Component Library Research Articles

Multigranularity Coverage Criteria for Deep Learning Libraries

ABSTRACTDeep learning (DL) systems are becoming increasingly widely used in safety domains such as self‐driving cars and unmanned aerial vehicles, which arouse natural concerns about their trustworthiness. Underlying DL libraries used in the construction and execution of DL models are involved in the testing processes of DL systems. Therefore, bugs in DL libraries can inevitably cause unexpected behaviours in DL systems. The internal structures of DL libraries are described as APIs with different functionalities, and DL libraries offer model developers access to DL techniques with various API parameter settings. The above characteristics of DL libraries reveal that existing DL coverage criteria are not designed specifically for DL libraries, and traditional software coverage criteria do not apply to DL libraries either. The paper introduces the first set of coverage criteria specifically designed for the systematic measurement of DL libraries across various granularities. APIs, as the fundamental components of DL libraries, are used to define coverage criteria gauging testing adequacy by thoroughly considering their invocation, implementation, parameter quantities and parameter attributes. Furthermore, some properties depicting relations between coverage criteria are investigated. Experiments on the effectiveness of the proposed coverage criteria and comparative analysis are conducted by interval estimate and hypothesis testing techniques for APIs in two well‐known DL libraries. The experimental results demonstrate that the proposed coverage criteria are effective in measuring the test adequacy of DL libraries, and they can be used for the quantitative analysis of test model quality in DL libraries.

Design of a Universal Library of Components for the Development of Medical Systems in the Field of Thyroidology

Reducing the time and cost of developing application information systems by increasing the efficiency of the work performed is one of the main priorities of their modern production. With the development of AI technologies in all areas of activity, including medicine, there is a need for continuous improvement of both the client and server parts of information systems for many different nosologies. The purpose of this study is to form a ready-made library of components for the template design of user interfaces in the field of thyroidology (a field of medicine aimed at diagnosing and treating thyroid diseases) based on the experience gained in the development of several medical information systems for identifying thyroid diseases. Ensuring a conveyor mechanism for developing interfaces for medical information systems is possible only with specialized components of the tool based on a detailed understanding of the specifics of the actions of an endocrinologist. The components of the developed library cover up to 60 % of the component base of the interface of thyroidological systems, and are divided into several parts: for manipulating medical images and texts, annotating, creating input forms, working with tables of medical values, etc. The developed component library has been tested in the creation of intelligent information systems for the work of doctors of ultrasound and cytological diagnostics of thyroid diseases.

Sherpa: An Open-source Python Fitting Package

We present an overview of Sherpa, an open-source Python project, and discuss its development history, broad design concepts, and capabilities. Sherpa contains powerful tools for combining parametric models into complex expressions that can be fit to data using a variety of statistics and optimization methods. It is easily extensible to include user-defined models, statistics, and optimization methods. It provides a high-level user interface for interactive data analysis, such as within a Jupyter notebook, and it can also be used as a library component, providing fitting and modeling capabilities to an application. We include a few examples of Sherpa applications to multiwavelength astronomical data.

A Combinatorial Strategy for API Completion: Deep Learning and Heuristics

Remembering software library components and mastering their application programming interfaces (APIs) is a daunting task for programmers, due to the sheer volume of available libraries. API completion tools, which predict subsequent APIs based on code context, are essential for improving development efficiency. Existing API completion techniques, however, face specific weaknesses that limit their performance. Pattern-based code completion methods that rely on statistical information excel in extracting common usage patterns of API sequences. However, they often struggle to capture the semantics of the surrounding code. In contrast, deep-learning-based approaches excel in understanding the semantics of the code but may miss certain common usages that can be easily identified by pattern-based methods. Our insight into overcoming these challenges is based on the complementarity between these two types of approaches. This paper proposes a combinatorial method of API completion that aims to exploit the strengths of both pattern-based and deep-learning-based approaches. The basic idea is to utilize a confidence-based selector to determine which type of approach should be utilized to generate predictions. Pattern-based approaches will only be applied if the frequency of a particular pattern exceeds a pre-defined threshold, while in other cases, deep learning models will be utilized to generate the API completion results. The results showed that our approach dramatically improved the accuracy and mean reciprocal rank (MRR) in large-scale experiments, highlighting its utility.

