bluuebunny/crossref_metadata_2025_split huggingface dataset:
The role of a low protein diet supplemented with ketoanalogues on kidney progression in pre-dialysis chronic kidney disease patients
Authors: Ariyanopparut Saravanee , Metta Kamonchanok , Avihingsanon Yingyos , Eiam-Ong Somchai , Kittiskulnam Piyawan 
Published: September 2023

AbstractIn slowing kidney progression, numerous pre-dialysis chronic kidney disease (CKD) patients could not adhere to the well-established dietary pattern, including a very low protein diet, 0.3–0.4 g/kg/day, plus a full dose ketoanalogues (KAs) of amino acids. We evaluated the role of a low protein diet (LPD), 0.6–0.8 g/kg/day, combined with KAs (LPD–KAs) on CKD progression. We extracted data in the retrospective cohort using electronic medical records (n = 38,005). Participants with LPD–KAs for longer than six months were identified. An unmatched control group, LPD alone, was retrieved from the same database. Cox proportional hazard models were performed to examine the associations between LPD–KAs and outcomes. The primary outcome was either a rapid estimated glomerular filtration rate (eGFR) decline > 5 mL/min/1.73m2/year or commencing dialysis. Other secondary outcomes include changes in proteinuria, serum albumin, and other metabolic profiles were also assessed. A total of 1042 patients were finally recruited (LPD–KAs = 543). Although patients with LPD–KAs had significantly lower eGFR and a prevalence of diabetes, age, and dietary protein intake were comparable between LPD–KAs (0.7 ± 0.2 g/kg/day) and LPD alone groups (0.7 ± 0.3 g/kg/day, p = 0.49). During a median follow-up of 32.9 months, patients treated with LPD–KAs had a significantly lower risk of kidney function decline (HR 0.13; 95% CI 0.09–0.19, p < 0.001) and dialysis initiation (HR 0.24; 95% CI 0.12–0.49, p < 0.001) than LPD alone after adjusting for confounders. The annual rate of eGFR decline in patients receiving LPD–KAs was 4.5 [3.4–5.5] mL/min/1.73m2 compared with 7.7 [6.0–9.4] mL/min/1.73m2 in LPD alone (p = 0.001). According to KAs dose–response analysis, the daily dose of ≤ 5 tablets was conversely associated with a higher risk of the primary endpoint, whereas the association disappeared among patients receiving a dose of > 6 tablets. The spot urine protein creatinine ratio and serum phosphate levels were not significantly different between groups. LPD–KAs could retard kidney progression compared with LPD alone. This favorable effect was significant among CKD patients receiving a daily KAs dose of more than six tablets. Future randomized controlled trials should be performed to verify these findings.
Intensification of Arabian Sea cyclone genesis potential and its association with Warm Arctic Cold Eurasia pattern
Authors: Vidya P. J. , Chatterjee Sourav , Ravichandran M. , Gautham S. , Nuncio M. , Murtugudde R. 
Published: September 2023

AbstractThe present study examines the drivers of the observed increasing trend in the Genesis Potential Index (GPI) of the post-monsoon season (October-November-December) tropical cyclones in the Arabian Sea (AS) during the period, 1998–2021. The increase in atmospheric moisture loading, ocean heat content in the upper 300 m (OHC300) and reduction in vertical wind shear are the major factors which caused the intensification in cyclone GPI in the recent decades. The increase in atmospheric moisture loading and OHC300 are consistent with the overall observed ocean warming trend of the region. However, the reduction in vertical wind shear has resulted from an anomalous large-scale upper atmospheric anticyclonic circulation over central India. Further investigation shows a concurrent transition of the Warm Arctic Cold Eurasia (WACE) pattern to its positive phase which strengthened and shifted the Subtropical Jet (STJ) poleward. This resulted in the anticyclonic circulation anomaly and altered the upper tropospheric zonal winds over the AS cyclone genesis region, weakening the vertical wind shear. The study demonstrates a possible physical mechanism through which remote forcing due to changes in the northern high-latitude climate can influence the AS cyclone genesis.
Deep learning driven de novo drug design based on gastric proton pump structures
Authors: Abe Kazuhiro , Ozako Mami , Inukai Miki , Matsuyuki Yoe , Kitayama Shinnosuke , Kanai Chisato , Nagai Chiaki , Gopalasingam Chai C. , Gerle Christoph , Shigematsu Hideki , Umekubo Nariyoshi , Yokoshima Satoshi , Yoshimori Atsushi 
Published: September 2023

