Analytical Response Research Articles

Flexible Piezoelectric Nanocolumnar Composite Films as Flat-Panel Loudspeakers: Application and Modeling.

Highly anisotropic piezoelectric composites promise to progress electroacoustic devices as a class by combining the advantages of both piezoceramics and polymers. Fundamentally, piezoelectric loudspeakers employ the converse piezoelectric effect to convert electrical to mechanical energy. Quasi-1-3 piezoceramic/polymer composites enable flat-panel loudspeakers that are tunable in elastic modulus, with opportunities for mechanical flexibility, optical transparency, and large-area coverage. Their processing route enables relatively flexible design parameters, such as the particle loading, polymer-matrix modulus, film thickness, film size, and electrode-material stiffness. Alternative processing routes of electric field (E-field) aligned-piezoelectric composites are demonstrated, including using the relaxor ferroelectric lead magnesium niobate-lead titanate (PMN-PT) to enhance the acoustic performance and photocurable resins to accelerate the materials processing. Material properties critical for dielectrophoresis are characterized, and loudspeakers were fabricated based on the optimal processing conditions. Subsequently, electroacoustic characterization explores the effect of loudspeaker size, substrate stiffness, the microphone distance, the piezoceramic material, and the matrix modulus. Finally, finite-element (FE) modeling of the electromechanical behavior validates the natural frequencies and modes shapes of the loudspeakers via the analytical solution and frequency response to electrical and mechanical excitation. Good correspondence between the predicted electroacoustic performance and experimentally validated model is observed.

Catalytic competence of gold clusters decorated yellow 2 G polymer composite film for voltammetric sensing of dopamine and nicotine in biological fluids

A novel, simple, cost-effective, easy-to-prepare, and timesaving electrochemical sensor based on gold clusters decorated yellow 2 G polymer composite film was fabricated and comprehensively characterized for the determination of dopamine and nicotine in real samples. When gold clusters were modified on the yellow 2 G polymer film, a signal increase of 204 % for dopamine and 526 % for nicotine was obtained compared to the activated bare pencil graphite electrode. The signals at 90 mV for dopamine and 780 mV for nicotine were utilized as analytical responses. The fabricated platform serves noteworthy detection sensitivity values of 79.02μA.μM−1.cm−2 and 14.61μA.μM−1.cm−2 with a notable limit of detection values of 58.8 nM and 7.2 nM for dopamine and nicotine, respectively. The electrochemical method has linear ranges of 0.075–5 µM and 6–10 µM for dopamine alone, 0.01–10 µM and 12–25 µM for nicotine alone, 0.01–10 µM and 12–50 µM for nicotine in the presence of dopamine, 0.2–10 µM and 12–60 µM for dopamine in the presence of nicotine, and 0.4–2, 2–10 and 12–90 µM for dopamine and 0.2–8, 10–20 and 25–90 µM for nicotine at the increasing amounts of each substance. Moving forward, the developed method exhibits splendid accuracy and selectivity for determining dopamine and nicotine in biological samples of human saliva, serum, and urine.

Prompting Responses through Linguistic Cues: A Comparison of User and Chatbot Support for Consumers' Questions

ABSTRACTWhen interacting with chatbots, questioning is the starting point of the conversations. A well‐phrased question can elicit desired responses and enhance information‐seeking efficiency. Specifically, consumers can use various linguistic cues (e.g., emotional expressiveness) to phrase questions and shape responses. However, research on how to effectively phrase questions for chatbots was limited. This study focuses on consumers' questions for chatbots, examining how various linguistic cues (e.g., emotional expressiveness) influence responses. Further, it compares responses generated by community users and chatbots. Preliminary results showed that askers' self‐disclosure attracted emotional support from chatbots. Chatbots demonstrated higher expertise in responses to high‐specificity questions and produced more analytical and unified responses. In contrast, user‐generated responses were perceived with higher authenticity. This research underscores the role of question cues prompting chatbot‐generated responses and illustrates the strengths and limits of chatbot‐generated responses. Theoretical and practical implications are discussed in the final section.