Integrated BIM-GA approach for slab formwork design optimization

Purpose Formwork design and construction for reinforced concrete buildings take significant time, effort and money. Construction procedures are time-consuming for designers and costly for the contractor. Poor engineering decisions have led to several workplace accidents in the construction industry. This paper aims to present an integrated building information modeling – genetic algorithm (BIM-GA) model to automate formwork design, 3D visualization and optimization. Design/methodology/approach Data are precisely extracted from a 3D structural model and used to optimize formwork design based on available formwork components and prices. Optimization models are made using GA approach. A library of 3D formwork components was modeled and stored using Revit. The optimized design solution thereafter would be visualized automatically in Revit to readily acquire formwork quantities schedules and shop drawings. Findings A case study illustrating the proposed approach demonstrated that using BIM will reduce formwork design, quantification and drawing time by more than 50% of the traditional approach with safer design and accurate results due to process automation and optimize cost for the given data. Originality/value This research introduces an innovative integrated BIM and GA model for the optimization and automation of slab formwork design, which has significantly benefited the construction industry. The utilization of GA in the optimization process allows for the attainment of an optimal formwork design, ultimately leading to a reduction in construction cost and time.

Comprehensive Analysis of Chemical Ingredients of Waiganfengsha Granule and Absorbed Components in Rat Plasma Based on UHPLC-Q-TOF-MS.

Waiganfengsha Granule, an over-the-counter drug, is commonly used for treating windheat cold and sore throat in clinical settings. However, its material basis of medicinal efficacy is still unclear. In this study, an efficient integrated analytical strategy was established for its chemical and metabolite profiles study. Firstly, to avoid the possible false-positive results of structural elucidation, an in-house component library that contains chemical constituents reported in the literature from the six individual medicines of Waiganfengsha Granule was established. Secondary, mass data post-processing techniques, including precursor ion list and neutral loss filtering, were applied to enhance the identification accuracy. Thirdly, for the rapid characterization of those absorbed components after oral administration in rats, the identified chemical constituents were used as candidate components for the serum analysis. By comparing the retention time and analyzing mass data, the metabolites in rat plasma were identified. As a result, 57 chemical ingredients were identified, including 21 phenolic acids, 9 alkaloids, 2 flavonoids, 5 lignins, 13 saponins, and 7 other compounds. Among these, 12 compounds were unambiguously identified by comparison with reference standards, and 45 were tentatively characterized by analyzing their accurate MS data, MS/MS fragmentation patterns, and also by comparison with those data reported in the literature. Additionally, 46 metabolites were detected and identified in rat plasma. This study is beneficial for understanding the chemical composition and metabolic profiles of Waiganfengsha Granule, and the results obtained might provide a solid basis for further studies on its functional mechanism.

Multiscale modeling for viscoelasticity of woven CFRP considering preforming and curing effects via finite element and long-short term memory analysis

The constitutional model is crucial to model the complex response of woven carbon fiber reinforced plastics (CFRPs) during curing. This study developed a multiscale modeling method to describe the viscoelastic behavior of preformed woven CFRP parts during curing. The essence of the viscoelastic modeling lies in the stiffness matrix, which was predicted via the long-short term memory (LSTM) model. A library of viscoelastic stiffness components for the LSTM model was created through finite element method (FEM) on mesoscopic representation volume elements (RVEs). Specifically, FEM models for RVEs with different configurations were established first, and then utilized for virtual relaxation tests to build the stiffness component library for the woven CFRP. Afterwards, the LSTM model was embedded into the material model for FEM at the part-level. Finally, the prediction accuracy of the multiscale modeling method for viscoelasticity of the woven CFRP samples was validated by experiments with the average error of 6.62%.

