bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of STEM Approach to Developing Mathematical Thinking for Calculus Students among Sohar University
Authors: Tashtoush Mohammad A. , Al-Qasimi Aida B. , Shirawia Nawal A. , Rasheed Noha M.
Published: September 2024

This study aims to prepare an educational program based on integrating Science, Technology, Engineering and Mathematics (STEM) to develop students’ mathematical thinking skills. It also aims to provide proposals that could have a major role in rebuilding some of the general features on which mathematics curricula can be built according to the STEM approach. The study used an experimental approach; the study sample consists of 121 students in a Calculus course. The participants were grouped purposefully into 50 control group and 71 experimental group. Results showed that the students in the experimental group who were exposed to the STEM approach surpassed the control group students who studied in the traditional way. Findings also indicated that the educational STEM approach activities had a positive role in the process of learning and searching for various sources of information. Besides, the STEM approach engages students in observation, discovery, interpretation, and discussion; activities that help them solve various issues. The study therefore recommends that students also perform educational STEM based activities in other mathematics courses.
Feodal Kentten Sanayi/Sömürge Kentine: Osmanlı Kentinin Evrimi
Authors: Karaoğlan Burak
Published: September 2024

Kent, üzerinde yaşadığımız, karmaşık insan ilişkilerini konu alan ve çeşitli organizasyonlara ev sahipliği yapan mekânsal bir boyut olarak göze çarpar. Tarihsel süreç içerisinde kentlerin ortaya çıkışı, uygarlıkların ortaya çıkmaya başlamasına paralel olarak ilerlemiştir. Bu süreç içerisinde kentlerin gelişimi, Antik Çağ’dan günümüze kadar hemen her dönemde gündemdeki yerini korumuştur. Buna koşut olarak kente ve kentlere yüklenen anlam zaman içerisinde farklılaşmış ve kentlere büyük önem atfedilmiştir. Çalışmanın temelden özümsenmesi adına öncelikli olarak kentlerin ortaya çıkışı incelenecektir. Sonraki aşamada toplumsal statülerin ve toplumsal kast sisteminin hüküm sürdüğü Feodal kentten yani yerleşik kent kültüründen hareketle; Osmanlı kentlerinin zaman içerisinde hangi boyutlarda değişim ve dönüşüm yaşadığı, bunun akabinde sanayi kentlerinde meydana gelen gelişmeler ve farklılaşmalar neticesinde, Osmanlı kentlerinin geçirdiği evrim ele alınacaktır.
Review of the Influences of Sex Differences on Health and Disease: What Is the Role of Journals?
Authors: Regensteiner Judith G. , Templeton Kimberly
Published: September 2024

➢ Sex-based differences are understudied, which has potential consequences for the health of everyone.

➢ Women’s health is particularly affected given a lack of sex-specific data across many disease states.

➢ Journals do not consistently require the inclusion of both sexes and the disaggregation of data by sex in cell, animal model, and human studies.

➢ Instructions for investigators and journals regarding the inclusion of sex-specific data are found in guidelines such as those by the Sex and Gender Equity in Research (SAGER) group, but these guidelines are underutilized.

➢ Consistency in the inclusion of both sexes in studies (except in studies on diseases affecting only 1 sex), as well as in the disaggregation and reporting of results by sex, has the potential to improve health for all people.
Association of Technology Usage and Decreased Revision TKA Rates for Low-Volume Surgeons Using an Optimal Prosthesis Combination
Authors: McAuliffe Michael , Darwish Ibrahim , Anderson Jon , Nicholls Alex , Corfield Sophie , Harries Dylan , Vertullo Christopher
Published: September 2024

Background:

Technology (navigation and robotics) usage during total knee arthroplasty (TKA) is often supported by literature involving high-volume surgeons and hospitals, but the value of technology for lower-volume surgeons is uncertain. This study aimed to determine if there was a relationship among surgeon volume, technology usage, and revision rate when using an optimal prosthesis combination (OPC).

Methods:

Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) data were obtained from January 1, 2008, to December 31, 2022, for all primary TKA procedures performed for osteoarthritis using an OPC by a known surgeon ≥5 years after their first recorded procedure. The interaction between surgeon volume and conventional-instrumentation (CV) versus technology-assisted (TA) TKA was assessed. The cumulative percent revision (CPR) was determined by Kaplan-Meier estimates. Cox proportional-hazards methods were used to compare rates of revision by surgeon volume and by the interaction of volume and technology. Subanalyses were undertaken to examine major and minor revisions separately, and to assess the influence of technology on revision rates relative to those of a surgeon undertaking 100 TKA/year.

Results:

Of the 53,264 procedures that met the inclusion criteria, 31,536 were TA-TKA and 21,728 were CV-TKA. Use of technology reduced the all-cause revision rate for surgeons with a volume of <50 TKA/year and the rate of minor revisions for surgeons with a volume of <40 TKA/year. No interaction between surgeon volume and the rate of major revision surgery was found. With CV-TKA by a surgeon with a 100-TKA/year volume as the comparator, all-cause and major revision rates were significantly elevated for surgeons undertaking <50 and <100 TKA/year, respectively. In contrast, analysis of TA-TKA showed no difference in rates of all-cause or major revisions for surgeons undertaking <100 TKA/year compared with 100 TKA/year.

Conclusions:

TA-TKA was associated with a decrease in the revision rate for lower-volume surgeons but no significant alterations in revision rate for higher-volume surgeons. Preferential use of TA-TKA by lower-volume surgeons should be considered.

