Innovation for a greener future: Disentangling the asymmetric impact of green finance on green technology in european union economies.

Green finance has originated as a critical factor for green development, where green technology innovation is a primary approach. Yet, limited information is available regarding how green finance influences green technological creation. This work probes the asymmetric linkage between green finance and green technology innovation in the selected European Union countries (Germany, Sweden, France, Italy, Netherlands, Spain, Denmark, Norway, Belgium, and Finland). Prior works adopted panel data methods to get usual outcomes concerning the green finance-green technology nexus, nevertheless the reality is that various nations did not establish such connection separately. The present work, in contrast, utilizes a peculiar tool, 'Quantile-on-Quantile,' that facilitates research to probe temporal reliance in entire nations by giving global yet economy-specific intuitions on the variables' correlation. Estimates exhibit that green finance enhances green technology innovation in almost all our chosen nations at definite quantiles of data distribution. Furthermore, the findings expose that the extent of asymmetry throughout various quantiles of our variables differs by the economy, emphasising the relevance of policymakers paying particular consideration while employing green innovation and green finance policies.

The risk paradox: Exploring asymmetric nexus between climate policy uncertainty and renewable energy technology budgets.

The ups and downs of climate policy uncertainty (CPU) cast a captivating shadow over the budgets allocated to renewable energy (RE) technologies, where strategic choices and risk assessment will determine the course of our green environmental revolution. The main intention of this investigation is to scrutinize the effect of CPU on the RE technology budgets (RETBs) in the top 10 countries with the highest RE research and development budgets (the USA, China, South Korea, India, Germany, the United Kingdom, France, Japan, Australia, and Italy). Although former researchers have typically employed panel data tools to contemplate the connection between CPU and RE technology, they repeatedly ignored variations in this connection throughout different economies. In contrast, our research adopts a unique approach, "quantile-on-quantile," to check this association at the country-to-country level. This approach offers a comprehensive worldwide perspective while procuring tailor-made perceptions for individual economies. The outcomes suggest that CPU significantly decreases RETBs across several data quantiles in our sample nations. In addition, the outcomes underscore that the connections between our variables differ among nations. These outcomes highlight the significance of policymakers implementing thorough appraisals and skillfully governing plans relevant to CPU and RETBs.

Saving Hearts in Rural West Texas: The Impact of Critical Care Access on Mortality Rates.

Background The Critical Access Hospital (CAH) designation program was created in 1997 by the US Congress to reduce the financial vulnerability of rural hospitals and improve access to healthcare by keeping fundamental services in rural communities. Methods This is a retrospective observational study. Information on CAHs in West Texas in rural counties was extrapolated from the Flex Monitoring Team between 2010 and 2020. The study population included adults aged ≥25 years with a known heart failure (HF) diagnosis who were identified using ICD-10 codes. Mortality rates were obtained from the CDC Wide-ranging ONline Data for Epidemiologic Research (WONDER) database. The HF population was categorized by age, sex, and ethnicity. Mortality differences among these groups were analyzed using a two-sample t-test. The significance level was considered to be p < 0.05. Results The total study population analyzed was 1,348,001. A statistically significant difference in age-adjusted mortality rate (AAMR) was observed between the study and control groups, with a value of 3.200 (95% CI: 3.1910-3.2090, p < 0.0001) in favor of a lower mortality rate in rural counties with CAHs. When comparing gender-related differences, males and females had lower AAMRs in rural counties with CAHs. Among each gender, statistically significant differences were noted between males (95% CI: 2.181-2.218, p < 0.001) and females (95% CI: 3.382-3.417, p < 0.001). When examining the data by ethnicity, the most significant difference in mortality rate was observed within the Hispanic population, 6.400 (95% CI: 6.3770-6.4230, p < 0.0001). When adjusted to age, the crude mortality rate was calculated, which favored CAH admission in the younger population (10.200 (95% CI: 10.1625-10.2375, p < 0.001) and 11.500 (95% CI: 11.4168-11.5832, p < 0.001) in the 55-64 and 65-74 age groups, respectively). Conclusion The data clearly showed that West Texas rural county hospitals that received CAH designation performed better in terms of mortality rates in the HF population compared to non-CAH.

