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In the present study corrosion behaviour of three coated steel sheets in different corrosive environments was evaluated using various characterisation techniques. Multiple types of corrosion tests, like salt spray test, 100% relative humidity test and chemical resistance test, were performed to report the corrosion resistance of samples in different corrosive environments. Enhanced corrosion resistance properties of the colour-coated samples were obtained from all the studies, followed by galvalume and galvanised samples. Cyclic voltammetry reveals a slightly higher pitting for the galvalume sample. SEM, EDS, XRD and Raman analyses for the salt spray tested and 100% humidity tested galvanised samples shows various corrosion products with their morphologies. XRD analysis reveals Zn5(OH)8Cl2H2O (simonkolleite), ZnO (zinc oxide), β-Zn (OH)2, Zn (OH)2 (zinc hydroxide) and Zn (ClO4)2 for salt spray tested samples whereas for the 100% relative humidity tested samples, main corrosion products are ZnO (zinc oxide), β-Zn (OH)2, Zn (OH)2 (zinc hydroxide), Fe and Zn. Raman spectroscopy reveals the presence of ZnO, β-FeOOH, white rust, green rust, FeCl2, Fe3O4, FeOH, Fe2O3 and δ-FeOH for salt spray tested samples, but for 100% humidity test, only ZnO is revealed.

In the context of autonomous landing for unmanned aerial vehicles (UAVs), selecting a suitable landing site is crucial. This research presents a new method for automatically identifying safe landing sites based on point cloud data acquired through an airborne laser scanning (ALS) system. The proposed approach begins by detecting flat regions using principal component analysis (PCA) and region-growing algorithms. Subsequently, a terrain complexity assessment is conducted through plane fitting using an enhanced progressive sample consensus (PROSAC) algorithm. This assessment assists in identifying the most suitable landing site within a specified landing zone. The method's effectiveness is demonstrated through experiments conducted on two distinct natural terrains from the DALE dataset. The results show that the proposed approach can accurately classify landing zones and identify preferred sites that meet safety criteria. This study's findings underscore the proposed method's effectiveness and feasibility in improving the safety and reliability of autonomous UAV landings.

The three-dimensional (3D) preservation and repair of historic sites are increasingly in practice using modelling and digital documentation. This study focuses on replacing conventional techniques of historical documentation by creating a digital documentation procedure employing laser scanning for 3D mapping of a monument located in Prayagraj, India. To quickly record the entire monument structure, four scanning stations were planned, where three for the facades and one for the interior. A 3D structure of the monument and its elements dimension that included structural, architectural, historical, and non-engineering information was the end product. Researchers, architects, and conservationists can use this laser scanning-based technique to analyze data in great detail to identify weaknesses and conservation requirements. In order to preserve the monument's cultural relevance, it can also be used for virtual tours. Digital documentation can also provide an accurate monument record for restoration needs, protecting the monument from human- or natural-caused damage. Overall, 3D Modelling and digital documentation are valuable tools in heritage conservation, providing comprehensive records of heritage sites and aiding in practical conservation and restoration plans while making cultural heritage accessible to a broader societies.

The trees inventory is very important for forestry and environment-related issues, where tree morphology is one of the key components. LiDAR technology is being selected over other techniques for the trees three-dimensional mapping and inventory. In this paper a methodology for point cloud registration and georeferencing of LiDAR point cloud, and computation of tree morphological parameters, namely tree height, crown diameter, crown projection area is presented. The instruments used for the point cloud acquisition, registration and georeferencing were total station, global navigation satellite system, terrestrial laser scanner. Data from all three instruments were transformed into a common coordinate system that is Universal Transverse Mercator coordinate system. In transformed point cloud, the z-axis of the coordinate system is towards plumb line. The tree height, crown diameter, crown projection area are computed based on point cloud-derived canopy height model and tree top detection.

