Straightforward Interface Research Articles

AVM: A Manually Curated Database of Aerosol-transmitted Virus Mutations, Human Diseases, and Drugs

Abstract Aerosol-transmitted viruses possess strong infectivity and can spread over long distances, earning the difficult-to-control title. They cause various human diseases and pose serious threats to human health. Mutations can increase the transmissibility and virulence of the strains, reducing the protection provided by vaccines and weakening the efficacy of antiviral drugs. To this end, in this study, we aimed to establish a manually curated database (AVM) to store information regarding viral mutations (VMs). The current version of the AVM contains 42,041 VMs, including 2613 immune escape mutations, 45 clinical information datasets, and 407 drugs, antibodies, or vaccines. Additionally, we recorded 88 human diseases associated with viruses and found that the same virus can target multiple organs in the body, leading to diverse diseases. Furthermore, the AVM database offers a straightforward user interface for browsing, retrieving, and downloading information. We believe that this database is a comprehensive resource that can provide timely and valuable information regarding the transmission, treatment, and diseases caused by aerosol-transmitted viruses (http://www.bio-bigdata.center/AVM).

Diesel Level Monitoring System

Abstract: The ultimate objective of this project is to create a wireless diesel tank monitoring system that employs WebSocket protocol to connect fuel sensors and a mobile app in remote areas in real time. Through the use of Wi-Fi networks, customers can obtain consumption information, monitor the current diesel levels in various tanks, and log in to the mobile app, which has a straightforward interface. Diesel levels are shown as a percentage, translated from voltage readings, and alerts are delivered by the system when levels drop below preset limits. The goal of this effective and user-friendly technology is to maximize the use of diesel and make timely refills in distant places easier. A reliable and smooth solution for diesel level monitoring is made possible by the integration of the ESP32 microcontroller, WebSocket connection, and capacitive fuel level sensor. Accurate mapping of sensor readings to ESP32 values is made possible by the use of a 20k ohm potentiometer, which guarantees accurate and dependable data transfer. This work advances the area of remote monitoring systems by providing a workable and expandable method for monitoring diesel level in a variety of applications.

Student Result Analysis and Management

Abstract: Student result analysis and management (SRAM) gives a straightforward interface to support student data. It might be utilised by instructive universities or colleges to keep up the records of students effectively. Student information system manages all sorts of student details, academic related reports results, batch details, and other resource related details too. An effective result analysis system plays a pivotal role in facilitating efficient management of student data and performance assessment. Institutions staff and administrators need to manage students’ information and academic records. For staff by offering analysis, streamlined administrative tasks and efficient records management. For students, it provides easy access to their academic performance and results metrics. This abstract delineates the design and implementation of a robust result analysis system, encompassing a PHP-based backend. The system caters to the needs of teachers, students, and administrators, offering functionalities tailored to each user category. Ultimately, the deployment of the result analysis system on a web server caters to the needs of educational institutions, facilitating efficient management of student data and fostering a conducive environment for academic assessment and improvement

Achieving enhanced multifunctional performance for structural composite supercapacitors by reinforcing interfaces with polymer coating

Carbon fiber structural composite supercapacitors possess the multifunctionality of storing electrochemical energy and withstanding mechanical loads simultaneously, attracting increased attention in electric vehicles, drones, and aircraft sectors. A polymer-based coating was meticulously constructed at the electrode/electrolyte interface to enhance adhesion and stability between active materials and the carbon fiber fabric collector under diverse conditions, especially mechanical stress. Mechanical testing and corresponding physical characterization substantiated the superior performance of the polymer coating. With the protective polymer coating, the optimized structural composite Zn-ion supercapacitor (SZSC), consisting of carbon fiber@active carbon-P (CF@AC-P) cathode, ionogel electrolyte, and Zn anode, displayed a maximum energy density of 164.6 mWh kg−1, at power density of 563.3 mW kg−1. Moreover, the optimized SZSC demonstrated stable operation over more than 8000 cycles at 0.3 mA cm−2 without capacity degradation. The optimized SZSC exhibited a tensile strength of 399.7 MPa and Young's modulus of 11.5 GPa. Furthermore, employing vacuum infusion techniques, the fabricated three-dimensional (3D) wing skin model shell and tube shell curved-surface structural composite Zn-ion supercapacitor component composites showcased exceptional electrochemical performance. These achievements further validate the practicality of 3D multifunctional composites. Consequently, this research presented a practical and straightforward interface engineering approach to develop multifunctional structural devices with remarkable electrochemical and mechanical properties.

