Calcium alginate elastic capsules for microalgal cultivation.

Calcium alginate elastic capsules with a core-shell structure are versatile spherical solid beads that can be produced in large quantities using various techniques. This type of capsule is a promising platform for cell culture applications, owing to its mechanical elasticity and transparency. This paper reports the production of calcium alginate capsules with high consistency, and for the first time, demonstrates the feasibility of the capsules for microalgal cultivation. Cell growth analysis reveals that the vibrationally-shaken calcium alginate elastic capsule platform yielded a higher maximum cell number (4.86 × 108 cells per mL) during the cultivation period than the control solution platforms. Aquafeed and food supplements for humans are the targeted applications of this novel platform.

A novel multi-stage enrichment workflow and comprehensive characterization for HEK293F-derived extracellular vesicles.

Extracellular vesicles (EVs) are emerging as a promising drug delivery vehicle as they are biocompatible and capable of targeted delivery. However, clinical translation of EVs remains challenging due to the lack of standardized and scalable manufacturing protocols to consistently isolate small EVs (sEVs) with both high yield and high purity. The heterogenous nature of sEVs leading to unknown composition of biocargos causes further pushback due to safety concerns. In order to address these issues, we developed a robust quality-controlled multi-stage process to produce and isolate sEVs from human embryonic kidney HEK293F cells. We then compared different 2-step and 3-step workflows for eliminating protein impurities and cell-free nucleic acids to meet acceptable limits of regulatory authorities. Our results showed that sEV production was maximized when HEK293F cells were grown at high-density stationary phase in semi-continuous culture. The novel 3-step workflow combining tangential flow filtration, sucrose-cushion ultracentrifugation and bind-elute size-exclusion chromatography outperformed other methods in sEV purity while still preserved high yield and particle integrity. The purified HEK293F-derived sEVs were thoroughly characterized for identity including sub-population analysis, content profiling including proteomics and miRNA sequencing, and demonstrated excellent preclinical safety profile in both in-vitro and in-vivo testing. Our rigorous enrichment workflow and comprehensive characterization will help advance the development of EVs, particularly HEK293F-derived sEVs, to be safe and reliable drug carriers for therapeutic applications.

Enhancing catalytic activity of CuCoFe-layered double oxide towards peroxymonosulfate activation by coupling with biochar derived from durian peel for antibiotic degradation: The role of C=O in biochar and underlying mechanism of built-in electric field.

CuCoFe-LDO/BCD was successfully synthesized from CuCoFe-LDH and biochar derived from durian shell (BCD). Ciprofloxacin (CFX) degraded more than 95% mainly by O2•- and 1O2 in CuCoFe-LDO/BCD(2/1)/PMS system within 10 min with a rate constant of 0.255 min-1, which was 14.35 and 2.66 times higher than those in BCD/PMS and CuCoFe-LDO/PMS systems, respectively. The catalytic system exhibited good performance over a wide pH range (3-9) and high degradation efficiency of other antibiotics. Built-in electric field (BIEF) driven by large difference in the work function/Fermi level ratio between CuCoFe-LDO and BCD accelerated continuous electron transfer from CuCoFe-LDO to BCD to result in two different microenvironments with opposite charges at the interface, which enhanced PMS adsorption and activation via different directions. As a non-radical, 1O2 was mainly generated via PMS activation by C=O in BCD. The presence of C=O in BCD resulted in an increase in atomic charge of C in C=O and redistributed the charge density of other C atoms. As a result, strong adsorption of PMS at C atom in C=O and other C with a high positive charge was favorable for 1O2 generation, whereas an enhanced adsorption of PMS at negatively charged C accounted for the generation of •OH and SO4•-. After adsorption, electrons in C of BCD became deficient and were fulfilled with those transferred from CuCoFe-LDO driven by BIEF, which ensured the high catalytic activity of CuCoFe-LDO/BCD. O2•-, on the other hand, was generated via several pathways that involved in the transformation of •OH and SO4•- originated from PMS activation by the transition of metal species in CuCoFe-LDO and negatively charged C in BCD. This study proposed a new idea of fabricating a low-cost metal-LDH and biomass-derived catalyst with a strong synergistic effect induced by BIEF for enhancing PMS activation and antibiotic degradation.