A combined experimental and theoretical approach for doxycycline sensing using simple fluorescent probe with distinct fluorescence change in wide range of interferences.

Overuse of doxycycline (DOXY) can cause serious problems to human health, environment and food quality. So, it is essential to develop a new sensing methodology that is both sensitive and selective for the quantitative detection of DOXY. In our current research, we synthesized a simple fluorescent probe 4,4'-bis(benzyloxy)-1,1'-biphenyl (BBP) for the highly selective detection of doxycycline by through fluorescence spectroscopy. The probe BBP displayed ultra-sensitivity towards doxycycline due to Forster resonance energy transfer (FRET). Fluorescence spectroscopy, density functional theory (DFT), 1H NMR titration, UV-Vis, and Job's plot were used to confirm the sensing mechanism. The charge transfer between the probe and analyte was further examined qualitatively by electron density differences (EDD) and quantitively by natural bond orbital (NBO) analyses. Whereas the non-covalent nature of probe BBP towards DOXY was verified by theoretical non-covalent interaction (NCI) analysis as along with Bader's quantum theory of atoms in molecules (QTAIM) analysis. Furthermore, probe BBP was also practically employed for the detection of doxycycline in fish samples, pharmaceutical wastewater and blood samples.

The effect of turmeric and black pepper powder incorporated in breakfast on postprandial glycemia, appetite, palatability, and gastrointestinal well-being in normal-weight adults.

Culinary herbs and spices are primarily known as flavor enhancers, research suggests that black pepper (Piper nigrum) and turmeric (Curcuma longa) have now been proven to prevent many non-communicable chronic diseases such as diabetes. Bioactive components of black pepper and turmeric ameliorate glucose metabolism and appetite regulation. The present research was designed to investigate the impact of turmeric and black pepper on blood glycemia, gastrointestinal well-being, appetite, and palatability. In a randomized crossover study, four iso-caloric experimental meals each having 50 g of available carbohydrates were subjected to healthy human participants (N = 20). Turmeric and black pepper were incorporated in the breakfast meal, 1 g black pepper (BP), 1 g turmeric (TR), and combination of the (BP + TR) was added in the breakfast. Standard questionnaires were used to evaluate palatability, subjective appetite, and gastrointestinal well-being. Blood glycemia, subjective gastrointestinal well-being, and appetite were measured at 0, 30, 60, 120, and 180 min. Experimental meals BP and BP + TR resulted in lower blood glycemia (p < .05) significantly compared to control meal. A decrease in perceived eating ability and hunger, and an increase in satiety after BP + TR and BP meal was observed. No significant changes were observed after consuming test meals on gastrointestinal well-being. Compared to control and BP + TR meals, BP and TR meals had considerably lower palatability. Results showed that compared to the control intake of starchy meals supplemented with black pepper and turmeric reduced postprandial glycemia, hunger, and perceived eating ability without affecting gastrointestinal well-being.

Fabrication and Characterization of Montmorillonite Clay/Agar-Based Magnetic Composite and Its Biological and Electrical Conductivity Evaluation.

Montmorillonite clay and agar are naturally occurring materials of significant importance in designing biocompatible materials tailored for applications in biotechnology and medicine. The introduction of magnetic properties has the potential to significantly boost their characteristics and expand their applications. In this study, we have successfully synthesized highly intercalated magnetic composites, incorporating magnetic iron oxide nanoparticles (MNPs), montmorillonite clay (MMT), and agar (AG), through a thermo-physicomechanical method. Three samples of MMT-AG with 2, 1.5, and 0.5% MNPs and three sample composites of MNPs-AG with 2, 1, and 0.5% MMT clay are prepared. The synthesized composites were characterized by SEM, XRD, TGA, DTA, and FTIR. SEM analysis revealed a uniform dispersion of MNPs and MMT in the composite. The XRD pattern confirmed the presence of MNPs in the composite site. The TGA and DTA results demonstrated improved thermal stability due to the MNP incorporation. FTIR spectra showed all of the constituents of agar, MNPs, and MMT clay. The swelling ratio was observed to range from 835% to 1739%. The swelling study indicated an increased hydrophobicity with the addition of MNPs to the composite. Antibacterial activities revealed a significant inhibition of Escherichia coli (E. coli) growth by ranging from 10 to 19 nm in the composite. The composite also exhibited a considerable antioxidant action, with IC50 values of 7.96, 46.55, and 57.58 µg/mL, and electrical properties just like conductors.