Hydrophilic‐Zincophobic Separator Enabling by Crystal Structure Regulation toward Stabilized Zn Metal Anode

AbstractAqueous zinc‐ion batteries (ZIBs) hold significant promise for large‐scale energy storage. While considerable strides have been made in modifying separators, the challenge of developing dendrite‐free, corrosion‐resistant, and cost‐effective separators for achieving extended cycling performance of Zn anodes persists. In light of this, a TiO2 coating separator to mitigate interfacial corrosion and passivation reactions, thereby facilitating high‐performance ZIBs is designed. This study delves into the influence of the loading amount and crystal phase of the TiO2 coating layers on separator modification. Zn symmetric cells employing the anatase TiO2‐modified glass fiber (A‐TiO2@GF) separator demonstrate superior Zn2+ ion transport kinetics in a mild ZnSO4 electrolyte, ensuring sustained long‐term stability and uniform Zn deposition. Furthermore, the reduced hydrogen evolution reaction (HER) activity of A‐TiO2 coatings curbs H+ ion migration, minimizing interfacial corrosion and HER. Consequently, the assembled Zn||CaV8O20 zinc‐ion full cells demonstrate outstanding long‐term durability and impressive specific capacity, boasting a discharge capacity of 142 mAh g−1 after 1000 cycles. This work introduces a straightforward interface engineering strategy for creating efficient separators in zinc‐ion batteries, promoting uniform Zn deposition.

Examples and tutorials on using Google Colab and Gradio to create online interactive student‐learning modules

AbstractThis work provides online learning modules and instructions on how educators can leverage these technologies to help students learn in a personalized online environment. In particular, we focus on Google Colab, and the features provided by the Gradio Python library to provide interactivity within these modules. The contributions of this work include: (1) Development of a teaching framework using Gradio/Colab that offers automated grading and feedback for both educators and students; (2) Design of a versatile proposal, accommodating beginners with a straightforward interface while addressing the needs of advanced learners; (3) Creation of a comprehensive set of examples tailored for teaching digital logic subjects, with adaptability for application in various computer science areas. (4) A classification of these example learning modules in terms of their learning level for the students; (5) A novel client‐server approach based on Colab/Gradio, allowing teachers to manage the main notebook efficiently while providing a lightweight and reliable interface for students. The goal of this work is to further expose educators to the remarkable capabilities that cloud computing brings to online supplemental education, noting that large language models such as ChatGPT complement this work, in that chatbots will be able to guide students in these dynamic simulations.

ThumbUp: Secure Smartwatch Controller for Smart Homes Using Simple Hand Gestures

The development of creative applications and intelligent gadgets requires a secure and straightforward interface with human users. We propose, design, and implement ThumbUp, a smartwatch-based two-factor real-time identification and authentication system in which smartwatch users can identify and authenticate themselves using some simple hand and finger movements, such as thumb-up. ThumbUp leverages the signal from the Inertial Measurement Unit (IMU) in in Commercial-Off-The-Shelf (COTS) smart devices to discover the unique pattern generated by each user's simple gestures using a carefully constructed deep learning model. Smart homes provide a comfortable, safe, and efficient living environment, epecially help the sick and aged. We propose strategies for convenient and reliable control in smart homes with gesture command recognition. We build an Auto-Encoder-based filter that reconstructs the raw data to improve the representation of gesture features. Moreover, we adopt the random forest method to analyse the contextual command correlation. And we employ the authentication system based on smartwatch for personalized command feedback and ensure that illegals cannot use the device. We implement our system and undertake rigorous studies to determine its usefulness and efficiency over a three-month period with 65 users. It achieves a 97% accuracy for user classification and an EER of 0.014 for authentication task with a single simple gesture. And our method achieves 91% accuracy for command recognition and 96% command accuracy with contextual informations. Additionally, we conduct a study of user acceptability of our system and explain how gesture proficiency influences authentication accuracy.

