bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing photovoltaic parameter estimation: integration of non-linear hunting and reinforcement learning strategies with golden jackal optimizer
Authors: Sundar Ganesh Chappani Sankaran , Kumar Chandrasekaran , Premkumar Manoharan , Derebew Bizuwork 
Published: February 2024

AbstractThe advancement of Photovoltaic (PV) systems hinges on the precise optimization of their parameters. Among the numerous optimization techniques, the effectiveness of each often rests on their inherent parameters. This research introduces a new methodology, the Reinforcement Learning-based Golden Jackal Optimizer (RL-GJO). This approach uniquely combines reinforcement learning with the Golden Jackal Optimizer to enhance its efficiency and adaptability in handling various optimization problems. Furthermore, the research incorporates an advanced non-linear hunting strategy to optimize the algorithm’s performance. The proposed algorithm is first validated using 29 CEC2017 benchmark test functions and five engineering-constrained design problems. Secondly, rigorous testing on PV parameter estimation benchmark datasets, including the single-diode model, double-diode model, three-diode model, and a representative PV module, was carried out to highlight the superiority of RL-GJO. The results were compelling: the root mean square error values achieved by RL-GJO were markedly lower than those of the original algorithm and other prevalent optimization methods. The synergy between reinforcement learning and GJO in this approach facilitates faster convergence and improved solution quality. This integration not only improves the performance metrics but also ensures a more efficient optimization process, especially in complex PV scenarios. With an average Freidman’s rank test values of 1.564 for numerical and engineering design problems and 1.742 for parameter estimation problems, the proposed RL-GJO is performing better than the original GJO and other peers. The proposed RL-GJO stands out as a reliable tool for PV parameter estimation. By seamlessly combining reinforcement learning with the golden jackal optimizer, it sets a new benchmark in PV optimization, indicating a promising avenue for future research and applications.
The phylogeography of Middle Eastern tree frogs in Israel
Authors: Surizon Gal Mesika , Geffen Eli , Roll Uri , Gafny Sarig , Perl R. G. Bina 
Published: February 2024

AbstractWestern Palearctic treefrogs of the genusHylaprovide an example of a morphologically and ecologically cryptic group. Up to three distinctHylaspecies have been proposed as resident in Israel and this number has consistently been subject to taxonomical debates. Here, we analyzed 16S rRNA and COI gene fragments of 658 individuals sampled at 47 pools in nine regions across Israel and the West Bank in order to resolve the taxonomic status ofHylafrogs. We generated both Bayesian and Maximum Likelihood phylogenies, and constructed time-calibrated trees to provide an evolutionary and historical context of sequence variations. We further applied SAMOVA as well as Monmonier’s maximum-difference algorithm to study the genetic structure among populations and to identify potential zones acting as barriers to gene flow across locations. Our results revealed two distinct haplogroups for each gene fragment, with 95% CI divergence times dated from 8.9–17.1 Mya (16S) and 7.1–23.6 Mya (COI), respectively. SAMOVA and barrier analyses partitioned the populations into three groups. Our results highlight that, while there are probably only twoHylaspecies in Israel, one population of one of the species might qualify as a separate evolutionarily significant unit. Our findings elucidate the taxonomic status ofHylafrogs in Israel and provide the basis for determining appropriate management and conservation priorities.
The invention of writing on Rapa Nui (Easter Island). New radiocarbon dates on the Rongorongo script
Authors: Ferrara Silvia , Tassoni Laura , Kromer Bernd , Wacker Lukas , Friedrich Michael , Tonini Francesca , Lastilla Lorenzo , Ravanelli Roberta , Talamo Sahra 
Published: February 2024

AbstractPlacing the origin of an undeciphered script in time is crucial to understanding the invention of writing in human history. Rapa Nui, also known as Easter Island, developed a script, now engraved on fewer than 30 wooden objects, which is still undeciphered. Its origins are also obscure. Central to this issue is whether the script was invented before European travelers reached the island in the eighteenth century AD. Hence direct radiocarbon dating of the wood plays a fundamental role. Until now, only two tablets were directly dated, placing them in the nineteenth c. AD, which does not solve the question of independent invention. Here we radiocarbon-dated four Rongorongo tablets preserved in Rome, Italy. One specimen yielded a unique and secure mid-fifteenth c. date, while the others fall within the nineteenth c. AD. Our results suggest that the use of the script could be placed to a horizon that predates the arrival of external influence.
Association between uric acid and cardiac outcomes mediated by neutrophil-to-lymphocyte ratio in patients with left ventricular diastolic dysfunction and pulmonary hypertension
Authors: Du Ping , Gao Xin , Sun Qiaobing , Gong Minghui , Pan Yu , Guo Qinpeng , Zhao Xu , Guo Ran , Liu Yan 
Published: February 2024

