Scope Of Application Research Articles

Research on meshing method for industrial CT volume data based on iterative smooth signed distance surface reconstruction

Industrial Computed Tomography (CT) technology is increasingly applied in fields such as additive manufacturing and non-destructive testing, providing rich three-dimensional information for various fields, which is crucial for internal structure detection, defect detection, and product development. In subsequent processes such as analysis, simulation, and editing, three-dimensional volume data models often need to be converted into mesh models, making effective meshing of volume data essential for expanding the application scenarios and scope of industrial CT. However, the existing Marching Cubes algorithm has issues with low efficiency and poor mesh quality during the volume data meshing process. To overcome these limitations, this study proposes an innovative method for industrial CT volume data meshing based on the Iterative Smooth Signed Surface Distance (iSSD) algorithm. This method first refines the segmented voxel model, accurately extracts boundary voxels, and constructs a high-quality point cloud model. By randomly initializing the normals of the point cloud and iteratively updating the point cloud normals, the mesh is reconstructed using the SSD algorithm after each iteration update, ultimately achieving high-quality, watertight, and smooth mesh model reconstruction, ensuring the accuracy and reliability of the reconstructed mesh. Qualitative and quantitative analyses with other methods have further highlighted the excellent performance of the method proposed in this paper. This study not only improves the efficiency and quality of volume data meshing but also provides a solid foundation for subsequent three-dimensional analysis, simulation, and editing, and has important industrial application prospects and academic value.

Univerzální jurisdikce a postih závažných porušení Ženevských úmluv z r. 1949

Violations of the International Humanitarian Law (IHL) are characterized by two sets of legal consequences. Some of them are considered to be so serious that entail not only international responsibility of States for wrongful acts but also criminal responsibility of individua! perpetrators. The criminal repression of grave breaches of IHL, called also war crimes, is not just a matter of domestic law, but it results from international law. Four Geneva Conventions of 1949 have not only defined grave breaches (Articles 50/1, 51/11, 130/111, 147/IV) and provided for their investigation and prosecution, but set up also the obligatory universal jurisdiction of States Parties with respect to the grave breaches (Articles 49/I, 50/11, 129/III, 146/IV). It is a kind of paradox that in 2009, after 60 years from the adoption of the Geneva Conventions, the universal jurisdiction is perceived, by a number of States, mostly developing States, as being problematic. As evidence, there is a recent proposal of the African Union leading to the adoption the UN General Assembly resolution on “The scope of application of the principle of universal jurisdiction”. The universal jurisdiction has been established in customary international law in relation to the crime of piracy since the 17th century. In the second half of the 20th century, this principle has been embodied into treaty law, such as the Geneva Conventions or the 1984 Convention against Torture. The universal jurisdiction has its place in international law. In practice, however, it appears mainly in a narrow, subsidiary form, where a perpetrator is found in the territory of the State and cannot be extradited to another State. Lt is linked to the treaty obligation aut dedere aut judicare. On the contrary, the absolute universal jurisdiction is rather exceptional and has permissive rather than obligatory nature. The obligatory universal jurisdiction, as set up in the Geneva Conventions, is rare and in practice hardly enforced. The primary jurisdiction rests with the States applying territorial or persona! jurisdiction. The principle of universality is a kind of safeguard against impunity of certain crimes based on a horizontal complementarity. Its impact has to be assessed in the light of the current development of international law, including the ad hoc tribunals and the International Criminal Court. The binary obligation aut dedere aut judicare has been completed with a surrender as the third possibility.

Cleaning Robots: A Review of Sensor Technologies and Intelligent Control Strategies for Cleaning

ABSTRACTCleaning robots have revolutionized the way spaces and surfaces are cleaned, accessing areas that are often difficult for humans to reach. A significant segment of the cleaning robot industry is dedicated to home cleaning robots, which have undergone numerous enhancements since their initial introduction. Through extensive research and development efforts, the application scope of cleaning robots has expanded beyond floors to encompass walls, staircases, pools, tanks, ventilation ducts, windows, and other surfaces. These robots have seen improvements in cleaning effectiveness through the integration of new designs, technologies, and control methods. This review paper presents a comprehensive analysis of cutting‐edge cleaning robots recently developed, exploring various sensor technologies and intelligent control strategies employed to enhance cleaning efficiency. Additionally, the paper discusses the challenges associated with deploying these robots in real‐world scenarios.

