bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical Modelling of Vortex-Based Superconducting Memory Cells: Dynamics and Geometrical Optimization
Authors: Skog Aiste , Hovhannisyan Razmik A. , Krasnov Vladimir M.
Published: August 2024

The lack of dense random-access memory is one of the main obstacles to the development of digital superconducting computers. It has been suggested that AVRAM cells, based on the storage of a single Abrikosov vortex — the smallest quantized object in superconductors — can enable drastic miniaturization to the nanometer scale. In this work, we present numerical modeling of such cells using time-dependent Ginzburg-Landau equations. The cell represents a fluxonic quantum dot containing a small superconducting island, an asymmetric notch for vortex entrance, a guiding track, and a vortex trap. We determine the optimal geometrical parameters for operation at zero magnetic field and the conditions for controllable vortex manipulation by short current pulses. We report ultra-fast vortex motion with velocities more than an order of magnitude faster than those expected for macroscopic superconductors. This phenomenon is attributed to strong interactions with the edges of a mesoscopic island, combined with the nonlinear reduction of flux-flow viscosity due to nonequilibrium effects in the track. Our results show that such cells can be scaled down to sizes comparable to the London penetration depth, ∼100 nm, and can enable ultrafast switching on the picosecond scale with ultra-low energy per operation, ∼10−19 J.
How Different Forms of Knowledge Transfer at Workplace Are Related to Self-Rated Work Performance?
Authors: Stoyanova Stanislava , Giannouli Vaitsa , Miteva Silviya , Ivantchev Nikolay
Published: August 2024

Successful work performance is an important part of everyday functioning. Different factors could contribute to efficiency at the workplace. Two studies aim to establish how different forms of knowledge transfer at the workplace are related to self-rated work performance and whether better work performance is related to mindfulness as an aspect of cognitive functioning. The participants were 742 working Bulgarians in Study 1 and 259 workers in Study 2. Ten scales were used in Study 1, measuring different forms of knowledge transfer and self-rated work performance, and two scales were used in Study 2, measuring self-assessed work performance and mindfulness. The results revealed that higher self-assessment of work performance correlated positively but weakly with the sharing of tacit knowledge at the workplace, sharing knowledge with colleagues in dyads, work climate encouraging mastership, sharing knowledge in teams, knowledge transfer by means of cooperation between different generations, institutionalized transfer of knowledge, knowledge receiving, and estimated effectiveness of participation in supervision as a supervisee. Some forms of knowledge transfer (sharing of tacit knowledge and sharing knowledge with colleagues in dyads) seemed more closely related to self-assessed work performance than others. Self-assessment of work performance did not correlate statistically significantly with performance motivational climate at work. The different forms of knowledge transfer correlated with each other. Better work performance is related to better cognitive functioning, as the second study of 259 workers additionally revealed that higher self-assessment of work performance correlated with better self-awareness measured by the Mindful Attention Awareness Scale, i.e., more attention focused on own thoughts, emotions, and needs, i.e., on what is happening right now. Interconnectedness between the different forms of knowledge transfer indicates that stimulating one kind of knowledge transfer could also stimulate many other forms of knowledge transfer, but this may happen only when organizations support a mastery-motivated climate at work. Established connections between the different forms of knowledge transfer and self-rated work performance, as well as between self-assessed work performance and mindfulness, suggest that good cognitive functioning accompanied good functioning, and both may be facilitated by knowledge transfer at the workplace.
Decarbonizing Tall Building Structures: Implementing Machine Learning At The Early-stage Of Design Process
Authors: Askarinejad Peyman , Behnia Behzad
Published: August 2024

The construction of tall buildings generates a high spatial and temporal concentration of greenhouse gas (GHG) emissions. Research studies have shown that as building height increases, more resources per floor area are required to withstand the increasing effects of lateral loads (wind and earthquake). This has major implications for the environmental performance of tall buildings since the Embodied GHG Emissions (EGHGE) of structural systems tend to represent the greatest portion of the life cycle GHG emissions of tall buildings. This study presents a data driven-based approach for decarbonization of tall buildings and evaluates the significant impact of material types (concrete, steel, and timber), concrete strength, and structural systems relative to a building's height on the EGHGE associated with tall buildings. In mitigating the effects of climate change, this research implements machine learning (ML) algorithms as an early-stage design tool to facilitate the choice of materials, and structural systems for tall buildings. This work considers a wide range of high-rise buildings with four different types of lateral structural systems (Braced-Frame system, Outrigger-Belt system, Shear Wall system, and Tubular system), four different types of construction materials (concrete, steel, hybrid, and timber), varying heights (ranging from 10 to 100 stories), and various concrete materials with different compressive strength ranging from 32 to 90 MPa. Data gathered from more than 100 existing tall building projects along with the data obtained from finite element analysis of 120 high-rise buildings models were utilized to train various ML regression algorithms: Decision Tree, Support Vector Machine, Polynomial Regression, and Elastic-Net Regularized Regression. The performance of ML models was carefully assessed, and the best prediction model was selected to estimate the total amount of CO2 emissions for high-rise buildings. Results indicate that hybrid structures with the Out-Rigger-Belt system exhibit the lowest carbon emission (110 kg/m2) compared to other structural types and systems.
Fractional Flow Reserve Implications for Clinical Decision Making in Coronary Artery Disease
Authors: Grib Andrei , Abras Marcel , Surev Artiom , Grib Livi
Published: August 2024

