bluuebunny/crossref_metadata_2025_split huggingface dataset:
Friction Velocity Determination Techniques in Turbulent Boundary Layers with Miniature Vortex Generators
Authors: Kong Jiahao , Nogroho Bagus , Bennetts Luke , Chin Rey , Chan Chi 
Published: January 2024

Abstract

Miniature vortex generators (MVGs) have the potential to control turbulent boundary layers (TBLs). Analyzing the scaled turbulent structure of MVG TBLs in experiments typically requires indirect methods for accurate friction velocity Uτ determination. The established methods for Uτ -determination need to be verified for non-generic TBLs, such as MVG TBLs, especially at near-wake stations. This study compares the performance of the five most common Uτ -determination methods for MVG TBLs. The methods are tuned in terms of their free parameters and fitting ranges using direct measurements of Uτ from large eddy simulation data and applied to a corresponding experiment to assess their accuracy. Based on the findings, a novel “inner” method, which is the Musker function with a drifting buffer layer plus a bump function, is recommended for MVG TBLs of the form investigated, as it provides a good estimation of Uτ with uncertainty < 5% for all streamwise stations. The method is applied to three further experimental tests with different flow conditions to study trends in Uτ. The error of the drag variation is <6%, which indicates the method is reliable for MVG TBLs at high Reynolds numbers.
Optimal Allocations of Wind Turbines in Power Systems Using Artificial Rabbits Optimization Technique
Authors: El-Ela A. A. Abou , Ali M. K. , Nasef A. F. , Amer R. A. 
Published: January 2024

Abstract
Wind Energy Conversion Systems (WECS) is one of the burning research fields these days. Governments encourage researchers and planners to make plans towardincreasing the amount of power generation from renewable energy sources (RES) in the future because conventional energy sources will cause a crisis for the environment. The installationof WECS units can cause an adverse effect if they are notproperly allocated. Therefore, this paper presents the applications of modern optimization techniques such as the artificial rabbit optimization algorithm (ARO), the grey wolfoptimizer (GWO), and particle swarm optimization (PSO) for determining the optimal location and sizing of WECS. The effectiveness of these techniques is demonstrated with IEEE 14-bus and IEEE 30-bus considering various penetration conditions. Also, the effect of wind turbines on system transient performance is investigated using robust non-linear models ofboth synchronous machines and wind turbine generators whenthe system is exposed to a symmetrical three-phase short circuitfault. The results show the ability of the ARO algorithm compared to both GWO and PSO techniques in solving thewind turbine generator (WTG) placement and sizing problem.The result show that ARO-based WTG increases the stability ofthe power system, improves the voltage profile, reduces bothactive and reactive power losses in the systems, and enhances dynamics performance for the overall systems. All the simulations of the system models are carried out using MATLAB/SIMULINK and given in the form of comparative results with a three-phase short circuit, and changes in wind penetration level to show the stability of the system.
Enhanced artificial ecosystem-based optimization for global optimization and constrained engineering problems
Authors: Wang Yunpeng , Zhang Jixiang , Zhang Mengjian , Wang Deguang , Yang Ming 
Published: January 2024

Abstract

Artificial ecosystem-based optimization (AEO) is a nature-inspired intelligent optimization algorithm that has been widely applied to various real-world optimization problems. However, AEO has several limitations, including slow convergence and difficulty in escaping from local optima. To address these drawbacks, this study proposes an enhanced variant of AEO called enhanced artificial ecosystem-based optimization (EAEO). First, Latin hypercube sampling is introduced to achieve uniform population initialization. Then, a quadratic interpolation mechanism is embedded to accelerate convergence and improve accuracy. Finally, an adaptive neighborhood search inspired by animal migration behavior is designed to help to jump out of local optima. The performance of EAEO is evaluated using twenty-three benchmark functions and the CEC2017 test suite. Experimental results indicate that EAEO outperforms the original AEO and other comparison algorithms in terms of accuracy and stability. The proposed EAEO is applied to solve four engineering optimization problems. The results demonstrate the superiority of EAEO in addressing practical problems.
Hemoglobin A1c Level Is Associated With Lymphovascular Space Invasion In Diabetic Endometrial Cancer Patients
Authors: Senkaya Ayse Rabia , Kantarci Sercan , Yildirim Karaca Suna , Sanci Muzaffer 
Published: January 2024

