Minimal Interference Research Articles

Electrical signal interference minimization using appropriate core material for 3D integrate circuit at high frequency applications

As demand for smaller, quicker, and more powerful devices rises, Moore's law is strictly followed. The industry has worked hard to make little devices that boost productivity. The goal is to optimize device density. Scientists are reducing connection delays to improve circuit performance. This helped them understand three-dimensional integrated circuit (3D IC) concepts, which stack active devices and create vertical connections to diminish latency and lower interconnects. Electrical involvement is a big worry with 3D integrates circuits. Researchers have developed and tested through silicon via (TSV) and substrates to decrease electrical wave involvement. This study illustrates a novel noise coupling reduction method using several electrical involvement models. A 22% drop in electrical involvement from wave-carrying to victim TSVs introduces this new paradigm and improves system performance even at higher THz frequencies.

Polarization-frequency multiplexing holograms employing Bi-layered patterned coding metasurfaces

A surge in interest surrounding metasurfaces has been witnessed in recent years, driven by their capability to autonomously manipulate electromagnetic wavefront (EM) in three-dimensional space. While the initial focus in metasurface research has often been on manipulating electromagnetic waves using single polarization and frequency schemes, significant advancements have been made to overcome these limitations. Recent developments have introduced multifunctional metasurfaces that enable simultaneous control over multiple frequencies and polarizations, substantially enhancing their capacity for information processing and communication. Building on these advancements, our work introduces a novel three-channel full-space metasurface that leverages double-face copper-cladded patterns on a single-layer substrate, significantly increasing channel capacity through both frequency and polarization multiplexing. In order to achieve efficient control of the EM wavefront in multi-frequency and polarization scenarios, a super unit cell-based approach is utilized, wherein high-performance meta-atoms are combined to form super unit cells with minimal interferences. Specifically, different functionalities can be achieved in full space under different wave polarizations and frequencies. To validate the concept, a metasurface sample is fabricated and experimentally tested. The experimental results agree with both theoretical predictions and simulations, confirming the effectiveness of a three-channel metasurface holography. The metasurface achieves independent control of the incident EM wave's polarization and frequency, thus enhancing information storage capacity and encryption security.

Evaluation of a novel palm-free fat supplement to reduce the carbon footprint of diets for dairy cows

Most fat supplements added to dairy diets are derived from palm acid oil or palm fatty acid distillate. There are environmental concerns about palm oil production due to deforestation and high greenhouse gas (GHG) emissions. The objective of this study was to evaluate a palm-free fat supplement, Envirolac. Envirolac contains vegetable oils, marine oils and glycerine encapsulated within a cellulosic fibre-clay mineral carrier matrix. The carrier matrix has small particle size to facilitate rapid rumen passage and minimal interference with rumen digestion. Fifty cows were divided into two balanced groups of 25 cows. Each group received Control (calcium soap of palm fatty acid distilate, 0.5 kg/d) and Envirolac (0.5 kg/d) diets in a crossover design with two feeding periods of four weeks duration, so that each cow received both diets. Envirolac has a lower total fat concentration than the calcium soap, so the feeding rate delivered less total fat. When fed on Envirolac, cows yielded more milk 40.7 v 40.1 kg/d), energy-corrected milk (ECM; 42.9 v 41.3 kg/d) and milk components (1605 v 1514 g fat, 1239 v 1199 g protein, 1871 v 1839 g lactose, per day), and produced milk with higher concentrations of fat (40.1 v 38.6 g/kg) and protein (30.7 v 30.1 g/kg), than when fed on Control. When fed on Envirolac, cows produced milk with higher concentrations of fatty acids (FA) synthesised de novo in the mammary gland (25.5 v 23.6 g/100 g total FA), lower concentration of palmitic acid (35.5 v 37.2 g/100 g total FA), and higher concentrations of some long-chain fatty acids (C20:0, C20:1, C20:3n3, C21:0, C22:0, C22:6n3 and C23:0), than when fed on Control. There was no effect of treatment on dry matter intake (DMI; mean 23.4 kg/d), so feed efficiency was higher (1.83 v 1.76 kg ECM/kg DMI) for Envirolac than Control. There was no effect of treatment on dry matter digestibility (0.73), methane production (433 g/d), methane yield (19.3 g/kg DMI) or methane intensity (10.9 g/kg ECM). Feed carbon footprint of Envirolac was calculated to be 1028 g CO2eq/kg DM, which is 0.46 of the value for a calcium soap (2830 g CO2eq/kg DM), and reduced feed carbon footprint per kg ECM milk production by 11 %. This study demonstrates that Envirolac can replace palm-based fat supplements in dairy diets to improve feed efficiency and reduce the carbon footprint of milk production.