Nanocellulose-Based Hybrid Scaffolds for Skin and Bone Tissue Engineering: A 10-Year Overview.

Cellulose, the most abundant polymer on Earth, has been widely utilized in its nanoform due to its excellent properties, finding applications across various scientific fields. As the demand for nanocellulose continues to rise and its ease of use becomes apparent, there has been a significant increase in research publications centered on this biomaterial. Nanocellulose, in its different forms, has shown tremendous promise as a tissue engineered scaffold for regeneration and repair. Particularly, nanocellulose-based composites and scaffolds have emerged as highly demanding materials for both soft and hard tissue engineering. Medical practitioners have traditionally relied on collagen and its analogue, gelatin, for treating tissue damage. However, the limited mechanical strength of these biopolymers restricts their direct use in various applications. This issue can be overcome by making hybrids of these biopolymers with nanocellulose. This review presents a comprehensive analysis of the recent and most relevant publications focusing on hybrid composites of collagen and gelatin with a specific emphasis on their combination with nanocellulose. While bone and skin tissue engineering represents two areas where a majority of researchers are concentrating their efforts, this review highlights the use of nanocellulose-based hybrids in these contexts.

BrainNet: a fusion assisted novel optimal framework of residual blocks and stacked autoencoders for multimodal brain tumor classification.

A significant issue in computer-aided diagnosis (CAD) for medical applications is brain tumor classification. Radiologists could reliably detect tumors using machine learning algorithms without extensive surgery. However, a few important challenges arise, such as (i) the selection of the most important deep learning architecture for classification (ii) an expert in the field who can assess the output of deep learning models. These difficulties motivate us to propose an efficient and accurate system based on deep learning and evolutionary optimization for the classification of four types of brain modalities (t1 tumor, t1ce tumor, t2 tumor, and flair tumor) on a large-scale MRI database. Thus, a CNN architecture is modified based on domain knowledge and connected with an evolutionary optimization algorithm to select hyperparameters. In parallel, a Stack Encoder-Decoder network is designed with ten convolutional layers. The features of both models are extracted and optimized using an improved version of Grey Wolf with updated criteria of the Jaya algorithm. The improved version speeds up the learning process and improves the accuracy. Finally, the selected features are fused using a novel parallel pooling approach that is classified using machine learning and neural networks. Two datasets, BraTS2020 and BraTS2021, have been employed for the experimental tasks and obtained an improved average accuracy of 98% and a maximum single-classifier accuracy of 99%. Comparison is also conducted with several classifiers, techniques, and neural nets; the proposed method achieved improved performance.

Gender disparities and predictors of in-hospital mortality with Takotsubo cardiomyopathy.

