bluuebunny/crossref_metadata_2025 huggingface dataset:
Noble gas evidence of a millennial-scale deep North Pacific palaeo-barometric anomaly
Authors: Jenkins W. J. , Seltzer A. M. , Gebbie G. , German C. R.
Published: January 2024

Precise measurements of dissolved noble gases along the GP15 GEOTRACES Pacific Meridional Transect reveal the oldest northern bottom waters equilibrated with the atmosphere at a higher barometric pressure than more recent waters. Here, using a radiocarbon-calibrated multi-tracer-based diagnostic model, we reconstruct the magnitude and timing of this palaeo-barometric pressure anomaly. We hypothesize this multi-millennial trend in sea-level pressure results from local and regional processes extant in Antarctic Bottom Water formation regions.
The persistence of memory in ionic conduction probed by nonlinear optics
Authors: Poletayev Andrey D. , Hoffmann Matthias C. , Dawson James A. , Teitelbaum Samuel W. , Trigo Mariano , Islam M. Saiful , Lindenberg Aaron M.
Published: January 2024

Predicting practical rates of transport in condensed phases enables the rational design of materials, devices and processes. This is especially critical to developing low-carbon energy technologies such as rechargeable batteries1–3. For ionic conduction, the collective mechanisms4,5, variation of conductivity with timescales6–8 and confinement9,10, and ambiguity in the phononic origin of translation11,12, call for a direct probe of the fundamental steps of ionic diffusion: ion hops. However, such hops are rare-event large-amplitude translations, and are challenging to excite and detect. Here we use single-cycle terahertz pumps to impulsively trigger ionic hopping in battery solid electrolytes. This is visualized by an induced transient birefringence, enabling direct probing of anisotropy in ionic hopping on the picosecond timescale. The relaxation of the transient signal measures the decay of orientational memory, and the production of entropy in diffusion. We extend experimental results using in silico transient birefringence to identify vibrational attempt frequencies for ion hopping. Using nonlinear optical methods, we probe ion transport at its fastest limit, distinguish correlated conduction mechanisms from a true random walk at the atomic scale, and demonstrate the connection between activated transport and the thermodynamics of information.
Identification and characterization of TOR in Macrobrachium rosenbergii and its role in muscle protein and lipid production
Authors: Dai Xilin , Li Xuenan , Yin Danhui , Chen Xin , Wang Linwei , Pang Luyao , Fu Yuanshuai
Published: January 2024

The recent scarcity of fishmeal and other resources means that studies on the intrinsic mechanisms of nutrients in the growth and development of aquatic animals at the molecular level have received widespread attention. The target of rapamycin (TOR) pathway has been reported to receive signals from nutrients and environmental stresses, and regulates cellular anabolism and catabolism to achieve precise regulation of cell growth and physiological activities. In this study, we cloned and characterized the full-length cDNA sequence of the TOR gene of Macrobrachium rosenbergii (MrTOR). MrTOR was expressed in all tissues, with higher expression in heart and muscle tissues. In situ hybridization also indicated that MrTOR was expressed in muscle, mainly around the nucleus. RNA interference decreased the expression levels of MrTOR and downstream protein synthesis-related genes (S6K, eIF4E, and eIF4B) (P < 0.05) and the expression and enzyme activity of the lipid synthesis-related enzyme, fatty acid synthase (FAS), and increased enzyme activity of the lipolysis-related enzyme, lipase (LPS). In addition, amino acid injection significantly increased the transcript levels of MrTOR and downstream related genes (S6K, eIF4E, eIF4B, and FAS), as well as triglyceride and total cholesterol tissue levels and FAS activity. Starvation significantly increased transcript levels and enzyme activities of adenylate-activated protein kinase and LPS and decreased transcript levels and enzyme activities of FAS, as well as transcript levels of MrTOR and its downstream genes (P < 0.05), whereas amino acid injection alleviated the starvation-induced decreases in transcript levels of these genes. These results suggested that arginine and leucine activated the TOR signaling pathway, promoted protein and lipid syntheses, and alleviated the pathway changes induced by starvation.
Fourier transform-based method for quantifying the three-dimensional orientation distribution of fibrous units
Authors: Alberini Riccardo , Spagnoli Andrea , Sadeghinia Mohammad Javad , Skallerud Bjørn , Terzano Michele , Holzapfel Gerhard A.
Published: January 2024

Several materials and tissues are characterized by a microstructure composed of fibrous units embedded in a ground matrix. In this paper, a novel three-dimensional (3D) Fourier transform-based method for quantifying the distribution of fiber orientations is presented. The method allows for an accurate identification of individual fiber families, their in-plane and out-of-plane dispersion, and showed fast computation times. We validated the method using artificially generated 3D images, in terms of fiber dispersion by considering the error between the standard deviation of the reconstructed and the prescribed distributions of the artificial fibers. In addition, we considered the measured mean orientation angles of the fibers and validated the robustness using a measure of fiber density. Finally, the method is employed to reconstruct a full 3D view of the distribution of collagen fiber orientations based on in vitro second harmonic generation microscopy of collagen fibers in human and mouse skin. The dispersion parameters of the reconstructed fiber network can be used to inform mechanical models of soft fiber-reinforced materials and biological tissues that account for non-symmetrical fiber dispersion.
Deep neural operator-driven real-time inference to enable digital twin solutions for nuclear energy systems
Authors: Kobayashi Kazuma , Alam Syed Bahauddin
Published: January 2024

