Basic Components Research Articles

NAVIDRO, a CARES architectural style for configuring drone co-simulation

One primary objective of drone simulation is to evaluate diverse drone configurations and contexts aligned with specific user objectives. The initial challenge for simulator designers involves managing the heterogeneity of drone components, encompassing both software and hardware systems, as well as the drone’s behavior. To facilitate the integration of these diverse models, the Functional Mock-Up Interface (FMI) for co-simulation proposes a generic data-oriented interface. However, an additional challenge lies in simplifying the configuration of co-simulation, necessitating an approach to guide the modeling of parametric features and operational conditions such as failures or environment changes. The article addresses this challenge by introducing CARES, a model-driven engineering and component-based approach for designing drone simulators, integrating the FMI for co-simulation. The proposed models incorporate concepts from component-based software engineering and FMI. The NAVIDRO architectural style is presented for designing and configuring drone co-simulation. CARES utilizes a code generator to produce structural glue code (Java or C++), facilitating the integration of FMI-based domain-specific code. The approach is evaluated through the development of a simulator for navigation functions in an autonomous underwater vehicle, demonstrating its effectiveness in assessing various autonomous underwater vehicle configurations and contexts.

Laboratory investigations of sub-meter resolution telescope with segmented aperture dedicated to CubeSat platform

In current CubeSat observation satellites, the main design constraint is the available space. Standards dictating the unit dimensions of the payload severely restrict the maximum aperture and focal length of the optical instrument. In this paper, the authors present the results of work to produce a novel DeploScope optical system for a CubeSat-type observation satellite with a segmented aperture of the primary mirror deployed in space. The telescope is designed for Earth observation and is expected to find its application in the military, precision agriculture or environmental disaster prevention. The work includes a detailed analysis of the segment aperture effect on image repeatability for different numbers of main mirror segments. Based on it, the optimal configuration of the optical model of the telescope with an aperture of 188.5 mm and a focal length of 1100 mm was selected. Based on this analysis, a so-called laboratory version of the telescope was built, providing the possibility of free correction of each segment of the primary mirror while maintaining a solid stable base for other components of the module. Imaging tests were carried out on the laboratory version of the instrument and the system was optimized for a version suitable for implementation in the payload structure of the microsatellite.

Cohesion measurements between variables and methods using component-based software systems

AbstractThe practice of leveraging previously created software components to progress new software is identified as component-based software engineering (CBSE). Good software engineering design is the foundation of CBSE principles. The black box approach that underpins CBSE hides the execution of components in nature, and the components communicate with one another using strictly delineated interfaces. Component platforms are shared, which lowers the price of creation. To ascertain a system's complexity, various software metrics are employed. For superiority in software intricacy, coupling would be minimal, and cohesiveness must be high. It is predetermined that coupling should be low and cohesion should be increased for refinement in software complexity. We are identifying the combination of different software systems and improving the methods for doing so with our approach. Proposed: Cohm (cohesion of methods) and Cohv (cohesion of variables) are two cohesion metrics that have been proposed. The cohesiveness metrics in this study have been analytically and empirically evaluated, and a comparison has been made between them. Additionally, an effort was made to give the outcomes of an empirical estimation based on the case study. The T-test is used to determine the consequences of the metrics, and Python is used to validate the metrics. Python or R programming and the Matlab tool are used to determine the relationship between various variables and metrics. Findings: The consequence of the current investigation is very encouraging and might be used to estimate the involvedness of the parts. The proportional analysis of the proposed metrics and various cohesion metrics reveals that the suggested metrics are more cohesive than the present metrics, increasing the likelihood that they can be reused when creating new applications.