AbstractTo evaluate the association of uric acid (UA) with adverse outcomes and its potential mediator in patients with left ventricular diastolic dysfunction (LVDD) and pulmonary hypertension (PH). We retrospectively analyzed 234 patients with LVDD and PH. The baseline characteristics of patients with low UA (≤ 330 µmol/L) group were compared with high UA (> 330 µmol/L) group. Adverse outcomes included all-cause mortality, cardiac death and heart failure (HF) hospitalization. Their association with UA and the mediator were evaluated using Cox regression and mediation analysis. The mediation proportion was further quantified by the R mediation package. During a mean follow-up of 50 ± 18 months, there were 27 all-cause deaths, 18 cardiovascular deaths and 41 incidents of HF hospitalization. Multivariable Cox regression analysis showed UA was an independent risk factor of adverse outcomes in LVDD and PH patients, even after adjusting for age, sex, body mass index, medical histories, systolic blood pressure, fasting blood glucose, total cholesterol, triglyceride, eGFR, BNP and medications. The hazard ratios (HRs) for UA (per 10 µmol/L increase) were as below: for all-cause mortality, HR 1.143, 95% CI 1.069–1.221, P < 0.001; for cardiac death, HR 1.168, 95% CI 1.064–1.282, P = 0.001; for HF hospitalization, HR 1.093, 95% CI 1.035–1.155, P = 0.001. Neutrophil-to-lymphocyte ratio (NLR) played a partial mediation role in the association, and the mediation proportion for NLR on the UA-adverse outcomes were 21%, 19% and 17%, respectively. In patients of LVDD with PH, higher UA level was independently correlated with adverse outcomes. Furthermore, NLR partially mediated the effect of UA on the risk of all-cause mortality, cardiac death and HF hospitalization.
Differential functional consequences of GRIN2A mutations associated with schizophrenia and neurodevelopmental disorders
Authors: Shepard Nate , Baez-Nieto David , Iqbal Sumaiya , Kurganov Erkin , Budnik Nikita , Campbell Arthur J. , Pan Jen Q. , Sheng Morgan , Farsi Zohreh 
Published: February 2024

AbstractHuman genetic studies have revealed rare missense and protein-truncating variants in GRIN2A, encoding for the GluN2A subunit of the NMDA receptors, that confer significant risk for schizophrenia (SCZ). Mutations in GRIN2A are also associated with epilepsy and developmental delay/intellectual disability (DD/ID). However, it remains enigmatic how alterations to the same protein can result in diverse clinical phenotypes. Here, we performed functional characterization of human GluN1/GluN2A heteromeric NMDA receptors that contain SCZ-linked GluN2A variants, and compared them to NMDA receptors with GluN2A variants associated with epilepsy or DD/ID. Our findings demonstrate that SCZ-associated GRIN2A variants were predominantly loss-of-function (LoF), whereas epilepsy and DD/ID-associated variants resulted in both gain- and loss-of-function phenotypes. We additionally show that M653I and S809R, LoF GRIN2A variants associated with DD/ID, exert a dominant-negative effect when co-expressed with a wild-type GluN2A, whereas E58Ter and Y698C, SCZ-linked LoF variants, and A727T, an epilepsy-linked LoF variant, do not. These data offer a potential mechanism by which SCZ/epilepsy and DD/ID-linked variants can cause different effects on receptor function and therefore result in divergent pathological outcomes.
Targeting the receptor binding domain and heparan sulfate binding for antiviral drug development against SARS-CoV-2 variants
Authors: Yang Zi-Sin , Li Tzong-Shiun , Huang Yu-Sung , Chang Cheng-Chung , Chien Ching-Ming 
Published: February 2024

