bluuebunny/crossref_metadata_2025_split huggingface dataset:
Estuary salinity prediction using machine learning: case study in the Hau estuary in Mekong River, Vietnam
Authors: Nguyen Huu Duy , Dang Dinh Kha , Bui Quang-Thanh 
Published: January 2025

ABSTRACT
The prediction of saltwater intrusion in estuaries plays an important role, supporting decision-makers or farmers in building strategies, and also, policies made for agricultural development and water resource management. The objective of this study is to develop machine learning models, namely gated recurrent unit (GRU), GRU-GWO (grey wolf optimiser), and GRU-SFO (sailfish optimiser algorithm) to predict saltwater intrusion for 1, 7, 15, and 30 days ahead in the Mekong estuary of Vietnam. Several statistical indices, namely root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2), were applied to evaluate the accuracy of the saltwater intrusion model. The results showed that the GWO and SFO optimisation algorithms successfully improved the accuracy of the GRU model to predict saltwater intrusion. For a one day forecast, the R2 value of the proposed models ranged from 0.89 to 0.91, for a seven day forecast, it ranged from 0.81 to 0.85, for a 15-day forecast, from 0.67 to 0.76, and for a 30-day forecast, from 0.52 to 0.55. The results indicated the ability of the GRU model to predict saltwater intrusion.
Oridonin Suppresses the Malignant Progression of Lung Cancer by Targeting S100A11
Authors: Luo Yulin , Li Jingjing , Chen Yao , Huang Yan , Luo Qi , Luo Qiang , Huang Qingqing , Huang Gang , Jin Mingming 
Published: January 2025

Background:
Lung cancer (LC) is the second most lethal cancer and efficient
treatments are missing. Our understanding of the underlying pathogenic mechanisms remains
limited. Oridonin is a compound extracted from the Chinese herb Rabdosia rubescens
with anticancer properties. Nevertheless, its effects on LC and the underlying mechanisms
remain unknown.

Methods:
In the current research, A549 and Hcc1833 cells were treated with different
doses of oridonin, and cell proliferation and migration were detected using CCK8, EdU,
Transwell, and wound healing assays. A subcutaneous tumor and caudal vein metastasis
model was generated to verify the inhibitory effects of oridonin on Hcc1833 tumor
growth and metastasis in vivo. Proteomics analyses then were performed to examine the
regulatory mechanism. LiP-SMap combined with microscale thermophoresis and molecular
docking analyses were used to validate the relationship between oridonin and
S100A11.

Result:
Data showed that oridonin suppressed cell proliferation and migration depending
on dose and suppressed tumor growth and invasion. LiP-SMap and molecular docking
analyses confirmed that oridonin interacted with the Asn-53 residue of S100A11,
which inhibited the activation of oridonin. S100A11 overexpression reversed the inhibitory
effects of oridonin on cell proliferation and migration.

Conclusion:
In conclusion, the data indicate that oridonin suppresses LC malignant progression
by targeting S100A11.
Predicting Polymerase Chain Reaction Success: Integrating the K-Word Order Model, Physicochemical Properties Modeling of Double Bases, and
Support Vector Machine
Authors: Yan Long , Liu Yong , Yang Yan 
Published: January 2025

Introduction:
Polymerase Chain Reaction (PCR) has been a pivotal scientific technique
since the twentieth century, and it is widely applied across various domains. Despite its
ubiquity, challenges persist in efficiently amplifying specific DNA templates.

Method:
While PCR experimental procedures have garnered significant attention, the analysis of
the DNA template, which is the experiment's focal point, has been notably overlooked. This
study addresses the uncertainty surrounding the amplification of DNA fragments using conventional
Taq DNA polymerase-based PCR protocols. The imperative need to characterize DNA
templates and devise a reliable method for predicting PCR success is underscored.

Result:
In this study, we formulate a 72-dimensional feature vector representing a DNA template
through the utilization of k-word order and modeling of physicochemical properties of double
bases. Subsequently, a Support Vector Machine (SVM) model is employed to assess PCR results.

