Rich Samples Research Articles

Preparation of Calcium-based Phosphate Adsorbent and Mineral-rich Humic acid Fertilizer from Biomass ash and Bamboo by Hydrothermal-pyrolysis: Performance and Mechanism

Biomass ash (BA) contains alkaline cations such as K, Ca, and Mg. Due to its high pH, direct application to the soil may result in soil salinization. Composting of BA with organic matter is an effective strategy, but the composting cycle is long and there is a large amount of insoluble residue in the product. Therefore, this research proposed for the first time using the hydrothermal method to rapidly convert BA and bamboo powder (BP) into water - soluble fertilizer (WSF) within 2 hours. The insoluble hydrothermal residue was further converted into calcium - rich biochar phosphorus adsorption material by a simple pyrolysis process. WSF was neutral and contained humic acid and elements like K, Ca, Mg, and Si. A 14 - day wheat hydroponic experiment showed that the addition of 0.0125% WSF increased the fresh weight of wheat by 18.77% compared with deionized water. The calcium - based biochar adsorbent produced by pyrolysis had an ideal adsorption capacity of up to 113.6mg P g-1 for phosphate in water, higher than many existing reports. The adsorption mechanisms mainly included surface precipitation, ion exchange, and electrostatic attraction. Moreover, the calcium - rich biochar sample slowly released phosphorus into water after adsorbing phosphate. When the pH was 3 or 4, the removal rate of Pb2+, Cd2+, and Cu2+ at 15 - 20 mg L-1 was as high as 99%. This indicated its potential as a slow - release fertilizer and heavy metal remediation agent. This research provided a new way of thinking for the treatment and disposal of BA.

Combining style generative adversarial networks with particle swarm optimisation-support vector regression to design affective social robot for public health intervention

In order to improve the attractiveness of social robot serving health interventions in public workspace, we propose a product design method with the combination of Style-generative adversarial network (StyleGAN) model and particle swarm optimisation-support vector regression (PSO-SVR). This paper aims to explore the modelling generation method of social robots for health intervention based on artificial intelligence generated content (AIGC) and a mapping model between the shape characteristics and users’ visual perception based on Kansei Engineering (KE). Firstly, to address the defects of typical KE over-reliance on existing samples, we introduce the StyleGAN model in AIGC to learn and train existing robots’ shape samples and generate new robots’ shape sample images. Secondly, the morphological deconstruction method is used to deconstruct the shape features of the new robot sample. Factor analysis (FA) is also used to reduce dimension and cluster emotional words and establish a Likert scale between the shape features of robots and users’ emotional vocabulary. Finally, particle swarm optimisation-support vector regression (PSO-SVR) is used to establish a mapping model between the shape features of social robots and the emotional images of users, thus obtaining the most attractive shape combination scheme. The research results showed that the StyleGAN model in AIGC can be used to assist industrial designers in creative expression and provide rich sample sources for KE; and the PSO-SVR of machine learning can be used to build a mapping model among users’ visual feelings, emotional images and shape features. In the end, we designed an attractive social robot for public health intervention.

Model of oil pipeline tiny defects detection based on DDPM gated parallel convolutional swin transformer

Abstract To address the challenges of difficult detection of minute magnetic flux leakage (MFL) defects, insufficient inspection data, and low detection accuracy, the denoising diffusion probabilistic model (DDPM) gate dilated parallel convolution swin transformer (DGPST) is proposed. First, we introduce a DDPM-based data generation model, successfully generating a large quantity of diverse and rich MFL defect samples. Second, a gated parallel convolution layer is introduced into the backbone network. This strategy uses the characteristics of dilated convolution to broaden the receptive field of the model, thus enhancing the integration ability of global information. The addition of gating mechanism enables the model to adjust the calculation of attention weight based on broader context information in advance, which not only complicates the shortcomings of window self-attention in global dependence understanding, but also effectively suppress irrelevant calculation. Finally, the loss function of H Intersection over Union is introduced to improve the mean average precision. Following these enhancements, DGPST attains a satisfactory outcome in detecting tiny defects within the MFL problem. Experimental data indicates the accuracy of the algorithm reaches 95.6% and the delay is reduced to 7.6 ms.

