Comparison of Janani Suraksha Yojana (JSY) and augmented Arogya Laxmi scheme (ALS) in improving maternal and child health outcomes in urban settlements of Hyderabad, South India.

BACKGROUND: India accounts for the largest number of global neonatal deaths with around 20 per 1000 live births. To improve the utilization of government services for institutional deliveries, Augmented Arogya Laxmi Scheme (ALS) was launched in Telangana state of southern India. This study assessed the effectiveness of the Janani Suraksha Yojana (JSY), which combines cash assistance with delivery and post-delivery care, in comparison to ALS in improving the outcomes related to antenatal, natal, and postnatal care in urban settlements of Hyderabad, Telangana, southern India. METHODS: This was a two-year cross-sectional study conducted in 14 urban settlements of Hyderabad city from September 2017- August 2019. All mothers delivered during the 18 months preceding the survey were enrolled after a written informed consent. Field investigators collected data on variables related to socio-demographic characteristics, awareness, and utilization of JSY and ALS programs. Variables related to antenatal history, antenatal care, complications during birth, delivery outcomes, newborn care, and postnatal care till 28 days were assessed. We used multivariable logistic regression model to examine the association between the different maternal, child, and socio-demographic characteristics of the two study groups. RESULTS: A total of 926 mothers were beneficiaries of Janani Suraksha Yojana (JSY) program while 933 mothers were beneficiaries of augmented Arogya Laxmi Scheme (ALS). Mothers in ALS group (AOR 1.71; 95% CI 1.21-2.43) were at increased odds of having more than eight antenatal care (ANC) visits compared to the mothers availing JSY. Mothers in ALS group were at decreased odds of having complications like severe pain in the abdomen (AOR 0.43; 95% CI 0.22-0.86), swelling of legs or feet (AOR 0.59; 95% CI 0.44-0.80) compared to mothers in JSY group. Children of mothers in the ALS group had increased odds of receiving breastfeeding within 30 minutes of birth (AOR 1.46; 95% CI 1.13-1.88) compared to children of mothers in JSY group. CONCLUSIONS: The newly launched augmented ALS led to the increased utilization of the government health facilities and improved the maternal and child health outcomes.

Efficient synthesis of 3D ZnO nanostructures on ITO surfaces for enhanced photoelectrochemical water splitting.

New photoactive materials with uniform and well-defined morphologies were developed for efficient and sustainable photoelectrochemical (PEC) water splitting and hydrogen production. The investigation is focused on hydrothermal deposition of zinc oxide (ZnO) onto indium tin oxide (ITO) conductive surfaces and optimization of hydrothermal temperature for growing uniform sized 3D ZnO morphologies. Fine-tuning of hydrothermal temperature enhanced the scalability, efficiency, and performance of ZnO-decorated ITO electrodes used in PEC water splitting. Under UV light irradiation and using eco-friendly low-cost hydrothermal process in the presence of stable ZnO offered uniform 3D ZnO, which exhibited a high photocurrent of 0.6 mA/cm2 having stability up to 5 h under light-on and light-off conditions. The impact of hydrothermal temperature on the morphological properties of the deposited ZnO and its subsequent performance in PEC water splitting was investigated. The work contributes to advancement of scalable and efficient fabrication technique for developing energy converting photoactive materials.

The collision-induced dissociation mechanism of sodiated Hex-HexNAc disaccharides.

