bluuebunny/crossref_metadata_2025 huggingface dataset:
The nonspecific effects of COVID-19 vaccination upon non-COVID-19 all-cause mortality (NCACM) in the population of England: Effects of age, sex, COVID-19 variant, vaccination history, and time in a real-world study from Jan-21 to May-23
Authors: Jones Rodney P , Ponomarenko Andrey
Published: January 2024

All vaccines exhibit specific and nonspecific effects. Specific effects are shown by the efficacy against the target pathogen, while nonspecific effects can be detected by the change in all-cause mortality. The real-world non-COVID-19 all-cause mortality (NCACM) data for the population of England between January 2021 and May 2023 was assessed. All vaccines administered were based on the original Wuhan antigen. Each gender and age group, along with COVID-19 variant shows its own unique NCACM vaccination benefit/disbenefit time profile. The efficacy of COVID-19 vaccination against COVID-19 disease/death per se is undisputed, however, the nonspecific outcomes of COVID–19 vaccination is far more nuanced than have been widely appreciated. This confirms an earlier study on the unanticipated nonspecific effects of influenza vaccination against all-cause winter mortality. Interestingly, a high proportion of NCACM beneficial effects occurred during the first 21 days following COVID-19 vaccination, while the worst example of increased NCACM occurred during the fourth dose of COVID-19 vaccination in 19–40-year-olds for the interval >21 days post vaccination which led to NCACM 3- to 10-times higher than in the unvaccinated. By the time of the Omicron variant, NCACM outcomes in those aged 90+ are mostly adverse. The beneficial nonspecific effects of COVID-19 vaccination increase with age and reach their maximum effect during the second week post vaccination for age groups below 50 years, rising to during the third week for those aged 70+. Finally, we discuss the mechanisms by which COVID-19 vaccination could induce wider nonspecific effects. Most of these mechanisms seem to depend on gene regulation by noncoding RNAs which also interact with mRNAs. We suggest that further international studies are required to discern the nonspecific NCACM effects of the different COVID-19 variants other than the three variants prevalent in the UK, and different types/manufacturer of COVID-19 vaccines which have been employed around the world. We can only speculate regarding the nonspecific effects of the COVID-19 vaccines administered to persons with an asymptomatic infection, and during vaccine waning. Vaccines not only need to be effective against the target pathogen, as primarily determined by antibody production, but need to minimize any unanticipated adverse nonspecific effects against all-cause mortality.
The Survival Analysis of the Recurrent Epithelial Ovarian Cancer Patients Based on the Relapse Type: Multi-Institutional Retrospective Study in Armenia
Authors: Harutyunyan Lilit , Manvelyan Evelyna , Karapetyan Nune , Bardakhchyan Samvel , Jilavyan Aram , Tamamyan Gevorg , Avagyan Armen , Safaryan Liana , Zohrabyan Davit , Movsisyan Narine , Avinyan Anna , Galoyan Arevik , Sargsyan Mariam , Harutyunyan Martin , Nersoyan Hasmik , Stepanyan Arevik , Galstyan Armine , Danielyan Samvel , Muradyan Armen , Jilavyan Gagik
Published: January 2024

Background: About 200 new ovarian cancer cases per year are diagnosed in Armenia, an upper-middle-income country. This study aims to summarize the survival outcomes of relapsed ovarian cancer patients in Armenia based on the type of relapse, risk factors, and the choice of systemic treatment. Methods: A retrospective case-control study including 228 patients with relapsed ovarian cancer from 3 different institutions. Results: The median age of the patients was 55. The median follow-up from the relapse and primary diagnosis was 21 and 48 months. The incidence of platinum-sensitive relapse was 81.6% (186), while platinum-resistant relapse was seen only in 18.4% (42) patients. Median survival of the patients starting from the primary diagnosis in the platinum-sensitive compared to the platinum-resistant group was 54 versus 25 months (p < 0.001), and median survival after relapse: was 25 versus 13 months, respectively 3- and 5-year survival in these groups were: 31.2% vs. 23.8%, and 15.1% vs. 9.5%, respectively (p = 0,113). Conclusions: Overall, despite new therapeutic approaches, ovarian cancer continues to be one of the deadly malignant diseases in women, especially, in developing countries with a lack of resources, where, in fact, the main available systemic treatment for the majority of patients remains chemo-therapy. Low survival rates emphasize the urgent need for more research on this group of patients with poor outcomes.
Analysis of Socio-Emotional Competencies as a Key Dimension for Sustainability in Colombian Elite Athletes
Authors: Marín-González Fabián Humberto , Portela-Pino Iago , Funtes-García Juan Pedro , Martínez-Patiño María José
Published: January 2024

