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Addition of NO to a nonheme dithiolate-ligated iron(II) complex, Fe

Purpose The purpose of this paper is to develop a replicable model that ensures Household Water Treatment and Safe Storage as well as water treatment facilities at the community level by providing total service coverage at community scale. An intervention was implemented in one of the low-lying areas of Basirhat Municipality (West Bengal, India) that included a number of action programs in order to address household- and community-level water-induced challenges. Design/methodology/approach A research study was undertaken to identify the root causes of the problems that are generally spawned from geomorphological, hydro-fluvial, climatic factors and processes and the situation becomes complicated when many other cumulative problem-contexts layovers the existing ones. A number of social and technological innovations were tested in the field and this paper critically examined the intervention processes and outcomes. It was implemented through participatory process by involving related stakeholders working at that scale so that necessary public acceptance is received for scaling up, at least, in the similar physical, social, economic and institutional contexts. Findings The problem conceptualization process, spatial assessment for contextualizing the problem, design of interventions for different scales, development of project deployment strategies from field-based learnings contributed in developing a total solution based on fusing of household-level technical solutions, social innovations and actions for community engagements towards sustainability. Mobilized community members in addressing local inundation and waterlogging crisis. Satellite image-based maps shown to make them understand the upper-lower connection of drainage. People also developed their own action plans and engaged themselves in resuscitation of an old canal, removed the garbage that resulted in improved drainage conditions in the area. Research limitations/implications Pandemic due to COVID 19 and its related prolonged lock down, West Bengal State Assembly Election, closure of municipal governance system due to the forthcoming municipal election, closure of educational institutions, closure of Anganwadi Centre in the field area were the limitations. Due to the lock down, it was difficult for the team to maintain the time frame as well as the budget. As per the Election’s Code of Conduct gets released no public meeting was allowed without permission, people in the vicinity became suspicious, hence movement of the team members got restricted. Practical implications Due to the COVID protocols, the team could not organise mass training programs. It was difficult for the team members to commute in public/private transport, hence filed work got impacted. As the team could not access data from the health department, they developed a strategy of generation data on body mass index, mid-upper arm circumferences and waist-to-hip ratios to understand the status of health and nutrition of the community. It was difficult to access the Public Health Engineering Department’s laboratory situated in the municipality for water sample test. Cost escalated due to extension of the project time. Social implications During the second phase (wave) when people lost access to health facilities they requested the team to stop field visit. Women’s empowerment through acquiring knowledge and skill on treatment and safe storage of drinking water at home. Men appreciated and recognized this, which improved the status of women in the society. Children after expressing their willingness to learn the new technology of water purification were given handholding training by their mothers and knowledge transfer has taken place in the next generation. Mobilized community members in addressing local inundation and waterlogging crisis. Satellite image-based maps to understand the upper-lower connection of drainage helped them develop their own action plans and engaged themselves in resuscitation of an old canal, removed the garbage that resulted in improved drainage conditions in the area. Originality/value Household-level solutions include supply of low cost, easy operable, sustainable water purifiers, community-level solution focused on securing water-related challenges at social/public gathering places and wider catchment area level solutions include the engagement of local communities to drain out stagnant waters by clearing drains, creating/digging small canals through collective actions. Geo-spatial techniques (topographical mapping, spatial survey, water quality tests) along with social methods such as participatory appraisals for gathering information on human health, public awareness campaigns and partnership development with local government agencies were the major activities performed as part of the implementation of interventions. It is imperative to mention that water-related challenges in the low-lying settlement areas of Basirhat Municipality have effectively been addressed by relying on necessary theoretical underpinnings (Disaster risk reduction/humanitarian principles) transmitted through application of scientific techniques and mediated through local people and their agencies.