In the realm of data analytics, machine learning (ML) is one of the most successful techniques for making predictions. The ability of ML algorithms has also been studied in various aspects of land surface temperature (LST) besides its retrieval. The few investigations on LST retrieval using ML algorithms suggested that it may potentially obtain the LST values incorporating relevant variables of land surface parameters; however, the variables and ML models used differ, and so do their accuracies. The accuracy of the model is affected by the variable's contribution, its quality and quantity, and the fulfilment of each technique's assumptions. Hence this study provides a wide range of LST indicators to be employed for LST retrieval using a widely used ML algorithm, random forest. The ML algorithm framework for LST prediction is illustrated with significant spectral indices and terrain parameters across the highly industrialised district of Jharkhand, India. With the exception of one (aspect) variable, the analysis shows that all 20 variables that were included as independent factors were significant and equally contributed to the model. The model built with all the variables including the aspect of the terrain obtained an RMSE of 1.13 degree Celsius and R2 of 0.48. However, after the removal of aspect, the model obtained an R2 of 0.89 and RMSE of 0.74 °C. The performance of the model on consecutive removal of lesser significant variables are evaluated and the study made clear how crucial it is to consider several environmental or land-use factors that could be pertinent to LST.

Intro: In an unfavorable environment, bacteria improvise living strategy by ceasing growth and reducing metabolism to attain Viable But Non-Culturable (VBNC) state. Once these bacteria find a favorable environment, they resume growth process. In the last few decades, researchers have demonstrated that several human pathogens can attain VBNC state after exposure to several physical and chemical conditions. Due to low metabolism and non-culturability, VBNC escapes culture-based detection. Pieces of evidence are there to indicate emergence of new mutations and AMR phenotypes in VBNC and resuscitated states. Commonly used antibiotics, ciprofloxacin, amoxicillin and FDA-approved surface disinfectant Glutaraldehyde have not been tested for VBNC induction. We hypothesized that these xenobiotics can induce VBNC in bacterial species commonly found in hospital environments putatively driving emergence of AMR. This knowledge will help in improving pathogen detection, and infection and AMR control. Methods: Ciprofloxacin, Amoxicillin and Glutaraldehyde were demonstrated to induce VBNC in Klebsiella pneumoniae, Acinetobacter baumannii and Escherichia coli. VBNC induction was validated by CFU count, energy production, membrane integrity and basal metabolism. Confocal microscope for morphology visualizaion, disk diffusion for AST phynotype. Findings: All three xenobiotics induced VBNC state in ∼ 85% of cells in the bacterial population, leaving the rest 15% non-viable, and successfully resuscitated by removing the xenobiotic. The resuscitation started after 24 hours to 48 hours in various conditions and showed increased AMR phenotype. The microscopic visualization showed shrunken but elongated morphology in VBNC as well as resuscitated cells. Conclusion: Our study demonstrated that commonly used antibiotics and surface disinfectant can induce VBNC, which in turn poses a highly probable risk of missing surface microbial contamination in hospital settings. Also, the emergence of new AMR traits due to exposure to these xenobiotics indicates the necessity of further insights into the mechanism of VBNC induction and resuscitation at molecular level and development of safer alternative antimicrobial agents

Intro: Klebsiella pneumoniae causes wide range of infections including urinary tract infections, sepsis, bacteremia, pneumonia and liver abscesses. The emergence of multi drug resistance in this bacterium led to a major setback for clinical management. WHO also endorsed need for finding alternative therapy to antibiotics for the treatment of these infections. Development of vaccines and passive antibody therapy has been proven as a potent alternative to antibiotics in case of MDR, XDR and PDR Klebsiella infections. Methods: Antigen isolation, characterisation and identification through ultracentrifugation, SDS-PAGE and Triple-TOF Mass spectrometry. Cloning and expression of Fep A gene was done. Mice immunisation and challenge study with Klebsiella pneumoniae bacteria accomplished. Findings: Clinical strains of Klebsiella pneumoniae were grown in iron deficient conditions and the iron regulated outer membrane proteins were extracted and characterized through mass spectrometry for specific identification. The gene for identified protein was cloned in pET- 28a vector and expressed in E. coli. The native protein and the recombinant protein were isolated and purified and used as antigens for generation of immune response in BALB/c mice. The native protein of Klebsiella pneumoniae grown in iron deficient condition was identified as FepA (Ferrienterobactin receptor) and other siderophore receptors. This 80 kDa protein generated a significant immune response in BALB/c mice. The antiserum from mice after subsequent booster doses was collected and showed binding with FepA protein in western blot and phagocytic uptake assay of K. pneumoniae. From animal studies after bacterial challenge post immunisation in mice, signifant bacterial clearance was observed. The antiserum from mice showed binding and clearance of the Klebsiella pneumoniae bacteria in vitro and in vivo. Conclusion: The antiserum from immunised mice with FepA showed binding and clearance of the Klebsiella pneumoniae bacteria in vitro and in vivo.This study demonstrates the potential signifance of FepA as an immunogen or a therapeutic agent.