Determining carbohydrate structures, such as their compositions, linkage positions, and in particular the anomers and stereoisomers, is a great challenge. Isomers of different anomers or stereoisomers have the same sequences of chemical bonds, but have different orientations of some chemical bonds which are difficult to be distinguished by mass spectrometry. Collision-induced dissociation (CID) tandem mass spectroscopy (MS/MS) is a widely used technique for characterizing carbohydrate structures. Understanding the carbohydrate dissociation mechanism is important for obtaining the structural information from MS/MS. In this work, we studied the CID mechanism of galactose-N-acetylgalactosamine (Gal-GalNAc) and glucose-N-acetylglucosamine (Glc-GlcNAc) disaccharides with 1→3 and 1→4 linkages. For Gal-GalNAc disaccharides, the CID mass spectra of sodium ion adducts show significant difference between the α- and ß-anomers of GalNAc at the reducing end, while no difference in the CID mass spectra between two anomers of Glc-GlcNAc disaccharides was found. Quantum chemistry calculations show that for Gal-GalNAc disaccharides, the difference of the dissociation barriers between dehydration and glycosidic bond cleavage is significantly small in the ß-anomer compared to that in the α-anomer; while these differences are similar between the α- and ß-anomers of Glc-GlcNAc disaccharides. These differences can be attributed to the different orientations of hydroxyl and N-acetyl groups located at GalNAc and GlcNAc. The calculation results are consistent with the CID spectra of isotope labelled disaccharides. Our study provides an insight into the CID of 1→3 and 1→4 linked Gal-GalNAc and Glc-GlcNAc disaccharides. This information is useful for determining the anomeric configurations of GalNAc in oligosaccharides.

WITHDRAWN: Heavy metal ions and dyes removal from aqueous solution using Aloevera-based biosorbent: A systematic review.

This article has been withdrawn: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy). This article has been withdrawn at the request of the authors, editor and publisher. The publisher regrets that an error occurred which led to the premature publication of this paper. The publisher apologizes to the readers for this unfortunate erro

Sharp-edged pencil type ZnO flowers and BiOI flakes combined with carbon nanofibers as heterostructured hybrid photocatalysts for the removal of hazardous pollutants from contaminated water.

The growth of advanced micro-and nanostructures with metal oxides has consistently generated extraordinary interest in energy and environmental applications. Cutting-edge nanostructures exhibit superior reactive sites and surface areas, thus improving the performance in crucial domains. In this study, sharp-edged pencil-type ZnO flowers and BiOI flakes as pristine materials, and their composition with carbon nanofibers (CNFs) (ZnO-BiOI@CNFs) as a hetero hybrid catalyst as well as binary compositions such as ZnO-BiOI, ZnO@CNFs, and BiOI@CNFs catalysts were fabricated using a simple and convenient hydrothermal synthesis process. The composition of newly produced innovative nanostructures was examined for azo dye degradation under solar simulator exposure. Dye degradation of ∼95% was achieved by the hybrid catalyst (ZnO-BiOI@CNFs) during 120 min of irradiation, which was ∼1.8 and 2.1-times higher than pristine ZnO and BiOI nanostructures, respectively. The improved hybrid catalysts were able to degrade methyl orange (MO) and rhodamine B (RhB) dyes. Importantly, mixed dyes RhB, MO, and azo dye demonstrated 47% dye degradation using a hybrid catalyst. These mixed dye-scalable hybrid catalyst performances offer additional insights into commercialization/industrialization. The outstanding performance of the hybrid catalyst is attributed to the unidirectional electron flow with pencil-like ZnO, a catalyst with a larger absorption zone, high surface area, and reactive sites, particularly ZnO and BiOI nanostructures, and decreased recombination rate with a heterojunction interface. In addition, CNFs can operate as electron traps and sinks, providing very quick redox reactions. To produce the sophisticated nanostructures with homogeneous morphologies, this work presents new insights into energy and environmental applications.

Novel rhombus Co3O4-nanocapsule CuO heterohybrids for efficient photocatalytic water splitting and electrochemical energy storage applications.