This paper focuses on the feasibility of deep neural operator network (DeepONet) as a robust surrogate modeling method within the context of digital twin (DT) enabling technology for nuclear energy systems. Machine learning (ML)-based prediction algorithms that need extensive retraining for new reactor operational conditions may prohibit real-time inference for DT across varying scenarios. In this study, DeepONet is trained with possible operational conditions and that relaxes the requirement of continuous retraining - making it suitable for online and real-time prediction components for DT. Through benchmarking and evaluation, DeepONet exhibits remarkable prediction accuracy and speed, outperforming traditional ML methods, making it a suitable algorithm for real-time DT inference in solving a challenging particle transport problem. DeepONet also exhibits generalizability and computational efficiency as an efficient surrogate tool for DT component. However, the application of DeepONet reveals challenges related to optimal sensor placement and model evaluation, critical aspects of real-world DT implementation. Addressing these challenges will further enhance the method’s practicality and reliability. Overall, this study marks an important step towards harnessing the power of DeepONet surrogate modeling for real-time inference capability within the context of DT enabling technology for nuclear systems.
An approach for an enhanced anticancer activity of ferulic acid-loaded polymeric micelles via MicroRNA-221 mediated activation of TP53INP1 in caco-2 cell line
Authors: Sweed Nabila M. , Dawoud Marwa H. S. , Aborehab Nora M. , Ezzat Shahira M.
Published: January 2024

Ferulic acid (FA) has powerful antioxidant and antitumor activities, but it has low bioavailability owing to its poor water solubility. Our aim is to formulate polymeric mixed micelles loaded with FA to overcome its poor solubility and investigate its potential anticancer activity via miRNA-221/TP53INP1 axis-mediated autophagy in colon cancer. A D-optimal design with three factors was used for the optimization of polymeric mixed micelles by studying the effects of each of total Pluronics mixture (mg), Pluronic P123 percentage (%w/w), and drug amount (mg) on both entrapment efficiency (EE%) and particle size. The anticancer activity of FA and Tocopheryl polyethylene glycol 1000 succinate (TPGS) mixed micelles formula (O2) was assessed by MTT and flow cytometry. O2 showed an EE% of 99.89%, a particle size of 13.86 nm, and a zeta potential of − 6.02 mv. In-vitro drug release studies showed a notable increase in the release rate of FA from O2, as compared to the free FA. The (IC50) values for FA from O2 and free FA were calculated against different cell lines showing a prominent IC50 against Caco-2 (17.1 µg/ml, 191 µg/ml respectively). Flow cytometry showed that FA caused cell cycle arrest at the G2/M phase in Caco-2. RT-PCR showed that O2 significantly increased the mRNA expression level of Bax and CASP-3 (4.72 ± 0.17, 3.67 ± 0.14), respectively when compared to free FA (2.59 ± 0.13, 2.14 ± 0.15), while miRNA 221 levels were decreased by the treatment with O2 (0.58 ± 0.02) when compared to free FA treatment (0.79 ± 0.03). The gene expression of TP53INP1 was increased by the treatment with O2 compared to FA at P < 0.0001. FA-loaded TPGS mixed micelles showed promising results for enhancing the anticancer effect of FA against colorectal cancer, probably due to its enhanced solubility. Thus, FA-loaded TPGS mixed micelles could be a potential therapeutic agent for colorectal cancer by targeting miRNA-221/TP53INP1 axis-mediated autophagy.
An investigation of the effects of meteorological factors on the incidence of tuberculosis
Authors: Chang Minli , Emam Mawlanjan , Chen Xiaodie , Lu Dongmei , Zhang Liping , Zheng Yanling
Published: January 2024

To explore the influence of meteorological factors on the incidence of tuberculosis (TB) in Yingjisha County, Kashgar Region, Xinjiang, and to provide a scientific basis for the prevention and control of TB. The Spearman correlation analysis and distribution lag nonlinear model analysis were conducted on the number of daily reported cases of TB from 2016 to 2023 to study the association effect of various meteorological factors and the daily incidence number of TB in Yingjisha County. A total of 13,288 TB cases were reported from January 2016 to June 2023, and June to October is the peak period of annual TB incidence. Spearman correlation analysis revealed that average daily temperature (AT) and average daily wind speed (WS) were positively correlated with TB incidence (rAT = 0.110, rWS = 0.090); and average daily relative humidity (RH) and TB incidence was negatively correlated (rRH = − 0.093). When AT was − 15 °C, the RR reached a maximum of 2.20 (95% CI: 0.77–6.29) at a lag of 21 days. When RH was 92%, the RR reached a maximum of 1.05 (95% CI: 0.92–1.19) at a lag of 6 days. When WS was 5.2 m/s, the RR reached a maximum of 1.30 (95% CI: 0.78–2.16) at a lag of 16 days. There is a non-linearity and a certain lag between meteorological factors and the occurrence and prevalence of TB in the population, which is mainly manifested in the fact that the risk of incidence of TB decreases with the increase of the daily AT, has a hazardous effect within a certain range of humidity as the average daily RH rises, and gradually increases with the increase of the average daily WS. Local residents are advised to pay attention to climate change so as to take appropriate preventive measures, especially women and middle and old age group should pay close attention to climate change and add more clothes in time, minimise travelling in hazy weather and windy and sandy weather, maintain good nutrition, adequate sleep and moderate exercise in daily life to enhance their immunity, wash hands frequently and ventilate the air, and try to avoid staying in humid and confined spaces in order to reduce the risk of latent TB patients developing the disease.
Downstream network transformations dissociate neural activity from causal functional contributions
Authors: Fakhar Kayson , Dixit Shrey , Hadaeghi Fatemeh , Kording Konrad P. , Hilgetag Claus C.
Published: January 2024

