Simple Solution Research Articles

Solving the retention time repeatability problem of hydrophilic interaction liquid chromatography

Hydrophilic interaction (liquid) chromatography (HILIC) has become the first choice LC mode for the separation of hydrophilic analytes. Numerous studies reported the poor retention time repeatability of HILIC. The problem was often ascribed to slow equilibration and insufficient re-equilibration time to establish the sensitive semi-immobilized water layer at the interface of the polar stationary phase and the bulk mobile phase. In this study, we compare retention time repeatability in HILIC for borosilicate glass and PFA (co-polymer of tetrafluoroethylene and perfluoroalkoxyethylene) solvent bottles. During this study, we observed peak patterns shifting towards higher retention times (for metabolites and peptides) and lower retention times (oligonucleotide sample) with ongoing analysis time when standard borosilicate glass bottles were used as solvent reservoirs. It was hypothesized that release of ions (sodium, potassium, borate, etc.) from the borosilicate glass bottles leads to alterations (thickness and electrostatic screening effects) in the semi-immobilized water layer which is adsorbed to the polar stationary phase surface under acetonitrile-rich eluents in HILIC with concomitant shifts in retention. When PFA solvent bottles were employed instead of borosilicate glass, retention time repeatability was greatly improved and changed from average 8.4 % RSD for the tested metabolites with borosilicate glass bottles to 0.14 % RSD for the PFA solvent bottles (30 injections over 12 h). Similar improvements were observed for peptides and oligonucleotides. This simple solution to the retention time repeatability problem in HILIC might contribute to a better acceptance of HILIC, especially in fields like targeted and untargeted metabolomics, peptide and oligonucleotide analysis.

Ratiometric nonfluorescent CRISPR assay utilizing Cas12a-induced plasmid supercoil relaxation

Most CRISPR-based biosensors rely on labeled reporter molecules and expensive equipment for signal readout. A recent approach quantifies analyte concentration by sizing λ DNA reporters via gel electrophoresis, providing a simple solution for label-free detection. Here, we report an alternative strategy for label-free CRISPR-Cas12a, which relies on Cas12a trans-nicking induced supercoil relaxation of dsDNA plasmid reporters to generate a robust and ratiometric readout. The ratiometric CRISPR (rCRISPR) measures the relative percentage of supercoiled plasmid DNA to the relaxed circular DNA by gel electrophoresis for more accurate target concentration quantification. This simple method is two orders of magnitude more sensitive than the typical fluorescent reporter. This self-referenced strategy solves the potential application limitations of previously demonstrated DNA sizing-based CRISPR-Dx without compromising the sensitivity. Finally, we demonstrated the applicability of rCRISPR for detecting various model DNA targets such as HPV 16 and real AAV samples, highlighting its feasibility for point-of-care CRISPR-Dx applications.

Synergistic engineering of doped Ni2P-Ni12P5 heterostructure electrocatalysts for urea oxidation reaction

Urea oxidation reaction (UOR) is regarded as a potential approach for industrial hydrogen production to address energy scarcity and water pollution challenges. Fabrication of efficient and stable electrocatalysts is a crucial factor in H2 yield and energy conversion efficiency. Herein, we propose a synergistic engineering route to develop the heteroatom-doped Ni2P-Ni12P5 heterojunction on the porous carbon as the electrocatalyst via the simple solution combustion method. The shift of the diffraction peaks, the change of the lattice spacing, and the difference in the electronic distribution indicate that Cu or Mn heteroatoms are successfully doped into the heterojunction Ni2P-Ni12P5 structure, not only promoting the formation of the Ni3+ but also accelerating the electron transfer. As a result, the doping of Cu and Mn into the Ni2P-Ni12P5 heterojunction obtains high-performance electrocatalysts for the UOR. The Mn doping enhances the catalytic performance of the parent Ni2P-Ni12P5 heterostructure, achieving the potential of 1.319 V at 100 mA∙cm−2 in UOR. Moreover, the Cu-doped Ni2P-Ni12P5 heterojunction catalyst shows a low potential of 1.318 V at 100 mA∙cm−2 and demonstrates exceptional long-term stability under different current densities. Notably, when this catalyst is employed in the two-electrode cell for urea-assisted water electrolysis, the hydrogen production readily occurs at the voltage of 1.47 V for reaching 100 mA∙cm−2, manifesting the electrocatalyst with high activity and stability to be a promising candidate for energy-saving electrolytic hydrogen production on the industrial scale.

