bluuebunny/crossref_metadata_2025 huggingface dataset:
High-Risk Neuroblastoma Challenges and Opportunities for Antibody-Based Cellular Immunotherapy
Authors: Persaud Natasha V. , Park Jeong A. , Cheung Nai Kong V.
Published: August 2024

Immunotherapy has emerged as an attractive option for patients with relapsed or refractory high-risk neuroblastoma (HRNB). Neuroblastoma (NB), a sympathetic nervous system cancer arising from an embryonic neural crest cell, is heterogeneous clinically, with outcomes ranging from an isolated abdominal mass that spontaneously regresses to a widely metastatic disease with cure rates of about 50% despite intensive multimodal treatment. Risk group stratification and stage-adapted therapy to achieve cure with minimal toxicities have accomplished major milestones. Targeted immunotherapeutic approaches including monoclonal antibodies, vaccines, adoptive cellular therapies, their combinations, and their integration into standard of care are attractive therapeutic options, although curative challenges and toxicity concerns remain. In this review, we provide an overview of immune approaches to NB and the tumor microenvironment (TME) within the clinical translational framework. We propose a novel T cell-based therapeutic approach that leverages the unique properties of tumor surface antigens such as ganglioside GD2, incorporating specific monoclonal antibodies and recent advancements in adoptive cell therapy.
Mortality during the SARS-CoV-2 Pandemic: A Comparative Analysis between Lombardy in Italy and Israel
Authors: Najjar-Debbiny Ronza , Nobili Alessandro , Mannuccio Mannucci Pier , Barnett-Griness Ofra , Saliba Walid , Adir Yochai , Antonella Galbussera Alessia , Tettamanti Mauro , D’Avanzo Barbara , Harari Sergio
Published: August 2024

Background: This retrospective study contrasts the impact of the SARS-CoV-2 pandemic in Lombardy (Italy) and Israel, focusing on mortality, healthcare response, public health measures, and demographics. Methods: We analyzed SARS-CoV-2 data from Lombardy and Israel covering four viral waves. Data included infection rates, hospitalizations, and mortality. In Lombardy, healthcare data were collected from the administrative database of the Lombardy Welfare Directorate; in Israel, they were collected from Clalit Health Services and the Israeli Ministry of Health’s COVID-19 database. Statistical analyses compared trends in infection rates, demographics, and mortality rates across the four viral waves by using logistic and linear regression models and adjusting for age, sex, and comorbidities. Results: Lombardy exhibited significantly higher SARS-CoV-2 infections and COVID-19 hospitalization rates during the first wave than Israel, with 71,558 cases over a population sample of ~10 million versus 5741 over a population sample of ~4.7 million in Israel. The majority of cases in Israel were managed at home, with 18 cases only (0.3%) requiring intensive care unit (ICU) hospitalization during the first wave, compared to 4104 (5.7%) cases in Lombardy. Israel’s vaccination campaign began earlier, so that by the fourth wave, 439,545 (42.2%) people in Israel were fully vaccinated with three doses, compared to 214,542 (22.9%) in Lombardy. Mortality decreased over time in both sites, dropping from 103 cases (1.8%) to 1550 (0.1%) in Israel and from 13,372 (18.7%) to 4388 (0.3%) in Lombardy. Conclusions: Early public health interventions and vaccination were crucial in managing the SARS-CoV-2 impact.
Comparative Study of Zirconium Nitride Multilayer Coatings: Crystallinity, In Vitro Oxidation Behaviour and Tribological Properties Deposited via Sputtering and Arc Deposition
Authors: Dohm Julius C. , Schmidt Susann , Puente Reyna Ana Laura , Richter Berna , Santana Antonio , Grupp Thomas M.
Published: August 2024

This study aims to evaluate and compare the properties of a biomedical clinically established zirconium nitride (ZrN) multilayer coating prepared using two different techniques: pulsed magnetron sputtering and cathodic arc deposition. The investigation focuses on the crystalline structure, grain size, in-vitro oxidation behaviour and tribological performance of these two coating techniques. Experimental findings demonstrate that the sputter deposition process resulted in a distinct crystalline structure and smaller grain size compared to the arc deposition process. Furthermore, in vitro oxidation caused oxygen to penetrate the surface of the sputtered ZrN top layer to a depth of 700 nm compared to 280 nm in the case of the arc-deposited coating. Finally, tribological testing revealed the improved wear rate of the ZrN multilayer coating applied by sputter deposition.
Novel Modeling for the Calculation of the Center of Lateral Resistance Position of Different Ships Making Use of a Full Mission Bridge Simulator and AI Tools
Authors: Pérez-Canosa José M. , Lama-Carballo Francisco Javier , Salgado-Don Alsira , Cao-Feijóo Genaro , Pacheco Eliseo A. , Orosa José A.
Published: August 2024

