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J, Volume 7, Issue 1 (March 2024) – 6 articles

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13 pages, 1417 KiB  
Review
Self-Defense Mechanism in Rice to Salinity: Proline
by Yunus Emre Koc, Murat Aycan and Toshiaki Mitsui
J 2024, 7(1), 103-115; https://doi.org/10.3390/j7010006 - 11 Mar 2024
Viewed by 1362
Abstract
The increasing global population and climate change threaten food security, with the need for sustenance expected to rise by 85% by 2050. Rice, a crucial staple food for over 50% of the global population, is a major source of calories in underdeveloped and [...] Read more.
The increasing global population and climate change threaten food security, with the need for sustenance expected to rise by 85% by 2050. Rice, a crucial staple food for over 50% of the global population, is a major source of calories in underdeveloped and developing countries. However, by the end of the century, over 30% of rice fields will become saline due to soil salinity caused by earthquakes, tsunamis, and rising sea levels. Plants have developed strategies to deal with salt stress, such as ion homeostasis, antioxidant defense mechanisms, and morphological adaptations. Proline, an endogenous osmolyte, is the predominant endogenous osmolyte that accumulates in response to salinity, and its overexpression in rice plants has been observed to increase plant salinity tolerance. Exogenously applied proline has been shown to improve plant salt tolerance by reducing the destructive effect of salinity. Recent research has focused on ionic toxicity, nitrogen fixation, and gene expression related to salt tolerance. Exogenous proline has been shown to improve water potential and leaf content, restoring water usage efficiency. It can also ease growth inhibition in salt-sensitive plants. Exogenously applied proline increases antioxidant activities and enhances plant salinity tolerance. This review examines the role and processes of proline in rice plants under salt stress and its relationship with other tolerance mechanisms. Full article
(This article belongs to the Section Biology & Life Sciences)
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9 pages, 3254 KiB  
Case Report
Medial Patellofemoral Ligament and Lateral Patellofemoral Ligament Reconstruction after Tibial Tuberosity Transposition in a Young Woman with Patellar Instability
by Jakob Merkač and Mateja Sirše
J 2024, 7(1), 94-102; https://doi.org/10.3390/j7010005 - 24 Feb 2024
Viewed by 1073
Abstract
In patients with reccurent lateral and medial patellar instability, isolated medial patellofemoral ligament (MPFL) reconstruction may be insufficient due to poor lateral retinacular tissue quality. In this report, we describe a case of a patient that underwent simultaneous MPFL and lateral patellofemoral ligament [...] Read more.
In patients with reccurent lateral and medial patellar instability, isolated medial patellofemoral ligament (MPFL) reconstruction may be insufficient due to poor lateral retinacular tissue quality. In this report, we describe a case of a patient that underwent simultaneous MPFL and lateral patellofemoral ligament (LPFL) reconstruction on the left knee due to chronic bidirectional patellar instability. A 29-year-old female patient presented with first-time lateral patellar dislocation five years ago due to acute strain. She underwent a tibial tuberosity transposition in another hospital. After the surgery, she suffered from recurrent medial and lateral patellar dislocation and presented to our center. MPFL and concomitant LPFL reconstruction on the left knee was simultaneously performed due to bilateral patellar dislocation. The patella was stable postoperatively, and the patient underwent physiotherapy with successful results to date. Single-time patellar dislocation should be treated conservatively. Surgical treatment after the first episode of dislocation can magnitude the risk of postoperative complications. The simultaneous reconstructing of the LPFL yields patellar fixation indistinguishable from the native LPFL. These grafts provide separate tensioning depending on body anatomy, allowing for individualized stability. Anatomical MPFL reconstruction is supported by well-established high-quality research. Reconstructing the LPFL anatomically yields patellar fixation indistinguishable from the native LPFL. Full article
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22 pages, 6026 KiB  
Article
Aerodynamic Modification of High-Rise Buildings by the Adjoint Method
by Amirfarhang Nikkhoo, Ali Esmaeili, Shayan Rabizade and Majid Zamiri
J 2024, 7(1), 72-93; https://doi.org/10.3390/j7010004 - 5 Feb 2024
Viewed by 1321
Abstract
This study presents a novel numerical methodology that is designed for the dynamic adjustment of three-dimensional high-rise building configurations in response to aerodynamic forces. The approach combines two core components: a numerical simulation of fluid flow and the adjoint method. Through a comprehensive [...] Read more.
This study presents a novel numerical methodology that is designed for the dynamic adjustment of three-dimensional high-rise building configurations in response to aerodynamic forces. The approach combines two core components: a numerical simulation of fluid flow and the adjoint method. Through a comprehensive sensitivity analysis, the influence of individual variables on aerodynamic loads, including lift and drag coefficients, is assessed. The findings underscore that the architectural design, specifically the building’s construction pattern, exerts the most substantial impact on these forces, accounting for a substantial proportion (76%). Consequently, the study extends its evaluation to the sensitivity of fluid flow across various sections of the tower by solving the adjoint equation throughout the entire fluid domain. As a result, the derived sensitivity vector indicates a remarkable reduction of approximately 31% in the applied loads on the tower. This notable improvement has significant implications for the construction of tall buildings, as it effectively mitigates aerodynamic forces, ultimately enhancing the overall comfort and structural stability of these architectural marvels. Full article
(This article belongs to the Section Engineering)
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24 pages, 3065 KiB  
Article
An Advanced Deep Learning Framework for Multi-Class Diagnosis from Chest X-ray Images
by Maria Vasiliki Sanida, Theodora Sanida, Argyrios Sideris and Minas Dasygenis
J 2024, 7(1), 48-71; https://doi.org/10.3390/j7010003 - 22 Jan 2024
Cited by 1 | Viewed by 1618
Abstract
Chest X-ray imaging plays a vital and indispensable role in the diagnosis of lungs, enabling healthcare professionals to swiftly and accurately identify lung abnormalities. Deep learning (DL) approaches have attained popularity in recent years and have shown promising results in automated medical image [...] Read more.