Inferring in-home/out-of-home situations unreported in time-use surveys using supervised machine learning

Time-use surveys provide useful data for travel analyses. However, the survey on time use and leisure activities (TULA) Questionnaire A, a representative time-use survey in Japan, does not include questions related to the locations of activities, thus making it difficult to use for travel analyses. This study proposes machine-learning methods to determine the in-home/out-of-home situations of TULA Questionnaire A using TULA Questionnaire B with activity locations as the training data. Random forest performs better than logistic regression and decision trees in the inference. The activity was the most important factor in determining the in-home/out-of-home situations, followed by the accompanying person and time of day. The inferred outputs in the TULA Questionnaire A included the individual-based out-of-home rate profiles and the proportions of mobile persons from 1996 to 2016. Using these outputs, we analyzed trip misreporting in household travel surveys. Comparisons with nationwide and Tokyo person trip (PT) surveys implied soft refusals and trip misreporting in travel surveys. The comparison with the nationwide PT surveys suggested higher soft refusals on weekends than on weekdays. The comparison with the 1998, 2008, and 2018 Tokyo PT surveys implied the increased soft refusal in PT surveys, particularly among the male group aged between 20 and 39 and the female group aged between 35 and 49 during 1998–2018. These results suggest that careful handling of recent household travel survey data may be required. In addition, the proposed machine-learning-based method enables us to utilize the rich sample of Questionnaire A for activity-based travel analysis in future studies.

Morality through the lens of Confucian heritage countries: collective self variations and moral worldviews.

The issue of Western, Educated, Industrialized, Rich, and Democratic (WEIRD) samples dominating research has been ongoing for decades, and now the emerging trend is to turn to theoretical perspectives from the Majority World. Adopting Western-centric methods based on reductionism can overlook important details and differences between similar cultures, particularly in East Asian cultures, where the Confucian values of relational harmony take many forms. We discuss a novel theoretical perspective on moral constitutions in Confucian heritage cultures. Our central tenet is that divergent moral concepts and ideals are present in Confucian cultures because each culture emphasizes a specific pillar and the self is situated differently in the social relationships that define the scope of interpersonal moral obligations. We consider three Confucian countries: China, Japan, and South Korea as examples. Despite geographical proximity and conventional categorization in cultural psychology, each Confucian country manifests distinct patterns of the self, moral ideals, and behavior in socio-moral contexts. To understand how and why moral worldviews vary within a region, we need to examine how the self in socio-cultural contexts differs and guides interpersonal norms and behaviors across sociocultural contexts. We conclude this paper by offering methodological recommendations for including indigenous moral concepts outside the WEIRD context.

B-229 Extraction-free Nucleic Acid Sample Preparation from Inhibitor Rich Samples via Hyperbaric Heating

Abstract Background Extraction-based nucleic acid sample preparation for PCR is limited by long processing times, liquid transfers, cost, and storage requirements. Extraction-free approaches enable streamlined sample prep but are severely impacted by inhibitors present in biological sample matrices. We previously reported the use of Hyperbaric Heating (HBH) for effective organism lysis and demonstrate here its effectiveness to prepare nucleic acids for PCR from various inhibitor-rich sample matrix types. Methods HBH exposes the sample to high temperature/high pressure environment for a short duration. This process effectively lyses organisms and denatures inhibitors within seconds. Samples are sealed within a pressure-tight metallic vessel, then rapidly heated using magnetic induction. Within the sealed metallic vessel, vaporization of the aqueous sample raises the internal pressure, enabling an internal temperature higher than 100°C. Proprietary sample processing beads containing chelating agents and other proteins protect nucleic acids from fragmentation during heating. Results The efficacy of HBH for PCR amplification was tested against commercial kits and extraction-free methods. HBH treatment of nasal swab samples spiked with inactivated SARS-CoV-2 elicited detection down to 125 viral copies/mL. Viruses such as RSV and Influenza spiked in nasal swab samples demonstrated comparable PCR results as extraction prepped samples. HBH treatment of microbe samples, including Candida albicans spiked in urine and Bacillus subtilis spiked in serum, had comparable PCR threshold cycles as microbe specific DNA extraction methods (Table 1). Conclusions HBH is a generalizable extraction-free nucleic acid sample prep technology affording detection capabilities comparable to commercial sample prep methods. We demonstrated the use of HBH sample prep for detection of several infectious microorganisms in common biological matrices (nasal swab, serum, urine) without additional sample purification. With its ease of use, speed, and lower cost, HBH will be a key tool in applications where nucleic acid amplification is pivotal for diagnostic and research use.

