Great Impact Research Articles

Botanical Extracts and Compounds of Castanea Plants and Methods of Use: US20190125818A1 - The United States Patent Evaluation.

Bacterial infections are increasingly difficult to combat, which makes them a threat to public health on a global level. Staphylococcus aureus is considered one of the main causes of infections in hospitals, as it has a variety of virulence factors, as well as is able to produce bacterial biofilms, which, consequently, bring numerous damages to public health as a result of increased resistance to conventional antibiotics and a longer hospital stay. Therefore, the use of compounds extracted from medicinal plants is a potential pharmaceutically acceptable target, as they do not have toxicity and the potential to disrupt biofilms produced by Staphylococcus aureus already evidenced, thus revealing their relevance to our study. The objective of this work was to perform a critical analysis of a patent with natural extracts against bacterial biofilms found in the United States Patent and Trademark Office (USPTO) database, to map the possible bioactive compounds that may serve as potential future antimicrobial drugs. A technological survey was carried out to verify existing patents using natural extracts with anti-biofilm potential. For this, it was searched with the keywords: Botanical extracts AND biofilms; which were performed in the United States Patent and Trademark Office (USPTO) database. Thus, the selected patent used a non-aqueous extract partitioned and vacuum-contracted, subsequently lyophilized for assays with antimicrobial potential. Because of this, a patent was analyzed regarding its chemistry, and biological activity, followed by a critical analysis of the technology proposed in the invention. When using the keywords Botanical extracts AND biofilms in the USPTO, it was possible to find twenty-two inventions; however, only four patents in the USPTO were in agreement with the proposal of the natural extract having antimicrobial activity and an anti-biofilm potential, of which two belonged to the same applicant with similar proposals. The key point of this invention was to enable the compounds of the Castanea sativa plant and its methods of obtaining the extract to present a significant antimicrobial action associated or not with antibiotics, promoting the development of new therapies against bacterial infections capable of disrupting biofilms. The invention developed a methodology for extracting Castanea sativa, in which pentacyclic triterpene compounds were found mostly in its leaves. Whereas for the extraction, the crude methanol extracts called extracts 224 from the ground leaves were made by maceration, filtered, combined, concentrated under pressure in rotary evaporators, and lyophilized. After that, they were resuspended in water and partitioned in succession with hexane, ethyl acetate, and butanol. The most active refined partition was the 224C extract with the solvent ethyl acetate, which was subjected to further fractionation using silica column chromatography. Resulting in the most refined extract, which was 224C-F2, capable of acting directly on the quorum sensing of bacteria, mainly Staphylococcus aureus, blocking the translation of RNAIII, including a series of exotoxins. Regarding the antimicrobial capacity against Staphylococcus aureus, it presented Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) of 1.56 μg/mL-1 and > 100 μg/mL -1, respectively. Given the analyzed patent, it was possible to verify the importance of alternatives to reduce the impact of bacterial biofilms, which causes damage to industries in general and to health. From this, the invention analyzed has a promising proposal with antimicrobial potential focusing on the great impact of bacterial biofilms. Therefore, natural extracts with antibiofilmic potential can help to minimize the economic losses caused to health due to these multidrug-resistant microorganisms with different virulence mechanisms.

PLANT DISEASE RECOGNITION USING VGG-16

Agriculture and modern farming is one of the fields where IoT and automation can have a great impact. Maintaining healthy plants and monitoring their environment in order to identify or detect diseases is essential in order to maintain a maximum crop yield. The implementation of current high rocketing technologies including artificial intelligence (AI), machine learning, and deep learning has proved to be extremely important in modern agriculture as a method of advanced image analysis domain. Artificial intelligence adds time efficiency and the possibility of identifying plant diseases, in addition to monitoring and controlling the environmental conditions in farms. Several studies showed that machine learning and deep learning technologies can detect plant diseases upon analyzing plant leaves with great accuracy and sensitivity. In this study, considering the worth of machine learning for disease detection, we present a convolutional neural network VGG-16 model to detect plant diseases, to allow farmers to make timely actions with respect to treatment without further delay. To carry this out, 19 different classes of plants diseases were chosen, where 15,915 plant leaf images (both diseased and healthy leaves) were acquired from the Plant Village dataset for training and testing. Based on the experimental results, the proposed model is able to achieve an accuracy of about 95.2% with the testing loss being only 0.4418. The proposed model provides a clear direction toward a deep learning-based plant disease detection to apply on a large scale in future. Keywords—Machine learning; VGG-16; disease detection; convolutional networks; Plant Village; modern farming. Keywords—Machine learning; VGG-16; disease detection; convolutional networks; Plant Village; modern farming.

