bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the HPLC Profiling and Antioxidant Potency in Methanolic
Extracts of Curcuma longa L. Rhizomes
Authors: Shukla Babita , Kushwaha Poonam 
Published: September 2024

AbstractIn this exploration of Curcuma longa Linn., commonly known as turmeric,
renowned for its therapeutic history, our study focuses on the bioactive
compound curcumin. We established and validated an HPLC method for precise
curcumin quantification, complemented by an examination of total phenolic and
flavonoid content, as well as antioxidant capabilities in a methanolic extract
from C. longa rhizomes obtained through a methanol-based Soxhlet
extraction. The HPLC analysis utilized a C18 column with a mobile phase of
70:30 V/V Acetonitrile (ACN) to Water (with 1% Glacial Acetic Acid) under an
isocratic elution at 1 mL/min, detection at 420 nm, and a reference standard.
The method exhibited notable accuracy, precision, and reproducibility.
Antioxidant potential, assessed through DPPH, nitric oxide, and hydroxyl radical
scavenging assays, unveiled significant total phenol and total flavonoid
quantities, highlighting C. longa’s potent antioxidant capacity. The
study demonstrated a correlation between antioxidant activities and phenolic and
flavonoid concentrations, reinforcing the robustness of our method. In
conclusion, this method offers an effective means of quantifying curcumin within
C. longa rhizomes and holds promise as a valuable tool for
maintaining quality control in the production of this botanical material.
The Prevalence of Cytogenetic Abnormalities Detected by Interphase FISH Method in Chronic Lymphocytic Leukemia
Authors: Azhdari Shirin , Noori Sadat , Daneshbod Khosrow , Khalafi-Nezhad Abolfazl , Hashemi Seyed Mohammad Ali , Faghih Zahra , Haghighat Shirin , sarvari Jamal 
Published: September 2024

Abstract
Background Chronic lymphocytic leukemia (CLL) is the most prevalent adult leukemia. Identification of genomic aberration provides prognostic/predictive information that is helpful in the precision medicine management of these patients. The aim of this study was to determine prevalence of the most common cytogenetic abnormalities of CLL patients in the southwest region (Shiraz) of Iran and correlate with clinical prognostic parameters to clarify their prognostic value.
Materials and Methods In this cross-sectional study, 100 patients with CLL were recruited from April 2019 to October 2021. Four milliliters of anticoagulated peripheral blood was collected from each participant. The sample was used for complete blood count (CBC) test and fluorescence in situ hybridization (FISH) test. Interphase FISH (I-FISH) was performed for most common cytogenetic abnormalities, including trisomy 12, 13q14 deletion, 11q deletion, and 17p deletion on interphasic cell nuclei.
Results Among 100 patients with CLL, 33 (33%) were females and 67 (67%) were males. The mean age (mean ± standard error [SE]) of the patients was 59.00 ± 1.14 years, with a ranged of 25 to 79 years. Our analysis demonstrated that 86 (86%) patients had at least one chromosomal aberration. The most commonly detected abnormality was 13q deletion (61, 61%), followed by 17q deletion (50 cases, 50%). Trisomy 12 was detected in 14 (14%) cases and 10 cases (10%) had 11q deletion.
Conclusion The higher frequency of 13q14 and 17p anomalies in our study may be attributed to delayed medical consultations, leading to the emergence of secondary abnormalities. More studies are recommended for verifying the results.
Public acceptability of climate-motivated rationing
Authors: Lindgren Oskar , Elwing Erik , Karlsson Mikael , Jagers Sverker C. 
Published: September 2024

