Experimental Approach Research Articles

A refined method for characterizing afterpulse probability in single-photon avalanche diodes

Single-photon avalanche diodes (SPADs) are critical components in low-light-level sensing and photonic quantum information applications. For these, it is often necessary that a full characterization of the SPAD is performed, for which a key metric is the afterpulse probability. This study provides a detailed comparison of the common synchronized and non-synchronized methods used to measure afterpulse probability. Measurements on a single SPAD reveal inconsistencies between the afterpulse probabilities obtained by the two methods. By re-deriving the equations from first principles, the discrepancy is traced to the analysis approach for the non-synchronized experiment. An improved analysis approach is presented, leading to better agreement between the non-synchronized and synchronized methods. The study also provides guidance on the experimental conditions required for the valid application of both methods, along with a detailed analysis of the limitations of the non-synchronized method under high photon flux. These findings offer a more accurate approach for characterizing afterpulse probability and for reconciling the results of two methods, which enables better quantification of SPAD performance.

Investigating novel thin-film nanocomposite membranes for sustainable water recovery using fertilizer-driven forward osmosis – Experimental and machine learning approaches

Water recovery from municipal wastewater can augment freshwater resources to meet increasing demand. An osmotic-driven membrane separation process- forward osmosis (FO) is currently being explored as a sustainable technology. This work proposes to address the challenges associated with FO namely (i) robust membrane and (ii) draw solute (DS) recovery. Robust thin-film nanocomposite membranes incorporating a) nickel ferrite or b) nitrogen-enriched nanoporous polytriazine (NENP-1) covalent organic framework were fabricated with enhanced hydrophilicity, surface roughness and anti-fouling properties. The optimum membranes M2 and C2 displayed a pure water flux of 4.86 ± 0.11 and 5.4 ± 0.2 L/m2h respectively and a specific reverse solute flux (SRSF) <<1 when using 1 M NaCl solution as the DS (feed solution – DI water). Fertilizer-driven FO (FDFO) was proposed as the diluted DS need not be recovered but could be used directly for irrigation. The pure water flux for both M2 and C2 membranes were in the following order for the fertilizers used as DS (1 M) - (NH4)2SO4 + (NH₄)₂HPO₄ > (NH4)2SO4 > (NH₄)₂HPO₄ which indicates that the mixed ions in the DS enhanced the water permeance. In all cases, the SRSF was < 1 g/L indicating the feasibility of the process. The membranes exhibited a TOC removal of > 90 % from synthetic municipal wastewater containing persistent organic pollutants and personal & pharmaceutical care products and the membranes could be regenerated after washing with a 10 mM solution of SDS for 5 cycles of operation. Further, ANN was used to develop a predictive model for water flux in FO membranes and the optimized architecture of 7–5–50–40–1 displayed a remarkable overall R2 value of 0.98 (MSE= 0.027). The FDFO process using the fabricated thin-film nanocomposite membranes holds enormous potential to be investigated in larger-scale studies.

Developments in Localized Surface Plasmon Resonance

AbstractLocalized surface plasmon resonance (LSPR) is a nanoscale phenomenon associated with noble metal nanostructures that has long been studied and has gained considerable interest in recent years. These resonances produce sharp spectral absorption and scattering peaks, along with strong electromagnetic near-field enhancements. Over the past decade, advancements in the fabrication of noble metal nanostructures have propelled significant developments in various scientific and technological aspects of LSPR. One notable application is the detection of molecular interactions near the nanoparticle surface, observable through shifts in the LSPR spectral peak. This document provides an overview of this sensing strategy. Given the broad and expanding scope of this topic, it is impossible to cover every aspect comprehensively in this review. However, we aim to outline major research efforts within the field and review a diverse array of relevant literature. We will provide a detailed summary of the physical principles underlying LSPR sensing and address some existing inconsistencies in the nomenclature used. Our discussion will primarily focus on LSPR sensors that employ metal nanoparticles, rather than on those utilizing extended, fabricated structures. We will concentrate on sensors where LSPR acts as the primary mode of signal transduction, excluding hybrid strategies like those combining LSPR with fluorescence. Additionally, our examination of biological LSPR sensors will largely pertain to label-free detection methods, rather than those that use metal nanoparticles as labels or as means to enhance the efficacy of a label. In the subsequent section of this review, we delve into the analytical theory underpinning LSPR, exploring its physical origins and its dependency on the material properties of noble metals and the surrounding refractive index. We will discuss the behavior of both spherical and spheroidal particles and elaborate on how the LSPR response varies with particle aspect ratio. Further, we detail the fundamentals of nanoparticle-based LSPR sensing. This includes an exploration of single-particle and ensemble measurements and a comparative analysis of scattering, absorption, and extinction phenomena. The discussion will extend to how these principles are applied in practical sensing scenarios, highlighting the key experimental approaches and measurement techniques.

