonymous questionnaire published on the websites of Swedish NGOs, providing help and support to women and youths, such as those in women’s shelters. In total, 139 informants with a mean age of 27.9 years (range 15–64 years) were included in the study. Three main themes were found: (1) Normalization of sexual violence and a shift in boundaries could be seen as consequences of earlier experiences of sexual violence leading to SASI; (2) SASI could escalate into sexual violence through increased need of emotional regulation, increased risk-taking, and risk of victimization; (3) SASI could be used to regain control of re-experiences, the body, sexuality, and shame after sexual abuse. In conclusion, a complex connection was identified whereby SASI could escalate into sexual violence, and earlier experiences of sexual violence could lead to SASI in a vicious loop. Hence, SASI should be seen as a risk factor for further victimization and sexual abuse.
The December 2020 magnitude (Mw) 6.4 Petrinja earthquake, Croatia: seismological aspects, emergency response and impacts
Authors: Atalić Josip , Demšić Marija , Baniček Maja , Uroš Mario , Dasović Iva , Prevolnik Snježan , Kadić Alen , Šavor Novak Marta , Nastev Miroslav
Published: August 2023

On December 29, 2020, nine months after the March Mw 5.4 Zagreb earthquake and amidst the COVID-19 lockdown, a devastating Mw 6.4 earthquake struck near the town of Petrinja, about 50 km SE from the country’s capital Zagreb. It was preceded by the Mw 4.9 foreshock from the day before. The main shock claimed 7 fatalities and caused widespread damage. Historical centers of nearby cities with invaluable heritage buildings were significantly affected as were the many residential buildings, built mainly of unreinforced masonry. Damage was observed as far as 60 km from the epicenter. This paper summarizes the seismological aspects of the Mw 6.4 Petrinja earthquake, the emergency response and the main impacts to people and buildings. The description and findings are based on the field observations and a series of post-earthquake activities led by the team of the Faculty of Civil Engineering, University of Zagreb. Typical damage to buildings and usability data are presented with examples based on 50,000 inspection results. By far the most affected were the unreinforced masonry buildings, followed by confined masonry, whereas reinforced concrete buildings were the least affected. The total direct and indirect losses are estimated to 4.8 billion EUR. The provided information represents a useful basis and impetus for improving emergency action and long-term disaster reduction plans in other regions with similar building exposure and seismotectonic settings.
SALτ: efficiently stopping TAR by improving priors estimates
Authors: Molinari Alessio , Esuli Andrea
Published: August 2023

In high recall retrieval tasks, human experts review a large pool of documents with the goal of satisfying an information need. Documents are prioritized for review through an active learning policy, and the process is usually referred to as Technology-Assisted Review (TAR). TAR tasks also aim to stop the review process once the target recall is achieved to minimize the annotation cost. In this paper, we introduce a new stopping rule called SAL$$_\tau ^R$$τR(SLD for Active Learning), a modified version of the Saerens–Latinne–Decaestecker algorithm (SLD) that has been adapted for use in active learning. Experiments show that our algorithm stops the review well ahead of the current state-of-the-art methods, while providing the same guarantees of achieving the target recall.
Climate labels and the restaurant industry: a qualitative study
Authors: Gay Anne-Sophie , Warden Julia M. , Lane Hakan
Published: August 2023

As the food industry accounts for more than one-third of global anthropogenic greenhouse gas emissions, it is one of the largest contributors to climate change. Strategies for reducing CO2e (equivalent) emissions must be implemented to regulate the impact the food systems have on the climate. Environmental communication using climate labels and sharing information on carbon footprints can help reduce GHGs emissions from restaurant purchases on a systemic scale. The aim is to gain insights and study how a carbon label influences the concept of a climate-friendly restaurant and its capacity to bridge the gap between knowledge, awareness, and action. What are the motivations for restaurant employees to adopt climate-friendly behavior? How does the label’s use influence restaurants’ decision to track their carbon footprint over time, communicate the carbon footprint of dishes, and adapt menus to be more climate-friendly? The data were collected with semi-structured interviews with video communication with three restaurant chains, all using labels. The data collected via the interviews were examined using an inductive thematic analysis to identify key themes. The transcending transmission approach to communication was used to gain insights into instrumental and constitutive communication dynamics. As the theoretical framework, ‘symbolic interactionism’ helps untangle constitutive aspects of environmental communication surrounding climate labels to analyze the process of conceptualization through usage, co-creation, and interpretation. The analysis brought forward three main themes: the interactions between the scientific data accessible in the tool and the restaurants. Second, the diverse implications of sustainability marketing for motivating climate actions and what they look like. And finally, climate actions and how they are being apprehended and implemented by the restaurants. The promise of climate labels was discussed by elaborating on socio-cultural dynamics, sustainability marketing, and activism forces and impulses influencing the motivations for restaurants. We then discussed the capacity to transcend information into action through collaboration and inclusiveness to avoid greenwashing. Restaurants have a commercial interest in implementing climate labels in their business and an intrinsic desire to be a company that takes action for the planet because of the restaurants ‘employees’ convictions. However, restaurants find themselves in a tricky situation where they can be criticized if they take ‘wrong’ actions that can be considered greenwashing and criticized if they do nothing. The software enables restaurants to legitimize their actions and communicate them, making them resilient and evolving.
“I’m Not Teaching Them Per Se”: Designing and Delivering Asynchronous Undergraduate Online STEM Courses
Authors: Garza Mitchell Regina L. , DeCamp Whitney , Horvitz Brian S. , Kowalske Megan Grunert , Singleton Cherrelle
Published: August 2023