Chest X-ray imaging plays a vital and indispensable role in the diagnosis of lungs, enabling healthcare professionals to swiftly and accurately identify lung abnormalities. Deep learning (DL) approaches have attained popularity in recent years and have shown promising results in automated medical image analysis, particularly in the field of chest radiology. This paper presents a novel DL framework specifically designed for the multi-class diagnosis of lung diseases, including fibrosis, opacity, tuberculosis, normal, viral pneumonia, and COVID-19 pneumonia, using chest X-ray images, aiming to address the need for efficient and accessible diagnostic tools. The framework employs a convolutional neural network (CNN) architecture with custom blocks to enhance the feature maps designed to learn discriminative features from chest X-ray images. The proposed DL framework is evaluated on a large-scale dataset, demonstrating superior performance in the multi-class diagnosis of the lung. In order to evaluate the effectiveness of the presented approach, thorough experiments are conducted against pre-existing state-of-the-art methods, revealing significant accuracy, sensitivity, and specificity improvements. The findings of the study showcased remarkable accuracy, achieving 98.88%. The performance metrics for precision, recall, F1-score, and Area Under the Curve (AUC) averaged 0.9870, 0.9904, 0.9887, and 0.9939 across the six-class categorization system. This research contributes to the field of medical imaging and provides a foundation for future advancements in DL-based diagnostic systems for lung diseases. Full article
(This article belongs to the Special Issue Integrating Generative AI with Medical Imaging)
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29 pages, 13960 KiB  
Article
Blockchain in Smart Grids: A Bibliometric Analysis and Scientific Mapping Study
by Georgios Lampropoulos
J 2024, 7(1), 19-47; https://doi.org/10.3390/j7010002 - 6 Jan 2024
Viewed by 1795
Abstract
To achieve sustainability and fulfill sustainable development goals, the digitalization of the power sector is vital. This study aims to examine how blockchain can be integrated into and enrich smart grids. In total, 10 research questions are explored. Scopus and Web of Science [...] Read more.
To achieve sustainability and fulfill sustainable development goals, the digitalization of the power sector is vital. This study aims to examine how blockchain can be integrated into and enrich smart grids. In total, 10 research questions are explored. Scopus and Web of Science (WoS) were used to identify documents related to the topic. The study involves the analysis of 1041 scientific documents over the period 2015–2022. The related studies are analyzed from different dimensions including descriptive statistics, identification of the most common keywords and most widely used outlets, examination of the annual scientific production, the analysis of the most impactful and productive authors, countries, and affiliations. The advancement of the research focus and the most popular topics are also examined. Additionally, the results are analyzed, the main findings are discussed, open issues and challenges are presented, and suggestions for new research directions are provided. Based on the results, it was evident that blockchain plays a vital role in securing smart grids and realizing power sector digitalization, as well as in achieving sustainability and successfully meeting sustainable development goals. Full article
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18 pages, 1699 KiB  
Review
An Overview of Mathematical Methods Applied in the Biomechanics of Foot and Ankle–Foot Orthosis Models
by Hasan Mhd Nazha, Szabolcs Szávai and Daniel Juhre
J 2024, 7(1), 1-18; https://doi.org/10.3390/j7010001 - 22 Dec 2023
Viewed by 1282
Abstract
Ankle–foot orthoses (AFOs) constitute medical instruments designed for patients exhibiting pathological gait patterns, notably stemming from conditions such as stroke, with the primary objective of providing support and facilitating rehabilitation. The present research endeavors to conduct a comprehensive review of extant scholarly literature [...] Read more.
Ankle–foot orthoses (AFOs) constitute medical instruments designed for patients exhibiting pathological gait patterns, notably stemming from conditions such as stroke, with the primary objective of providing support and facilitating rehabilitation. The present research endeavors to conduct a comprehensive review of extant scholarly literature focusing on mathematical techniques employed for the examination of AFO models. The overarching aim is to gain deeper insights into the biomechanical intricacies underlying these ankle–foot orthosis models from a mathematical perspective, while concurrently aiming to advance novel models within the domain. Utilizing a specified set of keywords and their configurations, a systematic search was conducted across notable academic databases, including ISI Web of Knowledge, Google Scholar, Scopus, and PubMed. Subsequently, a total of 23 articles were meticulously selected for in-depth review. These scholarly contributions collectively shed light on the utilization of nonlinear optimization techniques within the context of ankle–foot orthoses (AFOs), specifically within the framework of fully Cartesian coordinates, encompassing both kinematic and dynamic dimensions. Furthermore, an exploration of a two-degree-of-freedom AFO design tailored for robotic rehabilitation, which takes into account the interplay between foot and orthosis models, is delineated. Notably, the review article underscores the incorporation of shape memory alloy (SMA) elements in AFOs and overviews the constitutive elastic, viscoelastic, and hyperelastic models. This comprehensive synthesis of research findings stands to provide valuable insights for orthotists and engineers, enabling them to gain a mathematical understanding of the biomechanical principles underpinning AFO models and fostering the development of innovative AFO designs. Full article
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