Level of Evidence:

Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.
Sexual Assault: Types and Associated Factors
Authors:   Associate Professor, Department of Forensic Medicine, Dr Chandramma Dayananda Sagar Institute of Medical Education and Research, Harohalli 562112, Karnataka, India,, S.H. Jayanth , Hugar Basappa ,   Professor, Department of Forensic Medicine, MS Ramaiah Medical College, Bangalore 560054, Karnataka, India. India., Chandra Y.P. Girish ,   Professor & HOD, Department of Forensic Medicine, MS Ramaiah Medical College, Bangalore 560054, Karnataka, India. India., S. Praveen ,   Professor, Department of Forensic Medicine, MS Ramaiah Medical College, Bangalore 560054, Karnataka, India. India.
Published: September 2024

BacKground: Sexual assault is a rising medico-legal issue and also an important social problem. Medico-legally sexual violence can be Penetrative sexual assault, Non penetrative Sexual assault and Sexual harassment. Thorough knowledge about manner and traits of sexual assault is vital for forensic examination. Keeping this in view, the study was taken up with the aim of analysing the circumstances and factors associated with sexual assault. MaterIals and Methods: The present prospective cross sectional study was conducted in the Department of Forensic Medicine, M.S. Ramaiah Medical College Bangalore from January 2018 and December 2020. All victims of alleged sexual assault brought for medical examination to the Department of Forensic Medicine were interviewed through a detailed questionnaire after taking consent. results: 82 victims of alleged sexual assault were examined. 80 of them were females and 2 were boys who were less than 12 years. Children and adolescents in the age group of 12-18 years constituted 65.85% of the cases. Penetrative sexual assault (peno-vaginal type) was reported by 62 of the victims (75%). Anal intercourse was alleged in 2.5 % (n=2) of the victims. conclusIon: Peno-vaginal type of sexual assault in the minors less than 18 years is the most common type of sexual assault reported. Health care professionals and others involved in providing care and support in all forms should be thoroughly trained and informed about the current laws. Preventive campaigns and sex education programmes in schools and colleges should be taken up the concerned authorities to create awareness amongst the teenagers.
Indicativos linguísticos para aferir composicionalidade semântica em palavras complexas
Authors: Bassani Indaiá de Santana , Costa Marcela Nunes
Published: September 2024

Este artigo aborda o conceito de composicionalidade semântica aplicado a palavras complexas (especialmente derivadas) e sugere indicativos linguísticos para classificar estruturas morfológicas quanto à composicionalidade. Ao fazê-lo, discute a relação entre composicionalidade semântica, transparência morfológica (formal), significado especial e lexicalização. Embora a composicionalidade semântica seja um conceito cada vez mais evocado na análise morfológica baseada na sintaxe, não há uma proposta ordenada de indicativos dessa propriedade para expressões linguísticas. Com base em dados do português brasileiro, e a fim de orientar a classificação de dados empíricos de palavras morfologicamente complexas, são elencados e discutidos possíveis indicativos obtidos através de testes linguísticos (i.e., transparência formal, formação de paráfrases e usos de sinônimos para raízes e afixos, modificação adverbial ou nominal, manutenção e perda de propriedades (morfo)fonológicas) e eventos psicolinguísticos (i.e., associação de palavras, decisão lexical, lapsos de fala e criações jocosas).
Enhanced EfficientNet Model for Multiclass Brain Tumor Prognostication Using Advanced MR Image Analysis Techniques
Authors: Ghaffar Ayesha , Javid Muhammad Arshad , Arshad Shoaib , Azeem Waqar
Published: September 2024

The prognosis of brain tumor diseases is essential for effective treatment planning and patient management. This study investigates the use of Dense EfficientNet models, specifically an enhanced EfficientNet-B1, for the prognostication of multiclass brain tumor diseases. A dataset comprising 6462 MR images, including T1-W, T2-W, and FLAIR sequences, was classified into four categories: glioma, meningioma, no tumor, and pituitary tumors. The proposed method incorporates advanced data augmentation techniques, image cropping, and pixel resizing to improve training accuracy. Additionally, modifications to the EfficientNet architecture layers and the application of normalization and histogram equalization further enhance model performance.The results indicate that the enhanced EfficientNet-B1 model achieves a superior training accuracy of 98%, outperforming the EfficientNet-B0 model, with the highest accuracy observed in glioma tumor classification. Compared with other CNN architectures, such as ResNet50 and VGG-16, the EfficientNet-B1 model demonstrates higher performance and computational efficiency with fewer parameters.The study concludes that the enhanced EfficientNet-B1 model offers a robust and efficient solution for brain tumor detection and prognostication using MR images. Its innovative modifications and advanced preprocessing techniques significantly contribute to its high performance, making it a valuable tool for developing clinically useful applications for MR image analysis in brain tumor management.
Telehealth and Virtual Supervision Practices for Health Professions Education in the Department of Veterans Affairs
Authors: Harada Nancy , Falco Kimberly , Bowman Marjorie , Byrne John
Published: September 2024