Bioinformatics Analysis and Validation of Potential Markers Associated with Prediction and Prognosis of Gastric Cancer

Gastric cancer (GC) is one of the most common cancers worldwide. Most patients are diagnosed at the progressive stage of the disease, and current anticancer drug advancements are still lacking. Therefore, it is crucial to find relevant biomarkers with the accurate prediction of prognoses and good predictive accuracy to select appropriate patients with GC. Recent advances in molecular profiling technologies, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, have enabled the approach of GC biology at multiple levels of omics interaction networks. Systemic biological analyses, such as computational inference of “big data” and advanced bioinformatic approaches, are emerging to identify the key molecular biomarkers of GC, which would benefit targeted therapies. This review summarizes the current status of how bioinformatics analysis contributes to biomarker discovery for prognosis and prediction of therapeutic efficacy in GC based on a search of the medical literature. We highlight emerging individual multi-omics datasets, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics, for validating putative markers. Finally, we discuss the current challenges and future perspectives to integrate multi-omics analysis for improving biomarker implementation. The practical integration of bioinformatics analysis and multi-omics datasets under complementary computational analysis is having a great impact on the search for predictive and prognostic biomarkers and may lead to an important revolution in treatment.

AggreProt: a web server for predicting and engineering aggregation prone regions in proteins.

Recombinant proteins play pivotal roles in numerous applications including industrial biocatalysts or therapeutics. Despite the recent progress in computational protein structure prediction, protein solubility and reduced aggregation propensity remain challenging attributes to design. Identification of aggregation-prone regions is essential for understanding misfolding diseases or designing efficient protein-based technologies, and as such has a great socio-economic impact. Here, we introduce AggreProt, a user-friendly webserver that automatically exploits an ensemble of deep neural networks to predict aggregation-prone regions (APRs) in protein sequences. Trained on experimentally evaluated hexapeptides, AggreProt compares to or outperforms state-of-the-art algorithms on two independent benchmark datasets. The server provides per-residue aggregation profiles along with information on solvent accessibility and transmembrane propensity within an intuitive interface with interactive sequence and structure viewers for comprehensive analysis. We demonstrate AggreProt efficacy in predicting differential aggregation behaviours in proteins on several use cases, which emphasize its potential for guiding protein engineering strategies towards decreased aggregation propensity and improved solubility. The webserver is freely available and accessible at https://loschmidt.chemi.muni.cz/aggreprot/.

Exploring the Bangladesh Liberation War: A Study of Tahmima Anam's Select Novels

This paper attempts to enunciate the Liberation War of Bangladesh, its history, and the occurrence of the events that led to the War as present Bangladesh is essentially the outcome of the sacrifice, loss, and bloodshed of millions of people involved in the war of 1971. It marked the creation of two nations separating East Pakistan from West Pakistan and forming a new nation called Bangladesh on 16th December 1971. The East Pakistanis wanted to preserve their culture, ethnicity, and identity as Bengali Muslims which was not possible in United Pakistan and this led to the Liberation War of Bangladesh. The 1971 war has a great impact on the creation of an independent identity for the Bangladeshi people. The stance for an independent national identity created the zeal to fight for their rights and self-recognition. The effects of war have always been engraved on the minds of the survivors as it is engulfed with human suffering, emotions, and violence. The paper will explore the Liberation War of Bangladesh, the struggle, pain, and hardship portrayed through the characters in Tahmima Anam’s select novels namely A Golden Age and The Good Muslim.