Fractional flow reserve (FFR) is regarded as the gold standard for assessing the functional significance of coronary artery lesions, yet it remains underutilized in clinical practice. Our objective was to investigate whether FFR results have the potential to alter treatment decisions for coronary lesions compared to visual assessments of angiographic images made by three operators at a high-volume interventional center. In this retrospective study, we aimed to reassess the angiographic images of 63 patients presenting with chronic coronary syndrome (n=39, 61.9%) and acute coronary syndrome (n=24, 38.1%) who underwent FFR. Three experienced interventional cardiologists (with >300 PCI procedures per year) reevaluated, blinded to FFR results, 105 ambiguous lesions in 63 patients to determine angiographic significance and treatment strategy. The observers reached a concordant agreement (≥2 operators made the same decision) to perform PCI in 60 (57.1%) of the lesions based on angiographic evaluation. Interestingly, 9 (15%) of these lesions were functionally non-significant (FFR >0.80). The observers agreed to defer PCI in 45 (42.9%) of the lesions; however, 4 (8.9%) of these were functionally significant (FFR ≤0.80) and required PCI. Thus, inter-observer concordance in visual-guided therapeutic decision-making is variable and not always confirmed by the functional significance of coronary lesions.
How Helpful May Be a CRISPR/Cas-Based System for Food Traceability?
Authors: Farinati Silvia , Devillars Aurélien , Vannozzi Alessandro , Scariolo Francesco , Palumbo Fabio , Barcaccia Gianni
Published: August 2024

Crops obtained by genome editing (GE) technologies represent a notable and disruptive shift from genetically modified or transgenic plants, outpacing public perception and regulatory frame-works. Multiple aspects of GE are contributing to the advancement of modern agriculture, in-fluencing the market structure by introducing specific changes within the existing genetic blue-print of an organism. Generally, the GE toolbox includes distinct technologies able to incorporate site-specific and pre-determined genomic modifications, exploiting well-established genetic modification strategies. For these reasons, GE-derived approaches are considered new plant breeding methods, known as new breeding techniques (NBTs). Particularly, CRISPR/Cas-based technologies represent a considerable improvement over prior techniques, being more precise, accurate and straightforward for targeted gene editing, in a reliable and reproducible way, with numerous applications. CRISPR/Cas system exploitation for non-editing purposes has also been widely documented, ranging from cell imaging to expression regulation and DNA assembly. Recently, CRISPR/Cas systems have been employed for target detection and could be used to ef-ficiently identify multiple organic chemicals. High-sensitivity and high-specificity detection are two main points of the CRISPR/Cas technology, without needing complex expertise or technical pipelines. This manuscript aims to provide an overview of the main advances of CRISPR/Cas-based systems into new frontiers of non-editing. The associated implications (e.g., molecular traceability) and their relative impacts are also presented and discussed.
RNAi-based Approaches to Control Mycotoxin Producers: Challenges and Perspectives
Authors: Stakheev Alexander A. , Taliansky Michael , Kalinina Natalia O. , Zavriev Sergey K.
Published: August 2024

Mycotoxin contamination of food and feed is a worldwide problem that needed to be addressed with highly efficient and biologically safe techniques. RNA interference (RNAi) is a natural mechanism playing an important role in different processes in eukaryotes, including regulation of gene expression, maintenance of genome stability, protection against viruses and others. Recently, RNAi-based techniques have been widely applied for the purposes of food safety and management of plant diseases, including those caused by mycotoxin-producing fungi. In this review, we summarize the current state-of-art of RNAi-based approaches for reducing aggressiveness of key toxigenic fungal pathogens and mycotoxin contamination of grain and its products. The ways of improving RNAi efficiency for plant protection and future perspectives of this technique, including progress in methods of double-stranded RNA production and its delivery to the target cells are also discussed.
Sustainability of Municipal Wastewater Treatment
Authors: Derco Jan , Guľašová Patrícia , Legan Maša , Zakhar Ronald , Žgajnar Gotvajn Andreja
Published: August 2024

The European Parliament had adopted legislative resolution of 10 April 2024 on the proposal for a directive of the European Parliament and of the Council concerning urban wastewater treatment. The reduction of pollution in discharged treated wastewater in the parameters of BOD5, total ni-trogen and total phosphorus was emphasized. Based on these results, it stated that the impacts on the quality of lakes, rivers and seas in the EU are visible and tangible. At the same time, it was emphasized that the sector of urban wastewater removal and treatment is responsible for 0.8% of the total electricity consumption and about 0.86% of all greenhouse gas emissions in the entire EU. Almost a third of these emissions could be prevented by improving the treatment process, better use of sewage sludge and increasing energy efficiency, as well as a higher rate of use of renewable resource technologies. It is also necessary to better integrate treatment processes into the circular economy. Sludge management and water reuse is sub-optimal as too many valuable resources are still being wasted. This review article is focused on sustainable municipal wastewater treatment, innovative and new wastewater treatment processes and technologies (combined and hybrid processes, Anammox, etc. and their use in practice with the aim of increasing environmental and energy efficiency and reducing the carbon footprint. The research is focused on the possibilities of increasing the efficiency of energy processing of sludge, reuse of nitrogen and phosphorus, sludge and reuse of treated wastewater.
The Arrest of Telegram CEO Pavel Durov: A Crossroad between Free Speech and Content Moderation through the Lens of the Harm Principle
Authors: DURAIVEL SAMUEL
Published: August 2024