Although online courses have been a part of academia for nearly 30 years, they are still perceived as “different” than face-to-face instruction. Through in-depth interviews with four instructors, we explored how STEM faculty approach teaching asynchronous online undergraduate STEM courses. The faculty interviewed for this study viewed online courses as “not regular class[es]” and teaching those classes as “not teaching per se.” Each of the instructors had assumptions about what a classroom was and about good instruction, but even for instructors who taught online for multiple years, those assumptions remained grounded in the face-to-face environment. There is a need for greater discussion about what it means to teach in an online environment.
Derangements in wreath products of permutation groups
Authors: Arumugam Vishnuram , Dietrich Heiko , Glasby S. P.
Published: August 2023

Given a finite group G acting on a set X let $$\delta _k(G,X)$$

δ
k

(
G
,
X
)

denote the proportion of elements in G that have exactly k fixed points in X. Let $$\mathcal {S}_n$$

S
n

denote the symmetric group acting on $$[n]=\{1,2,\dots ,n\}$$

[
n
]
=
{
1
,
2
,
⋯
,
n
}

. For $$A\leqslant \mathcal {S}_m$$

A
⩽

S
m

and $$B\leqslant \mathcal {S}_n$$

B
⩽

S
n

, the permutational wreath product $$A\wr B$$

A
≀
B

has two natural actions and we give formulas for both, $$\delta _k(A\wr B,[m]{\times }[n])$$

δ
k

(
A
≀
B
,

[
m
]

×

[
n
]

)

and $$\delta _k(A\wr B,[m]^{[n]})$$

δ
k

(
A
≀
B
,

[
m
]

[
n
]

)

. We prove that for $$k=0$$

k
=
0

the values of these proportions are dense in the intervals $$[\delta _0(B,[n]),1]$$

[

δ
0

(
B
,

[
n
]

)

,
1
]

and $$[\delta _0(A,[m]),1]$$

[

δ
0

(
A
,

[
m
]

)

,
1
]

. Among further results, we provide estimates for $$\delta _0(G,[m]^{[n]})$$

δ
0

(
G
,

[
m
]

[
n
]

)

for subgroups $$G\leqslant \mathcal {S}_m\wr \mathcal {S}_n$$

G
⩽

S
m

≀

S
n

containing $$\mathcal {A}_m^{[n]}$$

A
m

[
n
]

.
Personality trait analysis during the COVID-19 pandemic: a comparative study on social media
Authors: Fernández-Pichel Marcos , Aragón Mario Ezra , Saborido-Patiño Julián , Losada David E.
Published: August 2023

The COVID-19 pandemic, a global contagion of coronavirus infection caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has triggered severe social and economic disruption around the world and provoked changes in people’s behavior. Given the extreme societal impact of COVID-19, it becomes crucial to understand the emotional response of the people and the impact of COVID-19 on personality traits and psychological dimensions. In this study, we contribute to this goal by thoroughly analyzing the evolution of personality and psychological aspects in a large-scale collection of tweets extracted during the COVID-19 pandemic. The objectives of this research are: i) to provide evidence that helps to understand the estimated impact of the pandemic on people’s temperament, ii) to find associations and trends between specific events (e.g., stages of harsh confinement) and people’s reactions, and iii) to study the evolution of multiple personality aspects, such as the degree of introversion or the level of neuroticism. We also examine the development of emotions, as a natural complement to the automatic analysis of the personality dimensions. To achieve our goals, we have created two large collections of tweets (geotagged in the United States and Spain, respectively), collected during the pandemic. Our work reveals interesting trends in personality dimensions, emotions, and events. For example, during the pandemic period, we found increasing traces of introversion and neuroticism. Another interesting insight from our study is that the most frequent signs of personality disorders are those related to depression, schizophrenia, and narcissism. We also found some peaks of negative/positive emotions related to specific events.
Bespoke Energetic Zeolite Imidazolate Frameworks-8 (ZIF-8)/Ammonium Perchlorate Nanocomposite: A Novel Reactive Catalyzed High Energy Dense Material with Superior Decomposition Kinetics
Authors: Attwa Mohamed , Said Ali , ElGamal M. , El-Shaer Yasser , Elbasuney Sherif
Published: August 2023