Toward confident prostate cancer detection using ultrasound: a multi-center study.

PURPOSE: Deep learning-based analysis of micro-ultrasound images to detect cancerous lesions is a promising tool for improving prostate cancer (PCa) diagnosis. An ideal model should confidently identify cancer while responding with appropriate uncertainty when presented with out-of-distribution inputs that arise during deployment due to imaging artifacts and the biological heterogeneity of patients and prostatic tissue. METHODS: Using micro-ultrasound data from 693 patients across 5 clinical centers who underwent micro-ultrasound guided prostate biopsy, we train and evaluate convolutional neural network models for PCa detection. To improve robustness to out-of-distribution inputs, we employ and comprehensively benchmark several state-of-the-art uncertainty estimation methods. RESULTS: PCa detection models achieve performance scores up to 76 % average AUROC with a 10-fold cross validation setup. Models with uncertainty estimation obtain expected calibration error scores as low as 2 % , indicating that confident predictions are very likely to be correct. Visualizations of the model output demonstrate that the model correctly identifies healthy versus malignant tissue. CONCLUSION: Deep learning models have been developed to confidently detect PCa lesions from micro-ultrasound. The performance of these models, determined from a large and diverse dataset, is competitive with visual analysis of magnetic resonance imaging, the clinical benchmark to identify PCa lesions for targeted biopsy. Deep learning with micro-ultrasound should be further studied as an avenue for targeted prostate biopsy.

Current and emerging nanotechnology for sustainable development of agriculture: Implementation design strategy and application.

Recently, agriculture systems have faced numerous challenges involving sustainable nutrient use efficiency and feeding, environmental pollution especially heavy metals (HMs), infection of harmful microorganisms, and maintenance of crop production quality during postharvesting and packaging. Nanotechnology and nanomaterials have emerged as powerful tools in agriculture applications that provide alternatives or support traditional methods. This review aims to address and highlight the current overarching issue and various implementation strategies of nanotechnology for sustainable agriculture development. In particular, the current progress of different nano-fertilizers (NFs) systems was analyzed to show their advances in enhancing the uptake and translocations in plants and improving nutrient bioavailability in soil. Also, the design strategy and application of nanotechnology for rapid detection of HMs and pathogenic diseases in plant crops were emphasized. The engineered nanomaterials have great potential for biosensors with high sensitivity and selectivity, high signal throughput, and reproducibility through various detection approaches such as Raman, colorimetric, biological, chemical, and electrical sensors. We obtain that the development of microfluidic and lab-on-a-chip (LoC) technologies offers the opportunity to create on-site portable and smart biodevices and chips for real-time monitoring of plant diseases. The last part of this work is a brief introduction to trends in nanotechnology for harvesting and packaging to provide insights into the overall applications of nanotechnology for crop production quality. This review provides the current advent of nanotechnology in agriculture, which is essential for further studies examining novel applications for sustainable agriculture.

LensePro: label noise-tolerant prototype-based network for improving cancer detection in prostate ultrasound with limited annotations.

