bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rapid adsorptive removal of eosin yellow and methyl orange using zeolite Y
Authors: Adeoye John Busayo , Balogun David Ololade , Etemire Oghenefejiro Jeshurun , Ezeh Princewill Nnaneme , Tan Yie Hua , Mubarak Nabisab Mujawar 
Published: December 2023

AbstractIn this study, zeolite Y was synthesised using a novel method. The heat generated from the reaction of H2SO4 with metakaolin was used as a heat source instead of applying external heat for the dealuminated process. The synthesised zeolite Y produced was analysed by scanning electron microscope (SEM), X-ray diffraction (XRD), Fourier-infrared spectroscopy (FTIR), energy dispersive X-ray spectroscopy (EDS) and Brunauer–Emmett–Teller (BET). Zeolite Y synthesis was mesoporous because of its pore diameter (30.53 nm), as shown in the BET results. Surface area and pore size decrease after adsorption due to dye deposition on the adsorbent’s surface. FTIR has bonds like O–H, C–H, –CH3, and –COOH responsible for adsorption. The maximum adsorption capacity of eosin yellow (EY) and methyl orange (MO) on to zeolite Y by the Langmuir isotherm was 52.91 mg/g and 20.62 mg/g respectively, at pH 2.5 and 8 for EY and MO dye. The batch adsorption studies were conducted, and the influence of different parameters (i.e., adsorbent dose, adsorption time, initial dye concentration, pH and temperature) was investigated. Experimental data were analysed by two linear model equations (Langmuir and Freundlich isotherms), and it was found that the Langmuir isotherm model best describes the adsorption data for methyl orange and Freundlich isotherm for eosin yellow, respectively. Adsorption rate constants were determined using linear pseudo-first-order and pseudo-second-order. The results showed that MO and EY dye adsorption onto zeolite Y followed a pseudo-second-order kinetic model. Thermodynamic studies show that adsorption was an exothermic reaction (enthalpy < 0) and feasible ($$(Gibbs free energy)<0$$

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Species identification of phlebotomine sandflies using deep learning and wing interferential pattern (WIP)
Authors: Cannet Arnaud , Simon-Chane Camille , Histace Aymeric , Akhoundi Mohammad , Romain Olivier , Souchaud Marc , Jacob Pierre , Sereno Darian , Volf Petr , Dvorak Vit , Sereno Denis 
Published: December 2023

AbstractSandflies (Diptera; Psychodidae) are medical and veterinary vectors that transmit diverse parasitic, viral, and bacterial pathogens. Their identification has always been challenging, particularly at the specific and sub-specific levels, because it relies on examining minute and mostly internal structures. Here, to circumvent such limitations, we have evaluated the accuracy and reliability of Wing Interferential Patterns (WIPs) generated on the surface of sandfly wings in conjunction with deep learning (DL) procedures to assign specimens at various taxonomic levels. Our dataset proves that the method can accurately identify sandflies over other dipteran insects at the family, genus, subgenus, and species level with an accuracy higher than 77.0%, regardless of the taxonomic level challenged. This approach does not require inspection of internal organs to address identification, does not rely on identification keys, and can be implemented under field or near-field conditions, showing promise for sandfly pro-active and passive entomological surveys in an era of scarcity in medical entomologists.
Structure-based identification of novel inhibitors targeting the enoyl-ACP reductase enzyme of Acinetobacter baumannii
Authors: Khan Shama , Madhi Shabir A. , Olwagen Courtney 
Published: December 2023

AbstractAcinetobacter baumannii is a Gram-negative multidrug-resistant bacterial pathogen primarily associated with nosocomial infections resulting in increased morbidity and mortality in adults and infants, especially in sub-Saharan Africa where the clinical burden is high. New therapeutics are needed to treat multidrug-resistant Acinetobacter baumannii infections and reduce transmission. The study used computer-integrated drug discovery approaches including pharmacophore modelling, molecular docking, and molecular dynamics simulation to screen potential inhibitors against the enoyl-acyl carrier protein reductase—FabI protein of Acinetobacter baumannii. The top three potential inhibitors: 21272541 > 89795992 > 89792657 showed favourable binding free energies including coulombic energy, van der Waals energy, and polar and non-polar energies. Furthermore, all three complexes were extremely stable and compact with reduced fluctuations during the simulations period. Inhibitor 21272541 exhibited the highest binding affinity against the Acinetobacter baumannii FabI protein. This is similar to our recent report, which also identified 21272541 as the lead inhibitor against Klebsiella pneumoniae infections. Future clinical studies evaluating drug effectiveness should prioritise inhibitor 21272541 which could be effective in treating infections caused by Gram-negative organisms.
Defect modes in defective one dimensional parity-time symmetric photonic crystal
Authors: Wang Tiecheng , Niu Yong 
Published: December 2023