Life cycle inventory library for embodied emissions in ventilation components

Technical components are generally poorly described in environmental assessments of buildings. In this work, an extensive library of life cycle inventories for generic ventilation components and dimensions have been developed and documented. Components are described as unit processes and can be used to improve the understanding and coverage of ventilation systems in environmental assessment of buildings, and as potential building blocks for optimization of ventilation system design with minimum life cycle emissions. The ventilation components library has been tested on a modern and energy-efficient office building. Results show that more than 78 % of the climate footprint was covered directly by the library, while the main part of the remaining footprint was associated with non-standardized and building specific components. The coverage was even higher for other environmental impact categories. To assess the coverage of the library and estimate the full impacts for a complete ventilation system, inventories were developed also for the building specific components. Results from this showed an estimated total weight of 6.84 kg/m2 floor area, and a climate footprint of 22.7 kg CO2-eq./m2 floor area. Air handling units and circular ductwork were by far the top contributors with a combined 55 % of climate emissions, with roughly equal shares from both.

PROBLEMS OF CALCULATING THE CARBON FOOTPRINT IN SCOPE 3 USING BIM

The article presents the requirements of the EU EPBD (Energy Performance of Buildings Directive) for counting the carbon footprint (especially in Scope 3) and including it in construction projects from 2030. The obligation to count the carbon footprint will burden mainly designers, who are increasingly using BIM (Building Information Modelling) in the design process. Performing analysis and calculation of the carbon footprint in BIM models is hampered by the lack of nongraphical information on the subject in library components. The paper explains the concept of CO2 in 3 scope, also discusses currently available tools for counting the carbon footprint, and examines how many components available on the Internet already contain non-graphical information on emissions, as well as ideas for implementing this directive. The advantages and disadvantages of these approaches were presented from the perspective of various stakeholders in the planning and investment and construction processes. The aim of the paper was to present possible solutions, ensuring compliance with the EU directive by proposing specific techniques, enabling the calculation of the Scope 3 carbon footprint, using BIM. In addition to a review of existing ideas, an authorial proposal for a national repository of carbon footprint information taking into account all stakeholders was presented.

Design and Development of Component Library for Component-based University Orientation Management System

In the last few years, the orientation and management system of the universities has become more data-driven, information-based and intelligent. This article focuses on designing and implementing an orientation management system for universities. It analyses the actual needs of orientation work and determines the functional goals and design principles of the system. The text focuses on the design and development process of component libraries. This includes component classification, naming conventions, interface design, and re-usability and extensibility design. These aspects provide strong support for the construction of the system. This article elaborates on the methods and processes of system testing and evaluation. Comprehensive testing is conducted to verify the system’s functions and performance, ensuring that it meets actual needs. The research results presented in this article provide a constructive reference for the construction of orientation management systems in universities and lay a solid foundation for the optimization and upgrading of future systems.

Highly efficient fiber to Si waveguide free-form coupler for foundry-scale silicon photonics

As silicon photonics transitions from research to commercial deployment, packaging solutions that efficiently couple light into highly compact and functional sub-micrometer silicon waveguides are imperative but remain challenging. The 220 nm silicon-on-insulator (SOI) platform, poised to enable large-scale integration, is the most widely adopted by foundries, resulting in established fabrication processes and extensive photonic component libraries. The development of a highly efficient, scalable, and broadband coupling scheme for this platform is therefore of paramount importance. Leveraging two-photon polymerization (TPP) and a deterministic free-form micro-optics design methodology based on the Fermat’s principle, this work demonstrates an ultra-efficient and broadband 3-D coupler interface between standard SMF-28 single-mode fibers and silicon waveguides on the 220 nm SOI platform. The coupler achieves a low coupling loss of 0.8 dB for the fundamental TE mode, along with 1 dB bandwidth exceeding 180 nm. The broadband operation enables diverse bandwidth-driven applications ranging from communications to spectroscopy. Furthermore, the 3-D free-form coupler also enables large tolerance to fiber misalignments and manufacturing variability, thereby relaxing packaging requirements toward cost reduction capitalizing on standard electronic packaging process flows.