Determining of the thermophysical properties of materials with indirect control of the temperature of the medium bordering the wall

Temperature control of a medium bounded by walls without direct placement of sensors in it is important to ensure efficient operation of many devices and process units (heat treatment devices, engines, reactors, etc.). However, development of a monitoring method with a wide scope of application requires automation of determination of thermophysical properties of wall and medium materials without specialized tests, which is difficult due to the individual specifics of each object. The paper presents the results of determining the thermophysical properties of materials during indirect monitoring of the temperature of the medium bordering the wall. We investigated the difficulties arising in the automation of determining the properties of materials during adaptation of models of complex heat exchange between the medium and the wall with partially uncertain properties. We used simplified heat exchange models making it possible to present the model signals as increments relative to the initial moment for the time period and to reduce the effect of the mismatch between the functional form of the model and the object on the indirect monitoring results. The parameters unknown during model adaptation were determined based on retrospective data of a limited time domain. It is shown that the model can be used to monitor a generalized estimate of the temperature of the medium near the point of temperature monitoring in the wall with subsequent prediction of the consequences of varying the temperature of the isolated medium. The efficiency of the proposed approach is demonstrated using a case study of heating fireclay bricks. The results obtained can be used in developing universal temperature control methods applicable to various objects.

Readout System for Multipurpose Real-Time and Portable Spectrometer

A ready-to-use spectrometer-based product, which focuses on data acquisition using a BeagleBone board and a Hamamatsu C12666MA spectrometer module, is presented. The device meets stringent requirements, including the ability to measure the visible light spectrum over a wide range of intensities, being compact and lightweight, and having customizable electronics to suit different application needs. The system’s primary component is a Hamamatsu C12666MA spectrometer module with a measurement range of 341 nm to 780 nm, which is supplemented by supporting electronics such as a microcontroller and an analog-to-digital converter. The development encompasses hardware design, the fabrication of a control board, and software development for spectral acquisition and visualization. The software controls the spectral measurement process and facilitates data processing and analysis. The results demonstrate that the designed system can accurately capture spectra and fulfill the specified requirements. Additionally, this work investigates and evaluates the potential migration of the data acquisition system to Field-Programmable Gate Array technology. Such a migration offers several advantages, including real-time processing, parallel data handling capabilities, reduced latency, and greater flexibility in adapting to various spectrometer configurations, as well as the possibility to work in a synchronized way with other devices. These improvements would significantly expand the system’s potential applications in real-time spectroscopy and other demanding optical measurement tasks. The proposed system thus provides a foundation for future enhancements, which could exploit Field-Programmable Gate Array technology, potentially revolutionizing the efficiency and application scope of portable spectrometry devices.

Methods (techniques) of legal interpretation in the practice of the Сourt of Justice of the EU

The Court of Justice of the European Union (CJEU) uses a variety of tools in its activities, among which the most important are the methods of interpretation. Using a whole range of methods (methods) of interpretation, the CJEU fills existing gaps in the law or clarifies the meaning and scope of application of the rules of European Union law. The CJEU uses methods of interpretation in its legal interpretation activities that are used in both national and international law. However, their use in the interpretation of European Union law is somewhat different. Based on the analysis of the case law of the CJEU, researchers distinguish a wide range of methods of interpretation, among which the main ones are philological (linguistic), systemic, teleological, historical, etc. The combination of these methods allows for the adaptation of EU law to changing conditions and unification of its multilingual nature. The work is focused on the most commonly used methods of interpretation: philological, systemic and teleological. The philological interpretation is applied by the CJEU somewhat differently than in the generally accepted classical sense. This is a consequence of the multilingual nature of EU law, which influences both the procedure and the order in which this method of interpretation is used. The systemic method emphasizes the need for an interpretation that would allow EU legal norms to be integrated into a coherent and consistent framework within the complex system of EU legal sources, taking into account the hierarchy of primary and secondary law. In this regard, the general principles of EU law are of particular importance. As a result of the Court of Justice of the European Union’s application of the systemic interpretation mechanism, the unification of the understanding of EU law within the legal systems of various member states is ensured. Teleological interpretation in the practice of the CJEU lays the foundation for case law, considering the presence of extensive preambles in EU legal acts. An analysis of the ways, methods and practices of interpretation of EU law is necessary to prepare the national legal system and national courts for cooperation within the framework of the CJEU.