UNESCO highlights socio-emotional, cognitive, and behavioral learning as critical for advancing sustainability. As major events, sports generate significant social, economic, and environmental impacts. This study analyzed how academic background, gender, age, sport type, and modality influenced elite Colombian Olympic and Paralympic athletes' socio-emotional competencies. Methods: Colombian elite athletes who were members of the “Support to the Excellence Coldeportes Athlete” participated in the study. The total population studied included 334 Colombian elite athletes: mean age 27.10 ± 6.57 years old with 13.66 ± 6.37 years practicing his/her sports modality. The socio-emotional competencies of the participants were assessed using the Socio-emotional Competencies Scale (SECS). Results: Men scored higher in interpersonal regulation, self-awareness, conflict resolution, and emotional regulation. Younger athletes (≤25 years) had higher self-consciousness. Individual versus team sports did not differ. Paralympians showed higher motivation, self-awareness, teamwork, and emotional regulation. University educated athletes scored higher in motivation, self-awareness, teamwork, and empathy. All competencies positively correlated. Conclusion: Individualized interventions targeting improved socio-emotional performance are vital for sustainability and should account for differences across gender, age, education, and disability status.
Towards Structural and Aeroelastic Similarity in Scaled Wing Models: Development of an Aeroelastic Optimization Framework
Authors: Filippou Evangelos , Kilimtzidis Spyridon , Kotzakolios Athanasios , Kostopoulos Vassilis
Published: January 2024

The pursuit of more efficient transport has led engineers to develop a wide variety of 1 aircraft configurations with the aim of reducing fuel consumption and emissions. However, these 2 innovative designs introduce significant aeroelastic couplings that can potentially lead to structural 3 failure. Consequently, aeroelastic analysis and optimization has become an integral part of modern 4 aircraft design. In addition, aeroelastic testing of scale models is a critical phase in aircraft devel- 5 opment, requiring accurate prediction of aeroelastic behaviour during scale model construction to 6 reduce costs and mitigate risks associated with full-scale flight testing. Achieving a high degree of 7 similarity between the stiffness, mass distribution and flow field characteristics of scaled models 8 and their full-scale counterparts is of paramount importance. However, achieving similarity is 9 not always straightforward due to the variety of configurations of modern lightweight aircraft, as 10 identical geometry cannot always be directly scaled down. This configuration diversity has a direct 11 impact on the aeroelastic response, necessitating the use of computational aeroelasticity tools and 12 optimization algorithms. This paper presents the development of an aeroelastic scaling framework 13 using multidisciplinary optimization. Specifically, a parametric Finite Element Model (FEM) of the 14 wing is created, incorporating parameterisation of both thickness and geometry, primarily using 15 shell elements. Aerodynamic loads are calculated using the Doublet Lattice Method (DLM) em- 16 ploying twist and camber correction factors, and aeroelastic coupling is established using infinite 17 plate splines. The aeroelastic model is then integrated within an Ant Colony optimization (ACO) 18 algorithm to achieve static and dynamic similarity between the scaled model and the reference wing. 19 A notable contribution of this work is the incorporation of internal geometry parameterisation into 20 the framework, increasing its versatility and effectiveness.
Microgrid Model for Evaluating the Operational Dynamics of Solar-Powered Hydrogen Production
Authors: Osman Mohammed Gmal , Strejoiu Cristian-Valentin , Panait Cornel , Sima Catalina Alexandra , Lazaroiu Gheorghe
Published: January 2024

The utilization of solar energy technology is crucial for generating hydrogen in sustainable energy systems. While traditional methods involving natural gas, coal, and oil have been employed for hydrogen production, this study aims to explore environmentally friendly techniques. Green hy-drogen, despite being a more expensive option compared to fossil fuel-derived hydrogen, has prompted engineers to develop affordable and low-carbon technologies.
The microgrid model was developed to showcase a self-contained DC islanded system designed to supply power to an electrolyzer, capitalizing on both a solar array and an energy storage unit. This comprehensive model offers a versatile platform for evaluating the operational dynamics involved in the sustainable production of green hydrogen. Over a span of seven days, it permits the as-sessment of hydrogen generation characteristics through the utilization of solar energy, either di-rectly from a solar array or through an integrated system that incorporates energy storage. The model encompasses a multi-domain framework, encompassing electrical, thermal liquid, and thermal gas aspects, facilitating a holistic exploration of the intricate processes underlying the green hydrogen production system. Through this simulation, the feasibility and efficiency of harnessing renewable energy sources for hydrogen production in an off-grid setting can be comprehensively examined and optimized, contributing to the advancement of sustainable energy solutions.
Human Age Estimation from Face Images with Deep Convolutional Neural Networks Using Transfer Learning
Authors: George Gilbert , Uppin Chandrashekhar , Bello Usman Abubakar
Published: January 2024

In recent years, there has been a growing interest in the prediction of facial age due to its diverse applications in fields such as security, entertainment, and healthcare. The current scourge of underaged voting in Nigeria is a problem and this research delves into the realm of facial age prediction by employing four well-known convolutional neural network (CNN) architectures, namely VGG16, ResNet50, Mobile Net, and VGG19 to predict chronological ages from facial pictures of person. The objective is to achieve precise age estimation from facial images, utilizing two datasets: UTKFace and CASIA African Facial Datasets. The results of this investigation are noteworthy. Specifically, the VGG16 model which demonstrated remarkable performance, yielding a Mean Absolute Error (MAE) of 1.76 when applied to the UTK-Face dataset. Additionally, when utilizing Mobile-Net, an unprecedented MAE of 1.10 was achieved for the Casia Africa Face Dataset. Notably, this marks the first instance of employing the dataset for facial age detection with CNNs, and this approach outperformed previous works, yielding the lowest MAE among all the studies reviewed.
Effect of Bacteriophages against Biofilms of Escherichia coli on Food Handling Surfaces
Authors: Brás Ana , Braz Márcia , Martinho Inês , Duarte João , Pereira Carla , Almeida Adelaide
Published: January 2024

