Segment Size Research Articles

How to charge in servicizing: Per period or per use?

In a servicizing business model, the service provider sells a product’s functionality, not the product per se. This study aims to find the best profit-maximizing pricing strategies for this business model that can also yield the highest consumer welfare with minimal environmental impact. This approach identifies win-win-win strategies satisfying profit, planet, and people objectives. As providers charge consumers based on usage (pay-per-use) versus a regular flat fee (pay-per-period), the economic, environmental, and welfare implications of such strategies remain unclear. We tackle this problem using a stylized game-theoretic model where the service provider first designs the pricing schemes, and consumers react by adjusting use. When offering a single product, we observe that pay-per-use policies outperform pay-per-period when the service provider is cost-inefficient or small-scale. Also, where per-use consumers are not very sensitive to payment frequency, service providers tend to exclude low usage-valuation users. Outperformance also prevails when the proportion of low-use consumers is sufficiently low. Our results show that a win-win strategy can be achieved by offering a pay-per-use policy to high usage-valuation consumers, however, a win-win-win strategy is never possible. We also analyze the problem for a situation where the service provider offers a product line including green and regular products. Then, we characterize possible win-win-win strategies that hinge on environmental impact from different phases of a product’s lifecycle. We extend the models to allow SP i) influence the size of market segments and ii) decide on product greenness levels in different phases of its lifecycle.

Comparing Multi-Arm Robotics for In-Space Assembly

Robotic In-space assembly (ISA) is the next step to building larger and more permanent structures in orbit. Determining the best robot for ISA is difficult as it will not only depend on the structure being assembled but on how it is assembled. This analysis shows how changing some key design parameters can influence different robotic systems for ISA. This study focuses on the construction of a 20 m linear truss structure but also expands to a 10 and 50 m truss. Two categories of robots are included in this study: a stationary robot and a mobile robot which crawls along the structure. Both the stationary and crawling robotic systems utilize two planar dexterous manipulators to assemble individual truss pieces into a linear truss. In the case of the stationary robotic system a single long positioning leg is used to move the two dexterous arms into position. The crawling robotic system uses two planar manipulators to crawl along the truss. A systems level analysis is presented which details how the forces from the robotic systems drive the mass of the truss and also how the size of the truss segments drive the requirements of the robotic system. This analysis shows how changing some key design parameters can influence each of the different robotic systems and the truss design itself. The estimated masses of the robotic systems and the truss and the assembly time are presented. There are trade-offs to every robot design and understanding those trade-offs is essential to building a system that is not only efficient but also cost-effective.

Word-level text highlighting of medical texts for telehealth services

The medical domain is often subject to information overload. The digitization of healthcare, constant updates to online medical repositories, and increasing availability of biomedical datasets make it challenging to effectively analyze the data. This creates additional workload for medical professionals who are heavily dependent on medical data to complete their research and consult their patients. This paper aims to show how different text highlighting techniques can capture relevant medical context. This would reduce the doctors' cognitive load and response time to patients by facilitating them in making faster decisions, thus improving the overall quality of online medical services. Three different word-level text highlighting methodologies are implemented and evaluated. The first method uses Term Frequency - Inverse Document Frequency (TF-IDF) scores directly to highlight important parts of the text. The second method is a combination of TF-IDF scores, Word2Vec and the application of Local Interpretable Model-Agnostic Explanations to classification models. The third method uses neural networks directly to make predictions on whether or not a word should be highlighted. Our numerical study shows that the neural network approach is successful in highlighting medically-relevant terms and its performance is improved as the size of the input segment increases.

The line of fifths and the co-evolution of tonal pitch-classes

In this study, we determine the fundamental role of the line of fifths for the organization of tonal material by applying dimensionality reduction to a large historical corpus of pitch-class counts (ca. 1360–1940). We observe a historically growing trend in the exploitation of the fifths range, i.e. the size of segments that pitch-class distributions cover on the line of fifths. Moreover, we introduce the novel concept of pitch-class (co-)evolution, which traces the changing co-occurrence of pitch classes over time and likewise reaffirms the centrality of this linear tonal space from a historical angle, allowing us also to distinguish between historical periods in terms of the usage of pitch classes.