Smart Eye for Visually Impaired People

Abstract: This paper presents a novel mobile application tailored to enhance the daily experiences of individuals with visual impairments. Leveraging cutting-edge real-time object detection and Optical Character Recognition (OCR) techniques, the app, constructed using the TensorFlow algorithm and the comprehensive Common Objects in Context (COCO) dataset, aims to empower users by providing invaluable assistance through their mobile devices. The application utilizes the device's camera to seamlessly identify objects in real-time via the object detection algorithm, while simultaneously extracting and vocalizing text from captured images through OCR technology. A crucial aspect of the app lies in its commitment to user-friendliness, ensuring a straightforward interface tailored specifically for the needs of visually impaired individuals. The efficacy of the system was rigorously evaluated, focusing on both accuracy and real-time performance. Results conclusively demonstrate the app's effectiveness and efficiency in offering essential support to visually impaired users, marking a significant stride toward fostering independence and ease in their daily lives. Remarkably, this mobile application stands out for its affordability and accessibility, providing a practical and inclusive solution for individuals with visual impairments. By delivering audio feedback about identified objects and recognized text, this innovative app contributes to a more accessible and autonomous lifestyle for its users, contributing positively to the broader landscape of assistive technology for the visually impaired.

Synergistic effects of hole blocking and Förster resonance energy transfer process in high-performance photomultiplication organic photodetectors

Organic photodetectors (OPDs) are a potential next-generation photodetection technology because they are lightweight, flexible, and have customizable spectral responses. However, high dark currents with low detectability remain major challenges, limiting the widespread application of photomultiplication OPDs (PM-OPDs). This work describes a straightforward interface modification strategy based on the PBDB-T:N2200 bulk heterojunction (BHJ) structure to improve the PM-OPD performance. Introducing a thin rubrene layer achieves the synergistic effects of hole blocking and the Förster resonance energy transfer (FRET) process, resulting in a two-order-of-magnitude reduction in dark current density and an increased responsivity of 19.77 A W−1 at 660 nm. Moreover, the external quantum efficiency improves significantly through FRET, and a specific detectivity of 4.39 × 1013 Jones is demonstrated at 660 nm, which is the highest value among existing PM-OPDs, using BHJ structures. An impressive increase in the linear dynamic range from 91 to 144 dB was obtained due to the improved photocurrent density and balanced charge transport. The broad applicability of the strategy was verified through a PM6:Y6-based OPD system. Our approach offers more general application prospects by improving the detection capability of photodetectors for low-light environments.

Automated cell counting for Trypan blue-stained cell cultures using machine learning.

Cell counting is a vital practice in the maintenance and manipulation of cell cultures. It is a crucial aspect of assessing cell viability and determining proliferation rates, which are integral to maintaining the health and functionality of a culture. Additionally, it is critical for establishing the time of infection in bioreactors and monitoring cell culture response to targeted infection over time. However, when cell counting is performed manually, the time involved can become substantial, particularly when multiple cultures need to be handled in parallel. Automated cell counters, which enable significant time reduction, are commercially available but remain relatively expensive. Here, we present a machine learning (ML) model based on YOLOv4 that is able to perform cell counts with a high accuracy (>95%) for Trypan blue-stained insect cells. Images of two distinctly different cell lines, Trichoplusia ni (High FiveTM; Hi5 cells) and Spodoptera frugiperda (Sf9), were used for training, validation, and testing of the model. The ML model yielded F1 scores of 0.97 and 0.96 for alive and dead cells, respectively, which represents a substantially improved performance over that of other cell counters. Furthermore, the ML model is versatile, as an F1 score of 0.96 was also obtained on images of Trypan blue-stained human embryonic kidney (HEK) cells that the model had not been trained on. Our implementation of the ML model comes with a straightforward user interface and can image in batches, which makes it highly suitable for the evaluation of multiple parallel cultures (e.g. in Design of Experiments). Overall, this approach for accurate classification of cells provides a fast, bias-free alternative to manual counting.