Data Lakehouse: A survey and experimental study

Efficient big data management is a dire necessity to manage the exponential growth in data generated by digital information systems to produce usable knowledge. Structured databases, data lakes, and warehouses have each provided a solution with varying degrees of success. However, a new and superior solution, the data Lakehouse, has emerged to extract actionable insights from unstructured data ingested from distributed sources. By combining the strengths of data warehouses and data lakes, the data Lakehouse can process and merge data quickly while ingesting and storing high-speed unstructured data with post-storage transformation and analytics capabilities. The Lakehouse architecture offers the necessary features for optimal functionality and has gained significant attention in the big data management research community. In this paper, we compare data lake, warehouse, and lakehouse systems, highlight their strengths and shortcomings, identify the desired features to handle the evolving challenges in big data management and analysis and propose an advanced data Lakehouse architecture. We also demonstrate the performance of three state-of-the-art data management systems namely HDFS data lake, Hive data warehouse, and Delta lakehouse in managing data for analytical query responses through an experimental study.

Authentication of indigenous Brazilian specialty canephora coffees using smartphone image analysis

The prevention of coffee fraud through the use of digital and intelligence-based technologies is an analytical challenge because depending on the adulterant, visual inspection is unreliable in roasted and ground coffee due to the similarity in color and texture of the materials used. In this work, a 3D-printed apparatus for smartphone image acquisiton is proposed. The digital images are used to authenticate the geographical origin of indigenous canephora coffees produced at Amazon region, Brazil, against canephora coffees from Espírito Santo, Brazil, and to capture the adulteration of indigenous samples. The results evidenced that the technology is favorable to identify the geographical origin and adulteration with multiple substances using smartphone technology. Pure coffees were adulterated with arabica coffee, spent coffee ground, low-quality Canephora coffee, coffee husks, açaí, corn, and soybean in increasing proportions of 10, 20, 30, 40, 50, 60, and 70 %. These adulterants were roasted and grounded similarly to Canephora coffees to mimetize a highly-sophisticated fraud. The images were converted into Red-Green-Blue (RGB) fingerprinting and used as analytical response to construct Data-Driven Soft Independent Modeling of Class Analogy (DD-SIMCA) models. A total of 95 % of all target and non-target samples in the test set were correctely identified, aiding producers and consumers in ensuring accurate labeling and supporting traditional communities economically and culturally. Smartphone-based method demonstrated potential to innovate the coffee safety control representing a new analytical tecnology.

Automatic Differentiation for Explicitly Correlated MP2.

Automatic differentiation (AD) offers a route to achieve arbitrary-order derivatives of challenging wave function methods without the use of analytic gradients or response theory. Currently, AD has been predominantly used in methods where first- and/or second-order derivatives are available, but it has not been applied to methods lacking available derivatives. The most robust approximation of explicitly correlated MP2, MP2-F12/3C(FIX)+CABS, is one such method. By comparing the results of MP2-F12 computed with AD versus finite-differences, it is shown that (a) optimized geometries match to about 10-3 Å for bond lengths and a 10-6 degree for angles, and (b) dipole moments match to about 10-6 D. Hessians were observed to have poorer agreement with numerical results (10-5), which is attributed to deficiencies in AD implementations currently. However, it is notable that vibrational frequencies match within 10-2 cm-1. The use of AD also allowed the prediction of MP2-F12/3C(FIX)+CABS IR intensities for the first time.

Development of GC–MS coupled to GC–FID method for the quantification of cannabis terpenes and terpenoids: Application to the analysis of five commercial varieties of medicinal cannabis

Cannabis terpenes and terpenoids are among the major classes of pharmacologically active secondary metabolites of therapeutic interest. Indeed, these hydrocarbon molecules, responsible for the characteristic aroma of cannabis flowers, are thought to be involved in a synergistic effect known as the “entourage effect”, together with cannabinoids. Numerous analytical studies have been carried out to characterize the terpene and terpenoid contents of some cannabis varieties, but they have not proposed any real quantification or have described a limited number of analytical standards or average response factors, which may have led to over- or underestimation of the real content of the cannabis flowers. Real and reliable quantification is necessary to justify the entourage effect. Here, we report a rigorous and precise GC–FID and GC–MS method for the identification and quantification of cannabis terpenes and terpenoids. This method is distinguished by the use of a high number of analytical standards, the determination of retention indices for all compounds studied, an exhaustive comparison of databases and scientific literature, the use of relevant response factors, and internal calibration for reliable results. It was applied to the study of terpenic compounds in five commercial varieties of medicinal cannabis produced by Bedrocan International: a CBD-rich (Bedrolite®), a THC/CBD balanced (Bediol®), and three THC-dominant (Bedrocan®, Bedica® and Bedrobinol®). Two extraction solvents are described (ethanol and hexane) to compare their selectivity towards target molecules, and to describe as exhaustively as possible the terpenic profile of the five pharmaceutical-grade varieties. Twenty-three standards were used for accurate dosages. This work highlights that the choice of solvent and the analysis method reliability are critical for the study of these terpenic compounds, regarding their contribution to the entourage effect.