A Capillary-Force-Driven, Single-Cell Transfer Method for Studying Rare Cells

The characterization of individual cells within heterogeneous populations (e.g., rare tumor cells in healthy blood cells) has a great impact on biomedical research. To investigate the properties of these specific cells, such as genetic biomarkers and/or phenotypic characteristics, methods are often developed for isolating rare cells among a large number of background cells before studying their genetic makeup and others. Prior to using real-world samples, these methods are often evaluated and validated by spiking cells of interest (e.g., tumor cells) into a sample matrix (e.g., healthy blood) as model samples. However, spiking tumor cells at extremely low concentrations is challenging in a standard laboratory setting. People often circumvent the problem by diluting a solution of high-concentration cells, but the concentration becomes inaccurate after series dilution due to the fact that a cell suspension solution can be inhomogeneous, especially when the cell concentration is very low. We report on an alternative method for low-cost, accurate, and reproducible low-concentration cell spiking without the use of external pumping systems. By inducing a capillary force from sudden pressure drops, a small portion of the cellular membrane was aspirated into the reservoir tip, allowing for non-destructive single-cell transfer. We investigated the surface membrane tensions induced by cellular aspiration and studied a range of tip/tumor cell diameter combinations, ensuring that our method does not affect cell viability. In addition, we performed single-cell capture and transfer control experiments using human acute lymphoblastic leukemia cells (CCRF-CEM) to develop calibrated data for the general production of low-concentration samples. Finally, we performed affinity-based tumor cell isolation using this method to generate accurate concentrations ranging from 1 to 15 cells/mL.

COVID-19 and hospital activity: experience of the Nephrology Department of Ibn Sina Hospital-Rabat

The COVID-19 pandemic has led to a major health crisis, responsible for a very high morbidity in the world. This context represented an organizational challenge and required an adaptation of health services. The purpose of this study is to evaluate the activity of the Nephrology Department of Ibn Sina Hospital of Rabat during the period of confinement of the COVID-19 pandemic.Material and methods Retrospective study of hospitalization, dialysis and consultation activities in the nephrology, and dialysis and kidney transplantation department, during the period of confinement in Morocco from March 12 to June 16, 2020.Results We have identified, for the considered period of three months, 65 patients hospitalized in the nephrology department versus 218 patients during the 3 months preceding the start of confinement in Morocco, which corresponds to a decrease of 70%. The mean age of the patients was 50 ± 16 years with a male predominance. Kidney biopsy was performed in 14 patients. Lupus nephritis was found in 5 patients. Twelve patients received a bolus of methylprednisolone, 7 patients required intravenous cyclophosphamide, and only 1 patient was treated with rituximab. One-hundred twenty-nine patients underwent dialysis, and 554 patients benefited from telemedicine during this period.Conclusion Data collected in this study highlights that the global pandemic due to COVID-19 had a great impact on the activity of our department. The continuity of care for our patients has been ensured by the implementation of telemedicine and the reorganization of our hospital activity.

Marketing Strategy of the Coffee Industry under High Saturation of Globalized Brands-Take Luckin Coffee as an Example

With the arrival of the "Internet +" era, the marketing mode of coffee products is also undergoing constant changes, and the rise of the "new retail" sales model has brought great impact and challenges to the traditional marketing model. This paper will take the typical representative of this business model, Luckin Coffee, as an example, using qualitative research, STP theory, marketing theory, and the case study method to analyze. The article mainly discusses how to utilize and innovate the existing competitive advantages and business model of Luckin coffee, by analyzing and evaluating the strengths, weaknesses, threats, and challenges of Luckin coffee's pricing strategy, product strategy, and promotional strategy to realize precision marketing, introduce the relevant information and some marketing strategies of Starbucks, and borrow from Starbucks' strengths in product marketing, to propose solutions to the the current marketing state of Luckin Coffee: Customer-oriented, while focusing on product differentiation, and through effective "online + offline" publicity to achieve precision marketing and help the coffee industry diversify and develop sustainably under the high saturation of global coffee brands.

Medical care services interplay between individual and Medicaid managed care markets in expansion versus non‐expansion states

AbstractWe study enrollment, medical service utilization, and incurred expenses of individual comprehensive and Medicaid managed care plans in states with or without Medicaid expansion adopted at the Affordable Care Act (ACA) early stage 2014–2016. To make healthcare services more accessible, 27 states expanded Medicaid eligibility to cover nearly‐poor non‐elderly adults who have had incomes between 100% and 138% of federal poverty level in 2014. In non‐expansion states, early enrollees in this income cohort had to choose individual market plans rather than Medicaid. Early enrollees' enrollment choices and their health status have had a great impact on the individual market premiums and Medicaid spending. We examined health insurers' annual regulatory filings with the National Association of Insurance Commissioners for 2013–2016 and found that: First, individual comprehensive insurance enrollment grew much faster in states not expanding Medicaid eligibility. Second, after incorporating early enrollees, per member per month (PMPM) medical service utilization and expenses of individual comprehensive insurance grew much faster in non‐expansion states. Third, among major types of medical utilization and expense measures, PMPM hospital inpatient days and PMPM prescription drug expenses increased substantially since 2014. Finally, Medicaid beneficiaries generated more PMPM medical utilization and expenses in expansion states.

