Optimal Source Research Articles

Optimal Atmospheric Heat Sources for the Interannual Variability of South Asian Summer Monsoon

AbstractUsing a Green's function‐like approach, this study identifies optimal atmospheric heat sources for the two leading modes of South Asian Summer Monsoon (SASM) interannual variability. Optimal heating for the first mode, characterized by a lower‐level anomalous anticyclone over northern Bay of Bengal (BOB), is distributed over the Arabian Sea and tropical eastern Indian Ocean (EIO)‐Maritime Continent, with cooling over the BOB‐western North Pacific. In contrast, heating over the tropical southwestern Indian Ocean and equatorial Atlantic, along with cooling over the tropical EIO‐western Pacific, optimally drives the second mode, featuring an anomalous anticyclone over central‐northern India. El Niño/Southern Oscillation indirectly influences SASM by triggering heat sources resembling these optimal patterns. Other sea surface temperatures (SSTs), like those over equatorial Atlantic, can also generate similar heating structures, causing corresponding SASM anomalies. This suggests that the impact of SST modes on SASM depends on the similarity of induced heat sources to optimal patterns.

The Effectiveness of Biofloc Technology and Its Application Prospects in Sea Cucumber (Apostichopus japonicus) Aquaculture: A Review

This review aims to advance the development of biofloc technology (BFT), providing more sustainable and efficient practices for the farming of the Japanese sea cucumber (Apostichopus japonicus). BFT is a sustainable aquaculture method that promotes nutrient recycling and effective carbon source management, offering significant advantages such as improving water quality, enhancing growth performance, and boosting the physiological activity and disease resistance of cultured animals. In A. japonicus farming, the optimal carbon source is glucose, and the ideal carbon-to-nitrogen (C/N) ratio ranges between 15 and 20. Microbial additives, such as the Bacillus species, have been shown to enhance biofloc formation and growth, as well as the immune responses in A. japonicus. However, the technology also faces limitations, including finding suitable biofloc culture protocols that match the physiological habits of A. japonicus and potential challenges with biofloc stability under varying environmental conditions. Based on existing research, this review discusses these limitations in the farming of A. japonicus. Additionally, it compares biofloc farming models for other economically important aquatic species. By addressing these key aspects, this review offers insights to enhance BFT performance, ultimately contributing to more efficient and sustainable A. japonicus aquaculture practices.

Synergizing Organizational Values and Psychological Capital for Wellbeing: Insights from Sri Lankan Public Administration

The role of human cognitive processes and constructs such as psychological capital (PsyCap), wellbeing, and values in encouraging positive behavior has been extensively examined in the existing body of knowledge, especially capturing the attention of scholars and practitioners in the domains of management and organization studies. However, how these concepts interactively create positive behavior is rarely taken into consideration in scholarly discussions. Thus, the present paper aims to explore how the values professed by an organization (i.e. espoused values) could lead employees towards positive behaviors through PsyCap and wellbeing. The research setting is Sri Lankan public administrative organization (SLPAO) and the study participants are top-level managers. This study takes an interpretivist approach with a qualitative inquiry by employing a series of in-depth interviews and organizational documents, where the initial findings on espoused values of SLPAO were then subjected to a secondary qualitative framework analysis based on the theoretical lenses of CHOSE and PERMA models of PsyCap and well-being. The findings of the present study show that the public administrators’ perceived espoused values carry reflections of wellbeing and encompass the dimensions of PsyCap. Accordingly, positive emotions are reflected by the values independence and humanity & morality; engagement by service boundedness and duty consciousness; positive relations by fairness & justice and concern on employees; meaning by public inter-est and effectiveness; and accomplishment by efficiency, expertise and formality & order. The findings clearly highlight how the espoused values become a source of PsyCap, encompassing hope and optimism while also tending to the collective well-being, and thereby enhancing positive behaviors overall. The findings suggest the potential application of PsyCap and well-being to leverage espoused values as a precursor of positive behavior among public servants. Nonetheless, the study emphasizes the necessity for further scholarly endeavors to explore the intricate connections between organizational values, PsyCap, wellbeing, and positive organizational behavior.