Fabrication of nickel aluminate based electrochemical sensor for dopamine detection

Nickel aluminate nanoparticles (NiAl2O4 NPs) spinel structure is synthesized via a simple solution combustion method using aqueous nickel nitrate, aluminum nitrate and citric acid. The crystal structure and microstructure of the prepared NiAl2O4 NPs are confirmed by powder X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Fourier transform infrared (FTIR) spectrum, scanning and transmission electron microscopy (SEM/TEM). The characterized NiAl2O4 NPs are applied on a glassy carbon electrode (GCE) to design electrochemical sensor for the detection of dopamine (DA) using cyclic voltammograms (CV) and differential pulse anodic stripping voltammograms. The proposed electrochemical sensor exhibits excellent sensing activity with a low detection limit of 1.78 μM and applicable for a wide linear concentration range of 10 μM–140 μM. Further, the proposed electrode exhibits well resolved differential pulse voltammogram for the dopamine in presence of interfering uric acid and ascorbic acid.

Geometrical characterization of healthy red blood cells using digital holographic microscopy and parametric shape models for biophysical studies and diagnostic applications

Modeling of the red blood cell (RBC) shape is an integral part of the experimental and computer simulation investigations of light scattering by these cells for fundamental studies as well as diagnostic applications in techniques like cytometry and quantitative phase imaging. In the present work, a comprehensive study of the geometrical characterization of healthy human RBCs using digital holographic microscopy (DHM) and six frequently employed parametric shape models is reported. It is shown that the comparison of the optical phase profiles, and the thickness profiles given by the models with the DHM results gives a better judgment of the appropriateness of the parametric shape models. It is also shown that the RBC parametric models offer a simpler solution to the refractive index-thickness decoupling problem in QPI methods. Results of geometrical characterization of 500 healthy RBCs in terms of volume, surface area (SA), and sphericity index (SI) led to the classification of the parametric models in two categories based on the nature of variation of these quantities with the cell diameter. In light of the variability of the healthy RBC shapes, our findings suggest that the parametric models exhibiting a negative correlation between the SI and the cell diameter would provide more reliable estimates of the RBC parameters in diagnostic applications. Statistical distributions and descriptive statistics of the RBC volume, SA and SI serve as a guide for the assessment of the capability of the studied parametric models to give a reliable account of the variability of the healthy RBC shape and size.

The Potential for Digital Phenotyping in Understanding Mindfulness App Engagement Patterns: A Pilot Study.

Background: Low app engagement is a central barrier to digital mental health efficacy. With mindfulness-based mental health apps growing in popularity, there is a need for new understanding of factors influencing engagement. This study utilized digital phenotyping to understand real-time patterns of engagement around app-based mindfulness. Different engagement metrics are presented that measure both the total number of app-based activities participants completed each week, as well as the proportion of days that participants engaged with the app each week. Method: Data were derived from two iterations of a four-week study exploring app engagement in college students (n = 169). This secondary analysis investigated the relationships between general and mindfulness-based app engagement with passive data metrics (sleep duration, home time, and screen duration) at a weekly level, as well as the relationship between demographics and engagement. Additional clinically focused analysis was performed on three case studies of participants with high mindfulness activity completion. Results: Demographic variables such as gender, race/ethnicity, and age lacked a significant association with mindfulness app-based engagement. Passive data variables such as sleep and screen duration were significant predictors for different metrics of general and mindfulness-based app engagement at a weekly level. There was a significant interaction effect for screen duration between the number of mindfulness activities completed and whether or not the participant received a mindfulness notification. K-means clusters analyses using passive data features to predict mindfulness activity completion had low performance. Conclusions: While there are no simple solutions to predicting engagement with mindfulness apps, utilizing digital phenotyping approaches at a population and personal level offers new potential. The signal from digital phenotyping warrants more investigation; even small increases in engagement with mindfulness apps may have a tremendous impact given their already high prevalence of engagement, availability, and potential to engage patients across demographics.

