Optimal Sampling Research Articles

Employing 3D laser scanner for automated morphological assessment of aggregates produced from diverse sources and by different crushing methods

This study introduced an automated approach employing 3D scanner for quick and precise aggregates shape analysis. Recognizing existing gaps, there is still an industry demand to propose a standardized method for measuring material characteristics using 3D scanning. By addressing the limitations of previous studies, this research considered unexplored aspects of 3D scanning to improve the speed and efficiency of that. This research comprehensively examined nearly 1500 aggregates from five natural sources and five types of slag. Four statistical tests named Mann-Whitney U, Kolmogorov-Smirnov, Bootstrap, and Permutation were utilized to determine the optimal sample size for scanning. The findings suggest that scanning just 100 aggregates from each source is sufficient to be a small representative of the whole dataset and it can significantly reduce resource use while maintaining data integrity. As a practical insight, it has tried to scan a batch of 25 aggregates simultaneously in one session which could improve efficiency of scanning by reducing the processing time to just 0.6 min per particle. In MATLAB® software, some common bounding volume techniques such as Axis-Aligned, Oriented, Ellipsoid, and Sphere Bounding Box were used to analyze morphological properties. The findings showed that the aggregates sourced from Basalt, Moraine, and most of slags have more cubical shapes, while Porphyrit and Diabase aggregates are more elongated, flaky, and angular. This study also provided a comparative study of how various techniques for stone crushing affect the morphology of aggregates. The results indicate that a combination of jaw, cone, and horizontal impact crusher produces more spherical and cubical aggregates. Replacing of the cone crusher with a gyratory crusher in the same combination can improve elongation and sphericity slightly but may increase flaky particles. These insights offer valuable guidelines for future research and practical applications in construction material optimization.

Optimizing Energy Harvesting in Wireless Body Area Networks: A Deep Reinforcement Learning Approach to Dynamic Sampling

In energy-harvesting wireless body area networks (EH-WBAN), the self-sustainability of body sensor nodes without compromising the service quality criteria is very important. In remote vital signs monitoring applications, the sampling rate of body nodes in each period should be determined to achieve this goal. There are two fundamental challenges in determining the sampling rate: 1) In EH-WBAN, the rate of the harvestable energy is time-dependent and unpredictable. 2) The vital signs of the patient have different change rates relevant to the time. Therefore, a technique is required that can learn the changes of the harvestable energy and the change rates of vital signs simultaneously and specify the proper sampling rate for BNs. The reinforcement learning algorithms are among the efficient solutions for this problem because they are capable of learning environmental uncertainties. Previous RL-based methods for determining the BN's sampling rate have three fundamental problems: 1) focus on the optimization of the transmission energy and ignore the sensing energy, 2) only affect one of the two aspects of energy or sensed data in determining the sampling rate and 3) discretization of the problem space does not ensure the determination of the optimal sampling rate. Therefore, this paper proposes a method named “deep reinforcement learning-based dynamic sampling” (DRDS) which first formulates the sampling rate determination problem as a Markov decision process (MDP) and proposes a deep deterministic policy gradient algorithm (DDPG) to solve it. The proposed method considers both energy and data variability aspects in determining the sampling rate. Two parameters, the super-capacitor’s voltage level, and ambient light intensity, are considered for the energy aspect; for the data variability aspect, the long short-term memory (LSTM) algorithm is developed to predict the change rate of data in the next round. Simulations indicate that by preserving the data integrity, the proposed method can decrease the sampling rate and unnecessary data transmission by about 49.95% and 89.7%, respectively, compared with state-of-the-art methods, and allow the sensor to achieve self-sustainability.

Corncob-Derived Activated Carbon as Electrode Material for High-Performance Supercapacitor.

