Platform For Applications Research Articles

A CONCEPTUAL FRAMEWORK FOR ASSESSING THE FIELD EFFICIENCY OF DRONES IN IDENTIFYING POTENTIAL BREEDING SITES OF THE Aedes MOSQUITO

The identification of breeding sites is key to dengue prevention strategies. Community involvement and breeding site surveillance play a vital role in controlling the Aedes population. Drones have emerged as a promising tool to be used in surveillance activities. Therefore, the aim of this paper is to develop a conceptual framework and present comprehensive intervention methods to control dengue cases. This study explores the concepts of community engagement, habitat profiling and mapping, and technology integration that will be implemented in the three main phases. Phase I: Community engagement, in which to understand the implementation characteristics of the proposed system using the Consolidated Framework for Implementation Research (CFIR) and Human-Centred Design (HCD); Phase II: Profiling and mapping potential breeding sites, in order to compare and characterise vector breeding sites of the Aedes mosquito in selected urban and rural areas using innovative drone technologies; Phase III: Technology integration by developing automated linkage of information on the mapping of mosquito breeding sites for dengue risk to an application platform. This conceptual framework can assess the efficiency of drones as an alternative tool for dengue surveillance and the use of technology to locate breeding sites effortlessly, which can later be applied in dengue-endemic regions.

Hybrid accounting for people and bots: potential of C-RPA digital platform application

Hybrid accounting for people and bots: potential of C-RPA digital platform application

INVESTIGATING THE IMPACT OF AFFORDANCE VALUE AND TRUST ON THE USAGE OF FOOD DELIVERY APPLICATIONS: A CONCEPTUAL STUDY

Food delivery applications (FDAs) have been increasingly popular in recent years. Customers from developed and emerging countries are increasingly using these applications for quick and easy delivery of food to their homes. Furthermore, FDAs have provided restaurants with new chances to increase revenue without needing to increase sitting space. As a result, there has been a notable shift in the food sector, with an increasing number of customers relying on FDAs for their meal needs. Although FDAs are becoming more prominent, it is essential to understand the elements that affect their usage. This study utilises an extended Technology Acceptance Model (TAM) as an underpinning reasoning. The affordance value and trust in the application platform are also examined to bridge the hypothetical relationship for future research direction. This study aims to provide insights to future researchers in the food delivery research area regarding the potential factors influencing the usage of meal delivery apps. This study offers significant information for FDA service providers seeking to expand market share by knowing how to impact consumer usage.

Polydopamine-mediated facile Silver grown on ZnO Thin Films as High Performance SERS Substrates for R6G Detection

Surface-enhanced Raman spectroscopy (SERS) is a widely known technique that uses plasmonic structures (silver, gold, etc.) to detect low-concentration molecules. However, the limited number of metallic elements with plasmonic properties leads to limitations in their application. The qualitative detection method of SERS holds considerable promise in providing novel platforms for diverse applications, owing to its utilization of hybrid structures. Mussel-inspired polydopamine offers a promising avenue for the fabrication and integration of hybrid structures suitable for the SERS platform. Here, sputtered ZnO thin films were modified with Ag Nanostructures using polydopamine to fabricate a homogeneous Ag@ZnO hybrid high-performance SERS substrate. Ag/ZnO hybrid nanostructures were analyzed by FESEM and XRD to investigate their morphological and structural characterizations. SERS measurements were performed for all silver growth times to understand the effect of the silver growth process and hybrid structure synergy on SERS performance. The Ag@ZnO hybrid structure, cultivated with 24-hour silver growth, exhibited remarkable detectability even at an ultra-low R6G concentration of 10 pM

The Re-development of Proxsis Workspace with Responsive Design and Multiplatform approaches using Flutter Framework

