“Dark Web” usually describes a new world of e-living space perceived as a place, free from con-straints, in which its main actors generally are criminal, unstable, and mentally disturbed individ-uals. Nowadays, advancements in information and internet technologies have made the Dark Web more accessible in recent decades. The Dark Web is a virtual world component; therefore, as-sessing users’ behavior may be crucial in understanding motivation to use it. This study aims to discuss the behavior patterns of Dark Web users within the theoretical framework of the technol-ogy acceptance model via a structural equation model. The resulting structural equation model showed that considered causal relationships were statistically significant.

This research investigates the intricate dynamics between intellectual Capital (VAIC) and the stability of banks in the evolving context of Saudi Arabia's banking sector. Against the backdrop of rapid economic reforms under Vision 2030 and the challenges imposed by the COVID-19 pan-demic, the research provides a nuanced analysis of how intellectual capital and intellectual capital's components—Human Capital Efficiency (HCE), Structural Capital Efficiency (SCE), and Capital Employed Efficiency (CEE)—affect the financial stability of Saudi banks. The research analyses a decade-long panel dataset from 2012 to 2022, utilizing both fixed effects and cross-section random effects models to discern the impact of intellectual capital on bank stability. The findings reveal a positive overall influence of intellectual capital on bank stability; however, individual compo-nents present a complex relationship, with CEE showing a positive association and HCE and SCE demonstrating unexpected negative correlations with bank stability. The research identifies lev-erage (LEV) as a significant factor negatively impacting stability. Operational efficiency (OPEF) and size (SIZE) also negatively affect stability. Surprisingly, macroeconomic indicators and bank size exhibit non-significant effects on bank stability. Similarly, the direct impact of the COVID-19 pandemic was found to be non-significant, suggesting a resilient banking environment or the presence of effective mitigating strategies. As Saudi Arabia continues its ambitious economic transformation, this research underscores the critical role of effectively managed intellectual capital in ensuring the banking sector's stability. It provides a foundation for ongoing research in this vital area.

The optimal structural design is imperative to minimize material consumption and reduce the environmental impact of construction. Given the complexity in the formulation of structural design problems, the process of optimization is commonly performed using artificial intelligence (AI) global optimization, such as Genetic Algorithm (GA). However, the integration of AI-based optimization together with visual programming (VP) in building information modeling (BIM) projects warrants further investigation. This study proposes a workflow by combining structure analysis, VP, BIM, and GA to optimize trusses. The methodology encompasses several steps including: (i) generation of parametric trusses in Dynamo VP; (ii) performing the finite element modeling (FEM) using Robot Structural Analysis (RSA); (iii) retrieving and evaluating the FEM results interchangeably between Dynamo and RSA; (iv) finding the best solution using GA; and (v) importing the optimized model into Revit, enabling the user to perform simulations and engineering analysis, such as life cycle assessment (LCA) and quantity surveying. The feasibility of the proposed workflow was tested on benchmark problems and compared with open literature. The outcomes of this study offer insight into the opportunities and limitations of combining VP, GA, FEA, and BIM for structural optimization applications, particularly to enhance structural efficiency and sustainability in construction.

The study of rare diseases is important not only for the individuals affected but also for the advancement of medical knowledge and a deeper understanding of human biology and genetics. The wide repertoire of structural information now available from reliable and accurate prediction methods provides the opportunity to investigate the molecular origins of most of the rare diseases reviewed in the Orpha.net database. Thus, it has been possible to analyze the topology of the missense mutations found in the 2,535 proteins involved in Mendelian rare diseases (MRD), which form the database for our structural bioinformatics study. The amino acid substitutions responsible for MRD show different mutation site distributions at different three-dimensional protein depths. We then predicted the depth-dependent effects of mutations for the 20,248 pathogenic variants that are present in our database. The results of this structural bioinformatics investigation are relevant, as they provide additional clues to mitigate the damage caused by MRD.

Wind turbines (WTs) are clean a renewable energy source that has been growing in popularity in recent years. Gearboxes are complex, expensive, and critical components of WT, which are subject to high maintenance costs and several stresses including high loads and harsh environments that can lead to failure with significant downtime and financial losses. This paper focuses on the development of a digital twin-based approach for the modelling and simulation of WT gearboxes with the aim to improve their design, diagnosis, operation, and maintenance by providing insights into their behavior under different operating conditions. Pow-erful commercial computer-aided design tools (CAD) and computer-aided engineering (CAE) software are embedded into a computationally efficient multi-objective optimization framework (modeFrontier) with the aim of maximizing the power density, compactness, performance, and reliability of the WT gearbox. This entails minimizing its weight, volume, and maximum stresses and strains achieved without compromising efficiency. The 3D CAD model of the WT gearbox is carried out using SolidWorks, the Finite Element Analysis (FEA) to obtain the stresses and strains fields are modelled using Ansys Workbench, while the multibody kinematic and dynamic system is analyzed using MSC Adams. The method has been successfully applied to different case studies to find the optimal design and analyze the performance of the WT gearboxes. Simulation results can be used to identify potential failure modes and optimize gearbox design to improve performance, extend service life and relia-bility, thereby ensuring proper operation over its lifetime and reducing maintenance costs.

This research paper focuses on the synthesis and characterization of Cu-doped Mg-Co ferrites with varying compositions (Mg_0.6-xCo_0.4Cu_xFe₂O₄, where x = 0.0, 0.1, 0.2, and 0.3) using a solid-state reaction method. This paper also investigates the structural, morphological, magnetic, and electrical characteristics of synthesized Mg_0.6-xCo_0.4Cu_xFe₂O₄, where x = 0.0, 0.1, 0.2, and 0.3. The X-ray diffraction (XRD) technique confirms the ferrites spinel structure in the Fd-3m space group, with average crystallite sizes ranging from 57.29 to 48.57 nm. Fourier Transform Infrared (FTIR) spectroscopy verifies chemical and structural changes, while scanning electron microscopy (SEM) reveals cubic crystal growth with an average grain size of 1 to 1.5 μm. DC electrical resistivity decreases with increasing temperature and Cu²⁺ substitution, ranging from 1.4 x 10⁶ Ω-cm to 6.7 x 10⁵ Ω-cm. The study suggests a correlation between resistivity and Cu²⁺ concentration. Magnetic behaviour, studied using a Vibrating Sample Magnetometer (VSM), shows dependence on dopant concentration, with coercivity ranging from 157 Oe to 256 Oe. The results indicate potential applications in magnetic storage devices, antennas, transformers, and high-frequency electronics.

The sympathetic restoration and conservation of built cultural heritage play a significant role in the management and preparedness for future climate scenarios by facilitating adaptive reuse, enhancing cultural resilience, preserving traditional knowledge, and boosting tourism. The importance of restoring damaged heritage sites after an earthquake drew international attention to Nepal after the 2015 Gorka Earthquake. UNESCO established an office in Kathmandu to promote the restoration of tangible and intangible heritage in the area. This included developing structural analyses of buildings with historical and cultural value that due to their nature cannot be intervened with the same methodology as modern buildings. In this paper, the case study of the earthquake-damaged Gopinath temple, is discussed. First, an initial visual inspection phase and the following diagnosis of the structure are discussed. Then, the results from a series of static and dynamic structural analyses performed to determine the safety level of the structure, together with a sensitivity analysis, are presented. A sympathetic intervention proposal capable of increasing the temple safety level and based on the addition of timber plates, has resulted in substantial improvements of the lateral behavior of the structure. The proposed intervention is deemed sustainable and able to increase the resilience of the temple in the face of future hazards.

This paper details the comprehensive activities conducted in a laboratory setting to assess the Structural Health Monitoring (SHM) of prefabricated building envelopes. Aimed at enhancing the structural evaluation of buildings, the focus of this research lies in employing nondestructive sensors for SHM with the objective to advance in the understanding and assessment of facade conditions. The paper outlines the methodologies employed, starting with a modal analysis to define the structural vibration's modal frequency. Subsequently, tests were defined and executed to validate building envelope compliance in case of stress typical of high-rise building. Throughout these tests, continuous monitoring of the façade was conducted using both conventional (accelerometers, extensimeter washers) and non-conventional sensors (Fiber Optic Sensing) The gathered data underwent thorough processing and analysis to provide an overall perspective on the structure's behavior during the stress test. The investigation aimed to identify whether specific physical phenomena correlate with distinct signals and to evaluate if continuous façade monitoring over the building's lifespan aids in preventing potential structural damage. Moreover, two modal analyses were conducted to compare final data and frequencies with earlier data, enabling the detection of any structural alterations. The results from compliance testing and structural analysis yielded noteworthy insights contributing to the evolving field of structural health monitoring, offering valuable findings that advance our ability to proactively manage and maintain the integrity of building structures.

Adopting Building Information Modeling (BIM) within the Architecture, Engineering, and Construction (AEC) industry presents an opportunity to address enduring challenges, including chronic productivity deficits and emerging imperatives such as cleaner production and sustainability. However, the pace of BIM implementation (BIMI) across European Union (EU) countries is uneven due to varying contexts and the inherent complexity of BIM adoption. Notably, Portugal lags in BIMI among these countries. Using the Portuguese context, the manuscript endeavours to identify the main barriers to BIMI by the late-adopting countries in the EU and, based on the dynamics of their relationships, design effective mitigation measures to lessen their impact and eventually leverage BIMI. A comprehensive list of barriers was compiled from the literature and ranked by experts through a Delphi survey, resulting in 15 critical barriers. Subsequently, an Interpretive Structural Modelling (ISM) model was constructed to elucidate the hierarchical relationships among these barriers, while a fuzzy Impact Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) analysis was employed to determine their driving and dependence powers. The resulting main barriers were the lack of evaluation and feedback mechanisms on BIMI, ignorance of BIM capabilities/benefits, scarcity of BIM-capable professionals, lack of experience and cooperation in BIMI, resistance to change, and lack of support from top management. Finally, experts formulated mitigation measures aimed at tackling these main barriers. These measures were designed to not only address each barrier individually but also to have a comprehensive and practical impact on the entire barrier system as a whole. These findings will assist researchers, policymakers, and practitioners in comprehending the barriers and hierarchical structures affecting BIMI in EU late-adopting countries.

This paper presents a thorough investigation into the shear strength capacity of reinforced concrete deep beams, with a focus on improving predictive accuracy beyond existing code provisions. Analyzing 198 deep beams from 15 investigations, the study considers parameters such as concrete compressive strength (fc’), shear span to effective depth ratio (av/d), and reinforcement ratios (ρs, ρv, ρh ). Introducing a novel predictive model (Equation 7), the study rigorously evaluates it using nonlinear regression analysis and statistical metrics (MAE, RMSE, R2). The proposed model demonstrates a significant reduction in the coefficient of variation (COV) to 27.08%, surpassing existing codes' limitations. Comparative analyses highlight the model's robustness, revealing improved convergence of data points and minimal sensitivity to variations in key parameters. The findings suggest that the proposed model offers enhanced predictive accuracy across diverse scenarios, making it a valuable tool for structural engineers. This research contributes to advancing the understanding of shear strength in reinforced concrete deep beams, offering a reliable and versatile predictive model with implications for refining design methodologies and enhancing the safety and efficiency of structural systems.

This paper presents a study about the integration of Piezoelectric Energy Harvesting Systems (PE-EHS) in building envelopes for powering Fiber Bragg Grating (FBG) sensors, enabling efficient and low-consumption monitoring with the objective to leverage Structural Health Monitoring (SHM). The research includes preliminary tests conducted in a real environment to validate the PE-EHS when fully integrated into the façade, capturing mechanical vibrations generated mainly by wind loads. Based on these activities, the final configuration of PE-EHS is defined to provide a complete system for façade monitoring. This integrated system includes the Piezoelectric Generator (PEG), Supercapacitor (SC), Power Conditioner Circuit (PCC), Fibre Optic Sensing (FOS) Interrogator, and the IoT Gateway trans-mitting measurement data within an Internet of Things (IoT) monitoring platform. This configuration is tailored to address the challenges related to the structural integrity of building envelopes. Results demonstrate a potential for a stand-alone solution in the façade sector, but, raising issues for certain limitations, requiring further investigation. In particular, the study emphasizes constraints related to the energy production of PE-EHS for façade integration. It highlights the necessity to carefully consider these limitations within the broader context of their applicability, providing insights for the informed deployment of Piezoelectric Energy Harvesting technology in building envelope monitoring.

Acoustic emission monitoring (AEM) has emerged as an effective technique for detecting wire-breaks resulting from, e.g., stress corrosion cracking, and its application on prestressed concrete bridges is increasing. The success of this monitoring measure depends crucially on a carefully designed sensor layout. For this the attenuation of elastic waves within the structure’s material is determined ideally in-situ through object-related measurements with a reproducible signal source, typically a rebound-hammer. This assumes that the attenuation coefficients derived from rebound-hammer tests are comparable to those from wire-breaks, thus allowing their results to be directly applied to wire-break detection without further adjustments. This study challenges this assumption by analysing attenuation behaviour through an extensive dataset. Employing time-domain and frequency analysis, the research generates attenuation profiles from laboratory experiments and in-situ measurements across various girders and bridge structures, extracting the slope and standard deviation of the residuals. While generally validating this approach, the findings highlight differences in attenuation behaviour from among wire-break signals and rebound-hammer impulses, whereby the latter potentially underestimates the relevant attenuation of wire-breaks by approximately 20 %. Consequently, a transfer factor is proposed to adjust object-related measurement results for wire-break scenarios, including a variance of 1.0 dB/m to cover a 95 % confidence interval for sample scattering. Moreover, the anisotropic attenuation behaviour across different structures was studied, showing that transverse attenuation consistently exceeds the longitudinal, significantly influenced by structural features such as voids. In prefabricated concrete bridges with in-situ-cast concrete slabs, transverse signal transmission remains unhindered across multiple elements. Finally, the results provide a valuable reference for the design of sensor layouts in bridge monitoring, particularly benefiting scenarios where direct in-situ experiences are lacking.