Background: Telehealth and virtual supervision practices in health professions clinical education has grown rapidly, including in the Department of Veterans Affairs (VA) which oversees the largest interprofessional training effort in the United States. Telehealth is the provision of healthcare that is provided remotely through telecommunication technology, and virtual supervision is clinical supervision of health professions trainees (HPTs) that occurs through telecommunication technology. In this study we evaluate participation in telehealth and virtual supervision for physician, nursing, and associated health HPTs, and describe prevalent themes concerning HPT perceptions of telehealth and virtual supervision.
Methods: The survey study cohort included 10,865 HPTs that responded to the 2023 VA Trainee Satisfaction Survey. Descriptive and bivariate analyses were conducted to evaluate participation rates by profession. Responses to the open-ended question within the survey were coded and summarized using rapid qualitative analysis methods.
Results: Participation rates for telehealth and virtual supervision were associated health HPTs (47.2% telehealth, 33.8% virtual supervision), physician residents (31.1% telehealth, 21.5% virtual supervision), and nursing HPTs (22.9% telehealth, 21.5% virtual supervision) (p<.001). HPTs of all professions expressed positive views on their experiences, with profession-specific differences noted in location, frequency and depth of these practices.
Conclusions: Participation in telehealth and virtual supervision was common and well received by HPTs across multiple professions in VA. HPT responses suggest additional efforts are needed to refine profession-specific instructional methods tailored for defined educational needs and goals.
The complete chloroplast genome of three Syzygium species (Myrtaceae) and their phylogenetic relationships
Authors: Quang Minh Trong , Pham Thanh Phuc , Nguyen Danh Hoang
Published: September 2024

Syzygium cinereum (Kurz) Chantar. & J.Parn. (1993), Syzygium cumini (L.) Skeels (1912), and Syzygium grande (Wight) Walp. (1843) have different usages by humans as foods or medicines in the Southeast Asia regions. In this study, we assembled and characterized the complete chloroplast (cp) genome of three Syzygium species. The complete cp genomes of S. cinereum, S. cumini and S. grande were 158,956 bp, 158,448 bp, and 159,061 bp in length, respectively, with the overall GC content of 37.0%. All three Syzygium cp genomes consisted of 130 genes in total (including 85 protein-coding genes, 37 transfer RNA genes, and 8 ribosomal RNA genes). A phylogenetic tree based on cp protein-coding regions revealed the monophyly of Syzygium species and provided valuable insights into the phylogenetic relationships of three of our Syzygium species with other Myrtaceae species. The sequencing of this cp stands to expedite the development of molecular markers and significantly contribute to genetic research involving this distinctive plant.
Nitrogen-Doped Graphene Quantum Dots for Enhanced Oil Recovery: The Effects of Precursor Type, Molar Ratio, and Synthesis Duration on Interfacial Tension Reduction
Authors: Gholamzadeh Younes , Hemmati-Sarapardeh Abdolhossein , Sharifi Mohammad
Published: September 2024

Nanofluids have the capacity to reduce interfacial tension (IFT) of crude oil and water for enhanced oil recovery (EOR) operations, but traditional nanoparticles are limited in tight reservoirs due to their inappropriate size for micro-nano pores and their tendency to aggregate. In this paper, Graphene Quantum Dots (GQDs) with simple and favorable properties are developed, and their performance and mechanism for reducing IFT are evaluated. The paper also aims to explore the effects of GQD precursor type, synthesis duration, and molar percentages of precursors on reducing IFT. For this purpose, citric acid was used as a carbon source, and ethylenediamine, urea, and thiourea were used as nitrogen sources to synthesize different GQDs. FTIR, XPS, HR-TEM, XRD, UV visible, and PL photoluminescence were used to identify the GQDs' characteristics. The highest IFT reduction value is achieved by using 1000 ppm ethylenediamine-derived GQDs, which reduces the IFT from 19.03 to 0.70 mN/m at 200000 ppm NaCl concentrations without using any surfactants. The XPS analysis revealed that ethylenediamine-derived GQDs exhibit higher pyrrolic nitrogen content and a relative intensity ratio of sp3 C/sp2 C. It has been identified that the presence of more polar atomic bonds on the surfaces of GQDs decreases the ability of GQDs to reduce IFT. In this way, urea-derived and thiourea-derived GQDs exhibit less capability for IFT reductions from 19.03 to 12.33 and 18.04 mN/m at 1000 ppm GQDs and 200000 ppm NaCl concentration, respectively. Furthermore, ethylenediamine-derived and urea-derived GQDs perform optimally at approximately 5 and 10 hours, respectively, with a precursor molar ratio of 3 (mole ethylenediamine/urea per mole citric acid), while thiourea-derived GQDs show no significant IFT change with varying synthesis times or precursor molar ratio. The developed GQDs provide a promising solution for EOR operations in unconventional reservoirs by significantly decreasing the IFT between crude oil and nanofluids.
Broadband surface enhanced infrared absorption with multiple Fano resonance by metallic oblique-wire-bundle metamaterial absorbers
Authors: Lee Hsueh-Shun , Kuang Yu-Ping , Lu Cheng-Yu , Yen Ta-Jen , Huang Tsung-Yu
Published: September 2024

Higher sensitivity with specific recognition of a sensor could ease the burden of sample purification or labelling procedure for specific testing and detection and there appear two methods including surface enhanced infrared absorption (SEIRA) and surface enhanced Raman scattering (SERS), promising better sensitivity and specificity, simultaneously, via detection of molecular footprints. Furthermore, researchers employ Fano resonance to further boost the detection limit of SEIRA by coupling between the two absorption bands from molecules and metamaterials. Still, the current metamaterial absorbers are almost narrow band and required specific design, only suitable for limited chemicals. Thus, in this work, we would like to design a broadband oblique-wire-bundle (OWB) metamaterial absorbers (MA) which could interact with multiple functional groups’ absorption from a sample, thus easing the burden of custom-made resonators. In experiments, indeed, our designed OWB MA developed four Fano resonance responses with three PMMAs’ functional groups and one function group from carbon dioxide. The counterpart planar MA also performed SEIRA yet without occurrence of Fano resonance as a comparison. We believe this proposed OWB MA could facilitate the development of rapid detection in the field of food safety and chemical detection.
Evolutionary trajectories of venomous fish: complete mitogenomes of Paracentropogon rubripinnis and Inimicus japonicus reshape Scorpaeniformes phylogeny
Authors: Lee Sung-Gwon , Kim Seongmin , Park Chungoo
Published: September 2024