The bacterial adhesion to food contact surfaces is a threat to human health, as these surfaces can serve as a reservoir of pathogenic bacteria. Escherichia coli is a biofilm-forming bacterium involved in surface contamination. Despite the application of disinfection protocols, contamination continues to occur. Hence, new effective and sustainable approaches are needed. Bacteriophages (or simply phages), viruses that only infect bacteria, have proven to be effective in reducing biofilms. Here, phage phT4A was applied to prevent and reduce E. coli biofilm on plastic and stainless steel. The assays were performed in Tryptic Soy Broth (TSB), at 25 °C. The biofilm formation capacity of phage-resistant and sensitive bacteria, after treatment, was also evaluated. Maximum reductions on E. coli biofilm of 5.5 log colony forming units (CFU)/cm2 (after 6 h) and 4.1 log CFU/cm2 (after 9 h), on plastic and stainless steel, respectively, were observed. In the prevention assays, phage prevented biofilm formation in 3.2 log CFU/cm2, after 12 h. Although the emergence of phage-resistant bacteria has been observed during phage treatment, a lower biofilm formation capacity was observed by phage-resistant bacteria comparatively to phage-sensitive bacteria. Overall, phages have shown to be a promising approach to decontaminate food handling surfaces.
Sarcocystis spp. of New and Old World Camelids: Ancient Origin, Present Challenges
Authors: Wieser Sarah N , Giuliano Susana M , Reategui Ordoñez Juan , Barriga Marcapura Ximena , Olivera Marocho Luis V. M. , Chavez Fumagalli Miguel Angel , Schnittger Leonhard , Florin-Christensen Monica
Published: January 2024

Sarcocystis sp. are coccidian protozoans belonging to the Apicomplexa phylum. As other members of this phylum, they are obligate intracellular parasites having a complex cellular machinery for the invasion of host cells. Sarcocystis spp. display dixenous life cycles, involving a predator and a prey as definitive and intermediate hosts, respectively. Specifically, these parasites develop sarcocysts in the tissues of their intermediate hosts, ranging in size from microscopic to visible to the naked eye, depending on the species. When definitive hosts consume sarcocysts, infective forms are produced in the digestive system and discharged into the environment via feces. Consumption of oocyst-contaminated water and pasture by the intermediate host completes the parasitic cycle. More than 200 Sarcocystis spp. have been described infecting wildlife, domestic animals, and humans, some of which are of economic or public health importance. Interestingly, Old World camelids (dromedary, domestic Bactrian camel, and wild Bactrian camel) and New World or South American camelids (llama, alpaca, guanaco, and vicuña) can each be infected by two different Sarcocystis species: Old World camelids by S. cameli (producing micro- and macroscopic cysts) and S. ippeni (microscopic cysts); and South American camelids by S. aucheniae (macroscopic cysts) and S. masoni (microscopic cysts). Large numbers of Old and New World camelids are bred for meat production, but the finding of macroscopic sarcocysts in carcasses significantly hampers meat commercialization. This review tries to compile the information that is currently accessible regarding the biology, epidemiology, phylogeny, and diagnosis of Sarcocystis spp. infecting Old and New World camelids. In addition, knowledge gaps will be identified to encourage research that will lead to the control of these parasites.
Redox Regulation of PTEN by Reactive Oxygen Species: Role in Physiological Processes
Authors: Trinh Vu Hoang , Nguyen Thang Huu , Sah Dhiraj Kumar , Choi Jin Myung , Yoon Hyun Joong , Park Sang Chul , Jung Yu Seok , Lee Seung-Rock
Published: January 2024

Phosphatase and tensin homolog (PTEN) is a tumor suppressor due to its ability to regulate cell survival, growth and proliferation by down-regulating PI3K/AKT signaling pathway. In addition, PTEN plays an essential role in other physiological events associated with cell growth demands, such as ischemia-reperfusion, nerve injury and immune response. Therefore, recently PTEN inhibition has emerged as a potential therapeutic intervention in these situations. Increasing evidence demonstrates that reactive oxygen species (ROS), especially hydrogen peroxide (H2O2), are produced and required for the signaling in many important cellular processes under such physiological conditions. ROS have been shown to oxidize PTEN at the cysteine residue of its active site, consequently inhibiting its function. Here we provide an overview of studies that highlight the role of oxidative inhibition of PTEN in physiological processes.
Femtoscopy With Lévy Sources From SPS Through RHIC to LHC
Authors: Csanád Máté , Kincses Dániel
Published: January 2024