The arrest of Pavel Durov, the CEO of Telegram, represents a critical moment in the ongoing discourse surrounding free speech and content moderation. This event exemplifies the tension between upholding individual liberties and addressing the potential societal harms caused by unregulated digital communication. This paper explores the implications of Durov’s arrest and Telegram’s stance on free speech through the lens of John Stuart Mill’s Harm Principle. The Harm Principle, as articulated in Mill’s seminal work On Liberty (1859), provides a valuable theoretical framework for examining the balance between individual freedom and societal protection. This paper argues that the application of the Harm Principle can offer a nuanced perspective on the ethical responsibilities of digital platforms like Telegram in the age of global communication.
Challenges in Maritime Cybersecurity Training and Compliance
Authors: Chupkemi Divine C. , Mersinas Konstantinos
Published: August 2024

The implementation of cybersecurity standards and directives in the maritime sector plays a crucial role in protecting critical maritime infrastructures from cyber threats. The level of protection depends heavily on humans. However, the effectiveness of cybersecurity training and compliance programs, an essential component of these standards, is often hindered by challenges related to the sector’s environment, including the established technologies, practices, and norms. This paper aims to identify these challenges through a literature review and set the basis for more effective human risk minimisation, responses, and training. We identify 18 challenges and validate them with an online survey (N=205) capturing real-world perspectives from maritime-related stakeholders. Our findings contribute to enhancing the effectiveness of maritime cybersecurity training and compliance programs, ultimately strengthening the maritime cybersecurity posture.
‘TLDetect’ – AI-based Application for the Detection and Correction of Anomalous TLD Glow Curves
Authors: Amit Gal , Revayev Oran , Vagner Roy
Published: August 2024

This research reviews a novel artificial intelligence (AI) based application called ‘TLDetect’, which filters and classifies anomalous glow curves (GCs) of thermoluminescent dosimeters (TLDs). Until recently, GCs review and correction in the lab were performed using an old in-house software, which uses Microsoft Access database and allows the laboratory technician to manually review and correct almost all GCs without any filtering. The newly developed application ‘TLDetect’ uses a modern SQL database and filters out only the necessary GCs for technician review. TLDetect first uses an Artificial Neural Network (ANN) model to filter out all regular GCs. Afterwards, it automatically classifies the rest of the GCs into five different anomaly classes. These five classes are defined by GCs typical patterns, i.e. high noise at either low or high temperature channels, untypical GC width (either wide or narrow), shifted GCs whether to the low or to the high temperatures, spikes, and the last class contains all other unclassified anomalies. By this automatic filtering and classification, the algorithm substantially reduces the amount of technician’s time of reviewing the GCs and makes the external dosimetry laboratory dose assessment process more repeatable, accurate and fast. Moreover, a database of GCs class anomalies distribution over time is saved along with all their relevant statistics, which can later assist with preliminary diagnosis of TLD reader hardware issues.
Deciphering Epigenetic Mechanisms: The Role of DNA Methylation in Driving Phenotypic Diversity and Evolutionary Adaptation in Chickpea (Cicer arietinum)
Authors: Odah Mohammad
Published: August 2024

This study explores the critical role of DNA methylation in shaping phenotypic diversity and driving evolutionary adaptation in chickpea (Cicer arietinum). By employing whole-genome bisulfite sequencing and advanced genomic techniques, we analyzed DNA methylation patterns across various chickpea cultivars, focusing on key adaptive traits such as drought tolerance, disease resistance, seed size, and flowering time. Our results revealed significant methylation changes associated with these traits, providing novel insights into the epigenetic regulation of gene expression and its impact on phenotypic variation. Additionally, we investigated the dynamic responses of DNA methylation under different environmental stresses, highlighting the plasticity of the chickpea epigenome. This research not only enhances our understanding of the epigenetic mechanisms underlying plant evolution but also opens up new avenues for developing epigenetic-based strategies for crop improvement.
Study on the Spatial Layout Patterns of Townhouses: A Case Study of Kaohsiung City
Authors: Tseng Cheng Chi , Huang Long sheng , Huang Chung Fah
Published: August 2024

Due to their independent structure, piping, and access, townhouses offer great flexibility in floor plan changes and high spatial autonomy, making them the mainstream housing type in Taiwan. This study focuses on row houses and examines 2022 completion cases in Kaohsiung City. It collects floor plans from 14 newly constructed buildings, totaling 227 units, and analyzes spatial dimensions including facade width, depth, habitable room, staircases, bathrooms, and total floor area for each case. The objective of this study is to examine the spatial layout of row houses in Kaohsiung City, with the aim of providing reference for future planning and design of such structures. The study resulted showed that 81.8% of the row houses analyzed have a total floor area per unit ranging from 136 to 192 m², a facade width between 4.1 and 6.38 meters, and a building depth from 7.67 to 12.68 meters. In addition, low negative correlation between facade width and total floor area, a high positive correlation between building depth and total floor area, and a moderate negative correlation between facade width and building depth. The spatial distribution within these houses includes 78% allocated to habitable room, 13.1% to staircases, and 8.7% to bathrooms. The total area of habitable room and bathrooms increases with the total floor area of the building. However, the total area of staircases remains almost constant as the area of habitable room increases. Furthermore, the most common location for staircase planning is the rear-right (RB) position, while the least common is the rear-left (LB) position. Among various staircase types, the C-shaped staircase has the largest average area per floor and the highest average proportion. Conversely, the I-shaped staircase has the smallest average area and the lowest average proportion. The U-shaped staircase is the most frequently planned, whereas the C-shaped staircase is the least frequently used.
Evaluation of Different Form Topical Anesthesia Agents in Dental Practice
Authors: Cantekin Kenan
Published: August 2024