Case Report: Structural Changes in the Coronary Vessel Wall in a Patient With Incomplete Kawasaki Disease

BackgroundKawasaki disease (KD) is an acute systemic vasculitis of infants and young children that affects medium-sized vessels. Conventional cardiac imaging techniques, such as cardiac catheterization, are useful for characterizing the coronary arterial lesion (CAL) size and luminal diameter of the diseased coronary artery segment in patients with KD, but there are limitations to the visualization of the detailed vascular anatomy. Optical coherence tomography (OCT) is a high-resolution intracoronary arterial imaging modality that can distinguish the three layers of the coronary arterial wall. Several studies have reported coronary artery wall abnormalities in KD patients with coronary arterial aneurysm or regressed aneurysm. However, there have been no reports on changes in the coronary artery wall in cases of incomplete KD without CAL.Case PresentationWe herein report an 11-year-old girl with a history of incomplete KD without coronary arterial aneurysms. She had been diagnosed with perimembranous ventricular septal defect (VSD) after birth and had experienced incomplete KD at 1 year old. During her hospitalization for KD, she did not receive intravenous immunoglobulin (IVIG), because she did not meet the Harada score or criteria for treatment in patients with incomplete KD established by the American Heart Association. No dilatation or coronary artery aneurysm were observed on transthoracic echocardiography in the acute or follow-up period. At 11 years old, she received cardiac catheterization and coronary angiography (CAG) for the evaluation of a VSD and follow-up of KD. CAG demonstrated no aneurysm, dilatation, or significant stenosis of the coronary arteries. We performed an OCT study, which revealed the presence of intimal thickening, disruption of the media, and neovascularization in the left anterior descending artery.ConclusionOCT demonstrates the structural changes of CA even in the patient with incomplete KD who have not been treated with IVIG.

Rheological Behavior of HEUR Mixtures in Aqueous Media

Abstract Three S-G HEUR thickeners were synthesized by a step growth polymerization technique of poly (ethylene oxide) (PEO) and dicyclohexylmethane – 4,40-diisocyanate (H12MDI) and then end capped with two monofunctional aliphatic alcohols. These polymers were mixed together according to the hydrophilic and hydrophobic nature of their segments. Based on this, two sets of associating polymers were introduced. In one set, the samples had identical hydrophobic segments while in the other one, hydrophilic segments were similar. The steady shear viscosity profiles of aqueous solutions of all models were determined. In addition, aqueous binary mixtures with various ratios of the S-G HEUR models were studied using steady state and dynamic rheometry. It is suggested that combinations of associating polymers with different size of hydrophobic segments and similar hydrophilic segments produce an associative polymer-like behavior. However, the combination of those with similar long hydrophobic segments and different hydrophilic segments at similar weight ratio in solution falls short of displaying an associative polymer – like behavior.

Immunology-Based Sustainable Portfolio Management

Immunological principles can be used to build a sustainable investment portfolio. The theory of immunology states that information about recognized pathogens is stored in the memory of the immune system. Information about previous illnesses can be helpful when the pathogen re-enters the body. Real-time analysis of 11 automated financial trading datasets confirmed this phenomenon in financial time series. Therefore, in order to increase the sustainability of the portfolio, we propose to train the portfolio with the most similar segments of historical data. The segment size and offset may vary depending on the data set and time.

Reconstruction of Complex Soft Tissue Defects of the Heel With Versatile Double Skin Paddle Anterolateral Thigh Perforator Flaps: An Innovative Way to Restore Heel Shape.