Addition of dioxygen at low temperature to the nonheme ferrous complex, Fe(II)(Me(3)TACN)(OSi(Ph2))(2)O) (1), in 2-MeTHF produces a peroxo-bridged diferric complex, Fe(2)(III)(μ-O(2))(Me(3)TACN)(2)((OSi(Ph2))(2)O)(2) (2), which was characterized by UV-vis, resonance Raman, and variable field Mössbauer spectroscopies. Illumination of a frozen solution of 2 in THF with white light leads to homolytic O–O bond cleavage and generation of a Fe(IV)(O) complex 4 (ν(FeO) = 818 cm(−1); δ = 0.22 mm s(−1), ΔE(Q) = 0.23 mm s(−1)). Variable field Mössbauer spectroscopy measurements show that 4 is a rare example of a high-spin, S = 2 Fe(IV)(O) complex, and the first synthetic example to be generated directly from O(2). Complex 4 is highly reactive, as expected for a high-spin ferryl, and decays rapidly in fluid solution at cryogenic temperatures. This decay process in 2-MeTHF involves C–H cleavage of the solvent. However, the controlled photolysis of 2 in situ with visible light and excess phenol substrate leads to competitive phenol oxidation, via the proposed transient generation of 4 as the active oxidant.

A new nonheme iron(II) complex, FeII (Me3 TACN)((OSiPh2 )2 O) (1), is reported. Reaction of 1 with NO(g) gives a stable mononitrosyl complex Fe(NO)(Me3 TACN)((OSiPh2 )2 O) (2), which was characterized by Mossbauer (δ=0.52 mm s-1 , |ΔEQ |=0.80 mm s-1 ), EPR (S=3/2), resonance Raman (RR) and Fe K-edge X-ray absorption spectroscopies. The data show that 2 is an {FeNO}7 complex with an S=3/2 spin ground state. The RR spectrum (λexc =458 nm) of 2 combined with isotopic labeling (15 N, 18 O) reveals ν(N-O)=1680 cm-1 , which is highly activated, and is a nearly identical match to that seen for the reactive mononitrosyl intermediate in the nonheme iron enzyme FDPnor (ν(NO)=1681 cm-1 ). Complex 2 reacts rapidly with H2 O in THF to produce the N-N coupled product N2 O, providing the first example of a mononuclear nonheme iron complex that is capable of converting NO to N2 O in the absence of an exogenous reductant.

COVID-19 is a pandemic caused by novel coronavirus. Molecular diagnostic tests and serologic tests are the two types of testing procedures currently available to detect virus of COVID-19 in the human body. Another way to detect COVID-19 is the use of chest x-ray. Radiology doctors use x-ray report to identify COVID-19-positive patients and the severity of that. In the proposed methodology, the authors develop an algorithm that can detect COVID-19 from chest x-ray images automatically. In the proposed work, image descriptor such as local binary pattern (LBP) is used to extract the features of the x-ray images. Using those textural pattern, LBP image of the original image is generated, and a meta-data has been curated. This modified dataset is given as input to the convolutional neural network (CNN) for classification of the images. The CNN identifies whether the x-ray image is of a COVID-19-affected person or a healthy person with accuracy measured as high as 92.24%.

Reaction of the mononuclear nonheme complex [Fe(II)(CH(3)CN)(N3PyS)]BF(4) (1) with an HNO donor, Piloty’s acid (PhSO(2)NHOH, P.A.), at low temperature affords a high-spin (S = 2) Fe(II)-P.A. intermediate (2), characterized by (57)Fe Mössbauer and Fe K- edge X-ray absorption (XAS) spectroscopies, with interpretation of both supported by DFT calculations. The combined methods indicate that P.A. anion binds as the N-deprotonated tautomer (PhSO(2)NOH(−)) to [Fe(II)(N3PyS)](+), leading to 2. Complex 2 is the first spectroscopically characterized example, to our knowledge, of P.A. anion bound to a redox-active metal center. Warming of 2 above −60 °C yields the stable {FeNO}(7) complex [Fe(NO)(N3PyS)]BF(4) (4), as evidenced by (1)H NMR, ATR-IR, and Mössbauer spectroscopies. Isotope labeling experiments with (15)N-labeled P.A. confirm that the nitrosyl ligand in 4 derives from P.A. In contrast, addition of a second equivalent of a strong base leads to S-N cleavage and production of an {FeNO}(8) species, the deprotonated analog of an Fe-HNO complex. This work has implications for the targeted delivery of HNO/ NO(−)/NO‧ to nonheme Fe centers in biological and synthetic applications, and suggests a new role for nonheme Fe(II) complexes in the assisted degradation of HNO donor molecules.