Objective: Our aim in this study is to examine the relationship of hemoglobin A1c (HbA1c) and fasting glucose with the stage, grade and histological type of cancer and its value in predicting the prognosis of endometrial cancer in diabetic endometrial cancer patients.
Study Design: The data of 138 endometrial cancer patients with diabetes who met the study criteria were analyzed. Hemoglobin A1c levels and fasting glucose were compared with cancer stage, grade, histological type, lymphovascular invasion, chemotherapy and radiotherapy data.
Results: A statistically significant difference was found between the groups in terms of HbA1c values only according to the lymphovascular invasion (p=0.02). While there was no significant correlation between endometrial thickness and HbA1c, a low positive correlation was found between the fasting glucose value (r=0.191, p=0.025)
Conclusions: The higher rate of lymphovascular invasion in patients with high HbA1c value alone is insufficient in determining the prognosis when other parameters are considered.
Energy-based hydro-economic modeling of climate change effects on the Upper Euphrates Basin
Authors: Aytac Ayca , Dogan Mustafa Sahin , Tuna M. Cihat 
Published: January 2024

Abstract
Climate change and global warming are expected to affect water resources management and planning, requiring adaptations to changing conditions. Therefore, it is very important, especially for decision-makers, to identify demand deficits due to less water availability with climate change that may occur in the existing water supply system in advance. FEHEM, a hydroeconomic optimization model of the integrated reservoir system of the Upper Euphrates Basin, which is the largest and main basin providing water flow to the Euphrates River, is developed. Using a 45-year historical hydrological dataset, water management and hydroelectric operations are evaluated with a linear programming model at monthly time steps. The effects of climate change on the Upper Euphrates Basin are evaluated under low and high carbon emission scenarios. According to the average of the different climate scenarios studied in the model, the average decrease in flows is 37.5%. With climate change, peak flows will occur about 1–2 months earlier on average. As a result of these hydrological changes, the total amount of energy production in the basin will decrease by about 54% and energy revenue by the same percentage.
Effective degradation of quinoline by catalytic ozonation with MnCexOy catalysts: performance and mechanism
Authors: Zhang Jie , Wu Zhaochang , Dong Ben , Ge Sijie , He Shilong 
Published: January 2024

Abstract

Quinoline inevitably remains in the effluent of coking wastewater treatment plants due to its bio-refractory nature, which might cause unfavorable effects on human and ecological environments. In this study, MnCexOy was consciously synthesized by α-MnO2 doped with Ce3+ (Ce:Mn = 1:10) and employed as the ozonation catalyst for quinoline degradation. After that, the removal efficiency and mechanism of quinoline were systematically analyzed by characterizing the physicochemical properties of MnCexOy, investigating free radicals and monitoring the solution pH. Results indicated that the removal rate of quinoline was greatly improved by the prepared MnCexOy catalyst. Specifically, the removal efficiencies of quinoline could be 93.73, 62.57 and 43.76%, corresponding to MnCexOy, α-MnO2 and single ozonation systems, respectively. The radical scavenging tests demonstrated that •OH and •O2- were the dominant reactive oxygen species in the MnCexOy ozonation system. Meanwhile, the contribution levels of •OH and •O2- to quinoline degradation were about 42 and 35%, respectively. The abundant surface hydroxyl groups and oxygen vacancies of the MnCexOy catalyst were two important factors for decomposing molecular O3 into more •OH and •O2-. This study could provide scientific support for the application of the MnCexOy/O3 system in degrading quinoline in bio-treated coking wastewater.
Organogels: “GelVolution” in Topical Drug Delivery - Present and Beyond
Authors: Nikam Ajinkya Nitin , Roy Amrita , Raychaudhuri Ruchira , Navti Prerana D. , Soman Soji , Kulkarni Sanjay , Shirur Krishnaraj Somayaji , Pandey Abhijeet , Mutalik Srinivas 
Published: January 2024