Femtoscopy is a unique tool to investigate the space-time geometry of the matter created in ultra-relativistic collisions. If the probability density distribution of hadron emission is parametrized, then the dependence of its parameters on particle momentum, collision energy, and collision geometry can be given. In recent years, several measurements came to light that indicated the adequacy of assuming a Lévy-stable shape for the mentioned distribution. In parallel, several new phenomenological developments appeared, aiding the interpretation of the experimental results, or providing tools for the measurements. In this paper we review and discuss some of these advances, phenomenological and experimental.
Molecular and Cellular Mechanisms of Systemic Autoimmune Diseases: Lessons Learned from Human Genetic Studies and Therapies in Systemic Lupus Erythematosus (SLE)
Authors: Ling Siriust , Fan R. Andrea
Published: January 2024

A Systemic Lupus Erythematosus (SLE) is a prototypical systemic autoimmune disease characterized by a complex interplay of genetic, molecular, and cellular factors. It is considered a multifactorial disorder influenced by genetic susceptibility, environmental triggers, and dysregulated immune responses. Understanding the molecular and cellular mechanisms driving SLE pathogenesis has been instrumental in developing targeted therapies to manage the disease and improve patient outcomes. In this essay, we will delve into the intricate molecular and cellular processes underlying SLE and examine the key lessons learned from human therapies.
Vortex Induced Vibration Response of the Cylinder Inspired by Terebridae with Different Helical Angle
Authors: Yu Qi Dong , Mao Zhaoyong , Tian Wen Long , Wang Wei
Published: January 2024

Biomimetic design has recently received widespread attention. Inspired by the Terebridae structure, this paper provides a structural form for suppressing vortex-induced vibration (VIV) response. Four different structural forms are shown, including the traditional smooth cylinder (P0), the Terebridae-inspired cylinder with a helical angle of 30° (P30), the Terebridae-inspired cylinder with a helical angle of 60° (P60), and the Terebridae-inspired cylinder with a helical angle of 90° (P90). And computational fluid dynamics (CFD) method is adopted to solve the flow pass the Terebridae-inspired structures, and the vibration equation is solved using the Newmark-β method. The results show that the VIV responses are effectively controlled in the lock-in region for P30, P60, and P90, and P60 shows the best VIV suppression performance. The transverse amplitude and the downstream amplitude can be reduced by 82.67% and 91.43% respectively for P60 compared with that for P0, and the peak of the mean-drag coefficient is suppressed by 53.33%. The Q-criterion vortices of P30, P60, and P90 are destroyed, with irregular vortices shedding. It is also found that the boundary layer separation is located on the Terebridae-inspired ribs. The twisted ribs cause the separation point to constantly change along the spanwise direction, resulting in the development of the boundary layer separation being completely destroyed. The strength of the wake flow is significantly weakened for the Terebridae-inspired cylinder. In the lock-in region, the motion trajectory presents a typical 8-shaped for P0, while the motion trajectory of the Terebridae-inspired cylinder tends to be a flat 1-shaped.
Demographic Variation in Nutrition Knowledge and Relationship with Eating Attitudes among Chinese University Students
Authors: Deng Wen-Jing , YI ZIYUE , Lee Chi-Kin John
Published: January 2024

There is a noticeable absence of health education among college students. This study aimed to evaluate the extent of general nutrition knowledge among Chinese university students and explore its association with eating attitudes. Data were collected from a group of 273 students in Spring of 2023, using a valid and reliable research instrument consisting of three sections: demographic variables, the General Nutrition Knowledge Questionnaire (GNKQ), and the Eating Attitudes Test (EAT-26). The results were analyzed using SPSS, with correlations and t-tests to examine the relationships between nutritional knowledge and dietary attitudes. Furthermore, the present study employed the Random Forest (RF) algorithm, a machine learning technique, utilizing the Mean Decrease Impurity (MDI) method to investigate the influence of various features on participants' eating attitudes.
The findings revealed that Chinese university students had an average accuracy of over 60% in their nutritional knowledge, but their understanding of the relationship between diet and disease still needs improvement. Moreover, male students had significantly lower nutritional knowledge than female students, and there was a positive correlation between nutritional knowledge and parents’ income. The study also found a significant correlation between the level of nutritional knowledge and eating attitudes. RF results indicated that family income level exhibited the most substantial impact on the eating attitudes of the participants. The study highlights the need for nutrition education curriculum developers to focus more on improving students' nutritional knowledge, with particular attention given to male students, low-income individuals, and those with an abnormal BMI.
Early Extra-Uterine Growth Restriction in Very Low Birth Weight Neonates with Normal or Mildly Abnormal Brain MRI: Effects on 2–3 Years Neurodevelopmental Outcome
Authors: Massirio Paolo , Battaglini Marcella , Bonato Irene , De Crescenzo Sara , Calevo Maria Grazia , Malova Mariya , Caruggi Samuele , Parodi Alessandro , Preiti Deborah , Zoia Agata , Uccella Sara , Tortora Domenico , Severino Mariasavina , Rossi Andrea , Traggiai Cristina , Nobili Lino , Striano Pasquale , Ramenghi Luca Antonio
Published: January 2024

