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.

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.

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.

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.

This study investigates the critical success factors (CSFs) of Lean Six Sigma (LSS) implementation and their impact on organizational growth in Nigerian enterprises. The objectives were to identify crucial CSFs for successful LSS deployment and assess their significance in achieving organizational growth. A mixed-method approach was used, including literature analysis, expert judgments, and a survey of 130 participants from various industries. The survey questionnaire employed a 5-point Likert scale to collect data on LSS CSFs and implementation success metrics. Structural equation modeling (SEM) with SmartPLS 4.0 analyzed the data, revealing that LSS CSFs significantly contribute (up to 39.2 percent) to the success of LSS implementations. The study identified 12 critical LSS CSFs, categorized into workers, business, and management, each influencing LSS implementation. Recommendations include creating a supportive environment, providing comprehensive training, and prioritizing continuous improvement efforts for successful LSS deployment. Future research possibilities include longitudinal studies, sector-specific analyses, and qualitative investigations to deepen understanding and enhance LSS implementation outcomes. In conclusion, successful LSS implementation empowers Nigerian organizations with improved productivity, waste reduction, and sustainable production systems, leading to overall growth and success.

The crystal structure of Pb₁₀(PO₄)₆O, the proposed matrix for the potential room-temperature superconductor LK-99, Pb_10-xCu_x(PO₄)₆O (x = 0.9-1.0), has been reinvestigated by single-crystal X-ray diffraction using crystals prepared by Merker and Wondratschek (The crystal structure is trigonal, P, a = 9.8109(6), c = 14.8403(12) Å, V = 1237.06(15), R₁ = 0.0413 using 3456 unique observed reflections. The crystal structure of Pb₁₀(PO₄)₆O is a superstructure with regard to the ‘standard’ P6₃/m apatite structure type. The doubling of the c parameter is induced by the ordering of ‘additional’ O’ atoms within the structure channels running parallel to the c axis and centered at (00z). The O’ atoms form short bonds to the Pb1 atoms, resulting in splitting the Pb1 site into two, Pb1A and Pb1B. The structural distortions are further transmitted to the Pb phosphate framework formed by four Pb2 sites and PO₄ groups. The structure data previously reported by Krivovichev and Burns (Z. Kristallogr. 2003, 218, 357-365) may either correspond to the Pb₁₀(PO₄)₆O_x(OH)_2-x (x ~ 0.4) member of the Pb₁₀(PO₄)₆O - Pb₁₀(PO₄)₆(OH)₂ solid solution series, or to the high-temperature polymorph of Pb₁₀(PO₄)₆O (with the phase with doubled c parameter being the low-temperature polymorph).

Damage assessment is one of the most crucial issues for bridge engineers, especially for existing steel bridges. Among several methodologies, the vibration measurement test is a typical approach in which the natural frequency variation of the structure is monitored to detect the existence of damage. However, locating and quantifying the damage is still a big challenge. In this regard, the artificial intelligence (AI)-based approach seems a potential way to accomplish those obstacles. This study deploys a comprehensive campaign to determine all dynamic parameters of a pre-damage steel truss bridge structure. Based on the results of mode shape, natural frequency, and damping ratio, a finite element model (FEM) is created and keeps updating. The artificial intelligence network's input data will be analyzed and evaluation from damage cases. The trained artificial neural network model will be curated and evaluated to confirm the approach's feasibility. During the actual operational stage of the steel truss bridge, this damage assessment system is showing good performance in terms of monitoring the structural behavior of the bridge under some unexpected accidents.

Emerging soft actuators with various soft materials and traveling-wave motion have been frequently discussed. Various configurations and the resulting performances have been proposed, and it is very challenging for soft actuators in realizing large strokes. This study presents an experimentally validated nonlinear finite element model to predict the deformation produced by a spiral pneumatic rubber actuator to generate traveling-wave motion. The actuator consists of a membrane mounted on a rubber substrate with three air chambers in a spiral configuration, simplifying the actuator's structure. The sequential deformations of the successive chambers interact with each other and produce radial traveling-waves on the membrane surface, driving the objects placed on the actuator. Finite element analysis using ANSYS computer software analyzed the elastic movement by considering the influence of different initial structural types. The structure with three different length ratios was introduced using the four parameters: membrane thickness, chamber width, chamber depth, and wall thickness. The simulation results indicated an optimal structure with specific ratios. A reasonable correlation was obtained during experimental validation; the predicted displacement values were approximately 17% smaller than the experimental values. Finally, the transportation performance of the prototype was tested and a velocity of 2.28 mm/s in the desired direction was achieved. We expect that our demonstration will expand the range of applications of the spiral pneumatic rubber actuator to include conveying or worm-like robots.

Magneto-rheological dampers (MR-dampers) are increasingly used in construction applications to reduce the dynamic response of structures to seismic activities or severe wind loading. Sensors attached to the structure will signal the computer to supply the dampers with electric charge that transfers the MR fluid to a near-solid material with different physical and mechanical properties (viscoelastic behavior). Control algorithms govern the fluid to near-solid conversion, which controls the behavior of the damper, and the performance of the structure under the seismic or wind loading event. The successful optimization of control parameters minimize the overall structural response to dynamic forces. The main objective of this research is to change the output behavior of specific floors within a building subjected to seismic excitation by optimizing the MR-dampers control parameters to impact the behavior of a specific floor or number of floors within the building. The adjustment of control parameters to attain this objective was validated in multiple case studies throughout this research. The successful implementation of the research outcome will result in optimized MR-damper design to meet the performance-based criteria of building projects.

The integrity of the genome is crucial for the survival of all living organisms. However, genomes need to adapt to survive certain pressures and for this propose use several mechanisms to diversify. Chromosomal instability (CIN) is one of the main mechanism leading to the creation of genomic heterogeneity by altering the number of chromosomes as well as changing their structures. In this review we will discuss the different chromosomal patterns and changes observed in speciation, in evolutional biology as well as during tumor progression. By nature, human genome shows induction of diversity during gametogenesis but as well during tumorigenesis that can conclude in drastic changes such as whole genome doubling to more discrete changes as indels as well as the recent discovered complex chromosomal rearrangement chromothripsis. More importantly, changes observed during speciation are strikingly similar to the genomic evolution observed during tumor progression and resistance to therapy. The different origins of CIN will be treated as the importance of double strand breaks (DSB) or the consequences of micronuclei. We will also explain the mechanisms behind the controlled DSBs and recombination of homologous chromosomes observed during meiosis, to explain how errors lead to similar pattern observed during tumorigenesis. Then, we will also list several diseases associated to CIN resulting in fertility issue, miscarriage, genetic rare diseases and cancer. Understanding better chromosomal instability as a whole is primordial for the understanding of mechanisms leading to tumor progression.

The present paper investigates the 'soft' determinants of social environmental sustainability of the country. A three-dimensional research approach, covering the education system and educational culture; socio-economic integration; and the legal system and the importance of public administration and citizenship, was utilized. A cross-sectional survey of 1,021 respondents and a structural equation modelling were selected as main research tools. Lithuania served as an empirical basis for the research. It was revealed that the most important factors in shaping the modernisation of the country through the lens of social environmental sustainability are the participation of citizens in social communities and social activities. Factors that need improvement are public participation and tolerance for the disabled.

Smart cities will undoubtedly be the distinguishing characteristic of human geography in the twenty-first century. Throughout 1.3 million people move to cities every week around the world, and it is estimated that by 2040, cities will house 65 percent of the world's population. While the world's largest cities now contribute for 60% of global GDP, this percentage will continue to climb as cities get larger and smarter. According to experts, cities will account for up to 80% of future economic development in developing regions. Smart cities are no longer the wave of the future; they have here and are rapidly expanding as the Internet of Things (IoT) grows. With dozens of towns throughout the world, the smart city sector is expected to grow into a massive business as time goes on. Cities have been an increasingly crucial engine of the global economy and wealth over time. As a result, it is critical to guarantee that they are optimized to maximize efficiency and sustainability while also ensuring that each citizen's quality of life is improved. We can describe the need for smart cities through this project, and it also shows us how IoT technology and smart city enablers may be deployed in urban settings to help cities perform better for their residents and achieve overall sustainable growth. This initiative will educate urban planners, researchers, ICT professionals, and other city officials about the facilitators of IoT for smart cities and their long-term growth.

Poor households are more likely less resilient under climate change, risks of productive assets, social-related shocks, and decline of land productivity. The ability to deal with household resilience against poverty under the uncertain condition of risk is limited in the highlands of Ethiopia. The study aims to identify determinants of household resilience to livelihood insecurity under the crop-livestock mixed farming systems in Goncha district, Northwest highlands of Ethiopia. Primary data were collected by conducting face-to-face interviews among 280 households using structured questionnaire. Descriptive statistics, Kruskal-Wallis test and structural equation modeling were used to analyse the data. The results disclosed that sustainable management of the farming systems, cultivation of more fertile farmland, saving performance, diversification of income-earning activities, intensification of livestock husbandry practices, access to irrigation, and familiarity with practical technologies were found to be significant determinants at p<0.001 to household resilience of smallholder farmers. Social network development and tree plantation were explained household resilience to livelihood insecurity at P<0.01 and P<0.1 significant levels, respectively. The study concluded that scaling up sustainable management of the farming system and practical technologies, enhancing saving behavior, promoting income diversification, and intensifying agroforestry are significant for household resilience to livelihood insecurity of smallholders across agro-ecologies.

Ag+ pollution is great of harm to the human body and the biology. Therefore, it is an urgent need to develop inexpensive and accurate detection methods. Herein, lignin-derived structural memory carbon nanodots (CSM-dots) with outstanding fluorescence property were fabricated via a green method, which reserve functional and structural units of the precursor molecules. The CSM-dots could specifically bind Ag+, accompanied with a remarkable fluorescence quenching response. This “turn-off” fluorescence behavior was used for Ag+ determination in a linear range of 5-290 μM with the detection limit as low as 500 nM. Furthermore, the finding showed that this sensing nano-platform was successfully used for Ag+ determination in real samples and intracellular imaging, showing great potential in biological and environmental monitoring applications.