Aluminum is the universal fuel for solid propellants; however, its passive oxide layer could impede the full exploitation of its enthalpy. Meanwhile, common catalyst could not contribute to combustion enthalpy. This study shaded light on the multifunctional energetic metal-organic frameworks ZIF-8 with combustion enthalpy 21 KJ/g as high energy dense material as well as a novel catalyst for solid propellants. As-prepared ZIF-8 particles exhibited a highly crystalline structure with an average particle size of 40 nm. The performance of ZIF-8 as high-energy dense material was assessed to aluminum particles via integration into ammonium perchlorate (APC). ZIF-8/APC and Al/APC composites were prepared via the solvent–nonsolvent method; the decomposition enthalpy was investigated via DSC. ZIF-8 offered an increase in APC total decomposition enthalpy by 98.4%, to 39.11% for Al. ZIF-8 exhibited a superior catalytic behavior by lowering the APC high-temperature decomposition peak (HTD) by 81.48 °C compared to 70.3 °C for Al. The decomposition kinetics of ZIF-8/AP nanocomposite was investigated via Kissinger’s formula. The ZIF-8 offered a remarkable reduction in APC apparent activation energy at low-temperature decomposition peak and HTD peaks by peak by 16.5% and 30%, respectively. The superior catalytic performance of ZIF-8 was attributed to Zn+2 electron deficient centers with the exclusive formation of ZnO nanoparticles during combustion. ZIF-8 with gaseous decomposition products could boost specific impulses.
Polynomial Total Positivity and High Relative Accuracy Through Schur Polynomials
Authors: Díaz P. , Mainar E. , Rubio B.
Published: August 2023

In this paper, Schur polynomials are used to provide a bidiagonal decomposition of polynomial collocation matrices. The symmetry of Schur polynomials is exploited to analyze the total positivity on some unbounded intervals of a relevant class of polynomial bases. The proposed factorization is used to achieve relative errors of the order of the unit round-off when solving algebraic problems involving the collocation matrix of relevant polynomial bases, such as the Hermite basis. The numerical experimentation illustrates the accurate results obtained when using the findings of the paper.
Local look-up table upsampling for accelerating image processing
Authors: Tsubokawa Teppei , Tajima Hiroshi , Maeda Yoshihiro , Fukushima Norishige
Published: August 2023

The resolution of cameras is increasing, and speedup of various image processing is required to accompany this increase. A simple way of acceleration is processing the image at low resolution and then upsampling the result. Moreover, when we can use an additional high-resolution image as guidance formation for upsampling, we can upsample the image processing results more accurately. We propose an approach to accelerate various image processing by downsampling and joint upsampling. This paper utilizes per-pixel look-up tables (LUTs), named local LUT, which are given a low-resolution input image and output pair. Subsequently, we upsample the local LUT. We can then generate a high-resolution image only by referring to its local LUT. In our experimental results, we evaluated the proposed method on several image processing filters and applications: iterative bilateral filtering, $$\ell _0$$

ℓ
0

smoothing, local Laplacian filtering, inpainting, and haze removing. The proposed method accelerates image processing with sufficient approximation accuracy, and the proposed outperforms the conventional approaches in the trade-off between accuracy and efficiency. Our code is available at https://fukushimalab.github.io/LLF/.
Improving the generalization capability of YOLOv5 on remote sensed insect trap images with data augmentation
Authors: Suto Jozsef
Published: August 2023

In agricultural pest management, the traditional insect population tracking in the case of several insect types is based on outsourced sticky paper traps that are checked periodically by a human operator. However, with the aid of the Internet of Things technology and machine learning, this type of manual monitoring can be automated. Even though great progress has been made in the field of insect pest detector models, the lack of sufficient amount of remote sensed trap images prevents their practical application. Beyond the lack of sufficient data, another issue is the large discrepancy between manually taken and remote sensed trap images (different illumination, quality, background, etc.). In order to improve those problems, this paper proposes three previously unused data augmentation approaches (gamma correction, bilateral filtering, and bit-plate slicing) which artificially enrich the training data and through this increase the generalization capability of deep object detectors on remote sensed trap images. Even with the application of the widely used geometric and texture-based augmentation techniques, the proposed methods can further increase the efficiency of object detector models. To demonstrate their efficiency, we used the Faster Region-based Convolutional Neural Network (R-CNN) and the You Look Only Once version 5 (YOLOv5) object detectors which have been trained on a small set of high-resolution, manually taken trap images while the test set consists of remote sensed images. The experimental results showed that the mean average precision (mAP) of the reference models significantly improved while in some cases their counting error was reduced to a third.
Zinc oxide nanoparticles and PGPR strengthen salinity tolerance and productivity of wheat irrigated with saline water in sodic-saline soil
Authors: Alharbi Khadiga , Hafez Emad M. , Omara Alaa El-Dein , Rashwan Emadelden , Alshaal Tarek
Published: August 2023

Background and aims

Wheat growth and productivity need an exceptional approach to resist the deleterious effects of salt stress.