Purpose: The aim of this study was to compare the topical anesthetic effect of a 10% atomized lidocaine spray and an EMLA cream at different time intervals using parameters of visual analogue scale (VAS) score and heart rate (HR).
Methods: The randomized split-month study included 30 patients (17 boys, 13 girls) aged 8.22 ± 1.8 years. Application of atomized lidocaine spray or cream was randomly used in the upper second premolar region. The parameters was measured before and at each needle insertion after 10,30,60 and 120 sec. Paired t -test and independent t-test were used for statistic analyses.
Results: Compared to the first applications (10 sec), atomized lidocaine and EMLA cream applications significantly decreased scores of VAS at the applications at 30 and 120 seconds, respectively. Despite atomized lidocaine showed early effect compared to EMLA, there were no significant differences in VAS scores between the atomized lidocaine and EMLA cream at the 60 and 120 seconds measurements. Although HR significantly increased at first anesthetic administration with the atomized lidocaine spray, HR significantly decreased at 30 and 120 seconds administrations.
Conclusion: Atomized 10% lidocaine-based topical anesthetics significantly reduced pain more rapidly and better than EMLA from needle pricks in the buccal mucosa. Therefore, atomized lidocaine topical anesthesia could be used as a substitute for EMLA cream before buccal anesthetic administration. On the other hand, further comprehensive studies are required to explore the effects of several doses of atomized lidocaine in various areas of the oral cavity.
From Attitudes to Outcomes: The Role of Crowdfunding Platforms in Achieving Digital Sustainability
Authors: Um Namhyun
Published: August 2024

The significance of digital sustainability in donation-based crowdfunding platforms lies in its ability to encourage environmentally aware and socially responsible practices in the sphere of online philanthropy. Fundraising has been revolutionized by the emergence of donation-based crowdfunding platforms. This study explores the various factors influencing individuals' attitudes towards these platforms, particularly focusing on perceived usefulness, ease of use, credibility, and self-efficacy. The study examines how these factors affect donation intentions and electronic word-of-mouth intentions, utilizing data from 326 college students. The findings confirm that perceived usefulness, ease of use, credibility, and self-efficacy play crucial roles in shaping attitudes. Furthermore, these attitudes significantly impact both donation intentions and electronic word-of-mouth intentions. Adjustments to the structural model highlight the interconnectedness of these factors, improving the model's accuracy. The results provide practical guidance for platform administrators, campaign creators, and stakeholders involved in online philanthropy, emphasizing the need for user-friendly designs, trust-building, and fostering user confidence for successful crowdfunding efforts.
The field assessment of quiescent egg populations of Aedes aegypti and Aedes albopictus during the dry season in Tapachula, Chiapas, Mexico, has the potential to significantly impact vector control strategies by providing insights into potential in-situ vector reinfestations
Authors: Navarro-Kraul José Ignacio , Vázquez Luis Alberto Cisneros , Paiz-Moscoso Keila Elizabeth , Danis-Lozano Rogelio , Barbosa-Davila Jesus A , Lopez-Monroy Beatriz , Dominguez-Galera Marco Antonio , Mis-Avila Pedro Christian , Sanchez-Casas Rosa M , Fernandez-Salas Ildefonso
Published: August 2024

The lack of a Dengue vaccine and pharmacological antiviral drugs has made Vector Control Programs the primary resource in the fight against arboviral diseases. Although Integrated Management and Control programs implement intense control measures for adult, pupal, larval, and breeding sites during outbreaks, there is a lack of studies to understand the role of the vector egg stage in disease dynamics. This study aimed to assess the dry season quiescent Aedes aegypti and Aedes albopictus egg populations in houses and backyards in the tropical city of Tapachula, southern Mexico. Two hundred fifty ovitraps were placed in 125 homes in the Las Americas neighborhood. A total of 7,290 eggs were collected from 211 (84.4%) ovitraps, with 4,031 (71.1%) identified as Ae—aegypti, and 1,636 (28.8%) as albopictus, respectively. Eighty-three larval sites were sampled with desiccated eggs during the dry season; most of them were described as trash-like because larvicides are only used for larger containers of 5-10 L. Evolutionary characteristics for the two species include rapid and delayed hatching of eggs, ambient-regulated quiescence, the ability of the embryo to survive for a more extended period intra-seasonally, and the sticking of egg walls to container walls. This demands urgent operational research to achieve successful egg-proof larval container methods.
Barriers and Recommendations for Establishing a COVID-19 Patient Registry in a Regional Setting in the Philippines
Authors: Dumancas Gerard , Generalao Oliver , Rivera Hans Carlo Eugenio , Zamora Pia Regina Fatima , Rico Jonathan Adam , Climacosa Fresthel Monica M. , Caoili Salvador Eugenio , de Castro Romulo
Published: August 2024

