bluuebunny/crossref_metadata_2025 huggingface dataset:
Classifying Positive Results in Clinical Psychology Using Natural Language Processing
Authors: Schiekiera Louis , Diederichs Jonathan , Niemeyer Helen
Published: July 2024

Abstract: This study addresses the gap in machine learning tools for positive results classification by evaluating the performance of SciBERT, a transformer model pretrained on scientific text, and random forest in clinical psychology abstracts. Over 1,900 abstracts were annotated into two categories: positive results only and mixed or negative results. Model performance was evaluated on three benchmarks. The best-performing model was utilized to analyze trends in over 20,000 psychotherapy study abstracts. SciBERT outperformed all benchmarks and random forest in in-domain and out-of-domain data. The trend analysis revealed nonsignificant effects of publication year on positive results for 1990–2005, but a significant decrease in positive results between 2005 and 2022. When examining the entire time span, significant positive linear and negative quadratic effects were observed. Machine learning could support future efforts to understand patterns of positive results in large data sets. The fine-tuned SciBERT model was deployed for public use.
Sexualization and Emotional Valence in Audience Reactions to Popular Music Video Through Automated Language Analysis
Authors: Cela Herald , Wood Guilherme
Published: July 2024

Abstract: This study explores the interplay between sexualization, emotional valence, and audience reactions to music videos in the rap and pop genres, focusing on the effects of genre, gender, race, and release year. The study employs the Linguistic In-quiry and Word Count (LIWC) and Valence Aware Dictionary and sEntiment Reasoner (VADER) to quantify sexualization and emotional responses. Results indicate that rap music videos generate comments that feature more sex-related terms than pop. Female artists' videos elicited more emotional language, while failing to discriminate sexualized reactions compared to male artists’ videos. Additionally, videos by artists of color and more recent releases garnered heightened emotional responses, highlighting the influence of race and changing cultural norms. Correlation analysis revealed a positive association between sexual content and negative emotional valence, aligning with the negativity bias theory. These findings emphasize the need to consider the diverse audience reactions to sexualization and advocate for more sensitive portrayals in music videos.
Improving and Analyzing Open-Ended Survey Responses
Authors: Hahn Sonja , Kroehne Ulf , Merk Samuel
Published: July 2024

Abstract: Responses to open-ended items (OEI) in surveys in evaluation research are valuable but often short or even missing. We investigate how response behavior can be altered by means of survey design. In a survey on tutoring courses, 3,183 students responded to OEI. Participants were randomly assigned to conditions with or without a motivational cue and with OEI positioned at the beginning or the end of the survey, respectively. We simultaneously inspected response rates and answer lengths using Bayesian multilevel hurdle models. Positioning at the beginning enhanced response rates but reduced answer lengths. The motivational cue raised response rates only at the end of the survey. We also applied two different topic modeling approaches. Resulting topics cover different aspects of teacher behavior and positioning slightly altered the content of the responses. Based on motivational and cognitive theories, we address both the design of questionnaires and analysis approaches to OEI responses.
Influence of ENSO and Volcanic Eruptions on Himalayan Jet Latitude
Authors: Thapa Uday Kunwar , Stevenson Samantha
Published: July 2024

The position of the subtropical jet over the Himalayas (Himalayan jet) affects extreme precipitation and heat over Central and South Asia. We examine the influence of two major natural factors‐the El Niño/Southern Oscillation (ENSO) and explosive volcanic eruptions—on Himalayan jet interannual variability during the past millennium using simulations from the Community Earth System Model. We find that both El Niño events and eruptions shift the Himalayan jet equatorward by up to 3°. If an El Niño occurs following an eruption, this enhances the equatorward Himalayan jet shift, while La Niña tends to favor poleward jet migration. Subtropical cooling during El Niño or following eruptions is the primary cause of equatorward Himalayan jet shifts, while poleward shifts are associated with subtropical warming. Consistent across the CMIP6 models over the historical period, our results suggest that both ENSO and eruptions are the key drivers of interannual Himalayan jet variability.
Limited Benefits of Increased Spatial Resolution for Sea Ice in HighResMIP Simulations
Authors: Selivanova J. , Iovino D. , Vichi M.
Published: July 2024

State‐of‐the‐art coupled climate models struggle to accurately simulate historical variability and trends of Antarctic sea ice, impacting their reliability for future projections. Increasing horizontal resolution is expected to improve the representation of coupled atmosphere‐ice‐ocean processes at high latitudes. Here, we examine the historical changes in the Antarctic sea ice area and volume in High Resolution Model Intercomparison Project simulations against satellite data sets and ocean reanalyzes to assess the benefits of increased spatial resolution. Our results do not show considerable benefits when horizontal resolutions up to 0.25° in the ocean and 25 km in the atmosphere. Limited improvements are reported in the simulated historical sea ice trends, which are nevertheless model‐dependent, and associated with the use of model components with more complex sea‐ice parameterizations. Given the high computational cost of climate‐scale simulations at high spatial resolution, we advocate prioritizing enhancements in sea‐ice physics and the interactions among model components in coupled climate simulations.
Insights on Lateral Gravity Wave Propagation in the Extratropical Stratosphere From 44 Years of ERA5 Data
Authors: Gupta Aman , Sheshadri Aditi , Alexander M. Joan , Birner Thomas
Published: July 2024