Ouvrai opens access to remote virtual reality studies of human behavioural neuroscience.

Modern virtual reality (VR) devices record six-degree-of-freedom kinematic data with high spatial and temporal resolution and display high-resolution stereoscopic three-dimensional graphics. These capabilities make VR a powerful tool for many types of behavioural research, including studies of sensorimotor, perceptual and cognitive functions. Here we introduce Ouvrai, an open-source solution that facilitates the design and execution of remote VR studies, capitalizing on the surge in VR headset ownership. This tool allows researchers to develop sophisticated experiments using cutting-edge web technologies such as WebXR to enable browser-based VR, without compromising on experimental design. Ouvrai's features include easy installation, intuitive JavaScript templates, a component library managing front- and backend processes and a streamlined workflow. It integrates with Firebase, Prolific and Amazon Mechanical Turk and provides data processing utilities for analysis. Unlike other tools, Ouvrai remains free, with researchers managing their web hosting and cloud database via personal Firebase accounts. Ouvrai is not limited to VR studies; researchers can also develop and run desktop or touchscreen studies using the same streamlined workflow. Through three distinct motor learning experiments, we confirm Ouvrai's efficiency and viability for conducting remote VR studies.

Forward-Oriented Programming: A meta-DSL for fast development of component libraries

Libraries that implement Domain-Specific Language (DSL) components keep gaining traction when it comes to developing software for specific application domains. However, creating components that can be organically weaved into use cases is an extremely complex task. In this work, we introduce a meta-DSL to assist library development, called Forward-Oriented Programming (FOP). This combines lazy evaluation and aspect-oriented programming principles to align crosscutting component configurations and alter their execution outcomes depending on usage in subsequent code. Theoretical analysis shows that FOP simplifies component development and makes their combination logic learnable by library users. We realize the paradigm with a Python package, called pyfop, and conduct a case study that compares it with purely functional and object-oriented library implementations. In the study, source code quality metrics demonstrate reduced time and effort to write library components, and increased comprehensibility. Configurations are shared without modifying distant code segments.

Comparison of culture-dependent and -independent bacterial detection results on nasal swabs in dogs with nasal discharge.

The role of bacterial communities in the pathophysiology of canine nasal disease is still unclear. How and when to treat dogs with suspected secondary bacterial rhinitis and on which test to rely before making a decision to treat with antimicrobials has not been established. The objective is to compare the results of bacterial identification using agar-plate cultures and 16S rRNA gene amplicon sequencing in dogs with nasal discharge suspected to be of bacterial origin. Twenty-nine client-owned dogs presented for investigation of nasal disease were included in the study. Paired swabs were collected from the same affected nasal cavity. One swab was streaked on 4 agar media (Columbia Blood Agar, MacConkey, Chapman and Edward's). The other swab was stored in a sterile cryotube at -80°. Extracted DNA underwent a polymerase chain reaction targeting the V1-V3 region of the 16S rRNA gene. At least one of the species detected by amplicon sequencing with a relative abundance of >10% was also identified by culture in 14 cases (48.3%), in association with marked predominance of one taxon (>80% relative abundance) in six of 14 cases. In 12 dogs (41.4%), the cultured isolates were rare or undetected components of the corresponding sequence libraries. A negative culture in the face of bacterial predominance (>50% relative abundance) of a potentially pathogenic bacteria detected by sequencing occurred in 17% (n=5) of cases; however, the use of other agar media may have decreased this percentage. Standard culture does not reliably predict the bacterial profile detected by 16S rRNA gene amplicon sequencing.