Methods

This study proposed to assess the effectiveness of the exogenous application of plant growth-promoting rhizobacteria (PGPR; i.e., Azospirillum lipoferum SP2, Bacillus coagulans NCAIM B.01123, Bacillus circulance NCAIM B.02324, and Bacillus subtilis MF497446) at a rate of 950 g ha−1 and foliar application of zinc oxide nanoparticles (ZnO-NPs; 500 mg L−1) against irrigation with saline (from a groundwater well) and fresh water (from the Nile River water) of wheat (Triticum aestivum L.) in sodic-saline soil during 2021 and 2022 growing seasons under open field conditions.

Results

The integrated application of PGPR and ZnO-NPs protected wheat plants against irrigation with saline water through increasing antioxidant enzyme activities, i.e., catalase (47%), peroxidase (102%), and superoxide dismutase (106%), and K+ uptake (27%) over control. Conversely, higher stress mitigation through the integrated application was illustrated by a considerable decline in electrolyte leakage (−62%), proline (−39%), MDA (−56%), and H2O2 levels (−60%). The N uptake by wheat grains increased by 57% upon treating plants with PGPR+ZnO-NPs, which also increased the Zn contents in grain and straw by 117% and 72%, respectively. Also, PGPR+ZnO-NPs increased the activity of soil urease and dehydrogenase by 80% and 232%, respectively, in plots irrigated with saline water.

Conclusion

The results of the present investigation suggest the use of the integrated application of PGPR and ZnO-NPs to protect wheat plants against salinity of soil and/ or irrigation water.
Estimating and Using Block Information in the Thurstonian IRT Model
Authors: Frick Susanne
Published: August 2023

Multidimensional forced-choice (MFC) tests are increasing in popularity but their construction is complex. The Thurstonian item response model (Thurstonian IRT model) is most often used to score MFC tests that contain dominance items. Currently, in a frequentist framework, information about the latent traits in the Thurstonian IRT model is computed for binary outcomes of pairwise comparisons, but this approach neglects stochastic dependencies. In this manuscript, it is shown how to estimate Fisher information on the block level. A simulation study showed that the observed and expected standard errors based on the block information were similarly accurate. When local dependencies for block sizes <mml:math xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mnf="http://cambridge.org/core/manifest" xmlns:cup="http://contentservices.cambridge.org" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:m="http://cambridge.org/core/metadata" xmlns:core="http://cambridge.org/core" xmlns:c="http://cambridge.org/core/content">>2\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$>\,2$$\end{document} were neglected, the standard errors were underestimated, except with the maximum a posteriori estimator. It is shown how the multidimensional block information can be summarized for test construction. A simulation study and an empirical application showed small differences between the block information summaries depending on the outcome considered. Thus, block information can aid the construction of reliable MFC tests.
New trend in artificial intelligence-based assistive technology for thoracic imaging
Authors: Yanagawa Masahiro , Ito Rintaro , Nozaki Taiki , Fujioka Tomoyuki , Yamada Akira , Fujita Shohei , Kamagata Koji , Fushimi Yasutaka , Tsuboyama Takahiro , Matsui Yusuke , Tatsugami Fuminari , Kawamura Mariko , Ueda Daiju , Fujima Noriyuki , Nakaura Takeshi , Hirata Kenji , Naganawa Shinji
Published: August 2023

Although there is no solid agreement for artificial intelligence (AI), it refers to a computer system with intelligence similar to that of humans. Deep learning appeared in 2006, and more than 10 years have passed since the third AI boom was triggered by improvements in computing power, algorithm development, and the use of big data. In recent years, the application and development of AI technology in the medical field have intensified internationally. There is no doubt that AI will be used in clinical practice to assist in diagnostic imaging in the future. In qualitative diagnosis, it is desirable to develop an explainable AI that at least represents the basis of the diagnostic process. However, it must be kept in mind that AI is a physician-assistant system, and the final decision should be made by the physician while understanding the limitations of AI. The aim of this article is to review the application of AI technology in diagnostic imaging from PubMed database while particularly focusing on diagnostic imaging in thorax such as lesion detection and qualitative diagnosis in order to help radiologists and clinicians to become more familiar with AI in thorax.
Abnormal Brain Protein Abundance and Cross-tissue mRNA Expression in Amyotrophic Lateral Sclerosis
Authors: Ma Yanni , Jia Tingting , Qin Fengqin , He Yongji , Han Feng , Zhang Chengcheng
Published: August 2023