Alared: Solvatochromic and Fluorogenic Red Amino Acid for Ratiometric Live-Cell Imaging of Bioactive Peptides.

To fill the need for environmentally sensitive fluorescent unnatural amino acids able to operate in the red region of the spectrum, we have designed and synthesized Alared, a red solvatochromic and fluorogenic amino acid derived from the Nile Red chromophore. The new unnatural amino acid can be easily integrated into bioactive peptides using classical solid-phase peptide synthesis. The fluorescence quantum yield and the emission maximum of Alared-labeled peptides vary in a broad range depending on the peptide's environment, making Alared a powerful reporter of biomolecular interactions. Due to its red-shifted absorption and emission spectra, Alared-labeled peptides could be followed in living cells with minimal interference from cellular autofluorescence. Using ratiometric fluorescence microscopy, we were able to track the fate of the Alared-labeled peptide agonists of the apelin G protein-coupled receptor upon receptor activation and internalization. Due to its color-shifting environmentally sensitive emission, Alared allowed for distinguishing the fractions of peptides that are specifically bound to the receptor or unspecifically bound to different cellular membranes.

Structural Optimization of Trusses in Building Information Modeling (BIM) Projects Using Visual Programming, Evolutionary Algorithms, and Life Cycle Assessment (LCA) Tools

The optimal structural design is imperative in order to minimize material consumption and reduce the environmental impacts of construction. Given the complexity in the formulation of structural design problems, the process of optimization is commonly performed using artificial intelligence (AI) global optimization, such as the genetic algorithm (GA). However, the integration of AI-based optimization, together with visual programming (VP), in building information modeling (BIM) projects warrants further investigation. This study proposes a workflow by combining structure analysis, VP, BIM, and GA to optimize trusses. The methodology encompasses several steps, including the following: (i) generation of parametric trusses in Dynamo VP; (ii) performing finite element modeling (FEM) using Robot Structural Analysis (RSA); (iii) retrieving and evaluating the FEM results interchangeably between Dynamo and RSA; (iv) finding the best solution using GA; and (v) importing the optimized model into Revit, enabling the user to perform simulations and engineering analysis, such as life cycle assessment (LCA) and quantity surveying. This methodology provides a new interoperable framework with minimal interference with existing supply-chain processes, and it will be flexible to technology literacy and allow architectural, engineering and construction (AEC) professionals to employ VP, global optimization, and FEM in BIM-based projects by leveraging open-sourced software and tools, together with commonly used design software. The feasibility of the proposed workflow was tested on benchmark problems and compared with the open literature. The outcomes of this study offer insight into the opportunities and limitations of combining VP, GA, FEA, and BIM for structural optimization applications, particularly to enhance structural efficiency and sustainability in construction. Despite the success of this study in developing a workable, user-friendly, and interoperable framework for the utilization of VP, GA, FEM, and BIM for structural optimization, the results obtained could be improved by (i) increasing the callback function speed between Dynamo and RSA through specialized application programming interface (API); and (ii) fine-tuning the GA parameters or utilizing other advanced global optimization and supervised learning techniques for the optimization.