The most appealing and prominent approach for improving energy storage and conversion performance is the development of heterojunction interfaces with efficient and unique metal oxide nanostructures. Rhombus Co3O4, nanocapsule CuO, and their heterojunction composites were synthesized using a single-step hydrothermal process. The resulting heterojunction Co3O4-CuO nanocomposite outperformed the pristine Co3O4 and CuO nanostructures for the electrochemical supercapacitor and water splitting performances. The composite showed 2.4 and 1.3 times higher specific capacitance than the associated pristine CuO and Co3O4 nanostructures, while its capacitance was 395 F g-1 at a current density of 0.5 A g-1. In addition, long-term GCD results with more than 90% stability and significant capacity retention at higher scan rates revealed the unaffected structures interfaced during the electrochemical reactions. The composite photoelectrode demonstrated more than 20% of photocurrent response with light illumination than the dark condition in water splitting. Co3O4-CuO heterostructured composite electrode showed a 0.16 mA/cm2 photocurrent density, which is 3.2 and 1.7 times higher than the pristine CuO and Co3O4 electrodes, respectively. This performance was attributed to its unique structural composition, high reactive sites, strong ion diffusion, and fast electron accessibility. Electron microscopic and spectroscopic techniques confirmed the properties of the electrodes as well as their morphological properties. Overall, the heterojunction interface with novel rhombus and capsule structured architectures showed good electrochemical performance, suggesting their energy storage and conversion applications.

A Case of Laurence Moon Bardet Biedl Syndrome.

INTRODUCTION: Laurence-Moon-Bardet-Biedl syndrome (LMBBS) is a rare autosomal recessive disorder characterised by polydactyly, retinitis pigmentosa, obesity, hypogonadism and mental retardation. MATERIALS: A 20-year old male, who is morbidly obese [BMI = 41] with history of intellectual delay, speech impairment and progressive vision loss. Presented to Saveetha medical college, Chennai with chief complaints of breathlessness, oliguria, abdominal distension. On examination patient had short stature, obese, crowded teeth present, had polydactyly of feet, micro penis and retinitis pigmentosa, nystagmus. He had pedal edema and facial puffiness. Laboratory investigations revealed Hb-6.9, creatinine-12, urea 217, potassium-7.7, bicarbonate-8.3. Echo showed eccentric Left ventricular hypertrophy. CT abdomen revealed hepatomegaly, right contracted kidney with renal pelvic lipomatosis, left enlarged kidney with hydroureteronephrosis grade 4. RESULT: He presented with all the primary Pentad features of LMBBS along with CKD stage 5. He also had secondary features like speech delay, developmental delay, dental crowding, high arched palate, left ventricular hypertrophy. CONCLUSION: LMBBS is a disorder with an identified Pentad of symptoms which are obesity, hypogonadism, intellectual impairment, polydactyly and retinitis pigmentosa. Renal function loss is most common cause of mortality in these patients. Because of seemingly unrelated symptoms the disorder remains largely under diagnosed. Genetic counselling of effected families raise awareness about need to get the other family members assessed for renal and cardiovascular problems. References Khan PA, Nishaat J, Noor S, et al. Laurence Moon Bardet Biedl syndrome: a rare case report in a tertiary care teaching hospital, Hyderabad, Telangana, India. Int J Med Sci Public Health 2017;7(1):68-71. Katsanis N, Lupski JR, Beales PL. Exploring the molecular basis of Bardet-Biedl syndrome. Hum Mol Genet 2001;10(20):2293-2299.

Evaluation of swallowing in patients with T3/T4 oral squamous cell carcinoma.

Background: Follow-up of patients treated for head and neck cancer is an important part of the overall treatment. Oral cancers are one of the leading causes of dysphagia. Swallowing dysfunction occurs owing to the disease itself, its predisposing factors, and the treatment. This study aims to evaluate swallowing dysfunction in patients with oral cavity cancers. Methods: This prospective study was carried out in a tertiary care hospital institution. Thirty patients with T3, T4 oral cancers were evaluated using institutional dysphagia score and fiber optic endoscopic evaluation of swallowing (FEES) (Penetration-Aspiration Scale, Yale Pharyngeal Residue Scale) before treatment, after surgery, and after adjuvant therapy. Results: Advanced-stage tumor, larger resections, and adjuvant therapy are risk factors for dysphagia postoperatively. Although the dysphagia score is our institutional score, the results are promising, that is, 10 % of patients having symptoms at baseline evaluation, which increased to 60% and 70% after surgery and adjuvant radiotherapy respectively. Our study findings of the Penetration Aspiration Scale are 13% aspiration rate at the baseline evaluation, which increased to 57% and 73% after surgery and after adjuvant radiotherapy, respectively, and these results are consistent with those of other report studies. The Vallecular Residual Scale showed that there was a significant association between three different timelines and demonstrated dysphagia among study subjects. Conclusion: Subjective and objective assessment of swallowing dysfunction before and after the treatment of head and neck cancers is underreported and underrecognized. Most of the patients in our study had significant swallowing impairment after treatment. FEES is a very effective procedure to diagnose dysphagia and will help in incorporating better preventative and rehabilitative measures.