Background. Gene rearrangements affecting KMT2A are frequent in acute myeloid leukemia (AML) and are often associated with a poor prognosis. KMT2A gene fusions are often detected by chromosome banding analysis and confirmed by fluorescence in-situ hybridization. However, small intragenic insertions, termed KMT2A partial tandem duplication (PTD), are particularly challenging to detect using standard molecular and cytogenetic approaches. Methods. We have validated the use of a custom hybrid capture based next-generation sequencing (NGS) panel for comprehensive profiling of AML patients seen at our institution. This NGS panel targets the entire consensus coding DNA sequence of KMT2A; to deduce the presence of a PTD we used the relative ratio of KMT2A exons coverage. We sought to corroborate the KMT2A-PTD NGS results using (1) multiplex-ligation probe amplification (MLPA) and (2) optical genome mapping (OGM). Results. We analyzed 932 AML cases and identified 41 individuals harboring a KMT2A-PTD. MLPA, NGS and OGM confirmed the presence of a KMT2A-PTD in 22 of the cases analyzed where orthogonal testing was possible. Two false positive PTD calls by NGS could be explained by the presence of cryptic structural variants impacting KMT2A and interfering with PTD analysis. OGM revealed the nature of these previously undetected gene rearrangements in KMT2A, while MLPA yielded in-conclusive results. MLPA analysis for KMT2A-PTD is limited to exon 4, whereas NGS and OGM resolved KMT2A-PTD sizes and copy number levels. Conclusion. KMT2A-PTDs are complex gene rearrangements that cannot be fully ascertained using a single genomic platform. MLPA, NGS panels and OGM are complementary technologies applied in standard of care testing for AML patients. MLPA and NGS panels are designed for targeted copy number analysis; however, our results show that integration of concurrent genomic alterations is needed for accurate KMT2A-PTD identification. Unbalanced chromosomal rearrangements overlapping with KMT2A can interfere with the diagnostic sensitivity and specificity of copy number based KMT2A-PTD detection methodologies.

The Planetary Roller Screw Mechanisms (PRSMs), alongside Ball Screw Mechanisms (BSMs) and Electromechanical Actuators (EMAs), occupies a pivotal role in advancing the precision and efficiency of various industrial applications, including aerospace, automotive, and high-precision machining tools. Despite their critical advantages such as high load capacity, superior precision, and extended lifespan, the deployment of PRSMs in complex operational conditions reveals a landscape rife with challenges and opportunities for further research. This comprehensive review endeavors to dissect the multifaceted aspects of PRSMs, focusing on their mechanics and dynamics, tribology and thermal behavior, and the paramount importance of reliability and condition monitoring. By synthesizing current research findings, this paper highlights the significant advancements in understanding the static and dynamic characteristics of PRSMs, the intricate interplay between lubrication conditions and wear mechanisms, and the critical role of thermal effects on operational performance. Moreover, it delves into the dynamic models that address the impact of manufacturing imperfections, such as waviness and defects, on the reliability of these mechanisms. Despite the strides made, the review identifies critical gaps in the existing literature, particularly under conditions of extreme temperatures, large deformations, and multifaceted loads, advocating for a holistic approach to research. By proposing integrated thermo-mechanical models and emphasizing the need for empirical validations, this paper outlines a roadmap for future studies aimed at facilitating the development of more robust and reliable PRSMs, capable of meeting the demands of complex operational scenarios and advancing the field of high-precision applications in aerospace, robotics, and beyond.

Quantitative analysis of human gait is critical for early discovery, progressive tracking, and rehabilitation of neurological and musculoskeletal disorders, such as Parkinson’s Disease, stroke, and Cerebral Palsy. Gait analysis typically involves estimating gait characteristics, such as spatio-temporal gait parameters and gait health indicators (e.g., step time, length, symmetry, and balance). Traditional methods of gait analysis involve the use of cameras, wearables, and force plates, but are limited in operational requirements when applied in daily life - such as direct line-of-sight, carrying devices, and dense deployment. This paper introduces a novel approach for gait analysis by passively sensing footstep-induced floor vibrations during walking using vibration sensors mounted on the floor surface. Our approach is non-intrusive, scalable, and perceived as more privacy-friendly, making it suitable for continuous gait health monitoring in daily life. We developed a floor vibration-based gait analysis framework to estimate various gait parameters that are used as standard metrics in medical practices, including temporal parameters (step, stride, stance, swing, double-support, single-support time) and spatial parameters (step length, width, angle, stride length), and extracts gait health indicators (cadence/walking speed, left-right symmetry, gait balance, initial contact types). The main challenge is that floor vibrations are distinct across different floor types. To address this challenge, our approach develops floor-adaptive algorithms to extract floor-specific features and is designed to be generalizable to various settings, including homes, hospitals, and eldercare facilities. We evaluate our approach through real-world walking experiments with 20 adults with 12,231 labeled gait cycles across concrete and wooden floors. Our results show 90.5% (RMSE 0.08s), 71.3% (RMSE 0.38m), and 92.3% (RMSPE 7.7%) accuracy in estimating temporal, spatial parameters, and gait health indicators, respectively.

The beneficial effects of Lanthanide incorporation into 0.94Na0.5Bi0.5TiO3-0.06BaTiO3 (BNT-BT) matrix on its functional properties were investigated. The conventional solid-state method was used for synthesizing samples. The structural refinement revealed that all samples crystallized in R3c rhombohedral symmetry. Raman spectroscopy study was carried out using green laser excitation and revealed that no clear perceptible variation in frequency is observed. Dielectric measurements unveiled that the introduction of rare earth obstructed the depolarization temperature promoted in BNT-BT with decreasing the diffusive phase transition with increasing the lanthanide size. Only Dysprosium addition showed comparable diffusion constant and dielectric behavior as the unmodified composition. Further, the comparison of the obtained ferroelectric hysteresis and strain-electric field loops revealed that only Dy-phase exhibited interesting properties comparing parent composition. In addition, the incorporation of lanthanides Ln3+ into the BNT-BT matrix led to the development of luminescence characteristics in the visible and near infrared regions, depending on the excitation wavelengths. The simultaneous occurrence of photoluminescence and ferroelectric/piezoelectric properties opens up possibilities for BNT-BT-Ln to exhibit multifunctionality in a wide range of applications.Keywords: Sodium Bismuth Titanate; structural refinement; dielectric properties; ferroelectric properties; piezoelectric properties; Photoluminescence.

Reactions of Co(OAc)24H2O, N‚N'-bis(3-pyridylmethyl)oxalamide (L) and 4,4’-sulfonyldibenzoic acid (H2SDA) afforded four coordination polymers with the same mixed ligands, {[Co(L)(SDA)(H2O)2]·H2O·CH3OH}n, 1, {[Co(L)0.5(SDA)]·2H2O·0.5L}n, 2, {[Co(L)1.5(SDA)(H2O)]·H2O}n, 3, and {[Co2(L)1.5(SDA)2(H2O)2]·4H2O}n, 4, which have been structurally characterized by using single crystal X-ray crystallography. Complexes 1 – 4 are 2D layers, revealing the topologies of sql, 2,6L1, (4,4)Ia and 6L12, respectively, and demonstrating that the metal to ligand ratio, solvent system and reaction temperature are important in determining the structural diversity. Immersion of these complexes into various solvents show that the structural types govern the chemical stabilities of 1 – 4. Reversible structural transformation can be shown for complexes 1 and 2 upon solvent removal and adsorption, while those of 3 and 4 are irreversible.

This research work has been based on a previous study by the authors that characterized the behavior of a polyimide-coated FBG sensor in a structural monitoring system. Sensors applied to structural health monitoring are affected in the presence of a state of multidirectional strains simultaneously. The previous study observed the influence of transverse strain (ε_y) while keeping longitudinal strain constant (ε_x), where the direction x is the direction of the optical fiber. The present study developed an experimental methodology which has consisted of carrying out a campaign of biaxial tests on cruciform specimens with three embedded FBG sensors coated with polyimide, acrylate and ORMOCER®. Applying the Strain–Optic Theory as reference, a comparison of the results obtained with the different coatings has been studied. This experimental work has done it possible to study the influence of transverse strain (ε_y) in the longitudinal measurement of each of the FBG sensor and the influence of the coating material. Finally, the calibration procedure as well as the strain sensitivity factor K for each sensor has been defined.

The study aimed to know the direct effect of strategic leadership on the quality of service represented by wireless communications services, in addition to knowing the indirect effect of strategic leadership on the quality of service when using performance as an intermediary variable. This research was conducted in government institutions in the Republic of Yemen. Represented by the offices of the Ministry of Communications and Information Technology in five Yemeni cities, it targeted senior management employees, boards of directors, and middle management concerned with strategic planning and strategic leadership. To measure and evaluate the factors of strategic leadership and service quality in Offices of the Yemeni Ministry of Communications Ministry of Communications and Information Technology of the Republic of Yemen. Moreover, performance. A questionnaire was formulated and distributed to the study sample, and data was collected through questionnaires for 150 individuals in some offices of the Yemeni Ministry of Communications. This study uses structural equation model analysis from the Partial Least Squares program through the Smart Plus 4 programs. The study reached a set of results, including that all models show a direct, positive and significant effect of strategic leadership on the quality of service represented by the quality of services in the offices of the Ministry of Communications. As well as the positive relationship between them, as well as the direct and positive impact of performance on the quality of service, as well as the positive and significant relationship between them. While the results indicated a positive and significant indirect effect of strategic leadership on service quality, there is also a positive and significant indirect relationship between strategic leadership on service quality when using performance as an intermediary variable.

From a structural point of view, understanding interfacial electrostatic features of ligand-receptor complexes is crucial for biophysics-based design of therapeutics with improved efficacy and safety. Here, with a high-throughput structural feature extraction approach, this article reports a set of electrostatic structural features from glucagon-like peptide-1 (GLP-1) and GLP-1 receptor (GLP-1R) complex structures determined using experimental tools. Leveraging a set of computational structural biophysical analyses, this article systematically characterized the electrostatic interactions within the GLP-1-GLP-1R complexes with two sets of criteria to identify interfacial salt bridges and hydrogen bonds. Overall, the results here reveal intricate details of electrostatic interactions critical for GLP-1 binding to its receptor GLP-1R, providing biophysical insights into the stabilization of the GLP-1-GLP-1R complex structure and the molecular basis of GLP-1/GLP-1R signaling. Furthermore, the electrostatic structural features extracted from GLP-1 and GLP-1R complex structures are useful in the development of a machine learning-based ligand-receptor binding affinity calculating model, i.e., a GLP-1-GLP-1R-specific general intermolecular binding affinity calculator (GIBAC), paving the way for accelerated discovery and structure-based design of drug candidates targeting the GLP-1/GLP-1R system with improved efficacy and safety.

Structural variations (SVs) play a key role in the pathogenicity of hematological malignancies. Optical genome mapping (OGM) is an emerging technology that enables genome-wide detection of all classes of SVs at a high resolution and sensitivity. Identification of cryptic SVs leading to gene disruption or predicted novel gene fusions could be important drivers for cancer development and/or portend a prognostic relevance, which could be used to modify the treatment plan. A cohort of 106 consented cases that had a successful OGM analysis performed were included in the study. Demographic, clinical, laboratory and treatment data were collected. Routine diagnostic and prognostic testing were done on the peripheral blood and bone marrow aspirate as indicated. Additional samples of peripheral blood and/or bone marrow were sent for OGM testing. OGM led to a change in risk stratification in 17/66 (25.75%) of patients with hematological malignancies, the majority of these patients (15/66, 22.72%), having their risk stratification upgraded with a resulting change in treatment of 14 patients. This study highlights the ability of OGM to detect rare, cryptic and clinically relevant variants that potentially impact disease diagnosis, risk stratification and actionable treatment targets.

The early detection of small cracks in large structures is a crucial requirement for the implementation of structural health monitoring (SHM) system with a low transducer density. This work presents the results of the analysis of scattering of a submillimeter notch type defect with semielliptical shape with a groove at constant width 100µm in a 4.1mm thick aluminum plate. The defect is investigated with an ultrasonic guided wave (UGW) A0 mode at 550 kHz to cover long range in a thick plate. The mode selection is obtained by interdigital transducers designed to operate with 5mm central wavelength. The novel contribution is the assessment of the scattering amplitudes at different orientations of the defect when the distance is large as 35 cm in pulse-echo mode or 70 cm in pitch-catch mode. The system model is based on Finite Element Model (FEM) simulations and the results are in good agreement with experimental tests. The detection of the defect is obtained by comparing the scattered signals from the defect with base line signals of the pristine laminate. The analysis of scattering features and the efficient excitation with a probing UGW show the potential implementation in real structural health monitoring (SHM) systems.

In recent years, there has been an increasing interest in adopting novel sensing technologies for the continuous monitoring of structural systems. In this respect, Micro-Electro-Mechanical System (MEMS) sensors are widely used in several applications, including Structural Health Monitoring (SHM). Thanks to their significantly lower cost, ease of installation on the structure, and lower power consumption, they enable extensive, pervasive, and battery-less monitoring systems. This paper presents an innovative high-performance device for SHM applications, based on a low-noise triaxial MEMS accelerometer, providing a guideline and insightful results about the opportunities and capabilities of these devices. Sensor nodes have been designed, developed, and calibrated to meet structural vibration monitoring and modal identification requirements. These components include a protocol for reliable command dissemination through the network and data collection, and improvements to software components for data pipelining, jitter control, and high-frequency sampling. Devices were tested in the lab using shaker excitation. Results demonstrate that MEMS-based accelerometers are a feasible solution to replace expensive piezo-based accelerometers. Deploying MEMS is promising to minimize sensor node energy consumption. Time and frequency domain analysis show that MEMS can correctly detect modal frequencies, useful parameters for damage detection. The acquired data from the test bed were used to examine the functioning of the network, data transmission, and data quality. The proposed architecture has been successfully deployed in a real case study to monitor the structural health of the Marcus Aurelius Exedra Hall within the Capitoline Museum of Rome. The performance robustness was demonstrated and the results showed that the wired sensor network provides dense and accurate vibration data for structural continuous monitoring.

