Operation Principle Research Articles

Molecular profiling of invertebrate glia.

Caenorhabditis elegans and Drosophila melanogaster are powerful experimental models for uncovering fundamental tenets of nervous system organization and function. Findings over the last two decades show that molecular and cellular features are broadly conserved between invertebrates and vertebrates, indicating that insights derived from invertebrate models can broadly inform our understanding of glial operating principles across diverse species. In recent years, these model systems have led to exciting discoveries in glial biology and mechanisms of glia-neuron interactions. Here, we summarize studies that have applied current state-of-the-art "-omics" techniques to C. elegans and D. melanogaster glia. Coupled with the remarkable acceleration in the pace of mechanistic studies of glia biology in recent years, these indicate that invertebrate glia also exhibit striking molecular complexity, specificity, and heterogeneity. We provide an overview of these studies and discuss their implications as well as emerging questions where C. elegans and D. melanogaster are well-poised to fill critical knowledge gaps in our understanding of glial biology.

Systems Thinking Principles for Making Change

Traditionally, systems thinking support has relied on an ever-increasing plethora of systems tools, methods, and approaches. Arguably though, such support requires something different from, and more accessible than, detailed instruction on somewhat abstract laws and detailed principles and/or constitutive rules associated with conventional systems approaches or systems ‘tools of the trade’. For busy managers and decision makers working in often-stressful conditions, what is perhaps more valued are simple principles for enabling systems thinking in practice. Such principles should acknowledge and build on existing (multi)disciplinary skill sets and expertise, allowing for more meaningful interdisciplinary support amongst professions, as part of a nested transdisciplinary support for addressing wider social challenges. This monograph offers three principles of systems thinking in practice (STiP): relational STiP, perspective STiP, and adaptive STiP. They each have two sets of operational principles applicable to first-order and second-order practice, respectively. The three general principles are nested in an overriding principle of STiP as praxis (theory-informed action or thinking in practice) manifest in the need for being both systemic and systematic. The three principles represent a distilled expression of a systematic literacy of systems thinking, a literacy that speaks to the systemic sensibilities of Inter-relationships, Perspectives, and Boundaries (sometimes referred collectively as IPB), associated with any area of intervention. Drawing on metaphors of bricolage, conversation, and performance, and building on philosophical foundations of boundary critique, the three principles provide for a requisite systems literacy (as an emergent property of systemic sensibilities and systems thinking literacy) for enabling appropriate STiP capabilities to flourish when making a meaningful change.

The fragile nature of concentration of effort principle and the instability of the 3:1 force ratio

The complexity of the contemporary operating environment necessitates a continuous adaptation of the operational process, which is made possible by constant doctrinal adjustments, including a re-evaluation of the principles of operations dimensions.In this context, the analysis of the new requirements regarding the integration of the principle of concentration of effort and the rules underlying the dimensioning of the force ratio in operations represents a subject of interest. This approach is also significant in the context of Romania’s military transformation, which is geared towards a qualitative shift in emphasis over the quantitative one. Consequently, the assessment of the prospective realization of the fundamental tenets of the aforementioned operations yields valuable insights that can be leveraged by military planners irrespective of the operational scale.

Development Directions of Fire-Fighting Equipment Using Aircraft Engines Abroad

In the last century, outstanding fire-fighting technology developments have occurred in Hungary. Mobile, quickly deployable, efficient, environmentally friendly tools and technologies with optimal fire extinguishing material use have come to the fore. This included equipment using exhaust gas from internal combustion engines and combustion products from aircraft engines for fire-fighting. The developers’ goal is to reduce environmental and secondary damage during fire-fighting, and at the same time, they sought to increase the efficiency of fire-fighting processes by using measurably less fire-fighting material. In our article, we present the foreign developments of fire-extinguishing equipment that uses aircraft engines with a unique operating principle and is suitable for applying multiple types of fire-extinguishing materials, thus also for implementing complex fire-fighting. We review the design and construction of the equipment, their operating principle, examine their practical application possibilities, and present directions for future development.