Increased levels of versican and insulin-like growth factor 1 in peritumoral mammary adipose tissue are related to aggressiveness in estrogen receptor-positive breast cancer

The adipose tissue (AT) surrounding breast cancer (BC) plays a pivotal role in cancer progression and represents an optimal source for new biomarker discovery. The aim of this work was to investigate whether specific AT factors may have prognostic value in estrogen receptor-positive (ER+) BC. Proteoglycan Versican (VCAN), Insulin-like Growth Factor 1 (IGF1), Reticulon 4B (RTN4), chemokines CCL5 (also known as RANTES) and interleukin 8 (IL-8) are expressed in AT and may play important roles in BC progression. Peritumoral AT and tumoral biopsies were obtained from patients with ER+ BC (N = 23). AT specimens were collected also from healthy women (N = 17; CTRL-AT). The analysis of gene expression by qPCR revealed significantly higher mRNA levels of VCAN, IGF1, RTN4, and CCL5 in BC-AT compared to the CTRL-AT, and no difference in IL-8 mRNA levels. VCAN positively correlated with patient Body Mass Index (BMI) in BC-AT, while not in CTRL-AT. Moreover, VCAN and IGF1 positively correlated with RTN4 and negatively with CCL5. Interestingly, VCAN correlated with tumoral Ki67, while IGF1 with tumoral OCT4 that, in turn, correlated with tumoral Ki67 and patient BMI. Thus, peritumoral AT content of VCAN, and IGF1 are related to BC proliferation and aggressiveness.

Will the removal of carbon, nitrogen and mixed disinfectants occur simultaneously: The key role of heterotrophic nitrification-aerobic denitrification strain

The capacity and mechanism of heterotrophic nitrification-aerobic denitrification (HNAD) strain (H1) to remove carbon, nitrogen, disinfectants chloroxylenol (PCMX) and benzethonium chloride (BEC) were investigated in this study. PCMX was removed via metabolism and chemical oxygen demand co-metabolism process. BEC was eliminated through bacterial adsorption, which greatly inhibited the removal of other pollutants. Carbon source optimization tests revealed that glucose was the optimal carbon source for co-removal of pollutants under mixed disinfectants circumstances (PCMX + BEC). Comparing the groups without (G1) and with disinfectants (G2), the content of extracellular polymeric substances was higher, and hydrophobicity was enhanced under the hazardous conditions of G2. All the nitrogen metabolism functional genes in G2 were up-regulated, and the electron transport system activity was also improved. At the same time, G2 had lower reactive oxygen species content, which reduced the probability of resistance genes dissemination, but the abundance of most quantified resistance genes was elevated in G2. Toxicity assessment assays found a dramatic reduction in the virulence of G2’s effluent compared with the mixed disinfentants. The results confirmed that H1 strain could be used to treat the disinfectant-containing wastewater, which may aid in the application of HNAD process.

A novel method for tracing gasoline using GC-IRMS and Relief-Stacking fusion model

Due to China’s vast geographical expanse and the complexity of its natural environment, traditional methods are not suitable for tracing the origins of gasoline samples from different regions of China. The aim of this study is to trace the origins of gasoline samples through the analysis of carbon stable isotopic characteristics from 60 gasoline samples collected across four major regions in China. In this study, a novel method that combines gas chromatography-isotope ratio mass spectrometry (GC-IRMS) with Relief-Stacking was proposed for the first time, significantly enhancing the precision of the provenance results. Firstly, eight characteristic components were identified by Relief feature selection model for the first time and applied to the assessment of carbon stable isotope ratios across different regions. The discovery of these components effectively reduces data redundancy, thereby enhancing the accuracy of provenance analysis. Subsequently, five effective source tracing models (XGBoost, Random Forest, CatBoost, LightGBM, and KNN) were selected based on the CEI values. To further enhance the learning efficiency of the sourcing models, this study integrated the five selected source tracing models using three different methods(voting, stacking, and blending) and validated the performance of the optimal sourcing model. The results indicated that the Stacking fusion model achieves a CEI value of 0.923, significantly outperforming other fusion models. This advantage is attributed to the Stacking fusion model combining the s trengths of Boosting and Bagging ensemble methods and leveraging the advantages of individual classifiers within the model. The method proposed in this study can effectively address the limitations of previous tracing methods and offer valuable insights for the development of platforms related to stable isotope source tracing. In future research, through appropriate parameter adjustments and feature adaptations, the Relief-Stacking model can likewise be applied to source tracing studies in other countries characterized by extensive geographic ranges and variable environmental conditions.