Rapid detection and quantitation of dipicolinic acid from Clostridium botulinum spores using mixed-mode liquid chromatography-tandem mass spectrometry.

Analysis of the dipicolinic acid (DPA) released from Clostridium botulinum spores during thermal processing is crucial to obtaining a mechanistic understanding of the factors involved in spore heat resistance and related food safety applications. Here, we developed a novel mixed-mode liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for detection of the DPA released from C. botulinum type A, nonproteolytic types B and F strains, and nonpathogenic surrogate Clostridium sporogenes PA3679 spores. DPA was retained on a mixed-mode C18/anion exchange column and was detected using electrospray ionization (ESI) positive mode within a 4-min analysis time. The intraday and interday precision (%CV) was 1.94-3.46% and 4.04-8.28%, respectively. Matrix effects were minimal across proteolytic type A Giorgio-A, nonproteolytic types QC-B and 202-F, and C. sporogenes PA3679 spore suspensions (90.1-114% of spiked DPA concentrations). DPA recovery in carrot juice and beef broth ranged from 105 to 118%, indicating limited matrix effects of these food products. Experiments that assessed the DPA released from Giorgio-A spores over the course of a 5-min thermal treatment at 108 °C found a significant correlation (R = 0.907; P < 0.05) between the log reduction of spores and amount of DPA released. This mixed-mode LC-MS/MS method provides a means for rapid detection of DPA released from C. botulinum spores during thermal processing and has the potential to be used for experiments in the field of food safety that assess the thermal resistance characteristics of various C. botulinum spore types.

Predictive capability evaluation and optimization of Pb(II) removal by reduced graphene oxide-based inverse spinel nickel ferrite nanocomposite.

Pb(II) is a heavy metal that is a prominent contaminant in water contamination. Among the different pollution removal strategies, adsorption was determined to be the most effective. The adsorbent and its type determine the adsorption process's efficiency. As part of this effort, a magnetic reduced graphene oxide-based inverse spinel nickel ferrite (rGNF) nanocomposite for Pb(II) removal is synthesized, and the optimal values of the independent process variables (like initial concentration, pH, residence time, temperature, and adsorbent dosage) to achieve maximum removal efficiency are investigated using conventional response surface methodology (RSM) and artificial neural networks (ANN). The results indicate that the initial concentration, adsorbent dose, residence time, pH, and process temperature are set to 15 mg/L, 0.55 g/L, 100 min, 5, and 30 °C, respectively, the maximum removal efficiency (99.8%) can be obtained. Using the interactive effects of process variables findings, the adsorption surface mechanism was examined in relation to process factors. A data-driven quadratic equation is derived based on the ANOVA, and its predictions are compared with ANN predictions to evaluate the predictive capabilities of both approaches. The R2 values of RSM and ANN predictions are 0.979 and 0.991 respectively and confirm the superiority of the ANN approach.

Development of artificial neural networks software for arsenic adsorption from an aqueous environment.