The study presents (a) a 44‐year wintertime climatology of resolved gravity wave (GW) fluxes and forcing in the extratropical stratosphere using ERA5, and (b) their composite evolution around gradual (final warming) and abrupt (sudden warming) transitions in the wintertime circulation, focusing on lateral fluxes. The transformed Eulerian mean equations are leveraged to provide a glimpse of the importance of GW lateral propagation (i.e., horizontal propagation) toward driving the wintertime stratospheric circulation by analyzing the relative contribution of the vertical versus meridional flux dissipation. The relative contribution from lateral propagation is found to be notable, especially in the Austral winter stratosphere where lateral (vertical) momentum flux convergence provides a peak climatological forcing of up to −0.5 (−3.5) m/s/day around 60°S at 40–45 km altitude. Prominent lateral propagation in the wintertime midlatitudes also contributes to the formation of belts of GW activity in both hemispheres.
SiameseFWI: A Deep Learning Network for Enhanced Full Waveform Inversion
Authors: Saad Omar M. , Harsuko Randy , Alkhalifah Tariq
Published: July 2024

The performance of full‐wave inversion (FWI) depends highly on how we compare the simulated data to observed ones. The simplified assumptions used to generate the simulated data make such comparison even harder. To address this challenge, we introduce SiameseFWI, a novel approach to FWI that plays a critical role in the comparative analysis of simulated and observed seismic data. Employing a Siamese network, this methodology transforms the data into a shared latent space, enabling a robust and effective comparison of data representations. SiameseFWI leverages two identical Convolutional Neural Networks with shared weights trained in a self‐supervised framework, eliminating the necessity for labeled data. In each FWI iteration, the Siamese network and the velocity model are updated to minimize Euclidean distance loss between the latent representations of the data. Empirical evaluation conducted on the Marmousi2 and Overthrust models affirms the robust inversion performance of SiameseFWI compared to traditional FWI methodologies. Furthermore, its application to field data from Western Australia demonstrates its strength and efficacy in inversion. Notably, SiameseFWI exhibits robust inversion performance even in the presence of noise or when employing a linear initial model.
Template-independent enzymatic synthesis of RNA oligonucleotides
Authors: Wiegand Daniel J. , Rittichier Jonathan , Meyer Ella , Lee Howon , Conway Nicholas J. , Ahlstedt Daniel , Yurtsever Zeynep , Rainone Dominic , Kuru Erkin , Church George M.
Published: July 2024

RNA oligonucleotides have emerged as a powerful therapeutic modality to treat disease, yet current manufacturing methods may not be able to deliver on anticipated future demand. Here, we report the development and optimization of an aqueous-based, template-independent enzymatic RNA oligonucleotide synthesis platform as an alternative to traditional chemical methods. The enzymatic synthesis of RNA oligonucleotides is made possible by controlled incorporation of reversible terminator nucleotides with a common 3′-O-allyl ether blocking group using new CID1 poly(U) polymerase mutant variants. We achieved an average coupling efficiency of 95% and demonstrated ten full cycles of liquid phase synthesis to produce natural and therapeutically relevant modified sequences. We then qualitatively assessed the platform on a solid phase, performing enzymatic synthesis of several N + 5 oligonucleotides on a controlled-pore glass support. Adoption of an aqueous-based process will offer key advantages including the reduction of solvent use and sustainable therapeutic oligonucleotide manufacturing.
Exploring chaos and bifurcation in a discrete prey–predator based on coupled logistic map
Authors: Al-Kaff Mohammed O. , El-Metwally Hamdy A. , Elsadany Abd-Elalim A. , Elabbasy Elmetwally M.
Published: July 2024

This research paper investigates discrete predator-prey dynamics with two logistic maps. The study extensively examines various aspects of the system’s behavior. Firstly, it thoroughly investigates the existence and stability of fixed points within the system. We explores the emergence of transcritical bifurcations, period-doubling bifurcations, and Neimark-Sacker bifurcations that arise from coexisting positive fixed points. By employing central bifurcation theory and bifurcation theory techniques. Chaotic behavior is analyzed using Marotto’s approach. The OGY feedback control method is implemented to control chaos. Theoretical findings are validated through numerical simulations.
A shared-aperture pentaband antenna with high impedance surface for CubeSat application
Authors: Uddin Md Nazim , Alwan Elias A.
Published: July 2024

A circular polarized (CP) pentaband antenna based on the aperture-in-aperture (AIA) concept is presented for CubeSat applications. This AIA consists of five different bands ranging from L-band to Ka-band. Four different antennas, each operating at a specific frequency band, namely 12 GHz, 18.5 GHz, 26 GHz, and 32 GHz, were incorporated into an L-band (viz. 1.5 GHz) antenna. Notably, the five antennas can operate simultaneously for a CubeSat downlink operation with a frequency ratio of 21.3:1. The antenna structure shows a realized gain of 5–10 dBi with good CP bandwidth (< 3 dB) across the overall operational frequency range. That is, the realized gain of L-band (1.5 GHz), X-band (12.5 GHz), K-band1 (18.5 GHz), K-band2 (26 GHz), and Ka-bands (32 GHz) are 5.05 dBi, 8.21 dBi, 7.33 dBi, 7.97 dBi, and 8.56 dBi. A high impedance surface (HIS) is incorporated with the Ka-band antenna to mitigate the ripples in the radiation pattern created by the interference of surface waves. A prototype was fabricated and tested. The measurement data agrees well with the simulation.
Comparison of outcomes between modified double-flanged sutureless scleral fixation and conventional sutured scleral fixation
Authors: Kim Jinsoo , Lee Phil Young , Park Min Seon , Cho Bum-Joo , Kwon Soonil
Published: July 2024