AbstractRecent reports from climate scientists stress the urgency to implement more ambitious and stringent climate policies to stay below the 1.5 °C Paris Agreement target. These policies should simultaneously aim to ensure distributional justice throughout the process. A neglected yet potentially effective policy instrument in this context is rationing. However, the political feasibility of rationing, like any climate policy instrument, hinges to a large extent on the general public being sufficiently motivated to accept it. This study reports the first cross-country analysis of the public acceptability of rationing as a climate policy instrument by surveying 8654 individuals across five countries—Brazil, Germany, India, South Africa, and the US—on five continents. By comparing the public acceptability of rationing fossil fuels and high climate-impact foods with consumption taxes on these goods, the results reveal that the acceptability of fossil fuel rationing is on par with that of taxation, while food taxation is preferred over rationing across the countries. Respondents in low-and middle-income countries and those expressing a greater concern for climate change express the most favourable attitudes to rationing. As political leaders keep struggling to formulate effective and fair climate policies, these findings encourage a serious political and scientific dialogue about rationing as a means to address climate change and other sustainability-related challenges.
Quantum walks advantage on the dihedral group for uniform sampling problem
Authors: Dhamapurkar Shyam , Dang Yuhang , Wagh Saniya , Deng Xiu-Hao 
Published: September 2024

Abstract
Random walk algorithms are crucial for sampling and approximation problems in statistical physics and theoretical computer science. The mixing property is necessary for Markov chains to approach stationary distributions and is facilitated by walks. Quantum walks show promise for faster mixing times than classical methods but lack universal proof, especially in finite group settings. Here, we investigate the continuous-time quantum walks on Cayley graphs of the dihedral group D
2n
for odd n, generated by the smallest inverse closed symmetric subset. We present a significant finding that, in contrast to the classical mixing time on these Cayley graphs, which typically takes at least order

Ω
(

n

2

log
(
1

/

2
ϵ
)
)

, the continuous-time quantum walk mixing time on D
2n
is of order

O
(
n

(
log
n
)

5

log
(
1

/

ϵ
)
)

, achieving a quadratic improvement over the classical case. Our paper advances the general understanding of quantum walk mixing on Cayley graphs, highlighting the improved mixing time achieved by continuous-time quantum walks on D
2n
. This work has potential applications in algorithms for a class of sampling problems based on non-abelian groups.
Changing windstorm characteristics over the US Northeast in a single model large ensemble
Authors: Coburn Jacob , Barthelmie Rebecca J , Pryor Sara C 
Published: September 2024

Abstract
Extreme windstorms pose a significant hazard to infrastructure and public safety, particularly in the highly populated US Northeast (NE). However, the influence climate change and changing land use will have on these events remains unclear. A large ensemble generated using the Max-Planck Institute (MPI) Earth system model is used to generate projections of NE windstorms under different shared socioeconomic pathways (SSPs) and to attribute changes to projected land use land cover (LULC) change, externally forced changes and internal climate variability. To reduce the influence of coarse grid cell resolution and uncertainties in surface roughness lengths, windstorms are identified using simultaneous widespread exceedance of local 99th percentile 10 m wind speeds (U99). Projected declines in forest cover in the NE and the resulting reductions in surface roughness length under SSP3-7.0 lead to projections of large increases in U99 and derived windstorm intensity and scale. However, these projected changes in regional LULC under SSP3-7.0 are unprecedented in a historical context and may not be realistic. After corrections are applied to remove the influence of LULC on wind speeds, regionally averaged U99 exhibit declines for most of the single model initial-condition large ensemble (SMILE) members which are broadly proportional to the radiative forcing and global air temperature increase in the SSPs, with a median value of −0.15 ms−1 °C−1. While weak cyclones are projected to decline in frequency in the NE, intense cyclones and the resulting windstorms and indices of socioeconomic loss do not. Where present, significant trends in these loss indices are positive, and some MPI SMILE members generate future windstorms that are unprecedented in the historical period.
Fault Detection in Turbines Using Machine Learning: A study of the capabilities of Various Classification Algorithms
Authors: Baral Aditi , Verma Neha , Adhikari Image , Chitrakar Sailesh , Dahlhaug Ole Gunnar 
Published: September 2024