BACKGROUND: Takotsubo cardiomyopathy (TCM) is classically associated with significant gender disparities, such that it is more prevalent in females, but the clinical outcomes are worse for male patients. The goal of this study was to assess contemporary gender disparities in clinical outcomes of TCM hospitalizations and to determine predictors of male in-hospital mortality. METHODS: This was a retrospective analysis involving adult hospitalizations for TCM in the U.S between 2016 and 2020. Multivariable Logistic regression was used to estimate Odds Ratio (OR) for in-hospital mortality between the two genders. Univariable Cox regression was performed to identify predictors associated with in-hospital mortality for male hospitalizations. All factors from the univariable analysis with p < 0.20 were included in a multivariable Cox regression model. RESULTS: A total of 199,920 patients with TCM were identified. Female patients with TCM had 50% lower risk of in-hospital mortality compared to male patients (Adjusted OR 0.50, 95% CI 0.46-0.55, p < 0.001). Older age, higher Charlson comorbidity index, history of intracranial hemorrhage, cardiac arrest, need for vasopressor agents, mechanical intubation, and cardiogenic shock without the use of temporary mechanical circulatory support (MCS) were associated with higher in-hospital male mortality. CONCLUSIONS: Although TCM is more prevalent among females, gender disparities exist in the clinical outcomes of TCM patients. Cardiac arrest and cardiogenic shock without the use of temporary MCS were found to be the most significant predictors of male in-hospital mortality. Cardiogenic shock with use of temporary MCS did not lead to higher male in-hospital mortality.

A Deep Dive into Cu2 ZnSnS4 (CZTS) Solar Cells: A Review of Exploring Roadblocks, Breakthroughs, and Shaping the Future.

Renewable energy is crucial for sustainable future, and Cu2 ZnSnS4 (CZTS) based solar cells shine as a beacon of hope. CZTS, composed of abundant, low-cost, and non-toxic elements, shares similarities with Cu(In,Ga)Se2 (CIGS). However, despite its promise and appealing properties for solar cells, CZTS-based solar cells faces performance challenges owing to inherent issues with CZTS material, and conventional substrate structure complexities. This review critically examines these roadblocks, explores ongoing efforts and breakthroughs, providing insight into the evolving landscape of CZTS-based solar cells research. Furthermore, as an optimistic turn in the field, the review first highlights the crucial need to transition to a superstrate structure for CZTS-based single junction devices, and summarizes the substantial progress made in this direction. Subsequently, dive into the discussion about the fascinating realm of CZTS-based tandem devices, providing an overview of the existing literature as well as outlining the possible potential strategies for enhancing the efficiency of such devices. Finally, the review provides a useful outlook that outlines the priorities for future research and suggesting where efforts should concentrate to shape the future of CZTS-based solar cells.

Brain tumor classification from MRI scans: a framework of hybrid deep learning model with Bayesian optimization and quantum theory-based marine predator algorithm.

Brain tumor classification is one of the most difficult tasks for clinical diagnosis and treatment in medical image analysis. Any errors that occur throughout the brain tumor diagnosis process may result in a shorter human life span. Nevertheless, most currently used techniques ignore certain features that have particular significance and relevance to the classification problem in favor of extracting and choosing deep significance features. One important area of research is the deep learning-based categorization of brain tumors using brain magnetic resonance imaging (MRI). This paper proposes an automated deep learning model and an optimal information fusion framework for classifying brain tumor from MRI images. The dataset used in this work was imbalanced, a key challenge for training selected networks. This imbalance in the training dataset impacts the performance of deep learning models because it causes the classifier performance to become biased in favor of the majority class. We designed a sparse autoencoder network to generate new images that resolve the problem of imbalance. After that, two pretrained neural networks were modified and the hyperparameters were initialized using Bayesian optimization, which was later utilized for the training process. After that, deep features were extracted from the global average pooling layer. The extracted features contain few irrelevant information; therefore, we proposed an improved Quantum Theory-based Marine Predator Optimization algorithm (QTbMPA). The proposed QTbMPA selects both networks' best features and finally fuses using a serial-based approach. The fused feature set is passed to neural network classifiers for the final classification. The proposed framework tested on an augmented Figshare dataset and an improved accuracy of 99.80%, a sensitivity rate of 99.83%, a false negative rate of 17%, and a precision rate of 99.83% is obtained. Comparison and ablation study show the improvement in the accuracy of this work.

Harnessing the power of bacterial laccases for xenobiotic degradation in water: A 10-year overview.