Through the glass wall: architectural insights into the feminist Turkish play On İkinci Ev

ABSTRACT Theatre’s dynamic interaction with space is a recognised and evolving topic among artists and researchers, and independent theatres are the institutions most engaged with this topic in Turkey. This article focuses on a site-based and touring independent play, On İkinci Ev (The Twelfth House), which is performed behind glass walls in city locations and presents a one-person, autobiographical narrative of a woman trying to make herself heard. This article scrutinizes the play’s use of space from an architectural perspective to ascertain how the performance negotiates individual politics with built space and what it highlights about independent Turkish theatre. It surveys existing literature on Turkish independent theatres and their relation to space, conducts an architectural analysis of five performance spaces used for On İkinci Ev productions, and analyses how architectural and urban spaces contribute to the play’s feminist agenda. The article argues that On İkinci Ev critiques patriarchal views on women and space, and concludes that its depiction of women’s efforts to exercise their rights in public converges with experimental approaches to space found within independent Turkish theatre. As such, both the play and independent Turkish theatre more broadly resist the marginalisation and invisibility of women and theatre in public spaces.

Targeting mitochondrial dynamics: an in-silico approach for repurposing antifungal drugs in OSCC treatment

Drug repurposing for cancer treatment is a valuable strategy to identify existing drugs with known safety profiles that could combat the neoplasm, by reducing costs. Oral squamous cell carcinoma, an ulcer-proliferative lesion on the mucosal epithelium, is the most common oral malignancy. About 10% of cancer patients within the Indian subcontinent suffer from OSCC, primarily due to chewing of betel plant derivatives. Concomitant administration of the chemotherapeutic agent (Cisplatin/Paclitaxel) is the treatment of choice. Analysis of the oral mycobiome of OSCC patients has projected the role of Candida albicans in potentiating OSCC. Hence, repurposing antifungal drugs emerges as a promising approach, as these drugs could target both the cancer cells and the infection. Cancer cells often have heightened energy requirements, and targeting mitochondrial proteins to disrupt mitochondrial division and induce dysfunction contributing to cell death, offers a method for treating OSCC. We identified 18 mitochondrial targets playing a crucial role in the maintenance of mitochondrial homeostasis. They were docked against 125 antifungal ligand molecules sourced from PUBCHEM. Ligand profiling was performed using Lipinski’s rule of 5, SwissADME and ProTox. Also, molecular dynamics and MM-PBSA were performed to validate our results. Among all protein ligand interactions, we observed that targeting DRP1 with itraconazole yielded superior binding and stability. Overall, lower toxicity and thumping ADME properties solidified the choice of ligand. We hope this experimental approach will enable us to provide a basis for selecting a lead molecule for a possible novel nano-formulation and validate our finding through in-vitro cell line-based testing.