In this study, corncob was explored as a low-cost and abundant precursor for the preparation of activated carbon via carbonization and the KOH activation method. The alkaline/biochar ratios varied from 3:1 to 5:1, and the activation temperatures ranged from 700 to 900 °C. The characterized results reveal that the alkaline/biochar ratios and activation temperatures had a remarkable influence on the morphology and microstructure of as-prepared activated carbon (CACT-R). The CACT-R presented a porous structure with a large number of micropores and a small number of mesopores. The reasonable distribution of micropores and mesopores endows the ideal structure for ion transfer and charge storage. The optimal sample CAC700-4 exhibited the best capacitive performance with a specific capacitance of 260 F/g at 1 A/g. Moreover, the assembled CAC700-4//CAC700-4 symmetric supercapacitor showed a high energy density of 14.3 Wh/kg at a power density of 250 W/kg in 6 M KOH electrolyte. It also has a capacitance retention of 95.5% after 10,000 cycles, indicating its excellent cycle stability. These results indicate that corncob-derived activated carbon provides the possible application of biomass waste in high-performance supercapacitors.

PATIENT RECRUITMENT USING ELECTRONIC HEALTH RECORDS UNDER SELECTION BIAS: A TWO-PHASE SAMPLING FRAMEWORK.

Electronic health records (EHRs) are increasingly recognized as a cost-effective resource for patient recruitment in clinical research. However, how to optimally select a cohort from millions of individuals to answer a scientific question of interest remains unclear. Consider a study to estimate the mean or mean difference of an expensive outcome. Inexpensive auxiliary covariates predictive of the outcome may often be available in patients' health records, presenting an opportunity to recruit patients selectively, which may improve efficiency in downstream analyses. In this paper we propose a two-phase sampling design that leverages available information on auxiliary covariates in EHR data. A key challenge in using EHR data for multiphase sampling is the potential selection bias, because EHR data are not necessarily representative of the target population. Extending existing literature on two-phase sampling design, we derive an optimal two-phase sampling method that improves efficiency over random sampling while accounting for the potential selection bias in EHR data. We demonstrate the efficiency gain from our sampling design via simulation studies and an application evaluating the prevalence of hypertension among U.S. adults leveraging data from the Michigan Genomics Initiative, a longitudinal biorepository in Michigan Medicine.

A maghemite (γ-Fe2O3) incorporated activated carbon photocatalytic nanocomposite fabricated via Co-precipitation utilized against degradation of methyl orange

The γ−Fe2O3/ACP has been synthesized in different ratios by facile co-precipitation method to degrade the methyl orange dye. In order to check the stability and potential of photo activated catalyst, UV, PL, SEM, XRD, EDX, FTIR and Zeta Potential are discussed here. The bandgap has been reduced from 2.06 eV to 1.86eV. Here, 1:3 γ−Fe2O3/ACP sample showed maximum reduced bandgap of 1.86 eV. The PL spectroscopy showed that 1:3 sample has less intensity, which in turn have 94 % photo degradation of methyl orange dye in 180min. The 1:3 sample showed 87 % degradation of methyl blue dye at 125mins light irradiation and proved as an optimal concentration of ACP in maghemite at pH of 11. The inclusion of carbon into maghemite enhances the overall properties by reducing the charge recombination rate. No impurity has been found in the final synthesized samples confirmed through EDX. The XRD and SEM revealed that size of crystallites and particle size increases, which confirms that bandgap is reduced. While trapping techniques and recycling techniques has been employed on the optimal concentration sample to check its stability towards degradation of methyl orange (MO) dye. The photo catalysis through such nanocomposite is not reported before. The 1:3 sample showed promising potential towards pollutants degradation in waste water treatment.

Rapid determination of chlorate and perchlorate in tea by ion exchange chromatography-tandem mass spectrometry