Toward an Improved Electrocatalytic Determination of Immunomodulator COVID Medication Baricitinib Using Multiwalled Carbon Nanotube Nickel Hybrid.

The study presents a first electrochemical method for the determination of the immunomodulator drug Baricitinib (BARI), crucial in managing COVID-19 patients requiring oxygen support. A unique electrode was developed by modifying graphite carbon nickel nanoparticles (NiNPs) with functionalized multiwalled carbon nanotubes (f.MWCNTs), resulting in nanohybrids tailored for highly sensitive BARI detection. Comparative analysis revealed the superior electrocatalytic performance of the nanohybrid-modified electrode over unmodified counterparts and other modifications, attributed to synergistic interactions between f.MWCNTs and nickel nanoparticles. Under optimized conditions, the sensors exhibited linear detection within a concentration range from 4.00 × 10-8 to 5.56 × 10-5 M, with a remarkably low detection limit of 9.65 × 10-9 M. Notably, the modified electrode displayed minimal interference from common substances and demonstrated high precision in detecting BARI in plasma and medicinal formulations, underscoring its clinical relevance and potential impact on COVID-19 treatment strategies.

Hydraulic-based optimization algorithm for the design of stormwater drainage networks

Stormwater drainage networks are designed to reduce the risk of rainwater damage to the served area. The purpose of optimizing a stormwater drainage system is to reduce overall construction costs and to meet hydraulic design requirements. Currently, designs that rely on software or manual calculations are limited by the available time and the designer’s capabilities. In fact, manual optimization for large networks consumes a lot of time and effort, and there is no guarantee that the optimal design is reached, also it is subject to human errors. In recent years, several researchers have focused on creating optimization design algorithms specifically for sewer and storm networks, such as genetic algorithm (GA), linear programming (LP), heuristic programming (HP),…etc. However, these studies were limited to covering one or two design parameters and constraints. Additionally, in some studies, the hydraulic performance of the designed network was not treated in a proper way, especially the water surface profile effects. So, the main objective of the study is to develop an effective hydraulic-based optimization algorithm (HBOA) that can dynamically get the optimal design with minimum total cost for a given storm network layout and meet all hydraulic requirements. To achieve this, a MATLAB code is created and coupled with SewerGEMS software that automatically simulates all expected optimization scenarios based on network hydraulic performance. The HBOA is validated economically and hydraulically using two benchmark examples from the literature. According to the economic validation, the total network cost generated by HBOA was the lowest when compared to the optimization methods found in the literature. During the hydraulic evaluation, it was observed that the optimization algorithm (GA-HP) used in the literature for the benchmark examples does not meet the hydraulic requirements where the networks are flooded, whereas HBOA meets the hydraulic requirements with minimal overall network cost. Also, the HBOA is applied to four real stormwater drainage networks that were already designed, constructed, and optimized manually. The four redesigned real cases using HBOA revealed a cost reduction of about 15% compared to the original designs, while consuming a few hours for the design and optimization processes. Finally, the developed HBOA is a robust, time-efficient, and cost-effective optimization and hydraulic design tool which could be used in the design of stormwater drainage networks with different design constraints with minimal human interference.

Exploring the Influence of Seismic Source and Improvement Methods on Tunnel Seismic Prediction

Abstract Tunnel seismic advanced prediction method is essential for detecting abnormal bodies ahead of the tunnel face and minimizing risks during tunnel construction. Selecting the seismic source plays a crucial role in influencing the precision and effectiveness of data acquisition. At present, tunnel seismic data is usually collected using explosive and sledgehammer sources. Nevertheless, the various sources are located in different positions within the tunnel excavation zone, resulting in distinct characteristics observed on the surface and reflected waves in the acquired tunnel seismic data. The explosive source has minimal surface wave interference, but it is expensive. However, the sledgehammer source is economical yet plagued by inadequate energy and substantial surface wave disruption. Regrettably, there is a lack of research on seismic sources in tunnels, which impairs the precise interpretation of forecasting conclusions from these sources. This paper seeks to investigate how various sources impact tunnel seismic prediction and suggests a new method that integrates data acquisition and processing from these sources. The explosive source is used once, while the sledgehammer source is used 24 times. Cross-correlation calculations are conducted to enhance the resolution of sledgehammer source data, reducing surface wave interference, based on seismic data obtained from the explosive source. Extensive numerical simulations and tunnel experiments support the validity of this method, highlighting its potential to lower data acquisition expenses and enhance tunnel seismic prediction accuracy.