This retrospective study aimed to compare the outcomes of modified double-flanged sutureless scleral fixation versus sutured scleral fixation. Medical records of 65 eyes from 65 patients who underwent double-flanged scleral fixation (flange group) or conventional scleral fixation (suture group) between 2021 and 2022 were reviewed. Visual and refractive outcomes, as well as postoperative complications, were compared 1, 2, and 6 months after surgery. We included 31 eyes in the flange group and 34 eyes in the suture group. At 6 months postoperatively, the flange group showed better uncorrected visual acuity (0.251 ± 0.328 vs. 0.418 ± 0.339 logMAR, P = 0.041) and a smaller myopic shift (− 0.74 ± 0.93 vs. − 1.33 ± 1.15 diopter, P = 0.007) compared to the suture group. The flange group did not experience any instances of iris capture, while the suture group had iris capture in 10 eyes (29.4%; P < 0.001). In the flange group, all intraocular lenses remained centered, whereas in the suture group, they were decentered in 8 eyes (23.5%; P = 0.005). The double-flanged technique not only prevented iris capture and decentration of the intraocular lens but also reduced myopic shift by enhancing the stability of the intraocular lens.
Effects of negative ions on equilibrium solar plasmas in the fabric of gravito-electrostatic sheath model
Authors: Sarma Pankaj , Karmakar Pralay Kumar
Published: July 2024

The gravito-electrostatic sheath (GES) model, exploring the solar wind plasma (SWP) origin from the solar interior plasma (SIP) via the solar surface boundary (SSB), is revaluated by including realistic negative ionic species. A constructive numerical analysis of the structuring equations shows that the SIP volume shrinks with an increase in the negative ion concentration. This shrinking nature is independent of ion mass and plasma temperature. The electric potential is insensitive to the negative ion concentration, mass, and plasma temperature. The solar plasma flow dynamics is studied with the Mach number and current density profiles. The sonic transition of the SWP depends on the Ti/Te-ratio. The current density responds to the negative ion density and Ti/Te−ratio in both the SIP and SWP. A deviation from the local quasi-neutrality state is observed in the SIP. The GES model equations result in a modified GES-Bohm sheath criterion in a well justifiable and validated form. The obtained results are then compared with the various observed outcomes and previous GES-based predictions. The relevance of this multi-parametric solar plasma analysis is lastly emphasized on the basis of the current solar research progressions.
Differential potassium channel inhibitory activities of a novel thermostable degradation peptide BmKcug1a-P1 from scorpion medicinal material and its N-terminal truncated/restored peptides
Authors: Qin Chenhu , Yang Xuhua , Zuo Zheng , Yuan Peixin , Sun Fang , Luo Xudong , Ye Xiangdong , Cao Zhijian , Chen Zongyun , Wu Yingliang
Published: July 2024

Thermally stable full-length scorpion toxin peptides and partially degraded peptides with complete disulfide bond pairing are valuable natural peptide resources in traditional Chinese scorpion medicinal material. However, their pharmacological activities are largely unknown. This study discovered BmKcug1a-P1, a novel N-terminal degraded peptide, in this medicinal material. BmKcug1a-P1 inhibited hKv1.2 and hKv1.3 potassium channels with IC50 values of 2.12 ± 0.27 μM and 1.54 ± 0.28 μM, respectively. To investigate the influence of N-terminal amino acid loss on the potassium channel inhibiting activities, three analogs (i.e., full-length BmKcug1a, BmKcug1a-P1-D2 and BmKcug1a-P1-D4) of BmKcug1a-P1 were prepared, and their potassium channel inhibiting activities on hKv1.3 channel were verified by whole-cell patch clamp technique. Interestingly, the potassium channel inhibiting activity of full-length BmKcug1a on the hKv1.3 channel was significantly improved compared to its N-terminal degraded form (BmKcug1a-P1), while the activities of two truncated analogs (i.e., BmKcug1a-P1-D2 and BmKcug1a-P1-D4) were similar to that of BmKcug1a-P1. Extensive alanine-scanning experiments identified the bonding interface (including two key functional residues, Asn30 and Arg34) of BmKcug1a-P1. Structural and functional dissection further elucidated whether N-terminal residues of the peptide are located at the bonding interface is important in determining whether the N-terminus significantly influences the potassium channel inhibiting activity of the peptide. Altogether, this research identified a novel N-terminal degraded active peptide, BmKcug1a-P1, from traditional Chinese scorpion medicinal material and elucidated how the N-terminus of peptides influences their potassium channel inhibiting activity, contributing to the functional identification and molecular truncation optimization of full-length and degraded peptides from traditional Chinese scorpion medicinal material Buthus martensii Karsch.
Investigating the crowding effect on letters and symbols in deaf adults
Authors: Kamble Veena , Buyle Margot , Crollen Virginie
Published: July 2024

Reading requires the transformation of a complex array of visual features into sounds and meaning. For deaf signers who experience changes in visual attention and have little or no access to the sounds of the language they read, understanding the visual constraints underlying reading is crucial. This study aims to explore a fundamental aspect of visual perception intertwined with reading: the crowding effect. This effect manifests as the struggle to distinguish a target letter when surrounded by flanker letters. Through a two-alternative forced choice task, we assessed the recognition of letters and symbols presented in isolation or flanked by two or four characters, positioned either to the left or right of fixation. Our findings reveal that while deaf individuals exhibit higher accuracy in processing letters compared to symbols, their performance falls short of that of their hearing counterparts. Interestingly, despite their proficiency with letters, deaf individuals didn’t demonstrate quicker letter identification, particularly in the most challenging scenario where letters were flanked by four characters. These outcomes imply the development of a specialized letter processing system among deaf individuals, albeit one that may subtly diverge from that of their hearing counterparts.
Medical intelligence using PPG signals and hybrid learning at the edge to detect fatigue in physical activities
Authors: Liu Ping , Song Yazhou , Yang Xuan , Li Dejuan , Khosravi M.
Published: July 2024