Abstract
This paper presents a comprehensive study of application of different machine learning techniques for the prediction of turbine faults in an early stage. As the need to ensure an optimal turbine operation through early stage fault detection grows, precise predictive models using machine learning techniques are also increasing rapidly. This study primarily focuses on development and evaluation of the predictive models capable of anticipating fault phases using different range of classification algorithms. It assesses the effectiveness of different classification methods including Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Random Forest, and Convolutional Neural Networks (CNNs) to predict distinct turbine phases. These algorithms are evaluated on experimented dataset encompassing various stages of faults. The results from the algorithm show that CNN was accurately predicting the particular turbine fault phases achieving 80% accuracy with a small length of time series. The deep learning capabilities of CNN capture intricate spatial patterns in turbine data enabling them to discern fault indicators eluded by traditional machine learning methods. The insights gained from this research helps to extend the application of machine learning approaches in the field of turbine fault detection, paving the way for more precise and dependable early failure detection systems.
Calcium phosphate complex of recombinant human thrombomodulin promote bone formation in interbody fusion
Authors: Lin Cheng-Li , Chen Yu-Wei , Kuo Cheng-Hsiang , Tu Ting-Yuan , Wu Hua-Lin , Tsai Jui-Chen , Shyong Yan-Jye 
Published: September 2024

Abstract
Interbody fusion is an orthopedic surgical procedure to connect two adjacent vertebrae in patients suffering from spinal disc disease. The combination of synthetic bone grafts with protein-based drugs is an intriguing approach to stimulate interbody bone growth, specifically in patients exhibiting restricted bone progression. Recombinant human thrombomodulin (rhTM), a novel protein drug characterized by its superior stability and potency, shows promise in enhancing bone formation. A composite bone graft, termed CaP-rhTM, has been synthesized, combining calcium phosphate (CaP) microparticles as a delivery vehicle for rhTM to facilitate interbody fusion. In vitro studies have demonstrated that rhTM significantly promotes the proliferation and maturation of preosteoblasts at nanogram dosage, while exerting minimal impact on osteosarcoma cell growth. The expression levels of mature osteoblast markers, including osteocalcin, osteopontin, alkaline phosphatase, and calcium deposition were also enhanced by rhTM. In rat caudal disc model of interbody fusion, CaP-rhTM with 800 ng of drug dosage was implanted along with a polylactic acid cage, to ensure structural stability within the intervertebral space. Microcomputed tomography analyses revealed that from 8 to 24 weeks, CaP-rhTM substantially improves both bone volume and trabecular architecture, in addition to the textural integrity of bony endplate surfaces. Histological examination confirmed the formation of a continuous bone bridge connecting adjacent vertebrae. Furthermore, biomechanical assessment via three-point bending tests indicated an improved bone quality of the fused disc. This study has demostrated that rhTM exhibits considerable potential in promoting osteogenesis. The use of CaP-rhTM has also shown significant improvements in promoting interbody fusion.
Ecosystem services in the Yangtze River Basin and their trade-offs/synergies relationships in response to climate change
Authors: Xu Yuqing , Hou Ruiping , Xiao Fengjin 
Published: September 2024

Abstract
The Yangtze River Basin is an important ecological security barrier with significant economic status, but it is greatly affected by climate change. Therefore, we investigated the spatio-temporal evolution characteristics of annual ecosystem service (net primary production (NPP), water conservation and soil retention), their interrelationships and responses to climate change in the Yangtze River Basin from 2001 to 2020. The annual NPP, soil retention and water conservation were 511 gC m−2, 632 t and 272 mm, respectively and they all increased over 2001–2020 though this varied in both time and space. The capacities of soil retention and water conservation did not increase, and even gradually decreased for first 10 years (2001–2010), most likely due to the subsequent effects of the catastrophic flood of Yangtze River occurred in 1998. There are tradeoffs between NPP and soil retention/water conservation in the west Sichaun Province, which is different from the rest of the Yangtze River Basin where synergistic relationships dominate. Precipitation is the dominate climatic influencing factor on the ecosystem service trends found in the Yangtze River Basin. The concept of ecosystem services is being incorporated into decision-making and management, this study is critical to guide regional effective resource utilization, ecosystem management decisions and feasible policies.
An in-depth study of the synthesis of ReSe2 for anisotropic Raman characteristics
Authors: Nam Giho , Park Sohyeon , Heo Keun , Bong Jungwoo , Lee DongGyu , Kim Hyunsoo , Ponnusamy Krishna Moorthy , Bae Hagyoul , Park Hyeong Gi , Lee Jae-Hyun , Jang Hyeon-Sik 
Published: September 2024