Transaminases: high-throughput screening via a ketone-fluorescent probe and applications

Transaminases are a class of enzymes that catalyze the transfer of amino between amino acids and keto acids, playing an important role in the biosynthesis of organic amines and the corresponding derivatives. However, natural enzymes often have low catalytic efficiency against non-natural substrates, which limits their widespread applications. Enzyme engineering serves as an effective approach to improve the catalytic properties and thereby expand the application scope of transaminases. In this study, a high-throughput screening method for transaminases was established based on the fluorescent color reaction between methoxy-2-aminobenzoxime (PMA) and ketones. According to the changes in fluorescence intensity, the concentration changes of ketones could be easily monitored. The efficiency, sensitivity, and accuracy of the screening method were improved by optimization of the system. With 4-hydroxy-2-butanone as the substrate, the mutant library of the transaminase from Actinobacteria sp. was established and a mutant with increased activity was successfully obtained, which improved the production efficiency of (R)-3-aminobutanol by enzyme-catalyzed synthesis. This study laid an important foundation for efficient screening, modification, and application of transaminase.

The Induction of L-lysine-α-Oxidase from Trichoderma Harzianum Rifai by Metabolic Products of Brevibacterium sp. and the Improvement of Its Isolation and Purification Techniques

Background: The enzyme L-lysine-α-oxidase from Trichoderma harzianum Rifai is a promising anticancer, antifungal and antibacterial agent. Intensive exploring of its physico-chemical properties and possible ways of application requires sufficient amounts of the protein which in turn depends on good techniques of cultivation of the micro-organism producer, enzyme soft isolation and purification, and storage. Methods: An improved method has been suggested for isolation and purification of the enzyme. A specific combination of column sorbents was adapted and gradient elution with sodium chloride was applied to elevate the yield of the enzyme. The inductive influence of Metabolic Products (MP) of the Brevibacterium species, along with fungal metabolites of Ulocladium sp. and Trichoderma sp. was tested. The enzyme activity assay was based on the detection of oxidized dimethylbenzidine in a peroxidase reaction coupled with an L-lysine-α-oxidase reaction. Some enzyme properties were additionally explored. Results: The upgraded technique of isolation and purification resulted in a yield of enzyme of about 79%. All strains of Brevibacterium sp. proved to be potent enhancers of L-lysine-α-oxidase activity and concomitant activities. The induced enzyme appeared to be less specific but more thermostable. Possible application scopes for the enzyme with modified properties are discussed. Phosphate buffer solution (pH=5.6) appeared to be the best one for long-term storage of the enzyme. Conclusion: A significant inducing effect of MP of Brevibacterium sp. on L-lysine-α-oxidase has been detected, and its isolation and purification techniques have been improved.

A Generalized Shear Lag Model for the “Brick-Mortar” Staggered Composite With Arbitrary Soft Phase Contents

Abstract Although the mechanical mechanisms of staggered biological composites are widely investigated, each existing model has its own application scope. In order to comprehensively characterize the mechanical properties of the staggered composite with arbitrary soft phase content, a generalized shear lag model is established, in which the soft phase may simultaneously bear the tension and shear loads. A novel approach of considering the soft phase as virtual layered composites composed of sub-soft and sub-hard phases is developed. The sub-hard phase has zero thickness and undergoes tensile load, while the sub-soft phase endures shear load. Accurate stress fields in the staggered composite can be well achieved with the new approach. Two simplified models are further proposed based on the generalized shear lag model. Comparison with the finite element results shows that the shear stress in the end soft phase has little effect on the mechanical performance of the staggered composite; while the normal stress in the interlayer soft phase and the variation of shear stress in the thickness direction of interlayer soft phase must be considered for the staggered composite with high interlayer soft phase content. Furthermore, the applicable scopes of the existing typical partition models are determined by comparing the effective Young's modulus predicted by the generalized model, the finite element calculation, and the partition models. The obtained results could be helpful for the precise design of composite materials with high mechanical properties.