The Impact of Varying Ratios of Light Quality Emitted by Light-Emitting Diodes (LEDs) on the Butter Lettuce

Light-emitting diodes (LEDs) are considered the optimal artificial light source for plant factories, yet further research is needed to understand the impact of LED light quality on plant growth. This experiment investigated the growth and development of butter lettuce under varying ratios of red and blue light provided by LEDs. The specific effects of different red and blue light quality ratios on butter lettuce growth were systematically tracked and recorded, with comprehensive measurements of growth parameters and photosynthetic characteristics. Empirical findings revealed that a higher red light component compared to blue light led to improved butter lettuce characteristics. These included increased leaf length and width, elevated plant height, higher relative chlorophyll content, and an increased net photosynthetic rate. The study also highlighted that the light quality requirements of lettuce fluctuate across different growth stages, allowing for adaptable modulation of lighting conditions to align with specific growth stage needs.Total fresh weight, total dry weight and dry matter content of lettuce reached the highest values in the R8B2 treatment with 80% red light and 20% blue light, and the percentage differences reached 29.2%, 23.1% and 13.9%, respectively. Additionally, the photosynthetic chlorophyll content and net photosynthetic rate exhibited maximum percentage differences of 22.22% and 14.6%, respectively. In conclusion, the experimental evidence supports that an R8B2 spectral composition (80% red and 20% blue light) in a controlled indoor setting represents the optimal light environment for the accelerated growth and superior quality of butter lettuce.

The efficacy of infrared diode laser in enhancing the regenerative potential of human periodontal ligament stem cells (hPDLSCs)

BackgroundThe present study aimed to investigate the effects of infrared diode laser irradiation on the proliferation and differentiation capacity of periodontal ligament stem cells (hPDLSCs), which are optimal cell sources for periodontal regeneration.MethodshPDLSCs were isolated and characterized by flow cytometric analysis of mesenchymal stem cell markers, and their trilineage differentiation capacity was tested. hPDLSCs were then cultured and irradiated with infrared diode laser (970 nm) at a power of 200 mW and a fluence of 4 J/cm2 for 3 s. MTT assay was performed to assess cellular proliferation. Cell cycle analysis was performed, and the impact of infrared diode laser irradiation on the stemness and osteogenic differentiation potential of hPDLSCs was evaluated via RT‒PCR.ResultsInfrared diode laser application enhanced the stemness, viability, proliferation, and differentiation of PDLSCs. Stem cell markers (OCT4, SOX2, and NANOG) were significantly upregulated in hPDLSCs exposed to laser irradiation. There was significant overexpression of RUNX2, ALP, OPN, and OCN on day 14 after laser application.ConclusionsThese findings provide valuable insights into the specific applications of infrared diode lasers to effectively regenerate periodontal tissues. The results can aid in the development of precise clinical protocols aimed at enhancing osseointegration and promoting tissue regeneration. Ultimately, the combination of infrared diode laser with hPDLSCs is promising for stimulating periodontal regeneration.

Evaluating the therapeutic potential of different sources of mesenchymal stem cells in acute respiratory distress syndrome

BackgroundMesenchymal stem/stromal cells (MSCs) have attracted interest as a potential therapy given their anti-inflammatory and immunomodulatory properties. However, clinical trials using MSCs for acute respiratory distress syndrome (ARDS) have produced mixed and inconclusive data. In previous work, we performed a “head-to-head” comparison between different sources of MSCs and showed that each source had a unique genomic and proteomic “signature”.MethodThis study investigated which sources of MSC: bone marrow derived-MSCs (BM-MSCs), adipose tissue derived-MSCs (AD-MSCs) and umbilical cord derived-MSCs (UC-MSCs) would be the optimal candidate to be used as a therapy in an LPS-induced mouse model of ARDS. Immune cells assessment, tissue transcriptomics, animal survival, and endothelial-epithelial barrier assessment were used to evaluate their effects.ResultsWhen comparing the three most commonly used MSC sources, we found that UC-MSCs exhibited greater efficacy compared to other MSCs in improving animal survival, mitigating epithelial/endothelial damage, decreasing lung inflammation via reducing neutrophil infiltration, T cell proliferation, and M1 polarization. Bulk RNA sequencing of lung tissue also showed that UC-MSCs have the capability to downregulate extracellular trap formation, by the downregulation of key genes like Elane and Padi4. Notably, treatment with UC-MSCs demonstrated a significant reduction in Fc-γ R mediated phagocytosis, which has been associated with monocyte pyroptosis and intense inflammation in the context of COVID-19.ConclusionOur findings suggest that UC-MSCs are an optimal source of MSC to treat acute inflammatory conditions in the lungs, such as ARDS.