PURPOSE: The standard of care for prostate cancer (PCa) diagnosis is the histopathological analysis of tissue samples obtained via transrectal ultrasound (TRUS) guided biopsy. Models built with deep neural networks (DNNs) hold the potential for direct PCa detection from TRUS, which allows targeted biopsy and subsequently enhances outcomes. Yet, there are ongoing challenges with training robust models, stemming from issues such as noisy labels, out-of-distribution (OOD) data, and limited labeled data. METHODS: This study presents LensePro, a unified method that not only excels in label efficiency but also demonstrates robustness against label noise and OOD data. LensePro comprises two key stages: first, self-supervised learning to extract high-quality feature representations from abundant unlabeled TRUS data and, second, label noise-tolerant prototype-based learning to classify the extracted features. RESULTS: Using data from 124 patients who underwent systematic prostate biopsy, LensePro achieves an AUROC, sensitivity, and specificity of 77.9%, 85.9%, and 57.5%, respectively, for detecting PCa in ultrasound. Our model shows it is effective for detecting OOD data in test time, critical for clinical deployment. Ablation studies demonstrate that each component of our method improves PCa detection by addressing one of the three challenges, reinforcing the benefits of a unified approach. CONCLUSION: Through comprehensive experiments, LensePro demonstrates its state-of-the-art performance for TRUS-based PCa detection. Although further research is necessary to confirm its clinical applicability, LensePro marks a notable advancement in enhancing automated computer-aided systems for detecting prostate cancer in ultrasound.

Agarose-based 3D culture improved the developmental competence of oocyte-granulosa complex isolated from porcine preantral follicle.

Various models have been established to culture whole follicles of the Preantral stage; however, the process remains inefficient and is an ongoing challenge formation. It is reported that oocyte-cumulus-granulosa complexes (OCGCs) isolated from Early Antral follicles (EAFs) undergo in vitro growth (IVG) and acquire meiotic competence in some animals. However, IVG for the oocyte-granulosa complexes (OGCs) from Preantral Follicles (PAFs) has not been firmly established. The present study indicated that the use of a modified medium with Ascorbic Acid (50 µM) facilitated granulosa cell proliferation, promoted cumulus cell differentiations, and increased antrum formation for the OGCs isolated from PAFs (0.3-0.4 mm). However, the two-dimensional 96-well plate system (2D) experienced smaller size follicles and could not prolong more than 10 days of IVG. Another method is to use an Agarose matrix 3D system to provide a soft, non-adhesive base that supports the IVG of OGCs isolated from PAFs and promotes cell proliferation, antrum formation, and maintenance for 14 days. OGCs that were grown using this method retained their spherical morphology, which in turn helped to attain healthy granulosa cells and maintain their connection with oocytes, in addition, these oocytes significantly increased diameter and lipid content, indicating developmental competence. Our result indicated that the OGCs from PAFs after IVG undergo a change in chromatin morphology and expression of acetylation of histone H3 at lysine 9 (Ac-H3-K9) and methylation of histone H3 at lysine 4 (Me-H3-K4), similar to the in vivo oocytes isolated from the ovary. Likewise, IVG oocytes cultured for maturation showed full cumulus expansion and reached mature oocytes. Furthermore, after in vitro maturation, IVG oocytes underwent the first cleavage following parthenogenetic activation. In conclusion, while most studies used whole follicles from the Preantral stage for IVG, our research finding was the first to reveal that oocytes isolated from the final stage of PAFs can migrate out of the follicle and undergo IVG under suitable conditions.

Classification and application of metal-based nanoantioxidants in medicine and healthcare.

Antioxidants play an important role in the prevention of oxidative stress and have been widely used in medicine and healthcare. However, natural antioxidants have several limitations such as low stability, difficult long-term storage, and high cost of large-scale production. Along with significant advances in nanotechnology, nanomaterials have emerged as a promising solution to improve the limitations of natural antioxidants because of their high stability, easy storage, time effectiveness, and low cost. Among various types of nanomaterials exhibiting antioxidant activity, metal-based nanoantioxidants show excellent reactivity because of the presence of an unpaired electron in their atomic structure. In this review, we summarize some novel metal-based nanoantioxidants and classify them into two main categories, namely chain-breaking and preventive antioxidant nanomaterials. In addition, the applications of antioxidant nanomaterials in medicine and healthcare are also discussed. This review provides a deeper understanding of the mechanisms of metal-based nanoantioxidants and a guideline for using these nanomaterials in medicine and healthcare.

