bluuebunny/crossref_metadata_2025_split huggingface dataset:
Metabolome panels as potential noninvasive biomarkers for primary glomerulonephritis sub-types: meta-analysis of profiling metabolomics studies
Authors: Roointan Amir , Ghaeidamini Maryam , Shafieizadegan Saba , Hudkins Kelly L. , Gholaminejad Alieh 
Published: November 2023

AbstractPrimary glomerulonephritis diseases (PGDs) are known as the top causes of chronic kidney disease worldwide. Renal biopsy, an invasive method, is the main approach to diagnose PGDs. Studying the metabolome profiles of kidney diseases is an inclusive approach to identify the disease’s underlying pathways and discover novel non-invasive biomarkers. So far, different experiments have explored the metabolome profiles in different PGDs, but the inconsistencies might hinder their clinical translations. The main goal of this meta-analysis study was to achieve consensus panels of dysregulated metabolites in PGD sub-types. The PGDs-related metabolome profiles from urine samples in humans were selected in a comprehensive search. Amanida package in R software was utilized for performing the meta-analysis. Through sub-type analyses, the consensus list of metabolites in each category was obtained. To identify the most affected pathways, functional enrichment analysis was performed. Also, a gene-metabolite network was constructed to identify the key metabolites and their connected proteins. After a vigorous search, among the 11 selected studies (15 metabolite profiles), 270 dysregulated metabolites were recognized in urine of 1154 PGDs and control samples. Through sub-type analyses by Amanida package, the consensus list of metabolites in each category was obtained. Top dysregulated metabolites (vote score of ≥ 4 or ≤ − 4) in PGDs urines were selected as main panel of meta-metabolites including glucose, leucine, choline, betaine, dimethylamine, fumaric acid, citric acid, 3-hydroxyisovaleric acid, pyruvic acid, isobutyric acid, and hippuric acid. The enrichment analyses results revealed the involvement of different biological pathways such as the TCA cycle and amino acid metabolisms in the pathogenesis of PGDs. The constructed metabolite-gene interaction network revealed the high centralities of several metabolites, including pyruvic acid, leucine, and choline. The identified metabolite panels could shed a light on the underlying pathological pathways and be considered as non-invasive biomarkers for the diagnosis of PGD sub-types.
Fuzzy inference-based LSTM for long-term time series prediction
Authors: Wang Weina , Shao Jiapeng , Jumahong Huxidan 
Published: November 2023

AbstractLong short-term memory (LSTM) based time series forecasting methods suffer from multiple limitations, such as accumulated error, diminishing temporal correlation, and lacking interpretability, which compromises the prediction performance. To overcome these shortcomings, a fuzzy inference-based LSTM with the embedding of a fuzzy system is proposed to enhance the accuracy and interpretability of LSTM for long-term time series prediction. Firstly, a fast and complete fuzzy rule construction method based on Wang–Mendel (WM) is proposed, which can enhance the computational efficiency and completeness of the WM model by fuzzy rules simplification and complement strategies. Then, the fuzzy prediction model is constructed to capture the fuzzy logic in data. Finally, the fuzzy inference-based LSTM is proposed by integrating the fuzzy prediction fusion, the strengthening memory layer, and the parameter segmentation sharing strategy into the LSTM network. Fuzzy prediction fusion increases the network reasoning capability and interpretability, the strengthening memory layer strengthens the long-term memory and alleviates the gradient dispersion problem, and the parameter segmentation sharing strategy balances processing efficiency and architecture discrimination. Experiments on publicly available time series demonstrate that the proposed method can achieve better performance than existing models for long-term time series prediction.
A dynamic link between spring Arctic sea ice and the Tibetan Plateau snow increment indicator
Authors: Zhang Chao , Duan Anmin , Jia XiaoJing , Wang Zhibiao , Pan Zhulei 
Published: November 2023