A metabolomics analysis of inter-species and seasonal trends in ruminant milk: the molecular difference between bovine, caprine and ovine milk

Ruminant milk composition can be impacted by many factors, primarily inter-species differences, but also environmental factors (e.g., season, feeding system and feed composition). Pasture-based feeding systems are known to be influenced by seasonal effects on grass composition. Spring pasture is rich in protein and low in fiber compared with late-season pasture, potentially inducing variability in the composition of some milk metabolites across the season. This study aimed to investigate inter-species and seasonal differences in the milk metabolome across the 3 major commercial ruminant milk species from factories in New Zealand: bovine, caprine and ovine milk. Bovine and caprine raw milk samples were collected monthly for a period of 9 mo (August-April, 2016-2017; bovine n = 41, caprine n = 44 samples); while ovine milk samples were collected for a period of 5 mo (August-January, n = 20 samples). Milk samples were subjected to biphasic extraction, and untargeted metabolite profiling was performed using 2 separate liquid chromatography high-resolution mass spectrometry analytical methods (polar metabolites and lipids). Major differences in milk metabolome were observed between the 3-ruminant species, with 414 of 587 (71%) polar metabolite features and 210 of 233 (87%) lipid features significantly different between species. Significant seasonal trends were observed in the polar metabolite fraction for bovine, caprine and ovine milk (17, 24 and 32 metabolites, respectively), suggesting that the polar metabolite relative intensities of ovine and caprine milk were more susceptible to changes within seasons than bovine milk. There was no significant seasonal difference for the triglycerides (TG) species measured in bovine milk, while 3 and 52 TG species changed in caprine and ovine milk, respectively, across the seasons. Four phosphatidylcholines and 2 phosphatidylethanolamines varied in caprine milk within the season, and 8 diglycerides varied in ovine milk. The inter-species and seasonal metabolite differences reported here provide a knowledge base of components potentially linked to milk physiochemical properties, and potential health benefits of New Zealand pasture-fed dairy ingredients.

FOD-YOLO NET: Fasteners fault and object detection in railway tracks using deep yolo network1

Automated railway security systems prevent train collisions with trackside obstructions that cause accidents in high-speed railways. Rail safety is being improved and accident rates reduced through continuous research. A rapid advancement in deep learning has promoted new possibilities for research in this field. In this work, a novel deep learning-based FOD-YOLO net is proposed for detecting the fasteners faults and objects in the railway tracks. There are two basic components in the deep learning-based YOLOv8: the backbone and the head. YOLOv8 utilizes an improved version of the CSPDarknet53 network for detecting objects on the railway track. The head of YOLOv8 consists of EfficientNet with various convolutional layers with squeeze and excitation blocks for detecting any defect in the track fasteners. These layers are liable for detecting the objectness scores, bounding boxes and class probabilities structured with fully connected layers for the objects and faults in tracks. Based on the results from the Yolo network, the alert message is sent to the loco pilot to avoid accidents using fuzzy logic. The experimental fallouts of proposed FOD-YOLO net achieve higher accuracy and yields better evaluation results with 98.14% accuracy, 98.84% precision and 95.94% recall. From the experimental results, the FOD-YOLO net improves the overall accuracy range by 5.44%, 4.72%, 0.73%, and 13.18% better than Fast RCNN, YOLOv5s-VF, YOLO-GD, and 2D-SSA + Deep network respectively.

Performance Analysis of Application of BIM Technology and Two-Way Progressive Optimization Algorithm in Energy-Saving Design of Residential Buildings Based on BIM Technology

The current residential energy-saving design is lagging behind, and lack of systematic design methods and scientific technical means seriously restricts process of improving quality of residential buildings in China. With development and application of digital information technology in construction field, BIM technology has brought new opportunities construction industry, and building performance data has become information basis for scientific promotion of energy conservation. This paper uses BIM technology as a platform to establish an information base of common building materials and components in Chongqing through literature research, field studies, summarization, and application practice, and to help architects make wise decisions at early design stage by using "one-click" scheme comparison and design evaluation to avoid a large number of potential energy consumption problems at a later stage, It greatly improves energy efficiency and design quality of buildings.

Chemical, nutritional and sensory characteristics of milk and cheeses obtained from autochthonous, cosmopolitan, and crossbred goats