BackgroundComplex heel defects constitute a significant challenge for plastic surgeons.ObjectivesIn this study, versatilities of free double skin paddle ALT flaps in the reconstruction of complex soft tissue defects of heels were explored.MethodsFrom January 2010 to December 2019, 16 patients (13 male and 3 females) aged 16–74 years underwent double skin paddle ALT flap reconstruction in our department. All the patients had large defects located at the heel, and 5 had a dead space. Underlying structures such as vessels, bones, and tendons were exposed in all cases.ResultsFlap survival rate was 100% after the reconstruction. Eleven double skin paddle ALT flaps and 5 vastus lateralis muscle-chimeric double skin paddle ALT flaps were used. The size of the skin flap ranged from 9.5 × 4.5 cm2 to 22 × 10 cm2, and the size of a muscle segment ranged from 6 × 3 × 1 cm3 to 10 × 3 × 2 cm3. The mean follow-up was 22.6 months (range: 10–81 months). The wounds healed well, providing reliable soft tissue coverage and good heel contour. All the patients ambulated independently during the follow-up period. Most of them regained protective sensation. The average two-point discrimination was 32.7 mm (range: 27–37 mm).ConclusionDouble skin paddle ALT flaps are a feasible option for the reconstruction of complex heel defects, with good functional and aesthetic results. Nonetheless, further studies comparing double skin paddle ALT flaps to other flap techniques are needed.

Fgf8 dynamics and critical slowing down may account for the temperature independence of somitogenesis

Somitogenesis, the segmentation of the antero-posterior axis in vertebrates, is thought to result from the interactions between a genetic oscillator and a posterior-moving determination wavefront. The segment (somite) size is set by the product of the oscillator period and the velocity of the determination wavefront. Surprisingly, while the segmentation period can vary by a factor three between 20 °C and 32 °C, the somite size is constant. How this temperature independence is achieved is a mystery that we address in this study. Using RT-qPCR we show that the endogenous fgf8 mRNA concentration decreases during somitogenesis and correlates with the exponent of the shrinking pre-somitic mesoderm (PSM) size. As the temperature decreases, the dynamics of fgf8 and many other gene transcripts, as well as the segmentation frequency and the PSM shortening and tail growth rates slows down as T–Tc (with Tc = 14.4 °C). This behavior characteristic of a system near a critical point may account for the temperature independence of somitogenesis in zebrafish.

The relationship between MFN1 copy number variation and growth traits of beef cattle.

Copy number variation, as a kind of genetic submicroscopic structural variation, refers to the deletion or repetition of a large segment of genomic DNA, involving a segment size ranging from 50bp to several MB. Mitochondrial fusion protein (MFN1) gene regulates the fusion of mitochondrial outer membrane in cells and maintains the dynamic needs of reticular mitochondria in cells. In this study, we conducted to tested the dstribution characteristics of MFN1-CNV in 522 cattles across Xianan cattle (XN), Pinan cattle (PN), Qinchuan cattle (QC), Jiaxian cattle (JX), Yunling cattle (YL), and correlated it with phenotypic traits. Then we observed the expression of MFN1 in various tissues of QC cattle (n=3), and the expression levels were higher in lung and muscle. The results showed that there was significant correlation between MFN1 gene CNV and hucklebone width of QC cattle, hip width and height at sacrum of JX red cattle, chest width and rump length of YL cattle (P<0.05). Individuals with duplication type were better than the type of normal or deletion in phenotypic traits. In conclusion, our data showed the correlation between MFN1 gene and growth traits of Chinese cattle. MFN1 gene can be used as a molecular marker for cattle selection and breeding, and accelerate the improvement of Chinese cattle.

French and Swiss banks as initiators of implementation and use of Crowdfunding Systems