Human emotional states can be detected by various ways such as analysingthe brain signals (EEG), speech, skin responses, facial expressions, body gestures etc. But facial expressions recognition is one of the popular techniquesand easy to detect with computers using various computer visions techniques. In this work, we have proposed a new approach to detect basic facial expressions from textural images using deep learning model Convolution neural network (CNN). In the proposed approach textural images of human faces are generated using Local binary pattern(LBP) method and trained the CNN model with the LBPimages. In the proposed approach all the images of extended Cohn-Kanade(CK+)dataset are converted into LBP images that are used to train the CNN model. The performance of proposed facial expression recognition system has been validated on modifiedCK+dataset. Facial emotionRecognition Accuracy of conventional CNN model with CK+ dataset and proposed method on modified CK+ dataset is also compared.

This paper projects a new decision making model for face recognition from the original image fused with their true and partial diagonal images by integrating the type-2 fuzzy set based approach to mitigate the factors that pretend the face recognition accuracy. The G2DFLD based feature vectors corresponding to a test image are given input to neural network based classifier trained with the feature vectors of the fused images to generate the merit weights with respect to different classes (subjects) under consideration. A new scheme has been introduced in the present approach to generate a score by employing a fuzzy type-2 set based treatment. These scores with respect to each of the classes under consideration are rendered from the feature vectors of the test image and those of the diagonally fused training samples. For each class, the score is fused weighted by the corresponding merit weights to generate the concluding score. These class-wise concluding scores are deliberated in recognizing the test face image. Faces from the well-known databases (gallery) with varied pose, illumination and occlusion are used to evaluate the performance of the model. It has been found that our model exhibits more accurate classification performance than existing similar kind of image level fusion method.

A new nonheme iron(II) complex, Fe(II)(Me(3)TACN)((OSi(Ph2))(2)O) (1), is reported. Reaction of 1 with NO((g)) gives a stable mononitrosyl complex Fe(NO)(Me(3)TACN)((OSi(Ph2))(2)O) (2), which was characterized by Mössbauer (δ = 0.52 mm s(−1), |ΔE(Q)| = 0.80 mm s(−1)), EPR (S = 3/2), resonance Raman (RR) and Fe K-edge X-ray absorption spectroscopies. The data show that 2 is an {FeNO}(7) complex with an S = 3/2 spin ground state. The RR spectrum (λ(exc) = 458 nm) of 2 combined with isotopic labeling ((15)N, (18)O) reveals ν(N-O) = 1680 cm(−1), which is highly activated, and is a nearly identical match to that seen for the reactive mononitrosyl intermediate in the nonheme iron enzyme FDPnor (ν(NO) = 1681 cm(−1)). Complex 2 reacts rapidly with H(2)O in THF to produce the N-N coupled product N(2)O, providing the first example of a mononuclear nonheme iron complex that is capable of converting NO to N(2)O in the absence of an exogenous reductant.

A detailed investigation on the relative isotopic distributions has been carried out for the first time in case of even-even correlated fission fragments for the $^{235}\mathrm{U}({n}_{\text{th}},f$) fission reaction. High-statistics data were obtained in a prompt $\ensuremath{\gamma}$-ray spectroscopy measurement during the EXILL campaign at ILL, Grenoble, France. The extensive off-line analysis of the coincidence data have been carried out using four different coincidence methods. Combining the results from two-dimensional $\ensuremath{\gamma}\text{\ensuremath{-}}\ensuremath{\gamma}$ and three-dimensional $\ensuremath{\gamma}\text{\ensuremath{-}}\ensuremath{\gamma}\text{\ensuremath{-}}\ensuremath{\gamma}$ coincidence analysis, a comprehensive picture of the relative isotopic yield distributions of the even-even neutron-rich fission fragments has emerged. The experimentally observed results have been substantiated by the theoretical calculations based on a novel approach of isospin conservation, and a reasonable agreement has been obtained. The calculations following the semiempirical GEF model have also been carried out. The results from the GEF model calculations are found to be in fair agreement with the experimental results.

A nonheme {FeNO}6 complex, [Fe(NO)(N3PyS)]2+ , was synthesized by reversible, one-electron oxidation of an {FeNO}7 analogue. This complex completes the first known series of sulfur-ligated {FeNO}6-8 complexes. All three {FeNO}6-8 complexes are readily interconverted by one-electron oxidation/reduction. A comparison of spectroscopic data (UV/Vis, NMR, IR, Mossbauer, X-ray absorption) provides a complete picture of the electronic and structural changes that occur upon {FeNO}6 -{FeNO}8 interconversion. Dissociation of NO from the new {FeNO}6 complex is shown to be controlled by solvent, temperature, and photolysis, which is rare for a sulfur-ligated {FeNO}6 species.