Purpose: To explore the effect of pharmaceutical industry effluent on viability and persistence of microbial population (environmental and clinical) with regard to abundance of AMR genes and induction of Viable but non-Culturable (VBNC) state. Methods & Materials: Settings: Effluent from common effluent treatment plants (CETP),Sample collection: Samples were collected from industrial effluent inlet and river discharge pointSample Definition: CETP receives effluent from different manufacturing units and pharmaceutical industries dealing with small molecule drugs.Chemical and Phenotypical analysis: Chemical analysis of effluent, detection of AMR genes, VBNC induction by effluent and resuscitation, morphological identification of microbial species Results: Chemical analysis- Chemical analysis of samples, showed high level of lead, mercury, some hydrolyzed imidazole and other smaller hydrolyzed fragments.AMR gene detection- AMR genes for the fluoroquinolone, Aminoglycoside, beta-lactamase Class A/B/C/D, Erythromycin, Lincosamide Streptogramin_b, and vancomycin were present in test samples, with highest copy numbers of Macrolide and tetracycline. Sample from river discharge point had multidrug resistant efflux pump genes.VBNC induction and resuscitation- Based on chemical analysis and presence of AMR genes, further analysis of effect of heavy metals in test sample was explored on microbial population. Effluent sample upon ultra-centrifugation followed by ultra-filtration, did not show any microbial growth under normal culture conditions, but showed growth upon co-culture with E. coli. This indicates the presence of bacterial population in the shrunken form in effluent reflecting the VBNC state.Microbial identification- Different bacterial colonies that was observed during resuscitation were analyzed by gram staining. All 44 colonies were categorized into four groups, gram positive cocci (30), gram positive rod (8), gram negative cocci (4) and gram-negative rod (2), while from unfiltered culture it was 46, 12, 11 and 7 respectively. Conclusion: Presence of heavy metals in the industrial effluent generate selection pressure resulting in emergence of AMR traits. Also, heavy metal and imidazole rich effluent can induce VBNC state and persistence of microbial population, which upon attaining favorable condition, can be resuscitated. This work has significant implication in devising future strategies for effluent treatment to minimize environmental pressure and in turn reduce emergence of AMR.

Summary Background While patients and families struggling with atopic dermatitis (AD) have documented concerns for a contributory role of skin care products in AD pathology, nearly all the skin microbiome studies to date have asked participants to avoid topical products (such as soaps or select medications) for the preceding days to weeks prior to sample collection. Thus, given the established role of the microbiome in AD, the interactions between topical exposures, dysbiosis and AD remains underrepresented in the academic literature. Objectives To address this knowledge gap, we expanded our previous evaluations to test the toxicological effects of a broader range of common chemicals, AD treatment lotions, creams and ointments using both health‐ and AD‐associated strains of Roseomonas mucosa and Staphylococcus spp. Methods Use of in vitro culture techniques and mouse models were deployed to identify chemicals with dysbiotic or pre‐biotic potential. A proof‐of‐concept study was subsequently performed in healthy volunteers to assess global microbiome shifts after exposure to select chemicals using dermatologic patch testing. Results Numerous chemicals possessed antibiotic properties, including many not marketed as anti‐microbials. Through targeted combination of potentially beneficial chemicals, we identified combinations which promoted the growth of health‐associated isolates over disease‐associated strains in bacterial culture and enhanced microbe‐specific outcomes in an established mouse model of AD; the most promising of which was the combination of citral and colophonium (often sold as lemon myrtle oil and pine tar). Additional studies would likely further optimize the combination of ingredients use. Similar results were seen in the proof‐of‐concept human studies. Conclusions Our results could offer a systematic, multiplex approach to identify which products carry dysbiotic potential and thus may guide formulation of new topicals to benefit patients with AD.