The educational environment plays a vital role in the development of students who participate in athletic pursuits both in terms of their physical health and their ability to detect fatigue. As a result of recent advancements in deep learning and biosensors benefitting from edge computing resources, we are now able to monitor the physiological fatigue of students participating in sports in real time. These devices can then be used to analyze the data using contemporary technology. In this paper, we present an innovative deep learning framework for forecasting fatigue in athletic students following physical exercise. It addresses the issue of lack of precision computational models and extensive data analysis in current approaches to monitoring students’ physical activity. In our study, we classified fatigue and non-fatigue based on photoplethysmography (PPG) signals. Several deep learning models are compared in the study. Using limited training data, determining the optimal parameters for PPG presents a significant challenge. For datasets containing many data points, several models were trained using PPG signals: a deep residual network convolutional neural network (ResNetCNN) ResNetCNN, an Xception architecture, a bidirectional long short-term memory (BILSTM), and a combination of these models. Training and testing datasets were assigned using a fivefold cross validation approach. Based on the testing dataset, the model demonstrated a proper classification accuracy of 91.8%.
Eigen-entropy based time series signatures to support multivariate time series classification
Authors: Patharkar Abhidnya , Huang Jiajing , Wu Teresa , Forzani Erica , Thomas Leslie , Lind Marylaura , Gades Naomi
Published: July 2024

Most current algorithms for multivariate time series classification tend to overlook the correlations between time series of different variables. In this research, we propose a framework that leverages Eigen-entropy along with a cumulative moving window to derive time series signatures to support the classification task. These signatures are enumerations of correlations among different time series considering the temporal nature of the dataset. To manage dataset’s dynamic nature, we employ preprocessing with dense multi scale entropy. Consequently, the proposed framework, Eigen-entropy-based Time Series Signatures, captures correlations among multivariate time series without losing its temporal and dynamic aspects. The efficacy of our algorithm is assessed using six binary datasets sourced from the University of East Anglia, in addition to a publicly available gait dataset and an institutional sepsis dataset from the Mayo Clinic. We use recall as the evaluation metric to compare our approach against baseline algorithms, including dependent dynamic time warping with 1 nearest neighbor and multivariate multi-scale permutation entropy. Our method demonstrates superior performance in terms of recall for seven out of the eight datasets.
Changes of in vivo electrical conductivity in the brain and torso related to age, fat fraction and sex using MRI
Authors: He Zhongzheng , Soullié Paul , Lefebvre Pauline , Ambarki Khalid , Felblinger Jacques , Odille Freddy
Published: July 2024

This work was inspired by the observation that a majority of MR-electrical properties tomography studies are based on direct comparisons with ex vivo measurements carried out on post-mortem samples in the 90’s. As a result, the in vivo conductivity values obtained from MRI in the megahertz range in different types of tissues (brain, liver, tumors, muscles, etc.) found in the literature may not correspond to their ex vivo equivalent, which still serves as a reference for electromagnetic modelling. This study aims to pave the way for improving current databases since the definition of personalized electromagnetic models (e.g. for Specific Absorption Rate estimation) would benefit from better estimation. Seventeen healthy volunteers underwent MRI of both brain and thorax/abdomen using a three-dimensional ultrashort echo-time (UTE) sequence. We estimated conductivity (S/m) in several classes of macroscopic tissue using a customized reconstruction method from complex UTE images, and give general statistics for each of these regions (mean-median-standard deviation). These values are used to find possible correlations with biological parameters such as age, sex, body mass index and/or fat volume fraction, using linear regression analysis. In short, the collected in vivo values show significant deviations from the ex vivo values in conventional databases, and we show significant relationships with the latter parameters in certain organs for the first time, e.g. a decrease in brain conductivity with age.
Association of triglyceride glucose-body mass index with Alzheimer’s disease pathology, cognition and brain structure in non-demented people
Authors: Zhang Zihao , Chen Xin , Sheng Zehu
Published: July 2024

The relationship between the triglyceride glucose-body mass index (TyG-BMI) index and Alzheimer’s disease (AD) pathology, cognition, and brain structure remains unclear. This study aimed to investigate these associations, focusing on cerebrospinal fluid (CSF) biomarkers, cognitive measures, and brain imaging data. Eight hundred and fifty-five non-demented participants were included. Linear regression was used to explore associations between the TyG-BMI index and AD pathology, cognition, and brain structure. The association between the TyG-BMI index and AD risk was assessed using Kaplan–Meier and Cox proportional hazards models. Longitudinal relationships were assessed using linear mixed-effects models. Mediation analyses were conducted to examine AD pathology’s potential mediating role between the TyG-BMI index and cognition as well as brain structure. In the linear regression analyses, higher TyG-BMI levels were associated with increased Aβ42 and decreased Tau, pTau, Tau/Aβ42, pTau/Aβ42, and pTau/Tau. Positive correlations were observed with mini-mental state examination (MMSE), memory (MEM), executive function (EF), and the volumes of the hippocampus, entorhinal cortex, and middle temporal regions, while negative correlations were found with Alzheimer’s Disease Assessment Scale (ADAS). Longitudinally, the TyG-BMI index was inversely associated with ADAS, and positively with MMSE, MEM, EF, hippocampus, entorhinal, and middle temporal. High TyG-BMI levels were correlated with lower AD risk (HR 0.996 [0.994, 0.999]). Mediation analyses revealed AD pathology mediated the association between TyG-BMI index and cognition as well as brain structure. Additionally, the TyG-BMI index could mediate cognitive changes by influencing brain structure. The TyG-BMI index is associated with AD pathology, cognition, and brain structure.
Water body extraction from high spatial resolution remote sensing images based on enhanced U-Net and multi-scale information fusion
Authors: Cao Huidong , Tian Yanbing , Liu Yanli , Wang Ruihua
Published: July 2024