Purpose of the Study: The subjects of the considerations are initiatives to implement or use the method of online crowdfunding by banks. The focus was on such implementations in France and Switzerland, i.e. countries with a relatively large number of such projects. The presented research identifies crowdfunding platforms and (depending on access to data) determines the size in terms of value of the analyzed market sub-segment and its specificity. This work is a continuation of a series of author`s publications aimed at examining the crowdfunding market sub-segment of banks in Europe.&#x0D; Methodology: Crowdfunding platforms in individual French and Swiss banks were identified. Data was obtained from internet resources, supported by, inter alia, available publications. The final data was obtained directly from the websites of the analyzed financial institutions (or platforms), or they were aggregated, or the data was estimated on the basis of partial information. The research was carried out in October and November 2021, with data verification as of November 30.&#x0D; Main Findings: The article explores a specific market segment in France and Switzerland - banks implementing or using crowdfunding platforms. The scope of implementation of such systems was determined by identifying the individual analyzed financial institutions. The value of accumulated financial resources (capital) and the scope of project implementation were measured, distinguishing the size of the market sub-segment under study. The examined systems collectively obtained a relatively large amount, over EUR 4326 million.&#x0D; Applications of the Study: The presented article concerns the applications of the crowdfunding method in financial institutions (French and Swiss banks). This implies considerations in several scientific fields, incl. economics (the possibility of measuring the market segment), business informatics (electronic platforms; human-computer interactions).&#x0D; Novelty / Originality of this Study: The scientific literature on the use of crowdfunding in banks, and especially the measurement of the size of this market segment, is almost non-existent, it is only fragmentary. The separation in this article of the size of the crowdfunding sub-segment in French and Swiss banks, although partial, seems prospective, as it allows for further research in this area.

Early Identification of COVID-19 Progression to Its Severe Form Using Artificial Intelligence

Background: Early prediction of disease progression in coronavirus disease 2019 (COVID-19) patients can be helpful for personalized therapy, as well as the optimal allocation of public health resources. Objectives: This study aimed to present predictive models for identifying potential high-risk COVID-19 patients upon hospital admission, based on the examination of clinical and radiological features by radiologists and artificial intelligence (AI). Patients and Methods: A total of 786 initially non-severe COVID-19 patients were retrospectively enrolled in this study between January 2 and May 28, 2020. The patients were randomly divided into training (n = 628, 80%) and test (n = 158, 20%) groups. Clinical factors, laboratory indicators, and radiologist- and AI-extracted radiological features of pneumonia lesions were determined using a convolution neural network. The features were selected based on the Boruta algorithm with five-fold cross-validation. Four models, including a model based on clinical findings (model C), a model based on the physician’s examination of radiological features (R-Doc model), a model based on AI-derived radiological features (R-AI model), and an AI-based model mimicking the physician’s examinations (AI-Mimic-Doc model), were constructed for predicting COVID-19 progression upon admission, using a logistic regression analysis. The predictive performance of the four models was evaluated by calculating the area under the receiver operating characteristic (AUC) curve with a 95% confidence interval (95% CI) and then compared using the DeLong test. Results: Overall, 238 out of 786 patients (30.3%) progressed into severe or critical pneumonia during the 14-day follow-up. Nine clinical findings, 17 laboratory indicators, 48 physician-extracted radiological features of pneumonia lesions, and 126 AI-driven radiological features were collected. The urea, albumin level, and lesion size in the basal segment of the right lower lobe of the lung or the proportion of CT values in the range of -200 - 60 in the left lung were the representative features for constructing the R-Doc and R-AI models, respectively. Comparison of the R-Doc model (AUC: 0.840, 95% CI: 0.747 - 0.933 for the training set and 0.731, 95% CI: 0.606 - 0.857 for the test set) with the R-AI model (AUC: 0.803, 95% CI: 0.701 - 0.906 for the training set and AUC: 0.731, 95% CI: 0.606 - 0.857 for the validation set) indicated a marginal difference in identifying patients at risk of progression to pneumonia upon admission (P &lt; 0.1). The R-AI model was superior to model C, with an AUC of 0.770 for the training set (95% CI: 0.657 - 0.882) and 0.666 for the validation set to identify high-risk non-severe cases upon admission. Conclusion: By using radiological features along with blood tests, early identification of COVID-19 patients, who are at risk of disease progression, can be achieved on admission (rapidly by using AI); therefore, the use of these features can contribute to the clinical management of COVID-19.