Ion exchange chromatography-tandem mass spectrometry (IEC-MS/MS) has recently become the preferred method for detecting ionic substances in tea. In this study, an IEC-MS/MS method was developed for the rapid determination of chlorate and perchlorate residues in tea samples. The optimal sample extraction process, pretreatment column, and chromatographic and mass spectrometric conditions were systematically investigated. In the optimal process, the tea samples were ultrasonically extracted with methanol-water (13∶7, v/v), and a PRiME HLB SPE column was used to purify the sample extract. An AceChrom Hybri-A IEC column (150 mm×2.1 mm, 5.0 μm) was used for separation, and 100 mmol/L ammonium acetate-acetonitrile (40∶60, v/v) was used as the mobile phase for isocratic elution. The flow rate was 0.3 mL/min, the column temperature was 40 ℃, and the injection volume was 5.0 μL. The mass spectrometric data were collected in negative electrospray ionization mode combined with multiple reaction monitoring (MRM) mode to achieve the rapid and accurate separation and qualitative analysis of the desired chemical components. Quantification was performed using the internal standard (IS) method. The measurement results showed a good linear relationship when the mass concentrations of chlorate and perchlorate were between 2.00-200 and 1.00-100 μg/L, respectively, with correlation coefficients (r2) greater than 0.9990. The average recoveries of chlorate and perchlorate at three spiked levels of low, medium, and high ranged from 88.54% to 97.25% with relative standard deviations (RSDs, n=7) of 3.2%-5.2%. The limits of detection for chlorate and perchlorate were 12.0 and 8.0 μg/kg, respectively, while the limits of quantification were 40.0 and 26.6 μg/kg, respectively. The results of tests conducted to assess the linearity, specificity, accuracy, precision, and applicability of the method to the analysis of chlorate and perchlorate in 15 tea samples collected from a local market demonstrated its validity for the routine analysis of tea samples. The proposed method is simple, rapid, sensitive, and accurate, and can meet requirements for the rapid screening and quantitative analysis of residual trace chlorate and perchlorate in large quantities of tea samples.

Physical Properties of Embedded Clusters in ATLASGAL Clumps with H ii Regions

Using the optimal sampling model, we synthesized the embedded clusters of ATLASGAL clumps with H ii regions (H ii-clumps). The 0.1 Myr isochrone was used to estimate the bolometric luminosity of each star in an embedded cluster, we also added the accretion luminosity of each star in the embedded cluster. The total bolometric luminosity of synthetic embedded clusters can well fit the observed bolometric luminosity of H ii-clumps. More realistically, we considered the age spread in the young star and protostar populations in embedded clusters of H ii-clumps by modeling both constant and time-varying star formation histories (SFHs). According to the age distribution of the stellar population, we distributed the appropriate isochrones to each star, and sorted out the fraction of stellar objects that are still protostars (Class 0 and Class I phases) to properly add their accretion luminosities. Compared to a constant SFH, burst-like and time-dependent SFHs can better fit the observational data. We found that as long as 20% of the stars within the embedded cluster are still accreting, the contribution of accretion luminosity will be significant to the total bolometric luminosity of low-mass H ii-clumps with mass log10(M cl/M ⊙) < 2.8. Variations in the accretion rate, the SFE and the initial mass function and more physical processes like the external heating from H ii regions and the flaring from pre-main sequence stars and protostars need to be investigated to further explain the excess luminosity of low-mass H ii-clumps.

Sampling fish gut microbiota - A genome-resolved metagenomic approach.

Despite a surge in microbiota-focused studies in teleosts, few have reported functional data on whole metagenomes as it has proven difficult to extract high biomass microbial DNA from fish intestinal samples. The zebrafish is a promising model organism in functional microbiota research, yet studies on the functional landscape of the zebrafish gut microbiota through shotgun based metagenomics remain scarce. Thus, a consensus on an appropriate sampling method accurately representing the zebrafish gut microbiota, or any fish species is lacking. Addressing this, we systematically tested four methods of sampling the zebrafish gut microbiota: collection of faeces from the tank, the whole gut, intestinal content, and the application of ventral pressure to facilitate extrusion of gut material. Additionally, we included water samples as an environmental control to address the potential influence of the environmental microbiota on each sample type. To compare these sampling methods, we employed a combination of genome-resolved metagenomics and 16S metabarcoding techniques. We observed differences among sample types on all levels including sampling, bioinformatic processing, metagenome co-assemblies, generation of metagenome-assembled genomes (MAGs), functional potential, MAG coverage, and population level microdiversity. Comparison to the environmental control highlighted the potential impact of the environmental contamination on data interpretation. While all sample types tested are informative about the zebrafish gut microbiota, the results show that optimal sample type for studying fish microbiomes depends on the specific objectives of the study, and here we provide a guide on what factors to consider for designing functional metagenome-based studies on teleost microbiomes.