Development of photoelectrochemical(PEC) reduction of CO2 has helped in harnessing its potential as a versatile feedstock for generation of alternative fuels. In this regard, emergence of hybrid semiconductor based photocathodes in conjunction with metal cocatalysts, metal fabrications and other photoanodes are noteworthy owing to their efficient catalytic conversion and appreciable selectivity. Since its discovery in 1978, a series of reports have been presented that helped in production of CO, HCOOH, CH3OH as well as CH4 by CO2 reduction using hybrid semiconductor based systems. This review aims to highlight some of these major developments from the past few years with the aim of fostering further scientific perception about the true potential of this research area and encouraging future research investigations.

This paper deals with an efficient method for the detection and tracking of multiple moving faces from a video sequence. Appropriate detection of multiple faces from a video sequence is a challenging task due to the different combination of noise, illuminations, pose, and locations of the human face which is likely to differ from one frame to another. This paper presents a unique technique for multiple face detection from a video sequence. In this study, our major objective is to detect and track locations of multiple faces from video using elastic window. Additionally, the face tracking system includes the tracking of face motion. Firstly, for each pixel, local entropy is calculated by considering a \( 3 \times 3 \) window for detecting the face edges. Subsequently, Gaussian filtering technique is used to eliminate the undesired edges. In this context, it may be noted that a video frame passes through a number of preprocessing steps in order to eliminate the background noise to realize the thin binary image consisting of face boundaries. The human face from video sequences can be tracked by calculating the scalar and vector distances of four corner points between two adjacent frames. The movement of corner points represents the position and location change of the face in the upcoming frame. The presented method has been tasted on several video database and obtained efficient detection and tracking of multiple faces from the video sequences.

In this paper, proficient feature extraction techniques using efficient neural networks (NN) with evidence theory for face recognition are presented. This approach is established to reduce the computation periods required by these NN. Evidence theory based single or multi biometric fusion methods have established promising performance, but they cannot handle the uncertainty appropriately, suggesting that further improvement of the performance of single biometric authentication systems. Conventional ranking is upgraded, using some associations among the outputs (belief confidence factors) of a classifier. Then, the final result is achieved by fusing results from the combined classifier output (belief confidence factors) with evidence theory. The face database usually severely affected by various degradations such as, illumination, noise and pose variations etc. which affects the overall recognition accuracy. The outcome establishes that the proposed rank-level fusion method attains superior recognition accuracy than other feature extraction and other related rank level fusion approaches.

A palladium(II)-catalyzed protocol for the highly regioselective remote γ-C–H arylation of aliphatic carboxylic acid has been disclosed. The 8-aminoquinoline moiety as an intramolecular bidentate chelator was found to be suitable for this γ-C–H arylation. Various aryl iodides successfully produced the regioselectively mono-arylated products with negligible diarylation. Functional group tolerance and easy-to-handle reaction conditions make this method attractive.

Heterocyclic compounds are commonly found in the core structures of several pharmaceuticals, natural products, and agrochemicals, thus spurring intensive research for conducting their synthesis in a mild and simpler way. Over the years, a host of different strategies has been introduced in an effort to synthesize these heterocyles. In this context, significant attention has been gained by methodologies that ensure both step as well as atom efficiency. Synthesis of heterocyclic moieties via multiple C-H activations was found to fulfill these expectations besides guaranteeing the use of starting materials that are easily procurable. This review is focused on the current development in the field of benzofuran and indole synthesis using multiple C-H functionalization strategies.

To date, cleavage of the C-N bond in aromatic amides has been achieved in molecules with a distorted constitutional framework around the nitrogen atom. In this report, a nickel-catalyzed reduction of planar amides to the corresponding lower hydrocarbon homologue has been reported. This involves a one-pot reductive cleavage of the C-N bond followed by a tandem C-CO bond break in the presence of a hydride source. Substrate scope circumscribes deamidation examples which proceed via oxidative addition of nickel in the amide bonds of nontwisted amides. Mechanistic studies involving isolation and characterization of involved intermediates via different spectroscopic techniques reveal a deeper introspection into the plausible catalytic cycle for the methodology.

