bluuebunny/crossref_metadata_2025 huggingface dataset:
Diagnóstico de parásitos gastrointestinales en ovinos durante el período 2018-2021 en el Estado de México, México
Authors: Valladares-Carranza Benjamín , Ortega-Santana César , Velázquez-Ordoñez Valente , Vega-Castillo Luis Fernando , Sánchez-Torres Juan Edrei , Delgadillo-Ruiz Lucia , Bañuelos-Valenzuela Rómulo , Rivero-Pérez Nallely , Zaragoza-Bastida Adrián , Ocampo-Varón Víctor Daniel
Published: June 2024

La verminosis gastroentérica de los pequeños rumiantes, como la de otras especies de animales productivos, repercute notablemente en la salud y el desarrollo pecuario. Con el objetivo de determinar las parasitosis gastrointestinales diagnosticadas en ovinos durante el periodo 2018 al 2021 del Estado de México se obtuvieron y analizaron los reportes de muestras del área de parasitología (resultados emitidos de diagnóstico por flotación) del CIESA. Para el análisis de registros, valoración de casos y su clasificación se consideró: número de caso, número de animales en la unidad de producción, procedencia y tipo de unidad de producción. Para el reporte de resultados se utilizó estadística descriptiva. La procedencia de las muestras fue de varias áreas productoras de ovinos. Para el año 2018 el número de muestras fue de 63, para el 2019 fueron 49, en el 2020 diez, y cuatro para el 2021, dando un total de 126 muestras. Las razas correspondieron a: Suffolk, Hamshiere, Dorper, Kathadin e híbridos. En el análisis coproparasitoscópico se encontró: 5 muestras negativas; con una parasitosis leve 67; con una parasitosis moderada 33, y 21 con una parasitosis severa. De las parasitosis gastroentéricas se encontró una positividad del 96.03 %, y por especie de nematodos gastroentéricos se encontró: Chabertia 91 (72,72 %); Cooperia 28 (22,22 %); Haemonchus 25 (19.84 %); Nematodirus 8 (6,34 %), y a Trichostrongylus spp 4 muestras (3,17 %). Otras parasitosis observadas, fueron: Eimeria spp con 84,92 %; Moniezia spp 22,22 %; 17,46 % a Dictyocaulus, y 13,49 % a Trichuris. Por lo tanto, en el manejo sanitario de los rebaños se requiere un mejor control parasitario y aplicar medidas de control alternativas por la aparición de parásitos resistentes a los antihelmínticos.
Learning Strategy to Read The Qur'an Online Using The At-Tibyan Method
Authors: Efrita Norman  , Arman Paramansyah  , Rizki Firmansyah
Published: June 2024

This research aims to describe the implementation of the At-Tibyan method in Quranic reading education at Graha Qur'an Wadi Mubarak, as well as the strategies and factors that support or hinder online Quranic reading education using the At-Tibyan method. The research methodology employed is qualitative research, with 7 participants involved. Data analysis follows the Miles Huberman analysis approach, involving data collection, data reduction, data presentation, and verification/conclusion. The research findings indicate that the At-Tibyan method used in online Quranic reading education at Graha Qur'an Wadi Mubarak involves preparation, implementation, and evaluation stages, and is supported by factors such as qualified instructors and active participant involvement. However, challenges such as poor internet connectivity and limited participant engagement are also encountered.
THE RELEVANCE OF STOICISM PHILOSOPHY TO THE SOCIAL AND RELIGIOUS LIFE OF GENERATION Z
Authors: Zabryna Farrah Ananta Erva , Farihah Irzum
Published: June 2024

The development of all-digital technology has made Generation Z have a pattern of thought that tends to be unique and creative in terms of socializing and thinking. This uniqueness tends to be followed by the amount of information on the timeline that can be accessed through any platform. This affects how Generation Z acts in their social and religious lives. The influence of this information can lead to perceptions resulting from their thinking in processing an event. This research aims to find the relationship between the teachings of stoicism and Generation Z’s social and religious life in creating a wiser life and the ability for self-control. Generation Z’s social and religious life cannot be separated from digital advances that can influence their religious mindset. Meanwhile, the philosophy of stoicism is a form of teaching self-control through rational thinking behavior. This research uses qualitative methods with data collection through interviews and observations. In-depth interviews were conducted with Generation Z who have known the concept of stoicism in the age range of 18–23 years old and live in Kudus City. Secondary data was obtained through various journals related to the topic. The results of this study show that in carrying out social and religious life, Generation Z has been able to understand how to act properly without involving emotions and trying to think rationally. Furthermore, Generation Z can accustom themselves to doing spiritual activities in religion both personally and in groups, to provide religious awareness through self-control of the development of negative emotions. This is because there are similar indicators to achieve happiness in religious teachings and philosophy. In religion, the Qur’an is prioritized as the word of God with the main function of showing humans the essence of truth, while philosophy uses rationality as a tool to find truth without being bound by emotional factors. It can be concluded that the Qur’an and the philosophy of stoicism have the same concept related to gratitude and patience.
Developing a Cyber-Physical Rehabilitation System for Virtual Interaction between Patients and Occupational Therapists
Authors: Cheng Marvin H. , Camargo Hugo , Bakhoum Ezzat G.
Published: June 2024