An Exact Solution to the Inverse Problem of Steady Free-Surface Flow over Topography

A simple exact solution is presented to the inverse problem in steady, two-dimensional idealised flow over topography that seeks the bottom profile given knowledge of the free-surface data. Attention is focused on the case when a uniform stream flows over a localised obstacle, although the solution is not restricted to this case. The inverse problem is formulated as a Stieltjes integral equation which is solved exactly using a Fourier transform. The solution requires the analytic continuation of two real functions representing the surface speed and the angle between the surface velocity vector and the horizontal. Some example surface profiles and their corresponding bottom topographies are discussed. Although the solution requires the prescription of the surface as a function of the velocity potential, it is shown to closely resemble the corresponding profile in physical space, even for quite large surface displacements, while significant discrepancy occurs at the bottom. Inference of the bottom profile from discrete surface data is accomplished by way of polynomial interpolation and rational approximation in the complex plane for the sample case of a hydraulic fall.

SELECTION OF OPTIMAL PARAMETERS OF A LIGHTWEIGHT FLAT FLOOR WITH VOIDS MADE OF PLASTIC BALLS

Formulation of the problem. Architectural and construction design of buildings using reinforced concrete has led to an increase in the number of objects with an individual space-planning structure, a rich variety of facade and volumetric solutions. Today the question of the effectiveness of using flat prefabricated monolithic lightweight floors in the construction of multi-storey buildings with individual space-planning and architectural solutions is relevant. In a market economy interest in the issue of rational use of resources, namely the cost of concrete and reinforcement in construction, has sharply increased, which is directly related to attracting investment. As it is known, when designing buildings from prefabricated monolithic reinforced concrete, in contrast to prefabricated concrete, there is greater freedom in adopting the space-planning parameters of the building, and there may also be simpler design solutions, in particular for floors. The constructive solution of floors depends on numerous requirements for the building as a whole and directly for the floor. One of the requirements that influences the attraction of investments is a small material-intensive floor covering with significant spans of buildings of various structural systems. The effective use of lightweight precast monolithic reinforced concrete floors with voids made of plastic balls in construction requires a comprehensive technical and economic analysis of this innovative solution for the precast monolithic reinforced concrete floor structure. The purpose of the article is to perform a technical and economic comparison of various design options for a flat lightweight prefabricated monolithic floor. The influence of floor parameters on the consumption of concrete and reinforcement is considered. Conclusion. As a result of the research, it was established that it is rational to use hollow balls made from recycled materials as a material for making voids from balls in flat floors. Moreover, all studied floor options with spans of 6 m, 7 m, 8 m and void sizes made of balls with diameters of 180 mm, 315 mm and 50 0mm meet the requirements of the first and second groups of limit states.

A Microporous Gel Polymer Electrolyte with High Mg2+ Ionic Conductivity at Room Temperature

AbstractRechargeable magnesium batteries have attracted much attention due to the high theoretical volumetric capacity, abundance, and safety. However, solid‐state Mg batteries have been rarely studied because of limited choices of solid‐state electrolyte materials. In this research, poly(vinylidene fluoride)/poly(propylene carbonate) (PVDF/PPC) as matrix were prepared using a simple solution casting method. Ethylene carbonate (EC), diethyl carbonate (DEC), and magnesium(II) bis(trifluoromethanesulfonyl) imide [Mg(TFSI)2] were selected to prepare liquid electrolyte. A classification of novel gel polymer electrolytes (GPEs), PVDF/PPC/Mg(TFSI)2, was synthesized and investigated. The electrochemical measurements show that PVDF/PPC/Mg(TFSI)2 polymer electrolytes exhibit a high ionic conductivity, close to 10−2 S cm−1, at room temperature. The electrochemical stability window of PVDF/PPC‐based GPE was up to 3 V (versus Mg2+/Mg). Materials characterization shows that these GPEs have a porous structure, providing a pathway for magnesium ion transport. Thermal analysis and crystal structure results indicate that PVDF crystallinity was affected by the addition of PPC. Additionally, the ion transport mechanism in the gel polymer electrolyte has been discussed.