Industrialization and population growth are leading to the production of significant amounts of sewage containing hazardous xenobiotic compounds. These compounds pose a threat to human and animal health, as well as the overall ecosystem. To combat this issue, chemical, physical, and biological techniques have been used to remove these contaminants from water bodies affected by human activity. Biotechnological methods have proven effective in utilizing microorganisms and enzymes, particularly laccases, to address this problem. Laccases possess versatile enzymatic characteristics and have shown promise in degrading different xenobiotic compounds found in municipal, industrial, and medical wastewater. Both free enzymes and crude enzyme extracts have demonstrated success in the biotransformation of these compounds. Despite these advancements, the widespread use of laccases for bioremediation and wastewater treatment faces challenges due to the complex composition, high salt concentration, and extreme pH often present in contaminated media. These factors negatively impact protein stability, recovery, and recycling processes, hindering their large-scale application. These issues can be addressed by focusing on large-scale production, resolving operation problems, and utilizing cutting-edge genetic and protein engineering techniques. Additionally, finding novel sources of laccases, understanding their biochemical properties, enhancing their catalytic activity and thermostability, and improving their production processes are crucial steps towards overcoming these limitations. By doing so, enzyme-based biological degradation processes can be improved, resulting in more efficient removal of xenobiotics from water systems. This review summarizes the latest research on bacterial laccases over the past decade. It covers the advancements in identifying their structures, characterizing their biochemical properties, exploring their modes of action, and discovering their potential applications in the biotransformation and bioremediation of xenobiotic pollutants commonly present in water sources.

Unveiling the resistance of native weed communities: insights for managing invasive weed species in disturbed environments.

Weed communities influence the dynamics of ecosystems, particularly in disturbed environments where anthropogenic activities often result in higher pollution. Understanding the dynamics existing between native weed communities and invasive species in disturbed environments is crucial for effective management and normal ecosystem functioning. Recognising the potential resistance of native weed communities to invasion in disturbed environments can help identify suitable native plants for restoration operations. This review aims to investigate the adaptations exhibited by native and non-native weeds that may affect invasions within disturbed environments. Factors such as ecological characteristics, altered soil conditions, and adaptations of native weed communities that potentially confer a competitive advantage relative to non-native or invasive weeds in disturbed environments are analysed. Moreover, the roles of biotic interactions such as competition, mutualistic relationships, and allelopathy in shaping the invasion resistance of native weed communities are described. Emphasis is given to the consideration of the resistance of native weeds as a key factor in invasion dynamics that provides insights for conservation and restoration efforts in disturbed environments. Additionally, this review underscores the need for further research to unravel the underlying mechanisms and to devise targeted management strategies. These strategies aim to promote the resistance of native weed communities and mitigate the negative effects of invasive weed species in disturbed environments. By delving deeper into these insights, we can gain an understanding of the ecological dynamics within disturbed ecosystems and develop valuable insights for the management of invasive species, and to restore long-term ecosystem sustainability.

Microbial host engineering for sustainable isobutanol production from renewable resources.

Due to the limited resources and environmental problems associated with fossil fuels, there is a growing interest in utilizing renewable resources for the production of biofuels through microbial fermentation. Isobutanol is a promising biofuel that could potentially replace gasoline. However, its production efficiency is currently limited by the use of naturally isolated microorganisms. These naturally isolated microorganisms often encounter problems such as a limited range of substrates, low tolerance to solvents or inhibitors, feedback inhibition, and an imbalanced redox state. This makes it difficult to improve their production efficiency through traditional process optimization methods. Fortunately, recent advancements in genetic engineering technologies have made it possible to enhance microbial hosts for the increased production of isobutanol from renewable resources. This review provides a summary of the strategies and synthetic biology approaches that have been employed in the past few years to improve naturally isolated or non-natural microbial hosts for the enhanced production of isobutanol by utilizing different renewable resources. Furthermore, it also discusses the challenges that are faced by engineered microbial hosts and presents future perspectives to enhancing isobutanol production. KEY POINTS: • Promising potential of isobutanol to replace gasoline • Engineering of native and non-native microbial host for isobutanol production • Challenges and opportunities for enhanced isobutanol production.