Ship maneuvering in ports is increasingly reduced because the increase in ship size is not proportional to the increase in port areas. Furthermore, the number of assisted vessels and the need for tugboats working in densely populated areas make it necessary to reduce the number of involved tugboats, reducing pollution and costs. Therefore, shiphandlers must know, in addition to the pivot point, the center of lateral resistance under any circumstance to optimize the assistance from tugboats and improve maritime navigation. From the literature, it is evident that the practical determination of the center of lateral resistance is still unknown. This paper aims to propose novel mathematical models to identify the position of this point and the most important variables that determine its position. For that, data of different ships in different conditions were obtained from a full mission bridge simulator. Afterwards, 15 novel mathematical models were developed, making use of artificial intelligence tools and training neural networks. The high determination factor reached in some models shows the accuracy of the obtained models. One advantage of the presented models is that they are very easy to be applied by shiphandlers, because highly well-known parameters are involved. Moreover, original 3D charts showing the combination of the input variables were generated to identify the map of the whole process. The very simple new models obtained and the novel 3D charts shown in the present paper can be considered useful and applicable by the shiphandlers of most of the merchant fleet to improve the efficiency and safety of maritime navigation in increasingly restricted waters.
Numerical Simulation of a Floating Offshore Wind Turbine in Wind and Waves Based on a Coupled CFD–FEA Approach
Authors: Song Xuemin , Bi Xueqing , Liu Weiqin , Guo Xiaoxuan
Published: August 2024

A floating offshore wind turbine (FOWT) normally suffers from complex external load conditions. It is vital to accurately estimate these loads and the subsequent structural motion and deformation responses for the safety design of the FOWT throughout its service lifetime. To this end, a coupled computational fluid dynamics (CFD) and finite element analysis (FEA) approach is proposed, which is named the CFD–FEA coupled approach. For the CFD approach, the volume of fluid (VOF), the dynamic fluid–body interaction (DFBI), and overset with sliding meshes are used to capture the interface of the air and the water and to calculate wind/wave loads and the motion response of the FOWT. For the FEA approach, the explicit nonlinear dynamic finite element method is employed to evaluate structural deformation. The one-way coupling scheme is used to transfer the data from the CFD approach to the FEA approach. Using the NREL 5 MW FOWT with a catenary mooring system as the research object, a series of full-scale simulations with various wind speeds, wave heights, and wave directions are implemented. The simulation results provide a good insight into the effect of aero-hydrodynamics and fluid hydrodynamics loads on both the motion and deformation responses of the FOWT, which would contribute to improving its design.
Experimental Study of Negative Skin Friction of Pile Group Foundations for Offshore Wind Turbines on Artificial Islands
Authors: Yan Yeyu , Dai Guoliang , Chen Zhiwei , Hu Tao , Gong Weiming , Shi Chenchen
Published: August 2024

Constructing offshore wind turbines on artificial islands is considered a viable option, but negative skin friction (NSF) is a significant adverse factor that cannot be ignored. The NSF adversely affects the bearing capacity of pile foundations. Currently, design methods for studying the impact of NSF group effects mainly rely on empirical approaches. Moreover, existing experimental studies do not simulate the NSF experienced by offshore wind turbine pile groups on artificial islands. In order to further explore the impact of pile group effects on NSF experienced by offshore wind turbine pile foundations on artificial islands, this study conducted indoor model tests on single piles and 3 × 3 rectangular pile groups in sandy soil under uniformly distributed loading on surrounding soil. The experiment measured the settlement of piles at various positions within single piles and rectangular pile groups, as well as the settlement of the soil surrounding the piles and the NSF. Through calculations, the experiment determined the neutral points and NSF group effect coefficients for each pile. The results indicate that densely spaced pile groups are advantageous in reducing settlement of the surrounding soil, thereby mitigating the adverse effects of NSF. Due to the influence of pile group effects, different positions within the group experience varying degrees of NSF. Consequently, in practical engineering applications, settlement of both the pile groups and the surrounding soil should be calculated separately. Furthermore, design considerations for the uplift forces and neutral points of piles at different positions within the pile group should adhere to distinct standards.
Bibliometric Analysis of the Machine Learning Applications in Fraud Detection on Crowdfunding Platforms
Authors: Cardona Luis F. , Guzmán-Luna Jaime A. , Restrepo-Carmona Jaime A.
Published: August 2024

Crowdfunding platforms are important for startups, since they offer diverse financing options, market validation, and promotional opportunities through an investor community. These platforms provide detailed company information, aiding informed investment decisions within a regulated and secure environment. Machine learning (ML) techniques are important in analyzing large data sets, detecting anomalies and fraud, and enhancing decision-making and business strategies. A systematic review employed PRISMA guidelines, which studied how ML improves fraud detection on digital crowdfunding platforms. The analysis includes English-language studies from peer-reviewed journals published between 2018 and 2023 to analyze the pre- and post-COVID-19 pandemic. The findings indicate that ML techniques such as Random Forest, Support Vector Machine, and Artificial Neural Networks significantly enhance the predictive accuracy and utility of tax planning for startups considering equity crowdfunding. The United States, Germany, Canada, Italy, and Turkey do not present statistically significant differences at the 95% confidence level, standing out for their notable academic visibility. Florida Atlantic and Cornell Universities, Springer and John Wiley & Sons Ltd. publishing houses, and the Journal of Business Ethics and Management Science magazines present the highest citations without statistical differences at the 95% confidence level.
The Role of Artificial Intelligence in Eliminating Accounting Errors
Authors: Al Najjar Moustafa , Gaber Ghanem Mohamed , Mahboub Rasha , Nakhal Bilal
Published: August 2024