Extrauterine growth restriction (EUGR) is a common complication and a known risk factor for impaired development in very low birth weight (VLBW) preterms. We report a population of 288 patients with no or with low grade MRI lesions scanned at term equivalent age (TEA) born between 2012 and 2018. Griffiths mental development scale II (GMDS II) at 2 and 3 years, preterm complications and weight growth were retrospectively analysed. EUGR was defined for weigth z-score ˂10th percentile at TEA, 6 and 12 months of correct age or as z-score decreased by 1-point SDS from birth to TEA and from TEA to 6 months. Multivariate analysis showed that a higher weight z-score at 6 months is protective for global developmental quotient (DQ) at 2 years (OR 0.74; CI 95% 0.59-0.93; p=0,01). EUGR at 6 months was associated with worse locomotor, personal-social, language and performance DQ at 2 years and worse language and practical reasoning DQ at 3 years. In conclusion a worse weight z-score at 6 months of age seems to be an independent risk factor for significantly reduced GMDS in many areas. These results suggest to better invest on post-discharge nutritional, optimizing family nutritional education.
Mitigating the impact of temperature variations on ultrasonic guided wave-based structural health monitoring through generative artificial intelligence
Authors: Junges Rafael , Lomazzi Luca , Miele Lorenzo , Giglio Marco , Cadini Francesco
Published: January 2024

Structural health monitoring (SHM) has become paramount for developing cheaper and more reliable maintenance policies. The advantages coming from adopting such process have turned out to be particularly evident when dealing with plated structures. In this context, state-of-the-art methods are based on exciting and acquiring ultrasonic guided waves through a permanently installed sensor network. A baseline is registered when the structure is healthy, and newly acquired signals are compared to it to detect, localize and quantify damage. To this purpose, the performance of traditional methods based on tomographic algorithms has been overcome by machine learning approaches, which allow processing a larger amount of data without losing diagnostic information. However, to date, no diagnostic method can deal with varying environmental and operational conditions. This works aims to develop a framework for mitigating the impact of temperature variations on ultrasonic guided wave-based SHM through generative artificial intelligence. A variational autoencoder and singular value decomposition were combined to learn the influence of temperature on guided waves. After training, the generative part of the algorithm was used to reconstruct signals at new unseen temperatures. Moreover, a refined version of the algorithm called forced variational autoencoder was introduced to further improve the reconstruction capabilities. The accuracy of the proposed framework was demonstrated against real measurements on a composite plate.
Remdesivir and the Liver: A Concise Narrative Review of Remdesivir-Associated Hepatotoxicity in Patients Hospitalized Due to COVID-19
Authors: FakhriRavari Alireza , Malakouti Mazyar
Published: January 2024

Severe acute respiratory syndrome coronavirus 2 infects many people, but many infected individuals do not develop symptoms. COVID-19 is an inflammatory disease that affects a portion of individuals infected with the virus, and it is associated with liver injury and other complications leading to hospitalization, critical illness, and death. Remdesivir is an antiviral agent used for treatment of hospitalized patients with COVID-19 to improve time to recovery, reduce duration of mechanical ventilation, decrease the need for supplemental oxygen, and decrease the risk of mortality. Remdesivir-associated hepatotoxicity has been observed as increased transaminases more than 5 times the upper limit of normal in hospitalized patients with COVID-19 but causality has not been proven. It is generally difficult to distinguish between remdesivir-associated hepatotoxicity and COVID-19-induced hepatotoxicity. The purpose of this review is to evaluate the evidence for remdesivir-associated hepatotoxicity. Current evidence suggests that elevated liver enzymes in hospitalized COVID-19 patients are more likely to be due to the infection than remdesivir and that a 5-day course of remdesivir seems to be safe in regards to hepatotoxicity.
Decoding the Relationship of Artificial Intelligence, Advertising, and Generative Models
Authors: Park Han Woo , Lim Camille Velasco , Zhu Yu Peng , Omar Muhammad
Published: January 2024

In 2023, the technological landscape witnessed an unprecedented surge of transformative innovations, including Web 3.0 and machine learning, poised to revolutionize various aspects of our daily lives. At the forefront of this revolution stands artificial intelligence (AI), which has evolved from a concept once confined to science fiction into an indispensable force reshaping industries on a global scale. Notably, recent years have seen remarkable strides in AI functionalities, particularly in machine learning, computer vision, and natural language processing. These advancements have empowered AI to generate diverse interactions and media autonomously. This study ultimately provides invaluable insights into the dynamic intersection of AI and Advertising, con-tributing to a deeper comprehension of this evolving field. This study conducts a comprehensive review of Artificial Intelligence within the advertising domain, employing network analysis. By meticulously examining the evolution of AI through co-occurrences of terms, keywords, and co-authorship analysis, we aim to unveil the relationship of AI & Advertising through the lens of Generative models to identify pivotal trends, core concepts, and seminal studies that have profoundly influenced the industry.
The analysis charts the trajectory leading to the emergence of Generative Artificial Intelligence (GenAI), a transformative development poised to revolutionize advertising practices and consumer engagement. In tandem with these objectives, the results highlight vital trends, emphasizing the growing prominence machine learning tools and techniques such as deep learning techniques and advanced natural language processing methods like word2vec, GANs, and more in shaping the future of advertising practices.
Increase in Antibody Titer and Change over Time Associated with Severe Acute Respiratory Syndrome Coronavirus 2 Infection after mRNA Vaccination: Consideration of the Significance of Additional Vaccination
Authors: Kusunoki Hiroshi , Ohkusa Michiko , Iida Rie , Saito Ayumi , Kawahara Mikio , Ekawa Kazumi , Kato Nozomi , Motone Masaharu , Shimizu Hideo
Published: January 2024