. Interconnected control systems (ICS) widely apply to various technical systems. ICS has a complex description. Therefore, simplified models use, which the specifics of an object do not always reflect. So, the problem of synthesizing mathematical models is topical. The work purpose is to develop an approach to obtaining models in conditions of incomplete a priori information. We use an adaptive approach. As examples, two-channel systems (TCS) with cross-links and identical channels consider, and a method for mathematical model design. We consider the system with asymmetric cross-links and evaluate their impact on properties of an adaptive identification system. Approach proposed to assessing the TCS identifiability with cross-links. The excitation constancy influence on TСS parameter estimates is studied. A generalization of the proposed approach is given for an interconnected system.

The space shuttle, a revolutionary spacecraft that has played a significant role in human space exploration, was composed of various advanced materials that were carefully selected to meet the extreme demands of spaceflight. This review paper provides a comprehensive examination of the materials historically employed in the construction of space shuttles and explores the latest trends shaping the field. The evolution of space shuttle materials is traced from the inception of the space program to contemporary missions, highlighting key milestones, challenges, and breakthroughs. Emphasis is placed on the critical role that materials play in the overall performance, safety, and sustainability of space shuttles. The paper begins by elucidating the diverse requirements that materials must fulfill in the harsh and complex environment of space, encompassing extreme temperatures, radiation exposure, and mechanical stresses. A detailed analysis of the materials utilized in the fabrication of various shuttle components, such as thermal protection systems, structural elements, and propulsion systems, is presented. Special attention is given to the challenges posed by re-entry and the strategies employed to mitigate heat-related issues. Furthermore, the review explores recent innovations and emerging materials that are reshaping the landscape of space shuttle design. Advancements in nanotechnology, composite materials, and additive manufacturing are discussed in the context of their potential applications for enhancing shuttle performance and reducing mission costs. The paper also addresses the importance of sustainability in space exploration, exploring materials with lower environmental impact and improved recyclability. The review concludes with a forward-looking perspective on the future of materials, considering ongoing research, development, and the potential incorporation of cutting-edge technologies. Insights are provided into how the evolving landscape of materials science may influence the design and manufacturing processes of the next generation of space vehicles. This paper provides an overview of the materials used in the construction of the space shuttle, including their properties, applications, and challenges. The materials used in the space shuttle are critical in ensuring the safety, performance, and longevity of the spacecraft, and understanding their characteristics and performance in space is crucial for the advancement of aerospace engineering.

The mass of a direct-drive generator is often defined by the requirements for structural stiffness to meet the magnetic stiffness between the rotor and stator surfaces. This paper analyses this magnetic stiffness and estimates the structural stiffness of direct-drive generators for different modes of deflection. The magnetic stiffness modelling is based on an analytical model of the airgap closing forces. The final models are verified using Finite Element analysis and carried out for both permanent magnet and wound rotor generators. It shows that wound rotor machines have higher stiffness requirements than permanent magnet machines. The structural stiffness of the generator rotor and stator are evaluated for different modes by applying spatially-varying forces and finding the associated deflections. Structural stiffnesses for the rotor, stator and bearing are then combined. Finally, the magnetic and structural stiffnesses are combined and a stiffness margin can be found. For the airgap not to close, this combined stiffness must be greater than 0. This method is applied to a relatively stiff and a relatively compliant set of generator structures in a case study in order to find the optimum and more sustainable configuration.

It is commonly recognized that a ship’s ability to maintain stability is dependent upon the way its loads are distributed. This means making sure the center of gravity is sufficiently low and evenly distributed. Yet when a ship encounters turbulent water with extremely large wave amplitudes, load distribution is a critical factor in determining how stressed the ship becomes. In particular, this article examines several methods for increasing the ship's longitudinal strength to prevent ship structural damage during hogging and sagging. This research presents a number of proposed techniques to enhance the longitudinal strength of cargo ships in order to guarantee minimal stress and deformation during sagging and hogging. The first method is the stern-to-bow use of curved support structures to increase the longitudinal strength of a cargo ship. And another way to stiffen the lateral plate is the proposed use of different designs of the side plate, such as wavy curves, stars, etc. To further boost the strength, the lateral plate upper part is suggested to curve upward. A numerical simulation using ANSYS of the stiffened plate when subjected to uniform load distribution and fixed support on either end shows that there is a decrease in deformation of the plate when we use wavy curved plates compared with those of the other plate stiffening methods used, and furthermore, curving the plate on top increases its strength during sagging as well as hogging. Finally, the use of a curved support structure further enhanced the overall longitudinal strength of the vessel.

The normal ageing process significantly affects resistance arteries, leading to various biological and physiological consequences. Systolic hypertension is a common occurrence in ageing individuals, accompanied by increased large artery stiffening, heightened pulsatility, small artery remodeling, and damage to critical microvascular structures. Starting from young adulthood, there is a progressive elevation in mean arterial pressure, supported by clinical and epidemiological evidence as well as findings from animal models. The myogenic response, a protective mechanism for the microcirculation, may face disruptions during ageing. Dysregulation of calcium entry channels (T-type, L-type, TRP channels), dysfunction in intracellular calcium storage and extrusion mechanisms, altered expression of potassium channels, and a change in smooth muscle calcium sensitization may contribute to age-related dysregulation of myogenic tone. Flow-mediated vasodilatation, a hallmark of endothelial function, is compromised in ageing. This result of endothelial dysfunction is related to oxidative stress, lower nitric oxide bioavailability and a low-grade inflammatory response, further exacerbating vascular dysfunction. Resistance artery remodeling in ageing emerges as a hypertrophic response of the vessel wall, often seen in conjunction with outward remodeling (in normotension), but can also present as inward hypertrophic remodeling (in hypertension). The remodeling process involves oxidative stress, inflammation, reorganization of extracellular matrix fiber proteins and actin cytoskeletal components. Reactive oxygen species (ROS) signaling and chronic low-grade inflammation, often referred to as "inflammaging”, play substantial roles in age-related vascular dysfunction. Due to its role in regulation of vascular tone as well as structural proteins, the RhoA/Rho-kinase pathway becomes a new target in age-related vascular dysfunction and associated diseases. Understanding the intricate interplay of these factors is crucial for developing targeted interventions to mitigate the consequences of ageing on resistance arteries and enhance overall vascular health.

: AliCPT-1 is the first Cosmic Microwave Background (CMB) experiment in China, dedicated to achieve accurate measurements of B-mode polarization. Situated in Ali of Tibet, China, this telescope is currently undergoing deployment and will operate in two frequency bands centered at 90 and 150 GHz. The Far-Field Flat Mirror（FFF）is a calibration device of AliCPT-1 telescope for far-field beam mapping. The design of FFF is optimized for easy assembly and adjustment. Meteorological station data reveals that the maximum wind speed near FFF is 17.5 m/s, while the maximum wind speed on the windward side is 8 m/s. The wind pressure on FFF was analysed using a maximum wind speed of 17.5m/s as the input condition, based on the fluid-structure coupling method in ANSYS. The results demonstrate that it is safe and reliable when withstanding combined gravity and wind pressure loads. The torque on the mount is within the motor rated torque. The flatness of the FFF reflective surface can be adjusted to an RMS value of 0.05 mm when taken into account the effect of gravity and assembly accuracy. The deformation caused by the maximum wind loads is approximately 0.0587 mm under the protection of wind-proof wall. The combined deformation is 0.077 mm in RMS value combining the two influences, which is less than 1/20 of wavelength. The FFF mirror assembly is stable and precisely for telescope calibration.

The aim of the study is to explore how sharing status updated and receiving Likes on Facebook, as a form of positive social feedback, correlates with current and perceived changes in Quality of Life (QoL) Sample consisted of 1577 adult Facebook users (76.3% females; 65.9% aged 18-24, 21.9% aged 25-30, 12.3% aged > 30 years old). The study employed a longitudinal approach, collecting Facebook data from adult users over a 12-month period using the Graph API. Data were divided into 12 monthly segments. Two monthly indicators were calculated: the percentage of textual status updates and the average number of Likes per post. Current and perceived changes in Quality of Life (QoL) were administered as self-report measures. The findings indicated a positive correlation between the frequency of textual Facebook posts and the average received Likes. Furthermore, receivign more Likes was positively associated with a higher current QoL, and perceived improvements in QoL correlated with an increase in Likes over time. The study suggests that online positive social feedback, measured through Likes on Facebook, is associated with both current QoL and perceived improvements in QoL among adult Facebook users. This highlights the potential impact of online social interactions on individual well-being.

The goal of this article is to provide a review of the experimental techniques and procedures using vibration methods for the Structural Health Monitoring (SHM) of Polymer-Matrix Composites (PMC). It aims to be a guide for any researchers to carry out vibration experiments. The linear methods are first introduced. But as PMC is a complex material, these classic methods showed some limits, such as low accuracy for small damages, and a high environmental dependency. This is why the nonlinear methods are secondly studied, considering that the complexity of PMC induces a nonlinear behavior of the structure after damage occurrence. The different damage mechanisms are well explained in order to evaluate the potential of each vibration method to detect them.

Chromosome analysis (CA) and chromosomal microarray analysis (CMA) have been successfully used to diagnose genetic disorders. However, many conditions remain undiagnosed due to limitations in resolution (CA) and detection of only unbalanced events (CMA). Optical genome mapping (OGM) has the potential to address these limitations by capturing both structural variants (SVs) resulting in copy number changes and balanced rearrangements with high resolution. In this study, we investigated OGM’s concordance using 87 SVs previously identified by CA, CMA, or Southern blot. Overall, OGM was 98% concordant with only three discordant cases: (1) uncalled translocation with one breakpoint in a centromere; (2) uncalled duplication with breakpoints in the pseudoautosomal region 1; and (3) uncalled mosaic triplication originating from a marker chromosome. OGM provided diagnosis for three previously unsolved cases: (1) disruption of the SON gene due to a balanced reciprocal translocation; (2) disruption of NBEA gene due to an inverted insertion; (3) disruption of the TSC2 gene due to a mosaic deletion. We show that OGM is a valid method for detection of many types of SVs in a single assay and is highly concordant with legacy cytogenomic methods; however, it has limited SV detection capabilities in centromeric and pseudoautosomal regions.

Structural health monitoring (SHM) is critical for ensuring the safety of infrastructures like bridges. This article presents a digital twin solution for SHM of railway bridges using low-cost wireless accelerometers and Machine Learning (ML). The system architecture combines edge on-premises computing and cloud analytics to enable efficient real-time monitoring and complete storage of relevant time-history datasets. After train crossings, accelerometers stream raw vibration data, which is processed in the frequency domain and analyzed via machine learning to detect anomalies indicating potential structural issues. The digital twin approach is demonstrated on an in-service railway bridge, where vibration data was collected over two years under normal operating conditions. By learning allowable ranges for vibration patterns, the digital twin model identifies abnormal spectral peaks, suggesting changes in structural integrity. The long-term pilot proves that this affordable SHM system can provide automated and real-time warning of bridge damage and also supports the use of in-house designed sensors of lower-cost and edge computing capabilities than those used in the demonstration. The successful on-premises-cloud hybrid implementation provides a cost effective and scalable model for expanding monitoring to thousands of railway bridges, democratizing SHM to improve safety by avoiding catastrophic failures.

Аннотация . Периодически развиваются самоподобные движения структурно-вещественных комплексов (СМК) из состава Солнечной системы в течение периода около 4,5 миллиардов лет земной коры, развития Земли в условиях самоорганизации. Синхронные или близкие во времени ряды генетических или парагенетических групп магматических, рудно-минеральных, метасоматических, осадочных образований, их структур и других сопутствующих им процессов, включают в себя каждый комплекс (ГМК). Каждый комплекс в его пределах ограничен во времени и пространстве, по причине признаков самопроизвольного динамического процесса; распространяется на территорию Земли в текущий исторический период; формирует состав и структуру земной коры на этом этапе, определяя ее полициклическое развитие. Количество циклов около 14,

Plantation-based farmer cooperatives play an important role in promoting agricultural modernization and increasing farmer income, and the management of business risks of such cooperatives not only influences the development of the cooperatives themselves, but also concerns the interests of farmers. Based on the survey data of 226 sample cooperatives from Guizhou province, this article uses factor analysis to measure business risks of plantation-based farmer cooperatives and carries out empirical tests on influence factors of business risks through structural equation model. According to the research results, the ordering of business risks of plantation-based farmer cooperative based on their significance is as follows: market risk > policy risk > natural risk > technical risk > management risk. Influence factors including policy environment, economic environment, social service environment, technical environment, resource endowment of the cooperative and manager characteristics have significant positive influence on the cooperative, with economic environment and manager characteristics generating relatively stronger influence and social service environment generating relatively weaker influence. Through this research, several policy implications on driving high-quality development of plantation-based farmer cooperative are made, including specifying supportive policies of plantation-based farmer cooperative, improving economic environment of agricultural market, upgrading agricultural infrastructure, depending reform of land transfer system, and enhancing internal management of the cooperative.

In this work, we report a series of undoped and 1% Ga or Y doped lanthanum manganite compounds which have been synthesized via sol-gel technique. The obtained materials were characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM/EDX). The XRD results confirmed a good crystallinity for all the studied samples and a change in the crystal structure of Ga or Y doped lanthanum manganite (Pm-3m space group) is observed compared to pristine sample (R-3c space group). Thermal analysis highlighted a different behavior of the doped samples compared to the undoped sample observed by the different mass loss in the analyzed temperature range. For these materials, it is shown for the first time that the static electrical conductivity, σDC of Ga or Y doped LaMnO3 compounds increases compared to the σDC pristine sample, and the thermal activation energy of the conduction EA,cond increases linearly with the temperature, for all three studied sample.