Neuroscientists rely on distributed spatio-temporal patterns of neural activity to understand how neural units contribute to cognitive functions and behavior. However, the extent to which neural activity reliably indicates a unit's causal contribution to the behavior is not well understood. To address this issue, we provide a systematic multi-site perturbation framework that captures time-varying causal contributions of elements to a collectively produced outcome. Applying our framework to intuitive toy examples and artificial neural networks revealed that recorded activity patterns of neural elements may not be generally informative of their causal contribution due to activity transformations within a network. Overall, our findings emphasize the limitations of inferring causal mechanisms from neural activities and offer a rigorous lesioning framework for elucidating causal neural contributions.
A phased genome assembly of a Colombian Trypanosoma cruzi TcI strain and the evolution of gene families
Authors: Hoyos Sanchez Maria Camila , Ospina Zapata Hader Sebastian , Suarez Brayhan Dario , Ospina Carlos , Barbosa Hamilton Julian , Carranza Martinez Julio Cesar , Vallejo Gustavo Adolfo , Urrea Montes Daniel , Duitama Jorge
Published: January 2024

Chagas is an endemic disease in tropical regions of Latin America, caused by the parasite Trypanosoma cruzi. High intraspecies variability and genome complexity have been challenges to assemble high quality genomes needed for studies in evolution, population genomics, diagnosis and drug development. Here we present a chromosome-level phased assembly of a TcI T. cruzi strain (Dm25). While 29 chromosomes show a large collinearity with the assembly of the Brazil A4 strain, three chromosomes show both large heterozygosity and large divergence, compared to previous assemblies of TcI T. cruzi strains. Nucleotide and protein evolution statistics indicate that T. cruzi Marinkellei separated before the diversification of T. cruzi in the known DTUs. Interchromosomal paralogs of dispersed gene families and histones appeared before but at the same time have a more strict purifying selection, compared to other repeat families. Previously unreported large tandem arrays of protein kinases and histones were identified in this assembly. Over one million variants obtained from Illumina reads aligned to the primary assembly clearly separate the main DTUs. We expect that this new assembly will be a valuable resource for further studies on evolution and functional genomics of Trypanosomatids.
Disentangling boredom from depression using the phenomenology and content of involuntary autobiographical memories
Authors: Yeung Ryan C. , Danckert James , van Tilburg Wijnand A. P. , Fernandes Myra A.
Published: January 2024

Recurrent involuntary autobiographical memories (IAMs) are memories retrieved unintentionally and repetitively. We examined whether the phenomenology and content of recurrent IAMs could differentiate boredom and depression, both of which are characterized by affective dysregulation and spontaneous thought. Participants (n = 2484) described their most frequent IAM and rated its phenomenological properties (e.g., valence). Structural topic modeling, a method of unsupervised machine learning, identified coherent content within the described memories. Boredom proneness was positively correlated with depressive symptoms, and both boredom proneness and depressive symptoms were correlated with more negative recurrent IAMs. Boredom proneness predicted less vivid recurrent IAMs, whereas depressive symptoms predicted more vivid, negative, and emotionally intense ones. Memory content also diverged: topics such as relationship conflicts were positively predicted by depressive symptoms, but negatively predicted by boredom proneness. Phenomenology and content in recurrent IAMs can effectively disambiguate boredom proneness from depressive symptoms in a large sample of undergraduate students from a racially diverse university.
Efficacy of sodium glucose cotransporter 2 inhibitors on hepatic fibrosis and steatosis in non-alcoholic fatty liver disease: an updated systematic review and meta-analysis
Authors: Ong Lopez Albert Macaire C. , Pajimna Janine Audrei T.
Published: January 2024

Non-alcoholic fatty liver disease (NAFLD) is a substantial contributor to liver-related morbidity worldwide, and yet, there are no standard, universal pharmacologic therapies approved for this indication. The aim of this systematic review and meta-analysis is to evaluate the effectiveness of SGLT-2 inhibitors in improving hepatic steatosis and hepatic fibrosis in patients with NAFLD. An extensive electronic database search was done to identify studies published from inception until December 2023, without any language restrictions. All randomized controlled trials (RCT) that evaluated the use of SGLT-2 inhibitors for patients with NAFLD, regardless of diabetes mellitus status, were included. The Cochrane Risk of Bias 2.0 tool was used to assess the risk of bias of each study included. Evidence from all studies were synthesized as mean differences for continuous data, and as risk ratio for dichotomous outcomes. An inverse variance or Mantel–Haenszel test was used in conjunction with a random-effects meta-analysis model, where necessary. 18 eligible RCTs involving 1330 participants were analyzed, all of which had risk of bias ranging from low to some concerns. Significant difference in means was observed for controlled attenuation parameter (6 trials, n = 372; MD: − 10.59 dB/m, 95% CI [− 18.25, − 2.92], p = 0.007, I2 = 0%); L/S ratio (3 trials, n = 163; MD: 0.11, 95% CI [0.01, 0.21], p = 0.04, I2 = 78%); LSM (7 trials, n = 447; MD: − 0.67 kPa, 95% CI [− 1.19, − 0.16], p = 0.010, I2 = 69%); MRI-PDFF (5 trials, n = 330; MD: − 2.61%, 95% CI [− 5.05, − 0.17], p = 0.04, I2 = 78%), and FIB-4 index (10 trials, n = 648; MD: − 0.12, 95% CI [− 0.21, − 0.04], p = 0.005, I2 = 16%) after SGLT-2 inhibitor treatment as compared to controls. In conclusion, the use of SGLT-2 inhibitors may lead to slight improvement of hepatic steatosis and/or fibrosis as compared to controls in patients with NAFLD and Type 2 diabetes mellitus based on imaging and histopathology biomarkers with low to moderate certainty of evidence.
Prediction of atmospheric PM2.5 level by machine learning techniques in Isfahan, Iran
Authors: Mohammadi Farzaneh , Teiri Hakimeh , Hajizadeh Yaghoub , Abdolahnejad Ali , Ebrahimi Afshin
Published: January 2024