AbstractTibetan Plateau snow has long been recognized as a sensitive indicator of climate variability. However, the commonly used snow indicator cannot fully represent the interannual variability in late autumn Tibetan Plateau snow. Here, we establish a snow indicator for Tibetan Plateau snow variability: the snow cover extent increment within late autumn. This snow increment indicator improves the standard deviation by 72.6% and diabatic cooling by 89.7% over the entire Tibetan Plateau, which shows a robust link to the subsequent spring Arctic sea-ice concentration. Faster Tibetan Plateau snow cover extent increment leads to stronger Tibetan Plateau cooling and disturbance along the subtropical westerly jet, thereby inducing a Tibetan Plateau-Arctic wave train and a spring Arctic cyclonic anomaly. This cyclonic system favors the reduction in spring Arctic sea-ice by equatorward sea ice drift, implying a link between spring Arctic sea-ice and the Tibetan Plateau snow increment indicator through the wave train and sea-ice dynamic processes.
Endothelial progenitor cells in pregnancy-related diseases
Authors: Chen Yangyang , Wan Gui , Li Zeyun , Liu Xiaoxia , Zhao Yin , Zou Li , Liu Weifang 
Published: November 2023

Abstract
Placental neovascularization plays a crucial role in fetomaternal circulation throughout pregnancy and is dysregulated in several pregnancy-related diseases, including preeclampsia, gestational diabetes mellitus, and fetal growth restriction. Endothelial progenitor cells (EPCs) are a heterogeneous population of cells that differentiate into mature endothelial cells, which influence vascular homeostasis, neovascularization, and endothelial repair. Since their discovery in 1997 by Asahara et al., the role of EPCs in vascular biology has garnered a lot of interest. However, although pregnancy-related conditions are associated with changes in the number and function of EPCs, the reported findings are conflicting. This review discusses the discovery, isolation, and classification of EPCs and highlights discrepancies between current studies. Overviews of how various diseases affect the numbers and functions of EPCs, the role of EPCs as biomarkers of pregnancy disorders, and the potential therapeutic applications involving EPCs are also provided.
Evaluation of Lifetime Noise Exposure History Reporting
Authors: De Poortere Nele , Verhulst Sarah , Degeest Sofie , Keshishzadeh Sarineh , Dhooge Ingeborg , Keppler Hannah 
Published: November 2023

Purpose:
The purpose of this study is to critically evaluate lifetime noise exposure history (LNEH) reporting. First, two different approaches to evaluate the cumulative LNEH were compared. Second, individual LNEH was associated with the subjects' hearing status. Third, loudness estimates of exposure activities, by means of Jokitulppo- and Ferguson-based exposure levels, were compared with dosimeter sound-level measurements.

Method:
One hundred one young adults completed the questionnaires, and a subgroup of 30 subjects underwent audiological assessment. Pure-tone audiometry, speech-in-noise intelligibility, distortion product otoacoustic emissions, auditory brainstem responses, and envelope following responses were included. Fifteen out of the 30 subjects took part in a noisy activity while wearing a dosimeter.

Results:
First, results demonstrate that the structured questionnaire yielded a greater amount of information pertaining to the diverse activities, surpassing the insights obtained from an open-ended questionnaire. Second, no significant correlations between audiological assessment and LNEH were found. Lastly, the results indicate that Ferguson-based exposure levels offer a more precise estimation of the actual exposure levels, in contrast to Jokitulppo-based estimates.

Conclusions:
We propose several recommendations for determining the LNEH. First, it is vital to define accurate loudness categories and corresponding allocated levels, with a preference for the loudness levels proposed by Ferguson et al. (2019), as identified in this study. Second, a structured questionnaire regarding LNEH is recommended, discouraging open-ended questioning. Third, it is essential to include a separate category exclusively addressing work-related activities, encompassing various activities for more accurate surveying.
Polyvinylchloride surface modified with polymer brushes for reduced protein, cell and bacteria attachment
Authors: Almousa Rashed , Xie Dong , Li Jiliang , Anderson Gregory G. 
Published: November 2023