The paper presents an implementation and numerical study of the nonlinear optimal-based vibration control solutions for the full-scale TLP – NREL 5MW wind turbine tower-nacelle model with an MR-damper-based 10 ton tuned vibration absorber (TVA) located at the nacelle, under excessive wave/wind polyperiodic excitations yielding continual transient vibration states. The MR damper operates simultaneously with an electromagnetic force actuator (forming a hybrid TVA), or independently (a semiactive TVA). The study includes both actuators’ nonlinearities and dynamics, whereby the former are embedded in the Hamilton-principle-based nonlinear control solutions. As a reference, the structure model with a passive TVA, with a modified ground-hook control law, and without any vibration reduction solutions is used. The TVA was tuned either to the NREL 5MW tower-nacelle 1st bending mode frequency (TVA-TN) or to the TLP surge frequency (TVA-TLP). The optimal control task, redeveloped here with regard to the TVA stroke amplitude minimisation, including the implementation of the protected structure’s acceleration (control case III / III-H) and relative displacement terms as well as nonzero velocity term in the quality index, is stated and solved, yielding optimal-based control propositions for both the MR damper current and the actuator force. On the basis of the obtained results, the TVA-TN solution is by far superior to the TVA-TLP one regarding the tower deflection amplitude / root-mean-square (RMS) and TVA stroke amplitude values. All the regarded TVA-TN solutions provide tower deflection safety factor of ca. 2, while a structure without any vibration reduction solutions or with a TVA tuned to the TLP surge frequency (especially passive and hybrid TVA-TLPs) are at risk of tower structural failure. The obtained TVA stroke amplitudes are reduced with regard to the previously developed approaches. Moreover, these reductions are obtained due to the sole control algorithm enhancement; thus, no additional resources are necessary, while this attainment is accompanied with a reduction in the MR damper force that is necessary for the TVA operation. The protected structure’s acceleration term utilisation produce the TVA stroke amplitude reduction more efficiently than the TVA relative displacement term usage, as in the previously developed approach (the latter being ineffective for the semiactive TVA implementation) which, in turn, efficiently reduces TVA stroke RMS values and the required mean actuator power for the hybrid TVA implementation. Concerning the limited TVA stroke, the most favourable vibration control solutions are the newly introduced semiactive control case III, providing favourable cumulative primary structure deflection indexes at the lowest obtained TVA travel distance, and possibly the hybrid control case III-H, providing even more favourable primary structure deflection qualities and reduced nacelle acceleration levels thanks to the utilisation of the force actuator of the relatively low power (ca. 6 kW); however, side effect of the latter is the increased TVA stroke amplitude as for all hybrid solutions tested (comparing to semiactive solutions). The analysed passive TVA systems along with the modified ground-hook hybrid TVA solution, utilising the assumed absorber mass, can hardly be implemented in the nacelle, especially along the demanding side-side direction, without enforcing end-stop collision bumpers, which result in the efficiency deterioration. The ground-hook control, well proven for the primary structure steady-state deflection minimisation, yielded unsatisfactory results, comparing to the newly implemented solutions. The results of the current study may be used during the design of the full-scale vibration reduction system for the real-world NREL 5MW-class floating, TLP-based, wind turbine structure.

The Sei Dareh Bridge is a cable-stayed bridge located in West Sumatra Province, Indonesia. The bridge, which crosses the Batanghari River, has a main span of 123 meters long and 9 meters wide. Traffic load is transmitted through 24 prestressed cables to a 42.4-meter-high pylon made of concrete. The bridge deck and traffic loads are directly supported by steel box girders as main beams that are reinforced laterally with cross beams IWF 800.300.16.24 and stringers IWF 350.350.12.19. This paper discusses static and dynamic testing on the bridge which aims to assess its feasibility before it is opened to the public. Based on the test, it was concluded that a static load of 73% could not be achieved because the deflection that occurred was beyond the allowable deflection. This is exacerbated by a loud clanging sound on the ST2-X1 prestressed cable when loading to 240 tons or 58% of the targeted load. In addition, this bridge is included in the "lazy bridge" category because it takes 24 hours to return to an undeformed condition after loading. As a recommendation for this bridge, it is necessary to carry out a structural health monitoring system (SHMS) regularly on bridge slabs and cables.

Interior permanent magnet motors (IPMSMs) are extensively used as traction motors today because of their exceptional torque and power density, and wide constant power operating range. Under real-world usage, an IPMSM rotor undergoes varying electromagnetic, thermal, and mechanical loads. Under such conditions, fatigue life-based design criteria should be utilized over stress-based design criteria to ensure the structural integrity of the rotor. Moreover, the driving dynamics can change the rotor temperature continuously, which affects the electromagnetic, mechanical, and fatigue properties of rotor material. This paper proposes a robust thermo-mechanical rotor fatigue simulation workflow considering the significant loads acting on an IPMSM rotor and the temperature variation throughout a drive cycle. It discusses an accelerated fatigue life estimation approach based on peak valley extraction to reduce the simulation time significantly for stress and fatigue analysis. Then, it presents a method for stress-life curve generation for a variable loading. It also presents a sensitivity study with a median S-N curve, and a 90%-reliability 95%-confidence (R90C95) S-N curve.

Diabetic kidney disease (DKD) is a major cause of morbidity and mortality of type 2 diabetes mellitus (T2DM). Aim of this study was to investigate whether albumin structural alterations correlate with DKD severity and evaluate whether native and reduced albumin concentrations could complement the diagnosis of DKD. To this aim, one hundred and seventeen T2DM patients without (n=42) and with (n=75) DKD (DKD I-III upon KDIGO classification) were evaluated; total albumin concentration (tHA) was quantified by bromocresol green assay, while structural alterations were profiled assessed by liquid chromatography-high resolution mass spectrometry (LC-HRMS). The concentrations of albumin in native (eHA, effective albumin) and reduced (rHA) forms were then assessed. HRMS analyses showed a reduced relative amount of native albumin in DKD patients along with an increased abundance of altered forms, especially those bearing oxidative modifications. Accordingly, both eHA and rHA values varied along the stages of progressive renal failure, and alterations dose-dependently correlated with renal dysfunction. ROC curves analysis showed a significantly higher sensitivity and specificity of eHA and rHA with respect to tHA for the diagnosis of DKD. Importantly, at multivariable logistic regression analysis, eHA was identified as independent predictor of DKD.

In this work, the degassing process of corn seeds was experimentally and numerically analyzed by removing air or other gases from around the seeds, specifically from the seed coating, in a rough vacuum chamber. The two complementary variants are employed to understand and optimize this process to improve the quality and germination rate of the seeds. Several experiments were conducted with well-established durations and masses of corn seeds at different temperatures to observe and record the behavior of the system, facilitating the modeling of the degasification process in the vacuum compartment. Modeling the degasification operation in the vacuum chamber allowed for determining the pressure profiles on the vacuum chamber and its lid. Numerical simulations were either conducted using a simulation program developed in the Visual Basic Applications (VBA) language for Microsoft Excel to model the degassing process in the vacuum chamber, or with the assistance of specialized software (transient structural analysis and simulation program in the ANSYS Workbench environment). Statistical analysis of the correlation between experimental and estimated pressure values revealed that both the proposed mathematical model and the solution method are well-chosen, with differences expressed through the absolute error (EA) being very small. Structural dynamic analysis carried through the Finite Element Method (FEM) highlights that the chosen materials for manufacturing the vacuum chamber vessel (316 stainless steel) or the chamber lid (transparent acrylic plastic) are durable and capable of withstanding the desired pressure and temperature demands in the seed treatment process. Additionally, through structural dynamic analysis, it was possible to study the deformation of system components, providing a detailed perspective on their structural distribution.

A temporary monitoring system was installed on the 175-years-old historical Széchenyi chain bridge under its reconstruction process. The bridge is in the downtown area of the capital city of Hungary and plays a significant role in city life of Budapest. Six-month-long measurements were conducted during the reconstruction process of the bridge, yielding crucial insights into the structural behaviour of the historical structure. Measurement results were evaluated; the findings encompass the rotation capacity of pins between chain elements, and structural response to temperature changes. This information helped the decision-making of designers and construction company during the reconstruction made between 2021 and 2023. For instance, daily temperature fluctuations result in increased bending moments in the chain elements, rising up to 158% compared to the values observed during a proof load test in 2018. Furthermore, the measurements reveal an approximate 42% increase in normal forces compared to the proof load test, which highlights the high sensitivity of chain bridges to temperature fluctuations, where geometric stiffness plays a crucial role. Reconstruction, reducing self-weight, notably intensifies the impact on normal forces and bending moments. These outcomes strongly emphasize the dominance of dead load and self-weight in the case of chain bridges.

We evaluate performance of Isogeometric analysis (IGA) for structural deformation and automobile crash. In automobile crash analysis, ensuring the accuracy of the acceleration, velocity and load in time series as well as the deformation behavior is important. To maintain the aforementioned consistency, accurately reproducing the bending and buckling of structural members is indispensable. In this study, we firstly compute the bending and buckling of structural members using IGA and validate its performance by comparing the results with conventional finite element analysis and experiments. In addition, we utilize IGA for the crash analysis of an automobile body.

The Gulf of Suez is a sedimentary rift-basin with thick evaporites and complex structural settings that presents challenges to achieving quality imaging based on seismic reflection data. Such subsurface settings and the lack of 3D seismic data poses challenges in building reservoir models to guide hydrocarbon exploration and development, especially in southern parts the Gulf of Suez. This study attempts to overcome the challenges of both 2D seismic interpretation and building a static reservoir model of two Miocene reservoir formations, Ras Ghara Field, Southern Gulf of Suez. Integration of well log data analysis of nine wells and regional-tectonics cognizant 2D seismic interpretation of nineteen 2D seismic lines enabled a reliable 3D static reservoir model. The Miocene reservoir characterization reveals heterogeneity in lithofacies distribution, with thick evaporite sequences causing seismic reflection distortions. Significant hydrocarbon accumulations are associated with horst fault blocks. The Miocene reservoirs demonstrate effective porosity of 14-33%, water saturation of 16-65%, and hydrocarbon saturation of 35-84%. Two new prospects are identified based on structure, facies distribution, and petrophysical results, with estimated original oil in place (OOIP) of 2,002,404 stock tank barrels (STB) and 1,175,580 STB for the Kareem Formation, and 6,302,916 STB and 2,841,894 STB for the Rudeis Formation.

Understanding and predicting damage progression within thin plain-woven CFRP components is an essential issue for scheduling maintenance intervals and structural inspections, and typically require extensive test series. However, uncertainties always remain and result in conservative design and unnecessary downtimes due to the repeated inspections of a healthy structure. SHM can be used to reduce these uncertainties, as it allows to evaluate the condition of a mechanical structure during operation. Numerous SHM methods are developed , that achieve different levels of damage identification but are often investigated at small coupons with non-realistic structural damages and loading conditions on both, structure and sensor. The present research investigates the electrical impedance tomography (EIT) featuring an elastoresistive thin-film sensor to evaluate damage that propagates from a circular hole in a large plate under cyclic tensile-tensile multi-block loading. Applied fatigue loads were increased multiple times up to a total number of two million cycles. During the loading damage initiated at the hole and continuously propagated into the plate. Repeated EIT evaluations of the applied sensor and validating evaluations by means of digital image correlation clearly revealed the robustness of the hardware and the potential of the SHM method for damage evaluation of plain-woven CFRP components.

The R23Cu7Mg4 (R = Ca, Eu) intermetallics, studied by single crystal X-ray diffraction, were found to be isostructural with the Yb23Cu7Mg4 prototype (hP68, k4h2fca, space group P63/mmc), forming a small group inside the bigger 23:7:4 family, otherwise adopting the hP68-Pr23Ir7Mg4 crystal structure. The observed structural peculiarity is connected with the divalent character of the R component and with a noticeable volume contraction, resulting in a clear clustering of title compounds inside the whole 23:7:4 family. The occurrence of fragments typical of similar compounds, particularly Cu-centered trigonal prisms and Mg-centered core-shell polyicosahedral clusters with R at vertices, induced the search of significant structural relationships. In this work, a description of the hexagonal crystal structure of the studied compounds is proposed as a linear intergrowth along the c-direction of the two types of slabs R10CuMg3 (parent type: hP28-kh2ca, SG 194) and R13Cu6Mg (parent type: hR60-b6a2, SG 160). The ratio of these slabs in the studied structure is 2:2 per unit cell, corresponding to the simple equation 2XR10CuMg3 + 2XR13Cu6Mg = 2XR23Cu7Mg4. This description assimilates the studied compounds to the (Ca,Eu,Yb)4CuMg ones, where the same slabs (of p3m1 layer symmetry) are stacked in a different way/ratio, and constitutes a further step towards a structural generalization of R-rich ternary intermetallics.

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.

Five new cembrane-type diterpenes, lobocalines A–E (1–5), and four new steroids, lobocalines F–I (9–12), along with six known related compounds (6–8 and 13–15) were isolated from the Yalong Bay soft coral Lobophytum catalai. The structures of the new compounds were elucidated by extensive spectroscopic analysis, NMR calculation with DP4+ analysis, time-dependent density functional theory-electronic circular dichroism (TDDFT-ECD) calculations, X-ray diffraction analyses, and the comparison with the reported spectroscopic data of known compounds. Further, with the aid of X-ray diffraction analysis, the structure of lobocrasol B (15) was firmly revised as 15a. In in vitro bioassays, compound 2 showed moderate antibacterial activities against fish pathogenic bacteria Streptococcus parauberis KSP28 and Phoyobacterium damselae FP2244 with minimum inhibitory concentration (MIC) values of 8.7 and 17.3 µg/mL, respectively. All the steroids exhibited antibacterial activities against the S. parauberis KSP28 with MIC values ranging from 12.3 to 53.6 µg/mL. Compounds 2, 7 and 14 have remarkable inhibitory effects on the hemolysin production of Staphylococcus aureus, while compounds 8–12 have medium inhibitory effects on the pyocyanin production in Pseudomonas aeruginosa.

