bluuebunny/crossref_metadata_2025 huggingface dataset:
Perfusate Liver Arginase 1 Levels After End-ischemic Machine Perfusion Are Associated With Early Allograft DysfunctionPerfusate Liver Arginase 1 Levels After End-ischemic Machine Perfusion Are Associated With Early Allograft Dysfunction
Authors: Basta Giuseppina , Babboni Serena , Pezzati Daniele , Del Turco Serena , Balzano Emanuele , Catalano Gabriele , Russo Lara , Tincani Giovanni , Carrai Paola , Petruccelli Stefania , Bronzoni Jessica , Martinelli Caterina , Palladino Simona , Trizzino Arianna , Petagna Lorenzo , Romagnoli Renato , Patrono Damiano , Biancofiore Gianni , Peris Adriano , Lazzeri Chiara , Ghinolfi Davide
Published: November 2024

The rising use of liver grafts from donation after circulatory death (DCD) has been enabled by advances in normothermic regional perfusion (NRP) and machine perfusion (MP) technologies. Our study aimed to identify predictive biomarkers in DCD liver grafts subjected to NRP, followed by randomization to either normothermic machine perfusion (NMP) or dual hypothermic oxygenated perfusion (D-HOPE). Among 57 DCD donors, 32 liver grafts were transplanted, and recipients were monitored for one week after transplantation. Biomarkers linked with oxidative stress, hepatic injury, mitochondrial dysfunction, inflammation, regeneration, and autophagy gene expression were measured during NRP, end-ischemic MP, and one week post-transplant.
Arginase-1(ARG-1) levels were consistently higher in discarded grafts and recipients who later developed early allograft dysfunction (EAD). Specifically, ARG-1 levels at the end of ex-situ machine perfusion correlated significantly with other markers of hepatic injury. Receiver Operating Characteristic analysis indicated that ARG-1 at the end of MP had good predictive accuracy for EAD (AUC = 0.713 [95% CI: 0.538-1]; p = 0.02).
Additionally, lipid peroxidation, measured by TBARS, was elevated at the start of NRP but declined over time, with higher levels in D-HOPE than in NMP, suggesting a more sustained oxidative environment. Metabolites like Flavin mononucleotide (FMN) and NADH exhibited significant disparities between perfusion types, due to differences in perfusate compositions. Inflammatory biomarkers rose during NRP and NMP but normalized post-transplantation. Regenerative markers, including osteopontin and hepatocyte growth factor, also increased during NRP and NMP and normalized after transplantation.
In conclusion, ARG-1 demonstrates strong potential as an early biomarker for assessing liver graft viability during perfusion, supporting timely and effective decision-making in transplantation.
The Influence of Country of Origin on Consumer Perception and Purchase Decision: A Review
Authors: Samuel Aboagye , Haozhen Zhu
Published: November 2024

The influence of country of origin on consumer perceptions and purchase decisions is a well-researched topic in marketing and international business. This review of 67 articles highlights that country of origin significantly impacts how consumers perceive product quality, value, and prestige, influencing their early decision-making processes. However, the ultimate impact on purchase choice is less clear when considering other product and brand factors. The review emphasizes the context-specific nature of these effects, influenced by product stereotypes, consumer characteristics, and changing national reputations in a globalized market. As production becomes more globalized, a nuanced understanding of country of origin is needed, considering multiple origin facets throughout value chains. Further research is needed to explore these influences in blended sourcing environments and evolving perceptions of developing economies. Adapting measurement approaches to reflect contemporary global realities is crucial for leveraging country equity effectively in a complex, interconnected world.
TGFβ1 Restores Energy Homeostasis of Human Trophoblast Cells Under Hyperglycemia In Vitro by Inducing PPARγ Expression, AMPK Activation, and HIF1α Degradation
Authors: Nihad Khiat , Girouard Julie , Kana Tsapi Emmanuelle Stella , Vaillancourt Cathy , Van Themsche Céline , Reyes-Moreno Carlos
Published: November 2024