Abstract:
Topical drug delivery holds immense significance in dermatological treatments due to its non-invasive
nature and direct application to the target site. Organogels, a promising class of topical drug delivery systems,
have acquired substantial attention for enhancing drug delivery efficiency. This review article aims to explore
the advantages of organogels, including enhanced drug solubility, controlled release, improved skin penetration,
non-greasy formulations, and ease of application. The mechanism of organogel permeation into the
skin is discussed, along with formulation strategies, which encompass the selection of gelling agents, cogelling
agents, and additives while considering the influence of temperature and pH on gel formation. Various
types of organogelators and organogels and their properties, such as viscoelasticity, non-birefringence, thermal
stability, and optical clarity, are presented. Moreover, the biomedical applications of organogels in targeting
skin cancer, anti-inflammatory drug delivery, and antifungal drug delivery are discussed. Characterization parameters,
biocompatibility, safety considerations, and future directions in optimizing skin permeation, ensuring
long-term stability, addressing regulatory challenges, and exploring potential combination therapies are
thoroughly examined. Overall, this review highlights the immense potential of organogels in redefining topical
drug delivery and their significant impact on the field of dermatological treatments, thus paving the way for
exciting prospects in the domain.
Overcoming Low Adherence to Chronic Medications by Improving their
Effectiveness using a Personalized Second-generation Digital System
Authors: Bayatra Areej , Nasserat Rima , Ilan Yaron 
Published: January 2024

Introduction:
Low adherence to chronic treatment regimens is a significant barrier to
improving clinical outcomes in patients with chronic diseases. Low adherence is a result of multiple
factors.

Methods:
We review the relevant studies on the prevalence of low adherence and present some
potential solutions.

Results:
This review presents studies on the current measures taken to overcome low adherence,
indicating a need for better methods to deal with this problem. The use of first-generation digital
systems to improve adherence is mainly based on reminding patients to take their medications,
which is one of the reasons they fail to provide a solution for many patients. The establishment
of a second-generation artificial intelligence system, which aims to improve the effectiveness of
chronic drugs, is described.

Conclusion:
Improving clinically meaningful outcome measures and disease parameters may
increase adherence and improve patients' response to therapy.
Recent Advances in Pharmaceutical Design: Unleashing the Potential of
Novel Therapeutics
Authors: Prajapati Ram Narayan , Bhushan Bharat , Singh Kuldeep , Chopra Himansu , Kumar Shivendra , Agrawal Mehak , Pathak Devender , Chanchal Dilip Kumar , Laxmikant  
Published: January 2024

:
Pharmaceutical design has made significant advancements in recent years, leading to
the development of novel therapeutics with unprecedented efficacy and safety profiles. This
review highlights the potential of these innovations to revolutionize healthcare and improve patient
outcomes. The application of cutting-edge technologies like artificial intelligence, machine
learning, and data mining in drug discovery and design has made it easier to find potential drug
candidates. Combining big data and omics has led to the discovery of new therapeutic targets
and personalized medicine strategies. Nanoparticles, liposomes, and microneedles are examples
of advanced drug delivery systems that allow precise control over drug release, better bioavailability,
and targeted delivery to specific tissues or cells. This improves the effectiveness of the
treatment while reducing side effects. Stimuli-responsive materials and smart drug delivery systems
enable drugs to be released on demand when specific internal or external signals are
sent. Biologics and gene therapies are promising approaches in pharmaceutical design, offering
high specificity and potency for treating various diseases like cancer, autoimmune disorders, and
infectious diseases. Gene therapies hold tremendous potential for correcting genetic abnormalities,
with recent breakthroughs demonstrating successful outcomes in inherited disorders and
certain types of cancer. Advancements in nanotechnology and nanomedicine have paved the
way for innovative diagnostic tools and therapeutics, such as nanoparticle-based imaging agents,
targeted drug delivery systems, gene editing technologies, and regenerative medicine strategies.
Finally, the review emphasizes the importance of regulatory considerations, ethical challenges,
and future directions in pharmaceutical design. Regulatory agencies are adapting to the rapid
advancements in the field, ensuring the safety and efficacy of novel therapeutics while fostering
innovation. Ethical considerations regarding the use of emerging technologies, patient privacy,
and access to advanced therapies also require careful attention.
Emerging Therapeutic Approaches Targeting Ferroptosis in Cancer:
Focus on Immunotherapy and Nanotechnology
Authors: Yu Zongchao , Mo Zhongcheng , Qiu Yuan , Lu Hengzhe , Zheng Biao , Liu Longfei 
Published: January 2024