Abstract The aim of this study was to analyse the milk parameters and the chemical, nutritional, and sensory characteristics of cheeses made from the milk of three groups of goats: native Carpathian goat, Anglonubian and crossbred goats (Saanen × Alpine). For this study, milk was collected three times during the grazing season and was processed into rennet semi-hard cheeses according to a traditional recipe in a pre-farm cheese dairy. Samples of the milk were subjected to physicochemical analyses. The chemical composition, vitamin, macronutrient content, and fatty acid profile of the cheeses were determined. The cheeses were also subjected to organoleptic evaluation. The results showed that the factors studied, such as breed and month of milking, had a significant effect on the physicochemical properties and chemical composition of goat milk. The month of milking affected all the milk characteristics studied, with September having the highest values of acidity, dry matter, fat and protein content. The month did not affect the level of basic components in the cheeses, but it influenced the content of vitamins and macronutrients; the cheeses produced in September had significantly higher levels of Mg, K, and vitamin E. The month of milking had, as did the breed of goat, a significant effect on the profile of most fatty acids in the cheeses. As for the breed factor, it affected both the chemical composition and sensory value of the cheeses. Cheeses made from the milk of the native Carpathian goat had the best health-promoting properties: a more favourable fatty acid profile, the lowest PUFA-6/3 ratio, and the lowest atherogenic index. According to the panellists, cheese from the milk of Carpathian goats also had the most distinctive aroma, typical for goat cheese. The research shows that the cheeses made from the milk of the native Carpathian goat had the best health-promoting properties, which confirms the need for further popularisation of the breed and can be the basis for marketing more products.

Zirconia-incorporated yttria with a Lewis pair of acid–base surface sites for chemoselective dehydration of alcohols into alpha olefins

Alpha olefins are currently made by ethylene oligomerization to a broad range of carbon number. An alternative conversion is selective alcohol dehydration in which the conventional catalyst development focused on the addition of any basic components into acidic supports. We herein demonstrated that the Zr4+ addition to Y2O3 (acid-to-base addition) was more effective than the Y3+ addition to ZrO2 in alcohol dehydration to alpha olefins. The zirconia-incorporated yttria with 4 mol% Zr (named 4ZIY) was structurally more stable than the yttria-stabilized zirconia (YSZ) counterpart. Moreover, the 4ZIY showed a high purity of alpha olefins when various C4 and C6 alcohols were used. Catalyst characterization works revealed that the 4ZIY contains a large amount of strong Lewis base sites, which is associated with oxygen vacancy, with a little Lewis acid sites. Consequently, the 4ZIY is suggested to have the favorable acid–base pair for the conversion of alcohols to alpha olefins.

UIGuider: Detecting Implicit Design Guidelines Using a Domain Knowledge Graph Approach

Mobile application developers must adhere to a set of design guidelines to ensure consistency in graphical user interfaces (GUIs) and strive for best practices. Violating these widely accepted design guidelines can negatively impact user experience and diminish an application’s market value. Although a few explicit design guidelines outline specific user interface layouts to avoid, substantial design knowledge remains scattered across various web pages. This implicit design knowledge includes design guidelines for UI component usage scenarios, anatomy, fine-grained categorizations, etc. Manually inspecting design guideline violations is knowledge-intensive and time-consuming, demanding high levels of expertise. To address this, we propose UIGuider, a novel approach to automatically constructing a component-based design knowledge graph using multimodal data. UIGuider can discern valuable text containing design guidelines, extract component and concept entities, and establish relationships among them. Our experiments demonstrate the effectiveness and usefulness of UIGuider in automatically detecting implicit design guidelines and constructing domain knowledge graphs. Additionally, the result presentation of a design violation detection tool is optimized. The results of user studies confirm that the use of the knowledge graph and real-world app datasets enhances the overall usability of the tool.

Polyols and polyurethane foams based on chitosans of various molecular weights

AbstractShrinking resources of fossil oil prompt search for other biosphere‐present substrates to obtain polyols, which in turn are basic components to synthesize polyurethane foams (PUF). Widely available examples are biopolymers like starch, cellulose, and chitosan. It has been shown that oligomeric chitosan as well as water soluble chitosan can be applied to obtain polyols and rigid PUF of good performance properties. In this paper, the higher molecular mass chitosans, insoluble in organic solvents and water, were converted to polyols and ultimately into foamed polyurethane plastics. The polyols were characterized by the infrared spectra (IR), 1H‐NMR, and MALDI‐ToF methods. Their properties, such as density, viscosity, surface tension and hydroxyl numbers, were determined. The PUF were obtained from these polyols of various molecular mass. The biodegradable, rigid PUF of enhanced thermal resistance were obtained. Their physical parameters like apparent density, water volume absorption, dimension stability, heat conductance, compressive strength, and heat resistance at 150 and 175°C were studied and compared with those synthesized previously from oligomeric chitosan and water soluble chitosan.