An Energy-Efficient Integrated System by Coupling Carbon Dioxide Reduction and Methanol Oxidation to Produce the Identical Value-Added Formic Acid

Metal-organic frameworks (MOFs) are considered as promising catalytic materials for electrochemical carbon dioxide reduction (ECR) reactions due to their excellent properties. However, the development of efficient and stable electrocatalysts within a wide potential window remains a great challenge. Herein, the rod-like Sn-MOF is synthesized by a fast and simple solution reaction, which has good performance in converting CO2 to HCOOH. In particular, Sn-MOF reaches a maximum Faradaic efficiency of 86.4% at −1.15 V vs RHE with a current density of 25.2 mA cm−2. It is worth noting that Sn-MOF has excellent long-term stability, maintaining more than 80% of FEHCOOH production within 30 h of continuous electrolysis. Meanwhile, X-ray diffraction and X-ray photoelectron spectroscopy characterization confirm that Sn2+ in Sn-MOF can be reduced to Sn0 in the ECR reaction. The theoretical results show that *COOH intermediate tends to form in the ECR process on Sn-MOF, and it has a high selectivity for the formation of HCOOH. In addition, the two-electrode system driving the co-electrolysis of methanol and CO2 can significantly reduce the voltage by 500 mV at a current density of 20 mA cm−2.

Linear matrix genetic programming as a tool for data-driven black-box control-oriented modeling in conditions of limited access to training data

In the paper, a new evolutionary technique called Linear Matrix Genetic Programming (LMGP) is proposed. It is a matrix extension of Linear Genetic Programming and its application is data-driven black-box control-oriented modeling in conditions of limited access to training data. In LMGP, the model is in the form of an evolutionarily-shaped program which is a sequence of matrix operations. Since the program has a hidden state, running it for a sequence of input data has a similar effect to using well-known recurrent neural networks such as Long Short-Term Memory (LSTM) or Gated Recurrent Unit (GRU). To verify the effectiveness of the LMGP, it was compared with different types of neural networks. The task of all the compared techniques was to reproduce the behavior of a nonlinear model of an underwater vehicle. The results of the comparative tests are reported in the paper and they show that the LMGP can quickly find an effective and very simple solution to the given problem. Moreover, a detailed comparison of models, generated by LMGP and LSTM/GRU, revealed that the former are up to four times more accurate than the latter in reproducing vehicle behavior.

Hope on the Horizon? Aptamers in Diagnosis of Invasive Fungal Infections.

Despite remarkable advances in the diagnosis of invasive fungal infections (IFIs), rapid, specific, sensitive, and cost-effective detection methods remain elusive. Due to their stability, ease of production, and specificity to signature molecules of fungal pathogens, short single-stranded sequences of DNA, RNA, and XNA, collectively called aptamers, have emerged as promising diagnostic markers. In this perspective, we summarize recent progress in aptamer-based diagnostic tools for IFIs and discuss how these tools could potentially meet the needs and provide economical and simple solutions for point-of-care for better management of IFIs.