Surface-Initiated Reversible Addition-Fragmentation Chain Transfer Polymerization (SI-RAFT) to Produce Molecularly Imprinted Polymers on Graphene Oxide for Electrochemical Sensing of Methylparathion.

A nonenzymatic redox-responsive sensor was put forward for the detection of methylparathion (MP) by designing globular nanostructures of molecularly imprinted polymers on graphene oxide (GO@MIPs) via surface-initiated reversible addition-fragmentation chain transfer polymerization (SI-RAFT). Fourier transform infrared (FTIR) spectroscopy, field emission scanning electron microscopy (FESEM), and small-angle X-ray scattering (SAXS) studies have confirmed the successful formation of receptor layers of MIPs on RAFT agent-functionalized GO sheets. The electrochemical signal with an amplified current response was attained because of the enhanced diffusion rate of ions at the interface provided by widening the pore size of the MIP film. The analytical response of GO@MIPs, validated by recording square-wave anodic stripping voltammetry (SWASV) at varying MP concentrations, followed the linear response between 0.2 and 200 ng/mL. Under optimized conditions, the sensor exhibited a limit of detection of 4.25 ng/mL with high selectivity over other interfering ions or molecules. The anti-interfering ability and good recovery (%) in food samples directed the use of the proposed sensor toward real-time monitoring and also toward future mimicking of surfaces.

Screening Biogenic Volatile Organic Compounds from Common Portuguese Shrubs Using Headspace–Bar Adsorptive Microextraction (HS-BAµE)

In this study, headspace–bar adsorptive microextraction (HS-BAµE) combined with gas chromatography–mass spectrometry (GC-MS) was employed to screen the major biogenic volatile organic compounds (BVOCs) emitted by six different Portuguese shrub species (Erica scoparia L., Cistus ladanifer L., Cistus monspeliensis L., Lavandula stoechas L., Thymus villosus L., and Thymus camphoratus). The HS-BAµE/GC-MS methodology was developed, optimized, and validated using five common monoterpenoids (α-pinene, β-pinene, limonene, 1,8-cineole, and thymol) and one sesquiterpenoid (caryophyllene oxide). Under optimized experimental conditions (microextraction-sorbent phase: activated carbon (CN1), 3 h (35 °C); back-extraction: n-C6 (1 h)), good efficiencies (>45%), low analytical thresholds (5.0–15.0 µg/L) and suitable linear dynamic ranges (20.0–120.0 µg/L, r2 > 0.9872) were achieved, as well as acceptable intra and inter-day precisions (RSD ≤ 30.1%). Benchmarking the proposed methodology, HS-BAµE(CN1), against the reference methodology, HS-SPME(PDMS/DVB), revealed comparable analytical responses and demonstrated excellent reproducibility. Among the six shrub species studied, Thymus camphoratus exhibited the highest emissions of BVOCs from its leaves, notably, 1,8-cineole (4136.9 ± 6.3 µg/g), α-pinene (763.9 ± 0.5 µg/g), and β-pinene (259.3 ± 0.5 µg/g). It was also the only species found to release caryophyllene oxide (411.4 ± 0.3 µg/g). The observed levels suggest that these shrub species could potentially serve as fuel sources in the event of forest fires occurring under extreme conditions. In summary, the proposed methodology proved to be a favorable analytical alternative for screening BVOCs in plants. It not only exhibited remarkable performance but also demonstrated user- and eco-friendliness, cost-effectiveness, and ease of implementation.