AbstractThe introduction of defect layers into one-dimensional parity-time (PT) symmetric photonic crystals gives rise to resonances within the photonic bandgaps. These resonances can be effectively explained by our generalized temporal coupled mode theory. The scattering properties and dispersion relation of defect modes exhibit distinct characteristics compared to conventional one-dimensional Hermitian photonic crystals with defect layers. By tuning the non-Hermiticity or other model parameters, the modulus of the generalized decay rate can be reduced, consequently, the electric field concentrated within the defect layer strengthens. This arises due to the unique band structure of one-dimensional PT-symmetric photonic crystals, which differs significantly from that of traditional one-dimensional Hermitian photonic crystals. Furthermore, the interaction between multiple resonances is investigated through the introduction of multiple defect layers. Our study not only provides insights into resonance phenomena in defective non-Hermitian systems but also contributes to the design of relevant optical resonance devices.
Experimental results on nonlinear distortion compensation using photonic reservoir computing with a single set of weights for different wavelengths
Authors: Gooskens Emmanuel , Sackesyn Stijn , Dambre Joni , Bienstman Peter 
Published: December 2023

AbstractPhotonics-based computing approaches in combination with wavelength division multiplexing offer a potential solution to modern data and bandwidth needs. This paper experimentally takes an important step towards wavelength division multiplexing in an integrated waveguide-based photonic reservoir computing platform by using a single set of readout weights for up to at least 3 ITU-T channels to efficiently scale the data bandwidth when processing a nonlinear signal equalization task on a 28 Gbps modulated on-off keying signal. Using multiple-wavelength training, we obtain bit error rates well below that of the $$1.5 \times \,10^{-2}$$

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forward error correction limit at high fiber input powers of 18 dBm, which result in high nonlinear distortion. The results of the reservoir chip are compared to a tapped delay line filter and clearly show that the system performs nonlinear equalization. This was achieved using only limited post processing which in future work can be implemented in optical hardware as well.
Development of a distributed nonlinear Muskingum model by considering snowmelt effects for flood routing in the Red River
Authors: Atashi Vida , Barati Reza , Lim Yeo Howe 
Published: December 2023

AbstractThis research paper presents the development of a nonlinear Muskingum model which achieves precise flood routing through river reaches while considering lateral inflow conditions. Fourteen pairs of flood hydrograph found at two specific United States Geological Survey (USGS) stations located along the Red River of the North, namely Grand Forks and Drayton, are used for the calibrations and validations of the Muskingum model. To enhance the accuracy of the procedure, a reach is divided into multiple sub-reaches, and the Muskingum model calculations are performed individually for each interval using the distributed Muskingum method. Notably, the model development process incorporates the use of the Salp Swarm algorithm. The obtained results demonstrate the effectiveness of the developed nonlinear Muskingum model in accurately routing floods through the very gentle river with a bed slope of (0.0002–0.0003). The events were categorized into three groups based on their dominant drivers: Group A (Snowmelt-driven floods), Group B (Rain-on-snow-induced floods), and Group C (Mixed floods influenced by both snowmelt and rainfall). For the sub-reaches in Group A, single sub-reach (NR = 1), the Performance Evaluation Criteria (PEC) yielded the highest value for SSE, amounting to 404.9 × 106. In Group B, when NR = 2, PEC results the highest value were SSE = 730.2 × 106. The number of sub-reaches in a model has a significant influence on parameter estimates and model performance, as demonstrated by the analysis of hydrologic parameters and performance evaluation criteria. Optimal performance varied across case studies, emphasizing the importance of selecting the appropriate number of sub-reaches for peak discharge predictions.
Dihydrotanshinone I protects human chondrocytes and alleviates damage from spontaneous osteoarthritis in a guinea pig model
Authors: Zhang Yan-Zhuo , Wei Zhen-Jie , Yu Shu-Nan , Wang Xin-Yu , Wang Ying , Wu Cheng-Ai , Jiang Xu 
Published: December 2023