Highly flame retardancy, barrier, mechanical and persistent antibacterial polylactic acid film with high-parallel interconnected thousand layered cake architecture

In this work, a bio-based material (CGP) is obtained by combing chitosan, gelatin and polyvinyl alcohol through a simple solution mixing to simultaneously address polylactic acid film (PLA)' flammability and poor barrier, toughness and antibacterial properties by soaking. The results of open fire testing show that modified PLA films can effectively prolong the combustion time, improve the thermal stability and reduce the release of heat in the cone calorimeter test. For the PLA sample after soaking for 5 times (PLA-5) in particular, it can reduce the peak heat release rate (pHRR) and total heat release (THR) values to 85.8 kW/m2 and 1.3 MJ/m2 from the values of 129.5 kW/m2 and 1.8 MJ/m2 for PLA, respectively. Structural analysis suggests that CGP primarily operates in the condensed phase by forming physical barriers. Meanwhile, the modified PLA films can exhibit superior barrier effects, which indicate the oxygen transmission rate value of PLA-5 decreases to 0.9 cm3/(m2·day) from the 392.5 cm3/(m2·day) of raw PLA film. Moreover, the PLA-5 also have excellent toughness (the value increased to 200.5 % from 31.0 %) and persistent antibacterial effects (it still has 100 % sterilization after 500 days).

MSTG: Multi-Scale Transformer with Gradient for joint spatio-temporal enhancement

Despite the widespread availability of HDR (High Dynamic Range) display devices, the majority of video sources are still stored in SDR (Standard Dynamic Range) format, leading to an urgent need for UHD (Ultra High Definition) video reconstruction. A simple solution is to divide the task into two sub-tasks: video super-resolution (SR) and video Bit-Depth Enhancement (BDE). While some joint enhancement tasks led by SR have been explored in multiple dimensions, the quantitative dimension has often been overlooked. In this paper, we address the first joint task of BDE and SR and propose a succinct network called MSTG. We conduct a systematic analysis to explain how this effect can be achieved and overcome the core challenge arising from distortions exacerbated by the differing optimization directions of BDE and SR. This challenge is attributed to indistinguishable contours and detailed textures. To tackle this, we employ a dual-branch module that leverages both gradient and image information to discern between BDE and SR. Furthermore, we propose a novel model named Cross-scale Transformer (CTF) embedded with Cross-scale Attention (CSA). This model facilitates information aggregation while adaptively utilizing structural similarity features. It jointly extracts, aligns, and fuses frame features at multiple scales, forming the MST module. Experiments demonstrate that the proposed algorithm outperforms the cascaded video enhancement methods by large margins on both synthetic and realistic datasets.

Independent Long COVID Journalism as a Lens for Critical Information Literacy: Conversations with The Sick Times Founders Betsy Ladyzhets and Miles W. Griffis

Both the COVID-19 pandemic and the acceleration of climate change illuminate how difficult it can be to make sense of information about wicked problems—that is, issues that are highly complex and have no simple or complete solutions (Rittel & Webber, 1973). One approach to grappling with wicked problems is to consider the information practices that different people, communities, or professions use to make sense of those issues. In this Perspectives piece, I explore possible ways to practice and teach about critical information literacy by looking to the views, experiences, and professional practices of two independent journalists who report on an urgent but still under-reported wicked problem: Long COVID. Betsy Ladyzhets and Miles W. Griffis are the co-founders of the website The Sick Times, which is dedicated to reporting on Long COVID and the ongoing COVID-19 pandemic. Following highlights from their interviews with me about their work, I consider potential implications of these journalists’ experiences for practicing and teaching critical information literacy.

Dynamics of a stage-structured predator-prey system with fear-induced group defense in autonomous and nonautonomous settings.