On the time-dependent sliding contact behavior of three-phase polymer matrix smart composites

Abstract Three-phase smart composites consisting of magnetostrictive and piezoelectric reinforcements embedded with a polymer matrix can achieve specific multifunctional properties in response to external stimuli, which are well-suited for the application of sensors, actuators, and electronic devices. The materials exhibit complex behaviors characterized by electro-magneto-viscoelasticity coupling during the contact of these smart structures. This paper proposes a novel hybrid element method (HEM) for numerically analyzing the frictionless sliding contact problem stemming from the viscoelastic behavior and multiphase interactions of polymer matrix smart composites. The study aims to fully investigate the effects of material properties, sliding velocities, and action time on the contact behavior of materials via the integration of the conjugate gradient method (CGM) with the discrete convolution-fast Fourier transform (DC-FFT) algorithm. The analytical viscoelastic frequency response functions (FRFs) are derived by substituting elastic solutions with the time-dependent relaxation modulus. Numerical results show that three-phase polymer matrix smart composites exhibit lower contact pressure and higher surface electric/magnetic potential than three-phase magneto-electro-elastic composites. Sliding velocity and action time strongly influence the distribution of pressure/stress and electric/magnetic potential.

Non-stationary response determination of nonlinear systems endowed with fractional derivative elements subjected to evolutionary stochastic excitation

This study proposes a statistical linearization-based approach for the analysis of the stochastic response of nonlinear systems endowed with fractional derivative elements under non-stationary stochastic excitation characterized by non-separable power spectral density. The method involves iteratively solving a time-varying fractional-order equivalent linear equation obtained by statistical linearization. Specifically, an analytical solution for the response power spectrum of the fractional-order linear system is developed within the frequency-domain random vibration context where the analytical time-varying frequency response function (FRF) is formulated as a convolution integral involving a modulated Fourier kernel and the impulse response function (IRF). The analytical solution for the IRF is obtained through eigen-analysis of the associated fractional linear system. To demonstrate the method’s efficacy, we examine fractional time-invariant/time-variant linear systems, along with a nonlinear system exhibiting cubic stiffness (Duffing oscillator) subject to a stochastic excitation with non-separable power spectral density of the Spanos-Solomos and Conte-Peng kinds. Pertinent Monte Carlo simulations demonstrate the accuracy and applicability of the proposed method.

Utilizing nitrogen, sulfur, phosphorus, and chlorine co-doped carbon dots as a fluorescent probe for determination of vancomycin in exhaled breath condensate

Vancomycin is employed to treat infections caused by gram-positive bacteria. Ensuring precise vancomycin dosages is essential to avoid the emergence of bacterial resistance. In the current study, a fluorescent nanoprobe was designed for vancomycin determination in exhaled breath condensate samples. The nanoprobe was based on carbon dots (CDs) doped with nitrogen, sulfur, phosphorus, and chlorine (NSPCl-doped CDs). Vancomycin significantly reduced the fluorescence of NSPCl-doped CDs and presented a quenching process in the analytical response of the probe within a concentration range of 0.01–2.0 μg mL−1 due to forming a non-fluorescent complex. The nanoprobe's intra-day and inter-day relative standard deviations were 1.4 % and 3.2 %, respectively. This nanoprobe was successfully used to determine vancomycin in the patients receiving this drug collected from the expiratory circuit of the mechanical ventilator.

Harmonizing perspectives to understand attitudes: A mixed methods approach to crafting an assessment literacy attitude scale

Assessment literacy's vital role in faculty effectiveness within higher education lacks sufficient tools for measuring faculty attitudes on this matter. Employing a sequential mixed-methods approach, this study utilized the theory of planned behavior to develop the Assessment Literacy Attitude Scale (ALAS) and evaluate its psychometric properties within the U.S. higher education context. The qualitative phase involved a literature review of relevant studies and existing self-report measures, interviews with stakeholders, and panel reviews to shape initial item development. Following the establishment of a conceptual foundation and a comprehensive overview of the scale's construction, our study advanced to the quantitative stage that involves factor analytical and item response theory approaches using data from 260 faculty across three public universities in the U.S. Exploratory factor analysis (EFA) was employed initially to obtain preliminary insights into the scale's factorial structure and dimensionality. Confirmatory factor analysis (CFA) was subsequently applied with separate data and the findings largely supported the conclusions from the EFA. Exploratory and confirmatory factor analyses resulted in 15 items loading across two factors in a good model fit range. Finally, we used nonparametric item response theory (IRT) techniques based on Mokken Scale Analysis (MSA) to evaluate individual items for evidence of effective psychometric properties to support the interpretation of ALAS scores, including monotonicity, scalability, and invariant item ordering. The newly-developed scale shows promise in assessing faculty attitudes toward enhancing their assessment literacy.