Objective: Spontaneous infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after mRNA vaccination causes a marked increase in antibody titer because of the combined effect of vaccine and infection (“hybrid immunity”). In this study, we discuss the significance of the mRNA vaccine booster inoculation that has been repeatedly performed in Japan.Methods: We describe the temporal trends of antibody titers in cases in which antibody titers were markedly increased by hybrid immunization.Results: The antibody titer increased with hybrid immunization and tended to decrease with time. However, several cases maintained high antibody titers for approximately one year after coronavirus disease 2019 (COVID-19 diagnosis), even without booster vaccination.Conclusions: Most Japanese patients naturally infected with COVID-19 were infected after mRNA vaccination, and many maintained high antibody titers due to hybrid immunity. The significance of additional vaccination in hybrid-immunized cases is highly questionable regarding cost-effectiveness and risk-benefit.
Autosomal Dominant Polycystic Kidney Disease: Extrarenal Involvement
Authors: Righini Matteo , Mancini Raul , Busutti Marco , Buscaroli Andrea
Published: January 2024

Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disorder but kidneys are not the only organs involved in this systemic disorder. Individuals with the condition may display additional manifestations beyond the renal system, involving liver, pancreas and brain in the con-text of cystic manifestations, while vascular system, gastrointestinal tract, bones, and cardiac valves in the context of non-cystic manifestations. Despite kidney involvement remain the main feature of the disease, thanks to new generation therapies, early diagnosis and better management of kidney related problems, a new wave of complications must be faced from clinicians who treated polycystic patients. Involvement of the liver represents the most prevalent extrarenal manifestation and grows importance in symptom burden and quality of life. Vascular abnormalities are a key factor for patients’ life expectancy and there’s still de-bate whether to screen or not to screen all patients. Arterial hypertension is often the earliest onset among polycystic patients leading to frequent cardiovascular complications. Although cardiac valvular abnormali-ties is a frequent complication, it rarely leads to relevant problems in the clinical history of polycystic pa-tients. One of the new relevant aspects concern bone disorders, that can exert a considerable influence on the clinical course of these patients. This review aims to provide the “state of art” among extrarenal mani-festation of ADPKD.
Adaptive Trajectories CFAR Mirror Filters and Elevation Angle Evaluation for MIMO Radar-Based Hand Gesture Recognition
Authors: Tseng Tzu-Jung , Ding Jian-Jiun
Published: January 2024

Gesture recognition technology has been quickly developed in the field of human-computer interaction. The multiple-input multiple-output (MIMO) radar has been widely adopted in gesture recognition because of its notable spatial resolution. In this work, a highly accurate MIMO radar-based hand gesture recognition algorithm with very low complexity is proposed. To make the proposed system applicable in the industry and work well even when the size of the training data is limited, we applied several low-complexity adaptive signal processing methods to extract features and reduce the noise effect. First, spectrum analysis is applied to range-Doppler maps (RDMs) and a cell-averaging constant false alarm rate (CA-CFAR) with mirror filters is applied to improve the robustness to noise. Afterward, the features related to the distance, speed, direction, and the elevation angle of the moving object are determined by the proposed adaptive signal analysis techniques and the random forest is applied for classification. The proposed system has the capability to precisely distinguish and identify eight motions, including waving, moving to the left or right, patting, pushing, pulling, and rotating clockwise or anticlockwise, with an accuracy of 95%. Experiments demonstrate the capability of the proposed hand gesture recognition system to classify different movements precisely.
Elastic Buckling Behaviour of Skew Functionally Graded Material (FGM) Thin Plates with Circular Openings
Authors: Alashkar Adnan , Elkafrawy Mohamed , Hawileh Rami , AlHamaydeh Mohammad
Published: January 2024

This study investigates the elastic buckling behaviour of skew Functionally Graded Material (FGM) thin plates featuring a circular opening. FGM materials, known for their unique property gradients, have gained prominence in structural engineering due to their mechanical performance and durability. Including a circular opening introduces a critical geometric consideration, influencing the structural stability and load-carrying capacity of FGM plates. The study examines the effects of the skew angle, plate’s aspect ratio, opening position, and size on the critical buckling load, normalized buckling load, and various buckling failure modes through computer modelling and finite element analysis. The results offer valuable insights into the interplay between material heterogeneity, geometric configuration, and structural stability. For instance, the critical buckling load increases by 29%, 82%, and 194% with the increment of skew angle from 0° to 30°, 45°, and 60°, respectively. Moreover, as the opening shifts from the plate’s edge closer to the center, the critical buckling load decreases by 26%. This research contributes to the advancement of understanding FGM thin plates’ behaviour under skew loading conditions, with implications for the design and optimization of innovative structures. The findings presented provide a foundation for further exploration of advanced composite materials and their applications in structural engineering.
The “M and P” Technique for Damage Identification in Reinforced Concrete Bridges
Authors: Bakalis Athanasios , Makarios Triantafyllos , Lekidis Vassilis
Published: January 2024