PENGARUH EKSTRAK DAUN COCOR BEBEK (BRYOPHYLLUM PINNATUM) TERHADAP MORTALITAS LARVA NYAMUK

The aim of this research was to determine the effect of cocorbek (Bryophyllum pinnatum) leaf extract on mosquito larvae mortality. The research method uses a type of quantitative research with a true experimental approach (pure experiment). It is said to be true experimental because here the researcher intervenes by manipulating the independent variables used as factors, and to see the effects they cause. Researchers will closely observe all other factors that may be considered to influence, suppress and interfere with the results of the experiment. The research results were based on hypothesis testing using one way ANOVA analysis and the results obtained were an Fcount value of 34.536 and a sig value of 0.000. With the hypothesis that Fcount &gt; Ftable and it is said to be significant if the sig value &lt; 0.05. So if compared with Ftable in this study which is 2.77, then Fcount is 34.536 &gt; Ftable 2.77. So Ha is accepted (there is an effect of cocorbek leaf extract on mosquito larvae mortality) and Ho is rejected (there is no effect of cocorbek leaf extract on mosquito larvae mortality). The conclusion of the research is that cocorbek leaf extract has an effect on the mortality of mosquito larvae. In treatment P0, it showed that no mortality occurred because cocorbek leaf extract was not given. Treatment P1 given cocorbek leaf extract had the lowest average mortality value. Meanwhile, P5 treatment had the highest average mortality value. This shows that the higher the concentration of Cocor Bebek leaf extract given, the more mosquito larvae will die. Cocorbek leaf extract can affect the mortality of mosquito larvae because it contains active chemicals that can inhibit larval growth, such as alkoloids, flavonoids, saponins and tannins which are toxic to mosquito larvae.

Development of a Mexican corn landrace, Northern Conical, under temperature and rainfall conditions predicted by the middle of this century: an experimental field approach

Background: Corn is the most important crop in Mexico, but it can be affected by climate change. Small farmers from arid and semiarid ecosystems mainly use rainfed native landraces with short productive cycles (less than 90 days), which are adapted to elevated temperatures and intense drought. Among these landraces we can find the Norther Conical corn. Hypothesis: As Northern Conical seems to be adapted to arid agroecosystems, we hypothesize that this corn landrace can tolerate the mid-century climate change conditions. Studied species: Zea mays subsp. mays (Poaceae), Northern Conical landrace. Study site and dates: An abandoned agricultural field in San Luis Potosí, central Mexico, between August and October 2022. Methods: In a field experiment, corn seeds were sowed under the conditions of higher temperature and lower rainfall predicted by the middle of this century (period 2041-2060), as well as under the current climate. Emergence and survival of plants were regularly monitored, and their functional responses were measured by the end of the experiment. Results: Northern Conical plants performed better (in terms of emergence, survival, growth rates, and photosynthetic performance) under higher temperature and lower rainfall, as compared with those developed under the current climate. Conclusions: Our results suggest that the Northern Conical corn landrace may tolerate the increases in aridity expected in the short term. However, simulations under contrasting environmental and ontogenetical conditions are needed.

Deciphering the oncogenic potential of ADAM9 in hepatocellular carcinoma through bioinformatics and experimental approaches

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide. This study investigates the role and mechanisms of ADAM9 as a biomarker and potential therapeutic target in HCC. Utilizing RNA-sequencing data and clinicopathological characteristics from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we conducted survival and meta-analyses, functional enrichment, and immune infiltration studies. Additionally, we evaluated the effects of ADAM9 silencing on HCC cell proliferation, migration, and invasion through in vitro experiments. Our results demonstrate that high ADAM9 expression is associated with poor prognosis and increased immune infiltration in HCC patients. Furthermore, ADAM9 knockdown significantly inhibited tumor cell proliferation and migration. These findings indicate that ADAM9 is a promising prognostic biomarker and potential therapeutic target in HCC. In conclusion, ADAM9 could offer avenues for developing strategies to inhibit tumor progression and improve patient outcomes.