Development of Simplified Methods for Levitation Force Distribution in Maglev Vehicles Using Frequency Ratio Tests.

Maglev vehicles apply the entire vehicle load uniformly onto bridges through levitation forces. In assessing the dynamic characteristics of the maglev train-bridge coupling system, it is reasonable to simplify the distributed levitation force as a concentrated force. This article theoretically derives the analytical response of bridge dynamics under the action of a single constant force and conducts numerical simulations for a moving single constant force and a series of equally spaced constant forces passing over simply supported beams and two-span continuous beams, respectively. The topic of discussion is the response of bridge dynamics when different degrees of force concentration are involved. High-precision displacement and acceleration sensors were utilized to conduct tests on the Shanghai maglev line to verify the accuracy of the simulation results. The results indicate that when simplifying the distributed levitation force into a concentrated force model, a frequency ratio can be used to analyze the conditions for resonance between the train and the bridge and to calculate the critical speed of the train; the levitation distribution force of a high-speed maglev vehicle can be simplified into four groups of concentrated forces based on the number of levitation frames to achieve sufficient accuracy, with the dynamic response of the bridge being close to that under distributed loads.

A Double Legendre Polynomial Order N Benchmark Solution for the 1D Monoenergetic Neutron Transport Equation in Plane Geometry

As more and more numerical and analytical solutions to the linear neutron transport equation become available, verification of the numerical results becomes increasingly important. This presentation concerns the development of another benchmark for the linear neutron transport equation in a benchmark series, each employing a different method of solution. In 1D, there are numerous ways of analytically solving the monoenergetic transport equation, such as the Wiener–Hopf method, based on the analyticity of the solution, the method of singular eigenfunctions, inversion of the Laplace and Fourier transform solution, and analytical discrete ordinates in the limit, which is arguably one of the most straightforward, to name a few. Another potential method is the PN (Legendre polynomial order N) method, where one expands the solution in terms of full-range orthogonal Legendre polynomials, and with orthogonality and series truncation, the moments form an open set of first-order ODEs. Because of the half-range boundary conditions for incoming particles, however, full-range Legendre expansions are inaccurate near material discontinuities. For this reason, a double PN (DPN) expansion in half-range Legendre polynomials is more appropriate, where one separately expands incoming and exiting flux distributions to preserve the discontinuity at material interfaces. Here, we propose and demonstrate a new method of solution for the DPN equations for an isotropically scattering medium. In comparison to a well-established fully analytical response matrix/discrete ordinate solution (RM/DOM) benchmark using an entirely different method of solution for a non-absorbing 1 mfp thick slab with both isotropic and beam sources, the DPN algorithm achieves nearly 8- and 7-place precision, respectively.

Truncations and in silico docking to enhance the analytical response of aptamer-based biosensors

Aptamers are short oligonucleotides capable of binding specifically to various targets (i.e., small molecules, proteins, and whole cells) which have been introduced in biosensors such as in the electrochemical aptamer-based (E-AB) sensing platform. E-AB sensors are comprised of a redox-reporter-modified aptamer attached to an electrode that undergoes, upon target addition, a binding-induced change in electron transfer rates. To date, E-AB sensors have faced a limitation in the translatability of aptamers into the sensing platform presumably because sequences obtained from Systematic Evolution of Ligands by Exponential Enrichment (SELEX) are typically long (>80 nucleotides) and that obtaining structural information remains time and resource consuming. In response, we explore the utility of aptamer base truncations and in silico docking to improve their translatability into E-AB sensors. Here, we first apply this to the glucose aptamer, which we characterize in solution using NMR methods to guide design and translate truncated variants in E-AB biosensors. We further investigated the applicability of the truncation and computational approaches to four other aptamer systems (vancomycin, cocaine, methotrexate and theophylline) from which we derived functional E-AB sensors. We foresee that our strategy will increase the success rate of translating aptamers into sensing platforms to afford low-cost measurements of molecules directly in undiluted complex matrices.