The seismic damage in reinforced concrete bridges is identified in this study using the "M and P" hybrid technique initially developed for planar frames. The proposed methodology involves a series of pushover and instantaneous modal analyses with a progressively increasing target deck displacement along the longitudinal direction of the bridge. From the results of these analyses, the diagram of the instantaneous eigenfrequency of the bridge, ranging from the health state to near collapse, is plotted against the inelastic seismic deck displacement. By pre-determining the eigen-frequency of an existing bridge along its longitudinal direction through "monitoring and frequency identification", the target deck displacement corresponding to the damage state can directly be found from this diagram. Subsequently, the damage can be identified by examining the results of the pushover analysis at the step where the target deck displacement is indicated. The effectiveness of this proposed technique is evaluated in the context of multiple span bridges with unequal pier heights, illustrated through an example of a four-span bridge. The findings demonstrate that the damage potential in bridge piers can be successfully identified by combining the results of a monitoring process and pushover analysis.
Unmanned Airborne Bistatic InSAR Data Processing Method Using Bi-Directional Synchronization Chain Signals
Authors: Zhu Jinbiao , Lin Bei , Pan Jie , Yao Cheng , Qiu Xiaolan , Jiang Wen , Liu Yuquan , Liu Mingqian
Published: January 2024

The dual-station Interferometric Synthetic Aperture Radar (InSAR) system can overcome the physical limitations imposed by the baseline of single-station dual-antenna InSAR. It provides greater flexibility and can enhance elevation measurement accuracy through a well-designed baseline configuration.Unmanned aerial vehicles (UAV) equipped with dual-station InSAR, with relatively low cost and high flexibility, are useful for mapping and land resource exploration. However, due to challenges including spatiotemporal synchronization and motion errors, there are limited reports on UAV-borne dual-station InSAR. This paper proposes a comprehensive method for processing data from small UAV-borne dual-station InSAR by integrating two-way synchronization chain signals. The proposed method includes compensation for time and phase synchronization errors, trajectory refinement with synchronized chain and Position and Orientation System (POS) data, high-precision dual-station InSAR imaging and interferometric processing. Height inversion results based on the proposed method is also provided, demonstrating the effectiveness of the proposed method and improving interferometric accuracy at calibration points from 0.66 meters to 0.42 meters.
A Comprehensive Review for Strategies to Promote Anaerobic Digestion: Focus on Their Mechanism and Digestion Performance
Authors: Li Xiaoyong , Wang Zhi , He Yun , Wang Yuzhong , Wang Shilei , Zheng Zehui , Wang Songtao , Xu Jingliang , Cai Yafan , Ying Hanjie
Published: January 2024

The low and unstable performance is still one of the major obstacles for anaerobic digestion, which provokes researchers to develop some strategies to improve it. In addition to traditional approaches such as co-digestion, pretreatment, and recirculation, some emerging strategies, namely additive and microaeration have also been recognized and developed in recent years due to the update of knowledge. Many studies have evaluated the effect of those strategies on digestion performance. However, it lacks a unified analysis and induction, especially the mechanism for different strategies. Therefore, this review presents a comprehensive view of research progress on the strategies based on latest researches considering five main strategies. Critical think and summary of their mechanism, reactor performance, and availability of those strategies were executed. The results demonstrated that the contribution of microaeration is mainly to balance the composition and activity of hydrolysis, acidogenesis, and methanogenic archaea. Recirculation and co-digestion balance mass and reaction environments. Pretreatment makes the structure of the substrate (such as removing lignin, reducing cellulose crystallinity, and increasing the substrate-specific surface area) more conducive to microbial utilization. The mechanism of the additive strategy varies greatly depending on the type of additive, such as enhancing interspecies electrons transfer through conductive materials, resisting adverse digestion conditions through functional microbial additives, and accelerating nutrient absorption by regulating the bioavailability of trace elements. Although these strategies have different mechanisms for promoting digestion performance, their ultimate goal is to make the parameters of the reactor to an ideal status, and then to achieve a balance among substance, microorganisms and water in anaerobic reactor.
Innovative Tubular Thermoelectric Generator (TTEG) for Enhanced Waste Heat Recovery in Industrial and Automotive Applications
Authors: Du Kung-Wen , Wu Chun-I
Published: January 2024

