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Pharmaceuticals are among the most challenging products to assess by life cycle assessment (LCA). The main drawback highlighted by LCA practitioners is the lack of inventory data, both regarding the synthesis of active pharmaceutical ingredient (API) precursors (upstream) and the details concerning the downstream phases (use and end of life). A short critical review of pharma-LCAs found in the literature is here proposed, with discussion of several tools and models used to predict the environmental impacts derived from the life cycle of pharmaceuticals, emphasizing current strengths and weaknesses, and exploring the possibilities for improvements. The case of antibiotics is selected as a representative class of pharmaceuticals, due to their massive use worldwide and the growing related issue of antimicrobial resistance enrichment, which is generally not included in most of LCAs. Also, we comment on drafting product category rules (PCRs) in the relevant field to develop standard methodologies and enhance the comparability of the studies, ultimately advocating collaboration with companies and improving inventory data quality and availability for the whole value chain of products.

Choosing and booking a vacation can be difficult when the application where these things are done is not user-friendly. Therefore, the application that I have created will have to make the user experience much more pleasant. The purpose of the application is to be able to choose a holiday according to the desired filters, with the option to search for a flight in the same period. After booking it, the user who created an account will have stored in his account all the reservations made. Using the logic behind this application, any travel agency can create a new interface that they can customize according to their wishes, but the functionalities remain the same. They can also change what data they want to receive from the API, what data they want to store in their database and in addition modify the offers according to their wishes.

The paper discusses the application program interface (API). Most software projects reuse components exposed through APIs. In fact, current-day software development technologies are becoming inseparable from the large APIs they provide. An API is the interface to implemented functionality that developers can access to perform various tasks. APIs support code reuse, provide high-level abstractions that facilitate programming tasks, and help unify the programming experience. A study of obstacles that professional Microsoft developers faced when learning to use APIs uncovered challenges and resulting implications for API users and designers. The article focuses on the obstacles to learning an API. Although learnability is only one dimension of usability, there's a clear relationship between the two, in that difficult-to-use APIs are likely to be difficult to learn as well. Many API usability studies focus on situations where developers are learning to use an API. The author concludes that as APIs keep growing larger, developers will need to learn a proportionally smaller fraction of the whole. In such situations, the way to foster more efficient API learning experiences is to include more sophisticated means for developers to identify the information and the resources they need-even for well-designed and documented APIs.

In the rapidly evolving API Economy, quality of API management software has become a critical concern. This work analyzed the API management industry with a particular focus on the metrics available for various API Gateway products. The primary artifact is a catalog with 59 metrics, compiled from global industry reports and technical documentation of 68 leading API Gateway products. The Design Science Research (DSR) approach was adopted to design the catalog, and metrics were categorized based on clear definitions in recent scientific literature. Secondly, a quantitative analysis method was proposed and systematically performed. Findings indicate that the metrics mainly focus on latency, response time, API performance, error capturing, and traffic monitoring. Features such as caching, resource utilization, and system health were scarcely addressed by the examined products. The proposed artifacts provide an objective foundation for a deeper understanding of API Management software quality, and lay the groundwork for future research. En la Economía de las API, la calidad del software de administración de API se ha convertido en una preocupación crítica. Este trabajo analizó productos de administración de API con un enfoque particular en las métricas disponibles en productos API Gateway. Se obtuvo un catálogo de 59 métricas, compiladas y categorizadas a partir de la literatura vigente, reportes globales y documentación técnica de 68 API Gateways. Se adoptó el enfoque Design Science Research (DSR) para el diseño. Adicionalmente, se propuso y se implementó un método de análisis cuantitativo. Los hallazgos indican que las métricas se centran principalmente en latencia, tiempo de respuesta, rendimiento, captura de errores y monitoreo del tráfico. Características como almacenamiento en caché, utilización de recursos y estado del sistema fueron escasamente abordadas. Los artefactos propuestos proporcionan una base objetiva para comprender más profundamente la calidad del software de administración de API, y sientan bases para futuras investigaciones.