Effect of Strain Rate on Mechanical Deformation Behavior in CuZr Metallic Glass

Tensile tests were performed on Cu64Zr36 metallic glass at strain rates of 107/s, 108/s, and 109/s via classical molecular dynamics simulations to explore the underlying mechanism by which strain rate affects deformation behavior. It was found that strain rate has a great impact on the deformation behavior of metallic glass. The higher the strain rate is, the larger the yield strength. We also found that the strain rate changes the atomic structure evolution during deformation, but that the difference in the atomic structure evolution induced by different strain rates is not significant. However, the mechanical response under deformation conditions is found to be significantly different with the change in strain rate. The average von Mises strain of a system in the case of 107/s is much larger than that of 109/s. In contrast, more atoms tend to participate in deformation with increasing strain rate, indicating that the strain localization degree is more significant in cases of lower strain rates. Therefore, increasing the strain rate reduces the degree of deformation heterogeneity, leading to an increase in yield strength. Further analysis shows that the structural features of atomic clusters faded out during deformation as the strain rate increased, benefiting more homogeneous deformation behavior. Our findings provide more useful insights into the deformation mechanisms of metallic glass.

#3012 Great impact of the results of PREMs and PROMs in all stages of chronic kidney disease. Analysis of 281 patients

Abstract Background and Aims In recent years, there has been a growing interest in the use and relevance of Patient-Reported Outcomes Measures (PROMs) and Patient-Reported Experience Measures (PREMs). The main objective of the study is to analyze scores in quality of life, anxiety, depression, and functional capacity using tests that assess PREMs and PROMs in patients at different stages of chronic kidney disease (CKD). Method Multicenter, cross-sectional, observational, non-interventional study with 281 patients (84 on hemodialysis, 48 on peritoneal dialysis, 50 with kidney transplant, 50 with advanced CKD, and 49 patients with CKD stages 1-2). Two professionals conducted interviews for data collection from all patients. Collected data: For PROMs: PFS (Piper Fatigue Scale), HADS (Hospital Anxiety and Depression Scale), FACIT-F (Functional Assessment of Chronic Illness Therapy-Fatigue Scale), SF-36, VAS (Visual Analogue Scale). For PREMs - PACIC test (Patients' Assessment of Chronic Illness Care), in addition to other comorbidity indices and laboratory analyses. ANOVA statistical analysis was used for group comparison. Results Although patients showed significant differences in age and comorbidities, our analysis shows that the most PROMs do not discriminate between different stages of CKD. The PROMs that most discriminate between different stages of CKD are those related to the Piper Fatigue Scale test. PREMs, analyzed using the PACIC scale, do achieve said discrimination (Table 1). Conclusion The analysis of PROMs and PREMs show the significant impact that CKD has on health-related quality of life. Some PROMs can discriminate between different stages of CKD, but the most effective ones are PREMs, which are an indirect indicator of the quality of care received, contributing to patient involvement in decision-making and empowerment.

The Social Impact of Hearing Loss Associated with Clinical Practice Among University Students and Dental Professionals: Systematic Review

Objective: The objective of this study was to estimate the social impact of hearing loss associated with clinical practice on university students and dental professionals. Theoretical Framework: Hearing loss is a significant concern in various industries, but its association with clinical practice in dentistry has received less attention; even so, the use of high-speed equipment and tools would generate noise levels that could exceed the limits recommended and permitted by the WHO (World Health Organization). Method: The methodology adopted for this systematic review used the criteria of the PRISMA-SCR report, by means of which an extensive search was carried out without language limits and published from March 2019 to March 2024. Results and Discussion: Hearing pollution in university and non-university dental clinics is high due to the permanent contact with various acoustic sources of pollution; therefore, its prolonged use could cause damage in the short and long term. Research Implications: Hearing loss would not only impair the clinician's physical/clinical capabilities but would also have a great social impact on dental professionals and people around them; thus, hearing loss could lead to social anxiety and stigmatization, especially in settings where hearing is perceived as a crucial part of communication. Originality/Value: In this article, several basic recommendations for reducing hearing pollution in dental clinics worldwide are presented.