Fatty Acid Composition Analysis of Some Apiaceae Plants Using Gas Chromatography-Flame Ionization Detector (GC-FID)

Background/aim: The Apiaceae family, also referred to as the parsley or carrot family, comprises a diverse group of plants with significant ecological and economic importance. The fundamental building blocks of plant lipids, fatty acids are involved in a number of critical biological functions. Flame ionization detection in gas chromatography (GC-FID) is a potent analytical method widely used for the qualitative and quantitative analysis of fatty acid composition in plant samples. Materials and methods: In this study, we investigated the fatty acid profiles of several Apiaceae plants using GC-FID to elucidate their lipid composition and potential applications. Results: A wide spectrum of fatty acids was confirmed, ranging from C6:0 to C22:6. Astrodaucus orientalis leaf and fruit were found rich in palmitic acid (C16:0; 35.96% and 37.65%, respectively). Ferulago asparagifolia was determined as the richest sample in terms of poly-unsaturated fatty acids such as linoleic acid (C18:2 cis, 25.65%), alpha linoleic acid (C18:3n3, 7.42%) and eicosadienoic acid (C20:2, 32.66%). Ferulago syriaca ethanol and hexane extracts contained considerable amount of oleic acid (C 18:1 n9, 40. 37% and 49.19%, respectively). Conclusion: Our review of the literature revealed that no prior reports have been made about the fatty acid compositions of Astrodaucus orientalis, Ferulago asparagifolia and Ferulago syriaca. As a result, the information provided here may be the first to describe the fatty acid contents of these species. Exploring the lipid profiles of these plants can enhance their potential applications in the food, pharmaceutical, and cosmetic industries.

Evaluation of model-integrated evidence approaches for pharmacokinetic bioequivalence studies using model averaging methods.

Conventional approaches for establishing bioequivalence (BE) between test and reference formulations using non-compartmental analysis (NCA) may demonstrate low power in pharmacokinetic (PK) studies with sparse sampling. In this case, model-integrated evidence (MIE) approaches for BE assessment have been shown to increase power, but may suffer from selection bias problems if models are built on the same data used for BE assessment. This work presents model averaging methods for BE evaluation and compares the power and type I error of these methods to conventional BE approaches for simulated studies of oral and ophthalmic formulations. Two model averaging methods were examined: bootstrap model selection and weight-based model averaging with parameter uncertainty from three different sources, either from a sandwich covariance matrix, a bootstrap, or from sampling importance resampling (SIR). The proposed approaches increased power compared with conventional NCA-based BE approaches, especially for the ophthalmic formulation scenarios, and were simultaneously able to adequately control type I error. In the rich sampling scenario considered for oral formulation, the weight-based model averaging method with SIR uncertainty provided controlled type I error, that was closest to the target of 5%. In sparse-sampling designs, especially the single sample ophthalmic scenarios, the type I error was best controlled by the bootstrap model selection method.

Pharmacokinetics of Ganaplacide and Lumefantrine in Adults, Adolescents, and Children with Plasmodium falciparum Malaria Treated with Ganaplacide Plus Lumefantrine Solid Dispersion Formulation: Analysis of Data from a Multinational Phase 2 Study.