Most of previous studies implemented the responsive design approach for the web-based application platform only since it had several difficulties to apply in the mobile-based application platform. In addition, the mobile application required different codebases since there were several platforms like Android and iOS. However, this study tried to redevelopment the Proxsis Workspace website to mobile application with responsive design and multiplatform approaches using Flutter Framework, in order to explore the potentials and counter the difficulties these two approaches for mobile development. In addition, we provide the detailed improvement, and the software testing results of our redevelopment app. Eight participants were participated in this study to measure the improvement of the redevelopment application. The results showed that the redevelopment version of the Proxsis Workspace could implement the responsive design and multiplatform approaches well. Furthermore, the software testing found that the redevelopment version passed the responsive design and multiplatform testing. In addition, there was significant different and enhancement of the usability score from 52.50 with marginal category to 72.81 with acceptable category. Hence, the authors suggest implementing the responsive design and multiplatform with Flutter Framework to enhance and make efficient with single code base only.

Not just a pretty picture: Mapping Leaf Area Index at 10 m resolution using Sentinel-2

Achieving the Global Climate Observing System goal of 10 m resolution leaf area index (LAI) maps is critical for applications related to climate adaptation, sustainable agriculture, and ecosystem monitoring. Five strategies for producing 10 m LAI maps from Sentinel-2 (S2) imagery are evaluated: i. bi-cubic interpolation of 20 m resolution S2 LAI maps from the Simplified Level 2 Prototype Processor Version 1 (SL2PV1) as currently performed by the Sentinel Applications Platform (SNAP), ii. applying SL2PV1 to S2 reflectance bands spatially downscaled to 10 m using bi-cubic interpolation (BICUBIC), iii. Applying SL2PV1 to S2 reflectance bands spatially downscaled to 10 m using Area to Point Regression Kriging (ATPRK), iv. using a recalibrated version of SL2PV1 (SL2PV2) requiring only three S2 10m bands, and iv) a novel use of the previously developed Active Learning Regularization (ALR) approach to locally approximate the SL2PV1 algorithm using only 10 m bands.Algorithms were assessed in terms of per-pixel accuracy and spatial metrics when comparing 10 m LAI maps produced using either actual S2 imagery or S2 imagery synthesized from airborne hyperspectral imagery to reference 10 m LAI maps traceable to in-situ fiducial reference measurements at 10 sites across the continental US. ATPRK and ALR algorithms had the lowest precision error of ∼0.15 LAI, compared to 0.19 LAI for SNAP and BICUBIC and 0.35 LAI for SL2PV2, and ranked highest in terms of local correlation and Structural Similarity Index measure as well as qualitative agreement with reference maps. SL2PV2 LAI showed evidence of saturation over forests related to decreased sensitivity of input visible reflectance. All algorithms had a similar uncertainty of ∼0.55 LAI compared to traceable reference maps, due to the trade-off between bias and precision. However, ATPRK and ALR uncertainty reduced to 0.11 LAI and 0.16 LAI, respectively, when compared to reference maps that ignored canopy clumping. These results suggest that both ATPRK and ALR are suitable for producing 10 m S2 LAI maps assuming bias due to local clumping can be corrected in the underlying SL2PV1 algorithm.

Application of a cloud platform that identifies patient-ventilator asynchrony and enables continuous monitoring of mechanical ventilation in intensive care unit