The Scorpaeniformes order encompasses a diverse array of teleost fish, including commercially important and venomous species. Fish venoms offer significant pharmacological potential, but incomplete phylogenetic understanding has hindered research. Resolving relationships among venomous fish families is crucial for studying venom evolution and discovering novel bioactive compounds. To address these phylogenetic uncertainties, we generated and assembled the complete mitochondrial genomes of Paracentropogon rubripinnis (Tetrarogidae) and Inimicus japonicus (Synanceiidae), two representative venomous species. The circular mitogenomes, 16,465 bp and 16,676 bp in length, respectively, contain the typical vertebrate mitochondrial gene complement. Comparative analyses revealed a highly conserved gene order and orientation across Scorpaeniformes, with slight variations in the Notothenioidei outgroups. We identified novel conserved sequence blocks in the control regions and characterized structural features of protein-coding genes, tRNAs, and non-coding elements. Phylogenetic analyses using 13 mitochondrial protein-coding genes from 71 Scorpaeniformes and three outgroup species provided a higher-resolution phylogeny of the order, including 12 families and 31 genera. Our results support the monophyly of Tetrarogidae and Synanceiidae, placing them at the base of the Scorpaeniformes phylogeny. This study provides new insights into Scorpaeniformes evolution, particularly regarding venomous fish families, and lays a foundation for future research on fish venom evolution and applications.
A Novel Multifunctional Chiral Metasurface With Asymmetric Transmission
Authors: Noman Muhammad , Abutarboush Hattan , Tahir Farooq Ahmad , Zahid Adnan , Imran Muhammad , Abbasi Qammer H.
Published: September 2024

The multiband, multifunctional chiral metasurface with asymmetric transmission exhibits significant potential for diverse applications in modern communication systems, ranging from enhanced signal modulation and polarization control to advanced beam steering and compact antenna design. This research presents a versatile and advanced chiral metasurface operating at multiple bands with diverse functionalities, including asymmetric transmission. The proposed metasurface effectively transforms an incoming Linearly Polarized (LP) wave into a Circularly Polarized (CP) wave. Additionally, it functions as a 90° polarization rotator for the incident LP wave. The design starts with an element of a 2 × 2 supercell comprising a Square Split Ring Resonator (SSRR) and an I-shaped resonator. The right diagonal elements of a supercell undergo scaling down, giving rise to a rotational asymmetry. Chirality is introduced into the design, and cross polarization conversion is enhanced by rotating all four elements by 90° relative to each other. On the back side of the substrate, each element undergoes a 90° rotation compared to its counterpart on the front side, realizing the asymmetric transmission feature. The incorporation of multiband and multifunctional features within a single supercell equips the subject chiral metasurface to be utilized in various engineering applications.
A Novel Wavelet-Based Model For Android Malware Detection Utilizing System Calls Features
Authors: CHHAYBI Akram , LAZAAR Saiida
Published: September 2024

Security is a significant concern in the realm of Android platforms, given the ability to allow installations from unverified sources exposing devices to possible malware infiltration and malicious attacks. Malware classification remains a challenging task in the field of mobile malware detection, where dynamic analysis plays a central role in intrusion detection systems (IDS). This process aims real-time examination of application behavior enabling extraction of dynamic patterns exhibited by malware. System calls, provided by the device’s operating system and accessible from user applications, are deployed in machine learning methods for malware detection. The performance of machine learning-based detection algorithms requires improving the feature selection within system calls. This work suggests an original approach based on wavelets to enhance detection of a wide spectrum of Android malwares, such as adware, riskware, banking and SMS. The present methodology uses the Chi-Square test for feature selection, and Haar wavelet for converting selected attributes into wavelet coefficients. In our experiments, we use several machine-learning classifiers such as Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF), and Neural Network (NN). To assess the performance of these classifiers, we employ evaluation metrics in terms of Accuracy, Recall, F-Score, and Precision. Among the selected classifiers, the Random Forest model coupled with wavelet feature selection provided the highest performance, achieving an accuracy rate of 99.99%. The results clearly demonstrate the effectiveness of our proposed model.
Incorporating additive genetic effects and full LD information to discover genome-level gene-environment interactions with summary statistics of complex traits
Authors: Dong Zihan , Jiang Wei , Shen Jiangnan , Li Hongyu , DeWan Andrew , Zhao Hongyu
Published: September 2024