The impact of repeated pyrethroid pulses on aquatic communities

Pesticides are considered to be one of the main causes of the decline in macroinvertebrate biodiversity in small streams. In particular, pyrethroids are detected in agricultural surface waters worldwide and pose a high risk to aquatic invertebrates. Due to their knock-down effect, even short pyrethroid exposure pulses can have significant short- and long-term effects on macroinvertebrate communities. Therefore, it is necessary to consider more realistic exposure scenarios for the environmental risk assessment of pyrethroids and, consequently, to obtain more realistic effect data by using multi-stressor test systems.In an experimental setup with artificial indoor streams (AIS), four pyrethroid pulses simulated the exposure scenario of heavy rainfall events. Effects of these 12 h-exposures at different concentrations of deltamethrin (0.64 ng/L, 4 ng/L, 16 ng/L, 64 ng/L) with intervening recovery periods of six days were assessed on an aquatic community consisting of Gammarus pulex, Ephemera danica, Lumbriculus variegatus and Potamopyrgus antipodarum with various lethal and sub-lethal endpoints.The mortality rate of G. pulex significantly increased with increasing deltamethrin concentrations, whereas the mean number of offspring significantly decreased (NOECoffspring: 16 ng/L, LOECoffspring: 64 ng/L). The biomass of L. variegatus decreased with increasing deltamethrin concentrations (NOECdry weight: 16 ng/L, LOECdry weight: 64 ng/L).The findings of this study clearly demonstrate that 12 h-deltamethrin pulses at environmentally relevant concentrations adversely affect an aquatic community. Based on the results of this study a RAC value of 5.33 ng/L is assumed, which is below the concentrations measured in rivers of up to 58.8 ng/L. Unacceptable effects on the entire freshwater environment can therefore not be ruled out. The experimental AIS approach is a useful tool for assessing the effects of repeated pulse exposures that occur during surface runoff events.

New Experimental Approaches for the Determination of Flammability Limits in Methane–Hydrogen Mixtures with CO2 Inertization Using the Spark Test Apparatus

This study presents a novel experimental method to determine the flammability limits and the minimum oxygen concentration in methane–hydrogen mixtures using the spark test apparatus (STA), by incorporating CO2 as an inert compound. The proposed methodology allows for the more accurate and efficient assessment of the safety of these flammable mixtures, which is crucial for industrial applications where hydrogen-enriched fuels are used. When comparing the literature data, the differences between methods are not significant, although the procedure, apparatus, and test conditions influence the results. Then, the proposed method is experimentally validated in the STA. Methane is enriched with hydrogen at different concentrations (10, 20, 30, and 50%). The results in the STA show good alignment with the literature data. Furthermore, literature data analysis allows for the generation of an empirical curve that shows the influence of hydrogen addition in methane–air mixtures. The theoretical flammability intervals are also presented as a result. Such representations, after method validation, are the base of the flammability interval test in the STA. The capability of the STA to define flammability ranges in ternary diagrams provides an innovative graphical approach to control explosive atmospheres and facilitates its application in the prevention of industrial accidents.

Study on energy and exergy performance of a new hybrid perforated photovoltaic/solar air heater integrated with encapsulated phase change materials: An experimental study

The current study conducts energy and exergy analyses on an innovative hybrid perforated photovoltaic/solar air heater (PV/SAH) using passive and active methods to improve thermal and electrical efficiencies. Since increasing PVs’ temperature reduces their electrical efficiency, various techniques have been employed to handle this problem, employing effective cooling strategies. This study uses an experimental approach to analyze two cooling strategies: encapsulated phase change material (PCM) units as a passive method and forced-convection mechanism as an active method. Two scenarios were considered: hybrid PV/SAH with and without encapsulated PCM units at two mass flow rates of 0.05 kg/s and 0.07 kg/s. The results illustrate that the encapsulated PCM reduced the PV and outlet temperatures by 2 °C and 4 °C, and 3 °C and 1.5 °C at the mass flow rates of 0.05 kg/s and 0.07 kg/s, respectively. The lower the outlet temperature, the lower the thermal efficiency. Hence, using the PCM units decreased the thermal efficiency but improved the electrical efficiency. The PCM units caused a reduction in daily overall energy efficiency by 12.41 % and 8.36 % at the mass flow rates of 0.05 kg/s and 0.07 kg/s due to reducing thermal efficiency. Unlike the energy efficiency, the PCM units improved the daily overall exergy efficiency by 6.28 % and 8.71 % at the mass flow rates considered. Hence, using passive and active methods is a robust technique to improve the hybrid systems’ performance.