Complex systems can be described as the network of interactions between their components. In directed networks, information, energy and matter flow in dominant directions. Undirected networks, on the other hand, cannot easily capture these asymmetries. The local flow of information depends on the node spin, which is a function of the number of incoming and outgoing links attached to it. And yet, how the heterogeneous association between in-degree and out-degree constraints global dynamics remains poorly understood. Here, we develop a new theoretical model to study the relationship between node directionality and global flow dynamics. Our computational analysis of random and scale-free directed networks indicates that structural diversity constrains the dimensionality of reachable dynamical space. These results suggest how local directionality might be an universal driver of global dynamics in many systems, from social networks, to technological systems to the connectome.

Nowadays, customers play a very important and vital role in the field of global economy. As a result, companies give special significance to the customers to survive and grow in the field of economic competition in the modern world and increase their relationship with the buyers of their products and services throughout their lifetime. Marketing growth through mobile phones has provided further motives for performing more researches in the field of customer behavior and attitude in mobile marketing. The goal of the current study is to analyze the effective factors on customer behavior in mobile marketing. The variables used in this study are perceived ease of use, individual knowledge, user’s mobile phone technology, customers’ negative attitudes, and customers’ positive attitudes. The current research is practical in terms of objective and is descriptive-analytic in terms of methodology. Data were gathered by distributing a questionnaire among 284 students of Tehran University. Data were analyzed by structural equation modeling using Lisrel and Expert Choice software. Test results showed that ease of use, individual knowledge, mobile phone technology, positive attitude, and negative attitude variables have a meaningful effect on customer behavior in mobile marketing. The confirmation of all the assumptions of the research supports the importance of the customer behavior analysis in mobile phone services.

Hepatitis C Virus (HCV) is the main causative factor for liver cirrhosis and the development of liver cancer, with a confirmed ~ 180 million infections worldwide. E2 is an HCV structural protein responsible for virus entry to the host cell. Heat Shock Protein A5 (HSPA5), also termed BiP and GRP78, is the master regulator of the unfolded protein response mechanism, where it mainly localizes in the lumen of the Endoplasmic Reticulum (ER) in normal conditions. Under the stress of HCV infection or carcinogenesis, HSPA5 is upregulated. Consequently, HSPA5 escapes the ER retention localization and translocates to the cytoplasm and plasma membrane. Pep42, a cyclic peptide that was reported to target explicitly cell-surface HSPA5 in vivo. Owing to the high sequence and structural conservation between the C554-C566 region of HCV E2 and the Pep42, then we propose that the HCV E2 C554-C566 region could be the recognition site. The motivation of this work is to predict the possible binding mode between HCV E2 and HSPA5 by implementing molecular docking to test such proposed binding. Docking results reveal the high potent binding of the HCV E2 C554-C566 region to HSPA5 substrate-binding domain β (SBDβ). Moreover, the full-length HCV E2 also exhibits high binding potency to HSPA5 SBDβ. Defining the binding mode between HCV E2 and HSPA5 is of significance, so one can interfere with such binding and reducing the viral infection.

Coronavirus disease 2019 (COVID-19) was recently appeared all over the world. The viral main protease (3-chymotrypsin-like cysteine enzyme) controls COVID-19 duplication and manages its life cycle, making it a drug discovery target. Therefore, herein, we analyzed the theoretical approaches of 10 structurally different hydrolysable tannins as natural anti-COVID-19 through binding with the main protease of 2019-nCoV using molecular docking modelling via Molecular Operating Environment (MOE v2009) software. Our results revealed that there are top three hits may serve as potential anti-COVID-19 lead molecules for further optimization and drug development to control COVID-19. Pedunculagin, tercatain, and punicalin were found to faithfully interact with the receptor binding site and catalytic dyad (Cys145 and His41) of COVID-19 main protease, showing their successfully inhibit the protease enzyme of 2019-nCoV. We anticipated that this study would pave way for tannins based novel small molecules as more efficacious and selective anti-COVID-19 therapeutic compounds.

Retinoid X receptor (RXR) antagonists are not only useful as chemical tools for biological research, but also are candidate drugs for treatment of various diseases, including diabetes and allergy, although no RXR antagonist has yet been approved for clinical use. In this review, we describe currently available RXR antagonists, their structural classification, and their evaluation, focusing on the latest research.

Studies on the structure of economic systems are, most frequently, carried out by the methods of informational statistics. These methods, often accompanied by a wide range of indicators (Shannon entropy, Balassa coefficient, Herfindahl specialty index, Gini coefficient, Theil index etc.) around which a wide literature has been created over time, have a major disadvantage. Such weakness is related to the imposition of the system condition, therefore the need to know all the components of the system (as absolute values or as weights). This restriction is difficult to accomplish in some situations, and in others, this knowledge may be irrelevant, especially when there is an interest in structural changes only in some of the components of the economic system (either we refer to the typology of economic activities - NACE or of territorial units – NUTS). This article presents a procedure for characterizing the structure of a system and for comparing its evolution over time, in the case of incomplete information, thus eliminating the restriction existent in the classical methods. The proposed methodological alternative uses a parametric distribution, with subunit values for the variable. The application refers to Gross Domestic Product values for five of the 28 European Union countries, with annual values of over 1,000 billion Euros (Germany, Spain, France, Italy and United Kingdom) for the years 2003 and 2015. A form of the Wald sequential test is applied to measure changes in the structure of this group of countries, between the years compared. The results of this application validate the proposed method.

Identification of costs drivers and their influence level on building development costs play a key role in the development of construction models and improve the efficiency and effectiveness of any project. Forty-five indicators influencing building development costs in New Zealand are explored by literature review and pilot interviews. These indicators are grouped into seven categories. The determination and ranking of the cost drivers are carried out by a questionnaire survey distributed to key professionals working in New Zealand’s construction industry. Structural equation modeling (SEM) software was employed for analysis of the collected data. One of the key advantages of this powerful software is to provide the p-value according to the structure of the research model. Findings of this study indicate that the property market and construction industry factor, statutory and regulatory factor, and socio-economic factor are major factors affecting building development costs in New Zealand.

Fluctuations of protein three-dimensional structures and large-scale conformational transitions are crucial for the biological function of proteins and their complexes. Experimental studies of such phenomena remain very challenging and therefore molecular modeling can be a good alternative or a valuable supporting tool for the investigation of large molecular systems and long-time events. In this mini-review, we present two alternative approaches to the coarse-grained (CG) modeling of dynamic properties of protein systems. We discuss two CG representations of polypeptide chains used for Monte Carlo dynamics simulations of protein local dynamics and conformational transitions and, on other hand, highly simplified structure-based Elastic Network Models of protein flexibility. In contrast to classical Molecular Dynamics the modeling strategies discussed here allow quite accurate modeling of much larger systems and longer time dynamic phenomena. We briefly describe the main features of these models and outline some of their applications, including modeling of near-native structure fluctuations, sampling of large regions of the protein conformational space, or possible support for the structure prediction of large proteins and their complexes.

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.

Construction and demolition waste (CDW) represents 1/3 of the weight of all-waste produced. Increasing their recycling and reutilization with recycled aggregates (RA) means closing the life cycle of construction materials. Research has been carried out on artificial aggregates from the exclusive crushing of structural concrete waste in selective demolitions (CDWRConc). This study analyses the use of recycled concrete as graded aggregate (GARConc) and in cement soil (CSRConc). The material complies with the requirements as a road base, although due to the low values of resistance to fragmentation these materials are adequate for use in sensitive road systems and other places such as urban roads and car parks. The sensitive road systems are infrastructures in places of great natural wealth and low traffic intensity, with an annual average of heavy vehicle traffic (AADTh) below 50 vhp/d. As soluble salt contents have been detected, additional waterproofing or drainage measures must be adopted to prevent water infiltration into the layers made up of CDWRHorm. Finally, the high initial values of UCS allow the temporary passage of light vehicles over CSRConc after 3 days.

Objective: This study aims to investigate the relationship between sports psychological capital, coach leadership behavior, and satisfaction among middle school students in the 2023 sports college entrance examination in Chongqing. Methods: Using the structural questionnaire design, this paper carries out a questionnaire survey on the candidates who come to participate in the volleyball specialty college entrance examination in Chongqing, the corresponding database was established and the data were statistically processed by spss21.0 and amos18.0. Results: 1) there was a significant positive correlation between sports psychological capital, coach leadership behavior and examinees satisfaction; 2) sports psychological capital and coach leadership behavior had a certain influence on five dimensions of examinees' personal treatment, personal performance, team integration, team interaction and support from relatives and friends; 3) The sense of self-efficacy in sports psychological capital and coach's leading behavior are the most important to examinees' satisfaction; 4) Both coaches' leadership behavior and sports psychological capital can directly affect examinees' satisfaction, but sports psychological capital is the most important. It can not only directly affect examinees' satisfaction, but also act as an intermediary between coaches' leadership behavior and examinees' satisfaction. Conclusion: Sports College Entrance Examination Students can improve training satisfaction and sports performance by strengthening sports psychological capital training and perceiving coach's leadership behavior; In the leadership behavior of coaches, we should emphasize training and appropriately weaken authoritative teaching, while the training of sense of hope and toughness should be highlighted in sports psychological capital.