In response to the growing need for efficient energy conversion technologies, this pa-per introduces an innovative Tubular Thermoelectric Generator (TTEG), specifically de-signed for high-efficiency conversion of waste heat into electrical energy. Unlike conven-tional flat plate thermoelectric generators (FTEGs), the TTEG incorporates full-ring ther-moelectric elements within a tubular layout, offering a novel approach to thermal energy recovery from fluid-based systems. This design significantly enhances the heat transfer capabilities, thereby improving the efficiency of energy conversion.
Comprehensive simulations and analyses form the core of this study, where the per-formance of the TTEG is rigorously compared with traditional FTEGs. These comparisons highlight the advantages of the tubular design in terms of energy conversion efficiency and practical applicability in various scenarios. The findings reveal that the TTEG not only outperforms its flat plate counterparts but also presents a scalable and adaptable so-lution for waste heat recovery in a wide range of industrial and automotive applications.
This research contributes to the field of energy science and technology by presenting a detailed experimental setup, complete with reproducible procedures and results. It opens new pathways for the development of more sustainable and efficient energy conversion systems, aligning with the goal of harnessing renewable and sustainable energy sources. The potential applications of this technology in enhancing energy efficiency and reducing environmental impact are vast, making it a significant step forward in the quest for clean and sustainable energy solutions.
Identification and Mitigation of Predominant Challenges in the Utilization of Aged Traction Batteries within Stationary Second-Life Scenarios
Authors: Frank Merlin , Holz Daniel Serafin , Klohs Domenic , Offermanns Christian , Heimes Heiner Hans , Kampker Achim
Published: January 2024

As the production of battery cells experiences exponential growth and electric vehicle fleets continue to expand, an escalating number of traction batteries are nearing the conclusion of their operational life for mobility purposes, both presently and in the foreseeable future. Concurrently, the heightened interest in sustainable energy storage solutions has spurred investigations into potential second-life applications for aging traction batteries. Nonetheless, the predominant practice remains the removal of these batteries from electric vehicles, signifying the end of their life cycle, and their subsequent incorporation into recycling processes, with limited consideration for life-extending measures. This study seeks to elucidate the reasons behind the deprioritization of battery repurposing strategies. Therefore, the research team conducted two industry studies with over 20 battery experts from Europe, revealing concerns about the economic viability of repurposing batteries for stationary storage applications. A literature review of studies published since 2016 confirmed the industry's struggles to address this issue theoretically. In conclusion, a research question was formulated, and a solution approach was delineated to assess the economic prospects of aged traction batteries within the industry's landscape in the future. This solution approach encompasses pertinent market analysis, the identification of representative second-life applications, as well as the formulation of a methodology for evaluating the residual value of these batteries.
Experimental Investigations on the Ferromagnetic Resonance and Absorbing Properties of a Ferrofluid in the Microwave Range
Authors: Malaescu Iosif , Marin Catalin N. , Fannin Paul C.
Published: January 2024

Measurements of complex magnetic permeability, μ(f,H)=μ′(f,H)-iμ″(f,H) and dielectric permittivity ε(f,H)=ε′(f,H)-iε″(f,H), in the frequency range, f of (0.4-7) GHz, and polarizing field, H of (0–135) kA/m, were performed, for a kerosene-based ferrofluid with magnetite nanoparticles. Based on these measurements, the phenomenon of ferromagnetic resonance was highlighted and some microwave propagation parameters of the ferrofluid were determined: the attenuation constant, α(f,H), and the reflection coefficient, R(f,H), at the air-material interface. Knowing these parameters we proposed a theoretical model establishing for the first time a new equation that allows the calculation of the overall reflection coefficient, Rw(f,H), of a ferrofluid with thickness d, deposited on a totally reflective support, following multiple internal reflections of the electromagnetic wave in the material. The results show that by increasing both, H, and d, the parameter, Rw(f,H) presents a minimum that decreases from 0.90 (for d=2mm) to 0.64 (for d=10 mm), at frequency f=5 GHz, which indicates an increase in the absorption of the electromagnetic wave by the ferrofluid. The obtained results are useful in the study of some materials that could be used as electromagnetic absorbers in the microwave range, by the determination of the overall reflection coefficient, Rw(f,H), controlled both by the thickness, d , of the absorber and by the external applied field, H.
Lateral Convergence Deformation Prediction of Subway Shield Tunnel Based on Kalman Model
Authors: Bao Yan , Zheng Yexin , Tang Chao , Meng Xiaolin , Sun Zhe , Zhang Dongliang , Wang Li
Published: January 2024

In order to master the structure state of subway shield tunnel, reduce the diseases and avoid the potential safety hazards, the lateral convergence deformation of subway shield tunnels should be predicted. For the non-stationarity small sample size of subway shield tunnel lateral convergence deformation value, the existing prediction models have poor performance in terms of accuracy and stability. In this paper, a lateral convergence model of subway shield tunnel based on Kalman algorithm is constructed based on Kalman filtering theory. The model is efficient, adaptive and robust, and can accurately predict the lateral convergence deformation of subway shield tunnel. Taking the horizontal diameter of 200 rings shield segment in the interval section of a subway tunnel as an example, it is proved that the residuals of the Kalman prediction model are small, the residual distribution conforms to the normal distribution, and the prediction effect is great. The model is suitable for the prediction of more than 5 periods of data, and the prediction accuracy of the model is improved with the increase of the number of data periods. In addition, the Kalman model is compared with GM(1,1) model and GM-Markov model, and RMSE and MAPE are introduced as evaluation indexes. The results show that the Kalman model has higher prediction accuracy and is more suitable for predicting the lateral convergence deformation of subway shield tunnel.