Data-driven stochastic dynamic economic dispatch for combined heat and power systems using particle swarm optimization

In modern power systems, the uncertain behavior of renewable energy sources (RESs) may result in deviations from the optimal operating dispatches for the various power sources. The electric power generation from Combined Heat and Power (CHP) units is characterized by high efficiency with less pollution. To use CHP units more efficiently, the dynamic economic dispatch problem is applied to obtain the optimal power and heat sources’ outputs to satisfy heat and power demands while meeting the different operational constraints. In this paper, data-driven stochastic optimization is used to model these uncertainties utilizing the Generative Adversarial Networks in scenario generation that are accurate and do not require fitting models or modeling probability distributions. Then, the Fast Forward Selection technique is used to decrease the number of scenarios to improve system tractability. The results obtained indicate that the variability in electrical load, photovoltaic (PV), and wind turbine (WT) output significantly impacts the overall operational costs of the power system. Therefore, it is essential to incorporate the uncertainties associated with electrical load, PV, and WT when aiming for accurate results in economic dispatch. the study found that the overall operation cost of the dynamic economic dispatch of the electrical system for 24 hours after integrating RES achieved a daily savings of 2.5 % in the first scenario. Furthermore, the findings demonstrate that RESs positively contribute to reducing the total operational costs of the power system. The economic dispatch of CHP systems is influenced by the integration of RESs and the uncertainties associated with electrical parameters.

IMPACT OF CAPITAL STRUCTURE ON PROFITABILITY OF VIETNAMESE INSURANCE COMPANIES

Insurance companies have an important function of absorbing and storing economic risks. Therefore, companies need to have optimal, safe, and stable capital sources to be able to finance, diversify, and transfer risks. Previous studies have only focused on market share, customers, competitive strategies, and insurance premiums without paying attention to the capital sources of insurance companies. This is more necessary when Vietnamese insurance companies have a non-optimal capital structure, leading to low profitability. The study aims to fill the above gap by analyzing the impact of capital structure on the profitability of insurance companies through the research sample of the Data Set of 40 insurance companies (listed on HNX, HOSE, UPCOM), corresponding to 297 observations in the period from 2013 - 2023. By using GMM estimation, the author has identified three independent variables explaining (and two control variables) the variation of the dependent variable profitability (ROE), including (i) General debt ratio (GDR), (ii) Debt ratio (DR), (iii) Long-term debt ratio (LDR). Based on the research results, the authors discuss and assess the important role of capital structure in insurance companies and provide financial solution recommendations to improve their profitability.

MCGDM approach based on (p, q, r)-spherical fuzzy Frank aggregation operators: applications in the categorization of renewable energy sources

The growing demand for energy, driven by population growth and technological advancements, has made ensuring a sufficient and sustainable energy supply a critical challenge for humanity. Renewable energy sources, such as biomass, solar, wind, and hydro, are inexhaustible and environmentally friendly, offering a viable solution to both the energy crisis and the fight against global warming. However, selecting the optimal renewable energy source remains a complex decision-making problem due to the varying characteristics and impacts of these sources. Motivated by the need for more accurate and nuanced decision-making tools in this domain, this paper introduces a novel multicriteria group decision-making (MCGDM) approach based on \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:(p,q,r)-$$\\end{document}spherical fuzzy Frank aggregation operators. By integrating Frank t-norm with \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:(p,q,r)-$$\\end{document}spherical fuzzy sets, we develop aggregation operators (AOs) that effectively manage membership, neutral, and non-membership degrees through parameters \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:p$$\\end{document}, \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:q$$\\end{document}, and \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:r$$\\end{document}. These AOs provide a more refined framework for decision-making, leading to improved outcomes. We apply this approach to evaluate and identify the superior and optimal renewable energy source using artificial data, demonstrating the advantages of the proposed operators compared to existing methods. This work contributes to the field by offering a robust tool for addressing the energy crisis and advancing sustainable energy solutions.