This study investigates the impact of artificial intelligence (AI) on reducing accounting errors from two distinct angles: that of accounting software developers and of certified public accountants. We employ a questionnaire-based approach informed by prior research and validated through pilot testing. Our findings reveal significant benefits for software developers. AI effectively addresses various accounting errors, including tax rate discrepancies, cutoff period inaccuracies, principal violations, concealed transactions, mathematical mistakes, and manipulation errors. However, when considering users, AI’s effectiveness varies. While it successfully mitigates certain errors, such as those related to principles, it falls short in eliminating mathematical errors. This research contributes fresh insights into the role of AI in accounting within emerging markets, enhancing our understanding of its potential and limitations.
Rainbow Step Barrier Options
Authors: Guillaume Tristan
Published: August 2024

This article provides exact analytical formulae for various kinds of rainbow step barrier options. These are highly flexible and sophisticated multi-asset barrier options based on the following principle: the option life is divided into several time intervals on which different barriers are monitored w.r.t. different underlying assets. From a mathematical point of view, new results are provided for the first passage time of a multidimensional geometric Brownian motion to a boundary defined as a step function. The article shows how to implement the obtained option valuation formulae in a simple and very efficient manner. Numerical results highlight a strong sensitivity of rainbow step barrier options to the correlations between the underlying assets.
Does the Carbon Emissions Trading Pilot Policy Have a Demonstrated Impact on Advancing Low-Carbon Technology? Evidence from a Case Study in Beijing, China
Authors: Zhong Jiaxin , Zhang Jianjun , Fu Meichen
Published: August 2024

In response to the international appeal of developing low-carbon economy and realizing carbon peaking and neutrality goals, China has been exploring the construction of the carbon emissions trading market for years. Without the guidance of advanced technology, there would not be a low-carbon economy in the first place. Based on panel data of 30 provinces and cities in China from 2005 to 2020, this paper takes Beijing—which is the first pilot city in China—as the only treated group and uses the Synthetic Control Method to study the impact of the pilot policy on low-carbon technology innovation. The results show that, firstly, the number of low-carbon technology patents in Beijing increases significantly after the implementation of the pilot policy, proving a positive influence on technology innovation. Secondly, the policy effect has a certain time lag and is sensitive to the shock from both domestic and foreign carbon market, but this effect is gradually stable over time. This paper confirms that technological innovation is the key means of promoting the development of the low-carbon economy and calls on various carbon trading markets to pay attention to the internal mechanism of promoting low-carbon technology innovation to stimulate the vitality of market entities.
Assessing Historical LULC Changes’ Effect on Ecosystem Services Provisioning and Their Values in a Mediterranean Coastal Lagoon Complex
Authors: Mirli Anastasia , Latinopoulos Dionissis , Galidaki Georgia , Bakeas Konstantinos , Kagalou Ifigenia
Published: August 2024

Urbanization and land claim trends for agriculture have led to land use/land cover (LULC) changes, acting as driving forces for several natural environment alterations. The ecosystem services (ES) concept links ecosystem degradation with direct adverse effects on human welfare, emphasizing the importance of balancing human activities and ecosystem health. LULC changes and their impacts on ES are crucial for nature conservation and decision-making. To support sustainable management, a historical (75-year) assessment of Nestos Delta lagoons was conducted, using aerial photos and satellite images, providing valuable insights into the drivers and trends of these changes. Until 1960, water-related Biomes were affected the most, in favor of agricultural (Nestos River incubation) and urban ones, but anthropogenic activities development rate reduced after land reclamation. Since their inclusion in the Natura 2000 network and designation as a National Park, they have been protected from rapid development. Over the past two decades, they have increased the economic value of their cultural ES, while deteriorating regulating and having a minimal impact on provisioning services, resulting in a cumulative loss exceeding USD 30 million during the study period. This study strongly indicates the vital importance of legislative protection and the integration of the ES approach in priority habitat management.
English Immersion as Family Language Policy in Spanish Households: Agentive Practices and Emotional Investments
Authors: Relaño-Pastor Ana María
Published: August 2024

This article explores English immersion as a type of family language policy in the Spanish region of Castilla-La Mancha. Although the field of family language policy (FLP) has exponentially grown in the last decade to include a range of multilingual contexts across the world, the policies regarding the use of English in monolingual Spanish households have received little attention. Due to the global spread of English, Spanish families invest in their children’s language education by maximizing opportunities for exposure to English inside and outside the home. This sociolinguistic ethnography of a group of 15 monolingual Spanish families with no to advanced English proficiency explores the interplay of English language ideologies, language socialization practices, and emotional investments in narratives of language experiences. This article discusses the enactment of agency among these families to sustain English immersion, which is driven by families’ English learning trajectories, professional development identities, and affective stances shaping lived experiences with English. Two main research questions organize this article: (1) How do Spanish families envision, manage, and implement English immersion practices? (2) How do these English immersion policies shape the sociolinguistic order at home and beyond for their children? Based on the findings provided by narratives of language experiences among these families, this study addresses the tensions and dilemmas related to English immersion in the field of family language policy.
Disabled Pedestrians, Micromobility, and Furthering Disability Equality Law through Consultation: A Case Study of the Toronto E-Scooter Ban
Authors: Jacobs Laverne , Dhaliwal Harry
Published: August 2024