Abstract
Two-dimensional transition metal dichalcogenides (TMDs) have received more interest for their potential role in future electronic and optoelectronic applications. Unlike other TMDs, Rhenium diselenide (ReSe2) stands out for its distinctive anisotropic growth characteristics. These unique features arise from its low lattice symmetry and interlayer decoupling, this has sparked significant interest among researchers. Previous research has indicated the presence of various growth patterns, including dendritic formations and structures resembling flowers. In this study, we effectively produced ReSe2 using the ‘Tilting Boat’ method to achieve growth on a 21 μm scale. Through precise manipulation of the growth conditions, we successfully attained flakes of 21 μm scale in comparison to prior findings. Moreover, we successfully produced a variety of shapes, including triangles, diamonds, and hexagons, on 1 × 1 cm2 Si/SiO2 substrates. Furthermore, we achieved the successful production of a continuous ReSe2 film on a 1 × 3 cm2 Al2O3 substrate. We verified the distinct anisotropic properties of ReSe2 via Raman Spectroscopy. Furthermore, we acquired three-dimensional visual representations of ReSe2 flakes and continuous films via SEM measurements. By employing EDS data and analysing x-ray photoelectron spectroscopy spectra, we have established a compositional ratio of 1:2 for Re and Se, which aligns with the MX2 structure. This confirmation indicates the successful synthesis of high-quality ReSe2 flakes.
Process optimization of preparing CMOS backplane for ultrahigh pixel density red Micro-LED display
Authors: Wang Xue-Yan , Guo Cheng-Long , Zhou Yi-Jian , Zhu Xue-Qi , Yan Zhi-Bing , Li Yang , Yang Tian-Xi , Sun Jie , Yan Qun 
Published: September 2024

Abstract
In this paper, an AlGaInP-based red Micro-LED display measured 17.78 mm (0.7 in), with a resolution of 1920 × 1080, a light-emitting mesa size of 6 μm, a pixel pitch of 8 μm and a pixel density of 3175 PPI was designed and fabricated with a CMOS driver backplane. The metal bump preparation technology of the complementary metal-oxide semiconductor driver backplane was optimized to enhance the bonding yield and create an optimal display effect. Improper sizing of the etched window in the SiO2 insulation and passivation layer can have a detrimental impact on the metal bump preparation and subsequent bonding process. By optimizing the settings of lithography and dry etching, the appropriate size of the etched aperture in the passivation layer was achieved. The high density, small size, and large aspect ratio of the photoresist openings for the bump fabrication made it challenging to remove the photoresist following the metal evaporation. To successfully remove the photoresist, it is important to carefully choose suitable experimental conditions for the removal. Afterwards, an 8 μm AlGaInP-based red Micro-LED display was effectively integrated with complementary metal-oxide semiconductor using flip-chip bonding technology. This work may be of reference value to those who work on ultrahigh density red Micro-LEDs that is challenging but crucial for future full color micro displays.
A critical review on the high entropy material coatings: criteria for materials selection and coating procedure
Authors: Polyakova Marina , Ostovari Moghaddam Ahmad , Trofimova Svetlana , Samodurova Marina , Trofimov Evgeny 
Published: September 2024