With increasing levels of air pollution, air quality prediction has attracted more attention. Mathematical models are being developed by researchers to achieve precise predictions. Monitoring and prediction of atmospheric PM2.5 levels, as a predominant pollutant, is essential in emission mitigation programs. In this study, meteorological datasets from 9 years in Isfahan city, a large metropolis of Iran, were applied to predict the PM2.5 levels, using four machine learning algorithms including Artificial Neural |Networks (ANNs), K-Nearest-Neighbors (KNN), Support Vector |Machines (SVMs) and ensembles of classification trees Random Forest (RF). The data from 7 air quality monitoring stations located in Isfahan City were taken into consideration. The Confusion Matrix and Cross-Entropy Loss were used to analyze the performance of classification models. Several parameters, including sensitivity, specificity, accuracy, F1 score, precision, and the area under the curve (AUC), are computed to assess model performance. Finally, by introducing the predicted data for 2020 into ArcGIS software and using the IDW (Inverse Distance Weighting) method, interpolation was conducted for the area of Isfahan city and the pollution map was illustrated for each month of the year. The results showed that, based on the accuracy percentage, the ANN model has a better performance (90.1%) in predicting PM2.5 grades compared to the other models for the applied meteorological dataset, followed by RF (86.1%), SVM (84.6%) and KNN (82.2%) models, respectively. Therefore, ANN modelling provides a feasible procedure for the managerial planning of air pollution control.
Electric field-enhanced backscatter interferometry detection for capillary electrophoresis
Authors: De Silva Miyuru , Dunn Robert C.
Published: January 2024

Backscatter interferometry (BSI) is a refractive index (RI) detection method that is easily integrated with capillary electrophoresis (CE) and is capable of detecting species ranging from inorganic ions to proteins without additional labels or contrast agents. The BSI signal changes linearly with the square of the separation voltage which has been used to quantify sample injection, but has not been explored as a potential signal enhancement mechanism in CE. Here we develop a mathematical model that predicts a signal enhancement at high field strengths, where the BSI signal is dominated by the voltage dependent mechanism. This is confirmed in both simulation and experiment, which show that the analyte peak area grows linearly with separation voltage at high field strengths. This effect can be exploited by adjusting the background electrolyte (BGE) to increase the conductivity difference between the BGE and analyte zones, which is shown to improve BSI performance. We also show that this approach has utility in small bore capillaries where larger separation fields can be applied before excess Joule heating degrades the separation. Unlike other optical detection methods that generally degrade as the optical pathlength is reduced, the BSI signal-to-noise can improve in small bore capillaries as the larger separation fields enhance the signal.
Identification of shared pathogenetic mechanisms between COVID-19 and IC through bioinformatics and system biology
Authors: Sun Zhenpeng , Zhang Li , Wang Ruihong , Wang Zheng , Liang Xin , Gao Jiangang
Published: January 2024

COVID-19 increased global mortality in 2019. Cystitis became a contributing factor in SARS-CoV-2 and COVID-19 complications. The complex molecular links between cystitis and COVID-19 are unclear. This study investigates COVID-19-associated cystitis (CAC) molecular mechanisms and drug candidates using bioinformatics and systems biology. Obtain the gene expression profiles of IC (GSE11783) and COVID-19 (GSE147507) from the Gene Expression Omnibus (GEO) database. Identified the common differentially expressed genes (DEGs) in both IC and COVID-19, and extracted a number of key genes from this group. Subsequently, conduct Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the DEGs. Additionally, design a protein–protein interaction (PPI) network, a transcription factor gene regulatory network, a TF miRNA regulatory network, and a gene disease association network using the DEGs. Identify and extract hub genes from the PPI network. Then construct Nomogram diagnostic prediction models based on the hub genes. The DSigDB database was used to forecast many potential molecular medicines that are associated with common DEGs. Assess the precision of hub genes and Nomogram models in diagnosing IC and COVID-19 by employing Receiver Operating Characteristic (ROC) curves. The IC dataset (GSE57560) and the COVID-19 dataset (GSE171110) were selected to validate the models' diagnostic accuracy. A grand total of 198 DEGs that overlapped were found and chosen for further research. FCER1G, ITGAM, LCP2, LILRB2, MNDA, SPI1, and TYROBP were screened as the hub genes. The Nomogram model, built using the seven hub genes, demonstrates significant utility as a diagnostic prediction model for both IC and COVID-19. Multiple potential molecular medicines associated with common DEGs have been discovered. These pathways, hub genes, and models may provide new perspectives for future research into mechanisms and guide personalised and effective therapeutics for IC patients infected with COVID-19.
Outcomes and predictive factors of vital pulp therapy in a large-scale retrospective cohort study over 10 years
Authors: Asgary Saeed , Roghanizadeh Leyla , Eghbal Mohammad Jafar , Akbarzadeh Baghban Alireza , Aminoshariae Anita , Nosrat Ali
Published: January 2024