BackgroundPatient-ventilator asynchrony (PVA) frequently occurs in mechanically ventilated patients within the ICU and has the potential for harm. Depending solely on the health care team cannot accurately and promptly identify PVA. To address this issue, our team has developed a cloud-based platform for monitoring mechanical ventilation (MV), comprising the PVA-RemoteMonitor system and the 24-h MV analysis report. We conducted a survey to evaluate physicians' satisfaction and acceptance of the platform in 14 ICUs. MethodsData from medical records, clinical information systems, and ventilators were uploaded to the cloud platform and underwent data processing. The data were analyzed to monitor PVA and displayed in the front-end. The 24-h analysis report for MV was generated for clinical reference. Critical care physicians in 14 hospitals' ICUs that involved in the platform participated in a questionnaire survey, among whom 10 physicians were interviewed to investigate physicians’ acceptance and opinions of this system. ResultsThe PVA-RemoteMonitor system exhibited a high level of specificity in detecting flow insufficiency, premature cycle, delayed cycle, reverse trigger, auto trigger, and overshoot, with sensitivities of 90.31 %, 98.76 %, 99.75 %, 99.97 %, 100 %, and 99.69 %, respectively. The 24-h analysis report supplied essential data about PVA and respiratory mechanics. 86.2 % (75/87) of physicians supported the application of this platform. ConclusionsThe PVA-RemoteMonitor system accurately identified PVA, and the MV analysis report provided guidance in controlling PVA. Our platform can effectively assist ICU physicians in the management of ventilated patients.

Topological Network Modes in a Twisted Moiré Phononic Crystal.

Twisted moiré materials, a new class of layered structures with different twist angles for neighboring layers, are attracting great attention because of the rich intriguing physical phenomena associated with them. Of particular interest are the topological network modes, first proposed in the small angle twisted bilayer graphene under interlayer bias. Here we report the observations of such topological network modes in twisted moiré phononic crystals without requiring the external bias fields. Acoustic topological network modes that can be constructed in a wide range of twist angles are both observed in the domain walls with and without reconstructions, which serve as the analogy of the lattice relaxations in electronic moiré materials. Topological robustness of the topological network modes is observed by introducing valley-preserved defects to the network channel. Furthermore, the network can be reconfigured into two-dimensional patterns with any desired connectivity, offering a unique prototype platform for acoustic applications.

Aerogel honeycombs with orientation-induced microstructures for high-temperature lightweight composite sandwich structures

Lightweight honeycomb structures are widely used in applications that require high strength-to-weight ratios and low densities, including aircraft, automobiles, and various engine components. However, due to the immaturity of microstructure conditioning techniques and the fact that highly porous structures usually fracture during stretching, it is challenging to obtain both high-strength and lightweight porous structures. Herein, a newly developed multilayer interconnected polyimide aerogel-based paper honeycomb is successfully prepared based on the ice crystal reverse template method and multi-level structure regulation via chemical and physical interactions. The synergistic effect of the hot extrusion-stress strategy and the heat imidization process provides the submicron layer of the paper honeycomb wall with more orderly molecular chain stacking, excellent orientation, and an enhanced folding degree between layers. The prepared polyimide aerogel paper honeycombs have low density (approx. 8–9 kg/m3), good shear strength of 1.07 MPa (W direction) and 0.86 MPa (L direction), excellent specific compressive strength (0.38 MPa), and excellent thermal stability. These integrally molded polyimide paper honeycombs, as sandwich resin-based composite structures, provide a new versatile platform for aerospace and marine applications.

A microfluidic ratiometric electrochemical aptasensor for highly sensitive and selective detection of 3,3',4,4'-tetrachlorobiphenyl.

This study proposes a strategy using a microfluidic ratiometric electrochemical aptasensor to detect PCB77 with excellent sensitivity and specificity. This sensing platform combines a microfluidic chip, a wireless integrated circuit system for aptamer-based electrochemical detection, and a mobile phone control terminal for parameter configuration, identification, observation, and wireless data transfer. The sensing method utilizes a cDNA (MB-COOH-cDNA-SH) that is labelled with the redox probe Methylene Blue (MB) at the 5' end and has a thiol group at the 3' end. Additionally, it utilizes a single strand PCB aptamer that has been modified with ferrocenes at the 3' end (aptamer-Fc). Through gold-thiol binding, the labelled probe of MB-COOH-cDNA-SH was self-assembled onto the surface of an Au/Nb2CTx/GO modified electrode. On exposure to aptamer-Fc, it will hybridize with MB-COOH-cDNA-SH to form a stable double-stranded structure on the electrode surface. When PCB77 is present, aptamer-Fc binds specifically to the target, enabling the double-stranded DNA to unwind. Such variation caused changes in the differential pulse voltammetry (DPV) peak currents of both MB and Fc. A substantial improvement is observed in the ratio between the two DPV peaks. Under the optimum experimental conditions, this assay has a response that covers the 0.0001 to 1000 ng mL-1 PCB77 concentration range, and the detection limit is 1.56 × 10-5 ng mL-1. The integration of a ratiometric electrochemical aptasensor with designed microfluidic and integrated devices in this work is an innovative and promising approach that offers an efficient platform for on-site applications.