Employing deep learning techniques for the semantic segmentation of remote sensing images has emerged as a prevalent approach for acquiring information about water bodies. Yet, current models frequently fall short in accurately extracting water bodies from high-resolution remote sensing images, as these images often present intricate details of terrestrial objects and complex backgrounds. Vegetation, shadows, and other objects close to water boundaries have increased similarity to water bodies. Moreover, water bodies in high-resolution images have different boundary complexities, shapes, and sizes. This situation makes it somewhat challenging to accurately distinguish water bodies in high-resolution images. To overcome these difficulties, this paper presents a novel network model named EU-Net, specifically designed to extract water bodies from high-resolution remote sensing images. The proposed EU-Net model, with U-net as the backbone network, incorporates improved residual connections and attention mechanisms, and designs multi-scale dilated convolution and multi-scale feature fusion modules to enhance water body extraction performance in complex scenarios. Specifically, in the proposed model, improved residual connections are introduced to enable the learning of more complex features; the attention mechanism is employed to improve the model's discriminative ability by focusing on important channels and spatial areas. The implemented multi-scale dilated convolution technique enhances the model's receptive field while maintaining the same number of parameters. The designed multi-scale feature fusion module is capable of processing both small-scale details and large-scale structures in images, while simultaneously modeling the spatial context relationships of features at different scales. Experimental results validate the superior performance of EU-Net in accurately identifying water bodies from high-resolution remote sensing images, outperforming current models in terms of water extraction accuracy.
Efficient musculoskeletal annotation using free-form deformation
Authors: Fukuda Norio , Konda Shoji , Umehara Jun , Hirashima Masaya
Published: July 2024

Traditionally, constructing training datasets for automatic muscle segmentation from medical images involved skilled operators, leading to high labor costs and limited scalability. To address this issue, we developed a tool that enables efficient annotation by non-experts and assessed its effectiveness for training an automatic segmentation network. Our system allows users to deform a template three-dimensional (3D) anatomical model to fit a target magnetic-resonance image using free-form deformation with independent control points for axial, sagittal, and coronal directions. This method simplifies the annotation process by allowing non-experts to intuitively adjust the model, enabling simultaneous annotation of all muscles in the template. We evaluated the quality of the tool-assisted segmentation performed by non-experts, which achieved a Dice coefficient greater than 0.75 compared to expert segmentation, without significant errors such as mislabeling adjacent muscles or omitting musculature. An automatic segmentation network trained with datasets created using this tool demonstrated performance comparable to or superior to that of networks trained with expert-generated datasets. This innovative tool significantly reduces the time and labor costs associated with dataset creation for automatic muscle segmentation, potentially revolutionizing medical image annotation and accelerating the development of deep learning-based segmentation networks in various clinical applications.
Elevated TyG index is associated with increased risk of vitamin D deficiency among elderly patients with type 2 diabetes
Authors: Xiang Qunyan , Xu Hu , Liu Youshou , Huang Wu
Published: July 2024

Vitamin D deficiency (VDD) is associated with increased risk of type 2 diabetes mellitus (T2DM) and insulin resistance (IR). We aimed to investigate the association between the triglyceride-glucose (TyG) index that represents IR and VDD in elderly patients with T2DM. We enrolled 572 elderly participants with T2DM in this study. TyG index was calculated as ln [fasting triglyceride (TG, mg/dL) × fasting blood glucose (mg/dL)/2]. Serum 25-hydroxyvitamin D [25(OH)D] level below 50 nmol/L was defined as VDD. The association between the TyG index and the VDD risk was evaluated by multivariate logistic regression analysis. We observed a significant decreased 25(OH)D level with the increase of the TyG index in elderly diabetic patients, and a negative correlation between the TyG index and 25(OH)D level. The participants in the highest TyG quartile had a 2.40-fold higher risk of VDD than those in the lowest TyG index quartile [OR 2.40; 95% CI 1.47–3.92; P < 0.001]. The association persisted after adjustments for age, sex, smoking, obesity, insulin therapy, hypoglycemic agents’ medication, and some biochemical parameters. TyG index may be involved in the pathophysiology of VDD, which could be a predictor for VDD in elderly diabetic patients.
A cross-sectional study on the self-management of asthma and asthma control among adult asthmatic patients in the Aseer region, KSA
Authors: Makki Soha , Siddiqua Ayesha , Alqahtani Bushra Ali , Alkhuwaylidi Hanan , Alhefzi Lama , Hussain Maram , Saeed Sarah , Ahmed Waad , Abdelkarim Randa A. , Khaled Arwa
Published: July 2024