AbstractThe objective of this study was to coat negatively charged polymer brushes by a covalent bond onto the surface of polyvinylchloride using a simple conventional surface free radical polymerisation technique. The coated surfaces were assessed with contact angle, protein adsorption, cell adhesion, and bacterial adhesion. Bovine serum albumin and bovine fibrinogen were used for protein adsorption evaluation. Mouse fibroblast (NIH‐3T3) cells and Pseudomonas aeruginosa were used to assess surface adhesion. Results show that the surface modified with all the attached polymers exhibited significantly reduced contact angle, protein adsorption, and cell as well as bacterial adhesion among which the negatively charged polymers showed extremely low values in all the tests. The negatively charged polymer shows its contact angle at 5° as compared to 70° for original polyvinylchloride. Its bovine serum albumin, bovine fibrinogen, 3T3 adhesion, and P. aeruginosa adhesion were 93%, 84%, 92%, and 92% lower than the original PVC, respectively. Furthermore, the polyvinylchloride surface coated with negatively charged polymer brushes exhibited a hydrogel‐like property. The results indicate that coating a polyvinylchloride surface with acrylic acids using a simple surface‐initiated free radical polymerisation and then converting those to negatively charged salts can be an effective and efficient route for fouling‐resistant applications.
Bit error rate performance of underwater optical wireless communication with hybrid modulation
Authors: Luo Qiong , Chen Chao , Ji Jianhua , Xu Ming 
Published: November 2023

AbstractTurbulence effects can cause performance degradation for underwater optical wireless communication (UOWC) system. In this paper, a hybrid modulation (modulation–modulation, M–M) is presented to resist turbulence‐induced fading and improve the transmission performance of UOWC systems. The proposed differential phase shift keying‐multiple pulse position modulation (DPSK‐mPPM) is adopted as hybrid modulation to improve the bit error rate (BER) performance over UOWC turbulence channel of Gamma–Gamma distribution. Subsequently, the closed‐form average BER expressions of mPPM and hybrid DPSK‐mPPM modulation are derived and investigated, which are related to the oceanic turbulence parameters. The influence of the variation of anisotropy factor of ocean turbulence is analysed for the UOWC system over strong Gamma–Gamma turbulent channels. Finally, the numerical simulation results demonstrate the effectiveness of proposed DPSK‐mPPM to improve the BER performance compared to the traditional single modulation over UOWC channel under the same conditions. Furthermore, the work of this paper improves the practicality of the proposed DPSK‐mPPM scheme for underwater communication in complex oceanic environments.
Lag‐related noise shrinkage stacked LSTM network for short‐term traffic flow forecasting
Authors: Li Kai , Bai Weihua , Huang Shaowei , Tan Guanru , Zhou Teng , Li Keqin 
Published: November 2023

AbstractFor the transport networks only equipped with sparse or isolated detectors, short‐term traffic flow forecasting faces the following problems: (1) there are only temporal information and no spatial information; (2) the noises in the traffic flow significantly affect the forecasting performance. In this paper, a lag‐related noise shrinkage stacked long short‐term memory (LSTM) network is proposed for the traffic flow forecasting task only related to temporal information. To extract effective temporal features, the optimal time lags are selected in the traffic flow and converted into lag‐related multi‐dimensional data. Then, a discrete wavelet threshold denoising shrinkage algorithm is designed to filter the noises to construct a more reliable training set. A multi‐level stacked LSTM network is employed to learn the features of the training set to map the past traffic flow to the future flow. Four benchmark datasets are to evaluate the forecasting performance by extensive experiments. The comparison with the state‐of‐the‐art models demonstrates an average improvement of 7.28% in MAPE and 6.02% in RMSE. In addition, the proposed method has been applied in the Guilin Travel Network Bus Intelligent Dispatching System. It improves the utilization of the vehicles and reduces operating costs.
Frequency stabilization for interconnected renewable based power system using cascaded model predictive controller with fractional order PID controller
Authors: Sibtain Daud , Rafiq Turab , Bhatti Mehdi Hassan , Shahzad Sulman , Kilic Heybet 
Published: November 2023

AbstractIn today's electrical grid, frequency cannot be ignored. The proliferation of renewable energy sources into a power system degrades its frequency; hence, the need for frequency regulation has been increased as a result. The second major factor is the perturbation in the load that originates the frequency fluctuation which needs to be suppressed in minimum time to avoid any system collapse. The designing of an optimal controller is indispensable because of increasing power system complexity. In order to maintain the stability of the power system, this paper presents the cascaded design of the model predictive controller with fractional order PID controller (MPC‐FOPIDN) to mitigate the frequency oscillations due to disruption in load. The combination of the predictive capabilities of model predictive control (MPC) and fractional order control enhances control abilities, making it an optimal control strategy for load frequency control (LFC). The grasshopper optimization algorithm (GOA) is applied to obtain optimal gains values for the FOPID controller. The efficacy of the controller has effectively mitigated frequency fluctuations caused by a change in demand or any uncertainty in the power system.
Rolling bearing weak fault detection using transient structure‐optimal VMD and adaptive group sparse coding
Authors: Yuan Xing , Liu Hui , Zhang Huijie 
Published: November 2023