Boosting the adsorption capacity and anti-impurity performance of zeolitic imidazolate frameworks for antimony(III) in water through the synthesis of leaf-shaped structures

In recent years, the search for effective antimony adsorption materials has been unyielding. However, the exploration of zeolite imidazolate frameworks (ZIFs) as potential adsorbents, along with the influence of material surface structure and water chemistry on their performance remain under explored. In this study, various molar ratios of Zn2+ and 2-methylimidazole are employed to synthesize three distinct shapes of ZIFs: cube, leaf, and dodecahedron. The experimental outcomes reveal that Leaf-ZIFs, exhibit exceptional adsorption capabilities for Sb(III), the maximum adsorption capacity of Leaf-ZIFs was 57.3 mg g−1. The adsorption kinetics adhere to the pseudo-second-order model, and equilibrium is achieved in approximately 10 h. Additionally, the adsorption isotherm curve is consistent with the Freundlich model. Through comprehensive batch experiments, we thoroughly examined the impact of varying solution pH levels, coexisting ions, and the coexistence of humic acids on the adsorption of Sb(III). The Leaf-ZIFs exhibited remarkable adaptability in neutral, alkaline, and low-concentration heteroionic environments, while demonstrating minimal interference from humic acid present in the solution. Analysis using SEM, XPS, and FTIR techniques revealed that the adsorption mechanism of Leaf-ZIFs primarily involved the partial breakage of the Zn-N bond within the material's structure. This breakage led to the formation of Zn-OH groups, which subsequently reacted with Sb(III) molecules through the -OH groups. The culmination of this process was the formation of Zn-O-Sb bonds, resulting in the effective adsorption of Sb(III) from aqueous solutions.

Illuminating Urban Near-Surface with Distributed Acoustic Sensing Multimodal Noise Surface-Wave Imaging

Abstract Urban subsurface exploration requires high spatial and temporal resolution, cost-effective operation, and minimal interference with urban activities. Distributed acoustic sensing (DAS)—an innovative seismic observation tool—emerges as a promising solution for urban surveys. In this study, we repurposed a 7.9 km telecommunication cable traversing Hefei into a seismic observation array with 3850 channels spaced at 2 m intervals. Noise cross-correlation functions (NCFs) were constructed from recordings by iDAS2 and ZD-DAS interrogators along the entire cable. Spatial variation in the NCFs was observed and attributed to different traffic conditions. Employing the recently developed modified frequency–Bessel transform method to NCFs from the 2 km southern subsection of the optic cable, we extracted broadband, high-resolution multimodal dispersion curves. The inverted near-surface structure beneath the cable unveiled a sediment thinning trend from the center to the periphery of the Hefei basin, consistent with borehole inspections. The three-station interferometry (C3) method and beamforming with the Bessel kernel function are applied to mitigate challenges arising from the weak coupling between the cable and the Earth, as well as persistent localized noise sources. These techniques facilitated the acquisition of broadband surface waves. Distinct secondary scatters are observed in NCFs near channels 2090 and 2287, accompanied by a substantial velocity contrast of 30%–40%, suggesting the existence of a blind fault. The study reaffirms the significant potential of DAS arrays for high-resolution imaging of subsurface structures in challenging urban environments, emphasizing the importance of advanced processing techniques to enhance imaging accuracy and robustness.