The novel antimalarial ganaplacide combined with lumefantrine solid dispersion formulation (LUM-SDF) was effective and well tolerated in the treatment of uncomplicated falciparum malaria in adults, adolescents, and children in a multinational, prospective, randomized, active-controlled Phase II study conducted between August 2017 and June 2021 (EudraCT 2020-003284-25, Clinicaltrials.gov NCT03167242). Pharmacokinetic data from that study are reported here. The trial comprised three parts: a run-in part in 12 adult/adolescent patients treated with a single dose of ganaplacide 200 mg plus LUM-SDF 960 mg assessed potential pharmacokinetic (PK) interactions between ganaplacide and lumefantrine; in Part A, adult/adolescent patients received one of the six ganaplacide-LUM-SDF regimens or artemether-lumefantrine; and in Part B, three dose regimens identified in Part A, and artemether-lumefantrine, were assessed in children aged 2 to <12 years, with body weight ≥10 kg. A rich blood sampling schedule was used for all 12 patients in the PK run-in part and a subset of patients (N = 32) in Part A, with sparse sampling for remaining patients in Parts A (N = 275) and B (N = 159). Drug concentrations were determined by a validated protein precipitation and reverse phase liquid chromatography with tandem mass spectrometry detection method. Parameters including AUCinf, AUClast, AUC0-t, Cmax, and tmax were reported where possible, using non-compartmental analysis. In the PK run-in part, there was no notable increase in ganaplacide or lumefantrine exposure when co-administered. In Parts A and B, ganaplacide exposures increased with dose, but lumefantrine exposure was numerically under dose-proportional. Lumefantrine exposure was higher with ganaplacide-LUM-SDF than with artemether-lumefantrine, although high variability was observed. Ganaplacide and lumefantrine exposures (Cmax and AUC0-24 h) were comparable across age and body weight groups. Drug exposures needed for efficacy were achieved using the dose regimen 400 mg ganaplacide plus lumefantrine 960 mg once daily for 3 days under fasted conditions.

ATLAS upgrade for the HL-LHC

While the on-going Run-3 data-taking campaign will provide twice the integrated proton–proton luminosity currently available at the LHC, most of the data expected for the full LHC physics program will only be delivered during the HL-LHC phase. For this, the LHC will undergo an ambitious upgrade program to be able to deliver an instantaneous luminosity of 7.5⋅1034cm−2s−1, allowing the collection of more than 3 ab−1 of data at s=13.6(14)TeV. This unprecedented data sample will allow the ATLAS experiment to perform several precision measurements to constrain the Standard Model (SM) in yet unexplored regions of phase space, in particular in the Higgs sector, only accessible at the LHC. To benefit from such a rich data sample, it is fundamental to upgrade the detector to cope with the challenging experimental conditions that include radiation doses 10 times higher than what ATLAS experienced since its construction and increase in the number of interactions per bunch crossing from the current 50-60 to 200. The upgrade of the ATLAS detector comprises a completely new all-silicon tracker with extended rapidity coverage that will replace the current inner tracker detector; a redesigned trigger and data acquisition system for the calorimeters and muon systems, allowing the implementation of a readout system that can operate complex trigger algorithms at 40 MHz. Finally, a new subsystem called High Granularity Timing Detector will aid the track-vertex association in the forward region by providing timing information to the reconstructed tracks. An important ingredient, relevant to almost all measurements, is the precise determination of the delivered luminosity with systematic uncertainties below the percent level. This challenging task will be achieved by collecting the information from several detector systems using different and complementary techniques. This document will describe the ongoing ATLAS detector upgrade status and the main results obtained with the prototypes, giving a synthetic view of the whole upgrade project.

The art of research cohort construction using administrative datasets

ObjectivesUsing research case studies, I will give an overview as to how researchers can experience problems translating great research ideas, grounded in the relevant literature, into a robust research design. Assuming that the question cannot be reliably researched using small but rich sample surveys, I will present ways in which routine admin data can help in this context, along with the additional challenges posed when creating the correct cohort to address the research question. MethodsThe examples given are from a study which links together routinely collected administrative data for a representative sample of the population. It includes a wealth of information from census, civil registration data, education data, and with further permission health data can also be linked. The study in question is provided deidentified, and accessed within a data enclave. The size and scope of the study make it an unparalleled resource for analysing a range of socio-economic, demographic and health questions. ResultsI will demonstrate how despite the large number of study members, these cohorts must be carefully considered in order to research outcomes (events/results) due to inconsistency in the years that different admin data are available centrally in admin systems (health/education data). Examples include: life-course events for a cohort of women followed up to mid-life, and a complete sub-cohort followed up into later-life. ConclusionsTo showcase exciting ways in which linked admin data can be operationalised to take a longitudinal/life-course approach to address research questions, and to emphasise cohort construction is complex.

