Inference of how evolutionary forces have shaped extant genetic diversity is a cornerstone of modern comparative sequence analysis. Advances in sequence generation and increased statistical ...sophistication of relevant methods now allow researchers to extract ever more evolutionary signal from the data, albeit at an increased computational cost. Here, we announce the release of Datamonkey 2.0, a completely re-engineered version of the Datamonkey web-server for analyzing evolutionary signatures in sequence data. For this endeavor, we leveraged recent developments in open-source libraries that facilitate interactive, robust, and scalable web application development. Datamonkey 2.0 provides a carefully curated collection of methods for interrogating coding-sequence alignments for imprints of natural selection, packaged as a responsive (i.e. can be viewed on tablet and mobile devices), fully interactive, and API-enabled web application. To complement Datamonkey 2.0, we additionally release HyPhy Vision, an accompanying JavaScript application for visualizing analysis results. HyPhy Vision can also be used separately from Datamonkey 2.0 to visualize locally executed HyPhy analyses. Together, Datamonkey 2.0 and HyPhy Vision showcase how scientific software development can benefit from general-purpose open-source frameworks. Datamonkey 2.0 is freely and publicly available at http://www.datamonkey.org, and the underlying codebase is available from https://github.com/veg/datamonkey-js.
The Basis Set Exchange (BSE) has been a prominent fixture in the quantum chemistry community. First publicly available in 2007, it is recognized by both users and basis set creators as the de facto ...source for information related to basis sets. This popular resource has been rewritten, utilizing modern software design and best practices. The basis set data has been separated into a stand-alone library with an accessible API, and the Web site has been updated to use the current generation of web development libraries. The general layout and workflow of the Web site is preserved, while helpful features requested by the user community have been added. Overall, this design should increase adaptability and lend itself well into the future as a dependable resource for the computational chemistry community. This article will discuss the decision to rewrite the BSE, the new architecture and design, and the new features that have been added.
Due to growing user demand, web application development is becoming increasingly complicated. Multiple programming languages along with the complex multi-tier architecture commonly involved in web ...application development contribute to the probability of programming mistakes. Such mistakes may cause serious security vulnerabilities, which can then be exploited by malicious users. Current classifications include a wide variety of web application vulnerabilities, such as SQL injections, Cross-Site Scripting and File Inclusion. Various different protections exist against attacks associated with these vulnerabilities making it difficult to apply a single universal solution. This paper takes an alternative view of the core root of the vulnerabilities. Based on the discovered common traits, a unified extensible context-based model of web applications is proposed. A concept of context is introduced and different attacks are reformulated in terms of context boundary violation. The proposed model can be used to implement a more universal web application protection suitable against different types of attacks.
Dental cavities represent a widespread oral health issue on a global scale, impacting individuals across all age groups. The conventional approach to detecting cavities involves a visual examination ...by dentists, which is not only time-consuming but also subjective. Current methods for dental cavity detection heavily rely on subjective visual inspections, which may overlook early or concealed cavities. In this research paper, we present CatchCavity, a web application tool that utilizes deep learning for cavity detection in teeth. The diagnostic tool enables users to upload dental images, facilitating the assessment of dental cavity status. Furthermore, the web application functions as an online dental diagnostic service, providing the capability to securely store patients’ dental records and information in a dedicated database. The system is trained on a dataset of annotated images and employs a convolutional neural network (CNN) architecture for accurate cavity detection. We evaluate the system's performance using metrics such as accuracy and loss. Our results showcase that the proposed system attains a high level of accuracy and efficiency in detecting dental cavities, achieving an overall accuracy of 98.7%. Additionally, our system surpasses traditional cavity detection methods, highlighting the possibility of deep learning approaches to enhance oral health outcomes.
Web application providers have been migrating their applications to cloud data centers, attracted by the emerging cloud computing paradigm. One of the appealing features of the cloud is elasticity. ...It allows cloud users to acquire or release computing resources on demand, which enables web application providers to automatically scale the resources provisioned to their applications without human intervention under a dynamic workload to minimize resource cost while satisfying Quality of Service (QoS) requirements. In this article, we comprehensively analyze the challenges that remain in auto-scaling web applications in clouds and review the developments in this field. We present a taxonomy of auto-scalers according to the identified challenges and key properties. We analyze the surveyed works and map them to the taxonomy to identify the weaknesses in this field. Moreover, based on the analysis, we propose new future directions that can be explored in this area.