Uncovering environmental factors interacting with genetic factors to influence complex traits is important in genetic epidemiology and disease etiology. Existing methods examining gene-environment (G\(\:\times\:\)E) interactions either test G\(\:\times\:\)E interaction for each genetic variant individually, ignoring correlations with additive genetic effects, or use only partial information of the Linkage Disequilibrium (LD), leading to potential loss of statistical power to uncover interacting factors. In this paper, we introduce BiVariate Linkage-Disequilibrium Eigenvalue Regression for Gene-Environment interactions (BV-LDER-GE), a novel statistical method that detects the overall contributions of G\(\:\times\:\)E interactions in the genome using summary statistics of complex traits. BV-LDER-GE harnesses both correlations with additive genetic effects and full LD information to enhance the statistical power to detect genome-scale G\(\:\times\:\)E interactions. Extensive simulations demonstrate that the BV-LDER-GE is more powerful than existing methods while the type-I error rate is well-controlled. When examining 151 environmental covariate-phenotype (E-Y) pairs from the UK Biobank data, BV-LDER-GE identified 28 (80%) more statistically significant interacting environmental covariate phenotype pairs (E-Y pairs) than existing methods.
Hepatitis B and Hepatitis C Mortality in a Local Health Jurisdiction, Alameda County, CA 2005- 2022
Authors: Taye Beimnet F. , Chitnis Amit S. , Yette Emily , Beyers Matt , Wong Robert J. , Dunne Eileen F.
Published: September 2024

Background: Local data to characterize Hepatitis B Virus (HBV) and Hepatitis C Virus (HCV) mortality supports targeted use of public health resources.
Aims:To assess HBV and HCV mortality in Alameda County to guide elimination efforts.
Methods: Cross-sectional analysis of data from California’s Integrated Vital Records System, 2005–2022, consisting of Alameda County residents who died in California with International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes specific to HBV, HCV, or both listed as a cause of death. Main outcome measures were HBV and HCV death counts; crude mortality rates; and 2013–2022 Average Annual Percent Changes (AAPC) of HCV age-adjusted mortality rate by sex, race/ethnicity, and census tract Healthy Places Index (HPI) quartile.
Results: A total of 2165 HBV and HCV deaths were identified in Alameda County from 2005–2022 (313 HBV, 1809 HCV, 43 co-infected deaths). Most (73.2%) HBV decedents were Asian and/or born outside the United States (78.9%). Age-adjusted HCV mortality rates decreased for all groups from 2013–2022. African American/Black and Hispanic/Latinx residents had smaller percent decreases in HCV mortality than Asian residents (AAPC difference: 6.6% [0.4%,12.9%]; P=0.04 and 9.3% [3.5%,15.1%]; P=0.002). HPI quartile 1 (least advantaged) had a smaller percent decrease in HCV mortality than quartile 4 (AAPC difference: 8.3% [3.6%,12.9%]; P=0.01).
Conclusions: We identified disparities in the burden of HBV deaths and the declines in HCV deaths in Alameda County. Focused efforts to expand viral hepatitis screening, vaccination, and treatment in specific populations are needed to close these gaps and reach elimination targets.
Autonomous navigation with minimal sensors in dynamic warehouse environments: a multi-agent reinforcement learning approach with curriculum learning enhancement
Authors: Shen Zhilong , Chi Yongwei , Bai Yu , Liao Xiaojing , Zhao Peiyu , Lu Jianjiang , Niu Qian , Dai Qinya
Published: September 2024

This paper introduces an innovative approach to augmenting the capabilities of autonomous mobile robots (AMRs) in dynamic, multi-agent warehouse environments. We propose an integrated system that combines Multi-Agent Deep Deterministic Policy Gradient (MADDPG) a cutting-edge multi-agent reinforcement learning (MARL) algorithm with Curriculum Learning (CL). This hybrid method is specifically tailored to meet the complex demands of warehouse operations. Our approach is distinguished by the development of decentralized policies within a centralized training framework, progressively incorporating complexity through a carefully structured curriculum. This strategy enables autonomous agents to master sophisticated navigation and coordination tactics, adapting adeptly to the variable requirements of real-time warehouse scenarios. Through comprehensive experiments, we demonstrate significant enhancements in autonomous decision-making and operational efficiency, thereby validating the effectiveness of merging MARL with CL in intricate, multi-agent contexts. Our findings align with recent advancements in MARL applications for robotics 1 and underscore the potential of curriculum-based learning strategies in complex environments.
Enhancing Quantum Machine Learning: The Power of Non-Linear OpticalReproducing Kernels
Authors: Dehdashti Shahram , Tiwari Prayag , Safty Kareem H. El , Bruza Peter , Nötzel Janis
Published: September 2024

Amidst the array of quantum machine learning algorithms, the quantum kernel method has emerged as a focal point, primarily owing to its compatibility with noisy intermediate-scale quantum devices and its promise to achieve quantum advantage. This method operates by nonlinearly transforming data into feature space constructed with quantum states, enabling classification and regression tasks. In this study, we present a novel feature space constructed using Kerr coherent states, which generalize su(2), su(1,1) coherent states, and squeezed states. Notably, the feature space exhibits constant curvature, comprising both spherical and hyperbolic geometries, depending on the sign of the Kerr parameter. Remarkably, the physical parameters associated with the coherent states, enable control over the curvature of the feature space. Our study employs Kerr kernels derived from encoding data into the phase and amplitude of Kerr coherent states. We analyze various datasets ranging from Moon to breast cancer diagnostics. Our findings demonstrate the robustness of Kerr coherent states, attributed to their flexibility in accommodating different hyperparameters, thereby offering superior performance across noisy datasets and hardware setups.
Tick repellent activities of supercritical fluid extract from Perilla frutescens against Haemaphysalis longicornis
Authors: Jang Young Su
Published: September 2024