Highly siderophile element and Re-Os isotope systematics of a Neoproterozoic Iron Formation and its temporal relation to glaciation events

The Urucum iron- and manganese formation (IF-MnF) in the Santa Cruz Formation, Brazil, was deposited in a glacially influenced, late Neoproterozoic depositional environment. It has proven to be a reliable and robust archive for the late Neoproterozoic, allowing unique insights into the composition of seawater during an interval that is characterized by dramatic changes in the Earth’s litho-, hydros-, atmo-, and biosphere, including several episodes of low-latitude glaciations. Here we present highly siderophile element data of the Urucum IF-MnF to evaluate elemental sources that affected the Neoproterozoic seawater from which the Urucum IF-MnF precipitated. High uncertainties associated with current dating attempts of this formation overlapped with the Marinoan glaciation (∼650–635 Ma) as well as the Gaskiers glaciation event (∼580 Ma). A Re-Os regression line defined by iron-, manganese-, and chert-rich samples of the Urucum formation is interpreted as an isochron, yielding a refined age estimate of 577 ± 38 Ma and an initial 187Os/188Os ratio of 0.122 ± 0.003. The proposed depositional age overlaps with previous published age data of the Urucum IF-MnF, but relates the Urucum IF-MnF to the Ediacaran Gaskiers glaciation and overlaps with the age of the Shuram CIE (∼567 Ma). An initial 187Os/188Os ratio of 0.122 ± 0.003 is interpreted to represent pristine Neoproterozoic seawater and supports strong hydrothermal input, probably related to rifting, that promoted ferruginous conditions in the Urucum seawater.In an alternative scenario, Re-Os isotope data for the Urucum IF-MnF could also be interpreted in a multi-component mixing scenario, defined by hydrothermally influenced water masses that sourced most metals within the Urucum basin and a crustal component that entered the Urucum seawater either as detrital admixture or via riverine loads. Although none of the scenarios can be ruled out, we consider the isochron scenario as more plausible.

Expanding the Scope of Diverse Contexts in Affective Science.

The Future of Affective Science special issue covered a broad range of topics, ranging from the valuation and experience of emotions to their expression and regulation. Despite the breadth of these topics, consideration of diverse contexts was limited in that most studies relied on Western, Educated, Industrialized, Rich, and Democratic (WEIRD) samples and/or failed to explore the rich diversity present in those countries with vast population heterogeneity. We argue that a more systematic approach is essential to advance theory and research on how diverse contexts impact and interact with different components of emotion processes. Specifically, future research should compare a wider range of cultures; examine the interplay between culture, individual, and situation; and transcend the traditional Eastern/Western or WEIRD/non-WEIRD dichotomy and other group comparisons by embracing a dimensional approach to diverse contexts. We provide concrete examples of how leveraging these three approaches to expand the scope of diverse contexts can benefit the future development of affective science, a field heavily impacted by sociocultural context.

Signposting services in the UK: enhanced support or service diversion for people with health and social care needs: a rapid realist synthesis

PurposeIn the UK signposting services can be developed as enhanced support for people with health and social care needs or service diversion to help primary and urgent care services manage their workload. This review considers these two conflicting purposes.Design/methodology/approachThe review used a realist approach, initial searches to identify theory; we then selected 22 publications and extracted programme theories, from which we developed questions from three viewpoints: the service user, the front-line service provider and the commissioner. A rich sample of studies were found from purposive searching. To optimise the applicability of synthesis findings predominantly UK studies were included.FindingsUsers value signposting service that understand their needs, suggest a range of options and summarise potential actions. People with complex health and social care needs generally require extended time/input from signposting services. Front-line providers require initial and ongoing training, support/supervision, good knowledge of available services/resources and the ability to match users to them and a flexible response. Commissioned signposting services in England are diverse making evaluation difficult.Originality/valueMeaningful evaluation of signposting services requires greater clarity around roles and service expectations. Signposting services alone fulfil the needs of a small number of users due to the unreconciled tension between efficient (transactional) service provision and effective (relational) service provision. This is underpinned by competing narratives of whether signposting represents diversion of inappropriate demand from primary care and other urgent care services or improved quality of care through a joined-up response encompassing health, social care and community/voluntary services.