: The global impact of the COVID-19 pandemic has resulted in substantial morbidity and mortality rates. Consequently, there is a pressing need for clinical research focused on the prevention, diagnosis, and treatment of this disease. To comprehensively study the course of COVID-19 in the Philippine population, it is essential to have a comprehensive dataset that includes relevant treatment and diagnostic information. While individual patient reports related to the disease are available at various institutions in the Philippines, there is a need for a more extensive and representative database to facilitate robust analysis. The purpose of this review is to elucidate various challenges and opportunities as well as propose solutions for the development and implementation of a prospective COVID-19 patient registry within a regional context in the Philippines. The primary clinical objective of establishing this registry was to enhance the accuracy of disease diagnosis. In this review, we present a comprehensive explanation of the systematic rationale, design, and execution of a COVID-19 patient registry in the Western Visayas region of the Philippines. Based on this review, several factors exist that hinder the implementation of a COVID-19 patient registry in the regional setting in the Philippines including lack of funding, facilities, infrastructure, manpower, expertise, and unwillingness of some hospitals to pursue research. We also discussed herewith the proposed program implementation for the establishment of such registry in a regional setting in the Philippines.
Artificial Intelligence in Biotechnology Education: Evaluating the Effectiveness of Gemini and ChatGPT in Laboratory Training
Authors: Nguyen Jasmine , Nguyen Lilly , Huynh Khanh D
Published: August 2024

AI integration is becoming more important in today’s world and could potentially be very useful in the life sciences and biotechnology. This study evaluates the effectiveness of AI systems in teaching molecular cloning techniques to newcomers in molecular biology, focusing on a comparison between Gemini Advanced (powered by Gemini Ultra 1.0) and ChatGPT (GPT-4o). Molecular or DNA cloning is a lab technique for creating multiple copies of a specific DNA segment. It involves isolating the DNA fragment, inserting it into a vector, and introducing it into a host cell, typically bacteria, which then generates numerous copies of the DNA. This essential technique underpins genetic engineering, allowing for gene study, protein expression, and the creation of genetically modified organisms. The primary objective of this study was to assess whether individuals with limited laboratory experience could effectively acquire a specific molecular biology skill set solely through an AI system, rather than relying on the more traditional ‘learning by shadowing’ approach. Participants with limited lab experience completed these tasks using both Gemini and GPT-4o, and evaluated on quality of instructions, conciseness, scientific accuracy, and user satisfaction. Results indicated that both AI systems demonstrated strengths in delivering clear and comprehensive instructions, but in different ways. Gemini, although more interactive with images and diagrams lacked directness and had a harder time keeping past steps in its “memory”. On the other hand, GPT-4o was much more direct and concise in the steps listed and had more accurate results akin to what is performed in the lab. This study underscores the potential of AI-driven tools to simplify complex biotechnological procedures, making them accessible for learners at all levels.
Ubiquitin-Specific Protease 1 Promotes Bladder Cancer Progression by Stabilizing C-myc
Authors: Zhang Xia , Peng Peng , Bao Li-Wei , Zhang An-Qi , Yu Bo , Li Tao , Lei Jing , Zhang Hui-Hui , Li Shang-Ze
Published: August 2024

Background: Ubiquitination is an important post-transcriptional modification crucial for maintaining cell homeostasis. As a deubiquitination enzyme, ubiquitin-specific protease 1 (USP1) is associated with tumor progression; however, its role in bladder cancer is unknown. This study was aimed to analyze USP1 expression and study its roles in bladder cancer.
Methods: The web server GEPIA was used to analyze the USP1 expression. To explore USP1 function in bladder cancer, we constructed USP1-knockout cell lines in UMUC3 cells. A FLAG-USP1 (WT USP1) plasmid and a plasmid FLAG-USP1 C90S (catalytic-inactive mutant) used to overexpress USP1 in T24 cells. CCK8, colony formation, and transwell assays were used to assess cell viability, proliferation and migration. RNA sequencing (RNA-seq) and dual-luciferase reporter assays were performed to screen the pathway. Coimmunoprecipitation and immunofluorescence were used to explore the interaction between USP1 and c-MYC. Xenograft mouse model was used to study the role of USP1 in bladder cancer.
Results: USP1 expression is upregulated in human bladder cancer cells and correlated with poor patient prognosis. USP1 overexpression promoted cell proliferation, clone formation, and migration; this was attenuated by genetic ablation of USP1. Furthermore, we observed that USP1- deficiency inhibited tumor formation in vivo. Mechanistically, the c-MYC pathway was remarkably activated compared with the other pathways. Furthermore, USP1 could directly interact with c-MYC. and increase c-MYC stability depending on the catalytic activity of USP1.
Conclusions: Our results suggest that high expression of USP1 promotes bladder cancer progression by stabilizing c-MYC; hence, USP1 it may serve as a novel therapeutic target for treating bladder cancer.
Infective Endocarditis – Predictors of In-Hospital Mortality, 17 Years, Single-Center Experience in Bulgaria
Authors: Dobreva-Yatseva Bistra Vladimirova , Nikolov Fedya , Raycheva Ralitsa , Tokmakova Mariya Petkova
Published: August 2024