Elevated glucose levels at the fetal-maternal interface are associated with placental trophoblast dysfunction and increased incidence of pregnancy complications. Troph-oblast cells predominantly utilize glucose as an energy source, metabolizing it through glycolysis in the cytoplasm and oxidative respiration in the mitochondria to produce ATP. The TGFβ1/SMAD2 signaling pathway and the transcription factors PPARγ, HIF1α, and AMPK are key regulators of cell metabolism and known to play critical roles in extravillous trophoblast cell differentiation and function. While HIF1α promotes glycolysis over mitochondrial respiration, PPARγ and AMPK en-courage the opposite. However, the interplay between TGFβ1 and these energy-sensing regulators in trophoblast cell glucose metabolism remains unclear. This study aimed to investigate whether and how TGFβ1 regulate energy metabolism in tropho-blast cells exposed to normal and high glucose conditions. The trophoblast JEG-3 cells were incubated in normal (5 mM) and high (25 mM) glucose conditions for 24 h in the absence and the presence of TGFβ1. The protein expression levels of phosphor (p)-SMAD2, GLUT1/3, HIF1α, PPARγ, p-AMPK, and specific OXPHOS protein subunits were determined by western blotting, and ATP and lactate production by biolumines-cent assay kits. JEG-3 cells exposure to 25 mM glucose decreased ATP production but did not affect lactate production. These changes led to a reduction in the expression levels of GLUT1/3, mitochondrial respiratory chain proteins, and PPARγ, coinciding with an increase in HIF1α expression. Conversely, TGFβ1 treatment at 25 mM glucose reduced HIF1α expression while enhancing the expression levels of GLUT1/3, PPARγ, p-AMPK, and mitochondrial respiratory chain proteins, thereby rejuvenating ATP production. Our findings reveal that high glucose conditions disrupt cellular glucose metabolism in trophoblast cells by perturbing mitochondrial oxidative respiration and decreasing ATP production. Treatment with TGFβ1 appears to counteract this trend probably by enhancing both glycolytic and mitochondrial metabolism, suggest-ing a potential regulatory role of TGFβ1 in placental trophoblast cell glucose metabo-lism.
Modulation of Light Conditions and Root Nutrition Can Improve the Growth and Biosynthesis of Polyphenols in Ocimum basilicum L. Plants
Authors: Veremeichik Galina N. , Grigorchuk Valeria P. , Subbotin Evgenii P. , Kozhanov Sergei O , Tikhonova Olga A. , Brodovskaya Evgenia V. , Silantieva Slavena A , Subbotina Natalia I. , Yaroshenko Yulia L. , Bulgakov Victor P. , Kulchin Yurii N.
Published: November 2024

The sweet basil Ocimum basilicum L. is the subject of numerous studies and is cultivated as a food and ornamental plant. Moreover, O. basilicum could be useful in the prevention of stroke ischaemia, and its anticancer properties were recently shown. The caffeic acid derivatives, such as rosmarinic acid (RA), chicoric acid, salvianolic acids, and anthocyanins provide medicinal properties of basil. Therefore, investigations of the optimal growth conditions that can provide cost-effective cultivation of highly productive basil plants are relevant and important. The aim of the present work was to study the effects of a combination of soil composition and light conditions on the morphological and biochemical characteristics of O. basilicum. In totally artificial (indoor) environments, light-emitting diodes (LEDs) may provide a broad range of narrowband wavelengths with different intensities. This technology can lower operating costs. In addition to the spectral composition, the light intensity (PPFD, µmol m-2s-1) is an important parameter for the optimal growth of plants. In the experiment, we used different light intensities of 300 µmol m-2s-1: warm white, monochromatic (green and red), and a combination of blue and red. Plants were grown under various lighting conditions in soil supplemented with fertilizer, Z-ion, and Crystallon. The results showed that supplementation of soil with Crystallon had a greater effect on the growth both above and below ground parts of O. basilicum plants. Interestingly, growing O. basilicum plants under R and RB light led to a 2-fold increase in the biosynthesis of both the key caffeic acid derivative RA and anthocyanin. However, given that under RB light, there is no positive effect of Crystallon on growth, the productivity of RA and anthocyanin reached a maximum when O. basilicum plants were grown under R light and Crystallon.
Bridging Experimentation and Computation: OMSP for Advanced Acrylate Characterization and Digital Photoresin Design in Vat Photopolymerization
Authors: Okoruwa Leah , Tarak Fatih , Sameni Farzaneh , Sabet Ehsan
Published: November 2024

Vat Photopolymerization (VPP) is an additive manufacturing method that requires the design of photocurable resins to act as feedstock and binder for the printing of parts, both monolithic or composite. The design of a suitable photoresin is costly and time-consuming. The development of one formulation requires the consumption of kilograms of costly materials, weeks of printing and performance testing, as well as the need to have developers with the expertise and knowledge of the materials used, making the development process cost thousands. This paper presents a new characterization methodology for acrylates that allows for the computerization of the photoresin formulation development process, reducing the timescale to less than a week. Okoruwa Maximum Saturation Potential (OMSP) is a methodology that uses Attenuated Total Reflection (ATR-FTIR) to study the functional group of acrylates, assigning numerical outputs to characterize monomers, oligomers and formulations, allowing for more precise distinguishment between materials. It utilizes the principles of Gaussian normal distribution for the storage, recall and computerization of acrylate data and formulation design without the need to database numerous files of spectral data to an average coefficient of determination (R² ) of 0.97. The same characterization method can be used to define the potential reactivity of acrylate formulations without knowing the formulation components, something not possible when using properties such as functionality. This allows for modifications to be made to unknown formulations without prior knowledge of their contents. Validation studies were performed to define the boundaries of the operation of OMSP and assess the methodology’s reliability as a characterization tool. OMSP can confidently detect changes caused by the presence of various acrylates made to the photoresin system and distinguish between acrylates of the same viscosity and functionality. OMSP can compare digitally mixed formulations to physically mixed formulations and provides a high degree of accuracy (R² of 0.9406 to 0.9964), highlighting the future potential for building foundations for artificial intelligence in VPP, the streamlining of photoresin formulation design and transforming the way acrylates are characterized, selected and used.
Evaluating the Diagnostic Accuracy of Ultrasonography versus Computed Tomography for Detecting Renal Stones
Authors: Alqahtani Abdulwahab , Adam Mohamed , Mohtasib Rafat , Alshehri Fahd , Hadadi Ibrahim , Alqahtani Mansour , Gareeballah Awadia , Asiri Abdullah Ali , Alqarn Abdulelah , Alshardi Waleed , Alshahrani Mazen
Published: November 2024