AbstractThe emergence of SARS-CoV-2 variants diminished the efficacy of current antiviral drugs and vaccines. Hence, identifying highly conserved sequences and potentially druggable pockets for drug development was a promising strategy against SARS-CoV-2 variants. In viral infection, the receptor-binding domain (RBD) proteins are essential in binding to the host receptor. Others, Heparan sulfate (HS), widely distributed on the surface of host cells, is thought to play a central role in the viral infection cycle of SARS-CoV-2. Therefore, it might be a reasonable strategy for antiviral drug design to interfere with the RBD in the HS binding site. In this study, we used computational approaches to analyze multiple sequences of coronaviruses and reveal important information about the binding of HS to RBD in the SARS-CoV-2 spike protein. Our results showed that the potential hot-spots, including R454 and E471, in RBD, exhibited strong interactions in the HS-RBD binding region. Therefore, we screened different compounds in the natural product database towards these hot-spots to find potential antiviral candidates using LibDock, Autodock vina and furthermore applying the MD simulation in AMBER20. The results showed three potential natural compounds, including Acetoside (ACE), Hyperoside (HYP), and Isoquercitrin (ISO), had a strong affinity to the RBD. Our results demonstrate a feasible approach to identify potential antiviral agents by evaluating the binding interaction between viral glycoproteins and host receptors. The present study provided the applications of the structure-based computational approach for designing and developing of new antiviral drugs against SARS-CoV-2 variants.
Genome sequencing and functional analysis of a multipurpose medicinal herb Tinospora cordifolia (Giloy)
Authors: Mahajan Shruti , Chakraborty Abhisek , Bisht Manohar S. , Sil Titas , Sharma Vineet K. 
Published: February 2024

AbstractTinospora cordifolia (Willd.) Hook.f. & Thomson, also known as Giloy, is among the most important medicinal plants that have numerous therapeutic applications in human health due to the production of a diverse array of secondary metabolites. To gain genomic insights into the medicinal properties of T. cordifolia, the genome sequencing was carried out using 10× Genomics linked read and Nanopore long-read technologies. The draft genome assembly of T. cordifolia was comprised of 1.01 Gbp, which is the genome sequenced from the plant family Menispermaceae. We also performed the genome size estimation for T. cordifolia, which was found to be 1.13 Gbp. The deep sequencing of transcriptome from the leaf tissue was also performed. The genome and transcriptome assemblies were used to construct the gene set, resulting in 17,245 coding gene sequences. Further, the phylogenetic position of T. cordifolia was also positioned as basal eudicot by constructing a genome-wide phylogenetic tree using multiple species. Further, a comprehensive comparative evolutionary analysis of gene families contraction/expansion and multiple signatures of adaptive evolution was performed. The genes involved in benzyl iso-quinoline alkaloid, terpenoid, lignin and flavonoid biosynthesis pathways were found with signatures of adaptive evolution. These evolutionary adaptations in genes provide genomic insights into the presence of diverse medicinal properties of this plant. The genes involved in the common symbiosis signalling pathway associated with endosymbiosis (Arbuscular Mycorrhiza) were found to be adaptively evolved. The genes involved in adventitious root formation, peroxisome biogenesis, biosynthesis of phytohormones, and tolerance against abiotic and biotic stresses were also found to be adaptively evolved in T. cordifolia.
A pilot study of measuring emotional response and perception of LLM-generated questionnaire and human-generated questionnaires
Authors: Zou Zhao , Mubin Omar , Alnajjar Fady , Ali Luqman 
Published: February 2024

AbstractThe advent of ChatGPT has sparked a heated debate surrounding natural language processing technology and AI-powered chatbots, leading to extensive research and applications across various disciplines. This pilot study aims to investigate the impact of ChatGPT on users' experiences by administering two distinct questionnaires, one generated by humans and the other by ChatGPT, along with an Emotion Detecting Model. A total of 14 participants (7 female and 7 male) aged between 18 and 35 years were recruited, resulting in the collection of 8672 ChatGPT-associated data points and 8797 human-associated data points. Data analysis was conducted using Analysis of Variance (ANOVA). The results indicate that the utilization of ChatGPT enhances participants' happiness levels and reduces their sadness levels. While no significant gender influences were observed, variations were found about specific emotions. It is important to note that the limited sample size, narrow age range, and potential cultural impacts restrict the generalizability of the findings to a broader population. Future research directions should explore the impact of incorporating additional language models or chatbots on user emotions, particularly among specific age groups such as older individuals and teenagers. As one of the pioneering works evaluating the human perception of ChatGPT text and communication, it is noteworthy that ChatGPT received positive evaluations and demonstrated effectiveness in generating extensive questionnaires.
Development and validation of a cuproptosis-related prognostic model for acute myeloid leukemia patients using machine learning with stacking
Authors: Wang Xichao , Sun Hao , Dong Yongfei , Huang Jie , Bai Lu , Tang Zaixiang , Liu Songbai , Chen Suning 
Published: February 2024