This cohort study evaluated the long-term success/survival of vital pulp therapies (VPTs) after carious pulp exposure in adult teeth. Additionally, factors influencing long-term success were identified. Teeth treated during 2011–2022 in a private clinic were studied with clinical/radiographic follow-ups. Data included patient demographics, tooth specifics, and treatment details. Outcomes were classified as success/failure based on clinical/radiographic findings, with tooth functionality determining the survival rate. Encompassing 1149 patients and 1257 VPT-treated teeth, the average monitoring period was 42.2 months. Overall VPTs’ survival and success rates were 99.1% and 91.6%, respectively. Success rates for 768 direct pulp cappings, 217 miniature pulpotomies, and 272 full pulpotomies were 91.9%, 92.6%, and 90.1%, respectively (P > 0.05). Influencing factors included symptomatic irreversible pulpitis (SIP; HR 1.974, 95% CI 1.242–3.137; P = 0.004), radiographic signs of apical periodontitis (AP; HR 2.983, 95% CI 1.961–4.540; P < 0.001), restoration type (HR 2.263, 95%CI 1.423–3.600; P = 0.001), and restoration surfaces (HR 1.401, 95%CI 1.034–1.899; P = 0.030). This study concludes that VPT techniques consistently exhibit high long-term success/survival rates in treating carious pulp exposures. Critical predictors include initial clinical signs of SIP/AP, caries extent, and use of composite restorations.
A novel two-dimensional phantom for electrical impedance tomography using 3D printing
Authors: Creegan Andrew , Nielsen Poul M. F. , Tawhai Merryn H.
Published: January 2024

Electrical impedance tomography (EIT) is an imaging method that can be used to image electrical impedance contrasts within various tissues of the body. To support development of EIT measurement systems, a phantom is required that represents the electrical characteristics of the imaging domain. No existing type of EIT phantom combines good performance in all three characteristics of resistivity resolution, spatial resolution, and stability. Here, a novel EIT phantom concept is proposed that uses 3D printed conductive material. Resistivity is controlled using the 3D printing infill percentage parameter, allowing arbitrary resistivity contrasts within the domain to be manufactured automatically. The concept of controlling resistivity through infill percentage is validated, and the manufacturing accuracy is quantified. A method for making electrical connections to the 3D printed material is developed. Finally, a prototype phantom is printed, and a sample EIT analysis is performed. The resulting phantom, printed with an Ultimaker S3, has high reported spatial resolution of 6.9 µm, 6.9 µm, and 2.5 µm for X, Y, and Z axis directions, respectively (X and Y being the horizontal axes, and Z the vertical). The number of resistivity levels that are manufacturable by varying infill percentage is 15 (calculated by dividing the available range of resistivities by two times the standard deviation of the manufacturing accuracy). This phantom construction technique will allow assessment of the performance of EIT devices under realistic physiological scenarios.
Polymeric membrane potentiometric antibiotic sensors using computer-aided screening of supramolecular macrocyclic carriers
Authors: Liu Aohua , Liu Zhe , Liang Rongning , Qin Wei
Published: January 2024

A polymeric membrane potentiometric antibiotic sensor using computationally screened supramolecular macrocyclic carriers by the molecular docking technique is described.
Momentum transport of morphological instability in fluid displacement with changes in viscosity
Authors: Ban Takahiko , Ishii Hibiki , Onizuka Atsushi , Chatterjee Atanu , Suzuki Ryuta X. , Nagatsu Yuichiro , Mishra Manoranjan
Published: January 2024

State transition phenomena of irreversible processes coupled with mass and momentum transfers are quantitatively analyzed using thermodynamic flux and entropy production.
Early bird or night owl? Controlling the ultrafast photodynamics of triphenylamine substituted 2,2′:6′,2′′-terpyridine
Authors: Maroń Anna Maria , Cannelli Oliviero , Socie Etienne Christophe , Lodowski Piotr , Oppermann Malte , Machura Barbara , Chergui Majed
Published: January 2024

4′-(4-(di(4-tert-butylphenyl)amine)phenyl)-2,2′,6′,2′′-terpyridine presents a complex photodynamics tuned by the local environment, making it either an ‘early bird’ or a ‘night owl’.
Magnetic skyrmions and their manipulations in a 2D multiferroic CuCrP2Te6 monolayer
Authors: Liu Minghao , Wan Tsz Lok , Dou Kaiying , Zhang Lei , Sun Wei , Jiang Jiawei , Ma Yandong , Gu Yuantong , Kou Liangzhi
Published: January 2024

Magnetic skyrmions and their effective manipulations are promising for the design of next-generation information storage and processing devices, due to their topologically protected chiral spin textures and low energy cost.
Regulated stepwise ESDPT mechanism associated with chalcogen substitutions in BDIBD derivatives
Authors: Liu Chang , Zhao Jinfeng , Chen Jiahe , Wang Mingwei , Hou Mengmeng , Yang Liang
Published: January 2024