Ultra-low radioactive titanium alloy is a promising material for the manufacture of low-background detectors, which are being developed for experiments in astroparticle physics and neutrino astrophysics. Structural titanium is manufactured on an industrial scale from titanium-sponge. The ultra-low-background titanium-sponge can be produced on an industrial scale with a contamination level of less than 1 mBq/kg of uranium and thorium isotopes. The pathways of contaminants during the industrial production of structural titanium have been analyzed. The measurements have been carried out using two methods: inductively coupled plasma spectroscopy (ICP-MS) and gamma-spectroscopy using high-purity germanium detectors (HPGe). It has been shown that the level of contamination with radioactive impurities does not increase during remelting of titanium-sponge and mechanical processing. We examined titanium-alloys samples obtained at different stages of titanium production, namely, an electrode compaction, a vacuum arc remelting with a consumable electrode (VAR), and a cold rolling of titanium-sheets. It has been found out that all studied samples will be a source of uranium and thorium contamination of the final titanium-alloys. It has been established that the only product allowed obtaining ultra-low-background titanium was the VT1-00 which is manufactured without master alloys addition..

Density functional theory (DFT) and coupled cluster theory (CCSD(T)) calculations are performed to investigate the geometric, electronic structures and chemical bonding of a series of Cu-doped zinc oxide clusters, CunZn3O3 (n = 1-4). The structural evolution of CunZn3O3 (n = 1-4) clusters are elaborated in our work. The planar seven-membered ring of CuZn3O3 cluster plays an important role in the structural evolution, that is, the Cu atom, Cu dimer (Cu2) and Cu trimer (Cu3) anchor on the CuZn3O3 cluster. The aggregate behavior of Cu atoms on Zn3O3 may offer insight into the study of Cu/ZnO-based catalysts. Additionally, it is found that the CunZn3O3 clusters become more stable as the Cu content (n) increases. Bader charge analysis points out that as the Cu atoms doping, the reducibility of Cu aggregation (Cun-1) on the CuZn3O3 cluster increases. Combined with the d-band centers and the surface electrostatic potential (ESP), the reactivity and the possible reaction sites of CunZn3O3 (n = 1-4) clusters are also illustrated.

Olive trees have a unique reproductive pattern marked by biennial fruiting. This study delves into the repercussions of alternate fruit bearing on the water relations of olive trees and the associated ecophysiological mechanisms. The experiment spanned two consecutive years: the "ON" year, characterized by a high crop load, and the "OFF" year, marked by minimal fruit production. Key ecophysiological parameters, including sap flow, stomatal conductance, and photosynthetic rate, were monitored in both years. Pre-dawn water potential was measured using continuous stem psychrometers and the pressure chamber technique. Biochemically, non-structural carbohydrate concentrations (starch, sucrose, and mannitol) and the carbon-stable isotope ratio (δ13C) in olive leaves were examined. Results unveiled heightened leaf gas exchange during the "ON" year, leading to increased water consumption and photosynthetic rates. This escalated water usage during the "ON" year significantly reduced leaf water potential. Sucrose and starch concentrations were notably elevated in the "ON" year, with no significant impact on mannitol concentration. Regarding the carbon stable isotope ratio, leaves from the "OFF" year exhibited significantly higher δ13C abundance, indicative of heightened resistance to the CO2 pathway from the atmosphere to carboxylation sites compared to the "ON" year plants.

Recently, pharmaceutical research has been focused on the design of new antibacterial drugs with higher selectivity towards several strains. Major issues concern the possibility to obtain com-pounds with fewer side effects, at the same time effectively overcoming the problem of antimi-crobial resistance. Several solutions include the synthesis of new pharmacophores starting from piperazine or morpholine core units. Mass spectrometry-based techniques offer important sup-port for the structural characterization of newly synthesized compounds to design safer and more effective drugs for various medical conditions. Here, two new piperazine derivatives and four new morpholine derivatives were synthesized and structurally characterized through a combined approach of FT-ICR and LTQ mass spectrometry. The support of both high-resolution and low-resolution mass spectrometric data namely accurate mass measurements, isotopic distribu-tion and MSn spectra, was crucial to confirm the success of the synthesis. These compounds were further evaluated for inhibitory activity against a total of twenty-nine Gram-positive and Gram-negative bacteria to determine the action spectrum and the antimicrobial effectiveness. Results demonstrated compounds’ antimicrobial activity against many tested bacterial species, providing an inhibitory effect linked to different chemical structure and suggesting that the new-synthesized derivatives could be considered as promising antimicrobial agents.

Evapotranspiration (ET) is a major component of water budget in Bottomland Hardwood Forests (BHF) and is driven by a complex intertwined suite of meteorological variables. The understanding of these interdependencies leading to seasonal variations in ET is crucial in better informing water resource management in the region. We used a structural equation modeling approach to analyze the drivers of ET using Eddy covariance water and heat flux data collected from a BHF, located in the Russel Sage Wildlife Management Area (RSWMA). It consists of mature closed-canopy deciduous hardwood trees with an average canopy height of 27 m. Factor analysis was used to characterize the shared variance among drivers and path analysis was used to quantify independent contributions of individual drivers. In our results, ET and net radiation (Rn) showed similar variability patterns with Vapor Pressure Deficit (VPD) and temperature in Spring, Summer, and Autumn seasons while they differ in Winter season. The path analysis shows that Rn has the strongest influence on ET variations via direct and indirect pathways. In the deciduous forests like BHFs, our results suggest ET is more energy-dependent during growing season (Spring and Summer) and early non-growing season (Autumn) while more temperature-dependent during winter season.

Cordycepin has good antitumor activity, but its clinical application is limited due to the easy deamination of N6 in structure. In this study, a large lipopolysis group was introduced at the cordycepin N6 to improve the problem, Cordycepin derivatives(3a-4c) were synthesized, and biological evaluation of compounds were studied. In the study, the vitro antitumor activity of the compounds against MCF7 cells, HepG2 cells and SGC-7901 cells was evaluated by MTT assay. In the results, compound 4a showed the most obvious inhibitory effect on MCF7 cells with IC50 value of 27.566±0.52 μM, which was much lower than cordycepin. Compound 4a showed high selectivity between MCF7 and normal MCF-10A cells. Further biological evaluation showed that compound 4a promoted apoptosis and blocked the cell cycle in G0/G1 phase. Then, Western Blot was used to detect related apoptotic proteins. It was found that Compound 4a could down-regulate the expression of Bcl-2 protein and up-regulate the expression of p53, Bax, Caspase-3, and Caspase-9 proteins. The mitochondrial membrane potential decreased continuously and the positive expression rate decreased. It was speculated that compound 4a induced the apoptosis of MCF7 cells through the mitochondrial pathway.

Although the statistical methods of downscaling climate data have progressed significantly, the development of high-resolution precipitation products continues to be a challenge. This is especially true when interest centres on downscaling value over several study sites. In this paper , we report a new downscaling method termed the multi-site Climate Generative Adversarial Network (MSCliGAN), which can simulate annual maximum precipitation to the regional scale during the 1950-2010 period in different cities in Canada by using different AOGCM's from the Coupled Model Inter-Comparison Project 6 (CMIP6) as input. Auxiliary information provided to the downscaling model included topography and land-cover. The downscaling framework uses a convolution encoder-decoder U-net network to create a generative network and a convolution encoder network to create a critic network. An adversarial training strategy is used to train the model. The critic/discriminator used Wasserstein distance as a loss measure and on the other hand the generator is optimized using a summation of content loss on Nash-Shutcliff Model Efficiency (NS), structural loss on structural similarity index (SSIM), and adversarial loss Wasserstein distance. Downscaling results show that downscaling AOGCMs by incorporating topography and land-use/land-cover can produce spatially coherent fields close to observation over multiple-sites. We believe the model has sufficient downscaling potential in data sparse regions where climate change information is often urgently needed.

This paper aims to propose improvements for plastic waste management in Salvador – the Brazilian third most populated metropolis – via Partial Least Squares Structural Equation Modeling (PLS-SEM). All indicators, constructs, and hypotheses regarding collection, sorting, recycling, and disposal in the proposed PLS model were derived from the literature review, and the dependence of the performance construct on efficiency, effectiveness, municipality's socioeconomic aspects and municipality infrastructure is evaluated. Academic and practitioner publics were surveyed, and after analysis in both SmartPLS and RStudio software, suggestions for improvement regarding plastics recycling rate, market maturity, and infrastructural aspects for optimized reverse logistics were made. Since almost double the minimum number of respondents answered the survey questionnaire and the PLS-SEM statistics showed that the modeling presents consistency, the discussion is relevant. The model can and will evolve, but examples of suggested improvement are the installation of Deposit-Return Systems (DRS) in parks, streets, and avenues for increasing selective collection and the direct purchasing of waste from residents by municipal administration, compensating them with vouchers for food. The model can be a basis for other cities worldwide sharing analogous characteristics. By considering it, organizations can contribute to both reduced Greenhouse Gas (GHG) emissions and reduced terrestrial pollution.

The paper presents the results of experimental studies and mathematical modeling of the effect of stress accumulation in thermosetting epoxy polymer "hot" curing on anhydride hardener. Stress accumulation occurs under cyclic thermomechanical action in a locked rod, similar effects are observed, for example, in thermoplastic elements subjected to the combined effect of mechanical loads and variable temperatures. Experimental results have shown that under cyclic thermomechanical loading during exploitation it is possible to accumulate residual stresses in the thermosetting polymer. A multi-element structural mathematical model with memory for thermomechanical load, which allows to consider the accumulation of residual thermal stresses, has been proposed. The results of modeling and experiment are compared. Based on the results, corrections are made in the approach to the application of this model to thermosetting polymers such as the epoxy resin under study. Considering the corrections, a good agreement (the difference is from 1 to 6%) with the results of experimental determination of stresses under complex cyclic thermomechanical load was obtained.

The Digital Twin is one of the big technology trends of the last decade. In the course of its rapid expansion into the various fields of application, many different definitions emerged, tailored to the respective applications. Taxonomies can cluster the diversity and define application-specific archetypes. This paper presents a characterization of the Digital Twin in the context of structural mechanics and lightweight design. It begins by exploring various definitions of the Digital Twin concept and its application in different industries. The paper further analyzes the product life cycle of structures, dividing it into the design and operational phases and identifying the requirements for a Digital Twin in each phase. The structural design process is examined, including the definition of a structure and the stages of the product development process. Additionally, the paper discusses the operational phase of structures, highlighting the need for continuous monitoring, evaluation, and adaptation through Structural Health Monitoring (SHM) systems. The paper proposes two archetypes of Digital Twins for structures: a structure-designing Digital Twin for the design phase and a structure-monitoring Digital Twin for the operational phase. The findings provide a framework for implementing Digital Twins in structural mechanics, enabling digital design and monitoring of structures for improved performance and maintenance strategies.

Polysaccharide from Ficus carica L. (FCP) exert multiple biological activities, as a biological macromolecule, the available knowledge about the specific structures and mechanisms of biological activity of purified 'Brunswick' fig polysaccharide is currently limited. In the present study, by chemical purification and characteristics identified via specific instruments, and then the impact of FCP on the immunomodulation activity in vitro and in vivo was examined. Structural char-acteristics showed that the molecular weight of the FCP was determined to be 127.5 kDa, the primary monosaccharides present in the FCP were galacturonic acid (GalA), arabinose (Ara), galactose (Gal), rhamnose (Rha), glucose (Glc), and xylose (Xyl) at a ratio of 0.321:0.287:0.269:0.091:0.013:0.011. Based on the investigation of in vitro immunomodulatory ac-tivity, FCP was found to stimulate the production of NO, TNF-α, and IL-6 and increased the pi-nocytic activity of macrophages. Further analysis revealed that FCP activated macrophages by interacting with toll-like receptor 4 (TLR4). Moreover, the in vivo test results indicate that FCP showed significant increase serum pro-inflammatory factors in immunosuppressed mice. Overall, this study suggests that FCP has the potential to be utilized as a novel immunomodulator in the pharmaceutical and functional food industries.

While machine learning (ML) has been quite successful in the field of structural health monitoring (SHM), its practical implementation has been limited. This is because ML model training requires data containing a variety of distinct damaged instances captured from a real structure and the experimental generation of such data is challenging. One way to tackle this issue is by generating training data through numerical simulations. However, simulated data cannot capture the bias and variance of experimental uncertainty. To overcome this problem, this work proposes a deep learning-based domain transformation method for transforming simulated data to the experimental domain. Use of this technique has been demonstrated for debonding location and size prediction of stiffened panels using a vibration-based method. The results are satisfactory for both, debonding location and size prediction. This domain transformation method can be used in any field where experimental data for training machine learning models is scarce.

China is facing the development requirements of the dual carbon goal and the construction needs of resilient cities. Currently, high-strength composite structural systems are a feasible solution, but their research and application in the construction field are insufficient, especially for the combination forms of concrete above C100 and steel above Q550. In response to this issue, this paper proposes a new high-performance structural system, namely the composite frame - high-strength steel plate wall core tube resilient structure system, which includes high-strength steel plate (Q550) - ultra-high strength concrete (C100) shear walls, replaceable energy dissipation coupling beams, and composite frames. Taking a 200 meter building as an example, this paper designs and establishes calculation models for a conventional reinforced concrete frame-core tube structure and a high-performance structure based on PKPM software, and establishes elastoplastic analysis models for both based on SAUSAGE software, and then conducts dynamic elastoplastic time history analysis and seismic resilience assessment of structures under design basis earthquakes (DBEs), maximum considered earthquake (MCEs) and extremely rare earthquakes (EREs). Research has shown that compared to conventional structures, new high-performance structures can effectively reduce the size of shear walls, reduce the self-weight of the structure, and enhance the space for building use; The story drift ratio has higher redundancy than specification limits, lower plastic damage and overall stiffness degradation of the structure, and better seismic performance; The seismic resilience has significantly improved, especially in the case of casualties, which can better ensure the safety of people's lives and property.

The response of building elements during earthquakes has been an area of concern for different researchers around the world. The NSEs are the first elements to attain failure, the buildings after damages in safety priority are classified as in “Life Safety” mode, but in reality, they are in “Collapse Safety” mode and the occupants inside the buildings are in a state of “Non-Life Safety” as a result of falling of the hazardous NSE’s like cladding's, partitions, hanging objects. In addition to the Life Cycle Cost Assessment (LCCA), the Social Life Cycle Assessment (SLCA) is overlooked by the majority of the researchers, the community must be prepared to respond to an event more efficiently without any major casualties or loss of life. It is expected that by the end of 2050, almost double the construction will take place, the embodied energy during the pre-construction, post-construction and demolition generates a lot of CO2s into the environment, hence sustainability should be given due importance, helping in the achievement of Sustainable Developmental Goals (SDGs).