A fast and cost-effective integer restoring division hardware

In this work, the circuit for unsigned integer restoring division divides each bit in one clock cycle, resulting in total delay cycles equal to the number of bits (n) plus an extra cycle for the final result. Thus, the proposed n-bit division circuit has an access time of (n+1) clock cycles. The hardware cost includes a subtractor and six registers, aligned with a two-phase clocking system. The novelty lies in the shift register, which shifts to the left during the high phase and restores data during the low phase of the clock. Although there are two phases of operations, the subtractor completes a full cycle for computation. As a result, the subtractor's delay time determines the clock period. The control unit is a simple ring shifter triggered at the clock's low phase. The simulation results obtained from synthesized HDL and HSPICE at 90 nm TSMC technology validate the circuit's functionality and characteristic feature of a performance rate of O(n). Using a standard CMOS library component, the 32-bit arithmetic divider requires 33 ns to produce exact Quotient and Remainder values. The circuit operates at a 1 GHz clock cycle and consumes a power of 752 µW. The total number of transistors used in this circuit is 8,860.

Monolithic back-end-of-line integration of phase change materials into foundry-manufactured silicon photonics

Monolithic integration of novel materials without modifying the existing photonic component library is crucial to advancing heterogeneous silicon photonic integrated circuits. Here we show the introduction of a silicon nitride etch stop layer at select areas, coupled with low-loss oxide trench, enabling incorporation of functional materials without compromising foundry-verified device reliability. As an illustration, two distinct chalcogenide phase change materials (PCMs) with remarkable nonvolatile modulation capabilities, namely Sb2Se3 and Ge2Sb2Se4Te1, were monolithic back-end-of-line integrated, offering compact phase and intensity tuning units with zero-static power consumption. By employing these building blocks, the phase error of a push-pull Mach–Zehnder interferometer optical switch could be reduced with a 48% peak power consumption reduction. Mirco-ring filters with >5-bit wavelength selective intensity modulation and waveguide-based >7-bit intensity-modulation broadband attenuators could also be achieved. This foundry-compatible platform could open up the possibility of integrating other excellent optoelectronic materials into future silicon photonic process design kits.

Declarative Inversion of Control Configuration in Modern .NET8 Applications

As software systems continue to evolve in complexity and scale, the importance of adopting componentbased architectural paradigms becomes increasingly evident. Inversion of Control (IoC) and Dependency Injection (DI) patterns play important role in managing OO-components dependencies, reduce coupling and enable seamless integration of components. This article explores the theoretical foundations of IoC and DI, shedding light on their practical implementation in modern .NET applications.Standard .NET DI-container has a number of technical limitations: properties injection is not supported, dependencies definitions from keyed services partially breaks IoC principle, and finally lack of declarative way to define components and their dependencies. To address these limitations, it is proposed to implement a special extension for standard DI-container in the form of a component factory. This factory would register components within the container and define their dependencies based on declarative configuration. The configuration can be stored either in a standard (for .NET Core apps) appsettings.json file or loaded from a separate JSON file. In fact, this JSON could be even dynamically generated in specific usage scenarios.The capability to use a declarative configuration for standard DI-container opens up broad possibilities for generative programming. It becomes technically feasible to implement a model-driven development, particularly an approach that leverages the DI-container configuration as the final (execution) model in a chain of transformations of domain-specific models.Modern .NET8 platform assumes that software is assembled from libraries of pre-existing components that are hosted in a standard DI-container that provides suitable runtime environment for them. Practical aspects of applying the Inversion of Control pattern are examined, considering the use of a standard Dependency Injection (DI) container implementation. Existing technological limitations are defined, and a solution is proposed: implementation of declarative configuration of dependencies between components. This approach contributes to a reduced level of coupling between components and facilitates the decomposition of the program into more granular and abstract components – which increases their reusability in consequence.

Research Progress on Sesquiterpenoids of Curcumae Rhizoma and Their Pharmacological Effects.