Background: Despite tremendous advances in medicine, infective endocarditis (IE) continues to be a challenge for physicians due to increasing morbidity and unchanged high mortality. Objectives: Our aim was to evaluate clinical outcomes in patients with IE and to identify predictors of in-hospital mortality. Material and methods: The study was retrospective, single-centered, and included 270 patients diagnosed with IE, for the period 2005-2021 (median age 65 (51–74), man 177 (65.6%). Results: Native IE (NVIE) was found in 180 (66.7%), prosthetic IE (PVIE) in 88 (33.6%) and cardiac device-related IE (CDRIE) in 2 (0.7%), significantly more in the non-survivors group. Healthcare associated IE (HAIE) was 72 (26.7%), the most common pathogen were Staphylococci and the proportion of Gram-negative bacteria (GNB) non-HACEK were significantly higher in non-survivor’s vs survivors (11 (15%) vs 9 (4.5%), p=0.004). Overall, early surgery was performed in 54 (20%) patients, with a significant difference between deceased/alive (3 (4.5%) vs 51 (25.1%, p=0.000). The all-cause in-hospital mortality rate was 24.8% (67). The risk factors identified that increased the risk of death were septic shock (OR – 83 1; 95% CI (17.0-405.2), p=0.000) and acute heart failure (OR –24.6; 95% CI (9.2-65.0), p=0.000). Early surgery (OR – 0.03, 95% CI (0.01-0.16), p=0.000) and low Charlson comorbidity index (OR – 0.85, 95% CI (0.74-0.98, p=0.026) in turn reduce this risk. Conclusion: We found that acute heart failure and septic shock are independent predictors of in-hospital mortality. Low Charlson comorbidity index and early surgery increased survival. Knowing the predictors of death would change the therapeutic approach to a more aggressive one and improve the near and long-term prognosis of patients with IE.
Design and On-Orbit Performance of Ku-Band Phase-Array SAR Payload System
Authors: Yan Wei , Tan Xiaomin , Wu Jiang , Yuan Mingze , Dang Hongxing , Chang Wujun
Published: August 2024

The current emphasis in the advancement of space-based synthetic aperture radar (SAR) is on lightweight payloads under 100kg with resolutions surpassing 1m. This focus is directed towards meeting the launch criteria for multiple satellites on a single rocket and cutting costs. This article discusses the creation and progress of a Ku-band SAR payload for the Taijing-4(03) Satellite, launched on January 23, 2024 accompanied by four other satellites. The SAR payload design was customized to meet the demands of a micro-nano satellite platform, resulting in a lightweight, flat design weighing less than 80kg, seamlessly integrated with the plate-shaped satellite platform. The article also introduces a beam optimization strategy for the phased array SAR antenna, significantly boosting the SAR system’s performance. The SAR payload provides various operating modes like slide-spot, strip, scan 1, scan 2, and others, with a maximum achievable resolution exceeding 1m. Extensive in-orbit testing of the payload produced numerous high-quality SAR images with potential uses in emergency disaster mitigation, safeguarding ecosystems, monitoring forests, managing crops, tracking sea ice, and more.
Circulating Cell-Free Nuclear DNAs Predicted an Improvement of Systolic Left Ventricular Function in Individuals with Chronic Heart Failure with Reduced Ejection Fraction
Authors: Berezina Tetiana , Berezin Oleksandr O. , Lichtenauer Michael , Berezin Alexander E
Published: August 2024

Patients with heart failure (HF) with improved LVEF (HFimpEF) demonstrate better clinical outcomes when compared with individuals without restoration of cardiac function. Identification of predictors for HFimpEF may play a crucial role in individual management of HF with reduced EF (HFrEF). Cell-free nuclear (cf-nDNA) DNA are released from damaged cells and contribute to adverse cardiac remodeling, cardiac dysfunction and inflammation. The purpose of the study was to elucidate whether cf-nDNAs are associated with HFimpEF. It has been prescreened 1416 patients with HF using local database. Between October 2021 and August 2022 we included 452 patients chronic HFrEF after prescription of optimal guideline-based therapy and identified HFimpEF in 177 individuals from them according to the criteria of European Society of Cardiology. Measurements of circulating biomarkers were performed at baseline and in 6 months. Detection of cf-nDNA was executed with real time quantitative PCR (qPCR) using NADH dehydrogenase, ND2 and beta-2-microglobulin. We found that HFimpEF was associated with a significant decrease in the levels of cf-nDNA when compared with the patients from persistent HFrEF cohort. Presence of ischemia-induced cardiomyopathy (odds ration [OR] = 0.75; confidence interval [CI] = 0.62 – 0.88; p = 0.044), type 2 diabetes mellitus (OR = 0.77; CI = 0.71 – 0.82; p = 0.042) and digoxin administration (OR = 0.85; CI = 0.72-0.97; p = 0.042) were negative factors for HFimpEF, whereas NT-proBNP ≤1940 pmol/mL (OR = 1.42; 95% CI = 1.19-1.98, p = 0.001), relative decrease in NT-proBNP levels (>35% vs. ≤35%) from baseline (OR = 1.52; 95% CI = 1.38-0.69, p = 0.001) and cf-nDNA ≤7.5 μmol/L (OR = 1.56; 95% CI = 1.07-2.94, p = 0.001) were positive predictors for HFimpEF. Multivariate logistic regression adjusted to ischemia-induced cardiomyopathy, IV HF NYHA class, and digoxin use yielded that NT-proBNP ≤1940 pmol/mL (OR = 1.43; 95% CI = 1.21-1.88, p = 0.001) and cf-nDNA ≤7.5 μmol/L (OR = 1.64; 95% CI = 1.19-2.15, p = 0.001) independently predicted HFimpEF. In conclusions: we established that the levels of cf-nDNA≤7.5 μmol/L independently predicted HFimpEF and improved discriminative ability of as single measured NT-proBNP as well as relative decrease in NT-proBNP levels ≤35% from baseline.
Event-Triggered Two-Part Separation Control of Multiple Autonomous Underwater Vehicles Based on Extended Observer
Authors: Gu Yunyang , Xu Yueru , Jiang Mingzuo , Zhou Zhigang
Published: August 2024