Legal Education in Pakistan: An Overview of Stakeholders’ Perception

Abstract Legal education plays a vital role in the country’s justice system. The graduates with good quality of law education have a great impact on the quality of the judiciary, Bar, and Bench. There is a general perception amongst the stakeholders comprising of that the present legal education in Pakistan does not satisfactorily match the needs of the country. Thus, it needs to be reviewed and reformed. In line with this, the objective of the current qualitative study is to analyze the opinions of stakeholders. The article ends with recommendations for improvement in legal education as advocated by the stakeholders.

Re-interpreting basic values underlying social security law in times of climate change and ecological crisis

Shaping solidarity, guaranteeing basic subsistence, maintaining income and employment activation can be seen as basic values underlying social security law in many European welfare states. This article argues that the meaning of these values or concepts is determined by legitimating discourses within which they are interpreted. While so far Rawls's theory of justice and related egalitarian liberal philosophies have had a great impact on these discourses, the ecological crisis has given rise to new discourses which are inspired by neo-republican theory and green republicanism. Instead of legitimising a capitalist economy based on economic growth, these discourses promote a post-productive society that seeks to realise human flourishing and meaningful lives. The aim of this article is to contribute to the emerging debate on social security reform by explaining how neo-republican theory and green republicanism can fill social security law's basic values or concepts with meaning that is more in line with current ecological concerns. In contrast to previous contributions that have sought to rethink labour and social security law (‘social law’) in a way that is more compatible with our ecological and climate crisis, this article builds on Poststructuralist Discourse Theory to develop its argument.

Temperature-Dependent Residual Stresses and Thermal Expansion Coefficient of VO2 Thin Films

This study aims to investigate the thermomechanical properties of vanadium dioxide (VO2) thin films. A VO2 thin film was simultaneously deposited on B270 and H-K9L glass substrates by electron-beam evaporation with ion-assisted deposition. Based on optical interferometric methods, the thermal–mechanical behavior of and thermal stresses in VO2 films can be determined. An improved Twyman–Green interferometer was used to measure the temperature-dependent residual stress variations of VO2 thin films at different temperatures. This study found that the substrate has a great impact on thermal stress, which is mainly caused by the mismatch in the coefficient of thermal expansion (CTE) of the film and the substrate. By using the dual-substrate method, thermal stresses in VO2 thin films from room temperature to 120 °C can be evaluated. The thermal expansion coefficient is 3.21 × 10−5 °C−1, and the biaxial modulus is 517 GPa.

Quantifying risks of lane-changing behavior in highways with vehicle trajectory data under different driving environments

Improper lane-changing behavior may have a great impact on the safety of the surrounding vehicles, and accurate risk assessment of lane-changing behavior can detect improper lane-changing behavior. Many existing risk assessment methods are based on the traditional minimum safe distance model as the theoretical foundation, not taking into account the effects of different weather and road conditions. Moreover, the initially calculated safe lane-changing distance through the model is generally the limit safety distance, which deviates to some extent from the initial distance maintained when the vehicle begins to change lanes during the actual driving process. The ratio of these two distances can reflect the degree of risk between the changing vehicle and its neighboring vehicles during lane-changing. For this reason, a lane-changing safety coefficient is defined and lane-changing risk assessment model based on the hyperbolic tangent function is constructed by combining the change characteristics of this coefficient. An environmental adjustment factor was introduced into the model to consider the influence of different driving weather and road conditions on the lane-changing risk assessment. Then, based on survey data from the survey questionnaire, the weights of the influencing factors were determined by using the hierarchical analysis method, and the environmental adjustment factor in the model was calibrated by using the fuzzy comprehensive assessment method. Finally, to verify the effectiveness of the model, the lane-changing trajectories of 373 vehicles were extracted from the HighD dataset. The risk assessment value of lane-changing was calculated by using the constructed model and was classified into high-risk, medium-risk and low-risk by using the K-means++ clustering algorithm. Various evaluation results were compared with the evaluation results from the expert evaluation method and the classical risk evaluation indexes, and the evaluation results are basically the same, which verifies the effectiveness of the lane-changing risk model established.