The integration of robotic devices into healthcare settings for rehabilitation purposes represents a rapidly advancing field with significant benefits for both therapists and patients. However, standalone robot systems face limitations such as inefficient processing of patient data and logistical challenges for patients, such as travel time to rehabilitation centers. To address these shortcomings, this paper proposes the integration of cyber-physical systems into rehabilitation robotics. Cyber-physical systems leverage network connectivity and real-time data processing to enhance the efficiency and convenience of robot-based rehabilitation. By seamlessly integrating sensors, actuators, and computational algorithms, cyber-physical rehabilitation systems empower therapists to more effectively treat patients by providing actionable insights derived from comprehensive data analysis. This enables therapists to tailor treatment plans precisely to each patient’s unique needs, ultimately leading to improved outcomes. Additionally, cyber-physical rehabilitation systems facilitate remote monitoring and intervention, allowing therapists to oversee patient progress and make timely adjustments to treatment protocols without the need for in-person visits. This not only saves patients valuable time and resources but also ensures continuity of care, particularly for individuals residing in remote or underserved areas. Furthermore, cyber-physical rehabilitation systems enable collaborative decision-making by facilitating communication and information sharing among healthcare professionals, further enhancing the quality and efficacy of rehabilitation services. In summary, integrating cyber-physical systems into rehabilitation robotics represents a significant advancement in leveraging technology to optimize patient care and outcomes, promising to revolutionize rehabilitation therapy.
CAR-NK Cell Therapy: A Transformative Approach to Overcoming Oncological Challenges
Authors: Li Wangshu , Wang Xiuying , Zhang Xu , Aziz Aziz ur Rehman , Wang Daqing
Published: June 2024

The use of chimeric antigen receptor (CAR) in natural killer (NK) cells for cancer therapy is gaining momentum, marking a significant shift in cancer treatment. This review aims to explore the potential of CAR-NK cell therapy in cancer immunotherapy, providing a fresh perspective. It discusses the innovative approaches in CAR-NK cell design and engineering, particularly targeting refractory or recurrent cancers. By comparing CAR-NK cells with traditional therapies, the review highlights their unique ability to tackle tumor heterogeneity and immune system suppression. Additionally, it explains how novel cytokines and receptors can enhance CAR-NK cell efficacy, specificity, and functionality. The review underscores the advantages of CAR-NK cells, including reduced toxicity, lower cost, and broader accessibility compared to CAR-T cells, along with their potential in treating both blood cancers and solid tumors.
Effect of Flow Interference Between Cylinders Subjected to a Cross Flow Over a Cluster of Three Equally Spaced Cylinders
Authors: Dong Jia , Shi Xianrui , Yan Gen hua
Published: June 2024

Flow over a cluster of three equally spaced circular cylinders was studied by numerical simulation on base of the turbulent mode k-kl-ω for two incidence angles β=0° and 60°, at different Reynolds number,in this paper, flow interference pattern characteristics between cylinders, characteristics of force parameters and Strouhal number of each cylinder with different spacing ratios ranging from 1.5 to 4 at Re 8×104, 2×105and 2×106 had been obtained. At incidence angle β=0° and 60°, the wake was nearly symmetric if S/D≥2.0; at β=60°,S/D=1.5 and Re=2×105, the asymmetric periodic flow pattern occurred in the wake region which leaded to the significant effect on the surface mechanical parameters and Strouhal number which was found for the first time; the periodic flow regime of the wake region also occurred at S/D=1.35 and 1.5, without the same phenomenon at S/D=1.7 and 2.0; the phenomenon of periodic flow regime of the wake region was intrinsic and related to Reynolds number and space ratio. in addition, characteristics of force parameters of three cylinders mainly were affected by the interference between cylinders, at 1.5<S/D<4, which leaded to that the drag coefficient of three cylinders reduced with different Reynolds numbers. At incidence angle 60°, in subcritical and critical regime, the Strouhal numbers of the upstream cylinders were more than that of single cylinder, and with the enlargement of spacing ratio, the Strouhal number decreased; for the downstream cylinder , the Strouhal number is far less than that of single cylinder and with the enlargement of spacing ratio, the Strouhal number increases, which were another prominent flow inference influence. The results indicated the effect of flow interference between cylinders subjected to a cross flow over a cluster of three equally spaced cylinders on the flow pattern,surface mechanical parameters and Strouhal number.
Bioactive Bioxanthracene and Cyclodepsipeptides from the Entomopathogenic Fungus Blackwellomyces roseostromatus BCC56290
Authors: Phutthacharoen Kunthida , Llanos-Lopez Natalia Andrea , Toshe Rita , Noisripoom Wasana , Khonsanit Artit , Luangsa-ard Janet Jennifer , Hyde Kevin D , Ebada Sherif S. , Stadler Marc
Published: June 2024