The impact of propeller effects and power contribution on the aerodynamics of small aircraft is indispensable. The aerodynamic analysis of wings in flight varies from rigid wing analysis due to wing deflection caused by transferred aerodynamic loads. This paper investigates the intertwined influence of propeller effects and elasticity on the aerodynamics of small propeller-driven aircraft. Through a detailed methodology, a twin-engine propeller-driven aircraft is analyzed as a case study, providing insights into the proposed approach. Two critical analyses are presented: an examination of propeller effects in rigid aircraft and the incorporation of elastic wing properties. The former establishes a foundational understanding of aerodynamic behaviour, while the latter explores the impact of wing elasticity on performance. Validation is achieved through comparative analysis with wind tunnel test results from a similar rigid structure aircraft. Utilizing NASTRAN software, aerodynamic analysis of the elastic aircraft is conducted, complemented by semi-empirical insights. The results highlight the importance of these factors across different angles of attack. Furthermore, deviations from the rigid aircraft configuration emphasize the considerable influence of static aeroelasticity analysis, notably increasing longitudinal characteristics by approximately 20%, while showing a lower impact of 5% in lateral-directional characteristics. This study contributes to enhanced design and operational considerations for small propeller-driven aircraft, with implications for future research and innovation, particularly for the purpose of efficient concepts in advanced air mobility.

Elastic properties of materials and their changes with temperature are important for their applications in engineering. A study on the influence of phase composition of AISI 4130 alloy on Young's modulus (Ed), shear modulus (Gd), and damping (Q-1) was carried out by Impulse Excitation Technique (IET). The material characterization was carried out using confocal microscopy, XRD, MET, HV, and dilatometry. A stable structure, composed of ferrite (BCC) and pearlite (α-Fe+Fe3C), was obtained by annealing. Metastable structure of martensite (BCT) was obtained by quenching. The Ed, Gd, and Q-1 were measured, varying the temperature from RT to 900 °C. The values of Ed and Gd, at RT, were determined as 201.5 and 79.2 GPa (annealed), and 190.13 and 76.5 GPa (quenched), respectively. In the annealed steel, the values Ed and Gd decrease linearly on heating up to 650 °C, with the thermal expansion. In the quenched steel, weak changes in the dilatometric curve, Ed, Gd, and Q-1, in the range of 350-450 °C, indicated decompositions of the martensitic phase. Sharp decrease in the moduli and high peak of Q-1, was observed for both samples around 650-900 °C, revealing low lattice elastic stability of the phases during transformations α(BCC)+Fe3C↔γ(FCC).

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.

Based on the plate tectonic theory, using seismic, geology, and public literature data, the proto-type basins and lithofacies paleogeography during the main geological periods of the passive continental margin of East Africa are restored, and the architecture characteristics of the basins and the differences in sedimentary fillings are analyzed. Combined with the dissection of discovered oil and gas reservoirs, four types of hydrocarbon accumulation models are established, the favorable hydrocarbon accumulation combinations (plays), and the next exploration directions in this region are explored. The passive continental margin basins in East Africa experienced three proto-type stages: intracontinental aborted rift during the Late Carboniferous-Triassic Karoo period, intracontinental-intercontinental rift during the Jurassic period, and passive continental margin basin since the Cretaceous period. Affected by the difference in sedimentary filling thickness between the rift period and depression period, four types of passive continental margin basins are formed: rifted type, depressed type, faulted depression type, and reformed delta type. The maximum sedimentary thickness of the rifted basins during the rift period is greater than 3500 m, and that during the depression period is less than 4000 m, forming a "single-source structure type" hydrocarbon accumulation model. The exploration of rifted basins should focus on giant structural traps at the top of the rifted sequences. The maximum sedimentary thickness of the depressed basins during the depression period exceeds 4000 m, forming a "single-source fan group type" hydrocarbon accumulation model. The dominant exploration directions of depressed basins are sedimentary sand bodies and structural-lithologic traps during the depression and drift periods. The maximum sedimentary thickness of the faulted depression basins during the rift period is greater than 3500 m, and that during the depression period is greater than 4000 m, forming a "double-source and double-combination type" hydrocarbon accumulation model. The exploration of rifted basins should focus on giant slip-collapse-debris flow sedimentary sand bodies on the upper and middle slopes. In addition to the large sedimentary thickness of the early rift and the central depression, the delta thickness of the reformed delta basins during the late depression period since the Miocene is more than 4000 m, and four structural belts (growth fault, mud diapir, thrust fold, and foredeep gentle slope) were formed from onshore to offshore, forming a "three-source and multi-combination type" hydrocarbon accumulation model. All four structural belts can form giant oil and gas fields.

A framework for optimal sensor placement (OSP) for virtual sensing using the modal expansion technique and taking into account uncertainties is presented based on information and utility theory. The OSP maximizes a utility function that quantifies the expected information gained from the data for reducing the uncertainty of quantities of interest (QoI) predicted at the virtual sensing locations. The utility function is extended to make the OSP design robust to uncertainties in structural model and modelling error parameters, resulting in a multidimensional integral of the expected information gain over all possible values of the uncertain parameters and weighted by their assigned probability distributions. Approximate methods are used to compute the multidimensional integral and solve the optimization problem that arises. The Gaussian nature of the response QoI is exploited to derive useful and informative analytical expressions for the utility function. A thorough study of the effect of model, prediction and measurement errors and their uncertainties, as well as the prior uncertainties in the modal coordinates on the selection of the optimal sensor configuration is presented, highlighting the importance of accounting for robustness to errors and other uncertainties.

Background: The infant mortality rate (IMR) is an important reflection of the well-being of infants and the overall health of the population. This study aims to examine the macroeconomic (ME), sociodemographic (SD), and health status and resources (HSR) effects on IMR, as well as how they may interact with each other. Methods: A retrospective time-series study using yearly data for Oman from 1980 to 2022. Partial Least Squares-Structural Equation Modelling (PLS-SEM) was utilized to develop the exploratory model of the determinants of IMR. Results: The model indicates that HSR determinants directly but negatively affect IMR (= -0.617, p&lt;0.001). SD directly and positively affects IMR (= 0.447, p&lt;0.001). ME only indirectly affects IMR (=-0.854, p&lt;0.001). ME determinants also exert some direct influences on both HSR (= 0.722, p&lt;0.001) and SD (= -0.916, p&lt;0.001) determinants. Conclusions: These findings indicate that an integrated policy that addresses socioeconomic and health-related factors and the overall ME environment is necessary for the health and well-being of the children and the population overall in Oman.

In this study various samples were fabricated by increasing the amount of CNT from 0% to 5%. The bulk mechanical properties of the samples were measured using DMA. Alternatively, the local mechanical properties were assessed using nanoindentation technique. There is a clear trend that the behavior of the material is dependent of carbon fillers before, during and after percolation threshold. The bulk mechanical properties were reduced after the percolation threshold due to CNT agglomeration. Then the samples were exposed to acid solution for one week and one month. Regardless the amount of CNT in the matrix, there is always a gradient of properties from the skin to the core of the sample. There is a net reduction of in physical properties. However, the level of degradation was a dependent of the amount of CNT in the host polymer. At higher concentration the CNTs behave as a barrier. However due to the formation of porosity around the CNT agglomerates, the acid diffusion encounters preferential path ways. . Both techniques lead to the same observation..

The role of human resource management practices and organizational loyalty dealing with employee retention has been widely explored and examined in the existing literature. The majority of human resource management researchers have focused on the role of policies and practices in different sectors related to employee retention. However, less attention has been given to identifying the practices and procedures common across all industries and sectors. The present study attempts to determine and examine the most important constructs like HR practices and organizational loyalty of employee retention management and proposes a comprehensive structural equation model to measure the impact of these constructs on employee retention. After an extensive review of the literature, organizational loyalty, and human resources management practices like recruitment and selection, compensation and benefit, training and development, supervision and evaluation have been identified as four essential practices dealing with employee retention and are common across all industries. These practices constitute the component factors of an employee retention management predicting employee’s turnover intentions. The survey method was adopted, and the original data obtained through the self-administered questionnaire. The valid one hundred and eighty-nine (189) respondents analyzed by using Lisrel 8.7, Structural equation model (SEM) analysis results shows that human resource management practices and organizational loyalty have strong positive impact on employee retention. This study tends to assist human resource managers and decision makers in selecting the appropriate motivating factors to retain and satisfy their employees

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.

Despite marked advancements, life expectancy (LE) growth in Saudi Arabia and the United Arab Emirates (UAE) has remained stagnant compared to other developed nations. This study aims to investigate the significant correlation between macroeconomic (ME), sociodemographic (SD), and health status-resources (HSR) factors and LE to formulate an explanatory model for Saudi Arabia and the UAE – a previously unexplored area. Utilizing an ecological, retrospective, time-series study design, we delved into secondary data on SD, ME, HSR, and LE of the UAE population spanning three decades (1980-2020). We employed the partial least squares-structural equation modeling for statistical analysis. Our analysis revealed significant direct impacts of HSR on LE for Saudi Arabia (Beta=0.958, p<0.001) and the UAE (Beta=0.716, p<0.001). Furthermore, we discerned a notable indirect influence of ME on LE, mediated through SD and HSR for Saudi Arabia (Beta=0.507, p<0.001) and UAE (Beta=0.509, p<0.001), along with a considerable indirect effect of SD on LE through HSR (Saudi Arabia: Beta=0.529, p<0.001; UAE: Beta=0.711, p<0.001). This study underscores the mediating role of a nexus of ME-SD-HSR factors on LE in Saudi Arabia and the UAE. Consequently, these findings signal an imperative need for holistically policy interventions addressing ME, SD, and HSR factors, aiming to alter health behaviors and improve LE projections for Saudi Arabia and the UAE in the long run.

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.

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.

Transition metal alloys have emerged as promising electrocatalysts due to their ability to modulate key parameters such as d-band electron filling, Fermi level energy, and interatomic spacing, thereby influencing their affinity towards reaction intermediates. However, the structural stability of alloy electrocatalysts during alkaline hydrogen evolution reaction (HER) remains a subject of debate. In this study, we systematically investigate the structural evolution and catalytic activity of the c-Co/Co3Mo electrocatalyst under alkaline HER conditions. We reveal that the instability of the Co3Mo alloy and H0.9MoO3 during alkaline HER leads to the destruction of the crystal structure, resulting in the formation of hexagonal cobalt (h-Co) from hexagonal Co(OH)2 as an intermediate species. Furthermore, we explore the re-adsorption and surface coordination of the Mo element, which enhances the catalytic activity for alkaline HER. This work provides valuable insights into the dynamic behavior of alloy-based electrocatalysts, shedding light on their structural stability and catalytic activity during electrochemical reduction processes

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.