Determination of beam oscillating pattern for tailoring melt flow and microstructural characteristics of laser welded Ti–6Al–4V alloy

The trajectory of beam is highly correlated to the heat distribution and fluid flow within the melting pool in laser welding, which has a great impact on improving the joint microstructure. This study employs fluid simulation techniques to investigate the temperature distribution and flow behavior of Ti–6Al–4V alloy under three laser oscillation welding patterns including none oscillation, sinusoidal oscillation, and circular oscillation, and the optimal oscillating pattern was determined through an analysis of microstructure characteristics. Temperature field simulation results indicate that the oscillation of the beam is efficaciously utilized to diminish the concentrated heat distribution on the base material. Moreover, a manifest difference in energy density and the area of laser action is produced, which leads to variations in the location and depth of the distribution of keyholes. Under circular oscillation, the flow behavior is more pronounced, with peak flow velocity increasing by approximately 80 % compared to none oscillation and new vortices were created in the horizontal section at the end of an oscillation period. Furthermore, compared to none oscillation and sinusoidal oscillation, the lower cooling rate under circular oscillating pattern contributes to the formation of equiaxed grains. The fine equiaxed grains are easy to move and form an ordered lattice structure, which favors the transformation of low-angle grain boundaries and the increase in the strength of the crystal texture. Therefore, with oscillation frequency and amplitude set at 80 Hz and 0.8 mm, respectively, the use of circular oscillating pattern in laser welding results in an improvement in weld seam microstructure.

The Correlation Between Education and Income Inequality

This paper analyzes the dynamics of wealth and education inequality in the world. This topic is very useful for the current economic situation. Meanwhile, the economic circle has different views on this issue by searching different literature. Each paper comes up with a different result and a different conclusion based on a different way of calculating economic inequality, and most scholars are divided into two groups, those who think they are strongly related and those who think they are not deeply related. These papers use some special calculations to calculate economic inequality. After analyzing the experimental process and results, it was found this issue and came up with personal views. In opinion, education does have a great impact on the economic situation of the middle class, but for the richest group of people, education has little impact on them. However, this research result still has some defects, so researchers need to consult more pieces of literature and obtain more data to obtain a more accurate result, which would greatly improve the level of economic inequality and extreme poverty in the world.

Paracrinal regulation of neutrophil functions by coronaviral infection in iPSC-derived alveolar type II epithelial cells

Coronaviruses (CoVs) are enveloped single-stranded RNA viruses that predominantly attack the human respiratory system. In recent decades, several deadly human CoVs, including SARS-CoV, SARS-CoV-2, and MERS-CoV, have brought great impact on public health and economics. However, their high infectivity and the demand for high biosafety level facilities restrict the pathogenesis research of CoV infection. Exacerbated inflammatory cell infiltration is associated with poor prognosis in CoV-associated diseases. In this study, we used human CoV 229E (HCoV-229E), a CoV associated with relatively fewer biohazards, to investigate the pathogenesis of CoV infection and the regulation of neutrophil functions by CoV-infected lung cells. Induced pluripotent stem cell (iPSC)-derived alveolar epithelial type II cells (iAECIIs) exhibiting specific biomarkers and phenotypes were employed as an experimental model for CoV infection. After infection, the detection of dsRNA, S, and N proteins validated the infection of iAECIIs with HCoV-229E. The culture medium conditioned by the infected iAECIIs promoted the migration of neutrophils as well as their adhesion to the infected iAECIIs. Cytokine array revealed the elevated secretion of cytokines associated with chemotaxis and adhesion into the conditioned media from the infected iAECIIs. The importance of IL-8 secretion and ICAM-1 expression for neutrophil migration and adhesion, respectively, was demonstrated by using neutralizing antibodies. Moreover, next-generation sequencing analysis of the transcriptome revealed the upregulation of genes associated with cytokine signaling. To summarize, we established an in vitro model of CoV infection that can be applied for the study of the immune system perturbations during severe coronaviral disease.

CuO nanostructure-decorated InGaN nanorods for selective H2S gas detection.

Establishing a heterostructure is one of the adequate strategies for enhancing device performance and has been explored in sensing, and energy applications. In this study, we constructed a heterostructure through a two-step process involving hydrothermal synthesis of CuO nanostructures and subsequent spin coating on MBE-grown InGaN NRs. We found that the CuO content on the InGaN NRs has a great impact on carrier injection at the heterojunction and thus the H2S gas sensing performance. Popcorn CuO/InGaN NR shows excellent gas sensing performance towards different concentrations of H2S at room temperature. The highest response is up to 35.54% to a H2S concentration of 100 ppm. Even more significantly, this response is further enhanced significantly (123.70%) under 365 nm UV light. In contrast, this composite structure exhibits negligibly low responses to 100 ppm of NO2, H2, CO, and NH3. The heterostructure band model associated with a surface reaction model is manifested to elucidate the sensing mechanism.