In the course of our ongoing research targeting the identification of potential biocontrol agents from entomopathogenic fungi (EPF), we explored a solid-state rice fungal extract of Blackwellomyces roseostromatus BCC56290 derived from infected lepidopteran larvae. Chemical and biological prospections afforded four unprecedently reported natural products differentiated into one dimeric naphthopyran bioxanthracene ES-242 derivative (1) and three cyclodepsipeptides (2-4) in addition to two known cyclodepsipeptides, cardinalisamides B (5) and C (6). Chemical structures of the isolated compounds were elucidated through comprehensive 1D/2D NMR and HR-ESI-MS data together with comparisons to the reported literature. The absolute configuration of the isolated cyclodepsipeptide was determined using Marfey’s method. All isolated compounds were assessed for their antimicrobial, cytotoxic and nematicidal activities with some compounds revealed significant activities.
Declining Bank Erosion Rate Related to Climate‐Change Driven Hydrological Alteration of a Small Sub‐Alpine River
Authors: Pusztai–Eredics Alexandra , Kiss Tímea
Published: June 2024

In the 21st century, climate change and its consequences are getting more serious. The changes in temperature and precipitation alter the run-off conditions, subsequently influencing the channel processes of rivers. The study aims to analyse the hydrological changes of a small, sub-alpine river (Rába River, Central Europe) and the bank erosional processes since the 1950s. The bank erosion was determined based on topographical maps, aerial photographs, and RTK–GPS surveys. Short (2–3 days) floods were common between 1950–1980, and low stages occurred in 65–81% of a year. However, in the 21st century, extreme regimes developed, as record-high, flashy floods alter with long low stages (91–96% of a year). The bank erosion shows a cyclic temporal pattern, gradually increasing until it reaches a high value (4.1–4.9 m/y), followed by a limited erosional rate (2.2–2.8 m/y). However, the magnitude of the bank erosion is decreasing. It could be explained by (1) the lower transport capacity of the more common low stages and (2) the seasonal shift of the flood waves, appearing in the vegetational period when the riparian vegetation can more effectively protect the banks from erosion.
Therapeutic Potential of Various Intermittent Fasting Regimens in Alleviating Type 2 Diabetes Mellitus and Prediabetes: A Comprehensive Review
Authors: Msane Sthembiso , Khathi Andile , Sosibo Aubrey
Published: June 2024

: Intermittent fasting has drawn significant interest in the clinical research community due to its potential to address metabolic complications such as obesity and type 2 diabetes mellitus. Various intermittent fasting regimens include alternate-day fasting (24 hours of fasting followed by 24 hours of eating), time-restricted fasting (fasting for 14 hours and eating within a 10-hour window), and the 5:2 diet (fasting for two days and eating normally for the other five days). Intermittent fasting is associated with a reduced risk of type 2 diabetes mellitus-related complications and can slow their progression. The increasing global prevalence of type 2 diabetes mellitus highlights the importance of early management. Since prediabetes is a precursor to type 2 diabetes mellitus, understanding its progression is essential. However, the long-term effects of intermittent fasting on prediabetes are not yet well understood. Therefore, this review aims to comprehensively compile existing knowledge on the therapeutic effects of intermittent fasting in managing type 2 diabetes mellitus and prediabetes.
FhMYB108 Regulates the Expression of Linalool Synthase Gene in Freesia hybrida and Arabidopsis
Authors: Yang Zhongzhou , Jin Wei , Luo Qi , Li Xiaoli , Wei Yunmin , Lin Yunlong
Published: June 2024

Acting as the most abundant and widely distributed volatile secondary metabolites in plants, terpenoids play crucial roles in diverse physiological regulations and metabolic processes. Terpene synthases occupy a decisive proportion in determining the composition and diversity of terpenoids; though their regulatory effects have been extensively investigated across various plant species, limited studies have focused on the upstream transcriptional regulation of terpene synthases. In this study, we unveil linalool as the predominant volatile compound in Freesia hybrida flowers, demonstrating a gradual release pattern during flower blooming. In the context of the transcriptome, a typical MYB transcription factor, FhMYB108, was screened based on digital expression profile correlation analysis and homologous gene comparison. FhMYB108 is capable of regulating the expression of terpene synthase FhTPS1, and both their expression levels exhibit a gradual increase concomitant with flower opening. Moreover, transcriptional regulation and transient expression assays revealed that FhMYB108 exerts a stimulatory effect on the transcription of A. thaliana AtTPS14, while no significant increase in AtTPS14 expression was observed upon stabilization of FhMYB108 in Arabidopsis. Investigate its reason, the highly expressed AtMYC2 in A. thaliana can interact with FhMYB108 to suppress the activation of AtTPS14 by FhMYB108. The present study not only elucidated the regulatory mechanism underlying linalool synthesis, but also discovered the synergistic effect of MYB and bHLH transcription factors in governing the biosynthesis of volatile terpenoids.
Single-track magnetic tape absolute position sensor with self-adaptivity
Authors: Kántor Zoltán , Szabó Attila
Published: June 2024

A single-track magnetic code tape based absolute position sensor system is demonstrated. Unlike traditional dual-track systems, our method simplifies manufacturing and avoids crosstalk between tracks, offering higher tolerance to alignment errors. The sensing system employs an array of magnetic field sensing elements that recognize the bit sequence encoded on the tape. This approach allows for accurate position determination even when the number of sensing elements is fewer than the number of bits covered, and without the need for specific spacing between sensing elements and bit length. We demonstrate the system's ability to learn and adapt to various magnetic code patterns, including those that are irregular or have been altered. Our method can identify and localize the sensed magnetic field pattern directly within a self-learned magnetic field map, providing robust performance in diverse conditions. This self-adaptive capability enhances operational safety and reliability, as the system can continue functioning even when the magnetic tape is misaligned or has undergone changes.
Dynamic architecture adaptation for MRI brain tumor Detection using SECNNs
Authors: beyaye cheikh abd elghader , Keradi Imane
Published: June 2024