AbstractOur objective is to develop a prognostic model focused on cuproptosis, aimed at predicting overall survival (OS) outcomes among Acute myeloid leukemia (AML) patients. The model utilized machine learning algorithms incorporating stacking. The GSE37642 dataset was used as the training data, and the GSE12417 and TCGA-LAML cohorts were used as the validation data. Stacking was used to merge the three prediction models, subsequently using a random survival forests algorithm to refit the final model using the stacking linear predictor and clinical factors. The prediction model, featuring stacking linear predictor and clinical factors, achieved AUC values of 0.840, 0.876 and 0.892 at 1, 2 and 3 years within the GSE37642 dataset. In external validation dataset, the corresponding AUCs were 0.741, 0.754 and 0.783. The predictive performance of the model in the external dataset surpasses that of the model simply incorporates all predictors. Additionally, the final model exhibited good calibration accuracy. In conclusion, our findings indicate that the novel prediction model refines the prognostic prediction for AML patients, while the stacking strategy displays potential for model integration.
Process implications on the stability and reliability of 300 mm FAB MoS2 field-effect transistors
Authors: Illarionov Yu. Yu. , Karl A. , Smets Q. , Kaczer B. , Knobloch T. , Panarella L. , Schram T. , Brems S. , Cott D. , Asselberghs I. , Grasser T. 
Published: February 2024

AbstractRecent advances in fabricating field-effect transistors with MoS2 and other related two-dimensional (2D) semiconductors have inspired the industry to begin with the integration of these emerging technologies into FAB-compatible process flows. Just like in the lab research on 2D devices performed in the last decade, focus during development is typically put on pure technology-related issues, such as low-temperature growth methods of large-area 2D films on target substrates, damage-free transfer from sacrificial substrates and growth of top-gate oxides. With maturing technology, the problem of stability limitations caused by oxide traps is gradually coming into focus now. Thus, here we report an in-depth analysis of hysteresis and bias-temperature instabilities for MoS2 FETs fabricated using a 300 mm FAB-compatible process. By performing a comprehensive statistical analysis on devices with top gate lengths ranging between 18 nm and 10 μm, we demonstrate that aggressive scaling results in additional stability problems, likely caused by defective edges of the scaled top gates, in particular at higher operation temperatures. These are important insights for understanding and addressing the stability limitations in future nanoscale 2D FETs produced using FAB process lines.
Criticality in FitzHugh-Nagumo oscillator ensembles: Design, robustness, and spatial invariance
Authors: Al Beattie Bakr , Feketa Petro , Ochs Karlheinz , Kohlstedt Hermann 
Published: February 2024

AbstractReservoir computing is an efficient and flexible framework for decision-making, control, and signal processing. It uses a network of interacting components varying from abstract nonlinear dynamical systems to physical substrates. Despite recent progress, the hardware implementation with inherent parameter variability and uncertainties, such as those mimicking the properties of living organisms’ nervous systems, remains an active research area. To address these challenges, we propose a constructive approach using a network of FitzHugh-Nagumo oscillators, exhibiting criticality across a broad range of resistive coupling strengths and robustness without specific parameter tuning. Additionally, the network’s activity demonstrates spatial invariance, offering freedom in choosing readout nodes. We introduce an alternative characterization of criticality by analyzing power dissipation, and demonstrate that criticality supports the robustness of the classification accuracy with respect to the readout shrinkage. Our results indicate criticality as a valuable property for classification problems, and provides design concepts for bio-inspired computational paradigms.
Novel role of bone morphogenetic protein 9 in innate host responses to HCMV infection
Authors: Stempel Markus , Maier Oliver , Mhlekude Baxolele , Drakesmith Hal , Brinkmann Melanie M 
Published: February 2024