Incorporating Sb (III) and Bi (III) ions into Cs2AgNaInCl6 perovskite toward efficient white-light emission with high color rendering index

Single phosphor with efficient and high quality white-light emission is necessary for lighting applications. In this work, we report a double perovskite, Cs2AgNaInCl6 with Bi3+ and Sb3+ incorporation, which demonstrates excellent white-light properties including tunable emission component and correlated colour temperature (CCT). Using the broad-band emission of self-trapped excitons (STEs) associated with Bi3+ and Sb3+ in the Cs2AgNaInCl6 host, the blue and orange dual-band STEs emission located at 460 and 565 nm covers the entire visible range to achieve high-quality white light emission. The relative intensity of the dual emission components can be adjusted flexibly by modulating the doping ratio of Bi3+ and Sb3+. The dual STEs emission shares the same optimal excitation wavelength at 340 nm. The optimal sample of Bi3+ (1 %) and Sb3+ (10 %) codoped Cs2Ag0.1Na0.9InCl6 exhibits high color rendering index (CRI) of up to 93, and high photo-luminescence quantum yield (PLQY) of 76 %. This codoping in double perovskite approach represents a promising method for achieving high-quality white lighting application within a single phosphor.

Erratum for “Optimal Sampling Locations to Reduce Uncertainty in Contamination Extent in Water Distribution Systems”

Erratum for “Optimal Sampling Locations to Reduce Uncertainty in Contamination Extent in Water Distribution Systems”

Photocatalytic reduction of the uranium(Ⅵ) by ultra-thin porous g-C3N4 nanosheets synthesized via microwave-assisted

Graphitic carbon nitride (g-C3N4) has garnered significant attention in the realm of photocatalytic reduction of U(Ⅵ) from aqueous solutions owing to its favorable bandgap and visible light responsiveness. Nevertheless, conventionally prepared bulk g-C3N4 suffers from limitations such as a small specific surface area and high recombination of photo-generated charges, consequently impeding the efficiency of photocatalytic reactions and hampering practical applications. To address these shortcomings, this study presents a novel approach wherein ultra-thin porous g-C3N4 nanosheets were successfully synthesized through the microwave-assisted calcination of urea in a single step. The resulting g-C3N4 nanosheets exhibit a multi-hollow mesh structure with a significantly enlarged specific surface area, the specific surface area and pore size of MCN90 are 170 m²/g and 17 nm, respectively, which are 2.3 times and 8 times that of the bulk g-C3N4. Photocatalytic experiments revealed that these ultra-thin porous nanosheets demonstrate superior performance in the reduction of U(Ⅵ) to U(Ⅳ), achieving a reduction rate of 100 % within 20 minutes for the optimal sample, as opposed to 78 % in 40 minutes for bulk g-C3N4. This enhanced photocatalytic activity can be primarily attributed to the unique ultra-thin porous nanosheet structure, which facilitates increased specific surface areas, improve photoelectric properties, and substantially shortened electron migration distances which reduce the recombination efficiency of photogenerated electrons and holes pairs. Consequently, these findings not only offer insights into the optimization of g-C3N4 for U(Ⅵ) reduction but also provide a valuable reference for the preparation of other two-dimensional ultra-thin porous materials aimed at similar applications.

Sulfate modified Fe(OH)x/NF nanosheets with oxygen vacancies for enhanced oxygen evolution

The development of cost-effective and high-performance electrocatalysts for oxygen evolution reaction (OER) would be beneficial to future renewable energy storage. Herein, sulfate modified Fe(OH)x nanosheets grown on nickel foam (S–Fe(OH)x/NF) with rich undercoordinated atom centers and oxygen vacancies were fabricated through a facile hydrothermal method. The optimal sample S2–Fe(OH)x/NF exhibits outstanding OER activity with an ultralow overpotential of 261 mV to obtain a current density of 200 mA cm−2. The impressive catalytic activity is primarily attributed to the introduction of the undercoordinated atom (Fe) center, which offer rich active sites, as well as the creation of oxygen vacancies (Vo) that enhance the electron density and the intrinsic conductivity. This work opens up an in-depth understanding of transition metal oxides for OER mechanism by sulfate-decorated and a new prospect for designing highly efficient electrocatalysts.

Insights on feline infectious peritonitis risk factors and sampling strategies from polymerase chain reaction analysis of feline coronavirus in large-scale nationwide submissions.