Design and implementation of a solar power optimizer for module level power electronics application

AbstractPartial shading on series‐connected photovoltaic (PV) panels in conventional PV systems results in lower harvested power. To resolve this, it is vital to utilize module level power electronics (MLPE) such as Solar Power Optimizers (SPOs). This paper introduced a non‐isolated common ground non‐inverting output voltage buck‐boost converter as an SPO. Proposed converter benefits from continuous input and output currents which has a significant role in designing SPOs. Having a quadratic gain, beside acceptable step‐down range are other features of the converter. Operating principle, design, steady‐state, small‐signal analysis, and dynamic performance of proposed converter are included. Proposed converter is compared with other buck‐boost converters in terms of voltage gain, voltage stresses, continuous input and output current, and output polarity. To validate the performance of introduced converter, experimental results for a prototype with input voltage 24 V, output voltage 72 V for step‐up and 15 V for step‐down modes are given and results are examined. The maximum efficiency of the prototype is 93% and 89% for step‐up and step‐down modes, respectively. To evaluate the effect of proposed SPO for extracting maximum available power from PVs, simulation results of a grid connected PV system with two series connected SPOs is discussed.

Two-Stage Multiple-Vector Model Predictive Control for Multiple-Phase Electric-Drive-Reconstructed Power Management for Solar-Powered Vehicles

Electric-drive-reconstructed onboard chargers (EDROCs), also known as electric-drive-reconstructed power management systems, are a promising alternative to conventional onboard chargers due to their characteristics of low cost and high power density. The model predictive control offers a fast dynamic response, simple implementation, and the ability to control multiple targets simultaneously. In this paper, a two-stage multi-vector model predictive current control (MPCC) of a six-phase EDROC for solar-powered electric vehicles (EVs) is proposed. Firstly, the topology for the EDROC incorporating a six-phase symmetrical permanent magnet synchronous machine (PMSM) is introduced, and the operation principles of the DC charge mode, the drive mode, and, especially, the in-motion charge mode are analyzed in detail. After that, a two-stage multi-vector MPCC method is proposed by using the multi-vector MPC technique and designing a two-stage MPC structure to eliminate the regulation of the weighting factor of the MPC. Finally, the effectiveness of the proposed method is verified on a self-designed 2 kW EDROC platform.

A Development and Evaluation of a Vertical Yam-Pounding Machine

A vertical yam pounding machine having a similar operational principle to the traditional method of pounding was developed. The machine consists of a shaft, pulleys, V-belts, bearings, an electric motor, a vertical pounder, a gear train and a pounding bowl. White yam was used to carry out a performance evaluation of the developed machine compared to a commercial yam pounder QASA® (LBQ041A, made in China) yam pounding machine and pounded yam from the traditional method of using mortar and pestle. It was observed that the traditional pounding operation, the developed and the QASA® yam pounding machines gave 89.73, 96.24 and 98.25% of well-pounded yam excluding lumps. However, the QASA® yam pounding machine is limited to a maximum of 4 kg mass of boiled yam. The average throughputs of the traditional pounding operation, the developed and the QASA® yam pounding machines were 20.3, 39.46 and 47.34 kg/h, while pounding times were 18 min, 10 min, and 5 min respectively. The developed machine had comparable quality with similar sensory scores with regards to the taste, aroma, stretchability, and mouldability to the one from the traditional method. It also had a comparative long-life span, and overall acceptability score and was preferred over the pounded yam produced by QASA® pounding machine.

Building a pelvic organ prolapse diagnostic model using vision transformer on multi-sequence MRI.

Although the uterus, bladder, and rectum are distinct organs, their muscular fasciae are often interconnected. Clinical experience suggests that they may share common risk factors and associations. When one organ experiences prolapse, it can potentially affect the neighboring organs. However, the current assessment of disease severity still relies on manual measurements, which can yield varying results depending on the physician, thereby leading to diagnostic inaccuracies. This study aims to develop a multilabel grading model based on deep learning to classify the degree of prolapse of three organs in the female pelvis using stress magnetic resonance imaging (MRI) and provide interpretable result analysis. We utilized sagittal MRI sequences taken at rest and during maximum Valsalva maneuver from 662 subjects. The training set included 464 subjects, the validation set included 98 subjects, and the test set included 100 subjects (training set n=464, validation set n=98, test set n=100). We designed a feature extraction module specifically for pelvic floor MRI using the vision transformer architecture and employed label masking training strategy and pre-training methods to enhance model convergence. The grading results were evaluated using Precision, Kappa, Recall, and Area Under the Curve (AUC). To validate the effectiveness of the model, the designed model was compared with classic grading methods. Finally, we provided interpretability charts illustrating the model's operational principles on the grading task. In terms of POP grading detection, the model achieved an average Precision, Kappa coefficient, Recall, and AUC of 0.86, 0.77, 0.76, and 0.86, respectively. Compared to existing studies, our model achieved the highest performance metrics. The average time taken to diagnose a patient was 0.38s. The proposed model achieved detection accuracy that is comparable to or even exceeds that of physicians, demonstrating the effectiveness of the vision transformer architecture and label masking training strategy for assisting in the grading of POP under static and maximum Valsalva conditions. This offers a promising option for computer-aided diagnosis and treatment planning of POP.