An evaluation of fast segmented sorting implementations on GPUs

Many real-world problems require a sorting operation as part of their efficient solution. Some examples of this are real-time plasma diagnostic, image re-ranking, and suffix array construction. These problems usually involve a large amount of data, so their solutions need a particular application of the sorting procedure, consisting of sorting several arrays in matrix rows or array segments, an operation called segmented sorting. Previous studies showed that a merge sort-based strategy and a strategy called fix sort executed this operation on GPUs with good performance for different array sizes. In this work, we compare the fastest segmented sorting GPU implementations on seven different GPU models with various input data scenarios, including scenarios with varying numbers of segments, segment sizes, and considering segments of the same and different sizes. We first performed algorithm analysis to explain how the number of segments affects each implementation’s performance. Then, we perform an S-curve analysis and observe that, even though each strategy might be the fastest option for a subset of the sorting scenarios, some approaches may cause very high slowdowns on specific scenarios. We also compare the strategies using heat maps, show that their performance depends on the array size and number of segments, and propose a recommendation map to support selecting the best overall implementation based on the size and number of segments. Our experimental results show that choosing a strategy based on our recommendation map leads to the best strategy on 47.57% of the cases and a maximum slowdown of less than 1.5 times in 93.58% of the cases. Moreover, on average, the recommended strategy is only 1.11× worse than the optimum one.Finally, we evaluated how each strategy behaves when sorting arrays with different and equal segment sizes and showed that the fix sort-based approaches take roughly the same time to sort arrays with equal or different segment sizes, while the approach proposed by Hou et al. usually takes longer to sort arrays with different segment sizes than arrays with equal segment sizes.

Image Recognition of Male Oilseed Rape (Brassica napus) Plants Based on Convolutional Neural Network for UAAS Navigation Applications on Supplementary Pollination and Aerial Spraying

To ensure the hybrid oilseed rape (OSR, Brassica napus) seed production, two important things are necessary, the stamen sterility on the female OSR plants and the effective pollen spread onto the pistil from the OSR male plants to the OSR female plants. The unmanned agricultural aerial system (UAAS) has developed rapidly in China. It has been used on supplementary pollination and aerial spraying during the hybrid OSR seed production. This study developed a new method to rapidly recognize the male OSR plants and extract the row center line for supporting the UAAS navigation. A male OSR plant recognition model was constructed based on the convolutional neural network (CNN). The sequence images of male OSR plants were extracted, the feature regions and points were obtained from the images through morphological and boundary process methods and horizontal segmentation, respectively. The male OSR plant image recognition accuracies of different CNN structures and segmentation sizes were discussed. The male OSR plant row center lines were fitted using the least-squares method (LSM) and Hough transform. The results showed that the segmentation algorithm could segment the male OSR plants from the complex background. The highest average recognition accuracy was 93.54%, and the minimum loss function value was 0.2059 with three convolutional layers, one fully connected layer, and a segmentation size of 40 pix × 40 pix. The LSM is better for center line fitting. The average recognition model accuracies of original input images were 98% and 94%, and the average root mean square errors (RMSE) of angle were 3.22° and 1.36° under cloudy day and sunny day lighting conditions, respectively. The results demonstrate the potential of using digital imaging technology to recognize the male OSR plant row for UAAS visual navigation on the applications of hybrid OSR supplementary pollination and aerial spraying, which would be a meaningful supplement in precision agriculture.

Characterizing seasonal transitions: Breeding-like morphology and behavior during the late non-breeding season in green anole lizards