Latent fingerprint visualization with the novel white fluorescent fingerprint powders

Based on carbazole derivatives, a new fluorescent dye G-D was constructed. White fluorescent fingerprint powder was constructed by proportionally blending montmorillonite with G-D and the previously synthesized dyes (B-D and R-D). White fluorescent fingerprint powder is obvious in the dark and can be subjected to minimal fluorescent background interference. The white fluorescent fingerprint powder was successfully used to develop latent fingerprints left on various surfaces, including glass, tin foil, marble, acrylic plate with bright fluorescence, painted wood and coins. Impressively, the white fluorescent fingerprint powder also has excellent applications in developing aged fingerprints and replication. For complex criminal investigation activities, the white fingerprint powder with high resolution, wide applicability and real-time development is a competitive visualization means.

Interference is in the eye of the beholder: Application to the coherent control of collisional processes.

Interference is widely regarded as a foundational attribute of quantum mechanics. However, for a given experimental arrangement, interference can either contribute or not contribute to the outcome depending upon the basis in which it is measured. This observation is both foundational and particularly relevant to coherent control of molecular processes, an approach based upon quantum interference. Here, we address this issue and its relevance to controlling molecular processes via the "coherent control scattering (CCS) matrix," a formalism that allows for an analysis of modifications in an interference structure resulting from a change of basis. This analysis reveals that the change in the interference structure can be attributed to the non-commutativity of the transformation matrix with the CCS matrix and the non-orthogonality of the transformation. Additionally, minimal interference is shown to be associated with the CCS eigenbasis and that the Fourier transform of the eigenvectors of the CCS matrix provides the maximal interference and hence the best coherent control. The change of controllability through a change of basis is illustrated with an example of 85Rb+ 85Rb scattering. In addition, the developed formalism is applied to explain recent experimental results on He + D2 inelastic scattering demonstrating the presence or absence of interference depending on the basis.

Antigenic Peptide-Thioredoxin Fusion Chimeras for In Vitro Stimulus of CD4+ TCR+ Jurkat T Cells.

Study of CD4+ T cell response and T cell receptor (TCR) specificity is crucial for understanding etiology of immune-mediated diseases and developing targeted therapies. However, solubility, accessibility, and stability of synthetic antigenic peptides used in T cell assays may be a critical point in such studies. Here we present a T cell activation reporter system using recombinant proteins containing antigenic epitopes fused with bacterial thioredoxin (trx-peptides) and obtained by bacterial expression. We report that co-incubation of CD4+ HA1.7 TCR+ reporter Jurkat 76 TRP cells with CD80+ HLA-DRB1*01:01+ HeLa cells or CD4+ Ob.1A12 TCR+ Jurkat 76 TRP with CD80+ HLA-DRB1*15:01+ HeLa cells resulted in activation of reporter Jurkat 76 TPR after addition of recombinant trx-peptide fusion proteins, containing TCR-specific epitopes. Trx-peptides were comparable with corresponding synthetic peptides in their capacity to activate Jurkat 76 TPR. These data demonstrate that thioredoxin as a carrier protein (trx) for antigenic peptides exhibits minimal interference with recognition of MHC-specific peptides by TCRs and consequent T cell activation. Our findings highlight potential feasibility of trx-peptides as a reagent for assessing the immunogenicity of antigenic fragments.

Quantification and cultivation of Helicobacter pylori (H. pylori) from various urban water environments: A comprehensive analysis of precondition methods and sample characteristics