Social entrepreneurship: an innovative tool for solving social problems in Ukraine

It is indicated that in the modern world, where social and environmental problems are becoming increasingly acute, social entrepreneurship appears as an innovative and effective tool for solving them. This phenomenon is at the intersection of business and charity, combining an entrepreneurial approach with a social mission. This article explores the phenomenon of social entrepreneurship as an innovative tool for addressing social and environmental challenges in the modern world. It examines the relevance of developing social entrepreneurship in the context of the UN’s global sustainable development goals and in conditions of limited state resources to meet growing social needs. The author analyzes the historical roots of social entrepreneurship, tracing its evolution from the 17th century to the present day. Special attention is given to the «Triple Bottom Line» concept (profit, people, planet), which underlies social entrepreneurship, and the ideas of Nobel laureate M. Yunus regarding «social business». The article discusses the key characteristics of social entrepreneurship that distinguish it from traditional business, and the principles of social enterprise operation. The author identifies three main models of social entrepreneurship: inclusive, social reinvestment, and innovative social model. Particular attention is paid to the legal aspect of social entrepreneurship in Ukraine, specifically the absence of a special organizational and legal form for such activities and the opportunities provided by current legislation. The author emphasizes the role of social entrepreneurship in the development of the economy and civil society, particularly in job creation, overcoming social isolation, and promoting civic participation. The categories of population for whom social entrepreneurship is especially relevant are considered. The conclusions highlight the potential of social entrepreneurship as a tool for achieving sustainable development and building a more inclusive society, as well as the need for further research in this field, especially in the context of post-COVID reality and the state of war in Ukraine.

Ultrathin crystalline silicon-based omnidirectional strain gauges for implantable/wearable characterization of soft tissue biomechanics.

Monitoring soft-tissue biomechanics is of interest in biomedical research and clinical treatment of diseases. An important focus is biointegrated strain gauges that track time-dependent mechanics of targeted tissues with deforming surfaces over multidirections. Existing methods provide limited gauge factors, tailored for sensing within specific directions under quasi-static conditions. We present development and applicability of implantable/wearable strain gauges that integrate multiple ultrathin monocrystalline silicon-based sensors aligned with different directions, in stretchable formats for dynamically monitoring direction angle-sensitive strain. We experimentally and computationally establish operational principles, with theoretical systems that enable determination of intensities and direction of applied strains at an omnidirectional scale. Wearable evaluations range from cardiac pulse to intraocular pressure monitoring of eyeballs. The device can evaluate cardiac disorders of myocardial infarction and hypoxia of living rats and locate the pathological orientation associated with infarction, in designs with possibilities as biodegradable implants for stable operation. These findings create clinical significance of the devices for monitoring complex dynamic biomechanics.