Agroforestry is an integrated self-sustainable land use management system that is not only capable of producing food from marginal agricultural land but also capable of maintaining and improving the quality of environment. Accurate assessment of trees on farmlands i.e. agroforestry would help in determining their contribution in meeting timber demand and also in carbon sequestration vis-a-vis climate change mitigation. In the present, high resolution multispectral satellite imagery (LISS-IV) has been used for mapping and estimating agroforestry area in Koraput district of Odisha. Both supervised and Object based Image Analysis (OBIA) classifications methods have been applied. In case of supervised maximum likelihood method, those pixels are fully captured where trees exist, whereas in OBIA captures trees according to their crown shapes. This proved OBIA method to be better in identification of trees on farmlands (scattered trees, boundary, and block plantations) than supervised method. This can lead to accurate estimation of area under trees in scattered form, in linear form and also in patch form. Improved results were obtained in case of OBIA classification with more than 90% accuracy. This research implies that remote sensing provide promising tools for evaluating and mapping of agroforestry at district level. Hence, the proposed approach of using high resolution remote sensing data in conjunction with OBIA method would be promising for mapping agroforestry area.

High quality digital elevation model (DEM) is obtained from mobile LiDAR data and it is used in various applications like road widening, slope measurement of road side surfaces, and inundation of the roadway evaluation. Two steps algorithm is proposed to filter ground points using mobile LiDAR data. Initially unstructured input data is organized then standard deviation and flatness based approach is used to filter ground points. Proposed algorithm is tested on point cloud of test site located along 800 m of roadway. Type I, Type II and total error are 2.11%, 2.21% and 2.15%, respectively with kappa is equal to 96.61% are computed using ground filtered points and reference data points.

The accurate, detailed and up-to-date road information is highly essential geo-spatial databases for transportation, smart city and other related applications. Thus, the main objective of this research is to develop an efficient algorithm for road network extraction from airborne LiDAR data using supervised classification approach. The proposed algorithm first classifies the input data into the road and non-road features using modified maximum likelihood classification approach. Then Digital Terrain Model (DTM) mask is generated by removing non-ground features from Digital Surface Model using hierarchical morphology and road candidate image if obtained. The parking lots are removed and road network is extracted successfully.

Mobile LiDAR captures complete details of street trees located along roadway and it is most efficient tool for executing large scale projects for road side trees mapping. Information of road-side trees locations and their morphological characteristics are essential for road widening project planning, road safety and autonomous vehicles. We propose a method to generate GIS database of street trees using information of automatically extracted street trees using mobile LiDAR data. Proposed method first organizes mobile LiDAR input data in partially overlapping cylinders and then morphological characteristics of tree crown and trunk, respectively are used to detect trees falling within cylinders. Finally complete tree structure point cloud is recovered from cylinder by vertical cylinders fitting to crown and trunk separately. The proposed method is tested on point cloud data acquired by StreetMapper 360 of 57 m long roadway. Completeness and correctness of 88.24% and 93.75% respectively are obtained in test site.

The accurate three-dimensional road surface information is highly useful for health assessment and maintenance of roads. It is basic information for further analysis in several applications including road surface settlement, pavement condition assessment and slope collapse. Mobile LiDAR system (MLS) is frequently used now a days to collect detail road surface and its surrounding information in terms three-dimensional (3D) point cloud. Extraction of road surface from volumetric point cloud data is still in infancy stage because of heavy data processing requirement and the complexity in the road environment. The extraction of roads especially rural road, where road-curb is not present is very tedious job especially in Indian roadway settings. Only a few studies are available, and none for Indian roads, in the literature for rural road detection. The limitations of existing studies are in terms of their lower accuracy, very slow speed of data processing and detection of other objects having similar characteristics as the road surface. A fast and accurate method is proposed for LiDAR data points of road surface detection, keeping in mind the essence of road surface extraction especially for Indian rural roads. The Mobile LiDAR data in XYZI format is used as input in the proposed method. First square gridding is performed and ground points are roughly extracted. Then planar surface detection using mathematical framework of principal component analysis (PCA) is performed and further road surface points are detected using similarity in intensity and height difference of road surface pointe in their neighbourhood.A case study was performed on the MLS data points captured along wide-street (two-lane road without curb) of 156 m length along rural roadway site in the outskirt of Bengaluru city (South-West of India). The proposed algorithm was implemented on the MLS data of test site and its performance was evaluated it terms of recall, precision and overall accuracy that were 95.27%, 98.85% and 94.23%, respectively. The algorithm was found computationally time efficient. A 7.6 million MLS data points of size 27.1 MB from test site were processed in 24 minutes using the available computational resources. The proposed method is found to work even for worst case scenarios, i.e., complex road environments and rural roads, where road boundary is not clear and generally merged with road-side features.