Arsenic contamination is a global problem, as it affects the health of millions of people. For this study, data-driven artificial neural network (ANN) software was developed to predict and validate the removal of As(V) from an aqueous solution using graphene oxide (GO) under various experimental conditions. A reliable model for wastewater treatment is essential in order to predict its overall performance and to provide an idea of how to control its operation. This model considered the adsorption process parameters (initial concentration, adsorbent dosage, pH, and residence time) as the input variables and arsenic removal as the only output. The ANN model predicted the adsorption efficiency with high accuracy for both training and testing datasets, when compared with the available response surface methodology (RSM) model. Based on the best model synaptic weights, user-friendly ANN software was created to predict and analyze arsenic removal as a function of adsorption process parameters. We developed various graphical user interfaces (GUI) for easy use of the developed model. Thus, a researcher can efficiently operate the software without an understanding of programming or artificial neural networks. Sensitivity analysis and quantitative estimation were carried out to study the function of adsorption process parameter variables on As(V) removal efficiency, using the GUI of the model. The model prediction shows that the adsorbent dosages, initial concentration, and pH are the most influential parameters. The efficiency was increased as the adsorbent dosages increased, decreasing with initial concentration and pH. The result show that the pH 2.0-5.0 is optimal for adsorbent efficiency (%).

Knowledge extraction of sonophotocatalytic treatment for acid blue 113 dye removal by artificial neural networks.

Removing decolorizing acid blue 113 (AB113) dye from textile wastewater is challenging due to its high stability and resistance to removal. In this study, we used an artificial neural network (ANN) model to estimate the effect of five different variables on AB113 dye removal in the sonophotocatalytic process. The five variables considered were reaction time (5-25 min), pH (3-11), ZnO dosage (0.2-1.0 g/L), ultrasonic power (100-300 W/L), and persulphate dosage (0.2-3 mmol/L). The most effective model had a 5-7-1 architecture, with an average deviation of 0.44 and R2 of 0.99. A sensitivity analysis was used to analyze the impact of different process variables on removal efficiency and to identify the most effective variable settings for maximum dye removal. Then, an imaginary sonophotocatalytic system was created to measure the quantitative impact of other process parameters on AB113 dye removal. The optimum process parameters for maximum AB 113 removal were identified as 6.2 pH, 25 min reaction time, 300 W/L ultrasonic power, 1.0 g/L ZnO dosage, and 2.54 mmol/L persulfate dosage. The model created was able to identify trends in dye removal and can contribute to future experiments.

Awareness of Leprosy in an urban slum of Western Maharashtra Post 35 Years of the National Leprosy Eradication Program (NLEP).

Background: Even after 35 years of the National Leprosy Eradication Program (NLEP) and 15 years post-elimination, leprosy continues to be a public health challenge in India. This paper discusses the current awareness of leprosy among people living in urban slums of western Maharashtra. Methods: The study was conducted in an urban slum of western Maharashtra with 400 participants. A closed-ended questionnaire regarding the knowledge, attitude, practices, and stigma existing among the people was administered, followed by a small awareness talk and screening for leprosy. Results: Of the total 400 participants, 205 (51.25) were females and 195 (48.75) were males. Only 154/400 (38.5%) people were aware of leprosy. 130/400 (32.5%) people thought that it is treatable; however, 71/130 (54.6) of them thought that it would recur even after completing the treatment. Only 103/400 (25.75) said that they would marry a person with leprosy, denoting prevalent stigma in the society, and 79/400 (19.75) were aware of government services for leprosy and NLEP. Screening of all the participants surveyed did not reveal any new or doubtful cases of leprosy. Conclusion: The present study shows a lack of awareness and knowledge of leprosy among the target population. With only 20% of them being aware of government services and the NLEP, combined with an extremely low knowledge about the disease; it shows the need to further augment the government programs. There is also an increasing need to educate people to accomplish a positive attitude of the community towards leprosy patients.

Neodymium (Nd) based oxide perovskite nanostructures for photocatalytic and photoelectrochemical water splitting functions.