Due to the limitations of the present risk genes in understanding the etiology of amyotrophic lateral sclerosis (ALS), it is necessary to find additional causative genes utilizing novel approaches. In this study, we conducted a two-stage proteome-wide association study (PWAS) using ALS genome-wide association study (GWAS) data (N = 152,268) and two distinct human brain protein quantitative trait loci (pQTL) datasets (ROSMAP N = 376 and Banner N = 152) to identify ALS risk genes and prioritized candidate genes with Mendelian randomization (MR) and Bayesian colocalization analysis. Next, we verified the aberrant expression of risk genes in multiple tissues, including lower motor neurons, skeletal muscle, and whole blood. Six ALS risk genes (SCFD1, SARM1, TMEM175, BCS1L, WIPI2, and DHRS11) were found during the PWAS discovery phase, and SARM1 and BCS1L were confirmed during the validation phase. The following MR (p = 2.10 × 10−7) and Bayesian colocalization analysis (ROSMAP PP4 = 0.999, Banner PP4 = 0.999) confirmed the causal association between SARM1 and ALS. Further differential expression analysis revealed that SARM1 was markedly downregulated in lower motor neurons (p = 7.64 × 10−3), skeletal muscle (p = 9.34 × 10−3), and whole blood (p = 1.94 × 10−3). Our findings identified some promising protein candidates for future investigation as therapeutic targets. The dysregulation of SARM1 in multiple tissues provides a new way to explain ALS pathology.
Digital competences of teachers in the use of YouTube as an educational resource: analysis by educational stage and gender
Authors: Basgall Lauren , Guillén-Gámez Francisco D. , Colomo-Magaña Ernesto , Cívico-Ariza Andrea
Published: August 2023

The purpose of this study was to analyze the digital competence of teachers on the use of YouTube as a didactic resource in the teaching and learning process of students. Specifically, this was analyzed and compared for each educational stage (Preschool Education, Primary Education, Secondary Education, Adult Education, and Vocational Education-VET) between genders of the teacher (female and male). For this, an ex post facto non-experimental design was used, with a sample of 2157 in-service teachers from all over Spain. Among the main results found in this study, teachers of all educational stages had satisfactory skills on the use of YouTube to search and communicate information, although low in relation to the creation of audio-visual material through YouTube. In addition, it was evidenced how gender was a significant factor which affected the competencies of teachers, in most of the educational stages analyzed.
RBFOX2 recognizes N6-methyladenosine to suppress transcription and block myeloid leukaemia differentiation
Authors: Dou Xiaoyang , Xiao Yu , Shen Chao , Wang Kitty , Wu Tong , Liu Chang , Li Yini , Yu Xianbin , Liu Jun , Dai Qing , Pajdzik Kinga , Ye Chang , Ge Ruiqi , Gao Boyang , Yu Jianhua , Sun Shuying , Chen Mengjie , Chen Jianjun , He Chuan
Published: August 2023

N6-methyladenosine (m6A) methylation can be deposited on chromatin-associated RNAs (caRNAs) by the RNA methyltransferase complex (MTC) to regulate chromatin state and transcription. However, the mechanism by which MTC is recruited to distinct genomic loci remains elusive. Here we identify RBFOX2, a well-studied RNA-binding protein, as a chromatin factor that preferentially recognizes m6A on caRNAs. RBFOX2 can recruit RBM15, an MTC component, to facilitate methylation of promoter-associated RNAs. RBM15 also physically interacts with YTHDC1 and recruits polycomb repressive complex 2 (PRC2) to the RBFOX2-bound loci for chromatin silencing and transcription suppression. Furthermore, we found that this RBFOX2/m6A/RBM15/YTHDC1/PRC2 axis plays a critical role in myeloid leukaemia. Downregulation of RBFOX2 notably inhibits survival/proliferation of acute myeloid leukaemia cells and promotes their myeloid differentiation. RBFOX2 is also required for self-renewal of leukaemia stem/initiation cells and acute myeloid leukaemia maintenance. Our study presents a pathway of m6A MTC recruitment and m6A deposition on caRNAs, resulting in locus-selective chromatin regulation, which has potential therapeutic implications in leukaemia.
Natriuresis-guided diuretic therapy in acute heart failure: a pragmatic randomized trial
Authors: ter Maaten Jozine M. , Beldhuis Iris E. , van der Meer Peter , Krikken Jan A. , Postmus Douwe , Coster Jenifer E. , Nieuwland Wybe , van Veldhuisen Dirk J. , Voors Adriaan A. , Damman Kevin
Published: August 2023

Measurement of natriuresis has been suggested as a reliable, easily obtainable biomarker for assessment of the response to diuretic treatment in patients with acute heart failure (AHF). Here, to assess whether natriuresis-guided diuretic therapy in patients with AHF improves natriuresis and clinical outcomes, we conducted the pragmatic, open-label Pragmatic Urinary Sodium-based algoritHm in Acute Heart Failure trial, in which 310 patients (45% female) with AHF requiring treatment with intravenous loop diuretics were randomly assigned to natriuresis-guided therapy or standard of care (SOC). In the natriuresis-guided arm, natriuresis was determined at set timepoints, prompting treatment intensification if spot urinary sodium levels were <70 mmol l−1. The dual primary endpoints were 24 h urinary sodium excretion and a combined endpoint of time to all-cause mortality or adjudicated heart failure rehospitalization at 180 days. The first primary endpoint was met, as natriuresis in the natriuresis-guided and SOC arms was 409 ± 178 mmol arm versus 345 ± 202 mmol, respectively (P = 0.0061). However, there were no significant differences between the two arms for the combined endpoint of time to all-cause mortality or first heart failure rehospitalization, which occurred in 46 (31%) and 50 (31%) of patients in the natriuresis-guided and SOC arms, respectively (hazard ratio 0.92 [95% confidence interval 0.62–1.38], P = 0.6980). These findings suggest that natriuresis-guided therapy could be a first step towards personalized treatment of AHF. ClinicalTrials.gov registration: NCT04606927.
Propagation of activity through the cortical hierarchy and perception are determined by neural variability
Authors: Rowland James M. , van der Plas Thijs L. , Loidolt Matthias , Lees Robert M. , Keeling Joshua , Dehning Jonas , Akam Thomas , Priesemann Viola , Packer Adam M.
Published: August 2023