Strategies to enhance stress tolerance in lactic acid bacteria across diverse stress conditions.

Lactic acid bacteria (LAB) hold significant importance in diverse fields, including food technology, industrial biotechnology, and medicine. As basic components of starter cultures, probiotics, immunomodulators, and live vaccines, LAB cells resist a variety of stressors, including temperature fluctuations, osmotic and pH shocks, exposure to oxidants and ultraviolet radiation, substrate deprivation, mechanical damage, and more. To stay alive in these adversities, LAB employ a wide range of stress response strategies supported by various mechanisms, for example rearrangement of metabolism, expression of specialized biomolecules (e.g., chaperones and antioxidants), exopolysaccharide synthesis, and complex repair and regulatory systems. LAB can coordinate responses to various stressors using global regulators. In this review, we summarize current knowledge about stress response strategies used by LAB and consider mechanisms of response to specific stressful factors, supported by illustrative examples. In addition, we discuss technical approaches to increase the stress resistance of LAB, including pre-adaptation, genetic modification of strains, and adjustment of cultivation conditions. A critical analysis of the recent findings in this field augments comprehension of stress tolerance mechanisms in LAB, paving the way for prospective research directions with implications in fundamental and practical areas.

A two-view deep interpretable TSK fuzzy classifier under mutually teachable classification criterion

Most of the existing classification techniques generally requires the consistent distribution assumption between training and testing samples. However, recent results theoretically reveal that enhanced classification performance may be achieved by breaking this assumption and meanwhile managing to satisfy a subtle assumption between a prediction function, training and testing samples. Although such a subtle assumption is too hard to be leveraged as a criterion for designing a single-view classifier, this study as the first attempt exhibits its natural yet distinctive value in designing a two-view classifier. In this study, originating from the inconsistent distribution assumption between training and testing samples, a new mutually teachable classification criterion is proposed, and accordingly a two-view deep interpretable Tagaki-Sugeno-Kang fuzzy classifier called Tvd-TFC is developed. In order to keep both promising classification performance and high interpretability of Tvd-TFC, it simply takes our recent work-- deep Tagaki-Sugeno-Kang fuzzy classifier (D-TSK-FC) as a basic component of each deep sub-classifier for each view. The distinctive novelty of Tvd-TFC exists in that its double deep structures along with two respective views are interchangeably learnt in deep learning manner according to the proposed mutually teachable classification criterion. The proposed learning algorithm can not only minimize the testing error along with each view but also ensure the consistency between two views. Experimental results on two-view datasets demonstrate that the proposed classifier Tvd-TFC realizes enhanced or at least comparable classification performance and simultaneously has better interpretability in contrast to the comparative classifiers.

Non-destructive, whole-plant phenotyping reveals dynamic changes in water use efficiency, photosynthesis, and rhizosphere acidification of sorghum accessions under osmotic stress.

Noninvasive phenotyping can quantify dynamic plant growth processes at higher temporal resolution than destructive phenotyping and can reveal phenomena that would be missed by end-point analysis alone. Additionally, whole-plant phenotyping can identify growth conditions that are optimal for both above- and below-ground tissues. However, noninvasive, whole-plant phenotyping approaches available today are generally expensive, complex, and non-modular. We developed a low-cost and versatile approach to noninvasively measure whole-plant physiology over time by growing plants in isolated hydroponic chambers. We demonstrate the versatility of our approach by measuring whole-plant biomass accumulation, water use, and water use efficiency every twodays on unstressed and osmotically stressed sorghum accessions. We identified relationships between root zone acidification and photosynthesis on whole-plant water use efficiency over time. Our system can be implemented using cheap, basic components, requires no specific technical expertise, and should be suitable for any non-aquatic vascular plant species.