Proper management of asthma is crucial for maintaining control over the disease and has a significant impact on the patient’s overall condition. The purpose of this study was to determine the extent of self-management and the level of Asthma control in the patients from the Aseer region of Saudi Arabia, as well as to investigate determinants of illness control. A study was conducted using quantitative cross-sectional methods. Researchers utilised a web-based, self-administered structured questionnaire to gather data. The questionnaire included three sections: a socio-demographic section, an Asthma Self-Management Questionnaire (ASMQ), and Asthma Control Test (ACT). An analysis using the chi-square test was conducted to determine if there was a notable connection between the socio-demographic characteristics of the participants and the level of asthma control. A total of 305 responses were collected. The average score for the Asthma Self-Management Questionnaire was 5.72, which corresponds to 40.9%. Based on the scores from the Asthma Control Test, it was found that 60 patients (20.0%) had asthma that was not under control, 94 (30.0%) had asthma that was partially controlled, and 151 (50.0%) had asthma that was well controlled. Factors such as gender, non-smoking status, and having asthma for over 10 years (p ˂0.05) were found to be strongly correlated with improved disease control. Significant gaps were found in patients’ awareness of the most important and critical aspects concerning the condition, medications, and preventative actions that limit asthma aggravation. To address the current situation, hospitals and clinics must make substantial efforts.
Lightweight bobbin yarn detection model for auto-coner with yarn bank
Authors: Dai Ning , Hu Xiaohan , Xu Kaixin , Hu Xudong , Yuan Yanhong , Tu Jiajia
Published: July 2024

The automated replacement of empty tubes in the yarn bank is a critical step in the process of automatic winding machines with yarn banks, as the real-time detection of depleted yarn on spools and accurate positioning of empty tubes directly impact the production efficiency of winding machines. Addressing the shortcomings of traditional methods, such as poor adaptability and low sensitivity in optical and visual tube detection, and aiming to reduce the computational and detection time costs introduced by neural networks, this paper proposes a lightweight yarn spool detection model based on YOLOv8. The model utilizes Darknet-53 as the backbone network, and due to the dense spatial distribution of yarn spool targets, it incorporates large selective kernel units to enhance the recognition and positioning of dense targets. To address the issue of excessive focus on local features by convolutional neural networks, a bi-level routing attention mechanism is introduced to capture long-distance dependencies dynamically. Furthermore, to balance accuracy and detection speed, a FasterNeck is constructed as the neck network, replacing the original convolutional blocks with Ghost convolutions and integrating with FasterNet. This design minimizes the sacrifice of detection accuracy while achieving a significant improvement in inference speed. Lastly, the model employs weighted IoU with a dynamic focusing mechanism as the bounding box loss function. Experimental results on a custom yarn spool dataset demonstrate a notable improvement over the baseline model, with a high-confidence mAP of 94.2% and a compact weight size of only 4.9 MB. The detection speed reaches 223FPS, meeting the requirements for industrial deployment and real-time detection.
In vitro fertilization results of GNRH antagonists and medroxyprogesterone acetate used to prevent premature LH surge during ovarian hyperstimulation
Authors: Dinç Can , Arıkan Saltuk Buğra , Özer Mustafa , Olgan Şafak
Published: July 2024

The aim of this study was to evaluate the effects of medroxyprogesterone acetate (MPA) treatment in comparison to those of gonadotropin releasing hormone (GnRH) antagonists for the prevention of premature luteinizing hormone surges during controlled ovarian hyperstimulation (OS) and the impact of these effects on developing embryos and pregnancy outcomes. Data from 757 cycles of GnRH antagonist treatment and 756 cycles of MPA treatment were evaluated at the Akdeniz University Faculty of Medicine Assisted Reproductive Treatment Center between October 2018 and April 2022. Patient records were obtained from the electronic database of the centre and analysed. In our centre, GnRH antagonist protocols were used between 2018 and 2020, and MPA protocols were used between 2020 and 2022. We chose our study population by year. Our study is a comparative retrospective study. All methods in this study were performed in accordance with the relevant guidelines and regulations. Patients using MPA were significantly older (33.9 ± 5.6 vs. 32.6 ± 5.6, p < 0.001) and had a lower number of antral follicles (AFC) (10.7 ± 8.6 vs. 11.9 ± 10.8, p = 0.007) than those using GnRH antagonists. Both MPA (2.9%) and GnRH antagonists (2.2%) had similar effectiveness in preventing premature ovulation (p = 0.415). There was no significant difference between the two groups in terms of the number of total developed embryos (1.3 ± 1.3 vs. 1.2 ± 1.2, p = 0.765). There was no significant difference in the clinical pregnancy rates with the first ET (%35.4 vs. %30.1, p = 0.074), per total number of transfers (35.3% vs. 30.1%, p = 0.077). MPA was found to be effective at preventing premature ovulation during OS treatment, and the incidence of developing embryo and pregnancy outcomes in patients using MPA were similar to those in patients using GnRH antagonists. Therefore, the use of MPA instead of GnRH antagonists during OS may be a viable alternative for patients not scheduled for fresh ET.
Rising seas could cross thresholds for initiating coastal wetland drowning within decades across much of the United States
Authors: Osland Michael J. , Chivoiu Bogdan , Grace James B. , Enwright Nicholas M. , Guntenspergen Glenn R. , Buffington Kevin J. , Thorne Karen M. , Carr Joel A. , Sweet William V. , Couvillion Brady R.
Published: July 2024

Accelerated sea-level rise is an existential threat to coastal wetlands, but the timing and extent of wetland drowning are debated. Recent data syntheses have clarified future relative sea-level rise exposure and sensitivity thresholds for drowning. Here, we integrate these advances to estimate when and where rising sea levels could cross thresholds for initiating wetland drowning across the conterminous United States. Our results show that there is much spatial variation in relative sea-level rise rates, which impacts the potential timing and extent of wetlands crossing thresholds. High rates of relative sea-level rise along wetland-rich parts of the Gulf of Mexico and Atlantic coasts highlight areas where wetlands are already drowning or could begin to drown within decades, including large wetland landscapes within the Mississippi River delta, Greater Everglades, Chesapeake Bay, Texas, Georgia, and the Carolinas. Collectively, our results underscore the need to prepare for transformative coastal change.
Recommendations for evaluating photoplethysmography-based algorithms for blood pressure assessment
Authors: Elgendi Mohamed , Haugg Fridolin , Fletcher Richard Ribon , Allen John , Shin Hangsik , Alian Aymen , Menon Carlo
Published: July 2024