Neodymium (Nd) based perovskite (Nd1-xCoxFeO3) nanostructures were processed to address the rising energy and environment crisis through offering solutions by photocatalytic and photoelectrochemical (PEC) water splitting reactions. The impact of cobalt (Co) ions on the physicochemical properties of Nd-perovskites were studied using X-ray diffraction (XRD), Raman and electron microscopic instruments. The interaction of metal ions was studied in depth via X-ray photoelectron spectroscopy (XPS). Absorption and photoluminescence signals inferred the optical band gap to be lowered and defect states to increase upon Co substitution. Improved photocatalytic efficacy in Nd1-xCoxFeO3 was evaluated by comparative studies using NdFeO3. Secondly, the enhanced conductivities in Nd1-xCoxFeO3 studied via Nyquist plot was found to be advantageous in photoelectrode fabrication for PEC functions. Time-dependent photocurrent density results affirmed the stability in processed devices. Co ions were also inferred to boost the separation of charge carriers effectively. The improved performance in Nd1-xCoxFeO3 nanostructures were well justified to the successful incorporation of Co ions that sway the Nd-O, Co-O and Co-Fe-O bondings and boost the photon absorption and electronic conductivity to facilitate the observed performance.

Prediction of batch sorption of barium and strontium from saline water.

Celestite and barite formation results in contamination of barium and strontium ions hinder oilfield water purification. Conversion of bio-waste sorbent products deals with a viable, sustainable and clean remediation approach for removing contaminants. Biochar sorbent produced from rice straw was used to remove barium and strontium ions of saline water from petroleum industries. The removal efficiency depends on biochar amount, pH, contact time, temperature, and Ba/Sr concentration ratio. The interactions and effects of these parameters with removal efficiency are multifaceted and nonlinear. We used an artificial neural network (ANN) model to explore the correlation between process variables and sorption responses. The ANN model is more accurate than that of existing kinetic and isotherm equations in assessing barium and strontium removal with adj. R2 values of 0.994 and 0.991, respectively. We developed a standalone user interface to estimate the barium and strontium removal as a function of sorption process parameters. Sensitivity analysis and quantitative estimation were carried out to study individual process variables' impact on removal efficiency.

Artificial neural networks modeling for lead removal from aqueous solutions using iron oxide nanocomposites from bio-waste mass.

Heavy metal ions in aqueous solutions are taken into account as one of the most harmful environmental issues that ominously affect human health. Pb(II) is a common pollutant among heavy metals found in industrial wastewater, and various methods were developed to remove the Pb(II). The adsorption method was more efficient, cheap, and eco-friendly to remove the Pb(II) from aqueous solutions. The removal efficiency depends on the process parameters (initial concentration, the adsorbent dosage of T-Fe3O4 nanocomposites, residence time, and adsorbent pH). The relationship between the process parameters and output is non-linear and complex. The purpose of the present study is to develop an artificial neural networks (ANN) model to estimate and analyze the relationship between Pb(II) removal and adsorption process parameters. The model was trained with the backpropagation algorithm. The model was validated with the unseen datasets. The correlation coefficient adj.R2 values for total datasets is 0.991. The relationship between the parameters and Pb(II) removal was analyzed by sensitivity analysis and creating a virtual adsorption process. The study determined that the ANN modeling was a reliable tool for predicting and optimizing adsorption process parameters for maximum lead removal from aqueous solutions.

Photocatalytic hydrogen production from dye contaminated water and electrochemical supercapacitors using carbon nanohorns and TiO2 nanoflower heterogeneous catalysts.

In this research, efficient and novel catalysts based on hierarchical carbon nanohorns-titanium nanoflowers have been prepared by one-pot solvothermal process. Hydrogen generation from dye-contaminated water and dye degradation along with electrochemical supercapacitance performance have been investigated using the synthesized hierarchical catalyst to produce 4500 µmol g-1 h-1 of hydrogen from the photocatalytically generated aqueous methylene blue and methyl orange dyes, which were degraded up to 90% under natural solar light irradiation. These results offer a new path to generate hydrogen from the aqueous dyes. The catalysts electrode showed 164.6 F g-1 supercapacitance at 5 mV s-1 scan rate, which is nearly 1.3 and 1.65-times higher than that of pristine titanium nanoflower and carbon nanohorns electrodes, respectively. Such superior results were achieved due to good crystallinity, improved optical absorption strength, strong chemical composition between the two components, and hierarchical morphology as demonstrated from XRD, UV-DRS, TEM, XPS, and Raman spectral characterizations.