This work elucidates stepwise excited state intramolecular double proton transfer in BDIBD derivatives and proposes a chalcogen atomic-electronegativity-regulated excited state dynamical mechanism.
A monofunctional Pt(ii) complex combats triple negative breast cancer by triggering lysosome-dependent cell death
Authors: Shen Xiaomin , Peng Yue , Yang Zidong , Li Renhao , Zhou Haixia , Ye Xiaoxia , Han Zhong , Shi Xiangchao
Published: January 2024

A monofunctional Pt(ii) complex PtL induces DNA single-strand breaks in triple negative breast cancer and triggers lysosome-dependent cell death by modulating lysosomal function.
Novel bidentate N-coordinated alkylaluminum complexes: synthesis, characterization, and efficient catalysis for hydrophosphonylation
Authors: Wei Biao , Wang Chaoqun , Miao Hui , Qin Zhibiao , Huang Mengna , Xu Yan , Xue Wenhui , Yang Shucheng , Liu Chenxu , Bai Cuibing , Chen Zheng
Published: January 2024

Five new alkylaluminum complexes with different pyridinyl-substituted imines or cyclohexyl-substituted imines were synthesized and characterized successfully.
A cross-metathesis approach for polymetallic [FeFe]-hydrogenase mimics
Authors: Aguado Sergio , García-Álvarez Pablo , Cabeza Javier A. , Casarrubios Luis , Sierra Miguel A.
Published: January 2024

Diverse [FeFe]-H2ase mimics are available by cross-metathesis of [FeFe]-H2ase mimics bearing a double bond in the ADT-bridge nitrogen moiety and vinylmetallocenes, vinyl half-sandwich, or octahedral Ir-complexes.
Design of depolymerizable polymers toward a circular economy
Authors: Highmoore Julian F. , Kariyawasam Lasith S. , Trenor Scott R. , Yang Ying
Published: January 2024

While our society is facing the challenge of accumulating plastic waste, this review discusses recent advances towards polymer circularity with an emphasis on manipulations of the monomer–polymer equilibrium to create chemically recyclable polymers.
Transition metal ion assisted photochemical vapor generation of niobium and tantalum
Authors: Dong Liang , Ning Yongyan , Hu Jing , Wang Weigao , Yu Ying , Gao Ying
Published: January 2024

The photochemical vapor generation of Nb and Ta was reported for the first time. The addition of Cu2+ led to an enhancement of 76- and 91-fold for Nb and Ta, respectively.
Simultaneous and sensitive detection of dopamine and acetaminophen at a glassy carbon electrode modified with a carbonized-ZIF-67/Super P nanocomposite
Authors: Li Xiaobo , Yang Kaifeng , Han Fangming , Jin Yafeng , Zhang Haonan , Gao Heng
Published: January 2024

Fabrication of C-ZIF-67/SP/GCE for the simultaneous detection of DA and AC.
Chirality-induced supramolecular nanodishes: enantioselectivity and energy transfer
Authors: Zhao Hui-Yu , Liu Gui-Lang , Xu Qing , Pei Yi-Rong , Jin Long Yi
Published: January 2024

Asymmetric synthesis and chiral transfer have been achieved by introducing simple methyl side groups into amphiphilic molecules.
Two-dimensional complex metal halides: influence of restricted dimensionality on functional properties
Authors: Chen Charles , Xu Jianwei , Wang Xizu , Palgrave Robert G.
Published: January 2024

We use the term “complex metal halides” to refer to compounds such as halide perovskites. Our focus includes exploring various dimensionality types, with a specific emphasis on structurally 2D materials, including RP and DJ phases.
Breaking boundaries: advancements in solid-state redox mediators for decoupled water electrolysis
Authors: Wu Tianci , Hu Yue , Li Meng , Han Bin , Geng Dongsheng
Published: January 2024

Recent research progress, opportunities and challenges, and future perspectives are presented in this review, with the aim of exploring novel, high-performance solid-state redox media for decoupled water electrolysis.
Microscopic mechanism of thermal amorphization of ZIF-4 and melting of ZIF-zni revealed via molecular dynamics and machine learning techniques
Authors: Méndez Emilio , Semino Rocio
Published: January 2024

The microscopic mechanism of ZIF-4 amorphization and ZIF-zni melting are elucidated via a combination of data science and computer simulation approaches. Gradual density changes and the breaking and formation of Zn–N bonds are key to both processes.
Visible light degradable micelles for intraocular corticosteroid delivery
Authors: Qi Ronghui , Mundy Emily , Amsden Brian G.
Published: January 2024

Visible light responsive micellar drug delivery formulations are of notable interest for the treatment of ocular diseases given the accessibility of the eye to light transmission.
Perovskite/organic hybrid tandem light-emitting diodes with an external quantum efficiency of over 40%
Authors: Zhu Min , Sun Shuang-Qiao , He Wei , Xu Yan-Lin , Sun Qi , Xie Yue-Min , Fung Man-Keung , Lee Shuit-Tong
Published: January 2024