Sustainable production of bacterial flocculants by nylon-6,6 microplastics hydrolysate utilizing Brucella intermedia ZL-06.

Nylon-6,6 microplastics (NMPs) in aquatic systems have emerged as potential contaminants to the global environment and have garnered immense consideration over the years. Unfortunately, there is currently no efficient method available to eliminate NMPs from sewage. This study aims to address this issue by isolating Brucella intermedia ZL-06, a bacterium capable of producing a bacterial polysaccharide-based flocculant (PBF). The PBF generated from this bacterium shows promising efficacy in effectively flocculating NMPs. Subsequently, the precipitated flocs (NMPs + PBF) were utilized as sustainable feedstock for synthesizing PBF. The study yielded 6.91 g/L PBF under optimum conditions. Genome sequencing analysis was conducted to study the mechanisms of PBF synthesis and nylon-6,6 degradation. The PBF exhibited impressive flocculating capacity of 90.1 mg/g of PBF when applied to 0.01 mm NMPs, aided by the presence of Ca2+. FTIR and XPS analysis showed the presence of hydroxyl, carboxyl, and amine groups in PBF. The flocculation performance of PBF conformed to Langmuir isotherm and pseudo-first-order adsorption kinetics model. These findings present a promising approach for reducing the production costs of PBF by utilizing NMPs as sustainable nutrient sources.

Lignin developmental patterns and Casparian strip as apoplastic barriers: A review.

Lignin and Casparian strips are two essential components of plant cells that play critical roles in plant development regulate nutrients and water across the plants cell. Recent studies have extensively investigated lignin diversity and Casparian strip formation, providing valuable insights into plant physiology. This review presents the established lignin biosynthesis pathway, as well as the developmental patterns of lignin and Casparian strip and transcriptional network associated with Casparian strip formation. It describes the biochemical and genetic mechanisms that regulate lignin biosynthesis and deposition in different plants cell types and tissues. Additionally, the review highlights recent studies that have uncovered novel lignin biosynthesis genes and enzymatic pathways, expanding our understanding of lignin diversity. This review also discusses the developmental patterns of Casparian strip in roots and their role in regulating nutrient and water transport, focusing on recent genetic and molecular studies that have identified regulators of Casparian strip formation. Previous research has shown that lignin biosynthesis genes also play a role in Casparian strip formation, suggesting that these processes are interconnected. In conclusion, this comprehensive overview provides insights into the developmental patterns of lignin diversity and Casparian strip as apoplastic barriers. It also identifies future research directions, including the functional characterization of novel lignin biosynthesis genes and the identification of additional regulators of Casparian strip formation. Overall, this review enhances our understanding of the complex and interconnected processes that drive plant growth, pathogen defense, regulation and development.

Seed nano-priming with multiple nanoparticles enhanced the growth parameters of lettuce and mitigated cadmium (Cd) bio-toxicity: An advanced technique for remediation of Cd contaminated environments.

Seed nano-priming can be used as an advanced technology for enhancing seed germination, plant growth, and crop productivity; however, the potential role of seed nano-priming in ameliorative cadmium (Cd) bio-toxicity under Cd stress has not yet been sufficiently investigated. Therefore, in this study we investigated the beneficial impacts of seed priming with low (L) and high (H) concentrations of nanoparticles including nSiO2 (50/100 mg L-1), nTiO2 (20/60 mg L-1), nZnO (50/100 mg L-1), nFe3O4 (100/200 mg L-1), nCuO (50/100 mg L-1), and nCeO2 (50/100 mg L-1) on lettuce growth and antioxidant enzyme activities aiming to assess their efficacy for enhancing plant growth and reducing Cd phytotoxicity. The results showed a significant increase in plant growth, biomass production, antioxidant enzyme activities, and photosynthetic efficiency in lettuce treated with nano-primed nSiH + Cd (100 mg L-1), nTiH + Cd (60 mg L-1), and nZnL + Cd (50 mg L-1) under Cd stress. Moreover, nano-priming effectively reduced the accumulation of reactive oxygen species (ROS) and malondialdehyde (MDA) in lettuce shoots. Interestingly, nano-primed nSiH + Cd, nTiH + Cd, and nZnL + Cd demonstrated efficient reduction of Cd uptake, less translocation factor of Cd with high tolerance index, ultimately reducing toxicity by stabilizing the root morphology and superior accumulation of critical nutrients (K, Mg, Ca, Fe, and Zn). Thus, this study provides the first evidence of alleviating Cd toxicity in lettuce by using multiple nanoparticles via priming strategy. The findings highlight the potential of nanoparticles (Si, Zn, and Ti) as stress mitigation agents for improved crop growth and yield in Cd contaminated areas, thereby offering a promising and advanced approach for remediation of Cd contaminated environments.