Introduction: A number of studies on clinical evaluation of post menopausal bleeding have been conducted worldwide but there are a few reports from India so this study was intended to present a hospital based survey to investigate the clinical significance of post menopausal bleeding in terms of etiology, risk factors, incidence of malignancy and histopathological evaluation. Objectives: a) To study the clinical features in a patient with post menopausal bleeding. b) To study the different pathological changes in endometrium in post menopausal bleeding patients. c) To study the effect of risk factors like diabetes, hypertension and obesity on histopathology. d) To evaluate the causes of post menopausal bleeding. Materials and methods: The study recruited 70 patients above the age of 45 years who presented with post menopausal bleeding. Histopathological examination was done. Results: Most common presenting complaint is bleeding per vaginum (43%), followed by recurrent bleeding (34%). Age ranged between 44-80 years. High incidence in age group of 50-54 years. Majority were multiparous (88%). In current study, 54.2% were diabetic, 51% obese and 45% hypertensive. 94% had benign pathology and only 6% showed malignant pathology. Majority cases had endometrial thickness 5-12 mm in transvaginal sonography. Majority had proliferative endometrium, followed by hyperplasia, atrophy, polyp and secretory endometrium. Conclusion: a) Every post menopausal bleeding case has to be thoroughly evaluated with history, examination (age, presence of diabetes, hypertension, BMI) and TVS. To improve diagnostic accuracy. b) Dilatation and curettage can provide sufficient diagnostic accuracy. c) Early diagnosis makes successful treatment of endometrial hyperplasia and endometrial cancer in post menopausal bleeding cases. d) Endometrial sampling is mandatory prior to therapeutic gesture.

Systemic sclerosis (SSc) is an uncommon connective tissue disorder characterized by multisystem involvement with fibrosis of skin and internal organs. Antibody formation is one of the hallmarks of SSc. Antinuclear antibodies (ANA) are positive in 97% of patients with SSc. We report a rare case where the patient was negative for ANA, Anti-topoisomerase I, Anti-centromere and Anti-RNA polymerase III antibodies.

The use of a periodic electron beam bunch train to resonantly excite plasma wakefields in the quasinonlinear (QNL) regime has distinct advantages over employing a single, higher charge bunch. Resonant QNL excitation can produce plasma electron blowout using a small charge per pulse if the beam emittance beams are very low. The local density perturbation in such a case is extremely nonlinear, achieving total rarefaction, yet the resonant response of the plasma electrons at the plasma frequency is preserved. The needed electron beam pulse train with interbunch spacing equal to the plasma period can be produced via inverse free-electron laser bunching. As such, in achieving resonance with a laser wavelength of a few microns, a high plasma density is employed, with the attendant possibility of obtaining extremely large wakefield amplitudes, near 1 TV/m for FACET-II parameters. In this article, we use particle-in-cell (PIC) simulations to study the plasma response, the beam evolution including density modulation, and the instabilities encountered when using a bunched-beam scheme to resonantly excite waves in a dense plasma.

Escherichia vulneris is an opportunistic human pathogen. It has been primarily reported in adult patients and invasive infections have been observed in immune-suppressed individuals. This is the first report of E. vulneris causing complicated diarrhoea and sepsis in an infant. Two month old sick infant, born full-term, was admitted to the paediatrics department with loose motions and refusal to feed for four days. E. vulneris was isolated from blood in pure culture. The isolate was characterized for diarrhoeal virulence markers: heat labile and heat stable toxins (LT, ST) and hemolysin (hlyA) by PCR. The presence of LT enterotoxin and hemolysin provides strong evidence of the diarrhoeagenic potential of E. vulneris, further leading to the invasive infection triggering sepsis. As E. vulneris can lead to serious complications, an attempt should be made in clinical laboratories to identify and further characterize this new Escherichia species.