Conclusion:
A jackknife cross-validation test is used to evaluate the anticipated success rates,
resulting in an overall accuracy of 95.77%. Sensitivity, specificity, and Matthew's Correlation
Coefficient (MCC) stand at 95.75%, 95.79%, and 0.915, respectively.
Exploring Drug-Drug Interactions between Losartan and Carbamazepine: A
Pharmacokinetic and Pharmacodynamic Study
Authors: Sundargowda Shruthi A , Kadiri Sunil Kumar 
Published: January 2025

Background:
Hypertension, which affects 1.28 billion people globally aged 30 to 79, is characterized
by continuously high blood pressure (140/90 or more) and raises the risk of premature death. Losartan, an
angiotensin receptor blocker (ARB), is suggested for patients under the age of 55 who cannot take ACE inhibitors
as a first treatment option. Epilepsy, a chronic neurological illness marked by repeated seizures, affects
more than 50 million individuals worldwide and is the third most common chronic brain disorder. Both hypertension
and epilepsy are frequent chronic illnesses, with increased blood pressure greatly raising the risk of
epilepsy due to its relationship with cerebrovascular disease, doubling the risk when compared to people with
normal blood pressure.

Objective:
The effect on pharmacokinetic and pharmacodynamics of losartan on concomitant administration
with carbamazepine was investigated.

Materials and Methods:
Wistar rats of either sex, with a minimum of six animals per group, were used in the
investigation. The rats were treated with Losartan and Losartan-Carbamazepine for 30 days. Blood samples
were taken via retro-orbital plexus at 0, 1, 2, 4, 6, and 12 hours after treatment concluded, and they were subjected
to high-performance liquid chromatography for plasma analysis to calculate AUC, t1/2, and Clearance.
A pharmacodynamic evaluation was done by inducing hypertension in rats using a 10% fructose solution and
the effect of pretreated Losartan and Losartan-Carbamazepine on blood pressure was determined.

Results:
In the Losartan and Carbamazepine treated group, there was a reduction in the AUC and t1/2 and a reported
increase in the clearance value compared to Losartan alone treated rats. In fructose-induced hypertension
model to evaluate the effect of losartan and carbamazepine on BP showed an increase in mean arterial
pressure, plasma glucose, and a reduction in triglycerides level was noted in comparison to Losartan alone
treated rats indicating therapeutic failure of Losartan.

Conclusion:
Based on these studies, it is concluded that CBZ has reduced the effectiveness of losartan and
therefore, co-administration of these drugs should be avoided.
Molecular Mechanisms and Pathways of Mesenchymal Stem Cell-mediated Therapy in Brain Cancer
Authors: Singh Kuldeep , Singh Geetanjali , Gupta Jeetendra Kumar , Choudhary Alka N. , Kumar Arun , Jain Divya , Sharma Mukesh Chandra , Kumar Shivendra 
Published: January 2025

Abstract:
Mesenchymal stem cells (MSCs) have emerged as a promising therapeutic approach in
the treatment of brain cancer due to their unique biological properties, including their ability to
home tumor sites, modulate the tumor microenvironment, and exert anti-tumor effects. This review
delves into the molecular mechanisms and pathways underlying MSC-mediated therapy in
brain cancer. We explore the various signalling pathways activated by MSCs that contribute to
their therapeutic efficacy, such as the PI3K/Akt, Wnt/β-catenin, and Notch pathways. Additionally,
we discuss the role of exosomes and microRNAs secreted by MSCs in mediating anti-tumor effects.
The review also addresses the challenges and future directions in optimizing MSC-based
therapies for brain cancer, including issues related to MSC sourcing, delivery methods, and potential
side effects. Through a comprehensive understanding of these mechanisms and pathways, we
aim to highlight the potential of MSCs as a viable therapeutic option for brain cancer and to guide
future research in this field.
Excess Pore Water Pressure Ratio Comparison from Empirical and Numerical Methods to Determine Liquefaction Potential in Palu, Central Sulawesi, Indonesia
Authors: Al Rahman Mukhlis Habib , Fathani Teuku Faisal , Wilopo Wahyu 
Published: January 2025

Background
Palu is a city in Central Sulawesi Province with a very high level of seismic activity. The seismicity in Central Sulawesi is associated with the active movement of the Palu Koro fault. One of the most severe events occurred on September 28, 2018, which triggered liquefaction and a tsunami. This is also related to the lithology of Palu, which consists of alluvial deposits predominantly made up of sand.