Co-metabolic degradation and metabolite detection of hexabromocyclododecane by Shewanella oneidensis MR-1.

Hexabromocyclododecane (HBCD) is a widely used brominated flame retardant; however, it is a persistent organic pollutant as well as affects the human thyroid hormones and causes cancer. However, the degradation of HBCD has received little attention from researchers. Due to its bioaccumulative and hazardous properties, an appropriate strategy for its remediation is required. In this study, we investigated the biodegradation of HBCD using Shewanella oneidensis MR-1 under optimized conditions. The Box-Behnken design (BBD) was implemented for the optimization of the physical degradation parameters of HBCD. S. oneidensis MR-1 showed the best degradation performance at a temperature of 30 °C, pH 7, and agitation speed of 115 rpm, with an HBCD concentration of 1125 µg/L in mineral salt medium (MSM). The strain tolerated up to 2000 µg/L HBCD. Gas chromatography-mass spectrometry analysis identified three intermediates, including 2-bromo dodecane, 2,7,10-trimethyldodecane, and 4-methyl-1-decene. The results provide an insightful understanding of the biodegradation of HBCD by S. oneidensis MR-1 under optimized conditions and could pave the way for further eco-friendly applications. KEY POINTS: • HBCD biodegradation by Shewanella oneidensis • Optimization of HBCD biodegradation by the Box-Behnken analysis • Identification of useful metabolites from HBCD degradation.

Effects of Hybrid POSS Nanoparticles on the Properties of Thermoplastic Elastomer-Toughened Polyamide 6.

In this study, polyamide 6 (PA6)/thermoplastic elastomer (TPE) blends were prepared to decrease the notch sensitivity of PA6 for automotive applications, and the morphological, rheological, mechanical, and thermal properties of PA6/TPE blends, which are partially miscible or immiscible depending on the TPE ratio, were significantly improved in the existence of polyhedral oligomeric silsesquioxane (POSS) nanoparticles with multiple reactive epoxy groups as compatibilizers. An unstable phase morphology was obtained with the addition of TPE into PA6 without POSS nanoparticles, whereas interfacial interactions between phases in the presence of POSS were enhanced as a result of a significant decrease in the average particle size from 1.39 to 0.41 µm. The complex viscosity value of the 70PA6/30TPE blend, which was 20 kPa/s-1 at 0.1 rad/s angular frequency, reached 380 kPa/s-1 with the addition of POSS due to the formation of long chains by the generation of graft and/or block copolymers, which resulted in a 65% increase in Young's modulus value. Most notably, the Izod impact strength of pure PA6, which was 10 kJ/m2, increased by 290% with the incorporation of POSS. It was confirmed by FTIR analysis that the reactive multiple epoxy groups of MultEpPOSS and EPPOSS nanoparticles react with the proper groups of PA6 and/or TPE, and also, a partial hydrogen bonding interaction occurs between PA6-TPE from the shifting of N-H and carbonyl peaks. In conclusion, it can be suggested that POSS nanoparticles can serve as highly effective compatibilizers for PA6/TPE blends and have potential commercial applications, especially in the automotive sector.