AbstractRolling bearings are essential parts in machine equipment and detecting damage in the early stage is crucial for ensuring the safe production and machine life. However, it is difficult to extract weak fault features under strong background noise, discrete harmonic frequency interference and non‐stationary service conditions. This investigation proposes a hybrid fault diagnosis approach utilizing transient structure‐optimal variational mode decomposition (TS‐OVMD) and adaptive group sparse coding (AGSC) for addressing the formidable problem. According to the singular value structure between transient signal and the interference signal, this work investigates the singular value shrinkage (SVS) technique to adaptively obtain the independent components number. Then, we present a transient structure measure (TSM) to adaptively optimize the balance factor. This measure index systematically quantifies the typical characteristics of the bearing fault signal, which can maximize the fault information representation and effectively reduces the useful information loss caused by improper selection of VMD parameters. Finally, a sparse coding model called AGSC is furthermore designed to enhance the fault impulses readability and suppress residual noise based on the sparsity within group property and the TSM. The proposed approach is verified using experimental data and is found to be superiority comparison with the state‐of‐the‐art method.
The need for spatially resolved observations of polycyclic aromatic hydrocarbons in protoplanetary discs
Authors: Lange K. , Dominik C. , Tielens A. G. G. M. 
Published: November 2023

Context. The signatures of polycyclic aromatic hydrocarbons (PAHs) have been observed in protoplanetary discs, and their emission features obtained from spectral energy distributions (SED) have been used in the literature to characterise their size and determine their abundance.
Aims. Two simple disc models (uniform PAH distribution against a PAH gap in the inner disc) are compared to investigate the difference of their SED and obtainable information.
Methods. We used the radiative transfer code RADMC-3D to model the SED of two protoplanetary discs orbiting a typical Herbig star, one of which features a depletion of PAHs in the inner disc. We further created artificial images of the discs at face-on view to extract radial profiles of the PAH emission in the infrared.
Results. We find that the extracted PAH features from an SED provide limited information about the PAHs in protoplanetary disc environments, except for the ionisation state. The distribution of PAHs in a protoplanetary disc influences the total observed PAH luminosity in a non-linear fashion and alters the relative strength between the 3.3 µm and 11.3 µm features. Furthermore, we produced radial profiles at the 3 µm, 6 µm and, 11 µm PAH emission features and find that they follow a double power-law profile where the slope reflects the radiative environment (single photon regime vs. multi-photon regime) in which the PAHs lie.
Conclusions. Using spatially resolved techniques such as IFU or imaging in the era of the James Webb Space Telescope, we find that multi-wavelength radial emission profiles will not only provide information on the spatial distribution of the PAHs, but may also provide information on their size and underlying UV environment, which is crucial for photo-evaporative disc wind models.
Psychopharmakotherapie mit dem MAO-Hemmer Tranylcypromin Schwerpunkte
und Trends aus Theorie und Praxis
Authors: Ulrich Sven , Lewitzka Ute 
Published: November 2023