Background: Although computed tomography (CT) scans are the gold standard imaging modality for diagnosing renal stones, their usefulness is restricted because of radiation exposure, particularly for young patients and expectant mothers. This study aims to assess the diagnostic precision of ultrasonography (US) in identifying stones using CT as the gold standard. Method: A retrospective study conducted at the Radiology Department of Aseer Central Hospital, Abha, Saudi Arabia. It includes patients who had CT and US for suspected renal stones between January 2023 and March 2024. The US and CT of 243 individuals were compared to look for stones. Using CT as the gold standard, US sensitivity, specificity, accuracy, and positive and negative predictive values were computed. Results: From the 243 data sets, 153 stones were detected in US and CT. The US exhibited sensitivity (67.4%), specificity (18.8%), diagnostic accuracy (64.2%), positive (92.2%), and negative predictive values (3.9%) in renal stones detection. The mean size of the renal stone detected in the US was 0.95 ± 0.08 mm, while the mean size detected by CT was 0.83 ± 0.07 mm. Furthermore, Bland-Altman's analysis comparing US and CT for measuring renal stones indicated perfect agreement between the two modalities. Conclusion: The US can be employed as the first evaluation method for patients presenting with acute renal colic despite its limited use in diagnosing renal stones.
Advanced Coordinated Scheduling for Integrated Energy Systems with Enhanced Hydrogen Utilization and Source-Load Synergy
Authors: Wang Tao
Published: November 2024

In pursuit of dual-carbon objectives, establishing a low-carbon, efficient, and adaptable energy system has become a priority. This study introduces an advanced optimization scheduling model for integrated energy systems, enhancing system flexibility by optimizing combined heat and power (CHP) units, incorporating electric boilers and the Kalina cycle, and leveraging both electrical and thermal demand responses. A novel aspect of this model is the comprehensive integration of hydrogen production, utilization, and storage, forming an all-encompassing electricity-heat-gas-hydrogen framework. Simulation results validate the model's efficacy in minimizing operational costs and carbon emissions while improving renewable energy uptake.
Microstructural and Magnetic Properties of Polyamide-Based Recycled Composite with Iron Oxide Nanoparticles
Authors: Santos Lucas G. Dos , Buelvas Daina D. A. , Valezi Daniel F. , Vicentin Bruno L. S. , Rocha Christian Manuel Moreno , Mauro Eduardo Di , Porta Felipe de A. La
Published: November 2024

This study explores a sustainable approach to developing magnetic nanocomposites by synthesizing a mixed-phase iron oxide (IO) and recycled polyamide (RPA) composite derived from textile waste. The RPA/IO nanocomposite’s microstructural and magnetic properties were characterized using X-ray diffraction (XRD) with Rietveld refinement, scanning, and transmission electron microscopy (SEM, TEM), vibrating sample magnetometry (VSM), and Mössbauer spectroscopy. XRD confirmed the presence of both magnetite (Fe₃O₄) and maghemite (γ-Fe₂O₃) phases, with Rietveld refinement indicating 79.4 wt% Fe₃O₄. SEM and TEM showed a porous, agglomerated IO surface morphology with an average particle size of 14 nm. Magnetic analysis re-vealed ferrimagnetic and superparamagnetic behavior, with VSM showing saturation magnetization values of 22.2 emu/g at 5 K and 19.1 emu/g at 300 K. Anisotropy constants were estimated at 2.90×10⁵ and 1.26×10⁵, respectively, for IO and the composite, with a blocking temperature of approximately 149 K. Mössbauer spec-troscopy confirmed both Fe₃O₄ and γ-Fe₂O₃ phases, and the RPA matrix did not significantly impact the IO’s crystal structure. These findings contribute to understanding the magnetic behavior of IO and their nano-composites, which is crucial for their potential applications in emerging technologies.
Dual-Wavelength On-Chip Integrated Metalens for Epi-Fluorescence Single Molecule Sensing
Authors: Barulina Elena , Nguyen Dang Du , Shuklin Fedor , Podobrii Mikhail , Novikov Sergey , Chernov Alexander , Kim Inki , Barulin Aleksandr
Published: November 2024

Single molecule fluorescence spectroscopy offers unique capabilities of low concentration sensing or probing molecular dynamics. However, employment of such methodology for versatile sensing and diagnostics under point-of-care demands device miniaturization down to lab-on-a-chip sizes. Here, we numerically design metalenses with high NA of 1.1 that are composed of silicon nitride nanostructures deposited on a waveguide and may selectively focus guided light into an aqueous solution at two wavelengths of interest in a spectral range between 500 and 780 nm. Despite the chromatic focal shift in lateral directions owing to the wavelength-dependent propagation constant in a waveguide, a segmented metalens provides perfectly overlapped focal volumes which meets the requirements for epi-fluorescence light collection. We demonstrate that the molecule detection efficiencies for metalenses designed for excitation and emission wavelengths of fluorophores ATTO 490LS, Alexa 555, APC-Cy7 tandem are sufficient to collect several thousand of photons per second per molecule at modest excitation rate constants. Such sensitivity provides a reliable diffusion fluorescence correlation spectroscopy analysis of single molecules on chip to ex-tract their concentration and diffusion properties in the nanomolar range. Altogether, an achromatic integrated metalens opens new avenues for development of ultracompact and sensitive devices for precision medicine and environmental monitoring.
Effect of Extensive Solar Ultra-Violet Radiations on the Durability of High-Density Polyethylene and Polypropylene based Wood-Plastic Composites
Authors: Siddiqui Mohammad N. , Redhwi Halim H. , Andrady Anthony L. , Furquan Sarfaraz A. , Hussain Syed
Published: November 2024