Fractional Dynamical Behaviour Modelling Using Convolution Models with Non-Singular Rational Kernels: Some Extensions in the Complex Domain

This paper introduces a convolution model with non-singular rational kernels in which coefficients are considered complex. An interlacing property of the poles and zeros in these rational kernels permits the accurate approximation of the power law function t−ν in a predefined time range, where ν can be complex or real. This class of model can be used to model fractional (dynamical) behaviours in order to avoid fractional calculus-based models which are now associated with several limitations. This is an extension of a previous study by the author. In the real case, this allows a better approximation, close to the limits of the approximation interval, compared to the author’s previous work. In the complex case, this extends the scope of application of the convolution models proposed by the author.

Direct repeat region 3' end modifications regulate Cas12a activity and expand its applications.

CRISPR-Cas12a technology has transformative potential, but as its applications grow, enhancing its inherent functionalities is essential to meet diverse demands. Here, we reveal a regulatory mechanism for LbCas12a through direct repeat (DR)region3' end modifications and de-modifications, which can regulate LbCas12a's cis- and trans-cleavage activities. We extensively explored the effects of introducing phosphorylation, DNA, photo-cleavable linker, DNA modifications at the DR 3' end on LbCas12a's functionality. We find that the temporary inhibitory function of Cas12a can be reactivated by DR 3' end modification corresponding substances, such as alkaline phosphatase (ALP), immunoglobulin G (IgG), alpha-fetoprotein (AFP), DNA exonucleases, ultraviolet radiation, and DNA glycosylases, which greatly expand the scope of application of Cas12a. Clinical applications demonstrated promising results in ALP, AFP, and trace Epstein-Barr virusdetection compared to gold standard methods. Our research provides valuable insights into regulating LbCas12a activity through direct modification of DR and significantly expands its potential clinical detection targets, paving the way for future universal clustered regularly interspaced short palindromic repeats (CRISPR) diagnostic strategies.

Circularity in polydiketoenamine thermoplastics via control over reactive chain conformation.

Controlling the reactivity of bonds along polymer chains enables both functionalization and deconstruction with relevance to chemical recycling and circularity. Because the substrate is a macromolecule, however, understanding the effects of chain conformation on the reactivity of polymer bonds emerges as important yet underexplored. Here, we show how oxy-functionalization of chemically recyclable condensation polymers affects acidolysis to monomers through control over distortion and interaction energies in the rate-limiting transition states. Oxy-functionalization of polydiketoenamines at specific sites on either the amine or triketone monomer segments increased acidolysis rates by more than three orders of magnitude, opening the door to efficient deconstruction of linear chain architectures. These insights substantially broaden the scope of applications for polydiketoenamines in a circular manufacturing economy, including chemically recyclable adhesives for a diverse range of surfaces.

Research on Radionuclide Identification Method Based on GASF and Deep Residual Network

In nuclide identification, traditional methods based on nuclide library comparisons rely on the identification of characteristic peaks, often overlooking the full spectrum information, which leads to cumbersome operations and low efficiency. In recent years, machine learning and deep learning techniques have been introduced into the field of nuclide recognition to improve identification efficiency; however, most existing methods fail to effectively extract deep features from the data. To address this issue, this paper proposes a method that integrates the Gram Angular Summation Field (GASF) algorithm with a Deep Residual Network (ResNet) for processing nuclide energy spectrum data. First, the GASF algorithm is used to transform one-dimensional spectral data into two-dimensional images, thereby fully extracting spatial features from the data. Then, these two-dimensional images are input into the ResNet model, where features are automatically extracted through multiple convolutional layers. Finally, the Softmax layer is used for nuclide classification. Experimental results demonstrate that the proposed method can effectively improve both the accuracy and efficiency of nuclide identification; the recognition accuracy on the simulated data reaches 99.5%, and, when tested with actual measurement data containing unknown radionuclides, the model still achieves a high accuracy of 92.6%. This study shows that the combination of deep learning and signal processing techniques can significantly improve the accuracy and application scope of nuclide identification, offering substantial practical value.