Nosocomial infections are acquired during hospital treatment or in a hospital environment. One such infecting agent, Escherichia coli, harbours many virulence genes that enable it to become pathogenic, causing damage to the host. The mechanism of the E. coli virulence factors provenance to cause infection in host environments is not clearly elucidated. We investigated the virulence and pathogenicity of E. coli affected by the host environment. For this, blood (n = 78) and faecal (n = 83) E. coli isolates were collected from patients with and without sepsis, respectively, who had been admitted to the intensive care unit. The E. coli genomic DNA was isolated; the phylogenetic grouping was conducted by triplex PCR. The occurrence of nine virulence genes among the all the isolates was confirmed by gene-specific PCR. The prevalence of E. coli in blood isolates was more in phylogenetic groups B2 and D compared to groups A and B1. However, in faecal isolates, there was no significant difference. The prevalence of adhesin and toxin (papG, sfa, afa, cnf1, hlyA) genes was higher in blood compared to faecal E. coli isolates. However, the prevalence of aer, traT and PAI was similar as well as higher among both of these groups. These observations indicate a role of external environment (hospital setting) on host susceptibility (development of infection) in the faecal E. coli isolates, thereby making the patient prone to a sepsis condition.

Pole-shaped objects (PSOs) located along a road play key role in road safety and planning. Automation is required for calculating the numbers of trees need to be removed and utility poles need to be relocated during rural road widening. Road-side poles are among the most frequently struck road-side objects during road-side accidents. An automatic method is therefore proposed for detecting PSOs using LiDAR point cloud captured along the roadway using Mobile LiDAR system. The proposed method is tested on the point cloud data of rural road environment in India. Dataset of study area having text file size of 1.22 GB is processed in 13 minutes resulting in completeness of 88.63 % and correctness of 95.12 % in identifying PSOs within 10m of the road boundary. In data of across road coverage of 5m of the road boundary, the completeness of 93.10 % and correctness of 100% are achieved. Poles attached with other objects, tilted poles and the poles occluded by tree branches and shrubs are detected by the proposed method.

Rice is the most important cereal crop governing food security in Asia. Reliable and regular information on the area under rice production is the basis of policy decisions related to imports, exports and prices which directly affect food security. Recent and planned launches of SAR sensors coupled with automated processing can provide sustainable solutions to the challenges on mapping and monitoring rice systems. High resolution (3m) Synthetic Aperture Radar (SAR) imageries were used to map and monitor rice growing areas in selected three sites in TamilNadu, India to determine rice cropping extent, track rice growth and estimate yields. A simple, robust, rule-based classification for mapping rice area with multi-temporal, X-band, HH polarized SAR imagery from COSMO Skymed and TerraSAR X and site specific parameters were used. The robustness of the approach is demonstrated on a very large dataset involving 30 images across 3 footprints obtained during 2013-14. A total of 318 in-season site visits were conducted across 60 monitoring locations for rice classification and 432 field observations were made for accuracy assessment. Rice area and Start of Season (SoS) maps were generated with classification accuracies ranging from 87- 92 per cent. Using ORYZA2000, a weather driven process based crop growth simulation model; yield estimates were made with the inclusion of rice crop parameters derived from the remote sensing products viz., seasonal rice area, SoS and backscatter time series. Yield Simulation accuracy levels of 87 per cent at district level and 85- 96 per cent at block level demonstrated the suitability of remote sensing products for policy decisions ensuring food security and reducing vulnerability of farmers in India.

The prevalence of the tcpC in the blood Escherichia coli isolates collected from the sepsis patients admitted to the intensive care unit was investigated for the first time. The blood and faecal samples were collected from sepsis and nonsepsis patients, respectively. The prevalence of the tcpC and phylogroups was confirmed by gene-specific PCR. The occurrence of the tcpC in the blood E. coli isolates from sepsis patients was significantly higher than the faecal isolates. The higher prevalence of blood E. coli isolates among the pathogenic groups (B2, D) compared to the commensal groups (A, B1) suggests tcpC as a prospective new virulence marker for sepsis.