This paper presents an advanced approach for the Detection of MRI brain tumor images using Convolutional Neural Networks (CNNs). The study focuses on employing sophisticated techniques such as data augmentation, model optimization, and rigorous performance evaluation metrics to achieve high accuracy in multi-class classification tasks. Additionally, we integrate the concept of Self-Expanding Convolutional Neural Networks (SECNNs), which dynamically adjust model complexity during training. This approach ensures optimal performance while maintaining computational efficiency. The dataset used in this research comprises MRI images categorized into four distinct classes: glioma, meningioma, no tumor, and pituitary tumor. Our method demonstrates a notable test accuracy of 93.98%
Boundary Segmentation of Vascular Images in Fourier Domain Doppler Optical Coherence Tomography Based on Deep Learning
Authors: Wu Chuanchao , Wang Zhibin , Xue Peng , Liu Wenyan
Published: June 2024

Microscopic and ultra-microscopic vascular sutures are indispensable in the surgical procedures such as arm transplantation and finger reattachment. The state of the blood vessels after suturing, such as vascular patency, narrow, and blocked, determines the success rate of the operation. If we can grasp the golden window period after blood vessel suture and before muscle tissue suture to achieve accurate and objective assessment of blood vessel status, it can not only reduce medical costs but also improve social benefits. Doppler optical coherence tomography enables high-speed, high-resolution imaging of biological tissues, especially microscopic and ultra-microscopic blood vessels. Using Doppler optical coherence tomography to image the sutured blood vessels, not only the three-dimensional structure of the blood vessels, but also the blood flow information can be obtained. By extracting the contour of blood vessel wall and the contour of blood flow area, the three-dimensional shape of blood vessel can be reconstructed in three dimensions, which provides parameter support for the assessment of blood vessel status. In this work, we propose a neural network-based multi-classification deep learning model that can simultaneously and automatically extract blood vessel boundaries from Doppler OCT vessel intensity images and the contours of blood flow regions from corresponding Doppler OCT vessel phase images. Compared with the traditional random walk segmentation algorithm and cascade neural network method, the proposed model has better performance. This method is easier to realize system integration and has great potential for clinical evaluation. It is expected to be applied to the evaluation of microscopic and ultra-microscopic vascular status in microvascular anastomosis.
An Examination of the Very First Polarimetric X-ray Observations of Radio-quiet Active Galactic Nuclei
Authors: Marin Frédéric , Gianolli Vittoria Elvezia , Ingram Adam , Kim Dawoon E , Marinucci Andrea , Tagliacozzo Daniele , Ursini Francesco
Published: June 2024

Active galactic nuclei (AGNs), either radio-quiet or radio-loud, had never been observed in X-ray polarized light until the advent of the Imaging X-ray Polarimetry Explorer (IXPE [1]) in the end of 2021. This satellite opened a new observational window for studying supermassive black holes and their complex environment. In this regard, radio-quiet AGNs are probably better targets than radio-loud objects to probe accretion processes, due to the lack of synchrotron emission from jets that can dilute the polarized signal from the central engine. Their relatively clean environment not only allows to detect and measure the X-ray polarization originating from the hot corona responsible for X-ray emission, but also to assess the geometry of the media immediately surrounding the supermassive black hole. Such geometrical measurements work just as well for characterizing the corona morphology in pole-on AGNs as it does for determining the three-dimensional shape of the circumnuclear cold obscurer (the so-called torus) in edge-on AGNs. In this review paper, we will return to each of the observations made by IXPE so far in the field of radio-quiet AGNs and highlight the fundamental contribution of X-ray polarimetry to our understanding of how light is emitted and how matter is shaped around supermassive black holes.
Does ChatGPT Help Novice Programmers Write Better Code? Results from Static Code Analysis
Authors: Haindl Philipp , Weinberger Gerald
Published: June 2024

In the rapidly evolving landscape of AI-supported programming education, there's a growing interest in leveraging such tools to support students helping about what good code makes out. This study investigates the impact of ChatGPT on code quality among part-time undergraduate students enrolled in introductory Java programming courses. With no prior Java experience, students from two separate groups completed identical programming exercises emphasizing coding conventions and code quality. Utilizing static code analysis tools, we assessed adherence to a common coding convention ruleset and calculated cyclomatic and cognitive complexity metrics for submitted code. Our comparative analysis highlights significant improvements in code quality for the ChatGPT-assisted group (treatment group), with marked reductions in rule violations and both cyclomatic and cognitive complexities. Specifically, the treatment group demonstrated greater adherence to coding standards, with fewer violations across several rules, and produced code with lower complexity. These results suggest that ChatGPT can be a valuable tool in programming education, aiding students in writing cleaner, less complex code and better adhering to coding conventions. However, the study's limitations, including the small sample size and the novice status of the participants, necessitate further research with larger, more diverse populations and in different educational contexts.
Impact of Most Promising Ebola Therapies on Survival: A Secondary Analysis during the Tenth Outbreak in the Democratic Republic of Congo
Authors: Kikwango Esther Mamu , Akilimali Pierre Z , Tran Nguyen Toan Toan , Mbala Placide K , Ahuka Steve M , Muyembe Jean Jacque T
Published: June 2024