Interdisciplinary educational and methodological support of medical and biological disciplines using the resources of the Technopark of Universal Pedagogical Competencies

Introduction. Changes in the higher pedagogical education system require qualitatively new scientific and methodological support for educational programs and improved methodological support for various forms of students' educational work. In the context of modernization of education, modeling the educational process is to be based on an interdisciplinary approach. Technology parks for universal pedagogical competencies significantly expand the capabilities of teaching methods and provide the opportunity to strengthen the practical interdisciplinary training of the future teacher. Changed learning objectives and means of organizing the educational process require new-generation educational and methodological support where interdisciplinary educational and methodological complexes play the leading role, which allows implementing the conceptual approaches of the Federal State Educational Standard of higher education. Materials and methods. The study employed the following methods: theoretical analysis of publications on interdisciplinary educational and methodological support for biomedical disciplines, including identification of the main methodological approaches and principles, basic provisions and components of the integrative approach within such disciplines; a survey of students for assessing the effective implementation of the developed interdisciplinary educational and methodological support and student satisfaction with the quality of teaching biomedical disciplines. 56 undergraduate students (2-5th year) of South Ural State Humanitarian and Pedagogical University (Russian Federation) took part in the survey. Results. The subject of this study is the methodology for forming and developing students’ professional competence using the integrative approach and the resource base of the Technopark of Universal Pedagogical Competencies when studying biomedical disciplines. A means of implementing interdisciplinary learning is interdisciplinary tasks and assignments, including those performed using Technopark equipment (digital neurotechnology laboratory BiTronics Lab, interactive anatomical table Pirogov, binocular digital microscopes with the possibility of video and photo recording of the studied objects. The student survey showed that 85.7% of respondents consider it necessary to use a wider interdisciplinary approach in studying biomedical disciplines to improve the quality of education. Conclusion. Interdisciplinary educational and methodological support of medical and biological disciplines in training biology teachers using the capabilities of the Technopark of Universal Pedagogical Competencies and the pedagogical Quantorium of South Ural State Humanitarian Pedagogical University allows students to develop natural science literacy and provides professional training for a future biology teacher in accordance with the needs of society in the context of modernizing higher pedagogical education.

Применение резонансно-рефлектометрического метода для поиска GPS-трекеров

The principles of operation of the advanced resonant-reflectometric method for detecting GPS trackers and its advantages are described. It is shown that the detection of the re-radiated signal depends on parameters such as the power level and duration of the probing pulses, the frequencies of the probing pulses relative to the resonance frequency of the GPS tracker's input tract; the quality factor of the GPS tracker's input tract and the distance from the scanning antenna to the GPS tracker. A block diagram for experimental validation and determination of the optimal parameters for detecting the re-radiated signal is proposed, and a component base for its implementation is selected. A prototype module of a hardware-software complex based on the resonant-reflectometric method has been developed. The obtained experimental data confirmed the viability of the resonant-reflectometric method for detecting GPS trackers.

Efficient Software Development Process Using Component-Based and ORM

The software development process has many variations. Each software development technique has its own advantages and disadvantages. There are efficient development processes and some could be more efficient. This research aims to build a web-based application efficiently utilizing component-based and ORM with a case study of financial management applications on community radio. This research begins with data collection through observations and interviews, requirement analysis, and system design, implementation, and testing. This research shows that combining component-based software development and object-relational mapping (ORM) can increase software development efficiency compared to non-component-based and pure SQL.

Unveiling vocabulary teaching and learning beliefs of teachers and learners in an EFL context

Vocabulary is often considered as a key predictor of second language ability, and how teachers and learners’ beliefs and conceptualizations about vocabulary affect their teaching and learning has recently gained unprecedented momentum in the field of second language education. However, despite their importance, there is a paucity of research that has combined data from teachers and learners to illuminate their beliefs and conceptualizations. The main aim of this quantitative study is to combine data from English language teachers and learners to explore their beliefs and conceptualizations about vocabulary learning and knowledge. The study voluntarily recruited 113 learners and 91 teachers from a major Saudi university to fill out an online questionnaire. The findings revealed that both teachers and learners generally valued vocabulary on a par with grammar, listening, speaking, reading, and writing, and that both groups showed a general understanding of the basic components of word knowledge; however, their beliefs differed significantly. The results also indicated that despite showing an awareness of the role of textbooks and the incidental approach to vocabulary learning, there were significant differences in teachers and learners’ beliefs. The study concluded with a range of suggested implications, as well as suggestions for further studies on how to address the present lacunae in the field.