Clinical cases of the use of ESPB as a component of combined anesthesia in patients with liver resection operations

This scientific work is devoted to the topical and applied issue of modern anesthesiology – intensive care – rational anesthesia of laparoscopic liver resections. The transformation of surgical access from «open» to minimally invasive – laparoscopic and robot–assisted – encourages anesthesiologists to search for new methods of prolonged postoperative analgesia. The tendency of modern anesthesiology to limit the use of opioids and the popularization of ultrasound technologies expand the scope of application of myofascial blockades in various fields of surgery. The techniques are safe and effective and can be implemented in various groups of patients, in particular in those who has contraindications to neuroaxial block. Currently, the most commonly used method of anesthetic provision is combined anesthesia –general anesthesia and epidural analgesia. It should be remembered about the features of surgical interventions on the liver and the associated risk of developing massive blood loss syndrome, which increases the frequency of post-operative, primarily hemorrhagic complications, after the use of neuroaxial techniques of prolonged analgesia. The sympatholytic effect of local anesthetics with prolonged epidural infusion is well known, in some cases provoking hemodynamic instability, and, as a result, the need for monitoring the patient in the intensive care unit, as well as increasing the length of hospital stay in general. This circumstance contradicts the trend of modern surgery towards rapid and accelerated recovery after surgery. The above together is economically unprofitable and does not meet the requirements of modern protocols. An in-depth analysis of clinical practice led the authors to the idea of using myofascial blocks (in particular, erector spinae plane block), which have positive qualities of neuroaxial techniques, but are characterized by a better safety profile.

Distributed Inference Models and Algorithms for Heterogeneous Edge Systems Using Deep Learning

Computations performed by using convolutional layers in deep learning require significant resources; thus, their scope of applicability is limited. When deep neural network models are employed in an edge-computing system, the limited computational power and storage resources of edge devices can degrade inference performance, require a considerable amount of computation time, and result in increased energy consumption. To address these issues, this study presents a convolutional-layer partitioning model, based on the fused tile partitioning (FTP) algorithm, for enhancing the distributed inference capabilities of edge devices. First, a resource-adaptive workload-partitioning optimization model is designed to promote load balancing across heterogeneous edge systems. Next, the FTP algorithm is improved, leading to a new layer-fused partitioning method that is used to solve the optimization model. The results of simulation experiments show that the proposed convolutional-layer partitioning method effectively improves the inference performance of edge devices. When five edge devices are used, the speed of the proposed method becomes 1.65–3.48 times those of existing algorithms.

Ensemble Learning Layer for Wayang Recognition using CNN-based ResNet-50 and LSTM

Wayang is commonly used to tell epic stories of Mahabharata and Ramayana, as well as local legends and myths. There are various types of wayang, such as wayang kulit (made of buffalo or goat leather), wayang golek (made of wood), and wayang klithik (combination of leather and wood). Although it indicates cultural richness, such diversity also makes it difficult for the general public to identify the character of wayang they are seeing because each type has unique characteristics and details. Recognizing wayang characters is a challenging task due to their intricate designs and subtle variations. This research addresses this problem by leveraging machine learning technology, specifically CNN-based classification methods, to accurately identify wayang characters. This study proposed a novel method that integrates ResNet-50 transfer learning with LSTM, enhancing the model's ability to capture both spatial and sequential features of wayang images. The proposed model achieved an impressive accuracy of 97.92%, with precision, recall, and F1-scores all reaching 100%. Despite the extended training time of 188 minutes and 21 seconds, the results demonstrate the model's superior performance. This advancement can significantly aid in the preservation and educational dissemination of Indonesian cultural heritage. Future research can focus on optimizing the training process to reduce the time while maintaining or even improving the accuracy, potentially expanding the model's application scope and effectiveness.

Psychosynthesis in Positive Psychotherapy

This article examines the integration of psychosynthesis and positive psychotherapy as a holistic therapeutic approach. Psychosynthesis, developed by Roberto Assagioli, emphasizes integrating conscious and unconscious aspects of personality to foster personal growth and spiritual fulfillment. Positive psychotherapy, introduced by Nossrat Peseschkian, focuses on activating individual resources to address psychological challenges through a structured, transcultural framework. The integration of these modalities combines psychosynthesis’s spiritual depth with the practical tools of positive psychotherapy, offering a comprehensive strategy for addressing complex clinical issues such as identity crises, existential challenges, and developmental trauma. While highlighting their compatibility, the article also addresses potential risks, emphasizing the importance of systematic frameworks and rigorous training. This synthesis broadens the scope of therapeutic applications, enhancing client-centered, flexible, and effective interventions. The proposed model demonstrates the transformative potential of integrating distinct psychotherapeutic approaches for holistic personal and psychological development.