Objective
This study compares excess pore water pressure values analyzed empirically and numerically to identify liquefaction potential. It aims to provide additional perspectives for engineers in designing buildings around the study area that are resistant to liquefaction.

Methods
Excess pore water pressure was analyzed using empirical and numerical methods to determine liquefaction potential. The empirical method used the equation by Yegian and Vitteli (1981), while the numerical method involved finite element analysis using the Plaxis 2D application and nonlinear analysis using DEEPSOIL v7.

Results
The results from the three methods of analyzing excess pore water pressure to determine liquefaction potential at the four borehole points showed differences. For the empirical method, using the equation by Yegian and Vitelli (1981), the results indicated that the layers with a pore pressure ratio (ru>0.8) were deeper than the finite element and non-linear methods.

Conclusion
The differences in methods result in varying outcomes in analyzing excess pore water pressure to identify liquefaction potential. The empirical method uses the peak value of Peak Ground Acceleration (PGA) to evaluate the entire soil profile, leading to a more generalized assessment. In contrast, the non-linear and finite element methods consider each layer's behavior under the applied seismic load, providing more detailed and similar results.
Investigation of the Prevalence of Chronic Pulmonary Effusion Causes and Response to Treatment (Pleurodesis) in Patients
Authors: Shirzadi Alireza , Ahmadinejad Izadmehr , Ahmadinejad Mojtaba , Hatami Saeed , Soltanian Ali , Ahmadinejad Yasmina 
Published: January 2025

Background
Pleural effusion, the pathological accumulation of fluid in the pleural space, is widespread. This study investigates pleural effusion in terms of malignancy among patients referred to tertiary health care centers and evaluates the response rates to different pleurodesis techniques.

Methods
This cross-sectional study enrolled all patients with pleural effusion referred to a tertiary health care center. Laboratory data, including White Blood Cell count and differentiation (WBC), Hemoglobin levels (HB), Erythrocyte Sedimentation Rate (ESR), and biochemical analysis results of the pleural fluid (protein, glucose, and lactate dehydrogenase) were recorded. Data from pleural fluid cytopathological examination, including cell count, cell types, gram staining, and pleural fluid culture, were also documented. Patients undergoing pleurodesis were assessed for response rates, which were categorized as complete, partial, or no response based on clinical and radiological criteria. Collected data were subjected to statistical analysis.

Results
The study investigated 144 patients with chronic pleural effusion, with an average age of 47.59 years. Of these, 97 patients (66%) were male and 47 patients (34%) were female. The most common cause of chronic pleural effusion was malignancy, with a prevalence of 65.9%. Among patients treated with pleurodesis, the overall response rate was 78.4%, with chemical pleurodesis achieving a higher complete response rate (65%) compared to mechanical pleurodesis (55%). Other prevalent causes of chronic pleural effusion, in descending order, included heart failure, liver cirrhosis, chronic kidney failure, and unknown factors.

Conclusion
This study highlights malignancy and chronic heart failure as the predominant etiologies of chronic pleural effusion in a tertiary healthcare setting. Furthermore, it emphasizes the efficacy of pleurodesis techniques, with chemical pleurodesis demonstrating superior outcomes. These findings offer valuable insights into the pathogenesis and management of chronic pleural effusion.
Exploring the Therapeutic Potential of Benzimidazole Hybrids as Antimicrobial Agents: An In-Depth Analysis
Authors: Shukla Sugat , Azad Iqbal , Akil Mohd , Owais Mohammad , Siddiqui Benjamin , Verma Shikhar , Singh Kuldeep , Kumar Arun 
Published: January 2025

Background:
Heterocyclic compounds play an essential role in biological sys-tems and occur widely in nature. They are fundamental in the development of pharma-ceuticals aimed at combating microbial infections and other biological activities. Phar-macological evaluations have demonstrated their efficacy against diverse bacterial strains. This study investigates the antimicrobial properties of various benzimidazole hy-brids. The findings highlight the significant influence of substituting nitrogenous scaf-folds with various heteroatoms on the potential development of new antimicrobial agents.