Distributional ecology: Opening new research windows by addressing aggregation‐related puzzles

AbstractAimDistribution of species is one of the most elementary but fundamental biodiversity patterns, yet too many puzzles remain unsolved. In most cases, distribution of species is not random, but presents some degree of aggregation. Accordingly, the term ‘distributional aggregation’ is prevailingly used in ecology and evolutionary biology to reflect the non‐random distribution characteristic of species in space and time. However, its meanings are multiform and can be decomposed into a variety of components.LocationGlobal.MethodsIn this paper, through synthesizing historical literature and comparing relevant meanings of distributional aggregation under different contexts, we summarize the current statistical metrics in detecting and evaluating distributional aggregation that are suitable for different field‐survey methods, study models and sampling scales. In particular, we explore the concept under the multi‐species setting for which few conceptual advances and statistical methods have been developed.ResultsWe propose pure data dispersion and spatiotemporal proximity, as two basic components of distributional aggregation. We further explore three advanced components of distributional aggregation: orthogonal, hierarchical and parallel components that can simultaneously link sampling taxa, sampling sites and sampling methods.Main ConclusionsWe hope the systematic review can serve as a potentially useful primer to ecologists for better understanding and investigating complex and new distributional patterns of biological diversity. We further provide informative guides on developing new statistical methods and metrics. We also discuss useful simulation algorithms for generating diverse distributional aggregation patterns of species, aiming to help ecologists to test and compare the performance of different metrics related to diversity and distribution patterns of species.

Variables related to the stability of soil macro and microaggregates of a toposequence in the Brazil south region

Soil aggregates are the basic components of soil structure, being important to its environmental properties and functions. The objective of this study was to investigate the variables related to the aggregates stability, measured by the method of dry and wet sieving and by applying ultrasound energy, in three different soils of a toposequence in southern Brazil. The study was performed in three soils sampled in the city of Pinhais / PR: i) Oxisol (top slope); Ii) Inceptisol (medium third) and; Iii) Gleisol (floodplain). The aggregates stability was determined measured by the method of dry and wet sieving (macroaggregates), as well as by applying ultrasound energy (microaggregate). The results were correlated with soil chemical, physical and mineralogical attributes. The organic matter, the low crystallinity Fe oxides and kaolinite were the most important variables for the profile structural stability. In turn, the soil texture did not show a direct relation with soil aggregation. The Gleisol show highest structural stability, followed by Oxisol and Inceptisol.

Paulownia trees as a sustainable solution for CO2 mitigation: assessing progress toward 2050 climate goals

Due to the progressive climate change on our planet, scientists are interested in solving this issue since it threatens not only certain regions or countries but also the world’s ecosystems and economies. Therefore, minimizing carbon dioxide (CO2) emissions and reducing atmospheric levels are global priorities. Thus, it is necessary at this moment to develop an appropriate approach to reduce or stabilize CO2 levels in the atmosphere. However, CO2 capture projects are long-term, low-profitable, and high-risk environmental projects. Consequently, it is necessary to find an appropriate and sustainable CO2 capture approach that is efficient in reducing atmospheric CO2 levels while having a safe impact on the environment. Although carbon (C) is the key basic component used to produce biological compounds by photosynthetic organisms in terrestrial plants, the C pathway is a key factor affecting the capture of CO2 by photosynthetic organisms. Among photosynthetic organisms, Paulownia, a multipurpose tree, is popular around the world for its timber and its potential role in CO2 sequestration. Paulownia spp. belongs to the Paulowniaceae family and comprises a group of trees. These trees are primarily found in southeastern Asia, particularly in China, and have been intentionally grown for more than two millennia due to their ornamental, cultural, and medicinal value. The number of Paulownia species varies depending on taxonomic classification, ranging from 6 to 17. Among them, Paulownia tomentosa, Paulownia elongata, Paulownia fortunei, and Paulownia catalpifolia are the most widely recognized and favored species. The present review provides a comprehensive technical-economic scenario for the capture of one million tons of CO2 by Paulownia trees (as a terrestrial plant model, grown on 2,400 ha−1). P. tomentosa can be utilized in agroforestry systems to mitigate greenhouse gas (GHG) emissions within urban cities and emphasize the carbon storage potential of agroforestry. In conclusion, Paulownia trees as an environmental mass project showed great encouragement to investors and governments to expand these types of projects to achieve global climate goals by 2050.