:
Ferroptosis is a newly discovered form of programmed cell death characterized by
iron overload, ROS accumulation, and lipid peroxidation. It is distinguished by unique morphological, biochemical, and genetic features and stands apart from other known regulated cell
death mechanisms. Studies have demonstrated a close association between ferroptosis and various cancers, including liver cancer, lung cancer, renal cell carcinoma, colorectal cancer, pancreatic cancer, and ovarian cancer. Inducing ferroptosis has shown promising results in inhibiting
tumor growth and reversing tumor progression. However, the challenge lies in regulating ferroptosis in vivo due to the scarcity of potent compounds that can activate it. Integrating emerging
biomedical discoveries and technological innovations with conventional therapies is imperative.
Notably, considerable progress has been made in cancer treatment by leveraging immunotherapy
and nanotechnology to trigger ferroptosis. This review explores the relationship between ferroptosis and emerging immunotherapies and nanotechnologies, along with their potential underlying mechanisms, offering valuable insights for developing novel cancer treatment strategies.
Hydrogel Breakthroughs in Biomedicine: Recent Advances and
Implications
Authors: Mittal Ravi K , Mishra Raghav , Uddin Rehan , Sharma Vikram 
Published: January 2024

Objective::
The objective of this review is to present a succinct summary of the latest
advancements in the utilization of hydrogels for diverse biomedical applications, with a particular
focus on their revolutionary impact in augmenting the delivery of drugs, tissue engineering,
along with diagnostic methodologies.

Methods::
Using a meticulous examination of current literary works, this review systematically
scrutinizes the nascent patterns in applying hydrogels for biomedical progress, condensing crucial
discoveries to offer a comprehensive outlook on their ever-changing importance.

Results::
The analysis presents compelling evidence regarding the growing importance of hydrogels
in biomedicine. It highlights their potential to significantly enhance drug delivery accuracy,
redefine tissue engineering strategies, and advance diagnostic techniques. This substantiates their
position as a fundamental element in the progress of modern medicine.

Conclusion::
In summary, the constantly evolving advancement of hydrogel applications in biomedicine
calls for ongoing investigation and resources, given their diverse contributions that can
revolutionize therapeutic approaches and diagnostic methods, thereby paving the way for improved
patient well-being.
The Gut Microbiota and Major Depressive Disorder: Current
Understanding and Novel Therapeutic Strategies
Authors: Bahmani Mohaddeseh , Mehrtabar Saba , Jafarizadeh Ali , Zoghi Sevda , Heravi Fatemah Sadeghpour , Abbasi Amin , Sanaie Sarvin , Rahnemayan Sama , Leylabadlo Hamed Ebrahimzadeh 
Published: January 2024