Synthesis of novel Co3O4 nanocubes-NiO octahedral hybrids for electrochemical energy storage supercapacitors.

Fabrication of novel metal oxide nanostructured composites is a proficient approach to develop efficient energy storage devices and development of cost-free and eco-friendly metal oxide nanostructures for supercapacitor applications received considerable attention in recent years. The Co3O4 nanocubes-NiO octahedral structured composite was constructed using facile and one-step calcination process. Cyclic voltammetry, charge-discharge, and electrochemical impedance spectral techniques have been employed to analyze the specific capacitance of the synthesized nanostructures and the composites. Specific capacitance and cycling stability of the composites were evaluated with the pristine Co3O4 and NiO nanostructures. The composite showed a specific capacitance of 832 F g-1 at a current density of 0.25 A g-1, which was ~1.5 and ~1.9-times higher than pristine Co3O4 nanocubes and NiO octahedral structure, respectively. On the other hand, electrode showed approximately 50 % capacity retention at a higher current density (5 Ag-1) because of the uniform morphology of Co3O4 and NiO. The charge-discharge stability measurements of the composite showed an admirable specific capacitance retention capability, which was 94.5 % after 2000 continuous charge-discharge cycles at a current density of 5 A g-1. The superior electrochemical performance of the nano-composite was ascribed to synergistic effects and uniform morphology. Efficient nanostructure development using facile and one-step calcination process and electrochemical performance make the synthesized composite a promising device for supercapacitor applications.

Photocatalytic hydrogen production by ternary heterojunction composites of silver nanoparticles doped FCNT-TiO2.

Silver nanoparticles doped with FCNT-TiO2 heterogeneous catalyst was prepared via one-step chemical reduction process and their efficacy was tested for hydrogen production under solar simulator. Crystallinity, purity, optical properties, and morphologies of the catalysts were examined by X-Ray diffraction, Raman spectroscopy, UV-Visible diffuse reflectance spectra, and Transmission Electron Microscopy. The chemical states and interface interactions were studied by X-ray photoelectron spectroscopy and Fourier transform infrared spectroscopy. The optimized catalyst showed 19.2 mmol g-1 h-1 of hydrogen production, which is 28.5 and 7 times higher than the pristine TiO2 nanoparticles and FCNT-TiO2 nanocomposite, respectively. The optimized catalyst showed stability up to 50 h under the solar simulator irradiation. The natural solar light irradiated catalyst showed ~2.2 times higher hydrogen production rate than the solar simulator irradiation. A plausible reaction mechanism of Ag NPs/FCNT-TiO2 photocatalyst was elucidated by investigating the beneficial co-catalytic role of Ag NPs and FCNTs for enhanced hydrogen production.

Vegetation Type Does not Affect Nitrous Oxide Emissions from Riparian Zones in Agricultural Landscapes.

Riparian zones provide multiple benefits in agricultural landscapes, but nitrogen (N) loading can cause N2O emissions. There is a knowledge gap on how different types of riparian vegetation influence N2O emissions. This study quantified N2O emissions from a rehabilitated riparian zone with deciduous trees (RH), a herbaceous (grassed) riparian zone (GRS), a natural forested riparian zone with deciduous trees (UNF-D), a natural forested riparian zone with coniferous trees (UNF-C), and an agricultural field (AGR). N2O fluxes were not significantly different (p > 0.05) among riparian zones (11-17 µg N2O-N m-2 h-1) and were not significantly different (p > 0.05) when comparing riparian zones to the AGR field (34 µg N2O-N m-2 h-1). Despite high N-loading, cumulative N2O emissions (1989 µg N2O-N m-2) in the riparian zones was significantly lower (p > 0.05) than AGR (13,278 µg N2O-N m-2). The main predictors of N2O fluxes were soil temperature and soil NO3--N for the riparian zones and the AGR field. We found that environmental conditions played a greater role than the type of riparian vegetation or age in predicting N2O emissions. We suggest that soil environmental factors created an anaerobic environment that favored N2O consumption via complete denitrification.