Floating Offshore Wind Turbine (FOWT) is an innovative technology with little industry guidance for its hull design. Various FOWT floaters with different hull shapes claim to support the same turbines. Structural integrity and material expense analyses of different pontoon shapes were conducted, and it was found that some configurations, such as those with every two columns connected by both pontoon and bracing, have advantages over others. However, it is important to note that the choice of pontoon shape should be based on the wave loading conditions the floater will be exposed to. While a T-shaped pontoon provides a cost-effective solution under certain wave loading scenarios, it may not be the best option for all conditions. Specifically, ring pontoon designs with full bracing were found to be necessary for withstanding certain wave loads. Therefore, it is important to consider different Dominant Load Parameters (DLP) and ensure that a FOWT floater can withstand all applicable DLPs. An uneven hexahedral column shape, which combines the best attributes of square and round shapes, is proposed as a better alternative to cylindrical columns. It offers ease of manufacture and reasonably low drag. Bracing is found to be necessary for withstanding the wind turbine’s incurred moment and forces. The conclusion is that platform design should prioritize manufacturing costs and strength over maximizing hydrodynamic performance.

Research into lightweight structural concrete using volcanic tuff is of great importance to the construction industry. These materials have excellent thermal insulation properties, which helps improve the energy efficiency of buildings. A three-factor experimental design was used to build the statistical model. The test methods used were methods for determining the crushability of volcanic tuff, determining the average density, compressive strength and thermal conductivity of lightweight structural concrete. The influence of basalt fiber on the properties of lightweight structural concrete has been determined. The optimal compositions of lightweight structural concrete using tuff have been selected. The compressive strength of lightweight structural concrete reached 32.0 MPa. The average density range is 1754.6-2114.0 kg/m³. Good thermal conductivity values ​​were obtained in the range of 0.653-0.818 W/m·K. The article obtained the optimal compositions of lightweight structural concrete using volcanic tuff as a filler.

The field of construction materials is pivotal in developing sustainable and resilient infrastructure. This demands continuous research to understand the properties and behaviors of these materials under diverse conditions. Although advancements in material science and numerical modeling have been significant, experimental testing remains indispensable for a thorough comprehension of material characteristics, particularly under extreme stresses and environmental factors. This need has forced the development of a wide array of testing techniques, each designed to evaluate specific engineering properties, thus creating a complex and varied landscape of experimental methodologies. This study provides a comprehensive overview of both conventional and innovative experimental testing techniques used to characterize construction materials. It explores the related methodologies and identifies potential gaps in their application within the industry. The spectrum of testing covered includes mechanical, chemical, thermal, microstructural, durability, physical, rheological properties, and non-destructive testing methods. Mechanical tests assess strength, hardness, and fatigue, whereas chemical analyses utilize techniques such as spectroscopy and chromatography. Thermal properties are examined using thermogravimetric analysis, and microstructural characteristics are explored through advanced imaging techniques. Durability testing focuses on materials’ resistance to environmental challenges, while physical properties tests evaluate aspects like porosity and water absorption. Rheological and non-destructive tests further examine materials’ behavior and integrity without causing damage. By discussing these methodologies, the study sheds light on various approaches to material evaluation and aims to enhance the selection, application, and development of testing standards. This overview seeks to inform and inspire future research and innovation in the science of construction materials, contributing to the development of more resilient and sustainable construction practices.

Due to the complex and variable anatomy of the left atrial appendage, percutaneous left atrial appendage closure (LAAC) can be challenging. In this study, we investigated the impact of fusion imaging (FI) on the LAAC learning curve of 2 interventionalists. The first interventionalist (IC 1) was initially trained without FI and continued his training with FI. The second interventionalist (IC 2) performed all procedures with FI. We compared the first 36 procedures without FI of IC 1 (group 1) with his next 36 interventions with FI (group 2). Furthermore, group 1 was compared to 36 procedures of IC 2 who directly started his training with FI (group 3). Group 1 demonstrated that the learning curve without FI has a flat course with weak correlations for fluoroscopy time, contrast volume, and procedure time, but not for dose area product. Group 2 with FI showed improvement with a steep course and strong correlations for all 4 parameters. In group 3 we also saw a steep progression with strong correlations. Furthermore, the mean measurements of the procedural parameters in the groups with FI decreased significantly as indicator for procedural efficacy. We demonstrated that FI may improve the learning curve of experienced and non-experienced ICs.

Despite a growing concern over sustainability in tourism, research on this domain regarding, specifically, lake destinations, is still scarce. Although perceptions on lake destinations have been studied, no study is known that analyses the impact of visitors’ perceptions on satisfaction and behavioral intentions. Thus, this paper aims to develop and test a model to analyse the effect of lake visitors’ perceptions of destination’s sustainability on both satisfaction and loyalty towards lake destinations. A questionnaire survey was conducted in the Shchuchinsk-Burabay resort area, an important lake destination in northern Kazakhstan. The results support the proposed lake destination loyalty model, tested using partial least squares structural equation modelling (PLS-SEM). Sustainability proved to be decisively influential, with water quality being the dimension with the highest impact on satisfaction with the lakes, along with a positive key impact of the absence of congestion. In addition, both water quality and lack of congestion had a significant indirect impact on satisfaction with the lake destination, and on loyalty. Based on the research findings, theoretical conclusions and practical implications are drawn.

Smart flexible materials with piezoresistive property are increasingly used in sensors field. When embedded in structures, they would allow an in-situ structural health monitoring and damage assessment of impact loading such as crash, bird strikes and ballistic impacts. However, this could not be achieved without a deep characterization of the relation between piezoresistivity and mechanical behavior. The aim of this paper is to study the potential use of the piezoresistivity effect of a conductive foam made of a flexible polyurethane matrix filled with active carbon for integrated Structural Health Monitoring (SHM) and damage assessment applications. To do so, PolyUrethane Foam filled with Active Carbon, namely PUF-AC, are manufactured and tested under quasi-static compression tests and under Dynamic Mechanical Analyser (DMA) with in-situ measurement of its resistivity during tests. A relation is proposed for describing the evolution of the resistivity versus strain and stress. In addition, a demonstrative experiment of a PUF-AC sample subjected to low velocity impact assesses the interest of this type of materials for damage assessments.

The easternmost Mediterranean is a distinct transition zone from the ocean to the continent located at the junction between the largest Earth's lithospheric segments: Eurasian and African. The methodology of paleomagnetic mapping of such transition zones is based on integrating the mapping techniques for both continental and oceanic platforms: paleomagnetic reconstructions, results of radiometric dating of magnetized rocks, tectonic-structural reconstructions, biogeography, and utilization of the results of various geophysical surveys. The geodynamic-paleomagnetic mapping makes it possible to reveal the multilevel structural heterogeneity and display complex elements of the geodynamics of different ages inherent in this transition zone. Northern Israel is obviously the most complex area in the easternmost Mediterranean. For the combined paleomagnetic mapping, well-studied paleomagnetically and radiometrically areas were selected: (1) the Carmel area, (2) the Atlit area (internal part of the Carmel area), (3) the Sea of Galilee with the adjoining zones (primarily, the Kinnarot Valley), and (4) the area of the Hula Basin with adjacent areas of the Golan Plateau, Hermon Mt., and Galilea uplift. The constructed paleomagnetic profiles for the Carmel area (on the top of the accumulative surface of the Lower Cretaceous traps), and the Kinnarot Valley – Sea of Galilee – Hula Basin, evidently indicate the complex history of the paleogeodynamic evolution of the region. These studies demonstrate the effectiveness of paleomagnetic mapping integrated with paleomagnetic profiling, crossing these geologically complex areas.

Fusarium circinatum is an important global pathogen of pine trees. Genome plasticity has been observed in different isolates of the fungus, but no genome comparisons are available. To address this gap, we sequenced and assembled to chromosome level five isolates of F. circinatum. These genomes were analysed together with previously published genomes of F. circinatum isolates FSP34 and KS17. Multi-sample variant calling identified a total of 461683 micro variants (SNPs and small indels) and a total of 1828 macro structural variants of which 1717 were copy number variants and 111 were inversions. Variant density was higher on sub-telomeric regions of chromosomes. Variant annotation revealed that genes involved in transcription, transport, metabolism and transmembrane proteins were overrepresented in gene sets affected by high impact variants. A core genome representing genomic elements conserved in all the isolates and a non-redundant pangenome representing all genomic elements is presented. Whole genome alignments showed that an average of 93% of the genomic elements are present in all isolates. The results of this study reveal that some genomic elements are not conserved within the isolates and some variants are high impact. The described genome-scale variations will help inform novel disease management strategies against the pathogen.

In this paper we describe the potentialities of a tool for the visualization of experimental results directly on a three-dimensional model. The case study concerns the visualization of the results of a dynamic finite element analysis (FEA/FEM) applied to the calculation of seismic risk on works belonging to the Italian infrastructural heritage, specifically bridges, viaducts and overpasses. The project is based on finite element analysis performed on an exemplary set of 8 structures located on the Italian territory, performed by means of the open-source software framework OpenSees, according to the guidelines indicated in the Technical Standards for Construction NTC08. The application created for this project is classifiable as a webGIS, since all data are georeferenced and visualized on a map through an application executed through a browser. The graphical interface displays the interested works on the map of the Italian territory and allows to select them by mouse click. Following the selection, a 3D rendering of the model of the work and the surrounding terrain is shown, in which the results of the analysis are represented using color gradients directly on the three-dimensional model. The necessary tools are present for the selection of the type of result and for the animation in real time of the response of the work to the seismic action. The 3D representation is freely navigable by the user thanks to intuitive tools of panning, rotation and zoom through mouse and keyboard. The application takes advantage of HTML5, CSS and Javascript to show graphical features such as Cartesian diagrams of accelerograms used in modal analysis.