The natural and laboratory-accelerated weathering of wood-plastic composites (WPCs) based on high-density polyethylene (HDPE) and polypropylene (PP) plastics was investigated. Injection molded samples of the WPCs with different loadings of wood fiber ranging from 0 to 36 wt. percent of wood were subjected to laboratory accelerated weathering and natural weathering. The integrity of samples weathered to different extents was tested using a standard tensile test and surface hardness test to investigate the dependence of these properties on the duration of weathering exposure. Tensile data was used to identify the loading of wood fiber in either plastic matrix that afforded superior ultraviolet (UV) stability. The correlation between the tensile and hardness data for the WPC samples was explored.
Carbon Trading Opportunity and Challenges in Ethiopia
Authors: Bedhane Hailu Negu
Published: November 2024

International carbon offsets and global carbon markets were created to direct carbon financing for the mitigation of climate change toward emerging and impoverished nations. Companies, governments, and people purchased approximately 1 billion carbon offsets in the voluntary carbon markets during the past ten years, contributing slightly under $4.5 billion to clean energy and conservation. This review study aims to evaluate the extent of carbon trading, opportunities and challenges associated with carbon trading in Ethiopia, and potential solutions for issues linked to the concerns presented. Compared to several Asian and Western countries, very few carbon emissions come from African nations.
Buyers and sellers exchange "carbon offsets" or "carbon credits," which are measurements of carbon emissions that have been cut at the source, in carbon markets. Project based transactions and trade in emission allowances are the two main categories of transactions that make up these marketplaces. A local carbon emissions trading scheme in East Africa/Ethiopia might produce trading volumes, foster transparency, support local investment projects, and make the system more adaptable. There exist certain obstacles to carbon trading in East Africa; the two main ones being the unpredictability of the potential benefits and the high transaction costs.
The money made from the sale of carbon should be distributed across the nations, especially those with the guts and the desire to preserve forest resources. East African countries' ability to implement projects must be strengthened by offering various chances for skill development.
Ethiopia won't be able to cut its carbon emissions without carbon markets. The nation must develop a coherent plan on gas emission factors by determining environmentally suitable substitutes, like modern, sustainable agriculture and renewable energy sources. This is particularly significant for industries like agriculture, the production of charcoal from native plants, and the burning of wood for fuel.
Reflections on the Role of Differentiation Processes in Forming Behavioral Phenotypes: Can These Processes Replace the Concepts of Plastic Phenotype and Reversible Plastic Phenotype?
Authors: Chiappa Pilar
Published: November 2024

Comparative studies of various aspects of human development indicate that it has slowed down during evolution compared to the development of the great apes. From multiple areas of knowledge and at separate times, several authors have related this characteristic to behavioral phenotypic plasticity. Throughout the text, I keep a comparative perspective that emphasizes the crucial role that the selection of juvenile behavior has played in shaping cognitive behavior in various animal species, a critical factor in the evolution of cognitive differentiation. Anchored to the positive correlative evolution between cognitive behavior and modes of development, this perspective leads to an argument in favor of replacing the concept of behavioral plasticity with that of cognitive differentiation. Behind the classical concept of behavioral plasticity, there is a link between the purpose of the behavior and its genotype; likewise, behind this concept, in any cognitive behavior, there are different pre-existing phenotypic possibilities from a single genotype, each one depending on an earlier evolutionary interaction between genotype and environment. In conceptual contrast, the purpose of a behavioral phenotype developed from a process of cognitive and neural differentiation is evolutionarily independent of previous environmental interaction (i.e., it does not have any preexisting purpose). Understanding the neurocognitive aspects of behavioral phenotypes will allow researchers from several evolutionary disciplines to decouple behavioral purpose from genotype during evolutionary processes.
Inhibition of Liver Fibrosis by Polygonatum sibiricum Based on Network Pharmacology Investigation
Authors: Shen Haotian , Hu Xue , Du Ying , Song Yang , Tang Bin , Deng Fengmei
Published: November 2024

Background: Liver fibrosis (LF) is a chronic pathological process caused by hepatic pathological factors. Currently, there is no effective clinical method against LF. Polygonatum sibiricum (PS) is a commonly used traditional Chinese medicine. Studies have shown that PS can protect the liver and lower blood glucose and blood lipids. However, there are no clinically recognized drugs for the treatment of liver fibrosis. Research methods: This study utilized pharmacological networks and in vivo and in vitro experiments to investigate the mechanism of action of PS in improving LF. The mechanism and pathway of action of PS to improve LF were explored by CCK-8, Western blot, and immunofluorescence. The LF model was constructed by intraperitoneal injection of CCl4 (0.6 mL/kg) into C57BL/6 mice. The mice were given PS treatment by gavage. After four weeks, pathological changes in the liver were assessed by HE, Masson, and Sirius red staining. The expression of LF-related proteins in liver tissues was evaluated by immunohistochemistry (No. Cheng Medical Activity Lun [2024] 032). Results: PS inhibited α-smooth muscle actin (α-SMA), collagen type I α1 chain (COL1A1) and Bcl-2, promoted the expression of Bax and p53 signaling pathways and facilitated apoptosis in LX-2 cells. In in vivo experiments, PS reduced the serum levels of AST/ALT, inhibited the development of LF and decreased the expression of α-SMA, COL1A1 and COL3A1 in liver tissues. Conclusion: PS inhibits LX-2 proliferation and LF-associated protein expression by regulating the p53 signaling pathway, thereby improving LF.
Efficient Financial Fraud Detection: An Empirical Study Using Ensemble Learning and Logistic Regression
Authors: Wang Kewei
Published: November 2024