Substantial evidence suggests that all types of water, such as drinking water, wastewater, surface water, and groundwater, can be potential sources of Helicobacter pylori (H. pylori) infection. Thus, it is critical to thoroughly investigate all possible preconditioning methods to enhance the recovery of H. pylori, improve the reproducibility of subsequent detection, and optimize the suitability for various water types and different detection purposes. In this study, we proposed and evaluated five distinct preconditioning methods for treating water samples collected from multiple urban water environments, aiming to maximize the quantitative qPCR readouts and achieve effective selective cultivation. According to the experimental results, when using the qPCR technique to examine WWTP influent, effluent, septic tank, and wetland water samples, the significance of having a preliminary cleaning step becomes more evident as it can profoundly influence qPCR detection results. In contrast, the simple, straightforward membrane filtration method could perform best when isolating and culturing H. pylori from all water samples. Upon examining the cultivation and qPCR results obtained from groundwater samples, the presence of infectious H. pylori (potentially other pathogens) in aquifers must represent a pressing environmental emergency demanding immediate attention. Furthermore, we believe groundwater can be used as a medium to reflect the H. pylori prevalence in a highly populated community due to its straightforward analytical matrix, consistent detection performance, and minimal interferences from human activities, temperature, precipitation, and other environmental fluctuations.

Mxene-derived Na2O7Ti3 nanoribbon as a promising electrode material for the detection of ethyl paraoxon in complex matrices

This study reports the development of MXene (Ti3C2Tx) derived sodium titanate nanoribbon-based electrochemical sensor for pesticide detection. Titanium Carbide (Ti3C2) MXene-derived sodium titanate nanoribbon (MNR) was obtained by facile hydrothermal synthesis and characterized by powder X-ray Diffraction (XRD), field emission scanning electron microscopy (FE-SEM), energy-dispersive X-ray analysis(EDS) and, high-resolution transmission electron microscopy (HR-TEM). The synthesized water-dispersed MNR was stabilized with Nafion and deposited on the surface of glassy carbon electrodes (GCE), which provide a symmetrical uniform electrode surface. Further, the electrodes were electrochemically characterized with cyclic voltammetry (CV), differential pulse voltammetry (DPV), linear sweep voltammetry(LSV), and electrochemical impedance spectroscopy (EIS). The electrochemical sensing of ethyl paraoxon was carried out in 0.1 M phosphate buffer (PB) by CV, LSV, and DPV. The developed electrochemical sensor exhibited a limit of detection (LOD) of 0.22 nM, a very wide detection range from 0.69 nM to 174.03 nM, and a reliable sensitivity of 0.707 µA/nM/cm2. Moreover, the developed sensor was also employed for the detection of ethyl paraoxon in real samples (vegetable extract spiked with the pesticide). The results suggest that the developed MNR-based sensor would be a potential approach for efficient and accurate detection of ethyl paraoxon in ambient samples, with minimal interference.

Data encryption with chaotic light in the long wavelength infrared atmospheric window

In environments where traditional fiber optic cables are impractical, free-space optical communications offer a promising solution for transmitting large amounts of data, especially in the mid-infrared wavelength range. Despite the advantages of minimal atmospheric interference and stable signals, the vulnerability of wireless optical communications to eavesdropping poses a significant challenge. This study addresses this challenge by demonstrating a method for privately transmitting optical data using photonic chaos from distributed feedback quantum cascade lasers operating at 9.3 µm. Signal processing techniques are applied to enhance the quality of the transmission over distances exceeding 30 m, accompanied by a comprehensive analysis of the photonic chaos complexity to ensure data confidentiality. These findings mark a significant advancement in developing private communications systems within the thermal atmospheric window, with a substantially reduced risk of interception by adversaries. The research not only contributes to secure communications but also has potential implications for enhancing security of data transmission in challenging environments, impacting various industries and applications.

Chromene-derived red-fluorescent probes for sulfite detection in food and living cells based on an integrated ICT&PET platform

Sulfite, widely used in food and pharmaceutical industries, poses significant health and safety concerns, necessitating efficient detection methods. This study introduces three novel red fluorescent probes (MCC-BT, MCC-TI, and MCC-DM), synthesized by integrating chromene derivatives with various electron-withdrawing groups. These probes effectively detect sulfite in both food samples and living cells, leveraging a mechanism transition from intramolecular charge transfer (ICT) to photo-induced electron transfer (PET). They demonstrate low detection limits (2.0 μM, 0.42 μM, and 0.34 μM, respectively) and offer advantages including large Stokes shifts, minimal interference, and colorimetric capabilities. We also developed smartphone-compatible test paper strips for convenient sulfite detection in real-world samples. The probes' effectiveness is further evidenced through sulfite quantification in Traditional Chinese Medicine ingredients. Additionally, their robust fluorescent imaging potential for cellular sulfite sensing highlights their significant contribution to analytical chemistry and biomedical research.