Rotational microwave jet spectroscopy studies of the monoterpenol α-fenchol have so far failed to identify its second expected torsional conformer, despite computational predictions that it is only very slightly higher in energy than the most stable conformer. Vibrational FTIR and Raman jet spectroscopy investigations reveal unusually complex OH and OD stretching spectra compared to other alcohols. Via modelling of the torsional states, observed spectral splittings are explained by delocalization of the hydroxy hydrogen atom through quantum tunneling between the two non-equivalent but accidentally near-degenerate conformers separated by a low and narrow barrier. The energy differences between the torsional states are determined to be only 16(1) and 7(1) cm$^{−1}hc$ for the protiated and deuterated alcohol, respectively, which further shrink to 9(1) and 3(1) cm$^{−1}hc$ upon OH or OD stretch excitation. Comparisons are made with the more strongly asymmetric monoterpenols borneol and isopinocampheol as well as with the symmetric, rapidly tunneling propargyl alcohol. Assigned are also for α-fenchol the third – in contrast localized – torsional conformer and the most stable dimer, as well as for propargyl alcohol the two most stable dimers.

The civil construction industry is one of the sectors that most consume natural resources in the world and, consequently, one of that generate more waste. Thinking about constructive techniques that generate less impact on the environment is vital to ensure sustainable development. In this scenario, the Life Cycle Assessment (LCA) has been presented as an internationally recognized approach, that assesses the potential impact of products and services on human health and the environment, throughout its entire life cycle. Aimed to identify construction techniques and vertical closing systems that generate less impact and consumption of natural resources, the impacts generated by the life cycle of the three vertical closing systems most applied in construction sites in Brazil were compared: ceramic brick masonry system (CBr); concrete block masonry system (CBk); and structural blocks masonry system (SBk). The SBk proved to be the least impacting to the “Resource Scarcity”, “Damage to Human Health”, and “Damage to the diversity of Ecosystems” interesting areas. This performance is directly related to the use of cement CPIII type and also by the fact that the SBk consumes less concrete and mortar than the others. Already the "Water Consumption" area, the CBk was the least impacting due to the lower consumption of electricity during its life cycle. The reliability of the results was proven through a sensitivity analysis of the normalization and characterization factors, which consisted of comparing the results obtained by applying two different methodologies. It is believed that the LCA study carried out can assist in the decision-making process regarding the choice of the most sustainable construction method.

The change in the value of the breaking energy is discussed here for selected steel grades used in building structures after subjecting the samples made of them to episodes of heating in the steady-state heating regime and then cooling in a simulated fire conditions. These changes were recorded based on the instrumented Charpy impact tests, in relation to the material initial state. The S355J2+N, 1H18N9T steels and also X2CrNiMoN22-5-3 duplex steel were selected for detailed analysis. The fire conditions were modelled experimentally by heating the samples and then keeping them for a specified time at a constant temperature of: 600°C (first series) and 800°C (second series), respectively. Two alternative cooling variants were investigated in the experiment: slow cooling of the samples in the furnace, simulating the natural fire progress, without any external extinguishing action, and cooling them in water mist simulating an extinguishing action by a fire brigade. The temperature of the tested samples was set at the level -20oC and alternatively at the level + 20oC. The conducted analysis is aimed at assessing the risk of sudden, catastrophic fracture of load-bearing structure made of steel degraded as a result of a fire previously occurred with different development scenarios.

Recently, with the rapid advancement of the 4th Industrial Revolution, there has been a continuous outlook that Data (D), Network (N), and Artificial Intelligence (A) should be heavily utilized as resources in light of new value. South Korea is preparing policy training plans the likes of 5G network enhancement, AI manpower training, and data openings, etc., recognizing DNA technology as the key driving force behind the 4th Industrial Revolution and 5G network enhancement, AI manpower training, and data opening, etc. However, there is a criticism that the DNA industry remains in an early stage. Despite policy support within South Korea, the DNA industry has not been revitalized due to various causes, and in particular, not being concentrated on limited resources selectively is also pointed to as an important cause. this study would quantitatively draw the priority of policy measures as well as propose policy implications for the revitalization of the DNA industry by means of the ISM-ANP model. It is judged that South Korea’s experience in this way will be an important lesson for other countries which would politically promote the DNA industry as a new growth engine within the 4th Industrial Revolution environment.

When different strain hardening and strain rate sensitive materials are used for scaled model and prototype, the traditional pure geometrical similarity laws of solid mechanics will fail. Although correcting the basic scaling factors of velocity, density and geometry have been developed to compensate for the material distortion in recent non-geometric scaling works, it is difficult to be widely used because of its inherent indirect (depending on the structural strain and strain rate responses) and inexact (having significant prediction errors for prototype) defects. In this paper, a framework of material similarity, based on the new suggested material dimensionless numbers and the ‘Material number vs. strain/strain-rate’ function curves, are further developed, which represents the objective requirement of similarity theory for the basic mechanical properties of materials. It is demonstrated what is similitude materials of solid mechanics and how to use the best similitude materials to overcome the non-scalabilities of materials for identical or different materials. The direct and exact solution of the basic correction factors is further obtained and therefore overcomes the previous inherent indirect and inexact defects radically. Based on the similarity evaluation of different materials of the classical constitutive models, the impacted structures of circular plate and crooked plate with strain hardening and strain rate sensitive materials are verified numerically. The results show the completely different materials can be exact similitude for various structural behaviors (strain, strain rate, stress and displacement) of time and space fields after using the best similitude materials; and the basic correction factors do not depend on the structural strain and strain rate responses. As a contrast, when the non-similitude materials are used, the similarity results are very sensitive to the selection of strain/strain-rate and often leads to failed predictions. In addition, for the material elastic and temperature effects, the proposed method is also discussed to be valid.

The evolution of divaricate plants in New Zealand has been the subject of long-running debate among botanists and ecologists. Hypotheses about this remarkable case of convergent evolution have focused mainly on two different types of selective pressures: the Plio-Pleistocene advent of cool, dry climates, or browsing by now-extinct moa. Here, we review the scientific literature relating to the New Zealand divaricates, and present a list of 81 taxa whose architectures fall on the divaricate habit spectrum. We recommend a series of standardised terms to facilitate clear communication about these species. We identify potentially informative areas of research yet to be explored, such as the genetics underlying the establishment and control of this habit. We also review work about similar plants overseas, proposing a list of 47 such species as a first step towards more comprehensive inventories; these may motivate further studies of the ecology, morphology and evolutionary history of these overseas plants which could help shed light on the evolution of their New Zealand counterparts. Finally, we compile published divergence dates between divaricate species and their non-divaricate relatives, which suggest that the divaricate habit is fairly recent (< 10 My) in most cases.

This paper investigates whether optimisation methods with the population made up of one solution can suffer from structural bias just like their multisolution variants. Following recent results highlighting the importance of choice of strategy for handling solutions generated outside the domain, a selection of single solution methods are considered in conjunction with several such strategies. Obtained results are tested for the presence of structural bias by means of a traditional approach from literature and a newly proposed here statistical approach. These two tests are demonstrated to be not fully consistent. All tested methods are found to be structurally biased with at least one of the tested strategies. Confirming results for multisolution methods, it is such strategy that is shown to control the emergence of structural bias in single solution methods. Some of the tested methods exhibit a kind of structural bias that has not been observed before.

Flour yield determined the profitability of flour mill, but the intrinsic variability of the grain makes it very complex to analysis and estimate wheat grain flour yield. Simulation for flour yield attributes offer considerable advantages in flour mill, if reliable predictions of flour yield can be provided, because the wheat grain characteristics can be tested before milling. If this is possible, the characteristics thus observed could be quantified more reliably and objectively by Structural Equation Modelling (SEM). SEM was used to look for the most important wheat grain characteristics on flour yield, and then these wheat grain characteristics were used to simulate flour yield. Furthermore, the regressive equation was verified by the field experiment. The coefficient of variation of grain characteristics was low and distributed rather closely. The results of SEM showed that test weight had the most significantly effects on flour yield, followed by the hardness index. Test weight and hardness index could excellently estimate flour yield by multiplicative effect of test weight and hardness index, and which could determine 68% of the variation in flour yield. The simulation result can not only predict flour yield, but also look for the important grain characteristics for the flour yield.

Various sudden shifts in financial market conditions over the past decades have demonstrated the significant impact of market structural breaks on firms' credit behavior. To characterize such effect quantitatively, we develop a continuous-time modulated Markov model for firms' credit rating transitions with the possibility of market structural breaks. The model takes a semi-parametric multiplicative regression form, in which the effects of firms' observable covariates and macroeconomic variables are represented parametrically and nonparametrically, respectively, and the frailty effects of unobserved firm-specific and market-wide variables are incorporated via the integration form of the model assumption. We further develop a mixtured-estimating-equation approach to make inference on the effect of market variations, baseline intensities of all firms' credit rating transitions, and rating transition intensities for each individual firm. We then use the developed model and inference procedure to analyze the monthly credit rating of U.S. firms from January 1986 to December 2012, and study the effect of market structural breaks on firms' credit rating transitions.

Cross-laminated timber (CLT) possesses both good shape stability and the possible two-way force transfer ability due to its crosswise lamination. However, the transverse layers in CLT are prone to rolling shear failure under an out-of-plane load. An innovative multi-layer composite laminated panel (CLP) was developed by combining structural composite lumber (SCL) and dimension lumber to overcome the rolling shear failure while maintaining high mechanical performance and aesthetic appearance of natural wood. The mechanical properties of 5-layer CLP consisted of laminated strand lumber (LSL) and dimension lumber with different layups were evaluated by both static and modal tests. The results showed that the shear resistance, bending stiffness and moment resistance of CLP were up to 143%, 43% and 87% higher than their counterparts of regular CLT, respectively. The failure modes observed in both shear and bending tests indicated that the use of LSL in transverse layers could eliminate the potential rolling shear failure in CLT. With the lamination properties from components tests as inputs, the validity of shear analogy method was assessed by test results. The mechanical properties can be well predicted by shear analogy method except for the bending moment resistance of CLP and CLT with either rolling failure in the cross layer or tension failure in the bottom layer.