In this paper, we investigated the formation isolation regulation issue regarding multiple autonomous underwater vehicles (AUVs) characterized by a "leader-follower" framework. Considering the cooperative-competitive relationship among the follower AUVs and the impact of unknown external disturbances, an extended state observer was designed based on backstepping to mitigate these disturbances, and an event-triggered control scheme was designed to realize the two-part consensus control within the multi-AUV system. Through rigorous theoretical analysis, it is shown that the system achieves asymptotic steadiness and is free from zeno behavior under the proposed event-triggered control scheme. Finally, numerical simulations confirm the efficiency of the regulation strategy in achieving formation separation within the multi-AUV, where the trajectory tracking errors of individual AUVs gather in a compact vicinity close to the source and the structure converges was achieved, with the absence of zeno behavior also demonstrated.
Symmetry between Series if Entangled by Sums
Authors: Koppelaar Henk , Nasehpour Peyman , Looijen Maarten
Published: August 2024

In analogy with entanglement in physics, the concept of entanglement has been developed in mathematics as a symmetry to build upon as a tool to study 'proximity' relations between different number sequences and series in a unifying way. Examples of entanglement are shown. A general algorithm for detecting entangled sequences/series is given in the appendix. The novelty of this paper is to propose the concept of entanglement as a tool to study different sequences and se-ries-series phenomena. To enable useful treatment suggested by Poincaré.
Communication and Sensing: PHY Layer Threats to Security and Privacy for IoT Systems, and Possible Countermeasures
Authors: Lo Cigno Renato , Gringoli Francesco , Bartoletti Stefania , Cominelli Marco , Ghiro Lorenzo , Zanini Samuele
Published: August 2024

Recent advances in signal processing and AI-based inference enable the exploitation of communication signals to collect information on devices, people, actions and the environment in general, i.e., to perform Integrated Sensing And Communication (ISAC). This possibility opens new and exciting opportunities for IoT systems, but at the same time poses unprecedented threats to security and privacy of data, devices, and systems. In fact, ISAC operates at the PHY and Medium Access Control (MAC) layers, where it is impossible to protect the information with standard encryption techniques, or with any other purely digital methodologies. The work we present analyzes, within the framework of IoT and distributed, pervasive communication systems, the threats to security and privacy posed by ISAC and how they do intertwine at the PHY layer. Next, possible countermeasures are presented and discussed, with proper architectural choices and tradeoffs to implement them, as well as solutions and protocols to preserve the potential benefits of ISAC while ensuring data protection and users’ privacy.
Natural and Artificial Intelligence Interactions in Digital Networking:A Multilayer Network Model for Economic Value Creation
Authors: Moro Visconti Roberto
Published: August 2024

This study investigates the integration of natural intelligence (NI) and artificial intelligence (AI) within traditional firms, proposing a multilayer network framework to enhance economic value. The research explores the central question: How can the integration of NI and AI, facilitated by copula nodes, drive economic value creation in digitized firms? Through empirical testing across multiple industries—namely manufacturing, retail, and finance—the study evaluates the cost-benefit improvements associated with AI adoption. The findings reveal substantial efficiency gains, improved decision-making, and notable cost reductions, validating the proposed model's predictions. The study emphasizes the critical role of copula nodes in optimizing interactions between NI and AI, ensuring that their integration yields maximum economic benefits. By providing a novel framework for quantifying AI's economic impact within digitized firms, this research fills a significant gap in the literature on multilayer networks and intelligent systems. The practical implications are profound, offering a strategic pathway for firms to enhance profitability and competitiveness in the digital age.
A Case for the Optimization of Ophthalmic Care by Leveraging 3-D Printing: A Review
Authors: Mina Mina , Goel Ajay Kumar , Mina Fady , Goubran Doris , Goel Nand
Published: August 2024

Over 2.2 billion people across the globe face significant barriers to accessing essential ophthalmic care, with elderly, rural, and refugee populations being disproportionately affected. These obsta-cles deepen existing disparities in eye care. 3D printing is a novel technology that has the potential to transform the field and improve access through alleviating many patient-specific barriers. This article delves into the evolution of 3D printing within ophthalmology, highlighting its current ap-plications and future potential. It explores various 3D printing techniques and biomaterials, dis-cussing their effectiveness in creating advanced solutions such as bioengineered corneas, ocular prosthetics, and innovative treatments for dry eye syndrome. Additionally, 3D printing has rev-olutionized drug delivery systems for conditions like glaucoma, retinal diseases, and for ocular brachytherapy. Despite its promise, the integration of 3D printing into clinical practice presents challenges, which the article addresses alongside strategies for overcoming them. By mapping out the technological advancements and challenges, this review offers a roadmap for enhancing global eye care accessibility and improving patient outcomes on a global scale.
What Quality Suffices in Nanopore Metabarcoding? Reconsidering Methodology and Ectomycorrhizae in Decaying Fagus sylvatica Bark as a Case-Study
Authors: Dierickx Glen , Tondeleir Lowie , Asselman Pieter , Vandekerkhove Kris , Verbeken Annemieke
Published: August 2024