MaDroid: A maliciousness-aware multifeatured dataset for detecting android malware

System call sequences representing the runtime behavior of an application is particularly useful for anomaly detection in mobile applications. However, one of the main obstacles in this area is the lack of publicly available high-quality datasets. Because of the low computational power and storage constraints of mobile application platforms, a single mobile device cannot accomplish the task of massively installing applications and extracting interaction details with the operating system, making it extremely challenging to build large-scale fine-grained system call datasets. In this paper, we present the MaDroid dataset. It is the first comprehensive dataset and benchmark for anomaly detection in mobile applications using high-dimensional feature sequence data and maliciousness, and the first to incorporate virus total rating (VT) values into dataset features. It is constructed based on an automated collection framework that collects system call sequences from simulation environments at a fine-grained level for both normal and malicious mobile applications. The dataset is 457 GB in size and consists of 50,429 labeled system call sequences. The dataset covers mobile applications released at different times over the past 14 years, and the selected applications span across 10 major mainstream APP markets. We extract different feature subsets from the dataset and perform evaluations using RF, MLP, and GBDT to show the effectiveness and accuracy in detecting malicious mobile APPs. Our dataset can be a useful resource for security and machine learning community.

The Influence of Product Innovation and Price Perception on Coffee Purchasing Decisions on the Aerocoffeenery Soreang Online Platform Application

The purpose of this study was to determine the effect of Product Innovation and Price Perception on consumer purchasing decisions on the Coffee Online Platform Application Aerocoffeenery Soreang both partially and simultaneously. The population in this study were consumers and customers at Coffee Online Platform Application Aerocoffeenery Soreang, with a total of 100 samples. The sampling technique used in this study was a non-probability sampling technique. The method used in this research is Quantitative Method with the data collection technique used is interviews and distributing questionnaires to respondents. The data analysis technique used is multiple linear regression with the SPSS program. The results of the study concluded that: (1) Product Innovation has a positive and significant influence on Purchasing Decisions. (2) Price Perception has a positive and significant influence on Purchasing Decisions. (3) In simultaneous testing, Product Innovation and Price Perception have a positive and significant influence on purchasing decisions for consumers and customers of the Coffee Online Platform Application Aerocoffeenery Soreang. The magnitude of the influence of Product Innovation and Price Perception is indicated by the Adjusted R Field value of 74.8% and the remaining 26.2% is influenced by other variables not examined in this study.

Pd-Catalyzed Atroposelective C-H Olefination: Diverse Synthesis of Axially Chiral Biaryl-2-carboxylic Acids.

Axially chiral carboxylic acids are important motifs in chiral catalysts and ligands. We herein reported the synthesis of axially chiral carboxylic acids via Pd(II)-catalyzed atroposelective C-H olefination using carboxylic acid as the native directing group. A broad range of axial chiral biaryl-2-carboxylic acids were synthesized in good yields with high enantioselectivities (up to 84% yield with 99% ee). Gram-scale reaction and further transformation reactions also provide a platform for synthetic applications of this method.