Brains are composed of anatomically and functionally distinct regions performing specialized tasks, but regions do not operate in isolation. Orchestration of complex behaviors requires communication between brain regions, but how neural dynamics are organized to facilitate reliable transmission is not well understood. Here we studied this process directly by generating neural activity that propagates between brain regions and drives behavior, assessing how neural populations in sensory cortex cooperate to transmit information. We achieved this by imaging two densely interconnected regions—the primary and secondary somatosensory cortex (S1 and S2)—in mice while performing two-photon photostimulation of S1 neurons and assigning behavioral salience to the photostimulation. We found that the probability of perception is determined not only by the strength of the photostimulation but also by the variability of S1 neural activity. Therefore, maximizing the signal-to-noise ratio of the stimulus representation in cortex relative to the noise or variability is critical to facilitate activity propagation and perception.
A weighted-sum chaotic sparrow search algorithm for interdisciplinary feature selection and data classification
Authors: Jia LiYun , Wang Tao , Gad Ahmed G. , Salem Ahmed
Published: August 2023

In today’s data-driven digital culture, there is a critical demand for optimized solutions that essentially reduce operating expenses while attempting to increase productivity. The amount of memory and processing time that can be used to process enormous volumes of data are subject to a number of limitations. This would undoubtedly be more of a problem if a dataset contained redundant and uninteresting information. For instance, many datasets contain a number of non-informative features that primarily deceive a given classification algorithm. In order to tackle this, researchers have been developing a variety of feature selection (FS) techniques that aim to eliminate unnecessary information from the raw datasets before putting them in front of a machine learning (ML) algorithm. Meta-heuristic optimization algorithms are often a solid choice to solve NP-hard problems like FS. In this study, we present a wrapper FS technique based on the sparrow search algorithm (SSA), a type of meta-heuristic. SSA is a swarm intelligence (SI) method that stands out because of its quick convergence and improved stability. SSA does have some drawbacks, like lower swarm diversity and weak exploration ability in late iterations, like the majority of SI algorithms. So, using ten chaotic maps, we try to ameliorate SSA in three ways: (i) the initial swarm generation; (ii) the substitution of two random variables in SSA; and (iii) clamping the sparrows crossing the search range. As a result, we get CSSA, a chaotic form of SSA. Extensive comparisons show CSSA to be superior in terms of swarm diversity and convergence speed in solving various representative functions from the Institute of Electrical and Electronics Engineers (IEEE) Congress on Evolutionary Computation (CEC) benchmark set. Furthermore, experimental analysis of CSSA on eighteen interdisciplinary, multi-scale ML datasets from the University of California Irvine (UCI) data repository, as well as three high-dimensional microarray datasets, demonstrates that CSSA outperforms twelve state-of-the-art algorithms in a classification task based on FS discipline. Finally, a 5%-significance-level statistical post-hoc analysis based on Wilcoxon’s signed-rank test, Friedman’s rank test, and Nemenyi’s test confirms CSSA’s significance in terms of overall fitness, classification accuracy, selected feature size, computational time, convergence trace, and stability.
Disturbance intensification is altering the trait composition of Caribbean reefs, locking them into a low functioning state
Authors: Mudge Laura , Bruno John F.
Published: August 2023

Anthropogenic climate change is intensifying natural disturbance regimes, which negatively affects some species, while benefiting others. This could alter the trait composition of ecological communities and influence resilience to disturbance. We investigated how the frequency and intensification of the regional storm regime (and likely other disturbances) is altering coral species composition and in turn resistance and recovery. We developed regional databases of coral cover and composition (3144 reef locations from 1970 to 2017) and of the path and strength of cyclonic storms in the region (including 10,058 unique storm-reef intersections). We found that total living coral cover declined steadily through 2017 (the median annual loss rate was ~ 0.25% per year). Our results also indicate that despite the observed increase in the intensity of Atlantic cyclonic storms, their effect on coral cover has decreased markedly. This could be due in part to selection for disturbance-resistant taxa in response to the intensifying disturbance regime. We found that storms accelerated the loss of threatened acroporid corals but had no measurable effect on the cover of more resilient “weedy” corals, thereby increasing their relative cover. Although resistance to disturbance has increased, recovery rates have slowed due to the dominance of small, slow-growing species. This feedback loop is locking coral communities into a low-functioning state dominated by weedy species with limited ecological or societal value.
Bioinspired palladium-doped manganese oxide nanocorns: a remarkable antimicrobial agent targeting phyto/animal pathogens
Authors: Vikal Sagar , Gautam Yogendra K. , Kumar Ashwani , Kumar Ajay , Singh Jyoti , Pratap Dharmendra , Singh Beer Pal , Singh Neetu
Published: August 2023