Gangliosides are highly abundant in the human brain where they are involved in major biological events. In brain cancers, alterations of ganglioside pattern occur, some of which being correlated with the neoplastic transformation, while others with the tumor proliferation. Of all the techniques, mass spectrometry (MS) has proven to be one of the most effective in gangliosidomics, due to its ability to characterize heterogeneous mixtures and discover species with biomarker value. This review highlights the most significant achievements of MS in the analysis of gangliosides in human brain cancers. The first part presents the state-of-the-art in the MS development for discovery of ganglioside markers in primary brain tumors, with a particular emphasis on the ion mobility separation (IMS) MS and its contribution to the elucidation of the gangliosidome associated with aggressive tumors. The second part is focused on the MS of gangliosides in brain metastases, highlighting the ability of matrix-assisted laser desorption/ionization (MALDI)-MS, microfluidics-MS and tandem MS to decipher and structurally characterize species involved in the metastatic process. In the end, several conclusions and perspectives are presented, among which the need for development of a reliable software and a user-friendly structural database as a search platform in brain tumor diagnostics.

With the deterioration of the bridge performance and ever-increasing amount of traffic, the bridge safety is becoming a concern for engineering community. A method that can assess the bridge's condition in real-time is urgently needed. The main factors that hinder the bridge condition assessment are the uncertain operational environments. A new moving principal component analysis (MPCA) based method is developed for structural damage detection of bridges in operational environments in this paper. Two main operational environmental factors: the environmental temperature and traffic loads, are studied in the assessment process to verify the robustness and practicality of the proposed method. The numerical and experimental results show that the proposed method is effective and accurate to assess the bridge condition in operational environments.

When designing the battery of an electric vehicle, different parameters must be considered to obtain the safest arrangement of the battery/modules/cells from the mechanical and thermal point of view. In this study, the thermal runaway propagation mechanism of lithium-ion cells is analyzed as a function of their arrangement within a battery pack in case of a fire propagation of a battery pack in which a thermal runaway has occurred. The objective is to identify which cell/module arrangement is most critical within the battery pack by microscopic analysis of the structure and chemical composition of the most damaged cells, both horizontally and vertically, of a battery belonging to a burnt vehicle. And their final condition has been compared with the condition of new cells of the same type. In this way the structure and chemical composition of the anode, cathode and separator after Thermal Runaway has been compared. This research has been carried out to obtain information to understand the mechanical properties of lithium-ion cells and their behavior after thermal runaway heating leading to the propagation of a fire. Through the analysis carried out, it is concluded that cells placed in a vertical arrangement have worse behavior than cells in a horizontal arrangement. Regarding the safety of the battery, the results of this study will allow to determine which arrangement and structure of the cells within the battery pack is safer against thermal runaway due to thermal failure.

Robots in space are necessarily extremely light and lack structural stiffness resulting in natural frequencies of resonance so low as to reside inside the attitude controller’s bandwidth. A variety of input trajectories can be used to drive a controller’s attempt to ameliorate the control-structural interactions where feedback is provided by low-quality, noisy sensors. Traditionally, step functions are used as the ideal input trajectory. However, step functions are not ideal in many applications, as they are discontinuous. Alternative input trajectories are explored in this manuscript and applied to an example system that includes a flexible appendage attached to a rigid main body. The main body is controlled by a reaction wheel. The equations of motion of the flexible appendage, rigid body, and reaction wheel are derived. A feedback controller is developed to account for the rigid body modes. Additional filters are added to compensate for the system’s flexible modes. Sinusoidal trajectories are autonomously generated to feed the controller. Whiplash compensation is additionally implemented for comparison. The control method without random errors with the smallest error is the sinusoidal trajectory method, which showed a 97.39% improvement when compared to the baseline response when step trajectories were commanded, while the sinusoidal method was inferior to traditional step trajectories when sensor noise and random errors were present.

Recently, more wind turbine systems are being installed in deep waters far from the coast. Several concepts of floating wind turbine systems (FWTSs) are developed, among which the semisubmersible platform, due to its applicability in different water depths, good hydrodynamic performance, and facility in the installation process, constitutes the most explored technology compared to the others. However, a significant obstacle to the industrialization of this technology is a design of a cost-effective FWTS, which can be achieved by optimizing the geometry, size and weight of the floating platform, along with the mooring system. This is only possible by selecting a method capable of accurately analyzing the FWTS coupled hydro-aero-structural dynamics at each design stage. Accordingly, this paper aims at providing a detailed overview of the most common coupled numerical and physical methods, including their basic assumptions, formulations, limitations, and costs, used for analyzing the dynamics of FWTSs, mainly those supported by a semisubmersible, to assist the choice of the most suitable method at each design phase of FWTSs. Finally, the article discusses possible future research to address challenges in modeling FWTSs dynamics that persist to date.

The unsafe behavior of frontline workers at construction sites is the most important cause of construction accidents. This study proposed a comprehensive model of frontline workers' unsafe behaviors based on a systems perspective and used structural equation modeling (SEM) to explore the influence mechanisms between Objective Conditions (e.g., work environment, work climate, task complexity), Safety Management (e.g., safety education and training, safety reward and punishment regulations, safety inspection, safety technology disclosure, safety warning signs), Group Influence (propagation of unsafe behaviors among workers), Personal Perception (subjective judgment of operators on their safety knowledge and skills), and Unsafe Behaviors. Data from 460 frontline workers were collected through questionnaires and the correlation hypotheses were tested using SPSS 26.0 and Amos 26.0 software. The following conclusions were obtained: (1) Objective Conditions directly positively influence Safety Management, Group Influence, and Personal Perception, but indirectly negatively influence Unsafe Behavior; (2) Safety Management not only directly positively affects Personal Perception but also directly negatively affects Unsafe Behavior. However, the direct effect of Safety Management on Group Influence is not significant; (3) Group Influence has a direct positive effect on Unsafe Behavior, but the direct effect on Personal Perception is not significant; (4) The direct effect of Personal Perception on Unsafe Behavior is insignificant. These findings can be used as preliminary data to guide decision-makers or managers in construction companies to develop reasonable management plans to curb unsafe behaviors of frontline workers.

The aeroelastic response of lightweight low-speed aircraft with slender wings under extreme flow turbulence intensity is not well-understood. Experiments on a commmercial unmanned aerial vehicle (UAV) with a 3-meter wingspan and aspect ratio of 13.6 were performed in a large open-return wind tunnel with extreme flow turbulence intensity of T∞≈10%. The structural dynamics of the wing in the bending mode and the flow beneath the wing to capture the effect of aileron deflection was measured using laser displacement sensors and tomographic particle image velocimetry (PIV) techniques. The unsteady lift produced by the wing was also measured using a high-capacity load cell at an angle of attack, α of 2 degrees for three freestream velocities U∞ of 13.4 m/s, 17.9 m/s, and 26.8 m/s representing the UAV’s stall through cruise speed. It was found that high flow turbulence intensity with large integral length scales relative to the wing chord plays a dominant role in the large unsteady lift and wing displacements measured. The power spectral density (PSD) of wing structural vibration shows that flow shedding from the wing and the integral length scales have a significant impact on the overall power inherent in the bending vibration of the wing. Computation of vorticity iso-surfaces in the flow measurement volume surrounding the aileron reveal a striking observation; aileron deflection, δa of 10∘becomes less effective in producing additional spanwise vorticity, which is proportional to circulation and lift, at U∞ of 26.8 m/s because the freestream already has elevated levels of vorticity. A paradigm shift in design is suggested for light aircraft structures with slender wings operating in highly turbulent flow, which is to employ multiple control surfaces in order to respond to this flow and mitigate large bending or torsion displacements and the probability of structural failure.

Synthetic fiber ropes are frequently used as mooring lines in floaters supporting Floating Offshore Wind Turbines (FOWTs) due to their various advantages. Damages in these lines can lead to the disruption of the FOWTs normal operation and thus their early detection is crucial. Currently, this damage detection problem has been investigated exclusively for FOWT chain mooring lines. This study focuses on the damage detection in FOWT synthetic mooring lines under varying environmental-operational conditions (EOCs) via two types of vibration-based Structural Health Monitoring methods: those based on Multiple Models and those based on a single Functional Model. The methods are based on multivariate AutoRegressive or on scalar Transmittance Function (TF) AutoRegressive with eXogenous input models. All methods are evaluated through a Monte Carlo study involving 390 simulations with a 10MW wind turbine mounted on the semi-submersible OO-Star wind floater and two damage scenarios (10%, 14% stiffness reduction) to a single mooring line. The results using acceleration signals from only two measuring positions on the mooring line, indicate the great potential for robust SHM in FOWTs synthetic mooring lines with the TF model-based methods successfully detecting the considered early stage damage scenarios, even for EOCs not encountered in the methods training.

Corporate identity has played a vital role in the Halal industry to create a strong foundation for its reputation in the long run. This paper used two modeling analyses for two different data. The first analysis aims to predict the relationship between Corporate Identity Management between Internal Brand and Employee Brand Support (consequence) mediated by CIM using partial-least squares-structural equation modeling (PLS-SEM). A total of 206 employees from Malaysia’s Halal food SMEs took part in the survey. The second analysis to identify topic proportions patterns using the topic modeling approach on Halal brand identity Machine learning approach of knowledge mining was applied for this analysis. Metadata of 1,091 articles were mined from the Scopus database on Halal studies across all social sciences fields. The result revealed that there was a partial relationship between Internal Brand (antecedent) and Employee Brand Support (consequence) mediated by CIM. This finding was supported by the identified topic proportions patterns from the topic modeling approach that pointed out a weak topic proportion on the Halal brand identity discussion globally, interestingly the result also found that the Halal brand identity discussion involving the Halal food industry is almost non-existed in Malaysia’s Halal food SMEs. The contributions of this paper were apparent in three major areas which are methodology, theoretical and future suggestions. The utilization of two different model analyses was able to confirm the consistency of the major findings with the literature review which opens up more possibilities for future researchers.

Insulin icodec of Novo Nordisk is a novel long-acting insulin analogue that exhibits an extended duration of action, providing a promising treatment option for individuals with diabetes. It has been reported that the incorporation of fatty acid moieties into insulin icodec plays a crucial role in its prolonged action, as these fatty acid chains facilitate the formation of stable hexameric structures, thereby delaying insulin absorption and promoting sustained release. Yet, the underlying biophysics still is elusive of the roles of the three site-specific mutations (Y14A\_E, Y37B\_H, F46B\_H) of insulin icodec in its prolonged activity. Thus, through a comprehensive structural and biophysical analysis of the insulin (both native and icodec) structures bound to its receptor, this article delves deep into the biophysics underlying the molecular design of insulin icodec, and identified a delicate biophysical mechanism through which two missense mutations of insulin icodec (Y37B\_H and F46B\_H) contribute to its prolonged duration of action. Overall, this structural and biophysical investigation provides valuable insights into the mechanisms underlying the relationship between three site-specific mutations and prolonged duration of action of insulin icodec, while understanding these modifications at a structural and biophysical level can aid in the rational design of future long-acting insulin analogues, offering further enhanced therapeutic options for diabetic patients.

A new utilization of entropy in the context of buckling is presented. The novel concept connecting strain energy and entropy for a pin-ended strut is derived. This concept rationalizes the ranking of buckling modes based on strain energy under the assumption of given entropy. By assigning identical entropy to all buckling modes, they can be ranked according to their deformation energy. Conversely, with identical strain energy assigned to all modes, ranking according to entropy is possible. Decreasing entropy was found to represent the scaling factors of buckling modes that coincide with the measurement of initial out-of-straightness imperfections in IPE160 beams. Applied to steel plane frames, scaled buckling modes can be used to model initial imperfections. It is demonstrated that the entropy (scale factor) for given energy roughly decreases with the inverse square of the mode index. For practical engineering, the study presents the possibility of using scaled buckling modes of steel plane frames to model initial geometric imperfections. Entropy proves to be a valuable complement to strain energy in structural mechanics.

Bacteria are engaged in a constant battle against preying viruses, called bacteriophages (or phag-es). These remarkable nano-machines pack and store their genomes in a capsid and inject it into the cytoplasm of their bacterial prey following specific adhesion to the host cell surface. Tailed phages possessing dsDNA genomes are the most abundant phages in the bacterial virosphere, particularly those with long, non-contractile tails. All tailed phages possess a nano-device at their tail tip that specifically recognizes and adheres to a suitable host cell surface receptor, being pro-teinaceous and/or saccharidic. Adhesion devices of tailed phages infecting Gram-positive bacte-ria are highly diverse and, for the majority, remain poorly understood. Their long, flexible and multi-domain encompassing tail limits experimental approaches to determine their complete structure. We have previously shown that the recently developed protein structure prediction program AlphaFold2 can overcome this limitation by predicting the structures of phage adhesion devices with confidence. Here, we extend this approach and employ AlphaFold2 to determine the structure of a complete phage, the lactococcal P335 phage TP901-1. Herein we report the structures of its capsid and neck, its extended tail, and the complete adhesion device, the baseplate, which was previously partially determined by X-ray crystallography.

This study aimed to identify and categorize the influencing factors on the purchase of dairy products among customers of dairy companies in Mashhad city. This study is a mixed research (qualitative and quantitative), conducted with the aim of identifying and categorizing the influencing factors on consumers’ purchase. Therefore, the theoretical foundations were examined in the initial step, after which the customers and their needs and demands were addressed in terms of the company and its products. In the qualitative part, interviews were conducted in the focus group (23 people in 5 groups) to identify and extract these factors using the theme analysis technique. The reliability of the interviews was confirmed by retesting and the reliability between two encoders. Sixty themes (factors) that affected the purchase of dairy products were collected. In quantitative part, 517 questionnaires were collected from 13 regions of Mashhad city to perform statistic tests. A questionnaire was designed using the extracted themes in the previous (qualitative) stage to assess customers’ feedback. The validity of the questionnaire was confirmed by content and structure validity (exploratory and confirmatory factor analysis), and its reliability was checked by Cronbach’s alpha. Fourteen components were obtained by exploratory and confirmatory factor analyses, after which the variables were labeled as intrinsic, psychological, and personality factors, the identity of the company, production power of the company, competitive power of the company, competitive prices, social awareness, and store capabilities. The construct validity was confirmed using confirmatory factors.