Objective:
This review article is expected to make a substantial contribution to the ad-vancement of efficacious antibacterial medications. The research's goal is to improve the efficacy of combating bacterial infections by utilizing the potent properties of benzimid-azole-based hybrid scaffolds. In the end, this will aid in reducing the global incidence of this contagious illness.

Methods:
Several nitrogen-containing heterocyclic compounds display substantial poten-tial as antibacterial agents. These compounds possess fused benzene and imidazole nu-clei. These nuclei could change the number of electrons they have, which in turn affects their physiochemical characteristics. The versatility of drugs arises from their capacity to interact with receptors in various modalities, which is a key factor in drug pharmacolog-ical screening. Benzimidazole-based hybrids have demonstrated a wide range of pharma-cological effects, including antibacterial, anti-HIV, anticancer, antimalarial, antiviral, an-tifungal, antioxidant, anti-inflammatory, and anti-tubercular activities.

Results:
Pyrazole, imidazole, oxazole, thiazole, indole, and benzimidazole are examples of compounds that include nitrogen species. These nitrogen-containing compounds en-gage in metabolic interactions with other molecules within the cell. Nevertheless, an over-abundance of reactive nitrogen species can cause cytotoxicity, causing harm to vital bio-logical macromolecules. But benzimidazole is traditionally the most effective, with a wide range of important qualities, including antibacterial, anti-HIV, anticancer, antima-larial, antiviral, antifungal, antioxidant, anti-inflammatory, and anti-tubercular activities.

Conclusion:
This study focuses on the efficacy of novel benzimidazole-based hybrid scaffolds in inhibiting microbial growth or eradicating microorganisms. The study pri-marily focuses on recent studies carried out from 2009 to 2024. The study highlights the effectiveness of different benzimidazole-based hybrids using MIC values. More in-depth studies also show that adding electron-withdrawing groups (EWGs) to the nitrogenous framework might make them more effective. Further research is necessary to design strong, least-toxic benzimidazole-based hybrids that can either kill or inhibit multidrug-resistant (MDR) bacteria.
Research on ACC Control Strategy for Electric Vehicles Considering Cut-in Behavior
Authors: Runhua Li , Huanhuan Zhang , Shengli Hu , Mengyi Zhang 
Published: January 2025

Background:
Current adaptive cruise control systems primarily focus on the main target
vehicle in the primary lane. However, there may be a delay in updating their targets after a side vehicle
merges. This delay can impede the effective utilization of driving data from merging side vehicles,
resulting in delayed responses and an increased risk of collision.

Objective:
Aiming at the problem of untimely control of traditional adaptive cruise control systems
in cut-in scenarios, the authors establish a parallel model and collision analysis and design the control
strategy of adaptive cruise under parallel behavior to improve the safety, following, and comfort
of ACC.

Methods:
Initially, the vehicle model provided by CarSim is utilized and the power system parameters
are adjusted to match the dynamic performance index. The permanent magnet synchronous
motor model is then simplified to create an electric vehicle model. Following this, the cruise control
system is designed using a PID control method, incorporating a hierarchical control structure.
Simultaneously, a cut-in model characterized by sinusoidal acceleration is established, and a collision
avoidance strategy based on cut-in behavior is formulated. Building on this foundation, an
adaptive cruise control strategy is developed that takes cut-in behavior into account.

Results:
A test scenario utilizing the CarSim and Simulink co-simulation platforms was developed
to simulate and validate the conditions for mode switching and lane cut-in. The ACC system, considering
cut-in behavior recognition, demonstrated an ability to control the lead vehicle approximately
1 second earlier than traditional ACC systems. Notably, the distance error improved from -
0.1039 m to 0.040 m, the absolute value of velocity error decreased from 2.65 m/s to 2.02 m/s, the
absolute value of main vehicle acceleration reduced by 34%, and the jerk response in acceleration
diminished by approximately 14%.