Теоретические исследования процесса смешивания кормов центробежным смесителем

The article presents theoretical studies aimed at understanding the physical processes occurring in the production of compound feeds using a centrifugal cascade mixer, which open up new horizons in optimizing feed production technology. Special attention in these studies is paid to the analysis of the mixing process, which, as it turned out, is closely interrelated with the principles of operation of the dispenser. As a result of the analysis, it was found that the dispenser and mixer should be considered as a single system, regardless of the mixing mechanism used in the production process. This made it possible to develop a cascade mixer of feed materials of centrifugal type and continuous action, which is an innovative solution in the field of feed production. This mixer provides a homogeneous mixture of loose feed components and can be integrated into production lines for the preparation of both feed and combined mineral briquettes. The key advantage of the proposed mixer is the use of a centrifugal force field, which, unlike the gravity field, provides more efficient mixing. In this case, the process of preparing compound feeds can be represented as a sequence of three key stages: the metered supply of components, the introduction of one component into the composition of another, transportation (removal) of the finished product from the working area of the mixer. The research allowed us to obtain analytical dependences of the components of the centrifugal force on the angular velocity of the rotor and its radius. This allows you to optimize the operating parameters of the mixer to achieve maximum mixing efficiency. During the research, a mathematical model of the spatial motion of a particle in a mixer was developed. The model is presented in the form of Lagrange equations of the second kind, the generalized coordinates of which are the displacement of the particle along the cone and the polar angle of the particle position. This makes it possible to solve the optimization problems of centrifugal mixers according to a given objective function. Thanks to the conducted research, it was possible to develop an innovative mixer that provides a homogeneous mixture of components of loose compound feeds. The use of centrifugal forces in the mixer made it possible to increase the mixing efficiency and ensure that the final product meets the requirements of the formulation. The research results are of great practical importance and can be used to improve feed production technologies. Keywords: COMPOUND FEED, FEED MIXTURE, MIXER, DISPENSER, CENTRIFUGAL MIXER, PARTICLE MOTION IN THE MIXER

Research on Multi-Objective Optimization Methods of Urban Rail Train Automatic Driving Based on NSGA-II

In order to improve the control performance of automatic train operation (ATO) in urban rail trains, five typical operating sequences of urban rail trains were studied. Under the condition of meeting the safety and comfort principles of train operation, a train dynamics model was established to achieve the goals of low energy consumption, short running time, and high stopping accuracy in urban rail transit trains. In the process of finding a multi-objective solution to this problem, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) was used with an elite retention strategy, and the optimal Pareto multi-objective solution set was sought. In the process of optimal solution weight assignment, the hierarchical analysis Mahalanobis distance method, which combines subjective and objective analysis, was used. Finally, taking the Beijing Yizhuang subway line as the background design example, the simulation verified the effectiveness and feasibility of the algorithm and obtained high-quality automatic train driving curves under various working conditions. This research has important reference significance for the actual operation of automatic driving in urban rail trains.

Evaluation of a reduced-pressure chemical ion reactor utilizing adduct ionization for the detection of gaseous organic and inorganic species

Abstract. Volatile organic compounds (VOCs) and volatile inorganic compounds (VICs) provide critical information across many scientific fields including atmospheric chemistry and soil and biological processes. Chemical ionization (CI) mass spectrometry has become a powerful tool for tracking these chemically complex and temporally variable compounds in a variety of laboratory and field environments. It is particularly powerful with time-of-flight mass spectrometers, which can measure hundreds of compounds in a fraction of a second and have enabled entirely new branches of VOC and/or VIC research in atmospheric and biological chemistry. To accurately describe each step of these chemical, physical, and biological processes, measurements across the entire range of gaseous products is crucial. Recently, chemically comprehensive gas-phase measurements have been performed using many CI mass spectrometers deployed in parallel, each utilizing a different ionization method to cover a broad range of compounds. Here we introduce the recently developed Vocus AIM (adduct ionization mechanism) ion–molecule reactor (IMR), which samples trace vapors in air and ionizes them via chemical ionization at medium pressures. The Vocus AIM supports the use of many different reagent ions of positive and negative polarity and is largely independent of changes in the sample humidity. Within the present study, we present the performance and explore the capabilities of the Vocus AIM using various chemical ionization schemes, including chloride (Cl−), bromide (Br−), iodide (I−), nitrate (NO3-), benzene cations (C6H6+), acetone dimers ((C3H6O)2H+), and ammonium (NH4+) reagent ions, primarily in laboratory and flow tube experiments. We report the technical characteristics and operational principles, and compare its performance in terms of time response, humidity dependence, and sensitivity to that of previous chemical ionization approaches. This work demonstrates the benefits of the Vocus AIM reactor, which provides a versatile platform to characterize VOCs and VICs in real time at trace concentrations.