AbstractExisting drugs often suffer in their effectiveness due to detrimental side effects, low binding affinity or pharmacokinetic problems. This may be overcome by the development of distinct compounds. Here, we exploit the rich structural basis of drug-bound gastric proton pump to develop compounds with strong inhibitory potency, employing a combinatorial approach utilizing deep generative models for de novo drug design with organic synthesis and cryo-EM structural analysis. Candidate compounds that satisfy pharmacophores defined in the drug-bound proton pump structures, were designed in silico utilizing our deep generative models, a workflow termed Deep Quartet. Several candidates were synthesized and screened according to their inhibition potencies in vitro, and their binding poses were in turn identified by cryo-EM. Structures reaching up to 2.10 Å resolution allowed us to evaluate and re-design compound structures, heralding the most potent compound in this study, DQ-18 (N-methyl-4-((2-(benzyloxy)-5-chlorobenzyl)oxy)benzylamine), which shows a Ki value of 47.6 nM. Further high-resolution cryo-EM analysis at 2.08 Å resolution unambiguously determined the DQ-18 binding pose. Our integrated approach offers a framework for structure-based de novo drug development based on the desired pharmacophores within the protein structure.
Carbon dioxide and nitrate co-electroreduction to urea on CuOxZnOy
Authors: Anastasiadou Dimitra , Ligt Bianca , He Yunyang , van de Poll Rim C. J. , Simons Jérôme F. M. , Figueiredo Marta Costa 
Published: September 2023

AbstractUrea is a commonly used nitrogen fertiliser synthesised from ammonia and carbon dioxide using thermal catalysis. This process results in high carbon dioxide emissions associated with the required amounts of ammonia. Electrocatalysis provides an alternative method to urea production with reduced carbon emissions while utilising waste products like nitrate. This manuscript reports on urea synthesis from the electroreduction of nitrate and carbon dioxide using CuOxZnOy electrodes under mild conditions. Catalysts with different ratios of CuO and ZnO, synthesised via flame spray pyrolysis, were explored for the reaction. The results revealed that all the CuOxZnOy electrocatalyst compositions produce urea, but the efficiency strongly depends on the metal ratio composition of the catalysts. The CuO50ZnO50 composition had the best performance in terms of selectivity (41% at −0.8 V vs RHE) and activity (0.27 mA/cm2 at −0.8 V vs RHE) towards urea production. Thus, this material is one of the most efficient electrocatalysts for urea production reported so far. This study systematically evaluates bimetallic catalysts with varying compositions for urea synthesis from carbon dioxide and nitrate.
Tera-sample-per-second arbitrary waveform generation in a synthetic dimension
Authors: Guan Yiran , Zhang Jiejun , Li Lingzhi , Cao Ruidong , Wang Guangying , Chen Jingxu , Wang Xudong , Guan Bai-Ou , Yao Jianping 
Published: September 2023

AbstractSynthetic dimension opens new horizons in quantum physics and topological photonics by enabling new dimensions for field and particle manipulations. The most appealing property of the photonic synthetic dimension is its ability to emulate high-dimensional optical behavior in a unitary physical system. Here we show that the photonic synthetic dimension can transform technical problems in photonic systems between dimensionalities, providing unexpected solutions to technical problems that are otherwise challenging. Specifically, we propose and experimentally demonstrate a fully reconfigurable photonic Galton board (PGB) in the temporal synthetic dimension, in which the temporal high-speed challenge is translated into a spatial fiber-optic length matching problem, leading to the generation of tera-sample-per-second arbitrary waveforms with ultimate flexibility. In the experiments, an arbitrary waveform with a widely tunable sampling rate, ranging from 10.42 GSa/s to a record high of 1.64 TSa/s, is demonstrated. The concept of dimension conversion offers possible solutions to various physical dimension-related problems, such as super-resolution imaging, high-resolution spectroscopy, and high-precision time measurement.
Electron flux is a key determinant of uranium isotope fractionation during bacterial reduction
Authors: Brown Ashley R. , Molinas Margaux , Roebbert Yvonne , Sato Ataru , Abe Minori , Weyer Stefan , Bernier-Latmani Rizlan 
Published: September 2023