In the financial sector, fraud detection remains a crucial yet challenging task due to the increasing volume and complexity of transactions. This study focuses on developing an efficient fraud detection model using a highly realistic financial transaction dataset. The dataset, characterized by significant class imbalance, undergoes comprehensive preprocessing including PCA for feature extraction and various sampling techniques for balancing. We employ a range of machine learning classifiers, including logistic regression, K-Nearest Neighbors, support vector machine, and decision tree, alongside ensemble learning approaches to enhance detection performance. A comparative analysis is conducted, highlighting that ensemble models, including stacking with logistic regression and LightGBM, demonstrate superior performance over individual classifiers. The results show notable improvements in AUC-ROC and other metrics, underscoring the efficacy of combined approaches in detecting fraudulent activities with high accuracy and robustness. The findings offer valuable insights into the design of advanced fraud detection systems capable of mitigating financial losses and enhancing system security.
Breast Cancer Detection: A Comprehensive Study on Machine Learning and Deep Learning Techniques
Authors: Mathpal Jagrati
Published: November 2024

Breast cancer is among the most common cancers affecting women globally. Early detection is crucial in reducing mortality rates and improving treatment outcomes. This project utilizes machine learning to develop a breast cancer detection model based on patient medical data. The Random Forest Classifier was selected due to its high accuracy and capacity to handle imbalanced datasets. The project also integrates a frontend interface that allows users to input relevant data and find nearby cancer treatment centers through a location-based service. With an accuracy of over 95%, the model offers a promising tool to assist healthcare professionals and patients. Future improvements aim to enhance the dataset and user accessibility, making it a more versatile and scalable solution.
Innovationology and the Future of Finance: Reimagining Money, Markets, and Economic Governance for a Sustainable, Equitable World
Authors: Moleka Pitshou
Published: November 2024

As the world grapples with the compounding crises of environmental degradation, social inequality, and economic instability, the imperative for a radical rethinking of prevailing financial systems and economic governance frameworks has never been more pressing. Drawing on the transformative principles of Innovationology, a pioneering new science, this article offers an exploration of how the field of finance can be reimagined and reinvigorated to drive sustainable, equitable progress on a global scale. Transcending the limitations of neoclassical economic models and shareholder-centric approaches to value creation, Innovationology-informed finance provides a comprehensive, systems-oriented lens for understanding the complex, interdependent relationships between monetary systems, financial markets, and the broader social and ecological context. By embracing the core principles of Innovationology - collaborative governance, value-driven innovation, and adaptive resilience - this framework empowers policymakers, financial practitioners, and civil society actors to anticipate emerging economic and financial risks, respond to disruptive shocks, and continuously evolve innovative solutions to address the world's most pressing challenges. Through in-depth case studies and interdisciplinary analyses, the article delves into pioneering initiatives that have harnessed the power of Innovationology to redefine the role of finance in driving sustainable, equitable development, from innovative public-private investment mechanisms that channel resources towards regenerative, community-oriented projects to collaborative platforms that are reshaping the rules and practices of global financial governance. It unpacks how these initiatives have navigated the entrenched power dynamics and narrow profit-maximizing incentives that have historically undermined the potential of finance to serve the broader public good. Crucially, the article also examines the profound implications of Innovationology for the future of economic policymaking, the role of emerging and developing economies in shaping global financial systems, and the potential for more inclusive, sustainable models of value creation and distribution. By positioning Innovationology as a vital lens for reframing the study and practice of finance, this article offers a bold, visionary pathway for cultivating the collaborative, adaptive capacities necessary to address the world's most pressing challenges and unlock a more equitable, regenerative global future.
Plant-Derived Anti-Cancer Therapeutics and Biopharmaceuticals
Authors: Hashim Ghyda Murad , Shahgolzari Mehdi , Hefferon Kathleen , Yavari Afagh , Venkataraman Srividhya
Published: November 2024

In spite of significant advancements in diagnosis and treatment, cancer remains one of the major threats to human health due to its ability to cause disease with high morbidity and mortality. A multifactorial and multitargeted approach is required towards intervention of the multitude of signaling pathways associated with carcinogenesis inclusive of angiogenesis and metastasis. In this context, plants provide an immense source of phytotherapeutics that show great promise as anticancer drugs. There is increasing epidemiological data that diets rich in vegetables and fruits could decrease the risks of certain cancers. Several studies have proved that natural plant polyphenols such as flavonoids, lignans, phenolic acids, alkaloids, phenylpropanoids, isoprenoids, terpenes and stilbenes could be used in anticancer prophylaxis and therapeutics by recruitment of mechanisms inclusive of antioxidant and anti-inflammatory activities and modulation of several molecular events associated with carcinogenesis. The current review discusses the anticancer activities of principal phytochemicals with focus on signaling circuits towards targeted cancer prophylaxis and therapy. Also addressed are plant-derived anti-cancer vaccines, nanoparticles, monoclonal antibodies and immunotherapies. This review article brings to light the importance of plants and plant-based platforms as invaluable, low-cost sources of anti-cancer molecules of particular applicability in resource-poor developing countries.
Improved Research Paper: Leveraging AI for Enhancing Lung Cancer Detection
Authors: Patel Siddhant
Published: November 2024