3D printing has revolutionized orthoses manufacturing in assistive technologies, enabling development of custom-fitted orthoses in under 24 hours. Physician-engineer collaboration is essential to addressing the mechanical complexities of automated orthoses design. Single-step manufacturing of these devices is necessary for simplistic and translational technologies. This work proposes a novel automated program, application programing interface, to design a custom single-finger orthosis using only basic biometric data (body weight, height, and age) as input to enable fully virtual rehabilitation. Feasibility study, cross-sectional design, and survey study. Customization without body scans streamlines programming and enables gross estimate of hand orthosis size. Computer-aided design models are automatically generated using the Automated Custom Finger Orthoses system that was created using several macros with SolidWorks and Visual Basic Editor. A military database was used for the biometric data for the program to establish a relationship between finger size and biometric data. Survey data were taken from 10 human healthy participants (six male and four female, aged between 18 and 60) using Likert scales to check fitness of 3D-printed soft index finger orthosis part. Computer-aided design models were successfully created using the application programing interface using military database, the models were 3D-printed and fitted on subjects. The fitness of the device varies significantly under the current parameters. Eight of the 10 test devices fit their test subjects with overall average offsets of 7.00 mm, 6.14 mm, and 8.89 mm for DIP (L1), PIP (L2), and MCP joints (L3 offset), respectively and the subjects were fully donned. The biasing of current data toward male subjects results in slightly better fit accuracy in males than in females. Anthropometric studies can aid in discerning fundamental ratios for orthoses design, allowing for custom-fitted designs and manufacturing with ease and efficiency. •Gross body measurement estimation via minimal input parameters.•Automated computer-aided design model generation of finger orthoses.•Flexible hand orthoses designed for use with soft robotics.

Designing a new API for a large-scale project requires developers to make strategic design choices that will allow the codebase to evolve sustainably. To create well-structured API components, developers can learn from existing APIs. However, the lack of standardized methods for comparing API designs often makes this learning process inefficient and challenging. To bridge this gap, we introduce API-Miner, which, to our knowledge, is one of the first engines to recommend API-to-API specifications. API-Miner retrieves relevant components from OpenAPI specifications-a widely recognized standard for describing web APIs. The engine introduces several key innovations: (1) novel techniques for processing and extracting critical information from OpenAPI specifications, (2) specialized feature extraction methods tailored to the technical domain of API specifications, and (3) a log-linear probabilistic model that integrates multiple signals to retrieve relevant and high-quality OpenAPI components based on a query specification. Through both quantitative and qualitative evaluations, API-Miner achieves a recall@1 of 91.7% and an F1 score of 56.2%, outperforming baseline models by 15.4 percentage points (pp) in recall@1 and 3.2 pp in F1. API-Miner enables developers to access relevant OpenAPI components from public or internal databases early in the API development cycle, facilitating the learning of best practices and the identification of potential redundancies. This tool helps streamline the development process and supports the creation of maintainable, high-quality APIs. The code for API-Miner is available at https://github.com/jpmorganchase/api-miner.

Background Application Programming Interfaces (APIs) are now widely used to distribute biological data. And many popular biological APIs developed by many different research teams have adopted Javascript Object Notation (JSON) as their primary data format. While usage of a common data format offers significant advantages, that alone is not sufficient for rich integrative queries across APIs. Results Here, we have implemented JSON for Linking Data (JSON-LD) technology on the BioThings APIs that we have developed, MyGene.info , MyVariant.info and MyChem.info . JSON-LD provides a standard way to add semantic context to the existing JSON data structure, for the purpose of enhancing the interoperability between APIs. We demonstrated several use cases that were facilitated by semantic annotations using JSON-LD, including simpler and more precise query capabilities as well as API cross-linking. Conclusions We believe that this pattern offers a generalizable solution for interoperability of APIs in the life sciences.

In the introduction to this review the complex chemistry of solid-state pharmaceutical compounds is summarized. It is also explained why the density functional theory (DFT) periodic calculations became recently so popular in studying the solid APIs (active pharmaceutical ingredients). Further, the most popular programs enabling DFT periodic calculations are presented and compared. Subsequently, on the large number of examples, the applications of such calculations in pharmaceutical sciences are discussed. The mentioned topics include, among others, validation of the experimentally obtained crystal structures and crystal structure prediction, insight into crystallization and solvation processes, development of new polymorph synthesis ways, and formulation techniques as well as application of the periodic DFT calculations in the drug analysis.

Text sentiment analysis is mostly used for the assessment of the author’s mood depending on the context. The purpose of sentiment analysis is to discover the exactness of the underlying emotion in a given situation. It has been applied to various fields, including stock market predictions, social media data on product evaluations, psychology, the judiciary, forecasting, illness prediction, agriculture, and more. Many researchers have worked on these topics and generated important insights. These outcomes are useful in the field because they (outcomes) help people comprehend the general summary quickly. Additionally, sentiment analysis aids in limiting the harmful effects of some posts on various social media sites such as Facebook and Twitter. For these reasons and more, we are proposing an approach to filter the social media content that could be emotionally harmful to the user, through getting the social networks content; for that, we have used Twitter API to get the user posts, and then, we have used API natural understanding language API tool to extract and classify the emotions of the Twitter content into five basic emotional categories—Joy, sadness, anger, fear, disgust—into an array of emotions; after that, we have defined a perfect emotion array from over 450 words from the English language. The main purpose of this comprehensive research article is to examine the proposed solution that we have conducted to improve the quality of content displayed to users emotionally.