AbstractUranium isotopic signatures in the rock record are utilized as a proxy for past redox conditions on Earth. However, these signatures display significant variability that complicates the interpretation of specific redox conditions. Using the model uranium-reducing bacterium, Shewanella oneidensis MR-1, we show that the abundance of electron donors (e.g., labile organic carbon) controls uranium isotope fractionation, such that high electron fluxes suppress fractionation. Further, by purifying a key uranium-reducing enzyme, MtrC, we show that the magnitude of fractionation is explicitly controlled by the protein redox state. Finally, using a mathematical framework, we demonstrate that these differences in fractionation arise from the propensity for back-reaction throughout the multi-step reduction of hexavalent uranium. To improve interpretations of observed fractionations in natural environments, these findings suggest that a variable intrinsic fractionation factor should be incorporated into models of uranium isotope systematics to account for differences in electron flux caused by organic carbon availability.
Linking bacterial tetrabromopyrrole biosynthesis to coral metamorphosis
Authors: Alker Amanda T , Farrell Morgan V , Demko Alyssa M , Purdy Trevor N , Adak Sanjoy , Moore Bradley S , Sneed Jennifer M , Paul Valerie J , Shikuma Nicholas J 
Published: September 2023

Abstract
An important factor dictating coral fitness is the quality of bacteria associated with corals and coral reefs. One way that bacteria benefit corals is by stimulating the larval to juvenile life cycle transition of settlement and metamorphosis. Tetrabromopyrrole (TBP) is a small molecule produced by bacteria that stimulates metamorphosis with and without attachment in a range of coral species. A standing debate remains, however, about whether TBP biosynthesis from live Pseudoalteromonas bacteria is the primary stimulant of coral metamorphosis. In this study, we create a Pseudoalteromonas sp. PS5 mutant lacking the TBP brominase gene, bmp2. Using this mutant, we confirm that the bmp2 gene is critical for TBP biosynthesis in Pseudoalteromonas sp. PS5. Mutation of this gene ablates the bacterium’s ability in live cultures to stimulate the metamorphosis of the stony coral Porites astreoides. We further demonstrate that expression of TBP biosynthesis genes is strongest in stationary and biofilm modes of growth, where Pseudoalteromonas sp. PS5 might exist within surface-attached biofilms on the sea floor. Finally, we create a modular transposon plasmid for genomic integration and fluorescent labeling of Pseudoalteromonas sp. PS5 cells. Our results functionally link a TBP biosynthesis gene from live bacteria to a morphogenic effect in corals. The genetic techniques established here provide new tools to explore coral-bacteria interactions and could help to inform future decisions about utilizing marine bacteria or their products for coral restoration.
Theoretical study coupling DFT calculations and kMC simulation of CO methanation on Ni(111) and Ni3Fe(111)
Authors: Yu Yingzhe , Ji Peng , Zhang Weiwei , Yang Kuiwei , Zhang Minhua 
Published: September 2023

Due to their high activity, good selectivity of CH4, low price and easy availability, Ni-based catalysts are of the most practical in terms of application value and development prospects in the field of SNG, and have been widely investigated in academia and industry.
Differences in Child Language Assessment Practices Between School-Based and Non–School-Based Speech-Language Pathologists: Results From a Nationwide Survey
Authors: Fulcher-Rood Katrina , Castilla-Earls Anny 
Published: September 2023

Purpose:
The purpose of this study was to compare child language assessment practices of speech-language pathologists (SLPs) working in school and nonschool settings to determine if their place of employment impacts the diagnostic decision-making process.

Method:

School-based SLPs (e.g., direct service providers employed in preschool and/or K–12 schools;
n
= 382) and non–school-based SLPs (e.g., direct service providers employed in private practices, university clinics, and/or medical settings;
n
= 147) completed a web-based questionnaire. The questionnaire examined the types, frequency, and perceived importance of specific assessment tools and potential workplace factors that may impact their diagnostic decision-making process.