Supercritical fluid extraction (SFE) is a rapid, selective, and convenient method for sample preparation prior to the analysis of compounds in a volatile product of plant matrices. In this study, insecticidal activity and repellency were examined in a laboratory study to determine the active constituent of Perilla frutescens and a supercritical fluid extract from Perilla frutescens against hard tick Haemaphysalis longicornis. The repellency of P. frutescens oil extract was evaluated in comparison with two commercial repellents (Icaridin and DEET) against H. longicornis. Filter-paper diffusion assay revealed that P. frutescens oil (3.2 µg/cm2) had a 100% repellency and icaridine (3.2 µg/cm2) had a 96.1% repellency at 120 min. Repellencies of 4 compounds and microcapsule P. frutescens of against H. longicornis were compared with the repellency of Icaridine and DEET at 3.2 µg/cm2. Responses varied according to the test compound and exposure time. Repellencies of Perillaldehyde and microcapsule P. frutescens were 100% at 30 min post-treatment. P. frutescens oil merit further study as potential fumigants or lead compounds for the control of H. longicornis.
Spiral Polycyclic Aromatic Hydrocarbons Embedded in the B/N Center for Constructing Highly Efficient Multiple Resonance TADF Emitters
Authors: Ge Ziyi , Wu Lin , Liu Chunyu , Liu Denghui , Li Deli , Li We , Zhang Jiasen , Mu Xilin , Wang Zhiheng , Liu Di , Zhou Yubo , Wu Siyao , Su Shi-Jian
Published: September 2024

Introducing spiral polycyclic aromatic hydrocarbons (PAHs) in multiple resonances thermally activated delayed fluorescence (MR-TADF) emitters to achieve small FWHM values and high efficiency remains a formidable challenge. This research departs from the conventional molecular design strategy that utilizes spiral PAHs solely as side chains, terminal groups, or linkage units. Instead, we integrate the rigid 9,9'-spirobi[fluorene] (SF) unit fully or partially into the boron/ nitrogen MR (B/N-MR) emitting core and successfully developed a range of brand-new proof-of-concept isomerized MR-TADF emitters, SF-BN1, SF-BN2, SF-BN3, and SF-BN4. Remarkably, these novel emitters exhibit exceptionally narrow full-width at half-maximum (FWHM) values of 15～21 nm in dilute toluene solutions and high photoluminescence quantum yields (PLQYs) of up to 90% in doped films. The corresponding organic light-emitting diode (OLED) based on SF-BN1 achieved high external quantum efficiency (EQE) of up to 29.0%, with CIE coordinates of (0.13, 0.08), closely aligning with the BT.2020 blue emission standard. Sky-blue OLEDs based on SF-BN3 can achieve a high EQE of 29.8%, with an exceptionally highly narrow FWHM value of 18 nm; the hyperfluorescent OLEDs based on SF-BN3 improved the EQE of 35.5%. Moreover, we elucidated subtlevariations in the connectivity of chemical functional groups within emitters, as well as the polar environment and doping concentrations of OLEDs, which can significantly impact the optical and electroluminescent properties of these isomers. This research unveils new opportunities for exploration and yields potential novel luminescent materials suitable for ultra-high-definition (UHD) display technologies.
Neural dynamics of perceived agreement and disagreement with peer and expert opinions: An MEG study
Authors: Irani Fatemeh , Lyyra Pessi , Muotka Joona , Maunula Sini , Parviainen Tiina , Hytönen Kaisa , Monto Simo
Published: September 2024

Individuals change their opinions under the influence of others' opinions; however, the extent and nature of this influence critically depend on their attitudes toward those exerting the influence. In this study, we compare two sources of influence that drive conformity behavior: an expert group, and a peer group. Furthermore, we investigate the underlying neural dynamics using magnetoencephalography to determine whether the processing of these two influences shares their neural mechanisms. Twenty-two participants performed a task in a fashion choice context and received feedback from a peer and an expert group. When participants re-evaluated the clothing after a delay, we found that participants' opinions changed in line with disagreement feedback when feedback was lower than the participant's first rating – without distinct conformity to the social sources. On the neural level, however, there was a difference between conflict with peer and expert groups, with a stronger response for peers in 170–590 ms time window in gradiometer channels. Furthermore, agreement evoked stronger neural responses than conflict, in 590–960 ms time window in magnetometer channels. Taken together, our findings suggest that conflicting feedback from peers and experts regarding clothing preferences elicits distinct temporal dynamics. However, conformity behavior is influenced solely by the feedback valence.
Enhancing PID Control Robustness in CSTRs: A Hybrid Approach to Tuning Under External Disturbances with GA, PSO, and Machine Learning
Authors: AJlouni Naim , Osyavas Adem , Ajlouni Firas , Almassri Abdelrahman , Takaoglu Faruk , Takaoglu Mustafa
Published: September 2024

The optimization of PID controllers for Continuous Stirred Tank Reactors (CSTRs) is critical for ensuring stable and efficient chemical processing under varying operational conditions and external disturbances. This study presents a novel approach that integrates advanced tuning techniques, including Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and their hybrid combinations with a Machine Learning (ML) surrogate model, to improve PID controller performance in disturbed environments. A unique evolutionary framework is employed, where populations of both controllers and plants are co-evolved to handle the most challenging plant models. An adversarial testing approach is utilized to evaluate the best-tuned controller against the four most difficult CSTR plants, with disturbances such as feed concentration and temperature fluctuations. The results demonstrate that both GA and PSO, when enhanced with the ML surrogate model, effectively tune PID controllers to manage disturbances, with the GA tuned controller achieving faster convergence and the PSO tuned controller showing greater robustness. Additionally, the hybrid ML surrogate model significantly improved control performance and disturbance rejection. The findings highlight the ability of the ML_GA and ML_PSO controllers to maintain stability and accuracy across a range of challenging conditions, providing a robust solution for optimizing control systems in nonlinear dynamic environments. This research contributes to the field of process control, showcasing the potential of combining evolutionary algorithms with machine learning surrogate models for adaptive, resilient control strategies in complex chemical systems.
Pollution load and dynamics of phytoplankton communities in relation to environment variables in Lake Babogay, Ethiopia
Authors: Hiruy Andualem Mekonnen , Yibel Zeleke Balew , Alehegne Kassahun Atalay , Endalew Yirgalem Esuneh
Published: September 2024