Noise suppression of airborne transient electromagnetic data with minimum curvature

The airborne transient electromagnetic (ATEM) method is a geophysical exploration technique that offers several advantages, including rapid exploration, minimal interference from complex terrains, dense data sampling, and environmental friendliness. However, the full-frequency time-domain secondary field signal acquisition of the ATEM data is susceptible to various electromagnetic interferences, resulting in noise in the collected data. This noise complicates subsequent processing and interpretation. To address this issue, we have developed a 1D minimum-curvature difference equation with unequal spacing based on minimum-curvature differential equations. Through research, we develop an ATEM noise-suppression method based on multiple single-step and multiple superposition-step implicit iterative formats. In addition, we have investigated the convergence of explicit and implicit iterative schemes via Fourier spectrum analysis and proven that the implicit iterative schemes converge. This method effectively suppresses noise in synthetic and real ATEM data during processing. Our results show that the minimum-curvature method is particularly effective in suppressing sferic and Gaussian noises in ATEM data. As a result, our method provides high-quality and reliable ATEM data for further data processing and interpretation. Moreover, the minimum-curvature method is also capable of suppressing noise in ground and ground-space transient electromagnetic data, as well as magnetotelluric data noise. Therefore, this method exhibits a wide range of potential applications.

High visual salience of alert signals can lead to a counterintuitive increase of reaction times

It is often assumed that rendering an alert signal more salient yields faster responses to this alert. Yet, there might be a trade-off between attracting attention and distracting from task execution. Here we tested this in four behavioral experiments with eye-tracking using an abstract alert-signal paradigm. Participants performed a visual discrimination task (primary task) while occasional alert signals occurred in the visual periphery accompanied by a congruently lateralized tone. Participants had to respond to the alert before proceeding with the primary task. When visual salience (contrast) or auditory salience (tone intensity) of the alert were increased, participants directed their gaze to the alert more quickly. This confirms that more salient alerts attract attention more efficiently. Increasing auditory salience yielded quicker responses for the alert and primary tasks, apparently confirming faster responses altogether. However, increasing visual salience did not yield similar benefits: instead, it increased the time between fixating the alert and responding, as high-salience alerts interfered with alert-task execution. Such task interference by high-salience alert-signals counteracts their more efficient attentional guidance. The design of alert signals must be adapted to a “sweet spot” that optimizes this stimulus-dependent trade-off between maximally rapid attentional orienting and minimal task interference.

A micro-extraction/derivatization method for RP-HPLC-FLD analysis of amino acids in wild boar meat

Methods that are easy to use, spend small amounts of reagents, and have minimal human interference are precious tools in different areas. Sus scrofa is the wild animal most used in human diet, however, the knowledge about its protein fraction is still scarce. In this work, a method for 22 amino acids quantification was optimized and applied to the analysis of meat from animals of different ages and genders. The optimization of acid and basic hydrolyses reveal an ideal mass between 75 and 100 mg, with 3 mL of hydrolysis reagent, and 22 h for a maximum extraction of tryptophan. The hydrolysates were automatically derivatized using few µL, and the compounds were analyzed by reversed phase - high performance liquid chromatography with fluorescence detection. For comparison purposes, total protein was assessed, using the Kjeldahl method. The method showed high precision and accuracy, as well as very low limits of detection and quantification, with good potential to be applied to other animal meats. Significant differences were found between the amino acid profile of different animals (e.g. aspartic acid and taurine contents were slightly higher in juveniles than in adults).