Prediction models for post-traumatic stress disorder in family members of ICU patients: A systematic review.

Several predictive models have been developed for post-traumatic stress disorder (PTSD) in intensive care unit (ICU) family members. However, significant differences persist across related studies in terms of literature quality, model performance, predictor variables and scope of applicability. This study aimed to systematically review risk prediction models for PTSD in family members of ICU patients, to make recommendations for health care professionals in selecting appropriate predictive models. China National Knowledge Infrastructure, VIP database, Wanfang database, SinoMed, PubMed, Web of Science, Cumulative Index to Nursing and Allied Health Literature, The Cochrane Library, Embase and OVID were searched from inception to 1 May 2024. Two independent researchers conducted literature screening, data extraction and applied a risk of bias assessment tool for predictive models to evaluate included studies. The systematic review was registered on PROSPERO (registration number: CRD42024560815). Seventeen studies were included, with sample sizes ranging from 32 to 2734. Incidence rates of outcomes ranged from 1.6% to 63.6%. The most frequently used predictors were relative's female sex, longer duration of ICU stay, patient's death in the ICU and type of relationship with the patient. Two models reported area under the receiver operating characteristic curve (AUC) values ranging from 0.73 to 0.74; only three models reported calibration, and one study conducted internal validation. Overall, the 17 studies showed good applicability but exhibited a high risk of bias, particularly in data analysis. Research on predictive models for PTSD risk in family members of ICU patients is in the developmental stage. Future studies should validate existing models or develop high-performance localized predictive models. PTSD can have a significant impact on the families of ICU patients, making early identification of high-risk populations essential for health care professionals to implement timely interventions.

High-entropy engineered BaTiO3-based ceramic capacitors with greatly enhanced high-temperature energy storage performance

Ceramic capacitors with ultrahigh power density are crucial in modern electrical applications, especially under high-temperature conditions. However, the relatively low energy density limits their application scope and hinders device miniaturization and integration. In this work, we present a high-entropy BaTiO3-based relaxor ceramic with outstanding energy storage properties, achieving a substantial recoverable energy density of 10.9 J/cm3 and a superior energy efficiency of 93% at applied electric field of 720 kV/cm. Of particular importance is that the studied high-entropy composition exhibits excellent energy storage performance across a wide temperature range of −50 to 260 °C, with variation below 9%, additionally, it demonstrates great cycling reliability at 450 kV/cm and 200 °C up to 106 cycles. Electrical and in-situ structural characterizations revealed that the high-entropy engineered local structures are highly stable under varying temperature and electric fields, leading to superior energy storage performance. This study provides a good paradigm of the efficacy of the high-entropy engineering for developing high-performance dielectric capacitors.

Synthesis and Properties of Biodegradable Copolyester with Phenyl Side Groups

AbstractPoly(butylene adipate terephthalate) (PBAT) is a biodegradable copolyester that has garnered significant attention in recent years. However, its application is limited by low tensile strength and elastic modulus. Current research focuses on copolymerization modifications aimed at enhancing PBAT's performance. In this study, a novel copolyester with phenyl side groups, poly(butylene‐co‐3‐phenoxy‐1,2‐propylene adipate‐co‐terephthalate) (PBPAT), is synthesized via melt polycondensation. The impact of varying amounts of the fourth monomer, 3‐phenoxy‐1,2‐propylene glycol (PPDO), on the copolyester's properties is investigated. FTIR and NMR spectroscopy confirm the structure and composition of PBPAT. The molecular weight, thermal properties, mechanical properties, processing characteristics, and hydrophilicity of the copolymers are comprehensively evaluated. The results indicate that PPDO does not affect the crystal structure of PBAT. However, the performance of PBPAT is significantly influenced by the PPDO content, which the optimal mechanical properties are achieved with 12.5% PPDO, demonstrating a tensile strength of 26.1 MPa and an elastic modulus of 220.6 MPa. Furthermore, PBPAT copolyesters exhibit high crystallinity, heat resistance, good hydrophilicity, and superior processability. The novel PBPAT copolyester offers enhanced performance characteristics and holds potential for replace commercial PBAT, thereby expanding the application scope of biodegradable materials.