Lung cancer remains a leading cause of cancer-related deaths worldwide, with late-stage diagnoses contributing significantly to high mortality rates. Early and accurate detection is crucial for improving survival rates and treatment outcomes. Artificial intelligence (AI) technologies, particularly machine learning (ML) and deep learning (DL), offer exceptional promise in aiding lung cancer detection through advanced data analysis. This paper explores the potential of AI in enhancing lung cancer detection processes, including image analysis, risk prediction, and workflow optimization. By leveraging AI-driven methodologies, healthcare professionals can improve diagnostic accuracy, streamline operations, and ultimately enhance patient care.
Regional Scale Detection of Palms Using VHR Satellite Imagery and Deep Learning in the Guyanese Rainforest
Authors: Drouillard Matthew J. , Cummings Anthony R.
Published: November 2024

Arecaceae (palms) play a crucial role for native communities and wildlife in the Amazon region. This chapter presents a first-of-its-kind regional-scale spatial cataloging of palms using remotely sensed data for the country of Guyana. Using very high-resolution satellite images from the GeoEye-1 and WorldView-2 sensor platforms, which collectively cover an area of 985 km2, a total of 472,753 individual palm crowns are detected with F1 scores of 0.76 and 0.79, respectively, using a convolutional neural network (CNN) instance segmentation model. An example of CNN model transference between images is presented, emphasizing the limitation and practical application of this approach. A method is presented to optimize precision and recall using the confidence of the detection features; this results in a decrease of 45% and 31% in false positive detections, with a moderate increase in false negative detections. The sensitivity of the CNN model to the size of the training set is evaluated, showing that comparable metrics could be achieved with approximately 50% of the samples used in this study. Finally, the diameter of the palm crown is calculated based on the polygon identified by mask detection, resulting in an average of 7.83 m, a standard deviation of 1.05 m, and a range of {4.62,13.90} m for the GeoEye-1 image. Similarly, for the WorldView-2 image, the average diameter is 8.08 m with a standard deviation of 0.70 m and a range of {4.82,15.80} m.
Applying Recommender Systems to Predict Personalized Film Age Ratings of Parents
Authors: Papadakis Harris , Fragopoulou Paraskevi , Panagiotakis Costas
Published: November 2024

A motion picture content rating system classifies films for their suitability for audiences based on their treatment of issues such as sex, violence, or substance abuse, their use of profanity, etc., typically deemed unsuitable for children or adolescents. This rating is usually coupled with a minimum desired age that the film is suitable for. In this work, we apply Recommender Systems to predict personalized film age ratings of parents. According to the proposed methodology, we reduce the personalized film age prediction problem to the classic item recommendation problem by applying a recommender system for each age category of a film. The application of the recommender systems provides a recommendation for each age category of a film. Finally, these recommendations are combined to provide the final age recommendation of the parent (user). The proposed methodology is applied to state-of-the-art recommender systems. In addition, we have used as baselines for comparisons the direct application of a recommender system to the age prediction problem. This is achieved by treating each film as an item and assigning the given age as its rating. The experimental results demonstrate the efficiency and high performance of the proposed approach on a well-known, real-world dataset.
Design of a Highly Affordable and Reliable Data Acquisition Unit System Dedicated to Experimental Research and Education
Authors: PAYET Pepito , FAKRA Damien Ali Hamada , RAKOTOSAONA Rijalalaina , RATSIMBA Marie Hanitriniaina , RANDRIANARISON Mino Patricia
Published: November 2024

Most experimental research is based on trials that need a measurement acquisition chain (acquisition unit, sensors, and IoT). The units of acquisition employed in research are becoming more accurate and complex. However, they do have other disadvantages: they are rather costly, They are expensive, lack an Ethernet connection, the drivers’ source codes are not modifiable, and are designed to work with very specific sensors, making them incompatible with other sensors on the market outside those proposed by the device manufacturer. This article introduces the DL2C datalogger, which combines a previously unique mix of open source codes and inexpensive computer hardware. The acquisition unit is self-contained, portable, easy to build, and connects to a wireless internet network with a very accurate data values collection. Its operation consists of a well-balanced mix of hardware (i.e., Arduino Nano, Arduino Uno, and Raspberry Pi) and software (i.e., C, Python, LabView). According to the state-of-the-art realized, the combination of an Arduino, a Raspberry Pi, and a LabView environment is very original. The Arduino Uno enables the collection and visualization of a wider variety of measurement ranges directly on the acquisition unit. The Arduino Nano regulates the power supply and assures the security of the DL2C’s electronic circuit. The Raspberry Pi facilitates the DL2C to function without the assistance of a computer. Finally, the LabView graphical interface is utilized to manipulate and visualize the central unit’s data remotely. The DL2C measures between [-5V; +5V] with an average absolute error of 0.02V for Volt signals and 4.98mV for milliVolt signals. An application example using the datalogger was presented and the DL2C subjected to a S.W.O.T study to identify the strengths, weaknesses and possible future improvements of the DL2C database acquisition.
Response of Nitrogen Fertilizer Utilization, Yield, and Quality of Hybrid Indica Rice to Nitrogen Reduction with Organic Fertilizer Application in the Karst Region
Authors: Xu Linggui , You Xuanxiao , Feng Huayue , Wang Kexiao , Gao Qiyu , Ren Junhong , Han Lizhi , Li Lejia
Published: November 2024