AbstractOsteoarthritis (OA) is the most common degenerative joint disease. Currently, no satisfactory pharmacological treatment exists for OA. The potential anti-inflammatory properties of Dihydrotanshinone I (DHT) have been reported, but its effects on OA are unclear. In this study, we assess the impact of DHT on the viability of human chondrocytes in vitro. We then use a guinea pig model to investigate the effects of DHT on knee osteoarthritis progression. Twelve-week-old Dunkin Hartley guinea pigs spontaneously developing OA were intraperitoneally injected with different doses of DHT for eight weeks. Micro-CT analysis was performed on the subchondral bone in the knee, and histological assessment of the knee joint was done using stained sections, the ratio of hyaline to calcified cartilage, and Mankin scores. DHT successfully restored IL-1β-induced decreases in cell viability in human primary chondrocytes. In the guinea pig model, intraperitoneal injections of DHT ameliorated age-induced OA, effectively reduced the expression level of two cartilage metabolism-related genes (ADAMTS4 and MMP13) and decreased the inflammatory biomarker IL-6 in the serum of guinea pigs developing spontaneous osteoarthritis. These findings demonstrate DHT’s protective effects on chondrocytes and suggest that it alleviates cartilage degradation and proteoglycan loss in OA.
DNA methylation rates scale with maximum lifespan across mammals
Authors: Crofts Samuel J. C. , Latorre-Crespo Eric , Chandra Tamir 
Published: December 2023

AbstractDNA methylation rates have previously been found to broadly correlate with maximum lifespan in mammals, yet no precise relationship has been observed. We developed a statistically robust framework to compare methylation rates at conserved age-related sites across mammals. We found that methylation rates negatively scale with maximum lifespan in both blood and skin. The emergence of explicit scaling suggests that methylation rates are, or are linked to, an evolutionary constraint on maximum lifespan acting across diverse mammalian lineages.
Investigating the reciprocity between cognition and behavior in adaptation to large-scale disasters
Authors: Tao Tiffany Junchen , Li Tsz Wai , Liang Li , Liu Huinan , Hou Wai Kai 
Published: December 2023

AbstractCognition and behavior could reciprocally impact each other and together determine mental health amid large-scale disasters such as COVID-19. This study reports a six-month cohort study of a population-representative sample of Hong Kong residents (N = 906) from March–August 2021 (T1) to September 2021–February 2022 (T2). Cross-lagged panel analyses reveal that T1 poor behavioral functioning as indicated by high daily routine disruptions is inversely associated with T2 cognitive adaptation as indicated by self-efficacy and meaning-making but not vice versa. T1 routine disruptions but not cognitive adaptation are positively associated with T2 probable depression/anxiety. The positive link between T1 routine disruptions and T2 probable disorders is mediated by poor cognitive adaptation at T2. The present findings suggest that upholding daily behavioral functioning relative to positive states of mind could have a more pivotal role in mental health amid large-scale disasters. Future studies can test interventions that enhance the sustainment of regular daily routines.
Orographic amplification of El Niño teleconnections on winter precipitation across the Intermountain West of North America
Authors: Stagge James H. , Torbenson Max C. A. , Sung Kyungmin , Phillips Benjamin , Kingston Daniel G. 
Published: December 2023

AbstractA large proportion of western North America experiences regular water stress, compounded by high seasonal and interannual variability. In the Intermountain West region, the El Niño/Southern Oscillation (ENSO) is a critical control on winter precipitation, but the nature of this signal is entangled with a combination of orographic effects and long-term climate trends. This study employs a spatially distributed, nonlinear spline model to isolate ENSO impacts from these other factors using gauge-based observations starting in 1871. In contrast to previous modelling approaches, our approach uses original gauge data, without shortening the record to accommodate a common period. This enables more detailed separation of ENSO effects from the confounding influence of topography and long-term trends, whereas the longer time frame permits more robust correlation with the ENSO signal. Here we show that the complex topography of the Intermountain West exaggerates the underlying ENSO signal, producing a 2.3–5.8 times increase in the range of ENSO-induced precipitation changes along high-elevation western slopes relative to lower elevations. ENSO effects on winter precipitation can be as large as ± 100 mm at high elevations. Further, our approach reveals that the previously recognized dipolar pattern of positive (negative) association of ENSO with precipitation in the south (north) manifests as an incremental relationship in the south but as a near-binary switch in effects between El Niño and La Niña in the north. The location and extent of the strongest precipitation differences vary during the positive and negative ENSO phases within each region. The intricacies of these spatial- and elevation-based modulations of ENSO impacts are especially informative for the northern centre of this dipole, where ENSO-precipitation relationships have previously been difficult to resolve.
Multi‐layer task scheduling and resource allocation schemes considering idle resource and task priority in IoT networks
Authors: Wang Suhong , Guo Wenhao , Sun Hongmin , Ren Junyu , Yan Ming , Hu Yongle , Qin Tuanfa 
Published: December 2023