Water inrush from coal floor constitutes one of the main disasters in mine construction and mine production, which always brings high risks and losses to the coal mine safe production. As the mining depth of coal fields in North China gradually increased, especially in the complicated structural region, the threat posed by limestone karstic water of coal floor to the safe stoping of mines has become increasingly prominent. In this paper, the Taoyuan coalmine was taken as an example, for which, the directional borehole grouting technology was utilized to reinforce the coal seam floor prior to mining. Also, the factors affecting the grouting effect were analyzed. These were the geological structure, the crustal stress and the range of slurry diffusion. The layout principle of grouting drilling was put forward and the directional drilling structure was designed. The water level observations in the end hole indicated that the target stratum was accurate and reliable. The effect of grouting was validated through the audio frequency electric perspective method and the holedrilling in the track trough. The results demonstrated that the effect of grouting in third limestone and the rock stratum above the third limestone of coal seam floor was apparent. Simultaneously, no water inrush occurred following the actual mining of the working face, which further demonstrated that the grouting reinforcement effect was apparent. The research findings were of high significance for the prevention and control of floor water disaster and water conservation in deep complex structural areas.

Ostreococcus tauri is a simple unicellular green alga representing an ecologically important group of phytoplankton in oceans worldwide. Modern molecular techniques must be developed in order to understand the mechanisms that permit adaptation of microalgae to their environment. We present for the first time in O. tauri a detailed characterization of individual genomic integration events of foreign DNA of plasmid origin after PEG-mediated transformation. Vector integration appears to be random, occurring mainly at a single locus, and thus confirming the utility of this technique for insertional mutagenesis. While the mechanism of double-stranded DNA repair in the O. tauri model remains to be elucidated, we clearly demonstrate by genome resequencing that the integration of the vector leads to frequent structural variations (deletions/insertions and duplications) and some chromosomal rearrangements in the genome at the insertion loci, and often within the vector sequence itself. From these observations, we speculate that a non-homologous end joining-like mechanism is required during random insertion events, as described in plants and other freshwater algal models. PEG-mediated transformation is therefore a promising molecular biology tool, not only for functional genomic studies, but also for biotechnological research in ecologically important marine algae.

Due to advances in power electronics technology and the evolution of automation devices, the number of electrical devices that are sensitive to power quality is rapidly increasing, and for this reason, users are increasing their demand for high quality. To meet power quality demands, many power conversion devices are used, including dynamic voltage restorers (DVRs). DVRs are rec-ognized as devices that can effectively manage problems such as voltage segment, swells, and harmonics. DVR control requires many samples for harmonic compensation, which has the dis-advantage of being complicated to implement due to fast digital signal processing computation and the application of the cyclic discrete Fourier transform. In this paper, a high-precision DVR system configuration is proposed that compensates for harmonics using a periodically equivalent time-interval sampling technique and a novel circular structured memory filter. The proposed circular structured multi-pointer memory filter is an effective filter algorithm for high-precision input voltage measurement because it can remove noise and compensate for the delay of the phase angle of the filter in voltage measurement. A simulation and DVR prototype system was built, and the feasibility and effectiveness of the phase angle multi-filter voltage detection method and the compensation method were verified by experiments.

Rotavirus species H (RVH) has been detected in pigs, humans and bats. Moreover, porcine RVHs have been recently identified in several swine-producing countries. Despite their zoonotic impact, genome information of RVHs is still limited. This study aimed to establish a tentative complete genome-based genotyping system for RVHs, by appending genomic sequences from 12 porcine RVHs identified in Japan between 2013 and 2015 to those from human and other porcine RVHs reported in previous studies. Phylogenetic analysis of 11 RNA segments indicated that porcine RVHs could be classified into multiple genotypes. Consequently, the genotype classification for RVHs revealed the existence of genotypes 10G, 6P, 6I, 3R, 4C, 7M, 6A, 2N, 4T, 6E, 3H for the genes VP7, VP4, VP6, VP1, VP2, VP3, NSP1, NSP2, NSP3, NSP4 and NSP5, respectively. Surprisingly, two distinctive types in NSP1 and NSP3 genes were identified from among the twelve porcine RVHs. Our data suggest a potentially novel gene rearrangement event between porcine RVH and rotavirus species C in the NSP3 gene. These findings would provide a new insight in understanding for evolution of RV.

Background. In the last decade, it was concluded that glaucomatous optic neuropathy is part of the neurodegenerative diseases in which destructive neuronal lesions are located not only in the structure of the retina, but they are also present at the level of the central visual and nervous pathways. Patients with Primitive Open Angle Glaucoma may have experienced changes such as sensorineural hearing loss as well as balance changes. The purpose of this study is to evaluate the degree of involvement of the auditory system in patients with glaucoma, the structural changes in the optic nerve and, to establish correlation between the hearing loss and structural changes in the optic nerve. The subjects included in the study are grouped as follows: a group of patients with glaucoma that will be compared to a group of patients without glaucoma only as well as identi-fy-ing the evolution of structural changes in optic nerve to patients with glaucoma and to normal patients. Material and methods. It is a prospective, cross-sectional study on 32 eyes of 16 subjects with Primitive Open Angle Glaucoma in a study group and 24 eyes of 12 healthy subjects in con-trol group with a mean age of 62 years in both groups. Both groups underwent ophthalmo-logical, audiological and radio imaging evaluation: Pure-tone audiometry (PTA) were recorded, oph-thalmologic evaluations according to a standardized protocol and MRI cerebral examination was performed. Results: In the Study group patients, compared to the Control group, the average lev-els of the left PTA, the cup/disc (C/D) area in both eyes, the C/D ratio in both eyes are in-creased. The mean level of Retinal nerve fiber layer (RNFL) mean thickness was slightly lower in patients with glaucoma. Multivariate analysis demonstrates that gender can be a good predictor of C/D area, gender and age can be good predictors of PTA both eyes and C/D ratio in the right eye, and gender, age and background can be good predictors of disc area in the left eye. Conclu-sions: Pa-tients with Primitive Open Angle Glaucoma show changes in audiometry test in correla-tion with ophthalmological parameters demonstrating that the auditory system can be affected in Primitive Open Angle Glaucoma. This study emphasizes the problem of interdisciplinarity in medicine with the aim of ensuring the quality of life of patients with glaucoma. A good collabora-tion between ophthalmologist and otolaryngologist will be very useful for these patients.

Currently the majority of studies on vision-based measurement has been conducted under ideal environments so that an adequate measurement performance and accuracy is ensured. However, vision-based systems may face some adverse influencing factors such as illumination change and fog interference, which can affect the measurement accuracy. This paper develops a robust vision-based displacement measurement method which can handle the two common and important adverse factors given above and achieve sensitivity at the subpixel level. The proposed method leverages the advantage of high-resolution imaging incorporating spatial and temporal context aspects. To validate the feasibility, stability and robustness of the proposed method, a series of experiments was conducted on a two-span three-lane bridge in the laboratory. The illumination change and fog interference are simulated experimentally in the laboratory. The results of the proposed method are compared to conventional displacement sensor data and current vision-based method results. It is demonstrated that the proposed method gives better measurement results than the current ones under illumination change and fog interference.

The behaviour of steel frame buildings under progressive collapse conditions depends on a combination of several parameters including the interplay between different collapse resistance mechanisms mobilized in different structural components. Previous studies have shown that the extent to which these mechanisms may contribute to progressive collapse resistance depends on the ability of the beam-column connections to undergo large inelastic deformations prior to reaching their deformation capacity limits. For this reason, and due to the important role of their flexural strength and tying capacity in the development of essential collapse resistance mechanisms, the response of beam-column connections is one of the most important features of progressive collapse performance. Based on the knowledge gained through previous studies on the mechanics of the problem, the role of the connections is critically reviewed by examining the results of several experimental studies conducted during the past decade. The factors that may adversely affect progressive collapse resistance – such as failure modes of certain connection types – are evaluated, and novel approaches of limiting these factors which are currently under development are reviewed. The assessment of these parameters leads to useful conclusions of practical significance, while highlighting the aspects of the problem that need further study and understanding.

This study addresses the latent construct of attitudes towards environmental conservation based on study participant’s responses. We measured and evaluated the latent scale based on an 18-item scale instrument, over four experimental strata (N=945) in the US Virgin Islands and the Caribbean. We estimated the latent scale reliability and validity. We further fitted multiple alternative two-parameter logistic (2PL) and graded response models (GRM) from Item-Response Theory. We finally constructed and fitted equivalent structural and generalized structural equation models (SEM/GSEM) for the attitudinal latent scale. All scale measures (composite, alpha-based, IRT-based and SEM-based) were consistently and reliably valid measures of the study participants’ latent attitudes toward conservation. We found statistically significant differences among participant’s attributes relating to socio-demographic, physical and core environmental characteristics of participants. We assert that the nature of relationship between cognitive attitudes and individual as well as social behavior related to environmental conservation.

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.

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.

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.

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.

With demand for the long-term continued use of existing building facilities, structural health monitoring and damage detection are attracting interest from society. Sensors of various types have been practically applied in the industry to satisfy this need. Among the sensors, piezoelectric sensors are an extremely promising technology by virtue of their cost advantages and durability. Although they have been used in aerospace and civil engineering, their application for building engineering remains limited. Remarkably, recent catastrophic seismic events have further rein-forced the necessity of rapid damage detection and quick judgment about the safe use of facilities. Faced with these circumstances, this study was conducted to assess the applicability of piezoelectric sensors to evaluate building components. Specifically, this study emphasizes structural damage caused by earthquakes. After first applying to cyclic loading tests to composite beam component specimens and steel frame subassemblies with a folded roof plate, the prospective damage posi-tions were also found using finite element analysis. Crack propagation and buckling locations were predicted adequately. The piezoelectric sensors provided output when the concrete slab showed tensile cracks, or when the folded roof plate experienced local buckling. Furthermore, damage expansion and progression were detected multiple times during loading tests. Results showed that the piezoelectric sensors can detect structural damage of building components, demonstrating their potential for use in inexpensive and stable monitoring systems.