An Android-based Image Steganography Approach to Data Communication Security using LSB and Password-based Encryption

The study's ultimate goal is to develop an Android app dedicated to Image Steganography, a technique for concealing sensitive information behind seemingly innocuous photographs. This information hiding technique is essential because of its many potential uses. Symmetric encryption, asymmetric encryption, and steganography are all brought together in this method. The initial picture is encrypted using a symmetric technique in this procedure. After that, the encrypted picture is quietly placed using a least significant bits Steganographic approach to conceal the secret key that was encrypted using an asymmetric algorithm. The steganography algorithm's simple but effective security mechanism is a major benefit. Integrating a secret message into a seemingly benign source makes it very difficult to detect the hidden message without prior knowledge of its existence and the appropriate decryption algorithm. The privacy of the concealed data is protected by this feature. The planned Android app would provide a user-friendly interface for using picture steganography methods, making it simple for anybody to choose commonplace photos and secret messages for obfuscation. Both the original picture and the concealed message will be kept secret thanks to the app's robust encryption methods. The hidden message will be seamlessly included into the regular picture using advanced steganographic methods like the least significant bits approach. The creation of this software is motivated by a desire to provide an easily accessible solution for people who want safe communication through hidden messages or encrypted photos. The robust encryption and steganographic technologies, paired with the straightforward interface, will enable users to effectively protect sensitive information. This work will strengthen the area of data security and highlight the need of sophisticated encryption and steganography in modern digital communication.

FHIR-PYrate: a data science friendly Python package to query FHIR servers

BackgroundWe present FHIR-PYrate, a Python package to handle the full clinical data collection and extraction process. The software is to be plugged into a modern hospital domain, where electronic patient records are used to handle the entire patient’s history. Most research institutes follow the same procedures to build study cohorts, but mainly in a non-standardized and repetitive way. As a result, researchers spend time writing boilerplate code, which could be used for more challenging tasks.MethodsThe package can improve and simplify existing processes in the clinical research environment. It collects all needed functionalities into a straightforward interface that can be used to query a FHIR server, download imaging studies and filter clinical documents. The full capacity of the search mechanism of the FHIR REST API is available to the user, leading to a uniform querying process for all resources, thus simplifying the customization of each use case. Additionally, valuable features like parallelization and filtering are included to make it more performant.ResultsAs an exemplary practical application, the package can be used to analyze the prognostic significance of routine CT imaging and clinical data in breast cancer with tumor metastases in the lungs. In this example, the initial patient cohort is first collected using ICD-10 codes. For these patients, the survival information is also gathered. Some additional clinical data is retrieved, and CT scans of the thorax are downloaded. Finally, the survival analysis can be computed using a deep learning model with the CT scans, the TNM staging and positivity of relevant markers as input. This process may vary depending on the FHIR server and available clinical data, and can be customized to cover even more use cases.ConclusionsFHIR-PYrate opens up the possibility to quickly and easily retrieve FHIR data, download image data, and search medical documents for keywords within a Python package. With the demonstrated functionality, FHIR-PYrate opens an easy way to assemble research collectives automatically.

FarmDain, a Decision Support System for Dairy Sheep and Goat Production.