Effective activation of peroxymonosulfate by CoCr-LDH for removing organic contaminants in water: from lab-scale to practical applications.

In this study, CoCr layered double hydroxide material (CoCr-LDH) was prepared and used as an effective catalyst for peroxymonosulfate (PMS) activation to degrade organics in water. The prepared CoCr-LDH material had a crystalline structure and relatively porous structure, as determined by various surface analyses. In Rhodamine B (RhB) removal, the most outstanding PMS activation ability belongs to the material with a Co:Cr molar ratio of 2:1. The removal of RhB follows pseudo-first-order kinetics (R2 > 0.99) with an activation energy of 38.23 kJ/mol and efficiency of 98% after 7 min of treatment, and the total organic carbon of the solution reduced 47.2% after 10 min. The activation and oxidation mechanisms were proposed and the RhB degradation pathways were suggested with the key contribution of O2•- and 1O2. Notably, CoCr-LDH can activate PMS over a wide pH range of 4 - 9, and apply to a wide range of organic pollutants and aqueous environments. The material has high stability and good recovery, which can be reused for 5 cycles with a stable efficiency of above 88%, suggesting a high potential for practical recalcitrant water treatment via PMS activation by heterogeneous catalysts.

Pulmonary artery penetration due to fish bone ingestion: A rare case report.

Accidental fish bone ingestion is a common manifestation at emergency departments. In most cases, ingested foreign bodies usually pass uneventfully through the gastrointestinal tract and complications only present in less than 5% of all patients. In this report, we present the first documented case of pulmonary artery injury due to a fish bone in a 63-year-old male patient hospitalized with hemoptysis after accidentally swallowing a fish bone 30 days ago. This patient subsequently had surgery and endoscopy to safely remove the foreign body and then recovered well on a follow-up examination. For cases of fish bone ingestion, contrast-enhanced chest computed tomography is one of the most essential tools to assess vascular problems and associated mediastinal infections-risk factors for life-threatening and long-term recurrent inflammation. Reconstructing planes along the foreign body axis and changing windows when analyzing CT scans is necessary to avoid missing lesions and dilemmas.

Isothermal amplification-based microfluidic devices for detecting foodborne pathogens: a review.

The gold standard for nucleic acid amplification-based diagnosis is the polymerase chain reaction (PCR). The PCR recognizes the targets such as foodborne pathogens by amplifying their specific genes. The integration of nucleic acid amplification-based assays on microfluidic platforms represents a highly promising solution for convenient, cheap, and effective control of foodborne pathogens. However, the application of the PCR is limited to on-site detection because the method requires sophisticated equipment for temperature control, which makes it complicated for microfluidic integration. Alternatively, isothermal amplification methods are promising tools for integrating microfluidic platforms for on-site detection of foodborne pathogens. This review summarized advances in isothermal amplification-based microfluidic devices for detecting foodborne pathogens. Different nucleic acid extraction approaches and the integration of these approaches in microfluidic platforms were first reviewed. Microfluidic platforms integrated with three common isothermal amplification methods including loop-mediated isothermal amplification, recombinase polymerase amplification, and recombinase-aided amplification were then described and discussed.

A study on a broadband photodetector based on hybrid 2D copper oxide/reduced graphene oxide.

These days, photodetectors are a crucial part of optoelectronic devices, ranging from environmental monitoring to international communication systems. Therefore, fabricating these devices at a low cost but obtaining high sensitivity in a wide range of wavelengths is of great interest. This report introduces a simple solution-processed hybrid 2D structure of CuO and rGO for broadband photodetector applications. Particularly, 2D CuO acts as the active material, absorbing light to generate electron-hole pairs, while 2D rGO plays the role of a transport layer, driving charge carriers between two electrodes. Our device exhibits remarkable sensitivity to a wide wavelength range from 395 nm to 945 nm (vis-NIR region). Interestingly, our devices' responsivity and photoconductive gain were calculated (under 395 nm wavelength excitation) to be up to 8 mA W-1 and 28 fold, respectively, which are comparable values with previous publications. Our hybrid 2D structure between rGO and CuO enables a potential approach for developing low-cost but high-performance optoelectronic devices, especially photodetectors, in the future.