This article documents and explores the history of the e-scooter ban in Toronto, Ontario, Canada as a pathway to examining broader issues concerning the eradication of accessibility barriers in public spaces for pedestrians with disabilities and respectful uses of consultation to develop disability-inclusive regulations. The use of e-scooters poses a particular dilemma to accessibility for persons with disabilities. On the one hand, the concept of disability contemplates attitudinal and environmental barriers, as noted, for example, in the Preamble of the United Nations (UN) Convention on the Rights of Persons with Disabilities (CRPD). Attitudinal and environmental barriers have traditionally stemmed from interests that are inherently opposed to the collective interests of disabled persons. Examples include attitudes that project stigma against persons with disabilities or a focus on seeking to preserve historical features of the built environment for their aesthetics, without consideration for their accessibility or functionality for disabled persons. They have also generally originated in periods of historical marginalization or exclusion of persons with disabilities. By contrast, e-scooter debates and connected debates regarding the regulation of micromobility vehicles, contain at least one dimension that could very well be shared with persons with disabilities—that is, the preservation of the environment. E-scooters are also a phenomenon of contemporary disability exclusion: policies concerning environmental sustainability, including those promoting e-scooters, are being developed contemporaneously with growing international and national legal recognition of disability rights. These factors render arguments over appropriate regulation of the use of public spaces more complex as, within those arguments, one sees two competing positive policy directions that need to be addressed: the rights of pedestrians with disabilities and environmental sustainability. This article concludes with theoretical and practical suggestions for strengthening regulatory policymaking to address these and other complex intersectional issues of accessibility policy design.
Personalized Treatment for Obstructive Sleep Apnea: Beyond CPAP
Authors: Van Daele Margot , Smolders Yannick , Van Loo Dorine , Bultynck Charlotte , Verbraecken Johan , Vroegop Anneclaire , Lapperre Thérèse , Op de Beeck Sara , Dieltjens Marijke , Vanderveken Olivier M.
Published: August 2024

Obstructive sleep apnea (OSA) is a sleep disorder characterized by repetitive episodes of partial or complete obstruction of the upper airway during sleep. Continuous positive airway pressure (CPAP) is a method used as a first-line treatment for obstructive sleep apnea (OSA). However, intolerance and resistance to CPAP can limit its long-term effectiveness. Alternative treatments are available, such as Mandibular Advancement Devices (MADs), positional therapy, upper airway surgery, and maxillomandibular osteotomy. However, often less efficient in reducing the apnea-hypopnea index, the higher tolerance of and compliance to alternative treatment has resulted in the adequate treatment of OSA in CPAP-intolerant patients. This paper describes the protocol of a prospective single-center cohort study including adult patients with moderate to severe OSA (15 events/h ≤ apnea-hypopnea index (AHI) < 65 events/h) that failed to comply with CPAP therapy. Selected patients will be invited to the clinic to explore alternative treatment options where DISE will be a first step in further identifying upper airway collapse during sleep. By exploring alternative treatment options in CPAP-intolerant patients and systematically documenting their treatment paths, an algorithm can be defined to better guide patients towards personalized treatment for OSA. The follow-up is aimed at 5 years with an inclusion of 170 patients per year, including a drop-out rate of 15%. By leveraging a real-world database, this study aims to bridge the gap between research and clinical practice, facilitating the development of evidence-based guidelines and personalized treatment algorithms for CPAP-intolerant patients.
An Internal-State-Variable-Based Continuous Dynamic Recrystallization Model for Thermally Deformed TC18 Alloy
Authors: Wu Gui-Cheng , Lin Yong-Cheng , Wan Miao , Zeng Ning-Fu , Zhang Song , Zhang Hui-Jie , Chen Ming-Song , Jiang Yu-Qiang
Published: August 2024

Continuous dynamic recrystallization (CDRX) is widely acknowledged to occur during hot forming and plays a significant role in microstructure development in alloys with moderate to high stacking fault energy. In this work, the flow stress and CDRX behaviors of the TC18 alloy subjected to hot deformation across a wide range of processing conditions are studied. It is observed that deformation leads to the formation of new low-angle grain boundaries (LAGBs). Subgrains rotate by absorbing dislocations, resulting in an increase in LAGB misorientation and the transition of some LAGBs into high-angle grain boundaries (HAGBs). The HAGBs migrate within the material, assimilating the (sub)grain boundaries. Subsequently, an internal state variable (ISV)-based CDRX model is developed, incorporating parameters such as the dislocation density, adiabatic temperature rise, subgrain rotation, LAGB area, HAGB area, and LAGB misorientation angle distribution. The values of the correlation coefficient (R), relative average absolute error (RAAE), and root-mean-square error (RMSE) between the anticipated true stress and measured stress are 0.989, 6.69%, and 4.78 MPa, respectively. The predicted outcomes demonstrate good agreement with experimental findings. The evolving trends of the subgrain boundary area under various conditions are quantitatively analyzed by assessing the changes in dynamic recovery (DRV)-eliminated dislocations and misorientation angles. Moreover, the ISV-based model accurately predicts the decreases in grain and crystallite sizes with higher strain rates and lower temperatures. The projected outcomes also indicate a transition from a stable and coarse-grained microstructure to a continuously recrystallized substructure.
Pad Alignment Methods and Their Impact on Large Hydrostatic Bearing Precision
Authors: Foltýn Jan , Hurník Jakub , Michalec Michal , Svoboda Petr , Křupka Ivan , Hartl Martin
Published: August 2024