The objective of this study was to investigate the water quality of Lake Babogaya in Ethiopia. Water samples were collected from six different sites, and analyzed for total coliform (TC), fecal coliforms (FC), and Escherichia coli (E.coli) content. Additionally, potential of hydrogen (pH), dissolved oxygen (DO), total dissolved solids (TDS), electrical conductivity (EC), and Secchi depth were measured. Nutrients and heavy metals were determined using standard methods. The abundance of phytoplankton was estimated by calculating the biovolume of the species. The results indicated that pH, TDS, DO, and turbidity ranged from 8.78 + 0.31 to 9.52 + 0.04, 129 + 4 to 419 + 3 ppm, 5.50 to 7.25 mg/l, and 0.96 to 17.29 NTU, respectively. TC bacteria exceeded the World Health Organization (WHO) standards at all sites, while FC levels exceeded in most samples. Cadmium and chromium were low in both seasons, whereas lead in the dry season exceeded the WHO limits. The levels of iron were high across all sites in the dry season and low in most sites in the wet season. Five major taxonomic phytoplankton groups were identified, comprising a total of 31 species with highest richness of green algae, blue-green algae, and diatoms species.
State-of-Art on the Synthesis of Heterocyclic Compounds Targeting SARS-CoV-2
Authors: Morais Pedro Alves Bezerra , Silva Jessica Adalgisa Barbosa , Javarini Clara Lirian , de Souza Fontes Gaspari Caroline , Bottocim Ramon Ramires Trancoso , Valim Thays Cardoso , Francisco Carla Santana , Neto Alvaro Cunha , Junior Valdemar Lacerda
Published: September 2024

The Corona virus disease-19 (COVID-19) pandemic challenged the scientific
community in the search for developing effective treatments, such as medicine and/or a
vaccine candidate. The SARS-CoV-2 virus and its variants, Omega, Omicron, and Delta,
remain as a major threat to human health, causing significant morbidity and mortality
worldwide. Given that computational methods are thought to be quick, easy, and inexpensive,
they have been widely used in this scenario to design new anti-COVID-19 drug candidates.
In addition, heterocyclic scaffolds have been explored exhaustively for their biological
properties and as fruitful sources of new molecular entities to fulfill the chemical space
available.In light of this, we intend to highlight the synthetic techniques used to produce
novel heterocyclic derivatives that may serve as effective anti-COVID-19 lead candidates
by focusing on important viral proteins and using computational tools. Then, the objective of this article, with a
theoretical nature, is to contribute to the delimitation of organic chemistry methods to achieve new anti-
COVID-19 agents.
Dysbiosis and Regulation of Gut Microbiota in Type 2 Diabetes Mellitus
Authors: Minakshi  , Kumari Hemlata , Prakash Shaurya , Kumar Antresh
Published: September 2024

Type 2 diabetes mellitus is a serious metabolic disease having a high growth rate and
becoming a global threat. An unhealthy lifestyle, food intake, and genetic susceptibility are the
major factors responsible for this metabolic disorder. This disease results in hyperlipidemia,
hyperglycemia, glucose intolerance, restricted insulin synthesis, and insulin resistance. Despite a
variety of treatments currently available, cases of diabetes and resulting complications are on the
rise. One promising approach to diabetes focuses on gut microflora and their associated metabolites.
Gut microbiota has attracted widespread attention due to its crucial role in disease pathophysiology.
This study explores the dysbiosis in the human gut microflora in Type 2 Diabetes
Mellitus and how the gut microbiota influences metabolites related to T2DM. It also sheds light
on early identification and targeted intervention for this. Understanding these mechanisms
could potentially lead to more effective strategies for managing and preventing T2DM. The
findings of our literature study are that gut microbiota can serve as biomarkers for early disease
detection. Finally, we also highlight gut microecological therapeutic strategies focused on
shaping the gut flora to emphasize the improvement of T2DM progression.
Therapeutic Potental of Quinolin-2H-one Hybrids as Anticancer Agents
Authors: Soniya Naik , Soumya Vasu , Shivlingrao Mamle Desai , M. Manickavasagam , Meeramol Chellappan
Published: September 2024