Managing a milk zone in the dairy industry is demanding. Data necessary for efficient management are difficult to acquire because they usually must be collected in organized and standardized ways. On the other hand, software practices constantly provide new tools that can go beyond simple record-keeping practices and add value to the data. In this work, FarmDain is a novel web-based application for sheep and goat management. It aims to improve milk production and processing by digitizing the value chain in data acquisition, processing and visualization between dairy production businesses and their milk suppliers. FarmDain uses state-of-the-art software technologies to model the data collection process and provides a straightforward user interface to facilitate data processing and visualization. Using the app in a case study carried out for 12 months in a dairy sheep farm resulted in lower feeding cost per milked ewe by 5.5% when ewes were allocated into high and low milk production groups compared to the scenario of remaining in one single group. Furthermore, based on reports provided by the app, culling and genetic selection decisions were made to improve the overall farm performance. Similar practices were applied in all farms optimizing their productivity, which led to increased profitability for farms and the Dairy Factory.

Analyzing The Phenomenon of VR Shopping Based on SWOT Analysis

People and businesses are becoming more interested in VR shopping as online shopping grows. The goal of this research was to examine the benefits, drawbacks, possibilities, and risks of virtual reality buying, as well as how perceived ease of use (PPEOU) and usefulness (PU) influence consumers' behavioral intentions. This paper used the method of SWOT analysis and came to several conclusions. That is, VR shopping has some strengths. Firstly, it is convenient, which is related to PEOU and PU. Additionally, it strongly affects behavioral intention. Secondly, it is enjoyable, allowing customers to have an immersive shopping experience, and it has perceived usefulness. Furthermore, PU enhances behavioral intention. Finally, it offers a more user-friendly and straightforward interface, which is connected to PEOU and PU. For the weakness, the technology of VR shopping is not perfect enough, which cannot show more details for consumers such as the texture of clothing. This is linked to PEOU and PU and, as a result, lowers behavioral intention. For the opportunities, VR shopping in the age of fast e-commerce growth. For the threatens, the epidemic cad problems with funding, which means there is not enough money to develop VR shopping technology. It affects PEOU and PU, ultimately lowering behavioral intention. Overall, companies should build on their strengths and avoid taking risks. Thus, developing VR shopping is better.

Lead halide coordination competition at buried interfaces for low VOC-deficits in wide-bandgap perovskite solar cells

A simple and straightforward interface engineering strategy, using stacked layers of small molecules (2PACz/Me-4PACz) as hole-selective layers, resulted in the formation of a dense buried interface perovskite film.

Simulation of interfacial deformations for 2D axisymmetric multi-material flows

A numerical method is developed to model the deformation of interfaces between various materials in a multi-material system. The method involves a new and straightforward interface reconstruction scheme integrated with the volume-of-fluid (VOF) technique capable of addressing triple-point configurations. The developed method can track various interfacial structures between liquids in liquid-liquid-gas systems. First, a few standard test cases are used to demonstrate the capabilities of the numerical scheme and examine its performance. Next, the impact of a water drop onto a pool of silicone oil is simulated. Experiments were also performed to obtain time-resolved images of this phenomenon for comparison and validation purposes. Computer simulations well agree with those of the experiments.

The Effectiveness of Monetary Policy in Neutralizing Oil Price Fluctuations on the Gross Domestic Product in Iraq for the Period (1990-2019)

The research aimed to measure the reality of monetary policy and its role in neutralizing the impact of fluctuations in total domestic oil prices, through the most important monetary policy variable (money supply). An example of this is using a simple technique in the previous example, turning it into a straightforward user interface by (Judd and Kunee). After estimating the impact of the policy with the domestic gross domestic oil prices in Iraq, the effect of fluctuations in the domestic gross domestic oil prices in the simple regression model, while the morale of oil prices was not proven with a negative sign, while the morale of money supply and their impact on the increase of the domestic was proven in the multiple regression model. Statistically, interpreting this indicates that the participation of other variables to oil prices in the graph of the rate of impact absorption and a negative impact was achieved in the nature of the original variable, and through the analysis of the path and direct graph of oil prices on the GDP, the evaluation of the Iraqi economy is equal to 95% of public revenues. It amounts to 60% of Iraq's GDP. A constant source of shocks because it is associated with cheap prices. In the light of this, the research reached a recommendation to reduce dependence on oil revenues, as it represents a permanent source of shocks due to its association with oil prices, which represents an external variable subject to market price fluctuations and the tendency to rely on other alternative sources of activating other sectors