Hydrostatic bearings are frequently used for moving large structures smoothly and precisely. In such applications, difficulties with manufacturing, transportation, and assembly arise. The safety and precision of the entire supported structure depend on the accuracy of the hydrostatic bearing alignment. There are several suitable methods for its alignment, yet it is not clear which method can achieve the highest bearing precision. This study provides a comparative experimental assessment of the three methods. The measurements were performed on a hydrostatic bearing test rig with independent positioning of the pads. Conventional measuring devices, a pressure distribution alignment method, and an optical method, OCMM (optical coordinate measuring machine), were compared. The accuracy of the selected methods and the difficulty of the aligning process were included in the comparison. The OCMM method was able to achieve an accuracy 1.6 times higher relative to the pressure method and 6 times higher compared to conventional measuring devices. This method is versatile and can be applied for a wide range of bearing sizes.
Artificial Intelligence Enabling Denoising in Passive Electronic Filtering Circuits for Industry 5.0 Machines
Authors: Massaro Alessandro
Published: August 2024

The paper proposes an innovative model able to predict the output signals of resistance and capacitance (RC) low-pass filters for machine-controlled systems. Specifically, the work is focused on the analysis of the parametric responses in the time- and frequency-domain of the filter output signals, by considering a white generic noise superimposed onto an input sinusoidal signal. The goal is to predict the filter output using a black-box model to support the denoising process by means of a double-stage RC filter. Artificial neural networks (ANNs) and random forest (RF) algorithms are compared to predict the output of noisy signals. The work is concluded by defining guidelines to correct the voltage output by knowing the predictions and by adding further RC elements correcting the distorted signals. The model is suitable for the implementation of Industry 5.0 Digital Twin (DT) networks applied to manufacturing processes.
Time-Delay Estimation Improves Active Disturbance Rejection Control for Time-Delay Nonlinear Systems
Authors: Nahri Syeda Nadiah Fatima , Du Shengzhi , van Wyk Barend J. , Nyasulu Tawanda Denzel
Published: August 2024

Lately, active disturbance rejection control (ADRC), a model-independent controller, has become popular for combating various forms of uncertain disturbances incurred in industrial applications. ADRC was validated for external disturbances, internal disturbances, and nonlinearities incurred under realistic scenarios. Time delay challenges all controllers, especially when it coexists with nonlinearities. This paper investigates the impacts of time delay and backlash-like hysteresis nonlinearity in ADRC-controlled systems. These impacts are analyzed, as in the case study, in two ADRC-based methods, namely the ADRC with delayed input method and the predictive extended state observer (PESO)-based ADRC (PESO-ADRC) method. To improve the system response and to attain a decent attenuation of uncertainties, the time-delay estimation (TDE) mechanism is introduced to the concerned ADRC-based methods. Experimental studies are conducted to verify the effectiveness and stability of the proposed TDE-ADRC methods. The results demonstrate the robustness and decent recovery of the transient response after the adverse impact of the backlash-like hysteresis on both concerned ADRC-controlled systems.
Output Feedback-Based Neural Network Sliding Mode Control for Electro-Hydrostatic Systems with Unknown Uncertainties
Authors: Dang Tri Dung , Do Tri Cuong , Truong Hoai Vu Anh
Published: August 2024

This paper proposes an output feedback-based control for uncertain electro-hydrostatic systems (EHSs) to satisfy high output tracking precision under the influences of unknown mismatched and matched uncertainties and unstructured dynamical behavior. In this configuration, an extended state observer (ESO) is first employed to obtain unmeasured states and suppress the adverse effect of matched uncertainty. Meanwhile, the influence of unstructured dynamical behavior is approximated by employing a radial basis function neural network (RBFNN)-based technique. With the unmeasured states observed, matched uncertainty, and system dynamics compensated, the robust backstepping sliding mode control is accordingly established and the lumped mismatched uncertainty is then suppressed through disturbance observer-based adaptive law. Interestingly, the proposed control methodology requires only output feedback but can address the whole system dynamics. The stability of the closed-loop system is theoretically proven through a Lyapunov theorem and the effectiveness of the proposed methodology is demonstrated through comparative simulations.
A COMSOL-Based Numerical Simulation of Heat Transfer in a Hybrid Nanofluid Flow at the Stagnant Point across a Stretching/Shrinking Sheet: Implementation for Understanding and Improving Solar Systems
Authors: Alharbi Ahmad Ayyad , Alzahrani Ali Rashash R.
Published: August 2024