To investigate the effect of nitrogen reduction (NR) and combined application of organic fertilizer (OF) on nitrogen (N) utilization, yield, and quality of hybrid indica rice in the karst area, using rice ‘Yixiangyou 2115’ as the material, a split-plot design experiment of two factors of OF application rate as the main plots and NR rate as the subplots was carried out. The OF application rate had three levels: M0 (0 kg/ha), M1 (low OF, 1673 kg/ha), and M2 (high amount OF, 3346 kg/ha). The NR rate had four levels: R1 (NR rate 0%), R2 (NR rate 25%), R3 (NR rate 50%), and R4 (NR rate 100%). In this experiment, there were three modes of NR and OM application. Mode1: NR under the same amount of OM; Mode 2: NR and OM application under equal N conditions; and Mode 3: NR and combined application of OM under non-isonitrogen conditions. Rice yield was the highest under R3 in mode1. In modes 2 and 3, compared with single N fertilizer (R1M0), the yield of 25% NR combined with a high amount of OM (R2M2) increased significantly. In terms of yield components, under mode 1, with an increase in the N reduction rate, the effective panicle number showed a continuous decreasing trend, and the number of spikelets per panicle increased first and then decreased. The1000-grain weight and spikelet filling had no obvious change trend, but both were highest under R4. In modes 2 and 3, spikelet filling under NR combined with organic fertilizer treatment was higher than that of the single fertilizer treatment. In terms of N efficiency, in mode 1, with the increase in the N reduction rate, N recovery efficiency (RE), agronomic efficiency (AE), and partial factor productivity (PFP) showed a continuous increase trend, all of which were highest under R4. In mode 2, compared with R1M0, the RE of R2M2 significantly increased. In mode 3, compared with R1M0, the AE and PFP of 50% N reduction with low or high amounts of organic fertilizer were significantly increased. In terms of rice processing quality, in mode 1, as the N reduction rate improved, the milled rice rate and head rice rate continued to decline, but in modes 2 and 3, compared with the treatment of chemical fertilizer alone, the brown rice rate, milled rice rate, and head rice rate of the treatment of NR combined with OF improved. In terms of appearance quality and cooking nutritional quality of rice, under the same amount of OF, compared with no NR, the chalky degree and chalky rice rate of NR decreased, but gum consistency increased; meanwhile, under the condition of isonitrogen or non-nitrogen, compared with single N fertilization, the consistency of gel of the treatment of NR combined with OF increased. In summary, NR combined with OF fertilization mode was conducive to the improvement of N efficiency, yield, and quality of hybrid indica rice.
A Transformer Encoder Approach for Indoor Localization Reconstruction from an IMU and GPS Based Sensor
Authors: Guyard Kévin Cédric , Bertolaccini Jonathan , Montavon Stéphane , Deriaz Michel
Published: November 2024

Accurate localization is crucial for numerous applications. While several methods exist for out-door localization, typically relying on GPS signals, these approaches become unreliable in indoor environments due to weak GPS signal or GPS outage. Many researchers have attempted to ad-dress this limitation, primarily focusing on real-time solutions. However, for applications that do not require real-time localization, these methods remain suboptimal. This paper presents a novel Transformer-based bidirectional encoder approach to address indoor localization challenges in postprocessing. Our method predicts velocity during periods of weak or lost GPS signal and calculates position through bidirectional velocity integration. Additionally, it incorporates posi-tion interpolation to ensure smooth transitions between active GPS and GPS outage phases. Applied to a dataset tracking horse positions—which features velocities up to 10 times those of pedestrians and higher acceleration—our approach achieved an average trajectory error below 3 meters, while maintaining stable relative distance errors regardless of GPS outages duration.
Validation of Psychometric Properties Of The Partners in Health Scale in Heart Failure
Authors: Iyngkaran Pupalan , Smith David , Mclachlan Craig , Battersby Malcolm , DeCourten Maximilian , Hanna Fahad
Published: November 2024