The effect of biosecurity heat treatment on soils: implications for soil analytical methods and mineral exploration

Soils are widely used as geochemical sample media. A recent advancement in soil analytical methods for exploration developed in Australia, the UltraFine+ ® method, concentrates the clay-sized fraction of <2 µm and then analyses this fraction for over 50 elemental concentrations, pH, electrical conductivity and spectral mineralogy/properties (i.e., visible –near- to shortwave and mid- infrared reflectance spectroscopy). This new approach was initially limited to Australian soils due to strict biosecurity legislation. However, since 2022 samples can be shipped to Australia and heat-treated to 160 °C to be released from quarantine-approved premises prior to analysis. A study was undertaken to determine the influence of the temperature heat treatment on the spectral and geochemical properties of soils. One hundred and three soils were collected from multiple regions of Australia to provide a background set of samples to test the effect of heat treatment on the analytical response using the clay-sized fraction analytical method. These soils comprised multiple clay types and are representative of general soil types and target commodities in mineral exploration settings. Results show that heat treatment did not significantly impact elemental abundance of common pathfinder and target elements in minerals exploration with strong correlation and linear trends between the treatments. Spectral parameters measured in the visible to mid infrared range were also unaffected by heating. Some observed elemental changes were related to inconsistent extraction of resistate elements (Hf, Nb, Zr). Counter to other studies, a pH decrease was observed in heat-treated samples. The study concludes that biosecurity release heat treatment at 160 °C does not hinder analysis of the ultrafine fraction soils with a concentrated aqua regia assay and spectral mineralogy measurements.

Disposable Carbon Electrochemical Sensor Modified with Gold Nanoparticles for Creatinine Detection

The social and economic impact of Chronic Kidney Disease on global health systems is devastating. It is estimated that annual spending on the treatment of Chronic Kidney Patients is in the order of 2 to 3% of annual health budgets. (1) In 2015, considering the United States, medical expenses for individuals with chronic kidney diseases were more than 64 billion dollars (1). Indeed, the early diagnosis of chronic kidney diseases is very important for the implementation of preventive measures that delay or even interrupt the progression to more advanced stages of the disease. In this context, this work aims to develop a disposable electrochemical sensor aimed at detecting creatinine for diagnosing kidney diseases. The flexible disposable lab made carbon sensor has been modified with gold nanoparticles. Morphological and electrochemical characterizations were carried out to better understand the proposed device. From cyclic voltammetry measurements, the proposed sensor showed reduction and oxidation peaks related to gold oxides formed on its surface. When adding creatinine there is a decrease in the electrochemical signal due to the adsorption of the target analyte. Therefore, it was inferred that it was possible to detect creatinine present in the solution from the reduction in the analytical response of the gold-modified electrode. Using the square wave voltammetry technique, in accordance with what was previously presented, when CNN was added to the solution, the Au-CNN interaction caused a reduction in the analytical response, therefore, with the increase in CNN concentration, this reduction increased linearly in the range of 0.5 to 10 µmol L-1 with a limit of detection and quantification, 0.15 and 0.45 µmol L-1, respectively, were calculated. Furthermore, it presented a sensitivity of 0.97 µA mol-1 L with a linear equation of Ipeak (µA) = 0.97 x C(CNN) + 0.23. Furthermore, the proposed sensor was successfully applied to determine creatinine in human serum samples and the recovery results were close to 100%. Therefore, the device modified with gold nanoparticles is an interesting alternative for creatinine detection.References(1) Luyckx V. A. et al. The global burden of kidney disease and the sustainable development goals, Bulletin of the World Health Organization Published online: 20 April 2018.