The present study investigates hybrid nanofluid (HNF) behavior at the stagnation point near a stretching/shrinking sheet using the Tiwari and Das model. The governing equations were transformed into a boundary layer flow model and simulated using COMSOL Multiphysics 6.0. This research examines flow characteristics, temperature profiles, and distributions by varying parameters: stretching/shrinking (λ, −2 to 2), slip flow (δ, 0 to 1 m), suction (γ, 0 to 1), and similarity variables (η, 0 to 5). The HNF comprised equal ratios of copper and alumina with total concentrations ranging from 0.01 to 0.1. The results showed that velocity profiles increased with distance from the stagnation point, escalated in shrinking cases, and decayed in stretching cases. Increased suction consistently reduced velocity profiles. Temperature distribution was slightly slower in shrinking compared to stretching cases, with expansion along the sheet directly proportional to η estimates but controllable through suction adjustments. The findings were applied to enhance photovoltaic thermal (PV/T) system performance. Stretching sheets proved crucial for improving electricity production efficiency. Non-slip wall conditions and increased copper volume fractions in the presence of suction effects led to notable improvements in electrical efficiency. The maximum average efficiency was achieved when γ = 0.4, λ = 2, δ = 0.7, and ϕ2 = 0.01, which was of about 10%. The present numerical work also aligned well with the experimental results when evaluating the thermal efficiency of conventional fluids. These insights contribute to optimizing PV/T system parameters and advancing solar energy conversion technology, with potential implications for broader applications in the field.
Dynamic Contact Analysis of Flexible Telescopic Boom Systems with Moving Boundary
Authors: Zhao Tianjiao , Qi Zhaohui , Wang Tianyu
Published: August 2024

A flexible telescopic boom is a multi-body system composed of several hollow booms nestled into each other. For this kind of system, due to the limitation of the elemental size being fixed, it is necessary to divide it into many small-sized elements and judge which two elements are in a contact state in real time using the traditional finite element methods. This complex operation often requires calculations on enormous scales and can even result in simulation failure. In view of the above difficulties, an efficient dynamic contact analysis model of flexible telescopic boom systems with a moving boundary is proposed in this study. Firstly, on the deformable axis of the boom, some crucial points are defined as inner and outer contact points, and spatial points are selected as nodes for describing the motion of the system. Secondly, in contrast to the traditional solid finite element method, the assumption that elemental nodes are fixed with the material points is removed, and on this basis, a geometrical nonlinear dynamic element with moving nodes is constructed, which can describe the moving boundary problem effectively and is used to model each boom. Thirdly, to better cooperate with the moving boundary conditions, a contact model and its corresponding discretization method are developed on the premise of not removing the sliding joint constraints, which are used for dynamic contact analysis considering the friction effect between adjacent booms. Finally, experiments were conducted to evaluate the accuracy of the modeling, wherein the dynamic response properties of the supported beam under the action of a moving load and the dynamic behavior of the telescopic boom being extracted were analyzed.
The T-Spherical Fuzzy Einstein Interaction Operation Matrix Energy Decision-Making Approach: The Context of Vietnam Offshore Wind Energy Storage Technologies Assessment
Authors: Nhieu Nhat-Luong
Published: August 2024

Fuzzy multi-criteria decision making (FMCDM) is a critical field that addresses the inherent uncertainty and imprecision in complex decision scenarios. This study tackles the significant challenge of evaluating energy storage technologies (ESTs) in Vietnam’s offshore wind sector, where traditional decision-making models often fall short due to their inability to handle fuzzy data and complex criteria interactions effectively. To overcome these limitations, the novel T-spherical fuzzy Einstein interaction operation matrix energy decision-making approach is introduced. This methodology integrates T-spherical fuzzy sets with matrix energy concepts and Einstein interaction operations, thereby eliminating the need for traditional aggregation processes and criteria weight determinations. My approach provides a structured evaluation of ESTs, highlighting that hydrogen storage, among others, demonstrates significant potential for high energy capacity and long-term storage. The findings not only underscore the robustness of this new method in managing the complexities of renewable energy assessment but also offer a comprehensive tool for selecting the most suitable ESTs to support Vietnam’s energy transition strategies. This study recognizes limitations related to data dependency, which could affect the generalizability of the results. Future research is suggested to expand the ESTs considered and integrate extensive real-world operational data, aiming to deepen the exploration of economic impacts and long-term viability of these technologies. This revised approach emphasizes both the challenge of evaluating ESTs under uncertain conditions and my innovative solution, enhancing the relevance and applicability of the findings.
Reinforcement Q-Learning for PDF Tracking Control of Stochastic Systems with Unknown Dynamics
Authors: Yang Weiqing , Zhou Yuyang , Zhang Yong , Ren Yan
Published: August 2024