Simulation-based evaluation of the Pharmpy Automatic Model Development tool for population pharmacokinetic modeling in early clinical drug development.

The Pharmpy Automatic Model Development (AMD) tool automates the building of population pharmacokinetic (popPK) models by utilizing a systematic stepwise process. In this study, the performance of the AMD tool was assessed using simulated datasets. Ten true models mimicking classical popPK models were created. From each true model, dataset replicates were simulated assuming a typical phase I study design-single and multiple ascending doses with/without dichotomous food effect, with rich PK sampling. For every dataset replicate, the AMD tool automatically built an AMD model utilizing NONMEM for parameter estimation. The AMD models were compared to the true and reference models (true model fitted to simulated datasets) based on their model components, predicted population and individual secondary PK parameters (SP) (AUC0-24, cmax, ctrough), and model quality metrics (e.g., model convergence, parameter relative standard errors (RSEs), Bayesian Information Criterion (BIC)). The models selected by the AMD tool closely resembled the true models, particularly in terms of distribution and elimination, although differences were observed in absorption and inter-individual variability components. Bias associated with the derived SP was low. In general, discrepancies between AMD and true SP were also observed for reference models and therefore were attributed to the inherent stochasticity in simulations. In summary, the AMD tool was found to be a valuable asset in automating repetitive modeling tasks, yielding reliable PK models in the scenarios assessed. This tool has the potential to save time during early clinical drug development that can be invested in more complex modeling activities within model-informed drug development.

Electrospray ionisation suppression in aquatic dissolved organic matter studies – Investigation via liquid chromatography–mass spectrometry

Ionisation suppression is a persistent issue in electrospray ionisation mass spectrometry, which decreases the signal of co-eluting analytes. In non-targeted analysis, where analyte and organic matrix identity is unknown, this poses a very challenging analytical problem when it comes to quantitatively assessing differences between samples, including in a compositional sense. In this study, I demonstrate the problems that arise due to ionisation suppression using a very simple sample mixing scheme between a fresh, metabolite rich sample (a leaf leachate) and a forest pond water. Samples were analysed after solid phase extraction on Agilent PPL and using high performance liquid chromatography coupled to electrospray ionisation – Orbitrap mass spectrometry, charged aerosol detector and diode array detector, the latter two allowing quantification of eluting material. I found that more than half of the well-resolved analytes expected to be present (at equal concentration) were completely lost from detection after mixing with pond water DOM. The average recovery of analytical signal (i.e., the signal weighted average), was about 50%, and was highly variable between analytes. Ionisation suppression also affected the signal obtained from the geochemical background DOM, and material recovery decreased slightly when mixing samples and extracting at a higher volume on PPL. Overall, the results showed that ionisation suppression is an extremely important problem for comparison of biogeochemical samples, even when only considering presence and absence of detected features. A multi detector approach and liquid chromatographic separation adds great value in comparison to use of only high resolution mass spectrometry (in direct infusion mode).

Culturally contextualized suicide prevention for international students: new opportunities for research and practice.

The rising incidence of suicide-related thoughts and behaviors among international students presents a significant public health challenge and growing concern among college campuses. Current intervention strategies often rely on Western-centric and colonized approaches developed and tested with primarily Western, Educated, Industrialized, Rich and Democratic (WEIRD) samples. Exclusion and historical underrepresentation of ethnoracially minoritized groups in suicide prevention treatment trials create gaps in advancing our science because they often miss the cultural contextualization crucial for effective prevention and intervention in diverse groups from different countries of origin. To address the limitations of these Western-centric strategies, we explored existing prevention recommendations and approaches through the lens of an expanded version of the newly developed Protective Factors Framework, tailored for non-Western cultural perspectives. We propose significant opportunities for enhancing current practices and point to promising future directions. The primary areas for development include: (1) bolstering community empowerment and ownership, (2) refining mechanisms of change to encompass multicultural viewpoints, and (3) focusing on effective implementation and thorough evaluation for ongoing refinement. This methodology not only shows promise for enhancing international student suicide prevention but also offers insights for broader application in suicide prevention among other culturally diverse populations.