Microbial pathogens are known for causing great environmental stress, owing to which emerging challenges like lack of eco-friendly remediation measures, development of drug-resistant and mutational microbial strains, etc., warrants novel and green routes as a stepping stone to serve such concerns sustainably. In the present study, palladium (Pd) doped manganese (II, III) oxide (Mn3O4) nanoparticles (NPs) were synthesized using an aqueousSyzygium aromaticumbud (ASAB) extract. Preliminary phytochemical analysis of ASAB extract indicates the presence of polyphenolics such as phenols, alkaloids, and flavonoids that can act as potential capping agents in NPs synthesis, which was later confirmed in FTIR analysis of pure and Pd-doped Mn3O4NPs. XRD, Raman, and XPS analyses confirmed the Pd doping in Mn3O4NPs. FESEM and HRTEM study reveals the mixed morphologies dominated by nanocorns appearance. Zeta potential investigation reveals high stability of the synthesized NPs in colloidal solutions. The developed Pd-doped Mn3O4NPs were tested against two fungal phytopathogens, i.e.,Sclerotinia sclerotiorumandColletotrichum gloeosporioides, known for causing great economic losses in yield and quality of different plant species. The antifungal activity of synthesized Pd‐doped Mn3O4NPs displayed a dose‐dependent response with a maximum of ~92%, and ~72% inhibition was recorded againstS. sclerotiorumandC. gloeosporioides, respectively, at 1000 ppm concentration. However,C. gloeosporioidesdemonstrated higher sensitivity to Pd‐doped Mn3O4NPs upto 500 ppm) treatment thanS. sclerotiorum. The prepared NPs also showed significant antibacterial activity againstEnterococcus faecalis. The Pd-doped Mn3O4NPs were effective even at low treatment doses, i.e., 50–100 ppm, with the highest Zone of inhibition obtained at 1000 ppm concentration. Our findings provide a novel, eco-benign, and cost-effective approach for formulating a nanomaterial composition offering multifaceted utilities as an effective antimicrobial agent.
Indoxyl sulfate induces apoptosis in mononuclear blood cells via mitochondrial pathway
Authors: Pieniazek Anna , Bernasinska-Slomczewska Joanna , Hikisz Pawel
Published: August 2023

The consequence of chronic kidney disease is the accumulation of metabolic products called uremic toxins in the body. Indoxyl sulfate (IS) is a toxin with a high affinity for proteins. This study focuses on the deleterious effect of IS, especially apoptosis induction, in mononuclear blood cells (MNCs). Thus, in MNCs treated with IS at three different concentrations for 24 h, the survival, mitochondrial potential, caspases activity and expression, Bcl-2 and Bax protein expression, DNA damage, and PARP degradation were estimated. The study showed a decrease in survival and mitochondrial potential of MNCs treated with IS compared to the control. IS increased the activity of caspase 2-, 3-, 9-, and the expression of caspase 3-, and 9- in MNCs but does not affect the activity of caspase 6- and 8. The treatment of MNCs with IS also increased DNA damage and degradation of PARP. Indoxyl sulfate significantly influences the expression of Bcl-2 and Bax proteins. Indoxyl sulfate induces the programmed death of MNCs through the intrinsic mitochondrial apoptotic pathway. The observed cellular changes are mostly dose-dependent.
New mutation in the β1 propeller domain of LRP4 responsible for congenital myasthenic syndrome associated with Cenani–Lenz syndrome
Authors: Masingue Marion , Cattaneo Olivia , Wolff Nicolas , Buon Céline , Sternberg Damien , Euchparmakian Morgane , Boex Myriam , Behin Anthony , Mamchaouhi Kamel , Maisonobe Thierry , Nougues Marie-Christine , Isapof Arnaud , Fontaine Bertrand , Messéant Julien , Eymard Bruno , Strochlic Laure , Bauché Stéphanie
Published: August 2023