Tracking control of the output probability density function presents significant challenges, particularly when dealing with unknown system models and multiplicative noise disturbances. To address these challenges, this paper introduces a novel tracking control algorithm based on reinforce-ment Q-learning. Initially, a B-spline model is employed to represent the original system, thereby transforming the control problem into a state weight tracking issue within the B-spline stochastic system model. Moreover, to tackle the challenge of unknown stochastic system dynamics and the presence of multiplicative noise, a model-free reinforcement Q-learning algorithm is employed to solve the control problem. Finally, the proposed algorithm’s effectiveness is validated through comprehensive simulation examples.
Solution of an Initial Boundary Value Problem for a Multidimensional Fourth-Order Equation Containing the Bessel Operator
Authors: Karimov Shakhobiddin , Tulasheva Yorkinoy
Published: August 2024

In the present work, the transmutation operator approach is employed to construct an exact solution to the initial boundary-value problem for multidimensional free transverse equation vibration of a thin elastic plate with a singular Bessel operator acting on geometric variables. We emphasize that multidimensional Erdélyi–Kober operators of a fractional order have the property of a transmutation operator, allowing one to transform more complex multidimensional partial differential equations with singular coefficients acting over all variables into simpler ones. If th formulas for solutions are known for a simple equation, then we also obtain representations for solutions to the first complex partial differential equation with singular coefficients. In particular, it is successfully applied to the singular differential equations, particularly when they involve operators of the Bessel type. Applying this operator simplifies the problem at hand to a comparable problem, even in the absence of the Bessel operator. An exact solution to the original problem is constructed and analyzed based on the solution to the supplementary problem.
Importance of Human Breast Milk in the Early Colonization of Streptococcus mutans
Authors: Córdova-Carrillo Karina , De la Peña-Lobato Cristina , Cuevas-González María Verónica , Cuevas-González Juan Carlos , Espinosa-Cristóbal León Francisco , Tovar-Carrillo Karla Lizette , Saucedo-Acuña Rosa Alicia , Zambrano-Galván Graciela , Reyes-López Simón Yobanny
Published: August 2024

Background and objectives: The development of the oral microbiome begins in the prenatal stage. Breast milk contains antimicrobial proteins, microorganisms, metabolites, enzymes, and immunoglobulins, among others; therefore, differences have been noted in the type of microorganisms that colonize the oral cavity of children who are breastfed compared to those who are formula-fed. Our objective was to establish the relationship between breastfeeding, formula feeding, or mixed feeding (breastfeeding and formula) with the presence of S. mutans in a population of children under 6 months of age. Materials and Methods: The patients were recruited from the Child Care Center of Ciudad Juárez, Chihuahua, and from the pediatric dentistry postgraduate clinics of the Autonomous University of Ciudad Juárez; children exclusively fed maternally, with formula, and/or mixed were included. Those who had been fed within the previous hour were excluded. The sample was taken with a smear of the jugal groove using a sterile micro-brush. For the identification of Streptococcus mutans, a culture of Mitis Salivarius Agar (Millipore) was used. Results: 53.3% corresponded to females and 46.7% to males, 36.7% corresponded to maternal feeding, 23.3% corresponded to formula feeding, and 40% corresponded to mixed feeding. In 90% of the infants, the parents indicated that they did not perform oral hygiene. The CFU count showed that infants who were exclusively breastfed had an average of 9 × 10 CF/mL, formula-fed infants had an average of 78 × 10 CFU/mL, and those who had mixed feeding 21 × 10 CFU/mL. Conclusions: According to the results obtained, it was possible to corroborate that exclusive breastfeeding limits the colonization of Streptococcus mutans compared to those infants who receive formula or mixed feeding; these results could have a clinical impact on the dental health of infants by having a lower presence of one of the main etiological factors involved in dental caries and the type of microbiome established in the oral cavity.
Ultrathin Small Outline Package Key Techniques for High-Speed Chips with Multi-Leads
Authors: Zhang Lijun , Dang Wenqiang , Wang Yongshun , Zhang Jinbing
Published: August 2024

The key technologies for the ultrathin small outline package (TSOP) of large-sized high-speed chips have been designed and developed in this paper. The designing techniques, such as a 25 µm precise positioning dice attaching technique, a lead frame unit structure without a base island, and a lead co-plane layout inside the frame, were developed. The TSO package outline with a large number of leads, a frame unit arrangement, and a frame distribution with a base island and without one were improved. The technological problems, including the reduction in thickness, wafer cutting, chip sticking bonding, and plastic sealing, were successfully solved. The designed large-sized package products have many advantages, such as high availability, low cost, high reliability, and a short production cycle. This package technique can be widely used in various intellectual application regions.
Prevalence of Antimicrobial Resistance in Klebsiella pneumoniae, Enterobacter cloacae, and Escherichia coli Isolates among Stillbirths and Deceased Under-Five Children in Sierra Leone: Data from the Child Health and Mortality Prevention Surveillance Sites from 2019 to 2022
Authors: Ojulong Julius , Gebru Gebrekrstos N. , Duduyemi Babatunde , Gbenda Edwin , Janneh Mohamed L. , Sharty Jack , Monteiro Leonel , Kowuor Dickens , Ameh Soter , Ogbuanu Ikechukwu U.
Published: August 2024