Abstract:
Background: MAb114, REGN-EB3, Remdesivir, and ZMapp, which are monoclonal antibody-based treatments, have been compared and shown to be promising therapies against the Ebola Virus Disease (EVD). There has been no comparison between these med-ications and standard treatment (without antiviral). Our study aimed to examine the con-tribution of each regimen compared to standard treatment on the survival of EVD patients and assess whether this association was modified by EVD vaccination (rVSV-ZEBOV Ebola vaccine) status.
Methodology: We performed a secondary analysis of data obtained from four EVD treatment centers located in Katwa, Mangina, Butembo, and Beni in the North Kivu region. The main outcome measure was mortality within a 28-day period. A Cox model was used to identify predictors of survival in hospitalized EVD patients.
Results: Vaccinated EVD patients were 1.7 times less likely to die compared to unvac-cinated patients (3.70 days vs. 5.00 days; p=0.0002). Delaying care and treatment at EVD treatment centres increased mortality risk by 5% for each day following symptom onset. Compared to the standard treatment group, adjusted mortality rates were significantly re-duced in the groups receiving MAb114 (0.29, p
Machine Learning (ML) Models to Enhance the Berlin Questionnaire (BQ) Detection of Obstructive Sleep Apnea (OSA) at-Risk Patients
Authors: Conte Luana , De Nunzio Giorgio , Giombi Francesco , Lupo Roberto , Arigliani Caterina , Leone Federico , Salamanca Fabrizio , Petrelli Cosimo , Angelelli Paola , De Benedetto Luigi , Arigliani Michele
Published: June 2024

Objective: With just ten questions, the Berlin questionnaire (BQ) stands out as one of the simplest and most widely implemented non-invasive screening tools for detecting subjects at high risk for Obstructive Sleep Apnea (OSA), a still underdiagnosed syndrome characterized by partial or complete obstruction of the upper airways during sleep. The main aim of this study was to enhance the diagnostic accuracy of the BQ through Machine Learning (ML) techniques. Methods: A ML classifier (hereafter, ML-10) was trained using the ten questions of the standard BQ. A simplified variant of the BQ, BQ-2, which comprises only two questions out of the total of ten, was also assessed in a ML context. A 10-fold cross validation scheme was used. Ground truth was provided by the Apnea-Hypopnea Index (AHI) measured by Home Sleep Apnea Testing. Model performance was determined comparing ML-10 and BQ-2 with the standard BQ by the Receiver Operating Characteristic Curve (ROC), Area Under the Curve (AUC), sensitivity, specificity, and accuracy. Results: ML-10 demonstrated superior performance in predicting the risk for OSA compared to the standard BQ and was also capable in classifying OSA with two different AHI thresholds (AHI>=15, AHI>=30), typically used in clinical practice. Remarkably, BQ-2 was also better in sensibility to assess moderate to severe OSA (AHI≥ 15) compared to the ML-10. Conclusions: The study underscores the importance of integrating ML techniques for early OSA detection, suggesting a direction for future research to improve diagnostic processes and patient outcomes in sleep medicine.
Effect of the Wing Morphology and Structural Form on the Flexible Hovering Flapping Wing
Authors: Yang XiaoJun , Luo Yang , Wang Wei , Lang XinYu , Du ZhangRui
Published: June 2024

Flapping wing aircraft represents a new frontier in biomimetic aviation. Researchers have developed various flapping wing aircraft intending to harness their high aerodynamic efficiency to enhance flight performance. However, current flapping wing designs still have differences in morphology and structure forms compared to real bird wings. These differences may contribute to the key problem of low lift generation in flapping wing aircraft while hovering. Hence, this paper aims to find the influence of morphology and to overcome the aerodynamic efficiency problems. By using fluid-structure interaction analysis, this study investigates the influence of variation in wing area, and aspect ratio. The results show that increasing the wing area will promote the flexible deformation and passive twist of the flapping wing, resulting in a 173.7% increase in lift coefficient. However, this also leads to increased structural stress that must be taken into consideration. Additionally, as the aspect ratio increases, total deformation and tip deformation also increase; lower aspect ratios result in a more pronounced passive twist on the wing surface (84.4% higher). Moreover, this study has designed different wing structure layouts. With different rib distributions, the passive twist, stress concentration between ribs and at rib joints, maximum stress values at the root of the wing spar, and fluctuations in stress curves are influenced. Based on the result of wing parameters and structure layout, this study proposed a flapping wing structure design with efficient aerodynamic performance. The results highlight the influence of the key parameters of wing design and lay the theoretical groundwork for future research endeavors.
Liquid Biopsy in the Clinical Management of Cancers
Authors: Yin Ho Ho , See Chung Kei , Ming Kan Chau , Wong Sze Chuen Cesar
Published: June 2024