Results:
Both school-based and non–school-based SLPs reported using a combination of assessment tools when evaluating children with potential language disorders. School-based SLPs tended to rank the frequency of use and importance of most assessment tools similarly, while non–school-based SLPs ranked interviews as the most frequently used and most important assessment tool. Statistically significant group differences indicated that school-based SLPs ranked the frequency of use and importance of standardized testing higher compared to their non–school-based counterparts. Also, school-based SLPs rated employment-based factors impacting diagnostic decision making higher compared to non–school-based SLPs.

Conclusions:
SLPs practicing in school-based settings seem to handle more employment-based factors that impact independent diagnostic decision making than SLPs working in different employment settings when assessing children for potential language disorders. Clinical recommendations are provided, and implications for implementation-based assessment research in child language are discussed.
Complete Vocal Technique-Voice Therapy as a Novel Intervention for Rehabilitation of Laryngeal-Phonatory Dysfunction in Acquired Brain Injury Patients—An Exploratory Retrospective Study
Authors: Aaen Mathias , Rose Alies , Christoph Noor , Sadolin Cathrine , McGlashan Julian 
Published: September 2023

Purpose:
The purpose of this study was to explore the use of Complete Vocal Technique (CVT) voice therapy in acquired brain injury (ABI) patients

Study:
This study is an exploratory retrospective study.

Method:

Five ABI patients (two female and three male) with an average age of 20.6 years (
SD
= 3.5) received CVT voice therapy from an authorized CVT teacher at a neurorehabilitation facility in conjunction with physical rehabilitation therapy and speech and language therapy. Pre- and postmeasures included Voice Handicap Index, Maximum Phonation Time, electroglottography, and acoustic measures.

Results:
All voice measures improved for all five patients after receiving CVT voice therapy. Voice Handicap Index scores decreased from an average of 48.4 to 22.8. Maximum Phonation Time improved while the electroglottography and acoustic data showed improved phonation stability in jitter and shimmer measures. Overall, following the intervention, patients demonstrated improved loudness range, improved range in contact quotient for different sound conditions, faster-paced speech, extended functional pitch range, and decrease in unwanted creaking and breathiness.

Conclusions:
The findings suggest that CVT may be used as therapy in ABI populations with promising results. Both patient self-assessment and objective voice measures demonstrate improved voice function. Given the longitudinal nature of recovery in ABI patients, more studies are needed to qualify at which stage(s) of recovery the CVT interventions are most effective and beneficial. Randomized controlled trials for specific patient populations of ABI are needed to assess the interventions' effectiveness in specific ABI diagnoses.
Parent-Reported Attention-Deficit/Hyperactivity Disorder–Linked Behaviors, Fatigue, and Language in Children Who Are Deaf and Hard of Hearing
Authors: Mattingly Jessica , Werfel Krystal L. , Lund Emily 
Published: September 2023

Purpose:The purpose of this study was to find out if children who are deaf and hard of hearing (DHH), particularly those without substantially delayed language, appear to be at risk for overreporting of inattentive and hyperactive behaviors and if attention-deficit/hyperactivity disorder (ADHD) measures are influenced by the presence of language-based items, by child language skills, and by child and parent report of fatigue.Method:This study included 24 children with typical hearing, 13 children with hearing aids (HA), and 16 children with cochlear implants (CI) in second through sixth grade. Parents of children in each group completed a measure reporting on inattentive and hyperactive behaviors, social and academic outcomes, and general fatigue for their child. Children participated in a norm-referenced language assessment and completed a self-report of fatigue.Results:Analyses revealed an effect of hearing status on overall inattention ratings and social/academic performance: Children with CI had significantly lower ratings of inattention, and children with HA had more social/academic performance deficits. Differences in inattention scores for children with CI remained even when items biased toward language skills were removed from the measure, but differences in performance for children with HA disappeared. Omnibus language scores significantly correlated with academic and social outcomes, whereas parent report of fatigue significantly correlated with inattention and hyperactivity.Conclusions:Parent report of behaviors linked with ADHD, including inattention and hyperactivity, is likely influenced by child language knowledge and overall fatigue. Comorbid diagnosis of ADHD in children who are DHH must consider these factors.
A novel optimally tuned super twisting sliding mode controller for active and reactive power control in grid‐interfaced photovoltaic system
Authors: Mohapatra Bhabasis , Sahu Binod Kumar , Pati Swagat 
Published: September 2023