Seasonally breeding animals, such as green anole lizards (Anolis carolinensis), allow for the examination of the control of reproduction during different reproductive states. During the breeding season, the gonads are large and reproductively active. Following the breeding season, gonads regress and become less active, and the lizards enter a refractory period where breeding is inhibited. After this stage, a post-refractory period occurs during which the lizards are still in a non-breeding state, but environmental changes can trigger the onset of breeding. However, it is unclear what causes these changes in reproductive state and we hypothesized that this may be due to alterations in gonadotropin-releasing hormone (GnRH) signaling. The present study aimed to identify morphological and behavioral differences in GnRH- and saline-injected refractory and post-refractory male anoles when housed under the same non-breeding environmental conditions. We found that post-refractory anoles had increased testicular weight, recrudescence, sperm presence, and reproductive behavior, with no impact of GnRH injection. Renal sex segment size and steroidogenic acute regulatory protein (StAR) mRNA levels did not differ among groups, indicating that testosterone levels likely had not increased in post-refractory lizards. Post-refractory anoles in this study were beginning to transition towards a breeding state without exposure to changing environmental conditions, and GnRH was not necessary for these changes. These data reveal a complex interaction between the activation of breeding, changing environmental conditions, and the underlying physiology regulating reproduction in seasonally breeding lizards. Future studies are needed to further elucidate the mechanisms that regulate this relationship.

Interaction potential for coarse-grained models of bottlebrush polymers

Bottlebrush polymers are a class of highly branched macromolecules that show promise for applications such as self-assembled photonic materials and tunable elastomers. However, computational studies of bottlebrush polymer solutions and melts remain challenging due to the high computational cost involved in explicitly accounting for the presence of side chains. Here, we consider a coarse-grained molecular model of bottlebrush polymers where the side chains are modeled implicitly, with the aim of expediting simulations by accessing longer length and time scales. The key ingredients of this model are the size of a coarse-grained segment and a suitably coarse-grained interaction potential between the non-bonded segments. Prior studies have not focused on developing explicit forms of such potentials, instead, relying on scaling arguments to model non-bonded interactions. Here, we show how to systematically calculate an interaction potential between the coarse-grained segments of bottlebrush from finer grained explicit side chain models using Monte Carlo and Brownian dynamics and then incorporate it into an implicit side chain model. We compare the predictions from our coarse-grained implicit side chain model with those obtained from models with explicit side chains in terms of the potential of mean force, the osmotic second virial coefficient, and the interpenetration function, highlighting the range of applicability and limitations of the coarse-grained representation. Although presented in the context of homopolymer bottlebrushes in athermal solvents, our proposed method can be extended to other solvent conditions as well as to different monomer chemistries. We expect that our implicit side chain model will prove useful for accelerating large-scale simulations of bottlebrush solutions and assembly.

Cloud-Based Framework for Spatio-Temporal Trajectory Data Segmentation and Query

Trajectory segmentation is a technique of dividing sequential trajectory into segments. These segments are building blocks to various applications. Hence a system framework is essential to support trajectory segment indexing, storage, and query. When the size of segments is beyond the computing capacity of a single processing node, a distributed solution is proposed. In this article, we develop a distributed trajectory segmentation framework that includes a greedy-split segmentation method. This framework consists of distributed in-memory processing and a cluster of graph storage respectively. For fast trajectory queries, we design a distributed spatial R-tree index of trajectory segments. Using the indexes, we build scalable query operations from both in-memory processing and access to graph storage. Based on this framework, we define two metrics to measure trajectory similarity and chance of collision. These two metrics are further applied to identify moving groups of trajectories. We quantitatively evaluate the effects of data partition, parallelism, and data size on the system. We identify the bottleneck factors at the data partition stage and validate two mitigation techniques to data skew. The evaluation demonstrates our distributed segmentation method and the system framework scale as the growth of the workload and the size of the parallel cluster.