Klebsiella pneumoniae, Escherichia coli, and Enterobacter cloacae are associated with most nosocomial infections worldwide. Although gaps remain in the knowledge of their susceptibility patterns, these are in antimicrobial stewardship. This study aimed to describe antimicrobial susceptibility profiles of the above organisms isolated from postmortem blood from stillbirths and under-five children enrolled in the Child Health and Mortality Prevention Surveillance (CHAMPS) program in Sierra Leone. This was a surveillance study of bacteria isolates from postmortem blood cultures taken within 24 h of death from stillbirths and children aged 0–59 months between March 2019 and February 2022. This was followed by identification and antibiotic sensitivity testing using Becton Dickinson Phoenix M50 (USA). Descriptive analysis was used to characterize the isolates and their antimicrobial susceptibility patterns. Of 367 isolates, K. pneumoniae was the most frequently isolated organism (n = 152; 41.4%), followed by E. coli (n = 40; 10.9%) and E. cloacae (n = 35; 9.5%). Using BACTEC™ FX 40 (Franklin Lakes, NJ, USA), 367 isolates were identified from blood using bacteriological methods. Extended spectrum beta-lactamase (ESBL) was observed in 143 (94.1%) of K. pneumoniae isolates and 27 (65.5%) of E. coli isolates. Carbapenem-resistant organisms (CRO) were seen in 31 (20.4%) of K. pneumoniae and 5 (12.5%) of E. coli isolates. A multidrug resistance (MDR) pattern was most prevalent in E.cloacae (33/35; 94.3%), followed by K. pneumoniae (138/152; 90.8%). Our study showed a high prevalence of multidrug resistance among bacterial isolates in the catchment areas under surveillance by the CHAMPS sites in Sierra Leone.
Identification and Functional Analysis of ncRNAs Regulating Intrinsic Polymyxin Resistance in Foodborne Proteus vulgaris
Authors: Zhang Hongyang , Wu Tao , Ruan Haihua
Published: August 2024

Polymyxin, known as the “last line of defense” against bacterial infection, exerts a significant inhibitory effect on a wide range of Gram-negative pathogenic bacteria. The presence of strains, specifically Proteus vulgaris species, displaying intrinsic polymyxin resistance poses significant challenges to current clinical treatment. However, the underlying mechanism responsible for this intrinsic resistance remains unclear. Bacterial non-coding RNAs (ncRNAs) are abundant in genomes and have been demonstrated to have significant regulatory roles in antibiotic resistance across various bacterial species. However, it remains to be determined whether ncRNAs in Proteus vulgaris can regulate intrinsic polymyxin resistance. This study focused on investigating the foodborne Proteus vulgaris strain P3M and its intrinsic polymyxin resistance regulation mediated by ncRNAs. Through a combination of bioinformatics analysis, mutant construction, and phenotypic experimental verification, we successfully identified the ncRNAs involved and their potential target genes. These findings serve as an essential foundation for the precise identification of ncRNAs participating in the intricate regulation process of polymyxin resistance. Additionally, this study offers valuable insights into the efficient screening of bacterial ncRNAs that contribute positively to antibiotic resistance regulation.
Potential Convergence to Accommodate Pathogenicity Determinants and Antibiotic Resistance Revealed in Salmonella Mbandaka
Authors: Lv Na , Ni Jinjing , Fang Shiqi , Liu Yue , Wan Shuang , Sun Chao , Li Jun , Zhou Aiping
Published: August 2024

Salmonella species are causal pathogens instrumental in human food-borne diseases. The pandemic survey related to multidrug resistant (MDR) Salmonella genomics enables the prevention and control of their dissemination. Currently, serotype Mbandaka is notorious as a multiple host-adapted non-typhoid Salmonella. However, its epidemic and MDR properties are still obscure, especially its genetic determinants accounting for virulence and MD resistance. Here, we aim to characterize the genetic features of a strain SMEH pertaining to Salmonella Mbandaka (S. Mbandaka), isolated from the patient’s hydropericardium, using cell infections, a mouse model, antibiotic susceptibility test and comparative genomics. The antibiotic susceptibility testing showed that it could tolerate four antibiotics, including chloramphenicol, tetracycline, fisiopen and doxycycline by Kirby–Bauer (K-B) testing interpreted according to the Clinical and Laboratory Standards Institute (CLSI). Both the reproducibility in RAW 264.7 macrophages and invasion ability to infect HeLa cells with strain SMEH were higher than those of S. Typhimurium strain 14028S. In contrast, its attenuated virulence was determined in the survival assay using a mouse model. As a result, the candidate genetic determinants responsible for antimicrobial resistance, colonization/adaptability and their transferability were comparatively investigated, such as bacterial secretion systems and pathogenicity islands (SPI-1, SPI-2 and SPI-6). Moreover, collective efforts were made to reveal a potential role of the plasmid architectures in S. Mbandaka as the genetic reservoir to transfer or accommodate drug-resistance genes. Our findings highlight the essentiality of antibiotic resistance and risk assessment in S. Mbandaka. In addition, genomic surveillance is an efficient method to detect pathogens and monitor drug resistance. The genetic determinants accounting for virulence and antimicrobial resistance underscore the increasing clinical challenge of emerging MDR Mbandaka isolates, and provide insights into their prevention and treatment.