In this investigation, we construct a predator-prey model that distinguishes between immature and mature prey, highlighting group defense strategies within the mature prey. First, we embark on exploring the positivity and boundedness of the solution, unraveling sustainable equilibrium points, and deducing their stability conditions. Upon further investigation, we observe that the system exhibits diverse bifurcations, including Hopf, saddle-node, transcritical, generalized Hopf, cusp, and Bogdanov-Takens bifurcations. The results reveal that heightened fear decreases mature prey density, potentially causing prey extinction beyond a certain threshold. Increased maturation rates lead to the coexistence of immature and mature prey populations and higher predator density. Stronger group defense boosts mature prey density, while weaker defense results in weak persistence. Lower values of the maturation rate of prey and the decline rate of predators sustain only the predator population, reliant on resources other than focal prey. Furthermore, our model demonstrates intriguing and diverse dynamical phenomena, including various forms of bistability across distinct bi-parameter planes. We also explore the dynamics of a related nonautonomous system, where certain parameters are considered to vary with time. In the seasonally forced model, we set out to define criteria regarding the existence and stability of positive periodic solutions. Numerical investigations into the seasonally forced model uncover a spectrum of dynamics, ranging from simple periodic solutions to higher periodicities, bursting patterns, and chaotic behavior.

Self‐Made Equipment for Automatic Methane Diffusion and Ebullition Measurements From Aquatic Environments

AbstractFreshwater ecosystems are believed to account for about half of global methane emissions, but this estimate is uncertain due to few measurements in some geographical regions and most important for our purposes, large local variations. We propose a simple, cheap (<200€), and effective solution to the urgent need for equipment that can provide accurate data on methane emission at high spatial and temporal resolution for many days, across many ecosystems and regions, and with limited inspection. A low‐cost metal oxide semiconductor sensor, placed in a floating chamber equipped with an air pump to flush the chamber's headspace at regular intervals, provides frequent and accurate high‐resolution measurements of diffusive and ebullitive methane emissions from lakes and rivers. We made several improvements that yield more useful data and enable the setup to operate for several days without visual inspection. To test the accuracy of the equipment, we compared its measurements of methane emission to parallel measurements by an expensive, commercially available laser sensor. The correspondence was excellent (R2 ≥ 0.94) and the deviation of measurements was minimal at fluxes within ranges encountered in the field. We also designed an R‐package (FluxSeparator), which associates the large sensor‐generated data sets with diffusive and ebullitive flux activity. Both the sensor setup and the R‐package are flexible and have been made publicly available to encourage others to use and further improve the equipment and calculations.

Efficient Determination of Critical Water Activity and Classification of Hydrate-Anhydrate Stability Relationship

For a pair of hydrated and anhydrous crystals, the hydrate is more stable than the anhydrate when the water activity is above the critical water activity (awc). Conventional methods to determine awc are based on either hydrate-anhydrate competitive slurries at different aw or solubilities measured at different temperatures. However, these methods are typically resource-intensive and time-consuming. Here, we present simple and complementary solution- and solid-based methods and illustrate them using carbamazepine and theophylline. In the solution-based method, awc can be predicted using intrinsic dissolution rate (IDR) ratio or solubility ratio of the hydrate-anhydrate pair measured at a known water activity. In the solid-based method, awc is predicted as a function of temperature from the dehydration temperature and enthalpy obtained by differential scanning calorimetry (DSC) near a water activity of unity. For carbamazepine and theophylline, the methods yielded awc values in good agreement with those from the conventional methods. By incorporating awc as an additional variable, the hydrate-anhydrate relationship is categorized into four classes based on their dehydration temperature (Td) and enthalpy (ΔHd) in analogy with the monotropy/enantiotropy classification for crystal polymorphs. In Class 1 (ΔHd< 0 and Td ≥ 373 K), no awc exists. In Class 2 (ΔHd>0andTd≥373K), awc always exists under conventional crystallization conditions. In Class 3 (ΔHd<0andTd<373K), awc exists when T>Td. In Class 4 (ΔHd>0andTd<373K), awc exists only when T<Td. The hydrate-anhydrate pairs of carbamazepine and theophylline belong to Class 4.