In its prefusion state, the SARS-CoV-2 Spike protein (similarly to other class I viral fusion proteins) is metastable, which is considered to be an important feature for optimizing or regulating their functions. After the binding process of its S1 subunit (S1) with the ACE2, the Spike protein (S) suffers a dramatic conformational change where S1 splits from the S2 subunit, which then penetrates the membrane of the host cell, promoting the fusion of the viral and cell membranes. This results in the infection of the host cell. In a previous work, we showed -using large scale molecular dynamics simulations- that the application of external electric fields (EF) induces drastic changes and damage in the receptor-binding domain (RBD) of the wild type Spike protein, as well of the Alpha, Beta and Gamma variants, leaving a structure which cannot be recognized any more by ACE2. In this work, we first extend the study to the Delta and Omicron variants and confirm the high sensitivity and extreme vulnerability of S to moderate EF (as weak as 104 V m-1), but, more importantly, we also show that, in contrast, the postfusion state of the spike protein does not suffer structural damage even if electric field intensities four orders of magnitude higher are applied. These results provide a solid scientific basis to confirm the prefusion state metastability roots of the SARS-CoV-2 Spike protein susceptibility to be damaged by EF. After the virus docks to the ACE2 receptor, the stable and robust postfusion conformation develops, which exhibits a similar resistance to EF (damage threshold higher than 108 V m-1) like most globular proteins.

With 500+ papers and 20+ books spanning many scientific disciplines, Mark Burgin has left an indelible mark and legacy for future explorers of human thought and information technology professionals. In this paper, I discuss his contribution to the evolution of machine intelligence using his general theory of information (GTI) based on my discussions with him and various papers I co-authored during the past eight years. His construction of a new class of digital automata to overcome the barrier posed by the Church-Turing Thesis, and his contribution to Super-Symbolic Computing with Knowledge Structures, Cognizing Oracles, and Structural Machines are leading to practical applications changing the future landscape of information systems. GTI provides a model for the operational knowledge of biological systems to build, operate, and manage life processes using 30+ trillion cells capable of replication and metabolism. The schema, and associated operations derived from GTI are also used to model a digital genome specifying the operational knowledge of algorithms executing the software life processes with specific purposes using replication and metabolism. The result is a digital software system with a super-symbolic computing structure exhibiting autopoietic and cognitive behaviors that biological systems also exhibit. We discuss here one of these applications.

The (benzylthio)acetic acid (HBTA) and some aminopyrimidines, namely 2-aminopyrimidine (2-AP), 5-aminopyrimidine (5-AP), 2-amino-4,6-dimethylpyrimidine (2-A-4,6-DMP) and 2,4,6-triaminopyrimidine (2,4,6-TAP), were successfully embodied as structural units into the construction of a total of four novel supramolecular organic frameworks. The received crystalline solids were inspected by single crystal X-ray diffraction (SC XRD) in order to obtain insight into the structural and supramolecular facets. The SOFs deriving from 2-AP, 5-AP as well as 2-A-4,6-DMP crystallize in the form of true co-crystals (1-3), while the one originating from 2,4,6-TAP crystallizes as salt solvate (4). The SC XRD results indicated the different contents of structural residues present in the asymmetric units of the crystals 1-4 despite the using the same molar ratio of molecular co-formers in each case. The molecular structures of co-crystals 1-3 consist of either one neutral residue of each starting components (1 and 3) or a half nonionized residue of aminopyrimidine ingredient and one neutral residue of acidic specie (2). The asymmetric unit of salt solvate 4 is composed of two ionized residues of each co-former (two 2,4,6-TAP+ cations and two BTA- anions) and one MeOH solvent molecule. The most extensive H-bonding network is observed in the crystal structure of salt solvate 4. The relevant molecular ingredients in co-crystals 1-3 are mainly hold together by the neutral Ocarboxylic–H···Npyrimidine and Namine–H···Ocarboxylic H-bonds. In the case of aggregate 4, the corresponding ionic residues are predominantly sustained by the charged-assisted Npyrimidinium–H···Ocarboxylate and Namine–H···Ocarboxylate hydrogen interactions. The MeOH solvent incorporated into the crystal lattice of adduct 4 is also involved in H-bonding by simultaneously serving as the single donor in OMeOH–H···S and the single acceptor in Namine–H···OMeOH H-bonds afforded the structural diversity within the 2,4,6-TAP+ cations and BTA- anions. Other weaker sets of additional non-covalent contacts existing in the crystal structures of analyzed conglomerates are involved in the self-assembly, stabilization and expansion of total supramolecular organic frameworks. The fact of the formation of non-covalent bonded supramolecular organic frameworks in question is also reflected in corresponding results obtained through elemental analysis (EA), Fourier transform infrared spectroscopy (FT−IR) and thermal analysis (TG/DSC).

With nearly 1,700 species, Microsporidia represent a group of obligate intracellular eukaryotes with veterinary, economic and medical impacts. To help in understanding the biological functions of these microorganisms, complete genome sequencing is used routinely. Nevertheless, the proper prediction of their gene catalogue is challenging due to taxon-specific evolutionary features. As innovative genome annotation strategies are needed to obtain a representative snapshot of the overall lifestyle of these parasites, the MicroAnnot tool, a dedicated workflow for microsporidian sequence annotation using data from curated databases of accurately annotated microsporidian genes, has been developed. Furthermore, specific modules have been implemented to perform small genes (< 300bp) and transposable element identification. Finally, functional annotation was performed using the signature-based InterProScan software. MicroAnnot’s accuracy has been verified by the re-annotation of four microsporidian genomes for which structural annotation had previously been validated. With its comparative approach and transcriptional signal identification method, MicroAnnot provides accurate prediction of translation initiation sites, efficient identification of transposable elements, as well as high specificity and sensitivity for microsporidian genes including those under 300 bp. Thanks to its web interface (https://microannot.org), MicroAnnot is available to the community to ensure high quality annotation of microsporidian genomes.

Drug-target affinity (DTA) prediction is crucial for understanding molecular interactions and aiding drug discovery and development. While various computational methods have been proposed for DTA prediction, their predictive accuracy remains limited, failing to delve into the structural nuances of interactions. With increasingly accurate and accessible structure prediction of targets, we developed a novel deep learning model, named S2DTA, to accurately predict DTA by fusing sequence and structural knowledge of drugs, targets, and pockets using heterogeneous models based on graph and semantic networks. Experimental findings underscored that complex feature representations imparted negligible enhancements to the model’s performance. However, the integration of heterogeneous models demonstrably bolstered predictive accuracy. In comparison to three state-of-the-art methodologies, the supremacy of S2DTA became strikingly apparent. It showcased a noteworthy 25.2% reduction in Mean Absolute Error (MAE) and an impressive 20.1% decrease in Root Mean Square Error (RMSE). Furthermore, S2DTA exhibited substantial advancements in other pivotal metrics, including Pearson Correlation Coefficient (PCC), Spearman, Concordance Index (CI), and R2. These metrics experienced remarkable increments of at least 19.6%, 17.5%, 8.1%, and a remarkable 49.4%, respectively. Finally, we conducted interpretability analysis on the effectiveness of S2DTA by bidirectional self-attention mechanism, fully proving that S2DTA is a valuable and accurate tool for predicting DTA. For further exploration, the source data and code repository can be accessed at https://github.com/dldxzx/S2DTA.

China is rich in coal resources, but the complex hydrogeological conditions lead to difficulties in coal mining, such as coal mine collapse, roof and water damage, and other accidents that occur frequently, resulting in many casualties and property losses. The use of coal mine hole detection technology to detect and analyze the internal environment of the coal mine in advance helps to reduce safety hazards and prevent coal mine accidents, for the existing coal mine hole detection technology operation is cumbersome, not easy to control, and insufficient depth of jacking prob-lems, this paper designs a new type of mine hole detection small robot. Firstly, this paper ana-lyzes the function and structural design of the mine hole detection robot, designs the variable diameter function according to the characteristics of narrow and uneven mine holes in coal mines, and analyzes the mechanics of the critical parts through theoretical calculations; secondly, based on the three-dimensional modeling software, established the structural model of the small robot for mine hole detection; after that, designed the robot's hardware circuits and control pro-grams for the presence of water and gas inside the mine hole, highlighting the need to carry out a new type of mine hole detection small robot. After that, we designed the robot's hardware circuit and control program, giving particular emphasis to the safety design of the circuit for the pres-ence of water and gas inside the mine hole of the coal mine. Finally, to verify the feasibility of the design program, the basic parameters and function tests of the mine hole detection small robot are carried out. The experimental results show that the mine hole inspection small robot realized by this design can adapt to the working hole diameter from 65 mm to 100 mm, the maximum working power is only 12 W, and the maximum crawling speed is 3.96 m/min. The maximum crawling slope reaches 90°, which can meet the actual mine hole inspection needs. The research can provide theoretical and design guidance for developing the mine hole detection robot with substantial engineering practical reference value.

The design of water Vessel fender system can minimize impact energy, which could result in severe vessel or offshore structure damage during collision. In order to protect Offshore structures and vessels from damage after impact, a Fender design approach is proposed which uses Soft materials like rubber, sand, inflated rubber tube, etc. to reduce damage on impacted vessels as well as offshore structures like wind turbines, bridges, oil drilling platforms in water etc. The fender is designed in such a way that it can handle vessels made of different material, sizes, and weights.The proposed solution is a fender consisting of a number of layers of soft sandwich materials, each layer getting softer as it moves away from the structure i.e. Hard-Soft fender design which can absorb impact energy upon collision. To handle lighter vessels made of soft or brittle materials, the outer layer is made of inflatable or Very soft foam rubber; however, the inner layer covering the offshore structure is made of hard material to handle heavy vessels made of hard material such as steel. Furthermore, the use of sand as a natural fender along waterways such as narrow channels is also proposed to reduce the cost of fender installation and catastrophic vessel impact damage on rocky ground since it produces less deformation just like rubber fender as demonstrated in the simulation. Finite Element Analysis using ANSYS software, Explicit Dynamic Autodyn, was performed. The results showed a considerable decrease in the total deformation and internal energy of the vessel and fended structure when collision occurs. Furthermore, the result showed that Hard-Soft fender layer performs much better than Soft-Hard-Soft followed by Soft-Hard Fender layer design.

The article presents a method for obtaining new composites using a well-known mineral, expanded perlite (EP), and an industrial polymer, butadiene rubber (BR). For the design of composites, a joint oxidative chlorophosphorylation reaction of BR and EP (as well as BR and modified EP) was carried out, and the modifications obtained from this reaction were further hydrolyzed. The structure and morphology of the obtained samples were characterized in detail using Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, X-ray powder diffraction, as well as scanning electron microscopy, and energy-dispersive X-ray analysis. EP and BR were separately modified with a similar reaction and characterized for data interpretation.

Intermolecular interactions are the fabrics underlying almost all processes in living organisms, where two cornerstone concepts, intermolecular binding affinity (K d ) and binding energy (ΔG), have long been established to physically describe the strengths of biomolecular interactions, e.g., drug-target K d and ΔG to describe the strength of drug-target interaction. The past two-three years saw a big step forward in the use of artificial intelligence (AI) in structural biology (e.g., AlphaFold for protein structure prediction) and drug discovery & design. In light of the roles of K d and ΔG in drug discovery & design, the speed of this AI progress raises a question of what’s next for its practical application in the pharmaceutical industry, in addition to a system-wide account of biomolecular structures and motions. Last August, the concept of a general intermolecular binding affinity calculator (GIBAC) was for the first time coined and proposed in an MDPI-published preprint. Here, this article puts forward an updated conceptual and practical framework of GIBAC, including its inception, definition, construction, practical applications, technical challenges and limitations, and future directions. Moreover, this article argues that the time is now ripe for the construction of such an accurate, precise and efficient GIBAC to be on the agenda of the entire drug discovery & design community, to ensure its applicability & reliability, and to enhance its value in drug R&D in future.

CagY is the largest and most complex protein from Helicobacter pylori's type IV secretion system (T4SS) and may participate in the modulation of gastric tissue inflammation. A three-dimensional structure has been reported for only two segments of the protein. To build a more complete model, particularly the region that spans between the outer membrane (OM) and the inner membrane (IM), we employed different approaches, including homology modeling, ab initio, and deep learning techniques. For the long-middle repeat region (MRR), modeling was performed using deep learning techniques and Molecular Dynamics. The modeled segments were assembled into a chain of 1595 aa, and a 14-chain CagY multimer structure was composed by structural alignment. The final multimer structure correlated with previously published struc-tures and allows to show how the multimer may form the T4SS channel through which CagA and other molecules are translocated to gastric epithelial cells. The model further confirmed that MRR, the most polymorphic and complex region of CagY, presents numerous cysteine residues forming disulfide bonds that stabilize the protein and suggest this domain probably functions as a contractile region that may play an essential role in the modulatory activity of CagY on tissue inflammation.

This article presents the results of studies of the structure and conductive properties of Na3Fe2(PO4)3 polycrystals synthesized by solid-phase and melt (using concentrated optical radiation) methods. It has been established that with the melt method, the synthesis of the material occurs under significantly nonequilibrium temperature-gradient conditions, which leads to the creation of deformations in the sample that contribute to an increase in ionic conductivity. The ability of the Na3Fe2(PO4)3 structure to adapt to anomalous deformations that occur under temperature-gradient conditions indicates the elasticity of the crystalline framework {[Fe2(PO4)]3-}3∞. Through a comparative assessment of the structural parameters and conductive properties of these materials, it is shown that polycrystals obtained by the melt method have a better texture and greater ionic conductivity. The advantage of this method is that the duration of the synthesis of α-Na3Fe2(PO4)3 is halved. It is concluded that this method is applicable to obtain effective polycrystals of other compositions.