Aero Web Software

The school's ERP system provides a straightforward interface for maintaining individual students, standards, educators, libraries, and former info. each academy typically has some customary and intellectual modules like subjects, exercises, halls, projects, and options. Manually managing these departments and former modules is a fragile, half-hearted and dear task. Therefore, we tend to are aiming for an ERP system for the academy here. Therefore, here we tend to propose an ERP system for colleges. Our school's ERP system has all the knowledge concerning students, teachers, activities, libraries, communication departments and alternative revered info. this method permits directors to feature student, faculty, and e-learning details. Our system permits college members to enter or enter student attending in an exceedingly information in order that students and school members will read it later. A student will read attending via another student's ERP login. directors will transfer timetables for various departments in preparation for the communication. The timetable is exhibited to college and students on the online portal. These systems are extraordinarily convenient as a result of they need a straightforward program and a strong knowledge management system?

“Tonga”: A Novel Toolbox for Straightforward Bioimage Analysis

Techniques to acquire and analyze biological images are central to life science. However, the workflow downstream of imaging can be complex and involve several tools, leading to creation of very specialized scripts and pipelines that are difficult to reproduce by other users. Although many commercial and open-source software are available, non-expert users are often challenged by a knowledge gap in setting up analysis pipelines and selecting correct tools for extracting data from images. Moreover, a significant share of everyday image analysis requires simple tools, such as precise segmentation, cell counting, and recording of fluorescent intensities. Hence, there is a need for user-friendly platforms for everyday image analysis that do not require extensive prior knowledge on bioimage analysis or coding. We set out to create a bioimage analysis software that has a straightforward interface and covers common analysis tasks such as object segmentation and analysis, in a practical, reproducible, and modular fashion. We envision our software being useful for analysis of cultured cells, histological sections, and high-content data.

Chromosome-Level Genome Assembly and HazelOmics Database Construction Provides Insights Into Unsaturated Fatty Acid Synthesis and Cold Resistance in Hazelnut (Corylus heterophylla).

Corylus heterophylla (2n = 22) is the most widely distributed, unique, and economically important nut species in China. Chromosome-level genomes of C. avellana, C. heterophylla, and C. mandshurica have been published in 2021, but a satisfactory hazelnut genome database is absent. Northeast China is the main distribution and cultivation area of C. heterophylla, and the mechanism underlying the adaptation of C. heterophylla to extremely low temperature in this area remains unclear. Using single-molecule real-time sequencing and the chromosomal conformational capture (Hi-C) assisted genome assembly strategy, we obtained a high-quality chromosome-scale genome sequence of C. heterophylla, with a total length of 343 Mb and scaffold N50 of 32.88 Mb. A total of 94.72% of the test genes from the assembled genome could be aligned to the Embryophyta_odb9 database. In total, 22,319 protein-coding genes were predicted, and 21,056 (94.34%) were annotated in the assembled genome. A HazelOmics online database (HOD) containing the assembled genome, gene-coding sequences, protein sequences, and various types of annotation information was constructed. This database has a user-friendly and straightforward interface. In total, 439 contracted genes and 3,810 expanded genes were identified through genome evolution analysis, and 17 expanded genes were significantly enriched in the unsaturated fatty acid biosynthesis pathway (ko01040). Transcriptome analysis results showed that FAD (Cor0058010.1), SAD (Cor0141290.1), and KAT (Cor0122500.1) with high expression abundance were upregulated at the ovule maturity stage. We deduced that the expansion of these genes may promote high unsaturated fatty acid content in the kernels and improve the adaptability of C. heterophylla to the cold climate of Northeast China. The reference genome and database will be beneficial for future molecular breeding and gene function studies in this nut species, as well as for evolutionary research on species of the order Fagales.