•Real-word deployment and evaluation of a P2P energy market with 37 households.•Relatively stable use of the web application.•Heterogeneous user behavior and stated preferences indicate three user ...clusters.•Indications for increased load-shifting due to salience of renewable energy.
Peer-to-peer (P2P) energy markets are a widely discussed approach toward a sustainable energy supply that allows private owners of distributed energy resources (e.g., solar panels) and consuming households to trade energy directly without intermediaries. P2P energy markets are expected to contribute to a green, local, and fair energy system in the future. The approach implies a paradigm shift regarding the role of citizens who evolve from passive consumers into active market participants. While first existing research primarily focused on the technical feasibility of such scenarios, end users and their role in P2P markets have received little attention. The present article studies the behavior of 35 households and two commercial entities in Switzerland's first real-world P2P energy market. In this unique real-world setting, based on a mixed methods approach, we developed and deployed a web application and empirically studied interaction, acceptance, and participation in electricity pricing in this P2P energy market, using data from system logs, surveys, and interviews. The findings are threefold. First, the P2P energy market was well received among its users, indicated by comparably high and stable usage activity of the web application throughout the study (4.5 months). Second, users in the sample are heterogeneous; based on their engagement with the web application and their stated preferences, they can be categorized into those who want to actively set prices (30%); those who prefer automated prices determined by an information system (35%); and non-users/non-respondents to surveys (35%). Third, an analysis of interviews with nine households suggests that P2P energy markets may increase the salience of renewable energies and may promote load-shifting activities. Thus, the article provides empirical insights about the user behavior of households and their future role in decentralized energy scenarios.
RNA-seq is widely used for transcriptomic profiling, but the bioinformatics analysis of resultant data can be time-consuming and challenging, especially for biologists. We aim to streamline the ...bioinformatic analyses of gene-level data by developing a user-friendly, interactive web application for exploratory data analysis, differential expression, and pathway analysis.
iDEP (integrated Differential Expression and Pathway analysis) seamlessly connects 63 R/Bioconductor packages, 2 web services, and comprehensive annotation and pathway databases for 220 plant and animal species. The workflow can be reproduced by downloading customized R code and related pathway files. As an example, we analyzed an RNA-Seq dataset of lung fibroblasts with Hoxa1 knockdown and revealed the possible roles of SP1 and E2F1 and their target genes, including microRNAs, in blocking G1/S transition. In another example, our analysis shows that in mouse B cells without functional p53, ionizing radiation activates the MYC pathway and its downstream genes involved in cell proliferation, ribosome biogenesis, and non-coding RNA metabolism. In wildtype B cells, radiation induces p53-mediated apoptosis and DNA repair while suppressing the target genes of MYC and E2F1, and leads to growth and cell cycle arrest. iDEP helps unveil the multifaceted functions of p53 and the possible involvement of several microRNAs such as miR-92a, miR-504, and miR-30a. In both examples, we validated known molecular pathways and generated novel, testable hypotheses.
Combining comprehensive analytic functionalities with massive annotation databases, iDEP ( http://ge-lab.org/idep/ ) enables biologists to easily translate transcriptomic and proteomic data into actionable insights.
Lake water surface temperature (LWST) is a critical component in understanding the response of freshwater ecosystems to climate change. Traditional estimation of LWST estimation considers water ...surface bodies to be static. Our work proposes a novel open-source web application, IMPART, designed for estimating dynamic LWST using Landsat reflectance and MODIS temperature datasets from 2004 to 2022. Results presented globally for over 342 lakes reveal a root mean square deviation of 0.86 °C between static and dynamic LWST. Additionally, our results demonstrate that 57% of the lakes exhibit a statistically significant difference between the static and dynamic LWST values. Improved LWST will ultimately enhance our ability to comprehensively monitor and respond to the impacts of climate change on freshwater ecosystems worldwide. Furthermore, based on the Koppen-Geiger climate classification, our zonal analysis demonstrates the deviation between static and dynamic LWST. It identifies specific zones where considering waterbodies as dynamic entities is essential.
•Introducing a web application for estimating Lake Water Surface Temperature (LWST) considering dynamic water extent.•Analysing over 342 lakes worldwide, we estimated a root mean square deviation of 0.86 °C between static and dynamic LWST.•57% of the lakes show a statistically significant difference between static and dynamic LWST values.•Using the Koppen-Geiger climate classification, the study identifies climate zones where dynamic LWST estimation is crucial.