Wind energy is becoming increasingly important as a renewable energy source due to its environmental and economic benefits. Wind turbines are key components in wind energy systems, and their performance is critical for efficient power generation. Wind turbine blades are the most critical components as they interact with the wind, and their design has a significant impact on the overall system performance. Therefore, it is essential to optimize the design of wind turbine blades to enhance their efficiency and reduce their costs. This paper presents an aero-structural optimization approach for wind turbine blade design. The optimization aims to maximize the torque generated by the blade while minimizing its mass. The optimization is implemented using DAFoam software for CFD simulation, TACS for FEM simulation, and Mphys under the OpenMDAO framework for fluid-structure interaction between the CFD and FEM. The optimization results show a 6.78% increase in torque and a 4.22% decrease in mass, which demonstrates the effectiveness of the proposed approach. Aerodynamic optimization focuses on maximizing the blade's torque by modifying the blade's shape. The optimization results show that the optimized blade generates more torque than the original blade design. Additionally, structural optimization aims to minimize the blade's mass while maintaining its structural integrity. This is achieved by adjusting the thickness of the blade's cross-section. The proposed aero-structural optimization approach presents an effective solution for the design optimization of wind turbine blades. The approach considers the interaction between the aerodynamic and structural aspects of the blade and optimizes them simultaneously. This leads to an optimized design that is efficient and cost-effective, which is crucial for the widespread adoption of wind energy systems. The results of this study highlight the importance of considering the interaction between the aerodynamic and structural aspects of wind turbine blades and the effectiveness of the proposed optimization approach in enhancing their performance.

Cabbage (B. oleracea var. capitata) contains three FLC homolog genes (BoFLC1, BoFLC2, and BoFLC3) and one pseudogene (BoFLC5) that responds to low temperatures necessary for flowering. We isolated three BoFLC-encoding genes from early-, mid-, and late-flowering cabbage plants. Leaf samples were collected for RNA extraction and expression analysis. Gene structure analysis and phylogenetic comparison were performed for intra- or interspecific relationships of the BoFLC homologs. Gene expression related to flowering regulators (BoGI, BoCOOLAIR, and BoVIN3) was analyzed. While BoFLC genes commonly have seven exons and six introns of 3,361–4.384 bp, variations in insertion or deletion were evident between the early- and late-flowering genotypes. Repressed expression of BoFLC 1, 2, and 3 genes under chilling temperatures appeared to occur from 8 weeks after vernalization. Higher expression levels of GI, COOLAIR, and VIN3 were initiated 7 weeks after chilling (WAT) treatment in the early flowering genotype. The vernalization trigger repressed the expression of BoFLC homologs. This study provides molecular insights into BoFLC homologs between early- and late-flowering cabbage genotypes, in which structural variations in BoFLC1 appeared to be important as a binding motif to flowering regulating factors such as BoGI, BoCOOLAIR, and BoVIN3 for which motif analysis is further implemented.

The effect of neutron irradiation of Si-Ge/Si film structures obtained by gas-phase epitaxy on the processes of charge carrier generation and the magnitude of the dark short-circuit current and open-circuit voltage caused by it is studied, it is shown that their magnitude practically does not change with time. The results obtained indicate that all types of structural defects, both associated with dopant impurities and radiation exposure, contribute to the generation of charge carriers in heated silicon structures with the participation of deep energy levels, which indicates the applicability of neutron processing of silicon materials to create thermal energy converters, operating at high temperatures.

Background: Aging rate is affected by genetic changes, epigenetic modifications, oxidative stress, inflammation, lifestyle and environmental factors. In accelerated aging (AA), biological age exceeds the chronological one. Objective: To undertake a critical reappraisal of the AA concept and to reveal its weaknesses and limitations. Methods: We reviewed over 300 recent articles dealing with physiology of brain aging and pathophysiology of neurodegeneration. Results: (1) Organ systems age at different rates, which interferes with application of the AA concept to individual organs. (2) Aging rate can be decelerated due to individual structure–functional reserves built with cognitive, physical training or pharmacological interventions. (3) The AA concept lacks standardised terminology and methodology. (4) Specific molecular biomarkers (MBM) reflect aging. To consolidate the AA theory, researchers should validate numerous MBM candidates. (5) Aging factors, mechanisms and the exact nature of their biological outcomes are not well understood. Conclusion: Although considered as a perspective theory, the AA concept has serious limitations and it requires an update.

The effects of the solvent used for the active layer materials of an OLED based on TADF emitters plays a fundamental role in solution-deposited devices. This work focuses the effects on the performance of different solvents employed to fabricate a very simple two organic layer OLED based on a green TADF emitter, under the concept of host:guest matrix. From the different results of the main figures of merit, it was possible to conclude that the OLED that used toluene as solvent for the active layer reached a maximum EQE of 14%, almost the maximum already obtained for this emitter in more complex device structures. With the analysis of the charge transport processes, it was possible to establish an explanatory model for the obtained results. Through impedance spectroscopy, additional characterization about the nature of charge transport processes was carried out. With these results, it was possible to corelate the relaxation times, with the electrical properties of the active layer, and infer about the interaction between the electrical charges and the defect levels opening new possibilities to further development in the printed OLEDs.

In recent years, the use of long-term seismic monitoring systems for the protection of structures is becoming increasingly widespread. This is because more and more awareness is gradually developing regarding the importance of keeping structures under observation so as to prevent any damage scenarios. Within the field of Structural Health Monitoring, data driven techniques allow to process and analyze data collected on site. This paper presents a Mode Tracking procedure to obtain the time-histories of the natural frequencies of a monumental structure. The procedure is applied on the Sanctuary of Vicoforte, an important monumental structure site in Piedmont known for its imposing oval dome and characterized by a permanent structural monitoring system. Through the procedure presented in the paper it has been possible to obtain and observe the time series of the first natural frequencies of the structure considering various aspects, including the temperature variation.

Recently, Electric Two-Wheelers ETW are changing the face of the global automotive market. This study focused on selecting proper material and mechanical isolation gap to design a protective enclosure for the battery pack of ETW. The integration of the Failure, Modes, Mechanism and Effect Analysis (FMMEA) method is utilized to develop the interface matrix and the severity index of different components of the enclosure. By analyzing different forces from the road conditions, dynamics during turn, acceleration, and deceleration with the enclosure, it becomes a crucial load-bearing element. Employing Finite Element Modeling (FEM), structural strength using materials like AL6061, Q235, C22000, DC 01 and Teflon are assessed under varying static, dynamic and thermal conditions. Modal analysis is conducted to observe the excitation frequencies where the maximum deformation for the metal enclosure is observed beyond 500Hz. AL6061 material that can withstand the stresses and deformations that are under allowable stress limits with negligible deformation is most preferable material based on the results. Minimal of 2.5 mm gap to be provided in case of metal casing and 10mm in case of Teflon is proven.

Digital Image Correlation (DIC) is an optical technique used to measure surface displacements and strains in materials and structures. This technique has demonstrated significant utility in structural examination and monitoring. This manuscript offers a comprehensive review of contemporary research and applications that have leveraged the DIC technique in laboratory-based structural tests. The reviewed works encompass a broad spectrum of structural components, such as concrete beams, columns, pillars, masonry walls, infills, composite materials, structural joints, steel beams, slabs, and other structural elements. These investigations have underscored the efficacy of DIC as a metrological instrument for precise quantification of surface deformation and strain in these structural components. Moreover, the constraints of the DIC technique have been highlighted, especially in scenarios involving extensive or complex test configurations. Notwithstanding these constraints, the DIC methodology has validated its effectiveness as a strain measurement instrument, offering numerous benefits such as non-invasive operation, full-field measurement capability, high precision, real-time surveillance, and compatibility with integration into other measurement instruments and methodologies.

Structural design optimization (SDO) plays a pivotal role in enhancing various aspects of construction projects, including design quality, cost-efficiency, safety, and structural reliability. Recent endeavors in academia and industry have sought to harness the potential of Building Information Modeling (BIM) and optimization algorithms to optimize SDO and improve design outcomes. This review paper aims to synthesize these efforts, shedding light on how SDO contributes to project coordination. Furthermore, the integration of sustainability considerations and the application of innovative technologies and optimization algorithms in SDO necessitate more interactive early-stage collaboration among project stakeholders. This study offers a comprehensive exploration of contemporary research in integrated SDO employing BIM and optimization algorithms. It commences with an exploratory investigation, employing both qualitative and quantitative analysis techniques following the PRISMA systematic review methodology. Subsequently, an open-ended opinion survey was conducted among construction industry professionals in Europe. This survey yields valuable insights into the coordination challenges and potential solutions arising from technological shifts and interoperability concerns associated with widespread SDO implementation. These preliminary steps of systematic review and industry survey furnish a robust knowledge foundation, enabling the proposal of an intelligent framework for automating early-stage sustainable structural design optimization (ESSDO) within the construction sector. The framework ESSDO addresses the challenges of fragmented collaboration between architects and structural engineers. This proposed framework seamlessly integrates with the BIM platform, i.e., Autodesk Revit for architects. It extracts crucial architectural data and transfers it to the structural design and analysis platform, i.e., Autodesk Robot Structural Analysis (RSA), for structural engineers via the visual programming tool Dynamo. Once the optimization occurs, optimal outcomes are visualized within BIM environments. This visualization elevates interactive collaborations between architects and engineers, facilitating automation throughout the workflow and smoother information exchange.

Single-particle cryo-electron microscopy (cryo-EM SPA) has recently emerged as an exceptionally well-suited technique for determining the structure of membrane proteins (MPs). Indeed, in the last years, it was observed a huge increase in the number of MPs solved by cryo-EM SPA at a resolution better than 3.0 Å in the Protein Data Bank (PDB). However, sample preparation remains a significant challenge in the field. Here, we evaluated in the MPs solved by cryo-EM SPA deposited in the PDB in the last two years at a resolution below 3.0 Å the most critical parameters for sample preparation: i) the surfactant used for protein extraction from the membrane, ii) the surfactant, amphiphiles, nanodiscs or other molecules present in the vitrification step, iii) the vitrification method employed, and iv) the type of grids used. The aim is not to provide a definitive answer on the optimal sample conditions for cryo-EM SPA of MPs, but rather assess the current trends in the MP structural biology community towards obtaining high-resolution cryo-EM structures.

In the current study, a two-dimensional numerical study is carried out to investigate the performance of a novel Double-chamber Parallel Flexible Valves micropump, which utilized the electrowetting-on-dielectrics (EWOD) effect to drive the microfluid flow. By observing the flow fields, the internal circulations are seen on both the left and right side of the pump. The generation of the backflow is discussed by tracking the movement of the vortices. Only slight flow fluctuation is seen in the micropump. Based on the simulation outcomes, the structural parameters including the width of the inlet/outlet, the width of the pumping channel and the diverging angle in the micropump are analyzed, the influence of these parameters on the pumping volume and the maximum pressure have been discussed. Eventually, a group of optimal parameter combinations is given according to the results to extend the operating potential of the micropump.

Block copolymers are a class of materials particularly interesting for their ability to self-assemble into ordered structures. In this context, the coupling between environment and dynamics is particularly relevant, given that movements at the molecular level influence various properties of macromolecules. Mixing the polymer with a second macromolecule appears to be an easy way to study these relationships. In this work, we studied a system based on two diblock copolymers of methyl methacrylate as first block and 3-methyl-4-[6-(methylacryloyloxy)-hexyloxy]-4’-pentyloxy azobenzene as second block and their blends with PMMA. The relaxational properties of these systems were investigated by electron spin resonance (ESR) spectroscopy sensitive to nanometric length-scales. The results of the study on the blends were related to the dynamic behavior of the copolymer. The study evidenced the presence of fast and slow molecular sites for the molecular reorientation at nanoscale, modulated by the ability of block copolymer to form supramolecular structures. For blends, the heterogeneities at nanoscale are still detected. However it was found that the presence of the PMMA as the major component of the blends modified their dynamic behaviour.

In order to better plan new or update sewer pipe condition assessment protocols, this paper presents systematic comparisons of four most widely-used sewer condition assessment protocols, including the fourth edition of Sewer Rehabilitation Manual (SRM-4) in UK, Pipeline Assessment and Certification Program (PACP) in America, Sewer Physical Condition Grading Protocols (SPCCM) in Canada, and Technical Specification for Inspection and Evaluation of Urban Sewer (TSIEUR) in China. In qualitative comparison, the defects, deduct values and assessment methods of the four protocols were analyzed; in quantitative comparison, protocols were used to evaluate the same 182 sewer pipe segments based on field data and the assessment results were compared. It was found that SRM-4 are the most optimistic with 59% pipes being Grade 1 and Grade 2, while SPCCM gives the most pessimistic results with 62% pipes being Grade 3 and Grade 4. Assessment results by PACP and TSIEUR are in the middle. The main reasons for the different evaluation results were due to the different weight of defect and evaluation methods used.

Diffuse optical tomography (DOT) technology enables a differentiation between oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) in the sensory and motor cerebral gyri, resulting in greater sensitivity for cerebral activation compared to functional magnetic resonance imaging (fMRI). Here, we introduce a novel approach where functional regions of interest (ROIs) are created based on the specific signal behavior observed in DOT measurements, in contrast to the conventional use of structural-ROIs obtained from anatomical information. The generation of cerebral activation maps involves using the general linear model (GLM) to compare the outcomes obtained from both the functional and structural ROI approaches. DOT-derived maps are then compared with maps derived from fMRI datasets considered the gold standard for assessing functional brain activity. The results obtained demonstrate the effectiveness of employing functional ROIs to improve the spatial location of functional activations in the sensory and motor cerebral gyri by leveraging the neural synchronization data provided by DOT. Furthermore, this methodology simplifies data processing in animal models, where anatomical differences compared to the human head can pose challenges. By incorporating functional ROIs prior to GLM application, this study offers enhancements to DOT analysis techniques and broadens its applicability in both human and animal models.