This nationwide study aimed to investigate risk factors associated with FIP and determine optimal sample submission strategies for its diagnosis. A total of 14,035 clinical samples from cats across the US were analyzed by means of reverse transcriptase quantitative PCR to detect replicating feline coronavirus (FCoV). χ2 and logistic regression analyses were conducted to assess the association between FCoV detection rates and risk factors such as age, gender, breed, and types of submitted samples. Higher FCoV detection rates were observed in younger cats, particularly those aged 0 to 1 year, and in male cats. Purebred cats, notably British Shorthairs [OR: 2.81; P < .001], showed a higher incidence of FCoV infection than other cats. Peritoneal fluid (OR, 7.51; P < .001) exhibited higher FCoV detection rates than other samples, while lower rates were seen in blood samples (OR, 0.08; P < .001) than in other samples. High FCoV detection rates were found in urine, kidney, and lymph node samples. The study identified significant risk factors associated with FIP. Optimal sample submission strategies, particularly emphasizing the use of peritoneal fluid, kidney, and lymph node, were identified to improve FIP detection rates. Urine yielded a relatively high frequency of infection and viral loads compared with most other samples. Understanding the risk factors and optimizing sample selection for FIP diagnosis can aid in the early detection and management of the disease, ultimately improving outcomes for affected cats. These findings contribute valuable insights to FIP epidemiology and underscore the importance of continued research to enhance diagnostic strategies and disease management approaches.

Effect of NH2-functionalization of MIL-125 on photocatalytic degradation of o-xylene and acetaldehyde

Ligand functionalization of metal organic framework (MOF) is a great important strategy to enhance the various properties of pristine materials. In this study, MIL-125 with different extents of NH2-functionalization were synthesized by solvothermal method. The photocatalytic degradation efficiency of the optimal sample for o-xylene and acetaldehyde were 88 % and 49 %, respectively, which were much improved compared to pristine MIL-125 (56 % for o-xylene and 3 % for acetaldehyde). Compared to pristine MIL-125, NH2-functionlized MIL-125 were more easily photoexcited to form photogenerated carriers, which facilitated the formation of more OH and O2− radicals under visible light irradiation. In addition, NH2 groups as the adsorption site interacted with o-xylene and acetaldehyde by the H-bonding and the Lewis acid-base effect, respectively. The above results contribute to a deep understanding of the influence of ligand functionalization of MOF on the photocatalytic degradation of VOCs.

Sampling Method to Estimate Fresh Fruit Bunch Production in Oil Palm Using Geostatistical Techniques

In oil palm cultivation, harvesting is a task that demands the most attention, resources, and accuracy. The logistics of harvesting activities, from bunch cutting through delivery to processing, are organized as a function of yield per hectare, and this planning depends on production samples collected from plantations to estimate the number of fresh fruit bunches that will be harvested per crop management unit. Conventionally, production is estimated through sampling grids, most commonly every five rows and every five palms (5 × 5), 7 × 7, or 10 × 10. Sampling density, however, does not typically result from a statistically rigorous method. Therefore, the objective of the present study was to define, using geostatistics, adequate sampling grids for estimating production. Specifically, seven lots in different Colombian oil palm-growing regions with planting ages between 5 and 9 years were analyzed, and the number of reproductive structures of all oil palms was recorded. From the semivariogram of each lot, different models were proposed, fitted, and cross-validated. For each sampling grid, all possible samples were simulated in the respective lots to determine the degree of accuracy in estimating oil palm production. The optimal sampling grids differed between lots, ranging from 3 × 3 to 15 × 15.

Reveal of relationship between microscopy architecture and mechanical performance of Y/Bi substituted Bi-2212 engineering ceramics.