МІЖНАРОДНА ЕКОНОМІЧНА ІНТЕГРАЦІЯ ТА ЕКОНОМІЧНА ГЛОБАЛІЗАЦІЯ: СПІЛЬНЕ ТА ВІДМІННЕ

The economic development of the modern world is taking place in the context of globalization, which is characterized by a comprehensive transformation of the world community into an open integrated system of information and communication, technological, financial and economic, political, socio-cultural ties and interactions. This process is confronted with the phenomenon associated with the formation of various types of integration associations. As a result, in the development of international economic integration (IEI) and economic globalization (EG) there are certain contradictions that need to be overcome in the interests of the world community. With this in mind, the aim of the study is to determine the common and distinctive features of IEI and EG. To implement it, the task of identifying the factors of the globalization process has been formulated and implemented; comparison of IEI and EG on certain grounds; characteristics of glocalization as fragmented global economic space, which is formed as a result of the interaction of IEI and EG. In identifying common and distinctive features of IEI and EG, features such as function, trend, process, object of influence and subject of action are used and their different importance in the interaction of these phenomena is proved. Different functions of IEI and EG are indicated. Their different process orientation and even the opposite was proved on the basis of analysis of the latest scientific sources. The tendencies of development of these phenomena are somewhat coincident, as integration as the union of certain parts as a whole confirms the tendency towards integrity, but in local terms. The greatest coincidence between IEI and EG is manifested in the object dimension, which is expressed through the various components of international economic activity. The key role among them belongs to world trade, the dynamics of which is constantly changing under the influence of such objective factors as the international division of labor, fragmentation of global production and value chains, specialization, accelerating foreign movement direct investment and increasing competition. The results of the study confirmed hypothesis about the relationship and at the same time the opposite of IEI and EG, interaction which are inherent the ratio of intersection. The analysis of IEI and EG trends was carried out taking into account the influence of various factors, including of convergent NBICS-technologies. Glocalization, which is a consequence of the interaction of IEI and EG, which is a certain synthesis of global and local, is characterized. In the global segment the boundary current states of IEI and EG intersect. Based on the formulated scientific statements, it is concluded that IEI, EG and glocalization form a fragmented global economic space. The size of this spatial segment and the characteristics are not constant, but depend on which trend ‒ global or local prevails. It is proved that in the future the most popular will be the research related to the systematic analysis of the essence of glocalization.

Retrofitting techniques of damaged concrete structure for environment concern: A review

Initiation and progression of damages in the concrete systems is the cause of reduction of structural strength and its durability. The significant retrofitting strategies are required to improve the damages and thus, the performance of infrastructures can be enhanced. The damages in the concrete system is due to several factors viz., ingress of alkaline water, wet-dry cycle, sulfate attack, thermal changes, chloride penetration, and freeze–thaw cycle etc. Changes in the shape and size of concrete segments before and after retrofitting decreases the strength of structural systems and consequently, reduced the durability of retrofitted materials. This review paper is motivated on the application of the retrofitting techniques using Fiber Reinforced Polymer (FRP) material for environment concerned. The deterioration of concrete structure and FRP retrofitted materials durability were discussed. The durability aspect of damaged concrete structure retrofitted with FRP materials under alkaline water, wet-dry cycle, freeze–thaw cycle, open cracks, and water immersion were reviewed. The de-bonding of FRP materials have been described to improve the structural integrity. The suitability of various retrofitting techniques were covered. This paper have been included the retrofitting techniques for the improvement of infrastructural facilities and further, the cracks filled rich cement mortar with FRP over that was the key finding. The review paper will facilitate innovative research directions to the industrialist and researchers.

Technology Roadmap for Aircraft Maintenance, Repair and Overhaul

Nowadays, the demand for aircraft Maintenance, Repair and Overhaul (MRO) is constantly growing. The market size of the European MRO segment is estimated to be USD 206.13 billion in 2022, growing at a Compound Annual Growth Rate (CAGR) of 2.8% between 2022 and 2030 [1]. This forecast is a good indication of the growth in the number of incoming assignments. As a result, airlines and aircraft operators will increasingly rely on companies with experience in the MRO field to perform maintenance and repair work. Furthermore, as many airlines now choose to outsource maintenance and repair, this will further increase the load on MRO companies. As the number of incoming jobs increases, the companies concerned are constantly looking for and implementing new and better methods and technologies, with another aim of gaining a larger market share. Moreover, as there is still scope for the development and introduction of new technologies and processes in this area, a significant number of research and development projects are underway or in the pipeline. Therefore, the main objective of this study is to use the available information to present a generalised technology roadmap for the companies involved in MRO activities and, on this basis, to collect, present and categorise the state-of-the-art developments in the MRO sector, highlighting what the future will hold for companies that incorporate these revolutionary innovations into their daily work processes.