Objective Congestive heart failure (CHF) is a complex chronic disease, and it is associated with a second comorbid condition in more than half of cases. Self-management programs can be specific to CHF or generic for chronic diseases. Several tools have been validated for CHF. Presently there are no established generic instruments validated for measuring self-management in CHF. This study aims to evaluate the internal reliability and construct validity (psychometric properties) of the Partners in Health (PIH) scale in the patients with congestive heart failure, a generic chronic disease self-management tool. Methods: The study included 210 adult CHF patients in Community Cardiology Outpatients in West Melbourne, Australia, treated in community cardiology were included between May 2022 and Jan 2024. The screened patient population were diagnosed with CHF and eligible for SGLT-2 inhibitor. Cohort analysis used the Bayesian confirmatory factor analysis to eval-uate a priori four-factor structure. Omega coefficients and 95% credible intervals (CI) were used to assess internal reliability. Results: In CHF cohorts, Heart Failure with reduced (HFrEF) and preserved ejection fraction (HFpEF), participants mean [standard deviation (SD)] age was 66.8 (13.5) and 71.3 (9.76) years. Description of study sociodemographics highlighted male were 88% and 52%, BMI > 50% in both cohorts, eGFR > 60 ml/min were 59% and 74%, LVEF < 40% and > 50% were 99% and 100% respectively. Model fit for the hypothesised model was adequate (posterior predictive P = 0.073) and all hypothesised factor loadings were substantial ( > 0.6) and significant (P < 0.001). Omega coefficients (95% CI) for the PIH subscales of Knowledge, Partnership, Management and Coping were 0.84 (0.79 – 0.88), 0.79 (0.73 – 0.84), 0.89 (0.85 – 0.91) and 0.84 (0.79 – 0.88) respectively. Conclusion: This study is original in confirming the dimensionality, known-group valid-ity, and reliability of the PIH scale for measuring generic self-management in outpatients with the CHF syndrome.
A Self-Gelling Powder Based on Polyacrylic Acid/ Polyethyleneimine/Polyethylene Glycol for High-Performance Hemostasis and Antibacterial Activity
Authors: Li Jia , Li Shu , Zhong Aozhen , Xing Jun , Li Ling , Wang Cai , Zheng Min
Published: November 2024

Powder-based hemostatic materials has offered unprecedented opportunities in effective sealing and repair of irregularly shaped wound and high-pressure, noncompressible arterial bleeding wounds caused by surgeries, traffic accidents and wars. However, inadequate adhesion to bleeding wounds or poor hemostasis in biological tissues remains challenging. Herein, we report a self-gelling hemostasis powder based on polyacrylic acid/ polyethyleneimine/ polyethylene glycol（named as PPG）for rapid hemostasis and effective antibacterial ability. PPG powder deposited on bleeding wounds can absorb interfacial water and rapidly swell into a physically cross-linked hydrogel in situ within 2 seconds to form a pressure-resistant physical barrier. Furthermore, the in vivo and in vitro result indicate the PPG powder as an effective sealant possesses ease of use, excellent hemocompatibility, strong antibacterial abilities, and superior blood clotting abilities. The effective hemostatic sealing capability of the PPG powder is demonstrated in a variety of injury models in rats and rabbits. All of these factors show that the PPG powder with superior wound treatment abilities is a profound biomaterial for surgical applications.
A description of trends in Gulf Stream path retroflections since the late 20th Century
Authors: Rojo de Anda Georgina , Parfitt Rhys , Dewar William , Jamet Quentin , Uchida Takaya
Published: November 2024

This paper describes recent variations that have emerged in spatial patterns of retroflections in the monthly Gulf Stream (GS) path. They have become less frequent and also shifted further to the east; we find this in both reanalysis and free-running model data of the ocean. A suite of eddy-rich North Atlantic ocean ensemble simulations, forced with varying combinations of realistic and climatological boundary conditions, is used to diagnose the relative importance of atmospheric and oceanic drivers of these changes. It is implied that the majority of the shifts and changes in the number of retroflections throughout the five decades (1963-2012) are products of realistic atmospheric forcing and oceanic boundary conditions but only the latter is found to be statistically significant.
<span lang="EN-US" style="font-size: 10.0pt; font-family: 'Palatino Linotype',serif; mso-fareast-font-family: SimSun; mso-bidi-font-family: 'Times New Roman'; color: black; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA; mso-no-proof: yes;">Influence of perceived maternal self-efficacy on exclusive breastfeeding initiation and consolidation: A systematic review
Authors: Saavedra Steven , Rodríguez-Gallego Isabel , Leon-Larios Fatima , Andina-Garcia Elena , Perez-Contreras Rosa , Gonzalez-Sanz Juan D.
Published: November 2024

Different international organizations recommend exclusive breastfeeding during the neonate's first six months of life; however, figures of around 38% are reported at the global level. One of the reasons for early abandonment is the mothers' perception of supplying insufficient milk to their newborns. The objective of this research is to assess how mothers' perceived level of self-efficacy during breastfeeding affects their ability to breastfeed and the rates of exclusive breastfeeding up to six months postpartum. A systematic review for the 2000-2023 period was conducted in the following databases: Cochrane, Web of Science, Scopus, PubMed, Science Direct and CINAHL. Original articles, clinical trials, and observational studies in English and Spanish were included. The results comprised 18 articles in the review (2006-2023), with an overall sample of 2004 participants. All studies were conducted in women who wanted to breastfeed, used the Breastfeeding Self-Efficacy Scale or its short version to measure postpartum self-efficacy levels, and breastfeeding rates were assessed up to 6 months postpartum. The present review draws on evidence suggesting that mothers' perceived level of self-efficacy about their ability to breastfeed affects rates of exclusive breastfeeding up to 6 months postpartum. High levels of self-efficacy are positively related to the establishment and maintenance of exclusive breastfeeding; however, these rates decline markedly at 6 months postpartum.