Liquid biopsy, a non-invasive diagnosis that examines circulating tumor components in body fluids, is increasingly used in cancer management. An overview of relevant literature emphasizes the current state of liquid biopsy applications in cancer care. Liquid biopsy, particularly circulating tumor DNA (ctDNA), circulating tumor RNAs (ctRNA), circulating tumor cells (CTCs), extracellular vesicles, and other cell-free nucleic acids, offers promising opportunities for early cancer diagnosis, treatment selection, monitoring, and disease assessment. The implementation of liquid biopsy in precision medicine has shown significant potential in various cancer types, including lung cancer, colorectal cancer, breast cancer, and prostate cancer. Advances in genomic and molecular technologies, such as next generation sequencing (NGS) and digital polymerase chain reaction (dPCR) have expanded the utility of liquid biopsy, enabling the detection of somatic variants and actionable genomic alterations in tumors. Liquid biopsy has also demonstrated utility in predicting treatment responses, monitoring minimal residual disease (MRD), and assessing tumor heterogeneity. Nevertheless, standardizing liquid biopsy techniques, interpreting results, and integrating them into clinical routine remain challenges. Despite these challenges, liquid biopsy has significant clinical implications in cancer management, offering a dynamic and non-invasive approach to understanding tumor biology and guiding personalized treatment strategies.
Photoinactivation of Mycobacterium tuberculosis and Mycobacterium smegmatis by Near-Infrared Radiation Using a Trehalose-Conjugated Heptamethine Cyanine
Authors: Kozobkova Natalia V. , Samtsov Michael P. , Lugovski Anatol P. , Bel’ko Nikita V. , Tarasov Dmitri C. , Kaprelyants Arseny S. , Savitsky Alexander P. , Shleeva Margarita O.
Published: June 2024

The spread of multidrug-resistant mycobacterium strains requires the development of new approaches to combat diseases caused by these pathogens. For that, photodynamic inactivation (PDI) is a promising approach. In this study, a tricarbocyanine (TCC) is used for the first time as a near-infrared (740 nm) activatable PDI photosensitizer to kill mycobacteria with deeper light penetration. For better targeting, a novel tricarbocyanine dye functionalized with two trehalose units (TCC2Tre) is developed. The photodynamic effect of the conjugate against mycobacteria, including Mycobacterium tuberculosis, is evaluated. Under irradiation, TCC2Tre causes more effective killing of mycobacteria compared to the photosensitizer without trehalose conjugation, with 99.99% dead vegetative cells of M. tuberculosis and M. smegmatis. In addition, effective photoinactivation of dormant forms of M. smegmatis is observed after incubation with TCC2Tre. Mycobacteria treated with TCC2Tre are more sensitive to 740 nm light than the Gram-positive Micrococcus luteus and the Gram-negative Escherichia coli. For the first time, this study demonstrates the possibility of in vitro PDI of mycobacteria including the fast-growing M. smegmatis and the slow-growing M. tuberculosis using near-infrared activatable photosensitizers. These findings are useful for the development of new efficient alternatives to antibiotic therapy.
Implementation of the mRNA-Lipid Nanoparticle Technology in Atlantic Salmon (Salmo salar)
Authors: Dahl Lars Ole Sti , Hak Sjoerd , Braaen Stine , Molska Alicja , Rodà Francesca , Parot Jeremie , Wessel Øystein , Fosse Johanna Hol , Bjørgen Håvard , Borgos Sven Even , Rimstad Espen
Published: June 2024

Background: The study was conducted to investigate if the mRNA vaccine technology could be adapted for the ectothermic vertebrate Atlantic salmon (Salmo salar). The lipid nanoparticle (LNP) technology has been developed and optimized for mRNA vaccines in mammals, stabilizing mRNA and facilitating delivery into cells. However, its utility at the temperature and specific biological environment in ectotherms remains unclear. In addition, it is unknown if modified mRNA containing non-canonical nucleotides can correctly translate in salmonid cells. Methods: We used an mRNA transcript coding for enhanced green fluorescence protein, flanked by the untranslated regions of the hemagglutinin-esterase gene of infectious salmon anemia virus, and a 120-base-long poly(A) tail. The mRNA was generated by in vitro transcription where uridine residues were replaced with N1-methyl-pseudouridines, and then encapsulated in LNPs. Results: When transfected into the salmonid cell line CHH-1, the mRNA-LNP construct induced expression of EGFP. Furthermore, when mRNA-LNPs were injected intramuscularly into salmon, in vivo protein expression was demonstrated by immunohistochemistry. EGFP was observed in cells infiltrating the space between the muscle cells in a focal inflammatory response. Conclusion: The results indicate that the N1-methyl-pseudouridine modified mRNA encapsulated in LNPs can be used to express antigens of interest in salmonid fish.
The Interactive Digital Media as a Scenography
Authors: Hilal Riham Mohamed
Published: June 2024