AbstractIn photovoltaic (PV) systems, inverters play a crucial role for supplying electricity to meet the demand while maintaining power quality. For a local load connected to a grid‐interfaced photovoltaic (GIPV) system, active and reactive power control is necessary at the distribution level. Thus, the foremost purpose of this article is to get the best optimally designed robust controller for control of active and reactive power. A GIPV system with Improved Arithmetic Optimisation Algorithm (IAOA)‐based Super Twisting Sliding Mode Controller (ST‐SMC) methodology has been proposed in this article for active and reactive power management. The conventional PI controller in the GIPV system that is most frequently used has considerable undershoot and a long settling period. PI controller tuning parameters were also changed to account for the wide change in the reference pattern. Therefore, STSMC and SMC are used for ensuring robustness against external disturbances. The conventional SMC comes out to have a chattering issue. Furthermore, the proposed IAOA technique is validated through some benchmark functions. The proposed IAOA technique outperforms Particle Swarm Optimisation (PSO), Forensic Based Investigation (FBI), and Traditional Arithmetic Optimisation Algorithm (TAOA) in terms of the number of iterations and accurately achieving optimal solutions for active and reactive power control. The results show that the proposed IAOA‐based STSMC technique has an improved performance of settling time and undershoot for active and reactive power control. This article also presents stability analysis and robustness test of the above mentioned controllers to illustrate the effectiveness of each optimally designed controller. A 40 kW GIPV system performance is evaluated using the MATLAB environment, and the results are validated in a real‐time simulator platform OPAL‐RT 4510.
A self‐supervised causal feature reinforcement learning method for non‐invasive hemoglobin prediction
Authors: Xu Linquan , Chen Yuwen , Lu Songmei , Zhong Kunhua , Li Yujie , Yi Bin 
Published: September 2023

AbstractAnemia (hemoglobin (Hb) < 12.0 g/dL) is significantly correlated with many diseases. An invasive technique is the peripheral blood Hb detection method, which is used to examine red and white blood cells and platelets in clinical laboratory settings. However, non‐invasive methods for measuring Hb mainly include low‐precision prediction based on eye images and complex operation prediction based on fundus images. Moreover, these types of anemia testing techniques are time‐consuming, tedious, or prone to errors. Thus, developing a convenient and high‐precision method is vital for predicting Hb concentration. This study proposes self‐supervised causal features using actor‐critical reinforcement learning to improve the model prediction performance. Two networks are proposed: Actor Predictor and Hemoglobin Predictor to predict Hb concentration. Moreover, the model performance is evaluated using different techniques, namely, Mean Absolute Error (MAE) and Mean Square Error (MSE), via real eye image data and a smartphone. This model achieved 1.19(1.01,1.38) on the MAE and 2.25(1.59,2.90) on the MSE, which outperformed previous eye images' Hb prediction methods and was nearly similar to the fundus images' Hb prediction methods. The inference time was less than 0.05 s, making it efficient and accurate for predicting Hb. This model can be used for mobile deployment and health self‐screening.
Traffic speed prediction using GARCH‐GRU hybrid model
Authors: Ali Muhammad , Yusof Kamaludin Mohamad , Wilson Benjamin , Ziegelmueller Carina 
Published: September 2023

AbstractTraffic speed prediction is an integral part of an intelligent transportation system (ITS) because an advanced knowledge of traffic speed can help taking proactive preventive steps to avoid impending problems and it can also help in trip planning. Traffic speed data comprises a time series that may be modelled using any statistical or machine learning technique. In most of the cases, however, the performance of such models is bottlenecked due to heteroskedasticity usually present in such datasets. ARCH/GARCH family of models are generally used to model variance in such data. This paper presents a novel technique, termed as GARCH‐GRU, based on additive decomposition that splits data into random (residual) and deterministic parts. Random part is normalized using rolling standard deviation. GARCH (1, 1) is used to predict conditional variance of the residual and the predicted variance is then used in the basic model equation along with normalized residual that mimic white noise as required by the model. The data other than residual is modelled using a GRU model. The approach is applied to two datasets corresponding to a downtown road and a motorway. For comparison, the same datasets are exposed to three classical techniques; seasonal ARIMA, CNN and GRU techniques. The results demonstrate that the GARCH‐GRU technique outperforms others for random data of downtown road but fails to handle dynamic variations present in the motorway data.