WhiteFox: White-Box Compiler Fuzzing Empowered by Large Language Models

Compiler correctness is crucial, as miscompilation can falsify program behaviors, leading to serious consequences over the software supply chain. In the literature, fuzzing has been extensively studied to uncover compiler defects. However, compiler fuzzing remains challenging: Existing arts focus on black- and grey-box fuzzing, which generates test programs without sufficient understanding of internal compiler behaviors. As such, they often fail to construct test programs to exercise intricate optimizations. Meanwhile, traditional white-box techniques, such as symbolic execution, are computationally inapplicable to the giant codebase of compiler systems. Recent advances demonstrate that Large Language Models (LLMs) excel in code generation/understanding tasks and even have achieved state-of-the-art performance in black-box fuzzing. Nonetheless, guiding LLMs with compiler source-code information remains a missing piece of research in compiler testing. To this end, we propose WhiteFox, the first white-box compiler fuzzer using LLMs with source-code information to test compiler optimization, with a spotlight on detecting deep logic bugs in the emerging deep learning (DL) compilers. WhiteFox adopts a multi-agent framework: (i) an LLM-based analysis agent examines the low-level optimization source code and produces requirements on the high-level test programs that can trigger the optimization; (ii) an LLM-based generation agent produces test programs based on the summarized requirements. Additionally, optimization-triggering tests are also used as feedback to further enhance the test generation prompt on the fly. Our evaluation on the three most popular DL compilers (i.e., PyTorch Inductor, TensorFlow-XLA, and TensorFlow Lite) shows that WhiteFox can generate high-quality test programs to exercise deep optimizations requiring intricate conditions, practicing up to 8 times more optimizations than state-of-the-art fuzzers. To date, WhiteFox has found in total 101 bugs for the compilers under test, with 92 confirmed as previously unknown and 70 already fixed. Notably, WhiteFox has been recently acknowledged by the PyTorch team, and is in the process of being incorporated into its development workflow. Finally, beyond DL compilers, WhiteFox can also be adapted for compilers in different domains, such as LLVM, where WhiteFox has already found multiple bugs.

Wheat Peptides as Catalysts for Athletic Performance Improvement in Cross-Country Skiers: A Randomized Controlled Trial.

This study investigated the efficacy of wheat peptide supplementation compared to regular proteins in elite cross-country skiers, providing insights into the metabolic and performance effects of these supplements in order to guide athletes in selecting optimal energy sources for training and competition. Nineteen healthy male cross-country skiers were enrolled and assigned to either the peptide group (PEP, n = 9) or the protein group (PRO, n = 10). A four-week intervention study involving supplementation with wheat peptides/regular proteins was conducted, and pre- and post-intervention assessments were performed to evaluate exercise capacity and metabolic profiles. The study found that the PEP group and the PRO group showed distinct within-group effects on exercise performance. The PEP group demonstrated improved aerobic capacity, including better performance in 10 km roller skating, an increased lactate threshold, and reduced resting blood lactate levels. The PRO group enhanced anaerobic capacity, such as improved sprint time, hexagon test performance, and lactate clearance. Metabolomic analysis revealed specific metabolic pathways affected in each group, with the PEP group showing impacts on the α-linolenic acid pathway and the PRO group on ketone body synthesis and degradation as well as vitamin B6 metabolism. Our findings indicate that wheat oligopeptides and regular proteins have comparable effects on exercise performance. However, the wheat peptides may offer greater advantages in enhancing aerobic capacity. No significant variations were observed in blood metabolite profiles between the two groups, but distinct metabolic pathways exhibited different responses.

Detection and Characterization of Lasiodiplodia pseudotheobromae Associated with Stem Wilt on Ficus hirta (Vahl) and Its Fungicidal Sensitivity