ZusammenfassungDer irreversible Monoaminoxidase-Hemmer Tranylcypromin ist seit mehr als 60
Jahren als Antidepressivum bekannt. Ziel dieses Übersichtsartikels ist
die Bestimmung des Standes der Wissenschaft und Therapie von Tranylcypromin.
Dafür wird die aktuelle Fachliteratur ausgewertet und hinsichtlich
gegenwärtiger Schwerpunkte und allgemeiner Trends der praktischen
Psychopharmakotherapie eingeordnet. Im Ergebnis kann Tranylcypromin heute durch
neue Metaanalysen kontrollierter Studien als gut etabliert für die
Behandlung der therapieresistenten Depression gelten. Die Dosierung
(Maximaldosis, Erhaltungsdosis) wird zunehmend für Anforderungen der
therapieresistenten Depression angepasst. Die Monoaminoxidase ist nicht nur
primäre pharmakologische Zielstruktur von Tranylcypromin sondern
bestimmt zu Therapiebeginn als arzneistoffmetabolisierendes Enzym
enantioselektiv auch die Pharmakokinetik des Monoaminoxidase-Hemmers. Mit
zunehmender Diversität der antidepressiven Pharmakotherapie ist eine
fortwährende Zuordnung von Tranylcypromin als therapeutische
„ultima ratio“ bei Depression überdenkenswert. Es wird
geschlussfolgert, dass Tranylcypromin als Mittel der zweiten Wahl eine wertvolle
Option der antidepressiven Therapie bleibt. Die Kriterien für eine
Umstellung von anderen Antidepressiva auf den Monoaminoxidase-Hemmer
müssen noch besser definiert werden.
Thermoregulation-Focused Implementation of Delayed Cord Clamping among <34 Weeks' Gestational Age Neonates
Authors: Orton Melissa , Theilen Lauren , Clark Erin , Baserga Mariana , Lauer Sarah , Ou Zhining , Presson Angela P. , Dupont Tara , Katheria Anup , Singh Yogen , Chan Belinda 
Published: November 2023

Objective Delayed cord clamping (DCC) is recommended for all neonates; however, adapting such practice can be slow or unsustainable, especially among preterm neonates. During DCC neonates are exposed to a cool environment, raising concerns for neonatal hypothermia. Moderate hypothermia may induce morbidities that counteract the potential benefits of DCC. A quality improvement project on a thermoregulation-focused DCC protocol was implemented for neonates less than 34 weeks' gestational age (GA). The aim was to increase the compliance rate of DCC while maintaining normothermia.
Study Design The DCC protocol was implemented on October 1, 2020 in a large Level III neonatal intensive care unit. The thermoregulation measures included increasing delivery room temperature and using heat conservation supplies (sterile polyethylene suit, warm towels, and thermal pads). Baseline characteristics, the compliance rate of DCC, and admission temperatures were compared 4 months' preimplementation and 26 months' postimplementation
Results The rate of DCC increased from 20% (11/54) in preimplementation to 57% (240/425) in postimplementation (p < 0.001). The balancing measure of admission normothermia remained unchanged. In a postimplementation subgroup analysis, the DCC cohort had less tendency to experience admission moderate hypothermia (<36°C; 9.2 vs. 14.1%, p = 0.11). The DCC cohort had more favorable secondary outcomes including higher admission hematocrit, less blood transfusions, less intraventricular hemorrhage, and lower mortality. Improving the process measure of accurate documentation could help to identify implementation barriers.
Conclusion Performing DCC in preterm neonates was feasible and beneficial without increasing admission hypothermia.
Key Points
Construction of a Shared Decision-Making Model Between Doctor and Patient in China Based on Selection Preferences
Authors: Lyu Yuwen , Liu Junrong 
Published: November 2023

AbstractInfluenced by Confucian values, China’s medical decision-making emphasizes a family-centric and harmonious approach, contrasting with Western practices that highlight individual autonomy. However, there’s a global shift towards “patient-centered” care, promoting shared decision-making (SDM) between healthcare practitioners and patients. This study aims to advance the SDM model in China by analyzing the alignment in decision-making between doctors and patients. The focus is on addressing the absence of quantitative tools for SDM coordination. An SDM coupling coordination model was developed, and the coordination level was assessed using data from questionnaires filled by 210 doctors and 248 patients from three prominent Chinese hospitals. Doctors’ and patients’ preferences were categorized into four areas: treatment efficacy, cost considerations, potential side effects, and overall treatment experience. The coordination degrees, represented by “D values,” for these areas were 0.6375, 0.5299, 0.5704, and 0.4586, respectively. A higher “D value” signifies better alignment between doctors and patients. Treatment efficacy showed the strongest alignment, followed by costs and side effects, while treatment experience had the least alignment. In conclusion, the alignment in doctor–patient SDM in China is currently not optimal. Improvements necessitate a foundational “patient-first” approach in SDM, an emphasis on optimization in collaborative strategies, and the establishment of a comprehensive platform for collaboration and coordination in SDM.