Influence of convection during droplet evaporation on corrosion product distribution in CFRP-AA2024 galvanic couple: Modeling and experimental approaches

This work aims to clarify the impact of convection, generated within an electrolyte droplet during evaporation, on the distribution of Al(OH)3 in the CFRP-AA2024 system. Both Finite Element and experimental approaches were employed to determine whether convection is significant or negligible. By coupling the Navier–Stokes and Nernst–Planck equations with appropriate geometric and boundary conditions, the transient distribution of corrosion products was numerically tracked. The results showed that Al(OH)3 preferentially deposits on the CFRP surface, a pattern absent when convection is excluded. Experiments confirmed that internal convective currents can transport the Al(OH)3 compound, aligning with the numerical predictions.

Advanced machine learning schemes for prediction CO2 flux based experimental approach in underground coal fire areas

IntroductionUnderground coal fires pose significant environmental and health risks due to releasing CO2 emissions. Predicting surface CO2 flux accurately in underground coal fire areas is crucial for understanding the distribution of spontaneous combustion zones and developing effective mitigation strategies. In recent years, advanced machine learning techniques have shown promise in various carbon-related studies. This research uses an experimental approach to explore the power of advanced machine learning schemes for predicting CO2 flux in underground coal fire areas. ObjectivesBy leveraging the power of advanced machine learning schemes and experimental approaches, this research aims to provide valuable insights into CO2 flux prediction in coal fire areas and inform environmental monitoring and management strategies. MethodsThe study involves the collection of an experimental dataset specific to underground coal fire areas, encompassing various parameters related to CO2 flux and underground coal fire characteristics. Innovative feature engineering techniques are applied to capture the unique characteristics of underground coal fire areas and their impact on CO2 flux. Different machine learning algorithms, including Natural gradient boosting regression (NGRB), Extreme gradient boosting (XGboost), Light gradient boosting (LGRB), and random forest (RF), are evaluated and compared for their predictive capabilities. The models are trained, optimized, and assessed using appropriate performance metrics. ResultsThe NGRB model yields the best predictive performances with R2 of 0.967 and MAE of 0.234. The novel contributions of this study include the development of accurate prediction models tailored to underground coal fire areas, shedding light on the underlying factors driving CO2 flux. The findings have practical implications for delineating the spontaneous combustion zone and mitigating CO2 emissions from underground coal fires, contributing to global efforts in combating climate change.

Tuning the performance of a TphR-based terephthalate biosensor with a design of experiments approach

Transcription factor-based biosensors are genetic tools that aim to predictability link the presence of a specific input stimuli to a tailored gene expression output. The performance characteristics of a biosensor fundamentally determines its potential applications. However, current methods to engineer and optimise tailored biosensor responses are highly nonintuitive, and struggle to investigate multidimensional sequence/design space efficiently. In this study we employ a design of experiments (DoE) approach to build a framework for efficiently engineering activator-based biosensors with tailored performances, and we apply the framework for the development of biosensors for the polyethylene terephthalate (PET) plastic degradation monomer terephthalate (TPA). We simultaneously engineer the core promoter and operator regions of the responsive promoter, and by employing a dual refactoring approach, we were able to explore an enhanced biosensor design space and assign their causative performance effects. The approach employed here serves as a foundational framework for engineering transcriptional biosensors and enabled development of tailored biosensors with enhanced dynamic range and diverse signal output, sensitivity, and steepness. We further demonstrate its applicability on the development of tailored biosensors for primary screening of PET hydrolases and enzyme condition screening, demonstrating the potential of statistical modelling in optimizing biosensors for tailored industrial and environmental applications.

Influence of Sr doping on BaTiO3 properties: A combined DFT and experimental approach

Influence of Sr doping on BaTiO3 properties: A combined DFT and experimental approach

Study of Gas Jets in Structured Loess Compaction Using a Numerical and Experimental Approach

Study of Gas Jets in Structured Loess Compaction Using a Numerical and Experimental Approach

Computational evaluation of phosphonium ILs as CO2 absorbents for electrochemistry