Shear deflection effects are traditionally neglected in most structural system identification methods. Unfortunately, this assumption might lead to significant errors in some structures, like deep beams. Although some inverse analysis methods based on the stiffness matrix method including shear deformation effects have been presented in the literature, none of these methods is able to deal with actual rotations in their formulations. Recently, the observability techniques, one of the first methods for the inverse analysis of structures included the shear effects into the system of equations. In this approach, the effects of shear rotation are neglected. When actual rotations on site are used to estimate the mechanical properties in the inverse analysis, it can result in serious errors in the observed properties. This characteristic might be especially problematic in structures such as deep beams where only rotations can be measured. To solve this problem and increase the observability techniques' applicability, this paper proposes a new approach to include shear rotations into the inverse analysis by observability techniques. This modification is based on the introduction of a new iterative process. To illustrate the applicability and potential of the proposed method, the inverse analysis of several examples of growing complexity is presented.

Gastric cancer (GC) is a highly heterogeneous, complex disease and the fifth most common cancer worldwide (about one million cases and 784 000 deaths worldwide in 2018). CG is lately diagnosed and guarantees a poor prognosis for GC (the 5-year survival rate is less than 20%, but in early detection can reach 90%). This study evaluated the transcriptional profile in tumor gastric samples to find genes highly expressed during tumor establishment and use the related proteins as targets to find new anticancer molecules. Data was collected at Gene Expression Omnibus (GEO) bank to obtain 3 dataset matrices that analyze gastric tumor tissue versus normal gastric tissue, performed microarray using GPL570 platform, and from different sources. The genes found in silico analysis were confirmed in several lines of GC cells by RT-qPCR. The protein data bank was used to find the correspondent proteins. Then a structural-based virtual screening was done to find molecules, and docking analysis was done using the DockThor server. Our results of transcriptomic analysis, together with RT-qPCR, confirm the high expression of the genes AJUBA, FBXL13, CCDC69, CD80 and NOLC1 in GC lines. Based on that, the correspondent proteins were used in SBVS analysis. Five molecules, one each target, MCULE-2386589557-0-6, MCULE-7343047040-0-1, MCULE-5230409338-0-3, MCULE-9178344200-0-1 and MCULE -5881513100-0-29. All molecules have favorable pharmacokinetic, pharmacodynamic and toxicological properties. Molecular docking analysis revealed that the molecules interact with proteins in critical sites for their activity. Using a virtual screening approach, a molecular docking study was performed for proteins encoded by genes that play important roles in cellular functions for carcinogenesis. Combining a systematic collection of public microarray data with a comparative meta-profiling, RT-qPCR, SBVS, and molecular docking analysis provided a suitable approach to find genes involved in GC and work the correspondent protein to strive for new molecules with anticancer properties.

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,

Knowledge processing is an important feature of intelligence in general and artificial intelligence in particular. To develop computing systems working with knowledge, it is necessary to elaborate means of working with knowledge representations (as opposed to data) because knowledge is an abstract structure. There are different forms of knowledge representations derived from data. One of the basic forms is called a schema. The goal of this paper is the development of theoretical and practical tools for processing schemas. To achieve this goal, we use schema representations elaborated in the mathematical theory of schemas and use structural machine as a powerful theoretical tool for modeling parallel and concurrent computational processes. We describe the schema of autopoietic machines as physical realizations of structural machines. An autopoietic Machine is a technical system capable of regenerating, reproducing and maintaining itself by production, transformation and destruction of its components and the networks of processes downstream contained in them. We present the theory and practice of designing and implementing autopoietic machines as information processing structures integrating both symbolic computing and neural networks. Autopoietic machines use knowledge structures containing the behavioral evolution of the system and its interactions with the environment to maintain stability by counteracting fluctuations.

In the field of stochastic optimisation, the so-called structural bias constitutes an undesired behaviour of an algorithm that is unable to explore the search space to a uniform extent. In this paper, we investigate whether algorithms from a subclass of estimation of distribution algorithms, the compact algorithms, exhibit structural bias. Our approach, justified in our earlier publications, is based on conducting experiments on a test function whose values are uniformly distributed in its domain. For the experiment, 81 combinations of compact algorithms and strategies of dealing with infeasible solutions have been selected as test cases. We have applied two approaches for determining the presence and severity of structural bias, namely a visual and a statistical (Anderson-Darling) tests. Our results suggest that compact algorithms are more immune to structural bias than their counterparts maintaining explicit populations. Both tests indicate that strong structural bias is found only in one of the algorithms (cBFO) regardless of the choice of strategy of dealing with infeasible solutions and cPSO mirror. For other test cases, statistical and visual tests disagree on some cases classified as having mild or strong structural bias: the former one tends to make harsher decisions, thus needing further investigation.

PD-1/PD-L1 axis is one key therapeutic target against tumor cell immune escape. Structurally essential to the PD-1/PD-L1-linked immune escape is the binding interface of the PD-1/PD-L1 complex structure. Incorporating currently available PD-1/PD-L1-related experimental structures, this article unveils two sets of experimentally observed inter-molecular electrostatic interactions which stabilize the binding interface of the PD-1/PD-L1 complex structure. For the first time, this article proposes an evolutionary structural hypothesis that, as a result of natural selection, PD-1 is able to genetically mutate itself to structurally disrupt the PD-1/PD-L1 axis towards the restoration of T cell-mediated anti-tumor immunity.

In this paper, we investigate a new subclass of univalent functions defined by a generalized differential operator, and obtain some interesting properties of functions belonging to the class R^m λµ ( α, β, γ, υ ).

Fibre-reinforced composite structures under complex loads exhibit gradual damage behaviour with a degradation of effective mechanical properties and change of their structural dynamic behaviour. Damage manifests itself as spatial increase of inter-fibre failure and delamination-growth, resulting in local changes of stiffness. These changes affect not only the residual strengths but more importantly the structural dynamic behaviour. In case of composite rotors, this can lead to catastrophic failure if an eigenfrequency coincides with the rotational speed. The description and analysis of the gradual damage behaviour of composite rotors therefore provides the fundamentals for a better understanding of unpredicted structural phenomena. The gradual damage behaviour on the example of composite rotors and the resulting damage-dependent dynamic behaviour is experimentally investigated under propagating damage for combined out-of-plane and in-plane loads. A novel observation is reported, where monotonic increase of damage results in non-monotonic frequency shift of significant amount of eigenfrequencies.

By reinterpreting the calibration of structural models, a reassessment of the importance of the input variables is undertaken. The analysis shows that volatility is the key parameter to any calibration exercise by several orders of magnitude. In order to maximize the sensitivity to volatility, a simple formulation of Merton’s model is proposed that employs deep out-of-the-money option implied volatilities. The methodology also eliminates the use of historic data to specify the default barrier thereby leading to a full risk neutral calibration. Subsequently, a new technique for identifying and hedging capital structure arbitrage opportunities is illustrated. The approach seeks to hedge the volatility risk, or vega, as opposed to the exposure from the underlying equity itself, or delta. The results question the efficacy of the common arbitrage strategy of only executing the delta hedge.

The availability of new self-sensing cement-based strain sensors allows the development of dense sensor networks for Structural Health Monitoring (SHM) of reinforced concrete structures. These sensors are fabricated by doping cement-matrix materials with conductive fillers, such as Multi Walled Carbon Nanotubes (MWCNTs), and can be embedded into structural elements made of reinforced concrete prior to casting. The strain sensing principle is based on the multifunctional composites outputting a measurable change in their electrical properties when subjected to a deformation. Previous work by the authors was devoted to material fabrication, modeling and applications in SHM. In this paper, we investigate the behavior of several sensors fabricated with and without aggregates and with different MWCNTs content. The strain sensitivity of the sensors, in terms of fractional change in electrical resistivity for unit strain, as well as their linearity are investigated through experimental testing under both static and dynamically varying compressive loadings. Moreover, the responses of the sensors when subjected to destructive compressive tests are evaluated. Overall, the presented results contribute to improving the scientific knowledge on the behavior of smart concrete sensors and to furthering their understanding for SHM applications.

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.

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.

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.

This work investigates the use of Non-destructive tests as a tool for monitoring the structural performance of concrete structures. The investigation encompassed four phases; the first of which involved the use of destructive and non-destructive mechanisms to assess concrete strength on cube specimens. The second phase research focused on site assessment for a twin engineering theatre located at the Faculty of Engineering, University of Lagos using rebound hammer and ultrasonic pulse velocity tester. The third phase was the use of linear regression analysis model with MATLAB to establish a relationship between calibrated strength as well as ultrasonic pulse velocities with their corresponding compressive strength values on cubes and values obtained from existing structures. Results show that the root-mean squared-R² values for rebound hammer ranged between 0.275 and 0.742 while ultrasonic pulse velocity R² values were in the range of 0.649 and 0.952 for air curing and water curing systems respectively. It initially appeared that the Ultrasonic pulse velocity was more suitable for predicting concrete strength than rebound hammer but further investigations showed that the latter was adequate for early age concrete while the former was more suited for aging concrete. Hence, a combined use is recommended in this work.

The aim of this work was to determine if the development of low-cost or no-cost finite element analysis (FEA) software has advanced to the point where it can be used in place of trusted commercial FEA packages for linear static structural analyses using isotropic material models. Nonlinear structural analysis will be covered in a separate paper. Several suitable packages were identified, these underwent a process of systematic elimination when they were unable to meet the minimum imposed qualitative criteria. Three packages were chosen to be subjected to performance benchmarking, namely: Code_Aster/Salome Meca; Mecway and Z88 Aurora. SimScale, a browser-based analysis package was included as well because it met all the baseline criteria and has the potential to offer a completely cloud-based approach to computer aided engineering, potentially reshaping the way an engineering business views its operational capabilities. This paper presents the test cases and simulation results for packages that fall under the linear static structural analysis type.