Enhanced Charge Carrier Dynamics on Sb2 Se3 Photocathodes for Efficient Photoelectrochemical Nitrate Reduction to Ammonia.

Ammonia (NH3 ) is recognized as a transportable carrier for renewable energy fuels. Photoelectrochemical nitrate reduction reaction (PEC NO3 RR) offers a sustainable solution for nitrate-rich wastewater treatment by directly converting solar energy to ammonia. In this study, we demonstrate the highly selective PEC ammonia production from NO3 RR by constructing a CoCu/TiO2 /Sb2 Se3 photocathode. The constructed CoCu/TiO2 /Sb2 Se3 photocathode achieves an ammonia Faraday efficiency (FE) of 88.01 % at -0.2 VRHE and an ammonia yield as high as 15.91 µmol h-1 cm-2 at -0.3 VRHE with an excellent onset potential of 0.43 VRHE . Dynamics experiments and theoretical calculations have demonstrated that the CoCu/TiO2 /Sb2 Se3 photocathode possesses high light absorption capacity, excellent carrier transfer capability, and high charge separation and transfer efficiencies. The photocathode can effectively adsorb the reactant NO3 - and intermediate, and the CoCu co-catalyst increases the maximum Gibbs free energy difference between NO3 RR and HER. Meanwhile, the Co species enhances the spin density of Cu, and increases the density of states near the Fermi level in pdos, which results in a high PEC NO3 RR activity on CoCu/TiO2 /Sb2 Se3 . This work provides a new avenue for the feasibility of efficient PEC ammonia synthesis from nitrate-rich wastewater.

Epilepsy self-management mobile health application: A needs assessment in people with epilepsy and caregivers in Viet Nam.

OBJECTIVES: This study aimed to determine (1) the needsof Vietnamese people with epilepsy (PWE) and their caregivers for self-management mobile health applications and (2) the self-management features expected to be included in an application. METHODS: The survey consisted of an anonymous self-administered questionnaire that was distributed to PWE and caregivers from the age of 18 in Vietnam through online platforms and onsite at Nguyen Tri Phuong Hospital and University Medical Center, Ho Chi Minh City, from February 2022 to May 2022. The questionnaire assessed the participants' attitudes toward epilepsy self-management mobile applications, their willingness to use applications, and their expectations of the contents of an application. RESULTS: Responses from 103 participants were submitted. Eighty-one participants (78.6%) reported using a smartphone, but only 50.6% of those claimed to know about self-management applications. Most respondents (70.9%) thought the applications would be useful for disease self-management, and 68.9% were willing to use epilepsy self-management applications. In addition, the most expected features to be included in self-management applications were epilepsy information, seizure first aid, connecting with medical professionals, and a seizure diary. CONCLUSION: Most Vietnamese PWE and caregivers had a willingness to use epilepsy self-management applications.The expected features are related to all aspects of self-management, including information, seizure, medication, and safety management.

Direct Tumor Irradiation Potentiates Adoptive NK Cell Targeting Against Parental and Stemlike Cancer in Human Liver Cancer Models.