Possibilities of developing technology for generating electricity using photovoltaic modules

The purpose of this paper is to present the most commonly used types of photovoltaic panels and principles of their operation. Mono- and polycrystalline cells are presented, with their advantages and disadvantages indicated. The following section describes the process of obtaining electricity by using the photovoltaic and thermoelectric phenomena occurring in cells. Then, the structure and principle of operation of dye cells, thin-film cells and fourth-generation cells were presented on the example of cells using the Schottky junction to generate energy. The article also presents the method of obtaining single crystals of silicon, developed by Jan Czochralski, who lived at the turn of the 19th and 20th centuries. The method he developed laid the foundations for the development of modern integrated circuits - it was a milestone in the development of electronics.

Regularity through randomness: Bioinspired quasi-amorphous photonic structures for multilevel information encryption

The biological world has produced a wealth of complex photonic materials offering abundant design inspirations. However, creating these intricate photonic structures intertwining order, disorder, and hierarchical arrangements remains challenging. Achieving this necessitates nano-fabrication technologies capable of integrating intended macroscopic properties while accommodating microscopic variability or randomness, akin to the operational principles observed in biological organisms. Here, we present quasi-amorphous photonic structure (QAPS) patterns with regulated sophisticated visual effects through hierarchically distributions of photonic elements with engineered randomness. Enabled by an infiltration-assisted (IFAST) inkjet printing method, the visual appearances of QAPS patterns are precisely controlled by collective harnessing of nanoscale resonant scattering of colloids, mesoscale interferences, and macroscale light transporting. The QAPS patterns exhibit isotropic diffuse colors, unprecedented iridescence and enable multichannel encrypted information that can be selectively identified using specific filters at particular specular illumination angles. Additionally, the intricate infiltration fields confer high adjustability in colloidal assembly, offering sophisticated packing geometries and color distributions at the microscale, which can serve as physical unclonable security features. The exceptional structural complexity and optical versatility of QAPSs enable the integration of multilevel security features within a single system, providing a promising roadmap to achieve larger information capacity, multichannel cryptography, and enhanced encryption levels.

СУЧАСНІ ТЕНДЕНЦІЇ У КОНСТРУЮВАННІ ЧУТЛИВИХ ШАРІВ ДЛЯ ОПТИЧНИХ СЕНСОРІВ ТОКСИЧНИХ РЕЧОВИН

The main trends in the creation of sensitive elements of gas sensors for the detection of toxic substances in polluted areas, in industrial premises and the atmosphere are analyzed. An important aspect of the application of gas sensors is the monitoring of the quality of food products, especially of animal origin, since the consumption of spoiled products can be a great danger to human health. The principles of operation and new directions in the field of gas sensor technologies based on thin films of polymers and their nanostructures and composites with semiconductor materials of various types are outlined. Modern trends in the creation of detectors of harmful substances involve the use of new sensor media based on nanostructured components of various nature and the formation of thin film structures, using new, advanced nanotechnological approaches. It is promising to use new compositions of indicator substances (copolymers and layered structures based on poly-3,4-ethylenedioxythiophene, polyanisidine, pentacene, carbon and silicon nanoclusters), and new technological methods of their formation ("in situ" polymerization, layered assembly, electropolymerization and etc.), which do not require the use of complex, expensive equipment. The principles of construction of multifunctional gas sensors are presented. The construction of a gas sensor is proposed, the information signal of which is determined by the selective absorption of the optical medium interacting with the gas. To obtain spectral characteristics, optocouples are used, which consist of controlled sources of optical radiation and photosensitive elements. The key issue for the successful implementation of all improvements in gas sensors and nanosensors at the current stage will remain the search for substances and structures that are highly sensitive to the action of toxic gases, including components of explosive and poisonous substances, and can selectively react to their presence by changing optical and/or electrical properties.

Low-power adaptive sampling electronic nose system with a Radon transform-based convolutional neural network for optimized gas recognition

The electronic nose (E-nose) systems provide great promise in capturing information about the identity of gaseous chemical analytes as well as their temporal variation. However, the regular and dense sampling events of the E-nose often lead to a substantial amount of redundancy in the temporal structure, which in turn limits their application in efficiency-sensitive scenarios such as advanced robotics and the Internet of Things. Herein, we introduce a novel operating mechanism for E-noses, which dynamically adjusts the time interval of operation to reduce power consumption and information content through an adaptive sampling mechanism. Three strategic schemes with different operating principles are presented to implement this mechanism: the accurate scheme targets the optimized discrimination accuracy, the vague scheme is oriented toward power-sensitive scenarios, and the balanced scheme aims to balance cost and benefit. In order to ensure that the adaptively sampled inhomogeneous data can be compatible with each other, we further propose an algorithm based on the Radon transform that can convert non-uniform time series with timestamp information into the same size tensor. Finally, we designed a convolutional neural network-based classification model for gaseous chemical analytes, providing guidance on scheme and parameter selection with an accuracy of up to 99 % and power savings of up to 96 %. Overall, this work provides a novel solution to optimize temporal redundancy in E-nose systems and a generalized approach to the corresponding deep-learning data processing.