Congenital myasthenic syndromes (CMS) are a clinically and genetically heterogeneous group of rare diseases due to mutations in neuromuscular junction (NMJ) protein-coding genes. Until now, many mutations encoding postsynaptic proteins as Agrin, MuSK and LRP4 have been identified as responsible for increasingly complex CMS phenotypes. The majority of mutations identified in LRP4 gene causes bone diseases including CLS and sclerosteosis-2 and rare cases of CMS with mutations in LRP4 gene has been described so far. In the French cohort of CMS patients, we identified a novel LRP4 homozygous missense mutation (c.1820A > G; p.Thy607Cys) within the β1 propeller domain in a patient presenting CMS symptoms, including muscle weakness, fluctuating fatigability and a decrement in compound muscle action potential in spinal accessory nerves, associated with congenital agenesis of the hands and feet and renal malformation. Mechanistic expression studies show a significant decrease of AChR aggregation in cultured patient myotubes, as well as altered in vitro binding of agrin and Wnt11 ligands to the mutated β1 propeller domain of LRP4 explaining the dual phenotype characterized clinically and electoneuromyographically in the patient. These results expand the LRP4 mutations spectrum associated with a previously undescribed clinical association involving impaired neuromuscular transmission and limb deformities and highlighting the critical role of a yet poorly described domain of LRP4 at the NMJ. This study raises the question of the frequency of this rare neuromuscular form and the future diagnosis and management of these cases.
Investigating the electrical crosstalk effect between pixels in high-resolution organic light-emitting diode microdisplays
Authors: Kang Haneul , Hwang Yeonsu , Kang Chan-mo , Kim Joo Yeon , Joo Chul Woong , Shin Jin-Wook , Sim Soobin , Cho Hyunsu , Ahn Dae Hyun , Cho Nam Sung , Youn Hyoc Min , An Young Jae , Kim Jin Sun , Byun Chun-Won , Lee Hyunkoo
Published: August 2023

Organic light-emitting diode (OLED) microdisplays have received great attention owing to their excellent performance for augmented reality/virtual reality devices applications. However, high pixel density of OLED microdisplay causes electrical crosstalk, resulting in color distortion. This study investigated the current crosstalk ratio and changes in the color gamut caused by electrical crosstalk between sub-pixels in high-resolution full-color OLED microdisplays. A pixel structure of 3147 pixels per inch (PPI) with four sub-pixels and a single-stack white OLED with red, green, and blue color filters were used for the electrical crosstalk simulation. The results showed that the sheet resistance of the top and bottom electrodes of OLEDs rarely affected the electrical crosstalk. However, the current crosstalk ratio increased dramatically and the color gamut decreased as the sheet resistance of the common organic layer decreased. Furthermore, the color gamut of the OLED microdisplay decreased as the pixel density of the panel increased from 200 to 5000 PPI. Additionally, we fabricated a sub-pixel circuit to measure the electrical crosstalk current using a 3147 PPI scale multi-finger-type pixel structure and compared it with the simulation result.
Automatic snoring detection using a hybrid 1D–2D convolutional neural network
Authors: Li Ruixue , Li Wenjun , Yue Keqiang , Zhang Rulin , Li Yilin
Published: August 2023

Snoring, as a prevalent symptom, seriously interferes with life quality of patients with sleep disordered breathing only (simple snorers), patients with obstructive sleep apnea (OSA) and their bed partners. Researches have shown that snoring could be used for screening and diagnosis of OSA. Therefore, accurate detection of snoring sounds from sleep respiratory audio at night has been one of the most important parts. Considered that the snoring is somewhat dangerously overlooked around the world, an automatic and high-precision snoring detection algorithm is required. In this work, we designed a non-contact data acquire equipment to record nocturnal sleep respiratory audio of subjects in their private bedrooms, and proposed a hybrid convolutional neural network (CNN) model for the automatic snore detection. This model consists of a one-dimensional (1D) CNN processing the original signal and a two-dimensional (2D) CNN representing images mapped by the visibility graph method. In our experiment, our algorithm achieves an average classification accuracy of 89.3%, an average sensitivity of 89.7%, an average specificity of 88.5%, and an average AUC of 0.947, which surpasses some state-of-the-art models trained on our data. In conclusion, our results indicate that the proposed method in this study could be effective and significance for massive screening of OSA patients in daily life. And our work provides an alternative framework for time series analysis.
A kind of planar waveguides for cheating the high-speed digital signals into misidentifying the characteristic impedance
Authors: Wu Chia Ho , Qian Zhenyu , Wang Wei , Peng Song Tsuen , Liu Chengyang , Shen Jianqi , Ni Donghua , Ye Guoqiang , He Fang , Wang Xiaolong , Shen Linfang , Li Qichao
Published: August 2023

Since a planar periodic transmission line can suppress drastically the electromagnetic coupling, it would be advantageous to use such a kind of transmission lines in solving the problem of miniaturization of circuit area. By adjusting the lattice constants and geometric parameters of periodic microstrip lines, a time domain characteristic impedance that is the same as that of conventional microstrip lines (CMLs) can be achieved. Such periodic microstrip lines can therefore be used to trick high-speed digital signals, causing a digital signal to misjudge the time domain characteristic impedance of the transmission lines. The theoretical analysis has been verified by our experimental measurement results. Besides, a specific expression for the characteristic impedance of lossless periodic artificial materials is deduced by a circuit model and a standard of misidentification for the characteristic impedance of periodic microstrip lines is given for the digital signals.