PURPOSE: Radiation therapy (RT) has been shown to effectively induce the expression of intercellular adhesion molecule-1 (ICAM-1), which is recognized by lymphocyte function-associated antigen 1 (LFA-1) expressed on natural killer (NK) cells. However, the potential synergistic antitumor immune response of tumor irradiation and administered NK cells has not been explored in intractable human liver cancers. Furthermore, NK cell targeting against both parental and cancer stemness has never been investigated. METHODS AND MATERIALS: Highly activated ex vivo NK cells were administered into the human liver tumor-bearing mice. Tumor direct RT was optimized according to tumor bearing site. HepG2 and Hep3B ICAM-1 knockout cells were generated using CRISPR/CAS9. Stemness tumor spheres were generated. NK cell cytolysis against parental and tumor sphere was evaluated using flow cytometry and real-time cytotoxicity assay. RESULTS: A combination of adoptive NK cell therapy with RT significantly improved therapeutic efficacy over monotherapies against subcutaneous, orthotopic, and metastatic human liver tumor models. Direct tumor irradiation potentiated NK cell recognition and conjugation against liver cancer through the LFA-1/ICAM-1 axis. Suppression of immune synapse formation on NK cells using high-affinity LFA-1 inhibitors or ICAM-1 knockout liver cancer induced "outside-in" signal blocking in NK cells, resulting in failure to eliminate liver tumor despite the combination therapy. NK cells effectively recognized and targeted triple-high epithelial cell adhesion molecule+CD133+CD24+ liver cancer expressing upregulated ICAM-1 in the irradiated tumor microenvironment, which led to prevention of the initiation of metastasis, improving survival in a metastatic model. In addition, the LFA-1/ICAM-1 axis interruption between NK cells and stemness liver tumor spheres significantly diminished NK cell cytolysis. Consistent with our preclinical data, the LFA-1/ICAM-1 axis correlated with survival outcomes in patients with metastatic cancer from the The Cancer Genome Atlas databases. CONCLUSIONS: NK cells in combination with tumor irradiation can provide synergistic therapeutic effects for NK cell recognition and elimination against both parental and stemlike liver cancer through LFA-1/ICAM-1.

The Impact of LiDAR Configuration on Goal-Based Navigation within a Deep Reinforcement Learning Framework.

Over the years, deep reinforcement learning (DRL) has shown great potential in mapless autonomous robot navigation and path planning. These DRL methods rely on robots equipped with different light detection and range (LiDAR) sensors with a wide field of view (FOV) configuration to perceive their environment. These types of LiDAR sensors are expensive and are not suitable for small-scale applications. In this paper, we address the performance effect of the LiDAR sensor configuration in DRL models. Our focus is on avoiding static obstacles ahead. We propose a novel approach that determines an initial FOV by calculating an angle of view using the sensor's width and the minimum safe distance required between the robot and the obstacle. The beams returned within the FOV, the robot's velocities, the robot's orientation to the goal point, and the distance to the goal point are used as the input state to generate new velocity values as the output action of the DRL. The cost function of collision avoidance and path planning is defined as the reward of the DRL model. To verify the performance of the proposed method, we adjusted the proposed FOV by ±10° giving a narrower and wider FOV. These new FOVs are trained to obtain collision avoidance and path planning DRL models to validate the proposed method. Our experimental setup shows that the LiDAR configuration with the computed angle of view as its FOV performs best with a success rate of 98% and a lower time complexity of 0.25 m/s. Additionally, using a Husky Robot, we demonstrate the model's good performance and applicability in the real world.

Comorbidity Burden and Treatment Patterns of Psoriasis in Vietnam: Real-World Data from the EXPAND Study.

INTRODUCTION: Psoriasis is a multi-faceted, immune-mediated inflammatory disease associated with a wide range of comorbidities. Real-world data on treatment patterns, comorbidities, and economic burden in patients with psoriasis are needed for comprehensive patient care in Vietnam. METHODS: A retrospective chart review study was conducted using secondary data extracted from patients' medical records of two hospitals in Vietnam, with the aim of identifying adult patients with a confirmed diagnosis of psoriasis. The index date was defined as the date of first diagnosis between 1 January 2020 and 31 October 2021. Sociodemographic factors, disease characteristics, comorbidities, medication usage, drug survival, and medication costs were analyzed. RESULTS: A total of 661 patients were identified (mean ± standard deviation [SD] age 43.5 ± 14.8 years). The most prevalent comorbidity was dyslipidemia (49.6% of patients), followed by hypertension (23.4%), and psoriatic arthritis (10.4%). In total, 44% of patients received biologic therapies. Overall, 66.7% and 54.3% of patients receiving biologic and non-biologic therapies, respectively, had ≥ 1 comorbidity. Only 23.2% of patients with psoriasis-related comorbidities stopped therapy with biologics. Biologics had a longer retention time (17.0 months) than non-biologics (6.0 months) in patients with comorbidities. Patients with comorbidities had significantly higher total annual healthcare costs than those without comorbidities (in US dollars: USD901 vs. USD304; p < 0.001), mainly due to the relatively higher costs associated with the use of biologics. CONCLUSION: Patients with psoriasis in Vietnam experience a high disease and economic burden due to comorbidities. Evidence from this real-world study supports the need for routine monitoring of and an appropriate treatment course for psoriasis-related comorbidities.