Isolation of seawater microplastics from biologically rich samples using an alkaline K2S2O8 method

In recent years, microplastics, especially marine microplastic pollution, have received global attention as a new type of environmental problem. The establishment of accurate and efficient methods for the detection of microplastics is the basis for in-depth research on the transport, transformation, fate, and ecotoxicological effects of microplastics in the environment. Microplastics in seawater frequently mix with biological tissues, resulting in challenges when identifying samples. However, commonly used pretreatment protocols for microplastics often suffer from long digestion times, inadequate digestion, and the risk of potentially damaging microplastics. This study compared the digestion efficiencies of five digestion reagents and provided further insights into two advanced oxidation methods involving Fenton’s reagent and an innovative alkaline K2S2O8 protocol based on sulfate and hydroxyl radicals. Using Raman spectroscopy, scanning electron microscopy-energy dispersive spectroscopy (SEM−EDS), and carbonyl index (CI) analyses, the status of microplastics after pretreatment was evaluated. The results revealed that the alkaline K2S2O8 method could enhance the reaction efficiency while reducing the potential for functional group damage during microplastic pretreatment. Moreover, the proposed K2S2O8 method was applied to the pretreatment of field seawater samples, and field microplastics were effectively separated from biologically rich samples. Thus, a digestion protocol based on alkaline K2S2O8 provides an effective way to isolate seawater microplastics from biologically rich samples. This study contributes to the development of efficiently microplastic monitoring and provides valuable insights into access to reliable data for fate and inventory of oceanic microplastics.

An overview of the replicability, generalizability and practical relevance of eyewitness testimony research in the Journal of Criminal Psychology

Purpose Before psychological research is used for policy reforms and recommendations, it is important to evaluate its replicability, generalizability and practical relevance. This paper aims to examine these three criteria for published articles in the Journal of Criminal Psychology. Design/methodology/approach Through a literature search for published articles in the Journal of Criminal Psychology related to the topics of the special issue Contemporary Developments in the Retrieval and Evaluation of Witness Testimony: Towards making research more applicable to investigations, this paper identified 158 eligible articles. For each article, this paper extracted variables related to the type of article, reported p-values, type of sample and stimuli, power analyses and conducted analyses and how effect sizes were used and interpreted. This paper analyzed these variables descriptively and conducted a z-curve analysis. Findings In terms of generalizability, the articles examined populations of interest (e.g. offenders, prisoners) and there was no sole reliance on Western, Educated, Industrial, Rich and Democratic samples. However, for replicability, there were currently no replication studies or published Registered Reports and the z-curve analysis indicated a low expected replication rate. Moreover, when examining practical relevance, almost no power analyses were conducted and when they were conducted, they were not reproducible or did not use meaningful effect sizes. Finally, although the majority of studies reported effect sizes, they were oftentimes not interpreted. Originality/value The present study sheds light on the potential societal impact of published articles in the Journal of Criminal Psychology.

Thermoelectric properties of reduced TiO2 -SrF2 composites

Highly stable thermoelectric materials based on inexpensive elements have great potential for heat recovery in high temperature applications. TiO2-d and SrTiO3 based thermoelectric materials are of great interest due to this reason. In this study TiO2–SrF2 based compounds were produced, to study the effect of fluorine on the thermoelectric properties of TiO2 type materials. From XPS measurements it is clear that some exchange from the TiO2–SrF2 happens forming a TiOxFy type phase. The electronic properties of the compound are very similar to the electronic properties of reduced TiO2 while some improvement is seen in the reduction of the thermal conductivity. A higher activation energy in the SrF2 rich samples might allow for increased electronic conductivity at higher temperatures interesting for further studies.