Since phosphonium-based ionic liquids (ILs) are suitable electrolytes for electrochemical reduction, a computationally informed analysis of these ILs was conducted to assess their ability to absorb CO2. In this work, theoretical and experimental approaches were mixed with a focus on gas solubility, transport properties, and structural characterization. The calculations included free energy of solvation (ΔG), the Henry constant (Kh), and short-range energies (Coulomb plus Lennard–Jones). Two ILs, [P1444][TFSI] and [P1444][FSI], were selected for further evaluation because of their lower Kh values. The enthalpy and entropy of the solvation process for these selected ILs were computationally determined; both ILs were found to have a favourable enthalpy of solvation for gas dissolution, and [P1444][TFSI] had a lower penalty for solvation (less negative entropy). Moreover, the analysis revealed competition among the ions interacting with the gas. The structural characterization of the [P1444][TFSI] and [P1444][FSI] with the CO2 systems involved radial and spatial distribution functions. The gas was likely enveloped by an anion cage, and oxygen and fluorine exhibited greater interactions with the carbon atom of CO2 than nitrogen. The viscosity and density were also calculated for the two systems, and the addition of CO2 only caused a slight change on these values. Experiments on viscosity and density confirmed the computational results; here, compared with those of neat ionic liquids, an approximate 4 % decrease in the viscosity of CO2-saturated systems was observed. Finally, the actual CO2 solubility in [P1444][TFSI] was experimentally determined to be 120 mM; this value was nearly four times greater than those of typical aqueous bicarbonate solutions.

Pyroptosis-related gene GSDMC indicates poor prognosis and promotes tumor progression by activating the AKT/mTOR pathway in lung squamous cell carcinoma.

Lung squamous cell carcinoma (LUSC) is one of the most common malignant tumors of the respiratory. Pyroptosis plays an essential role in cancer, but there is limited research investigating pyroptosis in LUSC. In this study, pyroptosis-related genes were observed to have extensive multiomics alterations in LUSC through analysis of the TCGA database. Utilizing machine learning for selection and verifying expression levels, GSDMC was chosen as the critical gene for further experiments. Our research found that GSDMC is overexpressed in LUSC tissues and cells, and is associated with poor prognosis. Knockdown of GSDMC in LUSC inhibits cell proliferation, invasion, metastasis, chemotherapeutic sensitivity, and reduced tumor formation in nude mice, accompanied by downregulation of proliferative and EMT-related protein expression. However, these effects were counteracted in cells where GSDMC is overexpressed. Mechanistically, the oncogenic role of GSDMC is primarily achieved through the activation of the AKT/mTOR pathway, and this effect can be significantly reversed by rapamycin. Finally, SMAD4's interaction with the promoter region of GSDMC results in the suppression of GSDMC expression. In summary, our study through bioinformatics and experimental approaches not only proves that SMAD4 regulates the protumorigenic role of GSDMC through transcriptional targeting, but also indicates the possibility of developing the SMAD4/GSDMC/AKT/mTOR signaling axis as a potential biomarker and treatment target for LUSC.

Additionality in Blue Carbon Ecosystems: Recommendations for a Universally Applicable Accounting Methodology.

Blue carbon ecosystems (BCEs) remove carbon dioxide from the atmosphere and store significant amounts of organic carbon (OC) in their soils. Consequently, the protection and restoration of BCEs may contribute to net greenhouse gas emissions abatement and help address the global challenges of both mitigating and adapting to climate change. An ongoing debate is whether OC sequestered out with the blue carbon (BC) project and transported to its present location (allochthonous) should be counted as 'additional'. There are inconsistencies in the treatment of allochthonous carbon between BCE methodologies, potentially undermining the credibility of global BC accounting initiatives. To explore these inconsistences, we compare the methodologies which we were able to find online, with particular focus on the VERRA, IPCC and BlueCAM methodologies, and review the science underlying any approach to account for allochthonous OC. Our findings indicate that there are currently no robust scientific approaches to define an appropriate apportioning of allochthonous OC for discounting in the calculation of additionality. We therefore advocate for the inclusion of allochthonous OC in BC crediting projects when an observational and experimental approach does not support the calculation (and discounting) of the refractory allochthonous carbon contribution.

Mechanical Property Prediction in Silica Fume and Crumb Rubber–Modified Concrete: Soft Computing and Experimental Approach

Mechanical Property Prediction in Silica Fume and Crumb Rubber–Modified Concrete: Soft Computing and Experimental Approach