Skeletal muscle TFEB signaling promotes central nervous system function and reduces neuroinflammation during aging and neurodegenerative disease.

Skeletal muscle has recently arisen as a regulator of central nervous system (CNS) function and aging, secreting bioactive molecules known as myokines with metabolism-modifying functions in targeted tissues, including the CNS. Here, we report the generation of a transgenic mouse with enhanced skeletal muscle lysosomal and mitochondrial function via targeted overexpression of transcription factor E-B (TFEB). We discovered that the resulting geroprotective effects in skeletal muscle reduce neuroinflammation and the accumulation of tau-associated pathological hallmarks in a mouse model of tauopathy. Muscle-specific TFEB overexpression significantly ameliorates proteotoxicity, reduces neuroinflammation, and promotes transcriptional remodeling of the aged CNS, preserving cognition and memory in aged mice. Our results implicate the maintenance of skeletal muscle function throughout aging in direct regulation of CNS health and disease and suggest that skeletal muscle originating factors may act as therapeutic targets against age-associated neurodegenerative disorders.

A visible-light photodetector based on heterojunctions between CuO nanoparticles and ZnO nanorods.

Optoelectronic devices have various applications in medical equipment, sensors, and communication systems. Photodetectors, which convert light into electrical signals, have gained much attention from many research teams. This study describes a low-cost photodetector based on CuO nanoparticles and ZnO nanorods operating in a wide range of light wavelengths (395, 464, 532, and 640 nm). Particularly, under 395 nm excitation, the heterostructure device exhibits high responsivity, photoconductive gain, detectivity, and sensitivity with maximum values of 1.38 A·W-1, 4.33, 2.58 × 1011 Jones, and 1934.5% at a bias of 2 V, respectively. The sensing mechanism of the p-n heterojunction of CuO/ZnO is also explored. Overall, this study indicates that the heterostructure of CuO nanoparticles and ZnO nanorods obtained via a simple and cost-effective synthesis process has great potential for optoelectronic applications.

Bayesian merging of numerical modeling and remote sensing for saltwater intrusion quantification in the Vietnamese Mekong Delta.

Saltwater intrusion has become one of the most concerning issues in the Vietnamese Mekong Delta (VMD) due to its increasing impacts on agriculture and food security of Vietnam. Reliable estimation of salinity plays a crucial role to mitigate the impacts of saltwater intrusion. This study developed a hybrid technique that merges satellite imagery with numerical simulations to improve the estimation of salinity in the VMD. The salinity derived from Landsat images and by numerical simulations was fused using the Bayesian inference technique. The results indicate that our technique significantly reduces the uncertainties and improves the accuracy of salinity estimates. The Nash-Sutcliffe coefficient is 0.74, which is much higher than that of numerical simulation (0.63) and Landsat estimation (0.6). The correlation coefficient between the ensemble and measured salinity is relatively high (0.88). The variance of the ensemble salinity errors (5.0 ppt2) is lower than that of Landsat estimation (10.4 ppt2) and numerical simulations (9.6 ppt2). The proposed approach shows a great potential to combine multiple data sources of a variable of interest to improve its accuracy and reliability wherever these data are available.