This study aims to find out how the crystallinity quality, surface morphology, and mechanical performances change with the substitution of yttrium (Y) for bismuth (Bi) impurity within molar ratios of 0.00 ≤ x ≤ 0.12 in the Bi2.0-xYxSr2.0Ca1.1Cu2.0Oy (Bi-2212) cuprates to reveal the dependence of micro surface topology on the substitution mechanism and achieve a strong relation between the impurity ions and crystallization mechanism. The materials are prepared by ceramic method. It is found that all the experimental findings improve remarkably with increasing yttrium impurity molar ratio of x = 0.01. Scanning electron microscopy (SEM) images indicate that the optimum Y ions strengthen the formation of flaky adjacent stacked layers due to the changes of thermal expansion, vibration amplitude of atoms, heat capacitance, reaction kinetics, activation energy, nucleation temperature, thermodynamic stability, and intermolecular forces. Besides, new engineering novel compound produced by optimum Y ions presents the best crystallinity quality, uniform surface view, greatest coupling interaction between grains, largest particle size distributions/orientations, and densest/smoothest surface morphology. Hardness measurement results totally support the surface morphology view. Moreover, mechanical design properties and durability of the tetragonal phase improve significantly with increasing replacement level of x = 0.01 due to the induction of new surface residual compressive stress areas, slip systems, and chemical bonding between the foreign and host atoms. Besides, the same sample exhibits the maximum strength and minimum sensitivity to loads depending on reduction of stored internal strain energy and degree of granularity. Consequently, cracks tend to propagate predominantly within the transcrystalline regions. Furthermore, each material investigated exhibits the characteristic behavior of the indentation size effect. In summary, the optimum Y-doped Bi-2212 sample paves the way for the expanded use of engineering ceramics across various applications based on the enhanced service life. RESEARCH HIGHLIGHTS: The presence of the optimum yttrium impurity significantly decreases the Ea value. As the Y/Bi replacement increases up to the molar substitution level of x = 0.01, the mechanical design properties and durability of the tetragonal phase enhance significantly.

Independent concentration extraction as a novel green approach resolving overlapped UV–Vis binary spectra and HPTLC-densitometric methods for concurrent determination of levocloperastine and chlorpheniramine

BackgroundThe proposed research study introduces independent concentration extraction (ICE) as a novel UV–Vis spectrophotometric approach. The approach can be used for extracting the concentration of two analytes with severely overlapped spectra from their binary mixtures. ICE is based on spectral extraction platform involving simple smart successive methods that can directly extract the original zero order spectra of the analytes at their characteristic (λmax). Chlorpheniramine maleate (CPM) and Levocloperastine fendizoate (LCF) are two commonly co-formulated drugs in cough preparations. The combined mixture was used to confirm the validity of the developed ICE tool. Another less green HPTLC was developed for the first time to separate both drugs and help also in confirming the proposed tool.MethodsFor the simultaneous determination of CPM and LCF, two ecologically friendly techniques were employed. The first approach encompasses the use of the ICE spectrophotometric method that could be successively applied for extracting the concentration of two analytes with severely overlapped unresolved spectra in their binary mixtures. Other complementary methods aiming at original spectral extraction; including spectrum subtraction (SS) and unity subtraction (US) were also successfully employed to resolve the zero order spectra of the combined drugs with all their characteristic features and peaks. The second technique used, a high-performance TLC-densitometric one, was performed on silica plates with silica plates F254 and a mobile phase with a ratio of 3:3:3:1 by volume of toluene, ethanol, acetone, and ammonia as a developing system at 230 nm.ResultsThe presented extraction approach was executed without any optimization steps or sample pretreatment for the simultaneous determination of CPM and LCF. The method was found to be valid for their determination within concentration range of 3.0–30.0 μg mL−1 for both drugs. For HPTLC method, the resulting Rf values of CPM and LCF were 0.37 and 0.78, within concentration ranges of 0.3–4.0 μg/spot and 0.8–10.0 μg/spot, respectively. Greenness assessment of both developed methodologies showed that the HPTLC method is less green than the spectrophotometric method, yet with comparable sustainability when it comes to the used technique.ConclusionThe procedures were found to be selective, accurate, and precise for analysis of the studied binary mixture. Furthermore, the environmental impact of the introduced methods was assessed using novel greenness metrics, namely AGREE and Green Analytical Procedure Index (GAPI) to prove their ecological safety. In addition, white analytical chemistry (WAC) evaluation metric was employed to ensure the synergy and coherence of analytical, practical, and ecological attributes.