Photoplethysmography (PPG) is a non-invasive optical technique that measures changes in blood volume in the microvascular tissue bed of the body. While it shows potential as a clinical tool for blood pressure (BP) assessment and hypertension management, several sources of error can affect its performance. One such source is the PPG-based algorithm, which can lead to measurement bias and inaccuracy. Here, we review seven widely used measures to assess PPG-based algorithm performance and recommend implementing standardized error evaluation steps in their development. This standardization can reduce bias and improve the reliability and accuracy of PPG-based BP estimation, leading to better health outcomes for patients managing hypertension.
Interconversion and functional composites of metal–organic frameworks and hydrogen-bonded organic frameworks
Authors: Hu Siwen , Zhao He , Liang Meng , Hao Jingjun , Xue Pengchong
Published: July 2024

This review describes the recent research on intercoversion and composites of metal–organic frameworks and hydrogen-bonded organic frameworks, along with their applications.
Zirconium-based metal–organic frameworks and their roles in electrocatalysis
Authors: Tsai Meng-Dian , Wu Kuan-Chu , Kung Chung-Wei
Published: July 2024

This article discusses the roles of Zr-MOFs in electrocatalysis, and the challenges and opportunities in using Zr-MOFs in electrocatalytic applications.
One flask cascade approach to a complex pyrano[2,3-c]pyrazole-pyrazolone hybrid heterocyclic system and its initiatory neurobiological profiling
Authors: Balasubramani Alagesan , Sudarshana K. A. , Kushwaha Roli , Chakravarty Sumana , Pabbaraja Srihari , Mehta Goverdhan
Published: July 2024

A one-pot multicomponent cascade approach towards a hybrid heterocyclic pyrano[2,3-c]pyrazole-pyrazolone framework.
Glycosylation with sulfoxide-based glycosyl donors
Authors: Wu Pinru , Zeng Jing , Meng Lingkui , Wan Qian
Published: July 2024

This feature article elucidates the development and notable progress of glycosyl sulfoxide-based glycosylation reactions, with a specific emphasis on cases where sulfinyl groups are situated either directly at the anomeric position or more distally.
Carbon and nitrogen-based gas fluxes in subarctic ecosystems under climate warming and increased cloudiness
Authors: Ndah Flobert A. , Maljanen Marja , Rinnan Riikka , Bhattarai Hem Raj , Davie-Martin Cleo L. , Mikkonen Santtu , Michelsen Anders , Kivimäenpää Minna
Published: July 2024

Increased temperatures coupled with reduced light availability due to increased cloudiness can alter the ecosystem–atmosphere exchange of trace gases in the northern high-latitude regions with important climate feedback implications.
Electric field temporal interference stimulation of neurons in vitro
Authors: Ahtiainen Annika , Leydolph Lilly , Tanskanen Jarno M. A. , Hunold Alexander , Haueisen Jens , Hyttinen Jari A. K.
Published: July 2024

Introducing a setup for temporal interference electrical stimulation for neurons in vitro. Created with Biorender.com.
Morphology-size map of zeolitic imidazolate frameworks: unveiling the bactericidal effects upon varying their zinc/cobalt ion contents
Authors: Antwi-Baah Ruth , Frimpong Dapaah Malcom , Wang Yajing , Chen Xiaoqin , Liu Heyang
Published: July 2024

A correlation between the morphology, size, and zinc/cobalt metal ion content of pristine ZIF particles and their antibacterial performance including mechanism pattern is established.
Congestion effect of an annulated tetracyclic thiophene-containing fragment on 18-crown-6 ether: manifestation in complex formation in solution and membrane transfer properties
Authors: Khoroshutin Andrey , Martynov Leonid , Yaltseva Polina , Kostenko Evita , Cheshkov Dmitry , Botezatu Anatoliy , Moiseeva Anna , Fedorov Yuri , Fedorova Olga
Published: July 2024

Photocyclization as a means to make crown ether be conjested. Congestion manifestation both in solution complexation (UV-vis, fluo, NMR, DOSY) and crown-facilitated ion transfer from solution to membrane.
Carboxymethylcellulose encapsulated fingolimod, siRNA@ZnO hybrid nanocomposite as a new anti-Alzheimer's material
Authors: Aljohani Nuha B. , Qusti Safaa Y. , Alsiny Madeeha , Aljoud Fadwa , Aljohani Norah Bakheet , Alsolami Eman S. , Alamry Khalid A. , Hussein Mahmoud A.
Published: July 2024

CMC-encapsulated fingolimod and siRNA@ZnO hybrid nanocomposite frameworks have been proven to prevent AD and improve AD treatment techniques as drug delivery carriers.
3-(Sulfamic acid)-propyltriethoxysilane on biochar nanoparticles as a practical, biocompatible, recyclable and chemoselective nanocatalyst in organic reactions
Authors: Emad-Abbas Norolhoda , Naji Jalil , Moradi Parisa , Kikhavani Tavan
Published: July 2024