:
Major depressive disorder (MDD) is a common neuropsychiatric challenge that primarily targets young females. MDD as a global disorder has a multifactorial etiology related to
the environment and genetic background. A balanced gut microbiota is one of the most important environmental factors involved in human physiological health. The interaction of gut
microbiota components and metabolic products with the hypothalamic-pituitary-adrenal system
and immune mediators can reverse depression phenotypes in vulnerable individuals. Therefore,
abnormalities in the quantitative and qualitative structure of the gut microbiota may lead to the
progression of MDD. In this review, we have presented an overview of the bidirectional relationship between gut microbiota and MDD, and the effect of pre-treatments and microbiomebased approaches, such as probiotics, prebiotics, synbiotics, fecal microbiota transplantation,
and a new generation of microbial alternatives, on the improvement of unstable clinical conditions caused by MDD.
In silico Approaches for Exploring the Pharmacological Activities of
Benzimidazole Derivatives: A Comprehensive Review
Authors: Srivastava Manisha , Singh Kuldeep , Kumar Sanjay , Hasan Syed Misbahul , Mujeeb Samar , Kushwaha Shom Prakash , Husen Ali 
Published: January 2024

Background:
This article reviews computational research on benzimidazole derivatives.
Cytotoxicity for all compounds against cancer cell lines was measured and the results revealed that
many compounds exhibited high inhibitions. This research examines the varied pharmacological
properties like anticancer, antibacterial, antioxidant, anti-inflammatory and anticonvulsant activities
of benzimidazole derivatives. The suggested method summarises in silico research for each activity.
This review examines benzimidazole derivative structure-activity relationships and pharmacological
effects. In silico investigations can anticipate structural alterations and their effects on these derivative’s
pharmacological characteristics and efficacy through many computational methods. Molecular
docking, molecular dynamics simulations and virtual screening help anticipate pharmacological
effects and optimize chemical design. These trials will improve lead optimization, target selection,
and ADMET property prediction in drug development. In silico benzimidazole derivative studies
will be assessed for gaps and future research. Prospective studies might include empirical verification,
pharmacodynamic analysis, and computational methodology improvement.

Objectives:
This review discusses benzimidazole derivative in silico research to understand their specific
pharmacological effects. This will help scientists design new drugs and guide future research.

Methods:
Latest, authentic and published reports on various benzimidazole derivatives and their
activities are being thoroughly studied and analyzed.

Result:
The overview of benzimidazole derivatives is more comprehensive, highlighting their
structural diversity, synthetic strategies, mechanisms of action, and the computational tools used to
study them.

Conclusion:
In silico studies help to understand the structure-activity relationship (SAR) of
benzimidazole derivatives. Through meticulous alterations of substituents, ring modifications, and
linker groups, this study identified the structural factors influencing the pharmacological activity of
benzimidazole derivatives. These findings enable the rational design and optimization of more
potent and selective compounds.
Antidepressant Effect of Sodium Butyrate is Accompanied by Brain Epigenetic Modulation in Rats Subjected to Early or Late Life Stress
Authors: Valvassori Samira Silva , Varela Roger Bitencourt , Resende Wilson Rodrigues , Possamai-Della Taise , Borba Laura de Araujo , Behenck João Paulo , Réus Gislaine Zilli , Quevedo João 
Published: January 2024

Background:
Major depression has a complex and multifactorial etiology constituted
by the interaction between genetic and environmental factors in its development.

Objective:
The aim of this study was to evaluate the effects of sodium butyrate (SD) on epigenetic
enzyme alterations in rats subjected to animal models of depression induced by maternal
deprivation (MD) or chronic mild stress (CMS).

Methods:
To induce MD, male Wistar rats were deprived of maternal care during the first
10 days of life. To induce CMS, rats were subjected to the CMS for 40 days. Adult rats were
then treated with daily injections of SD for 7 days. Animals were subjected to the forced swimming
test (FST), and then, histone deacetylase (HDAC), histone acetyltransferase (HAT), and
DNA methyltransferase (DNMT) activities were evaluated in the brain.

Results:
MD and CMS increased immobility time in FST and increased HDAC and DNMT activity
in the animal brains. SD reversed increased immobility induced by both animal models
and the alterations in HDAC and DNMT activities. There was a positive correlation between
enzyme activities and immobility time for both models. HDAC and DNMT activities also presented
a positive correlation between themselves.

Conclusion:
These results suggest that epigenetics can play an important role in major depression
pathophysiology triggered by early or late life stress and its treatment.