In order to investigate the relationship between government policy, the service and design of rural crowdsourcing spaces, the self-efficacy of returning youth, and the innovation performance of businesses, this study focuses on gathering data by distributing questionnaires to returning youth in rural crowdsourcing spaces and developing a structural model. The results demonstrate how important government policies are in encouraging youth entrepreneurship in their local communities. It has the potential to enhance both the development of rural crowdsourcing spaces and the self-efficacy of young entrepreneurs, thereby enhancing the innovative capabilities of local entrepreneurial businesses. Therefore, in order to encourage economic development in rural areas, the government should improve pertinent support measures.

In an era characterized by technological disruption and unprecedented challenges posed by the COVID-19 pandemic, this scholarly investigation explores the role of Artificial Intelligence (AI) in shaping Leadership Dynamics in Higher Education Institutions (LDHE) within the specific socio-cultural and regulatory environment of China. Utilizing Structural Equation Modeling (SEM) as operationalized through the SMART_PLS software, this research harnessed data from a robust sample of 381 key stakeholders in China higher education. The study's empirical findings indicate a noteworthy impact of AI-informed decision-making processes on LDHE, which was further mediated by the variable of AI Literacy among leadership. Moreover, the consequences of the ongoing pandemic served as a moderating factor in this relationship. These nuanced outcomes not only contribute to the theoretical discourse surrounding educational leadership and technological integration but also provide actionable insights for policy formulation and institutional strategies in an increasingly complex educational landscape.

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.

Bis-benzimidazole derivative (BBM) molecule, consisting of two 2-(2’-Hydroxyphenyl) benzim-idazole (HBI) halves, has been synthesized and successfully utilized as a ratiometric fluorescence sensor for the sensitive detection of Cu2+ based on enol-keto excited state intramolecular proton transfer (ESIPT). In this study, we strategically implement femtosecond stimulated Raman spec-troscopy and several time-resolved electronic spectroscopies, aided by quantum chemical calcula-tions to investigate the detailed primary photodynamics of BBM molecule. The results demonstrate that the ESIPT from BBM-enol* to BBM-keto* was observed in only one of HBI halves with a time constant of 300 fs, after that, the rotation of the dihedral angle between two HBI halves generate a planarized BBM-keto* isomer in 3 ps, leading to dynamics red shift of BBM-keto* emission.

The aim of this study is to investigate and determine the key factors guiding customer attitudes towards social media influencers, and on that base to explore their effects on purchase intentions towards advertised products or services. A total of 376 fulfilled questionnaires from an online survey were analysed. The main characteristics of digital influencers’ behaviour, affecting consumer perceptions have been systematized and categorized through a combination of both traditional and advanced data analysis methods. Structural Equation Modelling (SEM), machine learning and multi-criteria decision-making (MCDM) methods were selected to uncover the hidden dependencies between variables from the perspective of social media users. The developed models elucidate the underlying relationships that shape the acceptance mechanism of influencers’ messages. The results obtained provide specific recommendations for stakeholders across the social media marketing value chain. Marketers can make informed decisions and optimize influencer marketing strategies to enhance user experience and increase conversion rates. Working collaboratively, marketers and influencers can create impactful and successful marketing campaigns that resonate with the target audience and drive meaningful results. Customers benefit from more tailored and engaging influencer content that aligns with their interests and preferences, fostering a stronger connection with brands and potentially affecting their purchase decisions. As the perception of customer satisfaction is individual and evolving process, stakeholders should organize regular evaluations of influencer marketing data and explore the possibilities to ensure continuous improvement of this e-marketing channel.

The composition of fine-ground lead zirconate-titanate powder Pb(Zr_0.52Ti_0.48)O₃, suspended in PZT and bismuth titanate (BiT) solutions, is deposited on the curved surface of IN718 and IN738 nickel-based supper alloy substrates up to 100 µm thickness. Photochemical metal organic and infiltration techniques are implemented to produce smooth, semi-dense, and crack-free random orientated thick piezoelectric films as piezo-sensors, free of any dopants or thickening polymers. Every single layer of the deposited films is heated at 200 °C with 10 wt.% excess PbO, irradiated by UV lamp (365 nm, 6 watt) for 10 minutes, pyrolyzed at 400 °C, and subsequently annealed at 700 °C for one hour. This process is repeated successively until reaching the desired thickness. Au and Pt thin films are deposited as the bottom and top electrodes using evaporation and sputtering methods, respectively. PZT/PZT and PZT/BiT composite films are then characterized and compared to similar PZT and BiT thick films deposited on the similar substrates. The effect of composition and deposition process is also investigated on the crystalline phase development and microstructure morphology as well as dielectric, ferroelectric and piezoelectric properties of piezo-films. The maximum remnant polarization of P_r = 22.37 ± 0.01, 30.01 ± 0.01 µC/cm², the permittivity of ε_r = 298 ± 3, 566 ± 5 and piezoelectric charge coefficient of d₃₃ = 126, 148 m/V were measured versus the minimum coercive field of E_c = 50, 20 kV/cm for the PZT/PZT and PZT/Bit thick films, respectively. The thick film piezo-sensors are developed to be potentially used at frequency bandwidth of 1–5 MHz for rotary structural health monitoring and also in other industrial or medical applications as a transceiver.

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.

Drug-target binding is an essential parameter in drug discovery and design to ensure drug efficacy and specificity. In 2022, the concept of a general intermolecular binding affinity calculator (GIBAC) was for the first time coined: $Kd = f(molecules, envPara)$. Technically, GIBAC represents a set of in silico approaches for structural and biophysical data generation towards a paradigm shift in precise drug discovery and design, providing a comprehensive framework for intermolecular binding affinity calculation with adequate accuracy, precision and efficiency. For the first time, this study reports a prototype of GIBAC (semaGIBAC), i.e., a one-dimensional semaglutide-GLP-1R-based mini static GIBAC, based on an experimental complex structure of semaglutide and GLP-1R. Semaglutide is a potent GLP-1 receptor agonist used to treat type 2 diabetes mellitus by regulating blood glucose levels and promoting weight loss. In 2021, a structural modification involving a Val27-Arg28 exchange was manually introduced to enhance semaglutide-GLP-1R binding affinity. This study employs a comprehensive structural and biophysical analysis aimed at thoroughly exploring the sequence space of semaglutide-GLP-1R to design analogues with improved binding affinity, leading to the identification of a promising semaglutide analogue, which binds to GLP-1R with an affinity that is more than two orders of magnitude (113.3 times) higher than native semaglutide. To sum up, this article puts forward a promising structural biophysical approach for developing GLP-1 receptor agonists with enhanced efficacy, and with a GIBAC prototype (semaGIBAC), this article argues again that the time is now ripe for the construction of a real GIBAC to be listed on the agenda of the drug discovery and design community.

Heat waves represents a major concern for the tourism industry in the Mediterranean area. Therefore, it is necessary to deepen the study of the influence of high temperatures and their effects on tourist behavior. This research aims to develop a structural model that allows measuring how heat waves affect the behavior of external tourist demand in coastal destinations. The results are useful for the design by tourist destinations of adaptation measures to climate change. The proposed hypotheses have been contrasted using non-linear structural equations (SEM), estimated with data from the National Institute of Statistics on external demand in Spain. The results confirm lower tourist flows with the increase in high temperatures to the coasts of the Spanish Mediterranean area from traditional source markets, such as the United Kingdom. Furthermore, the tourist flow to the Balearic Islands decreases with high temperatures.

To date the role of green leaf volatiles has been mainly constrained to their role in protecting plants against pests and pathogens. However, increasing evidence suggests that among the stresses that can significantly harms plants, GLV can also provide significant protection against an array of those including heat, cold, drought, light, and salinity. But while the molecular basis for this protection is still largely unknown, it seems obvious that a common theme in the way GLV work is that most if not all of these stresses are associated with physical damage to the plants, which in turn is the major event responsible for the production of GLV. Here, I summarize the current state of knowledge on GLV and abiotic stresses and provide a model that explains the multifunctionality of these compounds.

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 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.

Findings primarily drawn from literature review and interviews with professional resource persons suggest that although the RMG industry of Bangladesh has made substantial progress in correcting structural risks within factory buildings, fire still remains an unresolved issue posing unceasing threat to safety. These findings are significant for all stakeholders within the global supply chain network of Bangladesh, concerned with improving sustainability of the RMG industry and seeking to outline the responsibilities for each group of actors towards preventing building disasters. Both Tazreen Fashion fire incident and the Rana Plaza building collapse served as ‘critical junctures’ in rapid transfer of physical technology to enhance structural safety and streamline production planning within the RMG manufacturing factories within Bangladesh. However, the transfer of social technology within the supply chain network of a developing nation in areas such as development of organisational safety culture or promoting workplace ethics, requires long-term planning and prolonged practices. The paper thus concludes that in developing countries, transfer of physical technology is more readily achievable than the adoption of social technology.

The concept of intellectual capital is increasingly recognized as one of the most important strategic assets of organizations. The significance of intellectual resources, which are now critical for every business unit, is underlined in this paper. Thus, this research aims to identify the effectiveness of intellectual capital and its components on the organizational innovation at Sulaimani Polytechnic University in Sulaymaniyah Governorate, from the point of view of the faculty members (academic and administrative staff). The study developed both theoretical and empirical sections. The descriptive approach was used to determine the effectiveness of intellectual capital and the quantities of research methodologies was used to measure this effectiveness. The study aims at investigating the correlations and causal effect between intellectual capital and organizational innovation. Moreover, the study investigates the correlations and causal effect between human capital, structural capital and relational capital on radical and incremental innovation in the organization. To achieve this, the 392 total sample were collected and analyzed by SPSS 22 software. The findings provide evidence that intellectual capital and its components have a positive and statistically significant effect on the organizational innovation and its components.