Interactive Digital Media have become the most important pillars on which contemporary 21st century scenography is based, allowing for the use of many modern digital media as scenographic elements. With the steady development of digital arts, particularly digital animation, it has become a key role as a 21st century in presenting their theatrical visions. My own issue is the use of digital Media as an Interactive scenographic element, as evidenced by the design of several spatial environments within the framework of an idea and a dynamic scenario that interacts with the Several Scenes of the theatrical Performances and is displayed on screen walls or dropped on thematic elements, resulting in a type of interaction between them and the Scenic Design. My project includes instances of models exhibiting the link of designs to theme composition on stage, such as works utilized in plays, musical/motion drama, and event performances . The design used music synced with digital animated media designs as a scenographic element to reinforce the overall visual picture. The study paper examines a theory of my own project, in which I offer a dynamic exhibition of full-back digital settings in rhythm with the music, suited to its movement and the character of the performance, to be employed as a Scenographic element at a Proscenium Theater (12W x 10D x 7H).
An Improved Method to Identify Built-Up Areas of Urban Agglomerations in Eastern and Western China Based on Multi-source Data Fusion
Authors: Lu Xiaoyi , Yang Guang , Chen Shijun
Published: June 2024

The rapid urbanization in China has significantly contributed to the vast expansion of urban built-up areas. Precisely extracting and monitoring these areas is crucial for understanding and optimizing the developmental process and spatial attributes of smart, compact cities. However, most existing studies tend to focus narrowly on a single city or global scale with a single dimension, often ignoring mesoscale analysis across multiple urban agglomerations. In contrast, our study employs GIS and image processing techniques to integrate multi-source data for the identification of built-up areas. We specifically compare and analyze two representative urban agglomerations in China: the Yangtze River Delta (YRD) in the east and the Chengdu-Chongqing (CC) region in the west. We use different methods to extract built-up areas from socio-economic factors, natural surfaces, and traffic network dimensions. Additionally, we utilize a high-precision built-up area dataset of China as a reference for verification and comparison. Our findings reveal several significant insights: (1) The multi-source data fusion approach effectively enhances the extraction of built-up areas within urban agglomerations, achieving higher accuracy than previously employed methods. (2) Our research methodology performs particularly well in the CC urban agglomeration. The average precision rate in CC is 96.03%, while the average precision rate in YRD is lower at 80.33%. This study provides an objective and accurate assessment of distribution characteristics and internal spatial structure of built-up areas within urban agglomerations. This method offers a new perspective for identifying and monitoring built-up areas in Chinese urban agglomerations.
Advancing Fast Frequency Response Ancillary Services in Renewable-Heavy Grids: A Global Review of Energy Storage-Based Solutions and Market Dynamics
Authors: Varhegyi Gergo , Nour Mutasim Ibrahim
Published: June 2024

This review paper addresses the growing challenges and developments in frequency control within power systems influenced by increasing penetration of renewable energy sources. It evaluates the advancements and limitations of renewable-based control technologies and explores the critical role of diverse energy storage technologies in providing fast frequency response ancillary services. Through a comprehensive analysis of global literature, this paper categorizes energy storage solutions according to their efficacy in meeting fast frequency response demands and potential for revenue generation. It reveals significant gaps in current research, which predominantly focuses on battery energy storage systems and microgrid applications, with insufficient attention to grid-scale storage solutions and innovative energy storage technologies. This analysis identifies a lack of detailed technical simulations and hybrid storage models for frequency control, as well as a minimal exploration of the environmental benefits, particularly in terms of carbon dioxide emission reductions, associated with deploying new energy storage technologies in ancillary service markets. The paper concludes by highlighting the necessity for further research incorporating detailed techno-economic evaluations and carbon dioxide reduction potential of modular, scalable energy storage technologies, facilitated by advanced network simulation models and comprehensive market analysis.
Practical Path for Developing “New Quality Productive Forces” Driven by the Digital Economy in China
Authors: Qing Zhao , Bing Chen
Published: June 2024

In China, "new quality productive forces" have become an important focus for high-quality development; accelerating this development is an important task for the Chinese government in 2024. Such development relies on the traction of the digital economy. In view of this, developing “new quality productive forces” driven by the Chinese digital economy requires focusing on blocking points, such as the insufficient vitality of data, inadequate algorithmic regulation, the uneven distribution of computing power resources and the immature market environment. In order to dredge these blocking points, it is necessary to establish basic rules on data, strengthening algorithm supervision, building a national integrated computing power network, and optimizing the market environment.
Beyond the Valve: Incidence, Outcomes, and Modifiable Factors of Acute Kidney Injury in Patients with Endocarditis Undergoing Valve Surgery — A Retrospective, Single-Center Study
Authors: Dinges Christian , Dienhart Christiane , Gansterer Katja , Rodemund Niklas , Rezar Richard , Steindl Johannes , Huttegger Raphael , Kirnbauer Michael , Kalisnik Jurij Matija , Kokoefer Andreas Stefan , Demirel Ozan , Seitelberger Rainald , Hoppe Uta , Boxhammer Elke
Published: June 2024