Abstract
There is a continuous demand to design materials with comprehensive properties as the boundaries of human works extend to new branches of technological activities. For designing parts from new materials, it is essential to consider the possible technological problems and economic aspects, however, not always the solution is evident. In this regard, multi-component high entropy materials (HEMs) have opened promising perspectives to be employed as both structural materials and coatings. This review paper summarizes the most important factors affecting fabrication of HEA coatings with a defined level of functional properties. The procedure is presented as a hierarchical system of the effective factors which are divided into two groups: functional and exploitation demands to the coating properties and technological features of the coatings deposition technique. We show that the most important factors in functional and exploitation demands are exploitation conditions and design/ergonomic properties, which determine the functional properties and subsequently material of the coatings. On the other hand, in technological features, parameters such as structural material (substrate), shape and dimension of the part, accuracy and surface finish and modes of the manufacturing process are critical ones and determine the coating deposition technique. This approach makes it possible to evaluate the importance of different factors on the exploitation conditions of HEAs coatings. By considering the published investigations, it is illustrated how to implement the proposed procedure to choose coatings which will be efficient for a definite exploitation condition.
Optimal initial duty for improved MPPT under change in irradiances and partial shading conditions
Authors: B S S Santosh , Mohammed Thameem Ansari M , P Kanta Rao , G Harish Kumar Varma 
Published: September 2024

Abstract
Solar photovoltaic cells are widely used in renewable energy power generation. The efficient operation of these photovoltaic (PV) system is based on maximum power point tracking (MPPT). Various MPPT methods have been proposed to increase the output of a PV system. But confusion arises when choosing the optimal MPPT algorithm and its parameters such as perturbation time and initial duty. This paper examines the optimal initial duty and perturbation time to improve the performance of conventional MPPT techniques under uniform shading and partial shading. During the change in irradiances, at the initial irradiance the Modified P&O tracked MPPT faster because the modified P&O had less settling time during changes in irradiance for different initial duty ratios. During partial shading conditions, the TCT generates more power than the S and SP topologies and modified P&O tracked the MPPT in less time. However, at the high duty ratio, the P&O and INC gave similar results, which were better than the modified P&O. It was also observed that the initial duty ratio (Di) in the MPPT algorithm had a negligible effect on TCT configuration under partial shading conditions. These findings help in various applications for PV systems.
Fault diagnosis of wind turbine gears based on OCSSA-VMD and WOA-CNN-BiLSTM
Authors: Liu Hongyue , Wang Zhen , Gong Jinlong , Kou Lei , Xu Yan 
Published: September 2024

Abstract
The accuracy of wind turbine gearbox fault diagnosis will be compromised if the fault feature data is not adequately extracted during operation. To enhance fault identification efficiency and mitigate human interference in parameter setting, this paper introduces an optimized mode decomposition algorithm OCSSA-VMD, derived from variational mode decomposition (VMD) and further optimized by osprey-Cauchy-sparrow search algorithm (OCSSA). This algorithm offers two key advantages: (1) automatic optimization of parameters such as the number of modes k and penalty factor α; (2) reduction of feature dimensionality through mean impact value (MIV) algorithm based on minimum envelope entropy principle, resulting in a multi-fault feature vector set from 13 time-domain features in the intrinsic mode function (IMF) optimal component of wind turbine gearbox vibration data. Additionally, a fault diagnosis model WOA-CNN-BiLSTM is proposed based on whale optimization algorithm (WOA) and convolutional neural network-bidirectional long-short-term-memory (CNN-BiLSTM), which demonstrates improved fault classification accuracy to 98.3333% and diagnosis accuracy to 98.3853% under conditions of insufficient data when compared with other models.
A prediction rigidity formalism for low-cost uncertainties in trained neural networks
Authors: Bigi Filippo , Chong Sanggyu , Ceriotti Michele , Grasselli Federico 
Published: September 2024

Abstract
Quantifying the uncertainty of regression models is essential to ensure their reliability, particularly since their application often extends beyond their training domain. Based on the solution of a constrained optimization problem, this work proposes ‘prediction rigidities’ as a formalism to obtain uncertainties of arbitrary pre-trained regressors. A clear connection between the suggested framework and Bayesian inference is established, and a last-layer approximation is developed and rigorously justified to enable the application of the method to neural networks. This extension affords cheap uncertainties without any modification to the neural network itself or its training procedure. The effectiveness of this approach is shown for a wide range of regression tasks, ranging from simple toy models to applications in chemistry and meteorology.