Feasibility Test of A Testing Station Trainer Situated in Virtual Reality Integrates Computational Thinking Concepts

This research focuses on integrating the Computational Thinking (CT) concept of automation system in vocational education to address the high costs and scarcity of educational resources in practical learning. The rapid industrial expansion of automation, particularly in Modular Production Systems (MPS), necessitates that students grasp both the components' functionalities and operational principles. Another point that needs to be considered is the integrated CT concept in the learning process. The CT for 21st-century skills, this research aims to facilitate knowledge absorption through systematic problem-solving strategies. To reduce cost and scarcity, this research developed an Interactive Virtual Reality Testing Station (IVRTS) employing a CT methodology to replicate MPS functions effectively in a Flexible Manufacturing System (FMS) Laboratory setting. Developing an Interactive Virtual Reality Testing Station (IVRTS) with a CT approach to simulate the working process is expected to overcome this problem in the Flexible Manufacturing System (FMS) Laboratory. The research procedure adopted from Lee Owens' ADDIE development procedure aims to create a CT-based IVRTS as an innovative educational tool. Experimental validation will compare the efficacy of CT-enhanced IVRTS against traditional methods among 36 students from higher schools. Based on the results of research on the IVRTS indicates its significant potential, receiving mainly "Good/Worth It" feedback. Despite the overall positive reception, users reported issues regarding its complex nature and the necessity for ongoing technical support. Refinements to make the system more intuitive and autonomous by streamlining the interface and clarifying functions are essential for broader user adoption.

The Use of eXplainable Artificial Intelligence and Machine Learning Operation Principles to Support the Continuous Development of Machine Learning-Based Solutions in Fault Detection and Identification

Machine learning (ML) revolutionized traditional machine fault detection and identification (FDI), as complex-structured models with well-designed unsupervised learning strategies can detect abnormal patterns from abundant data, which significantly reduces the total cost of ownership. However, their opaqueness raised human concern and intrigued the eXplainable artificial intelligence (XAI) concept. Furthermore, the development of ML-based FDI models can be improved fundamentally with machine learning operations (MLOps) guidelines, enhancing reproducibility and operational quality. This study proposes a framework for the continuous development of ML-based FDI solutions, which contains a general structure to simultaneously visualize and check the performance of the ML model while directing the resource-efficient development process. A use case is conducted on sensor data of a hydraulic system with a simple long short-term memory (LSTM) network. Proposed XAI principles and tools supported the model engineering and monitoring, while additional system optimization can be made regarding input data preparation, feature selection, and model usage. Suggested MLOps principles help developers create a minimum viable solution and involve it in a continuous improvement loop. The promising result motivates further adoption of XAI and MLOps while endorsing the generalization of modern ML-based FDI applications with the HITL concept.

Particles reinforcement via friction stir processing (FSP): A Review

Abstract Friction stir processing (FSP) is a variant of friction stir welding (FSW) follows the same principle of operation as that of FSW; however, its purpose is very much different. FSP can be employed for the reinforcement of particulate filler in materials to form surface composites. FSP carries a tool of cylindrical shape with shoulder and pin. Being mounted with the spindle of the machine, it can rotate with high speed as well as exert vertical force and hence plunges the pin in to the materials. Heat originated due to friction softens the material beneath shoulder and as tool passed through ahead the material is processed and consolidated. During processing, materials experience severe deformation and mixing. Also, the temperature of the materials goes high significantly due to the synergetic effect of friction and plastic deformation. Due to the material mixing and thermo-mechanical nature, the process opens the door for the possible incorporation of second phase particles in the processed region. In this review, firstly processing/reinforcement approaches will be discussed which will be followed by effect of process parameters. After that, microstructure evolution and related mechanical properties will be discussed in detail. The synergism among process parameters, microstructure and mechanical properties will also be discussed.