Novel designed perovskite/organic hybrid tandem light-emitting diode (POTLEDs) are developed by depositing OLED units onto bottom perovskite LED units, which illustrate a champion EQE of 41.1% with a maximum CE of 144.2 cd A−1 indicating the high-efficiency potential of POTLEDs.
Effects of the nature of donor substituents on the photophysical and electroluminescence properties of derivatives of perfluorobiphenyl: donor–acceptor versus donor–acceptor–donor type AIEE/TADF emitters
Authors: Danyliv Iryna , Danyliv Yan , Stanitska Mariia , Bezvikonnyi Oleksandr , Volyniuk Dmytro , Lytvyn Roman , Horak Yuriy , Matulis Vitaly , Lyakhov Dmitry , Michels Dominik , Stakhira Pavlo , Grazulevicius Juozas Vidas
Published: January 2024

The synthesis and properties of a group of organic electroactive compounds based on electron-deficient perfluorobiphenyl (PFBP) are described.
Examining the Relationship Between Multiple Tests of Receptive Vocabulary
Authors: Harel Daphna , Goudelias Deanna , Cheng Hung-Shao , Baese-Berk Melissa M. , Theodore Rachel M. , Levi Susannah V.
Published: January 2024

Purpose:

Numerous tasks have been developed to measure receptive vocabulary, many of which were designed to be administered in person with a trained researcher or clinician. The purpose of the current study is to compare a common, in-person test of vocabulary with other vocabulary assessments that can be self-administered.

Method:

Fifty-three participants completed the Peabody Picture Vocabulary Test (PPVT) via online video call to mimic in-person administration, as well as four additional fully automated, self-administered measures of receptive vocabulary. Participants also completed three control tasks that do not measure receptive vocabulary.

Results:

Pearson correlations indicated moderate correlations among most of the receptive vocabulary measures (approximately
r
= .50–.70). As expected, the control tasks revealed only weak correlations to the vocabulary measures. However, subsets of items of the four self-administered measures of receptive vocabulary achieved high correlations with the PPVT (
r
> .80). These subsets were found through a repeated resampling approach.

Conclusions:

Measures of receptive vocabulary differ in which items are included and in the assessment task (e.g., lexical decision, picture matching, synonym matching). The results of the current study suggest that several self-administered tasks are able to achieve high correlations with the PPVT when a subset of items are scored, rather than the full set of items. These data provide evidence that subsets of items on one behavioral assessment can more highly correlate to another measure. In practical terms, these data demonstrate that self-administered, automated measures of receptive vocabulary can be used as reasonable substitutes of at least one test (PPVT) that requires human interaction. That several of the fully automated measures resulted in high correlations with the PPVT suggests that different tasks could be selected depending on the needs of the researcher. It is important to note the aim was not to establish clinical relevance of these measures, but establish whether researchers could use an experimental task of receptive vocabulary that probes a similar construct to what is captured by the PPVT, and use these measures of individual differences.
Student-Led Individualized Education Programs: A Gateway to Self-Determination
Authors: McNaught John , Biegun Daniel , Swartzentruber Kendal
Published: January 2024

Purpose:

The purpose of this study was to explore the experiences of
I'm Determined
youth leaders with learning disability who have enrolled in higher education within 1 year of graduating high school to better understand if and how their experience participating in the
I'm Determined
project led to their participation in their Individualized Education Program (IEP) meetings.

Method:

The intent of the narrative inquiry methodology applied to this study was to create a unified story of collective experiences that described or explained the factors leading to participation in their IEP meeting. Although each of the eight narratives is unique to the individual, common themes emerged that were reflected in the literature and consistent across the time continuum of life before and life during participation in
I'm Determined
.

Results:

One experience that was consistent was the importance of participating in and leading their IEP meeting. A narrative timeline led to our findings presented here within a continuum of experiences before and during participation in
I'm Determined.
We made the decision to present the findings in such a way that highlights common themes specific to IEP participation across moments in time while honoring individual narratives through supportive text from the data. This is a study of people's perceptions of their experiences best told by direct quotes from the participants. The IEP experience is just one component of the self-determination experience.

Conclusions:

This study provided insight into the educational experiences of the eight
I'm Determined
youth leader participants and examined the importance of both their participation in
I'm Determined
and the development of self-determination skills deemed essential to participate and lead their IEP meeting. Their unique perspective documented in this study served to both inform and push the field forward.
Smart meter privacy control strategy based on multi‐agent hidden Markov energy management model under low trust communication
Authors: Wang Qingchen , Xu Qing , Lei Xiyu , Ma Dazhong
Published: January 2024

With the popularity of smart meters, the frequent information exchange between smart grids and consumers leads to easy leakage of consumers' electricity consumption data. These leaked electricity consumption data are obtained by some malicious attackers and used to infer consumers' behavioural patterns by non‐intrusive load monitoring (NILM), which seriously threatens consumers' privacy. Therefore, the multi‐agent Hidden Markov energy management model is proposed in this paper to safeguard the privacy of consumers. First, a weighted Bayesian risk model is proposed, which combines privacy leakage risks and energy storage system (ESS) losses in a microgrid with multiple agents. Next, a three‐loop model for lithium batteries is constructed to quantify the capacity degradation and cost issues of the ESS. Finally, the multi‐objective optimization problem is resolved by integrating the Bayesian risk model with a hidden Markov model to simulate attackers. The proposed multi‐agent Markov decision process method is validated on Electricity Consumption and Occupancy (ECO) dataset, and control strategies are evaluated based on different weights in the Bayesian risk model. The results demonstrate that by incorporating the multi‐agent approach and energy storage system capacity degradation into the privacy protection strategy, the lifespan of the energy storage system can be significantly increased.
Novel rod‐like carbon nanomaterials as near infrared‐responsive drug delivery system for potential anticancer applications
Authors: Liu Mengru , Du Xiaoxue , Liu Jingyi , Wang Guangshuo , Yang Jiajia , Wang Xueling , Han Shuai , Huo Zhongchao
Published: January 2024