Curcumae Rhizoma, a traditional Chinese medicine with a wide range of pharmacological activities, is obtained from the dried rhizomes of Curcuma phaeocaulis VaL., Curcuma kwangsiensis S. G. Lee et C. F. Liang, and Curcuma wenyujin Y. H. Chen et C. Ling. Sesquiterpenoids and curcuminoids are found to be the main constituents of Curcumae Rhizoma. Sesquiterpenoids are composed of three isoprene units and are susceptible to complex transformations, such as cyclization, rearrangement, and oxidation. They are the most structurally diverse class of plant-based natural products with a wide range of biological activities and are widely found in nature. In recent years, scholars have conducted abundant studies on the structures and pharmacological properties of components of Curcumae Rhizoma. This article elucidates the chemical structures, medicinal properties, and biological properties of the sesquiterpenoids (a total of 274 compounds) isolated from Curcumae Rhizoma. We summarized extraction and isolation methods for sesquiterpenoids, established a chemical component library of sesquiterpenoids in Curcumae Rhizoma, and analyzed structural variances among sesquiterpenoids sourced from Curcumae Rhizoma of diverse botanical origins. Furthermore, our investigation reveals a diverse array of sesquiterpenoid types, encompassing guaiane-type, germacrane-type, eudesmane-type, elemane-type, cadinane-type, carane-type, bisabolane-type, humulane-type, and other types, emphasizing the relationship between structural diversity and activity. We hope to provide a valuable reference for further research and exploitation and pave the way for the development of new drugs derived from medicinal plants.

Metabolites rapid-annotation in mice by comprehensive method of virtual polygons and Kendric mass loss filtering: A case study of Dendrobium nobile Lindl

With significant advancements in high-resolution mass spectrometry, there has been a substantial increase in the amount of chemical component data acquired from natural products. Therefore, the rapid and efficient extraction of valuable mass spectral information from large volumes of high-resolution mass spectrometry data holds crucial significance. This study illustrates a targeted annotation of the metabolic products of alkaloid and sesquiterpene components from Dendrobium nobile (D. nobile) aqueous extract in mice serum through the integration of an in-houses database, R programming, a virtual metabolic product library, polygonal mass defect filtering, and Kendrick mass defect strategies. The research process involved initially establishing a library of alkaloids and sesquiterpenes components and simulating 71 potential metabolic reactions within the organism using R programming, thus creating a virtual metabolic product database. Subsequently, employing the virtual metabolic product library allowed for polygonal mass defect filtering, rapidly screening 1705 potential metabolites of alkaloids and 3044 potential metabolites of sesquiterpenes in the serum. Furthermore, based on the chemical composition database of D. nobile and online mass spectrometry databases, 95 compounds, including alkaloids, sesquiterpenes, and endogenous components, were characterized. Finally, utilizing Kendrick mass defect analysis in conjunction with known alkaloids and sesquiterpenes targeted screening of 209 demethylation, methylation, and oxidation products in phase I metabolism, and 146 glucuronidation and glutathione conjugation products in phase II metabolism. This study provides valuable insights for the rapid and accurate annotation of chemical components and their metabolites in vivo within natural products.

Using model-driven engineering to automate software language translation

The porting or translation of software applications from one programming language to another is a common requirement of organisations that utilise software, and the increasing number and diversity of programming languages makes this capability as relevant today as in previous decades. Several approaches have been used to address this challenge, including machine learning and the manual definition of direct language-to-language translation rules, however the accuracy of these approaches remains unsatisfactory. In this paper we describe a new approach to program translation using model-driven engineering techniques: reverse-engineering source programs into specifications in the UML and OCL formalisms, and then forward-engineering the specifications to the required target language. This approach can provide assurance of semantic preservation, and additionally has the advantage of extracting precise specifications of software from code. We provide an evaluation based on a comprehensive dataset of examples, including industrial cases, and compare our results to those of other approaches and tools. Our specific contributions are: (1) Reverse-engineering source programs to detailed semantic models of software behaviour, to enable semantically-correct translations and reduce re-testing costs; (2) Program abstraction processes defined by precise and explicit rules, which can be edited and configured by users; (3) A set of reusable OCL library components appropriate for representing program semantics, and which can also be used for OCL specification of new applications; (4) A systematic procedure for building program abstractors based on language grammars and semantics.