The purpose of this paper is to evaluate the protective ability of 1-(2-aminoethyl)-2-oleylimidazoline (AEOI) and 1-(2-oleylamidoethyl)-2-oleylimidazoline (OAEOI) as corrosion inhibitors for N80 steel in 15% hydrochloric acid, which may find application as eco-friendly corrosion inhibitors in acidizing processes in petroleum industry. Different concentrations of synthesized inhibitors AEOI and OAEOI were added to the test solution (15% HCl) and the corrosion inhibition of N80 steel in hydrochloric acid medium containing inhibitors was tested by weight loss, potentiodynamic polarization and AC impedance measurements. Influence of temperature (298–323 K) on the inhibition behavior was studied. Surface studies were performed by using FTIR spectra and SEM. Both the inhibitors, AEOI and OAEOI at 150 ppm concentration show maximum efficiency 90.26% and 96.23%, respectively at 298 K in 15% HCl solution. Both the inhibitors act as mixed corrosion inhibitors. The adsorption of the corrosion inhibitors at the surface of N80 steel is the root cause of corrosion inhibition.

In the present investigation the protective ability of 1-(2-aminoethyl)-2-octadecylimidazoline (AEODI) and 1-(2-octadecylamidoethyl)-2-octadecylimidazoline (ODAEODI) as corrosion inhibitors for N80 steel in 15% hydrochloric acid has been studied, which may find application as ecofriendly corrosion inhibitors in acidizing processes in petroleum industry. Different concentration of synthesized inhibitors AEODI and ODAEODI was added to test solution (15% HCl), and corrosion inhibition of N80 steel was tested by weight loss, potentiodynamic polarization, and AC impedance measurements. Influence of temperature (298 to 323 K) on the inhibition behaviour was studied. Surface studies were performed by using SEM. It was found that both the inhibitors were effective inhibitors, and their inhibition efficiency was significantly increased with increasing their concentration. Polarization curves revealed that the used inhibitors represent mixed-type inhibitors. The adsorption of used inhibitors led to a reduction in the double-layer capacitance and an increase in the charge transfer resistance. The adsorption of used compounds was found to obey Langmuir isotherm. The adsorption of the corrosion inhibitors at the surface of N80 steel is the root cause of corrosion inhibition.

Mn(II), Fe(II), Co(II), Ni(II), Cu(II), Zn(II), and Cd(II) complex of N-thiophenoyl -N′-phenylthiocarbohydrazide (H2 TPTH) have been synthesized and characterized by elemental analysis, magnetic susceptibility measurements, infrared, NMR, electronic, and ESR spectral studies. The complexes were found to have compositions [Mn(H TPTH)2], [Co(TPTH) (H2O)2], [Ni(TPTH) (H2O)2], [Cu(TPTH)], [Zn(H TPTH)], [Cd(H TPTH)2], and [Fe(H TPTH)2(EtOH)]. The magnetic and electronic spectral studies suggest square planar geometry for [Cu(TPTH)], tetrahedral geometry for [Zn(TPTH)] and [Cd(H TPTH)2], and octahedral geometry for rest of the complexes. The infrared spectral studies of the 1 : 1 deprotonated complexes suggest bonding through enolic oxygen, thiolato sulfur, and both the hydrazinic nitrogens. Thus, H2TPTH acts as a binegative tetradentate ligand. H2 TPTH and its metal complexes have been screened against several bacteria and fungi.

This work investigated the effect of the modification of phenol-formaldehyde resins using different concentrations of nanoclay on specific physical and mechanical properties of Lantana camara composites. Different concentrations, i.e. 1, 2.5, 4 and 5 wt% nanoclay were added to phenol-formaldehyde adhesive. To ensure uniform distribution, the mixture was stirred mechanically followed by ultrasonication. Following the nanoclay concentrations, the mixtures were labelled accordingly as PF/NC-1, PF/NC-2.5, PF/NC-4 and PF/NC-5. Composites were made from L. camara particles mixed with 12% (w/w) nanoclay-fortified phenol-formaldehyde resins. Lantana camara composites were fabricated in a hydraulic hot press at a pressure of 21 kg cm-2 and curing temperature 150 °C for 15 min. The physical and mechanical properties of L. camara composites were evaluated following Indian Standards specification IS 3087 (2005). The results revealed that the physical and mechanical properties of L. camara composites improved compared with the composites prepared using unmodified phenol-formaldehyde. Composite prepared using phenolformaldehyde modified with 4% nanoclay showed better performance than the rest of the concentrations. A slight decline in mechanical properties was observed in L. camara composites when 5% nanoclay was used due to accumulation of nanoparticles. [ABSTRACT FROM AUTHOR]