Pricing strategy based on a stochastic problem with barter exchange under variable promotional effort for a retail channel

Barter exchange platform gains popularity as an effective trade exchange strategy to minimize the vast use of paper money. In retail management, the application of the barter platform is growing because of cashless trade. It allows a retail enterprise to trade unused products in exchange for other assets purchased by reducing the actual purchase of assets. In this context, the study analyzes a stochastic model of a barter exchange problem under a retail channel. It investigates the barter exchange policy in three different models: conventional newsvendor model without barter exchange, with barter exchange, and with barter exchange with promotional effort and emissions level. The market demand for products is considered random and random with deterministic variables for three types of models. Stochastic models are solved in two different ways: with and without probability distribution functions of the random market demand. For maximization of the retailer's profit, the proposed framework obtains optimal decisions on ordered quantity, retail price, promotional effort, and emissions level. Five examples are tested and numerical results show that the barter exchange policy is more profitable than a traditional newsvendor model. A combination of stochastic and deterministic variable demand provides 34.31% more profit than a stochastic demand. Sensitivity analysis, discussions, and managerial insights are provided in detail on optimal decisions.

An aptamer-mediated base editing platform for simultaneous knockin and multiple gene knockout for allogeneic CAR-T cells generation

Gene editing technologies hold promise for enabling the next generation of adoptive cellular therapies. Conventional gene editing platforms that rely on nuclease activity, such as Clustered regularly interspaced short palindromic repeats-CRISPR associated protein 9 (CRISPR-Cas9), allow efficient introduction of genetic modifications; however, these modifications occur via the generation of DNA double-strand breaks (DSBs) and can lead to unwanted genomic alterations and genotoxicity. Here, we apply a novel modular RNA aptamer-mediated Pin-point™ base editing platform to simultaneously introduce multiple gene knockouts and site-specific integration of a transgene in human primary T cells. We demonstrate high editing efficiency and purity at all target sites and significantly reduced frequency of chromosomal translocations compared to the conventional CRISPR-Cas9 system. Site-specific knock-in of a chimeric antigen receptor (CAR) and multiplex gene knockout are achieved within a single intervention and without the requirement for additional sequence-targeting components. The ability to perform complex genome editing efficiently and precisely highlights the potential of the Pin-point platform for application in a range of advanced cell therapies.

To Dilute or Not to Dilute: Nominal Titer Dosing for Genetic Medicines.

Recombinant adeno-associated virus (AAV) has become a popular platform for many gene therapy applications. The strength of AAV-based products is a critical quality attribute that affects the efficacy of the drug and is measured as the concentration of vector genomes, or physical titer. Because the dosing of patients is based on the titer measurement, it is critical for manufacturers to ensure that the measured titer of the drug product is close to the actual concentration of the batch. Historically, dosing calculations have been performed using the measured titer, which is reported on the drug product label. However, due to recent regulatory guidance, sponsors are now expected to label the drug product with nominal or "target" titer. This new expectation for gene therapy products can pose a challenge in the presence of process and analytical variability. In particular, the manufacturer must decide if a dilution of the drug substance is warranted at the drug product stage to bring the strength in line with the nominal value. In this paper, we present two straightforward statistical methods to aid the manufacturer in the dilution decision. These approaches use the understanding of process and analytical variability to compute probabilities of achieving the desired drug product titer. We also provide an approach for determining an optimal assay replication strategy for achieving the desired probability of meeting drug product release specifications.

MXene-based all-solid flexible electrochromic microsupercapacitor

With the increasing demand for multifunctional optoelectronic devices, flexible electrochromic energy storage devices are being widely recognized as promising platforms for diverse applications. However, simultaneously achieving high capacitance, fast color switching and large optical modulation range is very challenging. In this study, the MXene-based flexible in-plane microsupercapacitor was fabricated via a mask-assisted spray coating approach. By adding electrochromic ethyl viologen dibromide (EVB) into the electrolyte, the device showed a reversible color change during the charge/discharge process. Due to the high electronic conductivity of the MXene flakes and the fast response kinetics of EVB, the device exhibited a fast coloration/bleaching time of 2.6 s/2.5 s, a large optical contrast of 60%, and exceptional coloration efficiency. In addition, EVB acted as a redox additive to reinforce the energy storage performance; as a result, the working voltage window of the Ti3C2-based symmetric aqueous microsupercapacitor was extended to 1 V. Moreover, the device had a high areal capacitance of 12.5 mF cm−2 with superior flexibility and mechanical stability and showed almost 100% capacitance retention after 100 bending cycles. The as-prepared device has significant potential for a wide range of applications in flexible and wearable electronics, particularly in the fields of camouflage, anticounterfeiting, and displays.