AbstractWith more and more interconnected smart devices (ISDs) accessing the Internet of Things (IoT), massive and diverse tasks need to be transformed and computed. Mobile edge computing enables the offloading of tasks to nearby servers to enhance processing efficiency, which makes ISDs idle, causing resource waste and failing to satisfy the high real‐time requirements of tasks. Besides, when tasks with different priorities are processed in the order they are generated, it will be difficult for IoT to guarantee a timely response to high‐priority tasks. To address the aforementioned issues, we establish an edge‐terminal‐local architecture by software‐defined networking to centrally manage idle ISD resource (2ISDR). Then the proposed two‐step scheduling mechanism with preemptive priority queue ensures the real‐time responses to high‐priority tasks, and the minimum resource allocation coefficients make offloading effective. Finally, we also propose a modified NSGA‐III algorithm named MNSGA‐III, which is designed to make decisions about offloading and solve resource allocation for tasks, and we correct infeasible solutions by a two‐step correction function to ensure the feasibility of MNSGA‐III. Experimental results show that the method can ensure a timely response to high‐priority tasks and optimize processing time, energy consumption, and economic cost through the utilization of 2ISDR.
Coupling travel characteristics identifying and deep learning for demand forecasting on car‐hailing tourists: A case study of Beijing, China
Authors: Liu Zile , Liu Xiaobing , Wang Yun , Yan Xuedong 
Published: December 2023

AbstractOnline car‐hailing, with its advantages of convenience and efficiency, has quickly become popular among tourists, playing a crucial role in the accessibility of scenic spots. Due to the particularities of tourist travel behaviour and the complexity of travel supply and demand around scenic spots, research on car‐hailing tourists is relatively lacking at this stage. Based on multi‐source data, this study couples the identifying of travel characteristics, by introducing the concept of service dependency degree, with a Bayesian optimization–long short‐term memory–convolutional neural network (BO‐LSTM‐CNN) method to conduct multi‐task online car‐hailing demand forecasting. The evaluation of the dependency degree primarily encompasses the establishment of evaluation indices and the application of the entropy weight method and natural breakpoint method. The BO‐LSTM‐CNN model utilizes Bayesian optimization for hyperparameter tuning, LSTM for temporal variable processing, and CNN for the fusion of multi‐source information related to weather, space, and online car‐hailing attributes. Extracting online car‐hailing tourist travel orders based on spatial–temporal constraints, the proposed methods are applied to 72 scenic spots in Beijing, China. According to their dependency degree, Beijing's scenic spots are categorized into three levels of dependency on online car‐hailing services, from high to low. The outstanding forecasting efficacy of the proposed model for various scenic spots is verified through comparison tests with several benchmark models. Consequent to these findings, mobility service improvement strategies are specifically proposed for each class of scenic spots, which can provide valuable insights for the relevant tourism traffic management personnel.
Reliabilität und Validität des Lever Sign Tests bei Verdacht auf Band- und/oder Meniskus-Verletzung des Knies: ein Vergleich zwischen Orthopäde und Physiotherapeut
Authors: Cavelti David , Grehn Holger , Luomajoki Hannu 
Published: December 2023