The combination of chemotherapy and photothermal therapy shows great potential in cancer treatment, and the carbon nanomaterials have been attracted great attention in biomedical technology. However, it is still a great challenge to design stimuli‐responsive nano‐carbon‐based drug release systems with integrated functions. In this paper, rod‐like carbon nanomaterials (RCNs) were prepared by the soft template hydrothermal method with glucose as raw materials, which were proved to have high photothermal efficiency (∼23.7%), as well as good biocompatibility and excellent drug‐loading capacity. After that, RCNs were used to load doxorubicin (DOX) as DOX@RCNs for integrated photothermal/chemotherapy towards cancer, which demonstrated 52.2% higher cancer cell killing efficiency than that of RCNs under near infrared (NIR) irradiation in vitro. The authors’ approach provided a novel NIR‐responsive nano platform for combined photothermal/chemotherapy towards cancer, which was considered to be of great potential in anticancer applications.
Short‐term photovoltaic prediction based on CNN‐GRU optimized by improved similar day extraction, decomposition noise reduction and SSA optimization
Authors: Li Rui , Wang Mingtao , Li Xingyu , Qu Jian , Dong Yuhan
Published: January 2024

The accuracy of short‐term photovoltaic (PV) power prediction is crucial for maintaining power system stability and grid scheduling. Here, a short‐term PV power prediction framework is proposed considering combined weather similarity day screening, signal decomposition noise reduction and hybrid deep learning to realize PV power prediction. First, a combined meteorological similar day screening model is constructed to screen out historical days similar to the day, which reduces the number of training sets; Second, Synchrosqueezing Wavelet Transform is utilized to eliminate data noise. Third, a Convolution Neural Network‐Gate Recurrent Unit (CNN‐GRU) network is constructed to extract periodic and nonlinear features in the PV power generation data series and to capture the relationship features between PV power generation and meteorological factors to improve the prediction accuracy. Fourth, the Sparrow Search Algorithm is introduced to perform hyper‐parameter optimization of the CNN‐GRU network to accelerate the model convergence and improve the model training efficiency. Finally, this paper conducts simulation experiments and the experimental results show that the prediction method proposed in this paper can effectively improve the prediction accuracy of short‐term PV power compared to the baseline model, and the method proposed in this paper is superior to other conventional methods.
An artificial intelligence‐based non‐intrusive load monitoring of energy consumption in an electrical energy system using a modified K‐Nearest Neighbour algorithm
Authors: Kommey Benjamin , Tamakloe Elvis , Kponyo Jerry John , Tchao Eric Tutu , Agbemenu Andrew Selasi , Nunoo‐Mensah Henry
Published: January 2024

Energy profligacy and appliance degradation are the apex reasons accounting for the continuous rise in power wastage and high energy bills. The decline in energy conservation and management in residences has been largely attributed to the financial implications of using intrusive methods. This work aimed to resolve the challenges of intrusive load monitoring by introducing artificial intelligence and machine learning to optimise load monitoring. To solve this challenge, a non‐intrusive approach was proposed where modalities for load prediction and classification were achieved with a Bagging regressor and a modified multiclass K‐Nearest Neighbour algorithms. This developed supervised learning models produced a 0.9624 R2 score and 78.24% accuracy for prediction and classification, respectively, when trained and tested on a Dutch Residential Energy Dataset. This work seeks to provide a cost‐effective approach to the optimisation of energy using steady state active power features. Essentially, the adoption of this non‐intrusive technique for load monitoring would effectively aid customers on the distribution network save cost on energy bills, facilitate the detection of faulty appliances, provide recommendations for smart homes and buildings with the required information for efficient decision making and planning of energy needs. In the long term, easing the pressure on power generation to meet demand would translate to reduction in carbon emissions based on a wide‐scale implementation of this proposed system. Hence, these are important parameters in realising the development of smart sustainable cities and sustainable energy systems in this current industrial revolution.
Research of the potential opportunities of crowdshipping: The case study of Ukraine and the Czech Republic
Authors: Svadlenka Libor , Pivtorak Halyna , Vrba Radek
Published: January 2024

Urbanization and the growth of e-commerce are the main factors behind the growth of last-mile delivery volumes. Crowdshipping using the public transport system is one of the relatively new scenarios for the organization of such delivery. This solution has good potential to meet consumer demands for fast delivery while simultaneously minimizing the negative externalities of urban freight transportation, which is the basis of the sustainability of the urban freight transport system. An important condition for understanding the development of crowdshipping using the public transport system and the formation of certain practical recommendations for the effective functioning of such delivery is the study of the opinion of potential users and crowdshippers. Analysis of available literary sources allows us to assert that the potential of crowdshipping delivery depends on specific urban planning conditions and characteristics of the population. Studying the opinions of respondents from Ukraine and the Czech Republic will allow us to gain new knowledge about the attitude of residents of cities that differ in size and characteristics of the public transport system to the possibilities of crowdshipping.