An electrocatalytic sensing of 2, 6-dichlorophenol based on Dy2O3-Co3O4@CeO2 nanocomposite modified GCE: An enhanced environmental safety

Anthropogenic activities are continuously polluted our environment by releasing various kind of toxic chemicals as waste product. Their removal has gained the impressive importance among the scientists in order to maintain the integrity of our ecosystem. In this present work, Dy2O3-Co3O4@CeO2 nanocomposite (NC) was prepared by simple solution method with the aspiration to detect as well as electro-hydrolyzed the toxic chemicals in an aqueous system. Structural, morphological and optical properties of our newly synthesised nanocomposite were investigated by using advanced analytical tools such as ultraviolet–visible difused reflectance spectroscopy (UV-DRS), fourier transform infrared (FT-IR) spectroscopy, powder X-ray diffraction (XRD), field emission scanning electron microscope equipped with energy dispersive spectroscopy (FESEM-EDS), and transmission electron microscope (TEM) in addition to Brunauer-Emmet-Teller (BET) analysis. After detailed characterization of newly synthesized Dy2O3-Co3O4@Ce2O3 nanocomposite, it was used with 5 % PEDOT:PSS (poly(3,4-ethylenedioxythiophene) polystyrenesulfonate), a conducting polymer binder, to modify the glassy carbon electrode (GCE) as selective electrochemical sensor (Dy2O3-Co3O4@CeO2-NC/PEDOT:PSS/GCE). After that, this newly designed Dy2O3-Co3O4@CeO2-NC/PEDOT:PSS/GCE was evaluated so as to check its detection as well as electrocatalytic behaviour against the toxic chemicals in an aqueous system using novel electrochemical current–potential (I–V) approach, for the first time. A comparative investigation revealed that this newly designed Dy2O3-Co3O4@CeO2-NC/PEDOT:PSS/GCE was very selective against the 2, 6-dichlorophenol (2, 6-DCP) and had good affinity with it even in the company of other interference chemicals. In order to optimise newly developed Dy2O3-Co3O4@CeO2-NC/PEDOT:PSS/GCE as an effective as well as selective 2, 6-DCP electrochemical sensor, analytical parameters such as, limit of detection (LOD), limit of quantification (LOQ), sensitivity etc were calculated from slop of calibration curve. The LOD at signal-to-noise ratio (S/N) of 3, LOQ, and sensitivity were calculated as 0.014 ± 0.001 nM, 0.046 ± 0.001 nM, and 65.82 µAµM-1cm−2, respectively, over a linear dynamic range (LDR) of our target analyte concentration (0.1 nM – 0.1 M) with r2 square value as 0.9988. Consequently, this study enlightens us that this newly fabricated electrochemical sensor, selective only for 2, 6-DCP, is very cost-effective, efficient, and stable over time. Moreover, it also initiates a new way to effectively interrogate the various toxic chemicals in real samples by using a novel electrochemical (I–V) approach based on reported / non-reported different kind of semiconductor nanocomposite modified GCEs as selective electrochemical sensors.

A User Priorities Based Strategy for Three Phase Intelligent Recommendation and Negotiating Agents for Cloud Services

As the field of information technology expands, there is a huge need for cloud service providers (CSP). CSP’s vast solutions and services support Cloud, IoT, Fog, and Edge computing. In today’s competitive cloud market, customer satisfaction is critical more than ever. CSP and consumer satisfaction with service level agreement (SLA) fulfilment have always been given more attention. As a result of signing SLA and CSP agreements to supply resources in high demand, customers are now experiencing issues with resource delivery. Cloud and heterogeneous environments necessitate an intelligent recommender and negotiation agent model (IRNAM) to handle responsibilities in the current system. The Recommender system recommends CSP as per users’ priorities, which eases the filtration process. The negotiation process provided by IRNAM ensures that users’ choices are prioritized with maximum jobs to CSP. IRNAM keeps track of the most critical metrics and can reach decisions quickly and for the best possible deal. It uses an analytical concession algorithm that analyzes consumer and CSP choices to find a reliable, secure server with the simplest solution. The negotiation process uses user’s and CSP choice metrics, performance factors, evaluation measures, and success factors in the best execution time to decide. IRNAM provides a flexible and valuable way for selecting CSP and negotiating for services on the user’s terms while considering CSP satisfaction.