Nanopore raw read accuracy has improved to over 99%, making it a potential tool for metabarcoding. For broad adoption, guidelines on quality filtering are needed to ensure reliable taxonomic unit recovery. This study aims to provide those guidelines for a fungal metabarcoding context and to apply them to a case-study of ectomycorrhizae in decaying bark of Fagus sylvatica.We introduce the eNano pipeline to test two standard metabarcoding approaches: (1) reference-based mapping leveraging the UNITE’s species hypothesis system (SH-approach) and (2) constructing 98% OTUs (OTU-approach). We evaluate these approaches using a mock and natural community. Our results demonstrate that both approaches are effective with Nanopore data. When using a reference database, we recommend strict mapping criteria rather than Phred-based filtering. For 98% OTUs, filtering reads at ≥Q25 is recommended. Our case-study reveals that the decay gradient is a primary determinant of community composition, and that specific mycorrhizal fungi colonize decaying bark. Complementing our metabarcoding results with root tip morphotypification, we identify Laccaria amethystina and Tomentella sublilacina as key ectomycorrhizae of saplings on decaying logs. These findings demonstrate that Nanopore sequencing can provide valuable ecological insights and support its broader use in fungal metabarcoding as read quality continues to improve.
Analysis and Monitoring of Air Quality through Discrete Time Markov Chai
Authors: Asim Muhammad Muwahid , Amjad Muhammad Musa , Sarfaraz Amna , Ali Zaiwar
Published: August 2024

The term Air Quality (AQ) pertains to the standard of air, which has a direct impact on the health and well-being of individuals. It is crucial to maintain high Air Quality (AQ), for better health and productivity. Though most of people spend more time indoors nowadays, it is not to be overlooked that the pollutant concentration in indoor air is directly linked to the outdoor air quality. Due to the changes in occupancy patterns, outdated maintenance of ventilation systems, and structural flaws in buildings, the indoor air is significantly polluted; pollutants emitted outdoors enter indoor air through open windows, ventilation systems and infiltration. In this paper, we have proposed a new technique, DTMCPM (discrete-time Markov chain (DTMC) model for the analysis and forecasting of AQ, using the power method). Specialized sensors and equipment to measure different pollutants, such as particulate matter, ozone, nitrogen dioxide, sulfur dioxide, benzene and toluene, are used to collect data by the Institute of Pakistan Air Quality Monitor in various cities; the data is converted to US EPA standard for all pollutant species. This data is used to calculate the transition matrix, steady-state values and mean return rate for the analysis of IAQ. The calculated and actual return rates have been compared and the proposed model is found to have a low average prediction error of 2.356%.
Fatigue and Ultimate Strength Evaluation of GFRP-Reinforced, Laterally-Restrained, Full-Depth Precast Deck Panels with Developed UHPFRC-Filled Transverse Closure Strips
Authors: SAYED AHMED Mahmoud , Sennah Khaled , Afefy Hamdy M
Published: August 2024

Full depth precast deck panel (FDDP) is one element of the prefabricated bridge element and systems (PBES) that allows for quick un-shored assembly of the bridge deck on-site as part of the accelerated bridge construction (ABC) technology. This paper investigates the structural response of full-depth precast deck panels (FDDPs) constructed with new construction materials and connection details. FDDP is cast with normal strength concrete (NSC) and reinforced with high modulus (HM) glass fiber reinforced polymer (GFRP) ribbed bars. The panel-to-girder V-shape connections use the shear pockets to accommodate the clustering of the shear connectors. A novel transverse connection between panels has been developed, featuring three distinct female-to-female joint configurations, each with 175-mm projected GFRP bars extending from the FDDP into the closure strip, complemented by a female vertical shear key and filled with cementitious materials. The ultra-high performance fiber reinforced concrete (UHPFRC) was selectively used to joint-fill the 200-mm transverse joint between adjacent precast panels and the shear pockets connecting the panels to the supporting girders to ensure full shear interaction. Two actual-size FDDP specimens for each type of the three developed joints were erected to perform fatigue tests under the footprint of the Canadian Highway Bridge Design Code (CHBDC) truck wheel loading. The FDDP had a 200-mm thickness, 2500-mm width, and 2400-mm length in traffic direction; the rest was over braced steel twin girders. Two types of fatigue tests were performed; incremental variable amplitude fatigue (VAF) loading and constant amplitude fatigue (CAF) loading, followed by monotonically loading the slab ultimate-to-collapse. It was observed that fatigue test results showed that the ultimate capacity of the slab under VAF loading or after 4 million cycles of CAF exceeds the factored design wheel load specified into the CHBDC. Also, punching shear failure mode was dominant in all the tested FDDP specimens.