Convolution of Analyte-Electrode Interactions over Distinct Time-Scales Leading to Taste Discrimination in Single Response Electroplated Metal Microwires-Based Microfluidic Electronic Tongue

A microfluidic electronic tongue (MET) is demonstrated via analyzing a single equivalent admittance spectrum derived from stainless-steel microwires electroplated with copper, nickel, iron, and zinc, all interconnected in parallel. These microwires were integrated into a microfluidic chip composed of polydimethylsiloxane (PDMS). A single admittance response for taste analytes, passing through micro-channels, was measured by short-circuiting the ends of multi-wire MET chip. The resulting admittance response from the MET was processed via principal component analysis (PCA) for visualization of clustering according to the taste groups. The performance of MET was assessed in terms of cluster analysis and Silhouette coefficient (SC).This analytical method effectively clusters four primary taste samples based on their distinct flavor profiles, showcasing notable differentiation with a Silhouette coefficient surpassing 0.71. The elucidation provided by the biplot reveals that electronic and ionic interaction at analyte-electrode interactions over distinct time scales contribute synergistically towards discrimination of taste in dimensionally reduced 2-D PCA space. Real admittance responses at lower and higher frequency range contribute majorly in the composition of first and second principal components respectively. The equivalent electric circuit (EEC) was fitted to the developed MET to gain better understanding of response mechanism. A capacitor (C) in parallel to a series combination of resistor (R) and inductor (L), is (C[RL]) kind of EEC fitted to the admittance spectra. Interestingly, when relying on fitted equivalent electric circuit data, the taste discriminability of the MET is notably diminished as not all EEC elements are able to capture signature response specific to each taste. This observation critically evaluates the strategy of suitable data selection towards accurate and efficient taste discrimination as the admittance response over complete frequency range are pivotal contributors to the MET's impressive taste discrimination capabilities.A pivotal aspect of the MET's functionality lies in deploying a single admittance response, a convolution of the responses of multiwire configurations integrated into the MET. This approach ensures global selectivity by utilizing copper, nickel, iron, and zinc electrodeposited stainless-steel microwires. These functionalization-free sensing units exhibit the ability to discriminate sweet, sour, bitter, and salty taste groups with remarkable clarity, boasting a Silhouette coefficient value of 0.77.The MET's adaptability is further underscored by its electroplating modification, which is both expandable and enables clean room-free fabrication methods. This capability paves the way for the widespread manufacturing of MET chips featuring readily interchangeable and reusable calibration-free electrodes.Looking ahead, the MET holds promise for future applications in quality control, particularly in the assessment of real food and beverage samples such as milk and soft drinks. The efficiency demonstrated in discriminating between tastes suggests that the MET could offer a cost-efficient and simplified solution for taste and quality assessments across diverse commercial applications. This potential extends to scenarios where clean room facilities are not readily available.In summary, the MET's unique approach, utilizing a single equivalent admittance spectrum from electroplated metal wires in a microfluidic context, showcases robust taste discrimination capabilities. Integrating PDMS microfluidic chips and employing principal component analysis add layers of sophistication to the methodology. The MET's global selectivity, functionalization-free sensing units, and adaptability in manufacturing advocate its potential for revolutionizing taste and quality assessment in various industries, providing a glimpse into a future where simplicity and cost-efficiency are paramount considerations in analytical methodologies.

Diving into research without wading through content: A skills-based cell biology course emphasizing the unknown.

In a typical undergraduate biology curriculum, students do not dive into research until they first wade through large amounts of content. Biology courses in the first few years of the college curriculum tend to be lecture-based and exam-based courses. As a result, science students are mainly exposed to content knowledge-not the skills scientists practice daily. While students may practice manual techniques in lab sections of lecture courses, the higher-level analytical research skills are reserved for the final semesters of college. To address this issue, we created an undergraduate cell biology course centered around practicing research skills, and fully accessible to students with no prerequisite content knowledge. In our course, students read primary literature (no textbooks) and were assessed by writing 12 analytical response papers and a full research proposal (no exams). Each student chose a topic for their semester-long project, conducted a literature review, and proposed future experiments-all in a stepwise fashion with plentiful feedback. The students' thorough comprehension of the primary literature, along with successful completion of the research proposals, shows that the course achieved its goals of building these skills-even in the nonbiology majors taking this pilot course. Pre- and post-survey results demonstrate that students gained feelings of confidence and preparedness for future research experiences. We envision a future model in which such a skills-based course replaces a more traditional cell biology course, giving students the opportunity to practice high-level analytical research skills from very early on in the undergraduate biology curriculum.