Цифровизация сферы здравоохранения: тенденции развития и биоинформационная web-платформа компании Онко Генотест

Currently, an urgent task in all spheres of society is the creation of industry-specific digital platforms based on various economic methods for processing large amounts of information. The success of the implementation of the target program “Digital Economy of the Russian Federation” as a whole, and therefore the transition of sec-tors of the Russian economy to digitalization, largely depends on its solution. The healthcare sector today is among the leaders not only in the creation, but also in the practical application of digital platforms for the compre-hensive treatment of a wide range of diseases based on innovative approaches. In the course of the research, promising directions for the development of the global healthcare digitalization market in the field of medical diag-nostics and pharmacogenetics, as well as the activities of its main participants in the field of oncology, were iden-tified. The innovative advantages of the bioinformational web platform of the company Onco Genotest LLC are shown, ensuring the competitiveness of its activities.

Security, Privacy, and Decentralized Trust Management in VANETs: A Review of Current Research and Future Directions

Vehicular Ad Hoc Networks (VANETs) are powerful platforms for vehicular data services and applications. The increasing number of vehicles has made the vehicular network diverse, dynamic, and large-scale, making it difficult to meet the 5G network’s demanding requirements. Decentralized systems are interesting and provide attractive services because they are publicly available (transparency), have an append-only ledger (robust integrity protection), remove single points of failure, and enable distributed key management and communication in a peer-to-peer network. Researchers dedicated substantial efforts to advancing vehicle communications, however conventional cryptographic mechanisms are insufficient which enabled us to look at decentralized technologies. Therefore, we revisit decentralized approaches with VANETs. Endpoint devices hold a wallet which may incorporate threshold key management methods like MPC wallets, HD Wallets, or multi-party threshold ECDSA/EdDSA/BLS. We also discuss trust management approaches and demonstrate how decentralization can improve integrity, security, privacy, and resilience to single points of failure. We also conduct a comprehensive review, comparing them with current requirements, and the latest authentication and secure communication architectures, which require the involvement of trusted but non-transparent authorities in certificate issuance/revocation. We highlight the limitations of these schemes from PKI deployment and recommend future research, particularly in the realm of quantum cryptography.

Jellyfish-Inspired Self-Healing Luminescent Elastomers Based on Borate Nanoassemblies for Dual-Model Encryption.

Responsive luminescent materials that reversibly react to external stimuli have emerged as prospective platforms for information encryption applications. Despite brilliant achievements, the existing fluorescent materials usually have low information density and experience inevitable information loss when subjected to mechanical damage. Here, inspired by the hierarchical nanostructure of fluorescent proteins in jellyfish, we propose a self-healable, photoresponsive luminescent elastomer based on dynamic interface-anchored borate nanoassemblies for smart dual-model encryption. The rigid cyclodextrin molecule restricts the movement of the guest fluorescent molecules, enabling long room-temperature phosphorescence (0.37 s) and excitation wavelength-responsive fluorescence. The building of reversible interfacial bonding between nanoassemblies and polymer matrix together with their nanoconfinement effect endows the nanocomposites with excellent mechanical performances (tensile strength of 15.8 MPa) and superior mechanical and functional recovery capacities after damage. Such supramolecular nanoassemblies with dynamic nanoconfinement and interfaces enable simultaneous material functionalization and self-healing, paving the way for the development of advanced functional materials.