ZusammenfassungEinleitung Das Ziel dieser Studie war die Untersuchung der Intertester-Reliabilität und Validität des Lever Sign-Tests. Der Intertester-Reliabilität wurde in bisherigen Studiennoch wenig Beachtung geschenkt. Um Vergleiche mit anderen Studien ziehen zu können, wurde zusätzlich die Intertester-Reliabilität und Validität des Lachman- und Anterior Drawer-Tests berechnet.Patienten/Material und Methoden Eingeschlossen wurden Patienten und Patientinnen zwischen 18 und 50 Jahren mit Verdacht auf Band- und/oder Meniskus-Verletzungen. Ausschlusskriterien waren Verdacht auf bösartige, systemische oder zentralneurologische Erkrankungen, akute Knorpelverletzungen, Verdacht auf Fraktur oder Kenntnis über den Kniebefund der Teilnehmenden. Die Tests wurden von einem erfahrenen Orthopäden und einem Physiotherapeuten randomisiert und verblindet durchgeführt. Für die Intertester-Reliabilität wurde der Cohen’s Kappa und für die Validität die Sensitivität und Spezifität, der Positiv und Negativ Prädiktive Wert und die Positive und Negative Likelihood ratio berechnet. Der MRI-Befund wurde als Goldstandard genutzt.Ergebnisse Sechsunddreissig Patienten und Patientinnen wurden in die Studie eingeschlossen. Davon waren 27 männlich (75%) und 9 weiblich (25%). Die Prävalenz von vorderen Kreuzbandläsionen lag bei 44,4%. Der Cohen’s Kappa (κ) des Lever Sign-Tests lag bei κ=0,6 (KI 95% [0,29, 0,91]), beim Lachman-Test bei κ=0,64 (KI 95% [0,35, 0,93]) und beim Anterior Drawer-Test bei κ=0,63 (KI 95% [0,3, 0,95]). Die Sensitivität des Lever Sign-Tests war für den Orthopäden und Physiotherapeuten 0,53 und 0,40, die Spezifität 0,89 und 0,79, der Positiv Prädiktive Wert 0,80 und 0,60, der Negativ Prädiktive Wert 0,70 und 0,62, die Positive Likelihood ratio 4,80 und 1,90 und die Negative Likelihood ratio 0,76 und 0,53.Schlussfolgerung Die geschätzte Intertester-Reliabilität des Lever Sign-Tests war gut. Der Lever Sign-Test eignet sich als Ergänzung zum Lachman-Test, der in der Literatur als validester Test angesehen wird. Die Schwächen und Unklarheiten des Funktionsmechanismus des Lever Sign-Tests dürfen nicht ignoriert werden und sollten weiter erforscht werden.
Complete chiroptical signal detection using weak measurement with intensity-contrast-ratio pointers
Authors: Wang Yunhan , Yang Shaojie , Zhang Qianli , Chen Yanyu , Hu Xiaolong , Zhang Hong , Zhang Zhiyou 
Published: December 2023

Chiroptical signals, including optical rotation (OR) and circular dichroism (CD), are widely utilized as potent probes for investigating the structure and properties of chiral molecules. However, acquiring both coexisting weak OR and CD signals simultaneously in a single measurement process with a high precision remains a challenge for conventional setups. In this article, a high-precision yet easy-to-set-up method for simultaneous detection of OR and CD signals based on weak measurement is theoretically and experimentally demonstrated. In addition, the chiroptical signals are detected using two new intensity-contrast-ratio pointers, which provide an expanded measurement range compared with the shift of the mean value pointer. The proposed method has been validated through a spin Hall effect light based experiment, with precision reaching the order of 10−7 and 10−6 rad for the detection of OR and CD, respectively. These results may serve as a catalyst for further studies of fast, multi-parameter biosensing technologies with ultra-precision.
Analysis of ion conduction behavior of Nb- and Zr-doped Li3InCl6-based materials via material simulation
Authors: Usami Takeshi , Tanibata Naoto , Takeda Hayami , Nakayama Masanobu 
Published: December 2023

The Li-ion conductivities of Li3InCl6 (LIC), which is a promising chloride solid electrolyte, and its compositional derivatives, Nb5+- and Zr4+-doped LIC, i.e., Li3−2xIn1−xNbxCl6 and Li3−yIn1−yZryCl6, respectively, were experimentally and computationally investigated. An increase in the ionic conductivity caused by Nb5+ or Zr4+ doping, which was due to the increase in Li vacancies, was observed in both the experimental and computational results. Nb5+ doping yielded a larger increase in conductivity at 60 °C. First-principles molecular dynamics studies indicated two factors affecting the Li-ion conductivity under doping with higher-valent ions: (1) the vacancy trapping effect and (2) the reduction in the phase-transition temperature from a Li/vacancy ordered structure to a disordered structure. In particular, in factor (2), the effect of Nb5+ doping is larger than that of Zr4+ doping, which supports the improvement in ionic conductivity at 333 K in the experiment.