AbstractHerpesviruses modulate immune control to secure lifelong infection. The mechanisms Human Cytomegalovirus (HCMV) employs in this regard can reveal unanticipated aspects of cellular signaling involved in antiviral immunity. Here, we describe a novel relationship between the TGF-β family cytokine BMP9 and HCMV infection. We identify a cross-talk between BMP9-induced and IFN receptor-mediated signaling, showing that BMP9 boosts the transcriptional response to and antiviral activity of IFNβ, thereby enhancing viral restriction. We also show that BMP9 is secreted by human fibroblasts upon HCMV infection. However, HCMV infection impairs BMP9-induced enhancement of the IFNβ response, indicating that this signaling role of BMP9 is actively targeted by HCMV. Indeed, transmembrane proteins US18 and US20, which downregulate type I BMP receptors, are necessary and sufficient to cause inhibition of BMP9-mediated boosting of the antiviral response to IFNβ. HCMV lacking US18 and US20 is more sensitive to IFNβ. Thus, HCMV has a mutually antagonistic relationship with BMP9, which extends the growing body of evidence that BMP signaling is an underappreciated modulator of innate immunity in response to viral infection.
Effectiveness of Transcranial Direct Current Stimulation as an Adjuvant to Aphasia Treatment Following Stroke: Evidence From Systematic Reviews and Meta-Analyses
Authors: Raymer Anastasia M. , Johnson Rachel K. 
Published: February 2024

Purpose:
Transcranial direct current stimulation (tDCS) is a neuromodulation tool to amplify neural excitability and enhance outcomes associated with speech-language therapy (SLT). Stimulation currents to the left and right hemispheres vary in applying anodal (excitatory), cathodal (inhibitory), or bihemispheric signals. Several systematic reviews (SRs) and meta-analyses (MAs) have summarized the large literature examining tDCS for aphasia rehabilitation. The purpose of this project was to appraise the quality of SRs and MAs of tDCS for aphasia and examine the weight of the evidence for language outcomes in individuals with aphasia beyond SLT alone.

Method:
We searched four databases for SRs/MAs examining effects of tDCS for poststroke aphasia. We identified 16 reviews, with nine that incorporated MA to quantify results. Two reviewers reliably coded articles for methodological rigor using the AMSTAR 2 (A MeaSurement Tool to Assess Systematic Reviews, Version 2). We then summarized findings of the 16 reviews.

Results:
The AMSTAR 2 appraisal criteria suggest that critical weaknesses were noted among all reviews except those by Elsner et al. (2015, 2019). Reviews summarized three to 48 studies, as some included only randomized crossover trials and others included all trial designs. All SRs and one MA reported improvements following tDCS stimulation for general aphasia abilities and measures of repetition and speech fluency. Five recent MAs reported significant naming improvements following tDCS using all stimulation arrays. No tDCS effects were noted for comprehension measures.

Conclusions:
As the tDCS literature matured, the conclusions of MAs merged with earlier SRs reporting statistically positive benefits over SLT alone. Most consistent results are reported for naming measures, leaving some to question the clinical significance of tDCS effects for functional measures of aphasia recovery. Although the tDCS literature is expansive, important questions remain before the technique can be confidently recommended for clinical practice.
Hand gesture recognition based on micro‐Doppler radar using graph neural network
Authors: Xiong Zhangjin , Ma Kaixue , Yan Ningning 
Published: February 2024

AbstractHand gesture recognition based on micro‐Doppler (MD) radar has garnered considerable attention from researchers as a potential method for human–computer interaction (HCI). However, two significant challenges, that is, obvious differences in MD map size and lots of redundant information contained in the MD maps, are encountered. Here, a multi‐scale graph‐based hand gesture recognition framework is proposed. First, a MD graph representation method is developed, which is adapted to arbitrary‐sized frames and enables to map the key features in a sparse manner. Then, the multi‐scale information from MD graph is fully extracted for hand gesture recognition. Experimental results show that the proposed framework achieves a state‐of‐the‐art accuracy of 96.73% on the four‐class radar hand gesture dataset, while reducing up to 99% of the redundant information in the MD maps. This framework requires only a little amount of memory storage with good hand gesture recognition capability, demonstrating its high potential in the HCI field.