Conclusion:
The proposed multi-objective cooperative adaptive cruise control system, which considers
cut-in behavior, is effective.
MEM-8X8: A Multimodal Framework for Emotion Classification and Mismatch Analysis Using the ICE Dataset
Authors: Sharma Rishabh , Kukreja Vinay 
Published: January 2025

Aims:
The study aims to evaluate visual and textual emotions, understand mismatches
and overall explainability using the proposed multimodal emotion mapping-8X8
(MEM-8X8) framework on the developed IndiComics Emotion (ICE) dataset.

Background:
Understanding and aligning emotions in the visual and linguistic modes of comics
is difficult due to their stylized and abstract nature. However, existing unimodal methods
fail to obtain the interplay between text and visuals, highlighting the requirement for multimodal
techniques for advanced emotion classification and mismatch assessment.

Objective:
This study proposes a robust MEM-8X8 framework backed by VisualBERT to classify
and analyze the ICE dataset into visual and nuanced textual emotions, analyze mismatches,
and provide comprehensive explainability with advanced interpretation tools.

Methods:
The proposed MEM-8X8 framework combines the Vision Transformers (ViT) and
the bidirectional encoder representations from transformers (BERT) embeddings to evaluate
the multimodal emotion classification and mapping using VisualBERT. Chi-square tests are
conducted to analyze if the given emotions are in agreement, mismatched, and statistically significant.
Along with this, the proposed model has outperformed its performance when compared
with existing models.

Results:
The VisualBERT model outperformed the unimodal ViT and BERT with an average
accuracy of 93.5% across all 8 emotions and a gain of 6.5% over single-modality approaches.
The best agreement score of 93.6% has been recorded for the “Neutral” emotion. In comparison,
the “Angry-Disgust” emotion pair has the highest mismatch frequency of 18.4%, highlighting
challenges in their alignment across visual and textual modalities in comics.

Conclusion:
The proposed VisualBERT-based MEM-8X8 framework performs better in classifying
8 emotions, addressing mismatch alignment across visual and textual modalities. This
study lays the foundation for future comics and multimodal emotion recognition analysis advancements.
Improving the Nutritional, Antioxidant, and Sensory Characteristics of Ready-to-use Yellow Sauce Condiments
Authors: Foudjo Brice Ulrich Saha , Nkweda Carole Yankam , Kuagny Ronald Blaise Mouafo , Kansci Germain 
Published: January 2025

Objectives:
The study aimed to improve the nutritional, antioxidant, and sensory attributes of yellow sauce spice blends.

Methods:
A qualitative survey among housewives, traders, and restaurant owners identified commonly used spice blends for yellow sauce recipes. The blend with the highest sensory acceptability index was used as the base for modeling with a Simplex Lattice mixture design. Variables included the nature and proportion of spices, with responses being total phenolic compound content and sensory acceptability index. The resulting formulation was tested for in vitro antioxidant activities (TAC, FRAP, DPPH, and °OH), water and mineral contents (Fe, Cu, P, Mg, and Ca), and physical and functional properties (color, density, water, and oil absorption capacity).

Results:
The survey identified four spice blend recipes, with the most accepted having a sensory acceptability index of 0.7. Optimization produced a blend of 18% Afrostyrax lepi-dophyllus, 8% Piper guineense, 38% Tetrapleura tetraptera, 31% Dichrostachys glometara, and 5% Xylopia aethiopica (Dunal) A. riche. This blend exhibited fairly pleasant acceptabil-ity (index = 0.80) and a phenolic compound content of 1398.69 Eq mg AG/100g of DM. The developed formulation showed higher levels of zinc (19 ppm) and iron (234 ppm), as well as superior Total Antioxidant Capacity (310.04 Eq mg AG/100g DM) and °OH inhibition (75.32 μg/ml) compared to the survey-derived formulation.

Conclusion:
The modeling of the spice blends improved some sensory, antioxidant, and mineral properties, ensuring consistent quality in the yellow sauce condiments.