Biochar nanoparticles were functionalized by 3-(sulfamic acid)-propyltriethoxysilane (SAPES) as nanocatalyst in the synthesis of sulfoxides and tetrahydrobenzo[b]pyrans.
Synthesis of 1-aryl-2,3-diaroyl cyclopropanes from 1,3,5-triaryl-1,5-diketones and their transformation into E,E-1,4-diaryl-1,3-butadienes
Authors: Britto Kashpar John , Meenakshi Maniarasu , Srinivasan Kannupal
Published: July 2024

1-Aryl-2,3-diaroyl cyclopropanes, synthesized by iodine/DBU-mediated cyclization of 1,3,5-triaryl-1,5-diketones, when subjected to reduction followed by treatment with conc. HCl afforded E,E-1,5-diaryl-1,3-butadienes.
Real-time coloration control of gallium-based strips through cold rolling
Authors: Liu Jing , Kang Hao , Song Wencheng , Bi Xu , Shi Dandan , Sun Youzheng , Cheng Weizheng , Zhang Weiye , Zhao Junfeng , Dai Han
Published: July 2024

Fast discoloration of the liquid metal due to the addition of Al creates a solid colorful “skin” on the LM surface, which can be peeled off through real-time cold rolling.
Sonophotocatalytic degradation of sulfamethoxazole using lanthanum ferrite perovskite oxide anchored on an ultrasonically exfoliated porous graphitic carbon nitride nanosheet
Authors: Bayode Ajibola A. , Osti Andrea , Glisenti Antonella
Published: July 2024

Lanthanum ferrite, anchored on graphitic carbon nitride nanosheets, was synthesized and can degrade sulfamethoxazole. The degradation occurred through a sono-photocatalytic process in water. The material is reusable for up to eight cycles.
In vitro evaluation and in situ intestinal absorption characterisation of paeoniflorin nanoparticles in a rat model
Authors: Xiao Yifei , Wei Qidong , Du Lixin , Guo Zhihua , Li Ya
Published: July 2024

Purpose: the aim of this study was to improve the stability and bioavailability of paeoniflorin (PF) by using nanoparticle encapsulation technology.
Synthesis, enzyme inhibition assay, and molecular modeling study of novel pyrazolines linked to 4-methylsulfonylphenyl scaffold: antitumor activity and cell cycle analysis
Authors: Abdel-Aziz Alaa A.-M. , El-Azab Adel S. , Brogi Simone , Ayyad Rezk R. , Alkahtani Hamad M. , Abuelizz Hatem A. , Al-Suwaidan Ibrahim A. , Al-Obaid Abdulrahman M.
Published: July 2024

Antitumor activity using 59 cancer cell lines and enzyme inhibitory activity of a newly synthesized pyrazoline-linked 4-methylsulfonylphenyl scaffold (compounds 18a–q) were measured and compared with those of standard drugs.
Conjugated microporous polytriphenylamine as a high-performance anion-capture electrode for hybrid capacitive deionization with ultrahigh areal adsorption capacity
Authors: Kong Weiqing , Lu Xiaoyuan , Ge Xu , Zhang Qingao , Jin Xiaoyu , Zhang Meng , Feng Yuanyuan
Published: July 2024

We report conjugated microporous polytriphenylamine as a high-performance anion-capture electrode for capacitive deionization (CDI), thus opening a new pathway for the rational design of advanced polymer-based anodes in CDI and beyond.
Efficient and stable inorganic perovskite solar cells enabled by a lead silicate glass layer
Authors: Yang Wanpeng , Yu Haixuan , Zhang Zhiguo , Shi Haodan , Hu Yong , Huang Junyi , Liu Zhirong , Shen Yan , Wang Mingkui
Published: July 2024

We show a new method to form an ultrathin PbSiO3 glass layer at the grain boundary during the crystallization of films. The unsealed device achieves outstanding moisture resilience, retaining 92% initial efficiency post 600 h at 25 ± 5% RH.
Construction of 2D/2D BiOIO3/Bi2O2CO3 composite structures with face-to-face contacts can facilitate carrier transfer via a built-in electric field and a polar field for pyro–photo-electric catalysis
Authors: Wu Yunfei , Ruan Mengnan , Wang Chengyi , Zhong Tingting , Liu Zhifeng
Published: July 2024

A BiOIO3/Bi2O2CO3 catalyst was prepared by a one-step hydrothermal method. The catalyst exhibited high performance due to the built-in and polarized electric fields which significantly reduced the recombination of carriers.
The optimized energy level, morphology and photophysical procedure boosted the photovoltaic performance of monochlorinated benzothiadiazole-based polymer donors
Authors: Tong Junfeng , Liu Wuyan , An Lili , Qu Shilei , Zhang Aoxiang , Guo Pengzhi , Liang Zezhou , Yan Lihe , Yang Chunyan , Li Jianfeng , Xia Yangjun
Published: July 2024

Monooctylthiophene-π-bridge PClBDT-TClBT achieved an outstanding PCE of 11.52%, and bisoctylthiophene-π-bridge PClBDT-DTClBT exhibited a decreased PCE of 9.48% when paired with Y6. Unfortunately, PClBDT-ClBT exhibited an unsatisfactory PCE of 1.42%.
Influence of the catalyst surface chemistry on the electrochemical self-coupling of biomass-derived benzaldehyde into hydrobenzoin
Authors: Gong Li , Zhao Shiling , Yu Jing , Li Junshan , Arbiol Jordi , Kallio Tanja , Calcabrini Mariano , Martínez-Alanis Paulina R. , Ibáñez Maria , Cabot Andreu
Published: July 2024

Modifying the surface of Cu2S nanoparticles with OAm significantly influenced the selectivity of the BZH reduction reaction. Bare Cu2S favored the production of BA, while OAm-capped Cu2S promoted HDB formation.