Background/Objectives: Infectious Endocarditis often requires surgical intervention, with postoperative acute kidney injury (AKI) posing a significant concern. This retrospective study aimed to investigate AKI incidence, its impact on short-term mortality, and identify modifiable factors in patients with endocarditis scheduled for valve surgery. Methods: This single center study enrolled 130 consecutive endocarditis patients from 2013 to 2021 undergoing valve surgery. Creatinine levels were monitored pre- and postoperatively, and AKI was defined by Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Patient demographics, comorbidities, procedural details, and complications were recorded. Primary outcomes included AKI incidence, the relevance of creatinine levels for AKI detection, and the association of AKI with 30-, 60- and 180-day mortality. Modifiable factors contributing to AKI were explored as secondary outcomes. Results: Postoperatively, 35.4% developed AKI. The highest creatinine elevation occurred on the 2nd postoperative day. Best predictive value for AKI was a creatinine level of 1.35 mg/dl on the 2nd day (AUC: 0.901; sensitivity: 0.89, specificity: 0.79). Elevated creatinine levels on the 2nd day were robust predictors for short-term mortality at 30, 60 and 180 days postoperatively (AUC ranging from 0.708 to 0.789). CK-MB levels at 24 hours postoperatively and minimum hemoglobin during surgery were identified as independent predictors for AKI in logistic regression. Conclusions: This study highlights the crucial role of creatinine levels in predicting short-term mortality in surgical endocarditis patients. A specific threshold (1.35 mg/dl) provides a practical marker for risk stratification, offering insights for refining perioperative strategies and optimizing outcomes in this challenging patient population.
Research on Operation Optimization of Fluid Sampling in Wireline Formation Testing with Finite Volume Method
Authors: Wu Lejun , Wang Junhua , Liu Haibo , Huang Rui , Xie Huizhuo , Li Xiaodong , Li Xuan , Liu Jinhuan , Zhao Changjie
Published: June 2024

Wireline Formation Testing is an important technique in the oil field of exploration and development. Not only it can make real fluid samples of the formation directly obtained to know exactly oil existed in formation or not; but it can also show flowing pressure change to see the production capacity of the formation. So it is important measurement for formation evaluation during the drilling process and supports for activities of the exploration and development in the oil field. A numerical simulation model in this article is researched and established based on the Finite Volume Method with considering the influence of sensitive parameters such as reservoir heterogeneity, probe suction area, and mud-filtrate invasion depth during the drilling. The model is capable to design and evaluate for formation fluid sampling operations with calculating hydrocarbon content and flowing pressure. Furthermore, through case application, the performance and effect in the process of Wireline Formation Testing was demonstrated. The results indicate that this technology can be served as an effective auxiliary tool for fluid sampling operations with the function of optimizing fluid sampling measures. It can improve the accuracy of predicting indicators such as hydrocarbon content and breakthrough time during the sampling process. This study provides important backups and technical guidance for professionals in geological exploration and oilfield development.
Enhancing Financial Intelligence: AI Robo-Advisors for Strategic Investment Decisions
Authors: Needhi Jeyadev , G Ram Prasath , K Mohamed Riffath , S Manokar
Published: June 2024

The increasing popularity of Robo-Advisors highlights the need for sophisticated systems combining big data analytics and deep learning for portfolio optimization. Despite their potential, these AI-driven platforms face notable challenges such as financial data inaccuracies and the risk of overfitting in deep learning models. Overcoming these hurdles requires a concerted effort to enhance reliability and performance. To tackle these challenges effectively, it is imperative to prioritize real-time data integration while minimizing reliance on historical data. By adopting this approach, Robo-Advisors can better adapt to dynamic market conditions, enabling them to provide informed and timely investment recommendations. This proactive stance not only ensures computational efficiency but also fosters investor confidence in the platform's ability to navigate evolving market dynamics. In conclusion, by continually refining data integration methods and reducing dependencies on historical data, Robo-Advisors can offer more accurate and timely recommendations. This not only enhances the overall investor experience but also upholds ethical standards in automated investment platforms.
Semantic Visual SLAM Algorithm Based on Improved DeepLabV3+Model and LK Optical Flow
Authors: Li Yiming , Wang Yize , Lu Liuwei , Guo Yiran , An Qi
Published: June 2024

Aiming at the problem that dynamic targets in indoor environments lead to low accuracy and large errors in the localization and position estimation of visual SLAM systems and the inability to build maps containing semantic information, a semantic visual SLAM algorithm based on the semantic segmentation network DeepLabV3+ and LK optical flow is proposed based on ORB-SLAM2 system. First, the dynamic target feature points are detected and rejected based on the lightweight semantic segmentation network DeepLabV3+ and LK optical flow method. second, the static environment occluded by the dynamic target is repaired using the time-weighted multi-frame fusion background repair technique. Lastly, the filtered static feature points are used for feature matching and position calculation. Meanwhile, the semantic labeling information of static objects obtained based on the lightweight semantic segmentation network DeepLabV3+ is fused with the static environment information after background repair to generate dense point cloud maps containing semantic information, and the semantic dense point cloud maps are transformed into semantic octree maps using the octree spatial segmentation data structure. The localization accuracy of the visual SLAM system and the construction of the semantic maps are verified using the TUM RGB-D widely used dataset and real scene data, respectively. The experimental results show that the proposed semantic visual SLAM algorithm can effectively reduce the influence of dynamic targets on the system, has a higher localization accuracy, and compared with other advanced algorithms, such as DynaSLAM, has the highest performance in indoor dynamic environments while considering both localization accuracy and real-time performance. In addition, semantic maps can be constructed so that the robot can better understand and adapt to the indoor dynamic environment.