Ficus hirta Vahl is an important medicinal and edible plant in southern China. Typical green wilting on leaves and brown necrotic spots on the stems were observed since mid-June 2022 in an F. hirta plantation in Danzhou, Hainan (China). The disease rapidly developed, causing stem withering and plant death. The disease incidence varied from 45 to 85% prevalence, and the average disease index was 47 in the period of outbreak during June to December. Relevant hypothetical fungi were isolated from naturally infected wilt tissues, and their pathogens were preliminarily confirmed to be Lasiodiplodia pseudotheobromae through hypothetical fungal culturing, morphological characteristic observations, and pathogenicity testing on F. hirta plants. The phylogenetic tree constructed based on partial ITS, translation elongation factor (TEF1-α), and the β-tubulin gene (TUB2) further confirmed the identity of the pathogen as L. pseudotheobromae. Further research on the biological characteristics of L. pseudotheobromae showed that the optimal temperature for the growth of L. pseudotheobromae was PDA medium, with a temperature of 30 °C and pH of 6. Peptone and fructose were the optimal nitrogen and carbon sources for it. In vitro efficacy testing showed that among eleven fungicides, fluazinam and prochloraz had the highest mycelial growth inhibition, with an EC50 of 0.0477 µg/mL and 0.0996 µg/mL, respectively. And the two fungicides showed significant control on the stem wilt of F. hirta in a pot. To our knowledge, this is the first comprehensive report on the pathogen identification and biological characteristics of L. pseudotheobromae infecting the stem wilt of F. hirta in China. Our results provide important information for developing effective management measures and controlling this disease.

Exposure to bisphenols, parabens, and benzophenones in colostrum breast milk of Panamanian women: A pilot study from the PA-MAMI cohort

BackgroundBreast milk is the optimal source of nutrition for infants but can also expose them to endocrine-disrupting chemicals (EDCs), among other environmental contaminants. AimTo determine concentrations of non-persistent phenolic EDCs (three bisphenols, four parabens [PBs], and six benzophenones [BPs]), in colostrum samples from Panamanian mothers and to examine associated reproductive, sociodemographic, and life-style factors. MethodsDispersive liquid–liquid microextraction was used to measure concentrations of bisphenol A (BPA), bisphenol F (BPF), bisphenol S (BPS), methyl- (MeP), ethyl- (EtP), propyl- (n-PrP), and butyl-paraben (n-BuP), and benzophenones BP-1, BP-2, BP-3, BP-6, BP-8, and 4-hydroxy-BP in colostrum milk samples from 36 mothers. An ad hoc questionnaire was used to collect data on potential influentially variables, and multiple linear and logistic regression analyses were conducted. ResultsTwo or more tested EDCs were detected in 36 colostrum samples (100 %), at least four in 14 samples (38.9 %), and at least six in 4 samples (11.1 %). The most frequently detected compounds were BPA (91.7 %), BP-8 (63.9 %), MeP (47.2 %), and BPF (41.7 %). The median concentration was 3.45 ng/mL for BP-8 and 1.37 ng/mL for BPA. No concentrations of n-PrP, BP-1, BP-6, or 4-hydroxy-BP were detected. Associations were observed between phenolic EDC concentrations and maternal place of residence, consumption frequency of poultry, fish, fresh cheese, fruit, yogurt and chocolate, intake of nutritional supplements, and application of some personal care products. ConclusionsBisphenols, parabens, and benzophenones were widely present in colostrum milk samples from Panamanian women. Preventive measures are needed to maximize the benefits of breastfeeding.

Effect of discretization on off-axis listeners in binaural synthesis based on the optimal source distribution

3D sound reproduction based on binaural synthesis over loudspeakers is one of the most important techniques in immersive spatial audio. The system inversion involved in the binaural synthesis gives rise to several problems such as dynamic range loss, distortion of the reproduction transfer function, and a lack of robustness to room reflections. The principle of Optimal Source Distribution was proposed to overcome these problems. This utilizes a pair of conceptual monopole transducers whose azimuthal location varies continuously as a function of frequency. Another potential of the principle is that it can provide listening positions for multiple off-axis listeners, in addition to the on-axis listener whose inverse matrix is given, since the phase interference state is aligned at all frequencies. However, these continuously varying transducers are too conceptual to realize in practice. It is necessary to provide discretized sound sources with appropriate frequency ranges according to the principle. In this paper, the effect of discretization of the principle on off-axis listeners' performance is numerically investigated to reveal how those off-axis sweet spots are formed as the discretization becomes finer. An experiment is also carried out using an actual discretized system and the effect of the head-related transfer functions is considered.

Maternal Mediterranean Diet During Lactation and Infant Growth.