The statistical data related to cancer in recent years has shown a great increase in the
number of cases and is likely to further increase in the future. Even after seeking thorough
knowledge on the aetiology of cancer and related disorders and attempting to cure it by various
methods like gene therapy, T cell therapy, chemotherapy, surgery, hormone therapy, and photodynamic
therapy, there has always been disappointment concerning the survival rate. Hence, there is
still a great urge for the discovery of novel drugs for the treatment of cancer. Chemotherapy being
one of the widely used methods, several drug entities possessing anticancer properties are already in
the market but none of them is known to show good efficacy which necessitates researchers to design
newer drugs for the treatment of cancer. The urge to synthesize novel anticancer entities directed
researchers towards molecular hybridization as one of the novel methods for designing newer
drugs. Literature reveals wide research carried out on quinolin-2-one hybrids, possessing anticancer
properties through different mechanisms. Tipifarnib and Dovitinib are quinolin-2-one hybrids used
to treat cancer, possessing imidazole and benzimidazole heterocyclic rings. Different heterocyclic
scaffolds such as pyrone, pyrrole, pyrimidine, pyridine, thiazole, and pyrazole in combination with
heterocyclic quinolin-2-one have shown high potential to become lead for newer anticancer agents
with better and wider therapeutic properties and lesser side effects. The current review presents information
on the different quinolin-2-one hybrids and their effect on different cancer cell lines. It
also imparts knowledge of the structural requirements for designing novel anticancer agents.
Exploring the Therapeutic Potential of Glycyrrhiza Compounds in Alzheimer's Disease: A Comprehensive Review
Authors: Song Xiaona , Wang Xiaotang , Gao Yao , Xu Guoqiang , Yan Xiaoru , Chen Zhaoyang , Song Guohua
Published: September 2024

Alzheimer's disease (AD) is a progressive neurodegenerative disorder. Research shows
that the development of AD is linked to neuroinflammation, endoplasmic reticulum stress, mitochondrial
dysfunction, cell death, and abnormal cholinergic signaling. Glycyrrhiza compounds contain
active ingredients and extracts that offer multiple benefits, including targeting various pathways, high
efficacy with low toxicity, and long-lasting therapeutic effects. These benefits highlight the significant
potential of Glycyrrhiza compounds for preventing and treating AD. This review summarizes
recent advancements in Glycyrrhiza compounds for preventing and treating AD. It focuses on their
inhibitory effects on key signaling pathways, such as Toll-like receptor 4 (TLR4), nuclear factor-κB
(NF-κB), mitogen-activated protein kinase (MAPK), and cholinergic signaling. This study aims to
establish a scientific framework for using Glycyrrhiza compounds in the clinical prevention and
treatment of AD and to support the development of new therapeutic interventions.
Examination of Triazolinedione-Derived Dihydropyrrole Hybrid Compounds: ER Stress-Related Apoptosis in Breast Cancer Cells, Molecular Docking, and ADMET Analysis
Authors: Mesci Seda , Ayar Arif , Yazgan Burak , Gül Melek , Yıldırım Tuba
Published: September 2024

In many types of cancer, uncontrolled growth and proliferation of cells
occur due to abnormalities in their genes, mutations of pro-apoptotic proteins, or upregulation of
anti-apoptotic proteins. Triazolinedione and pyrrole derivatives are compounds with anti-microbial,
anti-fungal, anti-inflammatory, and anti-cancer activities. Pyrrole and its derivatives are critical
heterocycle compounds that are significant in anticancer studies and highly preferred in research.

Objective:

This study aimed to investigate the effects of dihydropyrrole derivatives substituted with
triazolinedione on the MCF-7 (breast cancer) cell line’s apoptosis, ER stress, and heat shock genes.

Methods:

The mRNA levels of apoptosis, ER stress, and heat shock proteins were assessed by
qRT-PCR method in the MCF-7 cell line. The investigation of ADMET features, crucial pharmacokinetic
indices for the potential candidacy of compounds as drugs, has been meticulously designed.
In silico-induced molecular docking studies were conducted to further explore the interaction
and elucidate the orientation of hybrid compounds within the active sites of BCL-2, PARP,
HSP70, HSP90, and GRP78.

Results:

It was determined that the compounds caused cell death by modulating apoptotic (compound
IV), ER stress, and heat shock proteins (compounds XI and XVI) through up- and downregulation.
Our findings have pointed to the effects of triazolinedione-substituted dihydropyrrole
derivatives, exhibiting antitumor activity on apoptosis, ER stress, and heat shock genes in the MCF-
7 cell line.

Conclusion:

The compounds investigated in this study have been found to be promising for anticancer
research.
Development and Validation of an Eco-Friendly Liquid Chromatography- Tandem Mass Spectrometry Method for Rapid Quantification of Γ-Aminobutyric Acid in Cordyceps sinensis and its Related Species
Authors: Wang Wenhao , Lei Qinggui , Wang Chuanxi , Huang Qi , Qian Zhengming
Published: September 2024

Introduction:

Cordyceps sinensis, a renowned traditional Chinese medicinal substance,
contains pharmacologically beneficial compounds, including γ-aminobutyric acid (GABA), necessitating
efficient analytical methods for quality assessment. This study aims to develop a rapid,
cost-effective, and eco-friendly liquid chromatography-tandem mass spectrometry (LC–MS/MS)
method for GABA quantification in Cordyceps sinensis and its related species. The objective is to
enhance the quality control standards within the Cordyceps sinensis industry and for those of its related
species.

Methods:

The study innovated a swift analytical procedure. Optimal conditions were determined
through systematic evaluations of extraction solvents, durations, and chromatographic settings, prioritizing
speed and solvent minimization.

Results:

The proposed LC–MS/MS method achieved precise quantification of GABA in a reduced
time frame and significantly lowered solvent consumption, enhancing method efficiency by 22-fold
compared to reported LC methods. The method exhibited robustness and scored the highest blue
applicability grade index score, underscoring its suitability for academic and industrial applicaition.

Conclusion:

The validated LC–MS/MS approach offers a sustainable avenue for the rapid and accurate
measurement of GABA in Cordyceps sinensis and its related species, improving the quality
control process and ensuring product authenticity. This method stands out as a model for green analytical
chemistry, propelling forward the eco-friendly analytical evaluation of health-related compounds.