Optimal variable acceptance sampling plan for exponential distribution using Bayesian estimate under Type-I hybrid censoring

Acceptance sampling plans with censoring schemes are crucial for improving quality control by efficiently managing incomplete information. This approach improves cost and time effectiveness compared to traditional methods, providing a more accurate assessment of product quality. In this study, a variable acceptance sampling plan under Type-I hybrid censoring is designed for a lot of independent and identical units with exponential lifetimes using Bayesian estimation of the mean life. This novel approach diverges from conventional methods in acceptance sampling plans, which rely on maximum likelihood estimation and the minimization of Bayes risk. Bayesian estimation is obtained using both squared error loss and Linex loss functions. Under each method, a nonlinear optimization problem is solved to minimize the testing cost, and the optimal values of the plan parameters are determined. The proposed plans are illustrated using various numerical examples, with each plan presented in tables. The acceptance sampling plan using the squared error loss function proves to be more cost-effective than the plan using the Linex loss function. A comparative analysis of the proposed plans with existing work in the literature demonstrates that our cost is much lower than the cost of existing plans using maximum likelihood estimation. Additionally, a real-life case study is conducted to validate the approach.

Revealing the sodium storage mechanism of cellulose separator-derived hard carbon anode materials for sodium-ion batteries

Hard carbon (HC) shows significant promise as a material for sodium-ion batteries (SIB). Cellulose-derived carbon is considered one of the most promising high-performance anode materials for sodium-ion batteries. In this study, waste cellulose separator-derived HC anode materials were rationally developed using the pre-oxidation-carbonization pyrolysis method. The as-prepared HC possessed advantageous characteristics for Na+ storage, including a unique fibrous structure, a reasonable space layer, and a small specific surface area (SSA). The optimal sample demonstrated a substantial reversible capacity of 361.29 mAh/g at 0.1C, an impressive high-rate performance with a reversible capacity of 272.93 mAh/g at 10C, and an initial coulombic efficiency of 84.85 %. Following 500 cycles at 1C, the capacity retained 96.38 % of its initial value. The sodium storage process was identified as the “adsorption-insertion-pore filling mechanism” through ex-situ XRD and in-situ Raman experiments. Moreover, the as-prepared HCs demonstrated better rate and cycle capability when evaluated as anodes in full-cell sodium-ion batteries (SIBs). This research provides valuable insights into the rational design of high-performance HC anodes for SIBs and other applications.

Definition of a concentration and RNA extraction protocol for optimal whole genome sequencing of SARS-CoV-2 in wastewater (ANRS0160)

Monitoring the presence of RNA from emerging pathogenic viruses, such as SARS-CoV-2, in wastewater (WW) samples requires suitable methods to ensure an effective response. Genome sequencing of WW is one of the crucial methods, but it requires high-quality RNA in sufficient quantities, especially for monitoring emerging variants. Consequently, methods for viral concentration and RNA extraction from WW samples have to be optimized before sequencing. The purpose of this study was to achieve high coverage (≥ 90 %) and sequencing depth (at least ≥200×) even for low initial RNA concentrations (< 105 genome copies (GC)/L) in WW. A further objective was to determine the range of SARS-CoV-2 RNA concentrations that allow high-quality sequencing, and the optimal sample volume for analysis. Ultrafiltration (UF) methods were used to concentrate viral particles from large influent samples (up to 500 mL). An RNA extraction protocol using silica beads, neutral phenol-chloroform treatment, and a PCR inhibitor removal kit was chosen for its effectiveness in extracting RNA and eliminating PCR inhibitors, as well as its adaptability for use with large influent samples. Recovery rates ranged from 24 % to 63 % (N = 17) for SARS-CoV-2 naturally present in WW samples. 200 mL WW samples can be enough for UF concentration, as they showed high quality sequencing analyses with between 5 × 104 GC/L and 6 × 103 GC/L. Below 6 × 103 GC/L, high-quality sequencing was also achieved for ∼40 % of the samples using 500 mL of WW. Sequencing analysis for variant detection was performed on 200 mL WW samples with coverage of >95 % and sequencing depth of >1000×. Analyses revealed the predominance of variant EG.5, known as Eris (66 %–100 %). The use of UF methods in combination with a suitable RNA extraction protocol appear promising for sequencing enveloped viruses in WW in a context of viral emergence.