Background: Human milk is considered the optimal source of nutrition for infants. Maternal diet is associated with the composition of human milk. The Mediterranean diet (MedDiet) has been studied in pregnancy and during lactation, and it has been associated with changes in milk composition, yet there is a lack of research on MedDiet during lactation and infant outcomes. Methods: Mother-infant dyads (n = 167) from ABC Baby, a prospective observational study, were included in this analysis. Maternal diet was obtained using an adapted version of the National Cancer Institute Diet History Questionnaire II, at 2 weeks or 2 months postpartum. Maternal MedDiet score was calculated using servings of vegetables, fruits, whole grains, nuts and seeds, legumes, fish, monounsaturated-to-saturated fatty acid ratio, red and processed meats, and added sugar. Infants' length, weight, and flank skinfold thickness were measured at 6 months. Using World Health Organization standards, weight-for-age (WAZ), length-for-age (LAZ), and weight-for-length (WLZ) Z-scores were calculated. Multiple linear regression models were adjusted for potential confounders. Results: Higher maternal MedDiet score and intake of fruit and fish were associated with lower flank skinfold thickness (β = -0.33, -0.52, and -1.26, respectively). Intake of nuts and seeds was associated with higher WLZ (β = 0.29). Intake of red and processed meats was associated with lower WAZ (β = -0.18) and LAZ (β = -0.18). Energy-adjusted added sugar intake was associated with lower WLZ (β = -0.02). Conclusions: The maternal MedDiet score was associated with lower skinfold thickness, while its components were associated with differences in anthropometric Z-scores. Further research on the maternal MedDiet and corresponding human milk composition is needed to explore this relationship.

Влияние биологически активных веществ на тепловой и окислительный стресс модельных объектов Caenorhabditis elegans

Modern medicine strives to prevent age-related diseases. Oxidative stress is associated with development and progression of various diseases. Reactive oxygen species are part of vital physiological processes. High levels of reactive oxygen lead to stress and pathology whereas low ones are associated with healthy physiology. Plant-derived adaptogens demonstrate good results in stress tolerance and homeostasis. Plant materials are a pharmacologically optimal source of chemical compounds to treat various diseases, including those caused by oxidative stress. The research featured biologically active substances isolated from extracts of callus, suspension, and root cultures of medicinal plants. Baicalin and trans-cinnamic acid were obtained from Scutellaria baicalensis while ursolic acid came from Thymus vulgaris. The biologically active substances were tested for neuroprotective properties, as well as for the impact on the expression of SOD-3 and HSP-16.2. Caenorhabditis elegans served as a model to study the accumulation of carbonylated proteins and lipofuscin. The neuroprotective activity of all tested substances decreased as their concentration fell from 200 to 10 μmol/L. C. elegans proved more resistant to thermal stress if pretreated with the biologically active substances. In response to thermal stress, nematodes expressed SOD-3 more actively than HSP-16.2. At 100 μmol/L, the biologically active substances could reduce the level of carbonylated proteins. Ursolic acid was especially effective against protein carbonylation and lipofuscin accumulation in all concentrations. Baicalin, trans-cinnamic acid, and ursolic acid made it possible to reduce oxidative and thermal stress, thus demonstrating good prospects for further studies as part of adaptogenic prepa rations.

Electricity system optimisation based on python model for renewable electricity generation portfolio

100% renewable electricity scenarios have received great attention from industry and policy makers, this is due to its widespread need for technical, economical, and renewable integration action plans. In this research, a python model named WIBSS, is developed and tested for adequacy using sensitivity analysis and then used to simulate the Irish electricity system.In this investigation, the optimal cost was identified with the installed capacities needed for the electricity system for high electricity demand scenario, and the generation portfolios for the electricity system in Ireland is proposed.The electricity system parameters are determined and the levelised cost of electricity is optimised and tabulated. In this investigation, the optimal solution is identified to decrease curtailment and minimize the total cost. Overlay graphs are plotted, and the optimal renewable sources combinations are presented.This research of determining generation portfolios toward 100% renewable electricity systems demonstrates simulations of two different pathways for 2030 scenarios to meet electricity demand in Republic of Ireland. The renewable energy target appeared in the government climate action plan and the authors renewable energy target determined based on the simulation of the python model, with more than doubled photovoltaic installation, a significant reduction in offshore wind, and a substantial integration of battery capacity, the authors renewable energy target performs better than renewable energy target, the levelised cost of electricity were 57.22 €/mWh and 51.11 €/mWh respectively. The least cost pathway is extended to balance between electricity generation and electricity demand in 2040 scenario, and keys target were proposed for generation portfolios.