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UAV selection for high-speed train communication using OTFS modulation

Descriptive study on oral health and pathologies in vulnerable migrant adolescents from North and West Africa

A fault tolerant CSA in QCA technology for IoT devices

Exploring condition in which people accept AI over human judgements on justified defection

Longitudinal MRI evaluation of the efficacy of non-enhanced lung cancer brain metastases

Effect of plasma free fatty acids on lung function in male COPD patients

Comparative transcriptome and metabolome analysis reveals the differential response to salinity stress of two genotypes brewing sorghum

Acid-decorated chitosan-magnetic aluminum ferrite as a bionanocomposite catalyst for green synthesis of biologically active [4,3‑d]pyrido[1,2‑a]pyrimidin-6‑ones

Impact of pollution on microbiological dynamics in the pistil stigmas of Orobanche lutea flowers (Orobanchaceae)

Tinea manuum: a 5 year retrospective study of demographic data, clinical characteristics, and treatment outcomes

Temporal-spatial evolution and formation mechanism of energy consumption carbon footprint at county scale in the Yellow River Basin

Evaluating AI performance in nephrology triage and subspecialty referrals

Next generation sequencing of multiple SARS-CoV-2 infections in the Omicron Era

Urban pandemic governance personal protective equipment allocation strategies: a system dynamics simulation

Effect of magnetization on antibacterial, lipid-lowering and antioxidant activities of isoquinoline alkaloids

Adsorption of Acid Yellow 36 and direct blue 86 dyes to Delonix regia biochar-sulphur

Abstract This study aims to investigate a new approach to removing hazardous dyes like Direct Blue 86 (DB86) and Acid Yellow 36 (AY36) from aqueous environments. Delonix regia biochar-sulphur (DRB-S), made from Delonix regia seed pods (DPSPs), is an inexpensive and environmentally friendly adsorbent. Different characterization investigations using BJH, BET, FTIR, SEM, DSC, TGA, and EDX were utilized in the descriptions of the DRB-S biosorbent. The optimal pH for AY36 dye and DB86 dye adsorption to the DRB-S adsorvbent was at pH 1.5. For the adsorption of AY36 and DB86 to DRB-S, equilibrium was attained at 30 and 90 min of reaction time interaction. The Langmuir model (LGM) and pseudo-second-order-model (PSOM) best describe the biosorption of both dye molecules to the biosorbent owing to the equal and homogeneous spread of the dye molecules over the biosorbent porous surface and a chemisorption process which involved the valency force through the exchange of electrons between the dye molecules and the prepared biosorbent. The determined biosorption capacities for both dyes (AY36 and DB86) were found to be 270.27 mg/g and 36.23 mg/g, respectively. In conclusion, this recently synthesised DRB-S adsorbent exhibited an impressive sorption capacity and successfully removed AY36 and DB86 dyes. This suggests that the biosorbent has potential applications in wastewater treatment and can be recycled without affecting its adsorption effectiveness.

Daily briefing: How a boy from the Bronx unearthed the workings of the Universe

A novel structure luminous flexible fiber was prepared via aerosol jet printing

Exogenous selenium enhances cadmium stress tolerance by improving physiological characteristics of Artemisia argyi seedlings

Optimal frequency bands for pupillography for maximal correlation with HRV

Abstract Assessing cognitive load using pupillography frequency features presents a persistent challenge due to the lack of consensus on optimal frequency limits. This study aims to address this challenge by exploring pupillography frequency bands and seeking clarity in defining the most effective ranges for cognitive load assessment. From a controlled experiment involving 21 programmers performing software bug inspection, our study pinpoints the optimal low-frequency (0.06-0.29 Hz) and high-frequency (0.29-0.49 Hz) bands. Correlation analysis yielded a geometric mean of 0.238 compared to Heart Rate Variability features, with individual correlations for low-frequency, high-frequency, and their ratio at 0.279, 0.168, and 0.286, respectively. Extending the study to 51 participants, including a different experiment focusing on mental arithmetic tasks, validated the previous findings and further refined bands, maintaining effectiveness with a geometric mean correlation of 0.236 and surpassing common frequency bands reported in the existing literature. This study represents a pivotal step toward converging and establishing a coherent framework for frequency band definition to be used in pupillography analysis. Furthermore, based on this, it also contributes insights into the importance of more integration and adoption of eye-tracking with pupillography technology into authentic software development contexts for cognitive load assessment at a very fine level of granularity.