The halogenation of the C-H bond by metal-oxo-peroxo species and the decarbonylation of aldehydes by metal-peroxo species are performed routinely in biological systems. However, metal-mediated decarbonylative halogenation is unknown in nature. In this work, we have shown that widely available V2O5 and VO(acac)(2) (acac=acetylacetonate) can catalyze decarbonylative halogenation through the generation of an inter-mediate vanadium-oxo-peroxo species, which was characterized by using V-51 NMR, UV/Vis, and resonance Raman spectroscopy. Further detection of formic acid from the reaction mixture confirmed the biomimetic aspects of decarbonylative halogenation. A detailed experimental and DFT study indicated a concerted mechanism for this decarbonylative halogenation performed under simple and mild reaction conditions.

Directing group assisted ortho-C-H activation has been known for the last few decades. In contrast, extending the same approach to achieve activation of the distal meta- and para-C-H bonds in aromatic molecules remained elusive for a long time. The main challenge is the conception of a macrocyclic transition state, which is needed to anchor the metal catalyst close to the target bond. Judicious modification of the chain length, the tether linkage, and the nature of the catalyst-coordinating donor atom has led to a number of successful studies in the last few years. This Review compiles the significant achievements made in this field of both meta- and para-selectivity using covalently attached directing groups, which are systematically classified on the basis of their mode of covalent attachment to the substrate as well as their chemical nature. This Review aims to create a more heuristic approach for recognizing the suitability of the directing groups for use in future organic transformations.

A nonheme {FeNO}(6) complex, [Fe(NO)(N3PyS)](2+), was synthesized by reversible, one-electron oxidation of an {FeNO}(7) analog. This complex completes the first known series of sulfur-ligated {FeNO}(6−8) complexes. All three {FeNO}(6−8) complexes are readily interconverted by one-electron oxidation/reduction. A comparison of spectroscopic data (UV-vis, NMR, IR, Mössbauer, X-ray absorption) provides a complete picture of the electronic and structural changes that occur upon interconversion between {FeNO}(6) – {FeNO}(8). Dissociation of NO• from the new {FeNO}(6) complex is shown to be controlled by solvent, temperature and photolysis, which is rare for a sulfur-ligated {FeNO}(6) species.

Owing to the synthetic importance of branched olefinated products, we report palladium catalyzed formation of branched olefins facilitated by a C-H activation based protocol. This involves selective insertion of olefins and subsequent decarboxylation using a completely unbiased benzene ring as the starting precursor. The significance of the protocol has been further highlighted by exhibition of functionality tolerance along with a late-stage modification of the branched olefinated products leading to the formation of other functionalized molecules.

This paper proposes a feature extraction technique called Gaussian probabilistic fuzzy generalized two-dimensional Fisher’s inverse linear discriminant analysis (GPFG-2DILDA) method based on fuzzy set theory, Gaussian probabilistic distribution information and inverse LDA. Like the FG-2DLDA, the proposed GPFG-2DILDA method also maximizes class separability along x- and y-axes directions simultaneously. The proposed method first calculates fuzzy membership matrix by fuzzy k-nearest neighbour (Fk-NN) algorithm. These values are combined with the training samples to obtain the global mean and class-wise mean training images. Thereafter, fuzzy membership values are integrated into intra-class and inter-class scatter matrices along both (x- and y-) directions. Similarly, Gaussian probabilistic distribution information is incorporated into the intra-class scatter matrices. Finally, by solving the eigenvalue problems of these scatter matrices, we find the optimal Gaussian-fuzzy inverse projection vectors, which actually used to generate more discriminant features and to solve the binary classification problem. The GPFG-2DILDA method has been evaluated on the AT&T face database to demonstrate the efficacy of the proposed method over some state-of-the-art face recognition methods.

In Face recognition, a combination of neural network (NN), known as an ensemble of neural network, often outperforms individual ones. This paper is aiming to present a support vector machines (SVM)-ensemble-based efficient face recognition system. The training samples are randomly chosen by means of bootstrap technique to train the different SVM independently. These SVM's are combined together to generate the ensemble SVM. The proposed method then makes a collective decision by aggregating them. It may be noted that, the performance of the practical SVM is far from the theoretical SVM as the implementations are based on approximated algorithms. The performance of the real SVM can be uplifted by using the proposed ensemble SVM with bagging (bootstrap aggregating). Finally, the proposed method takes the collective decision by aggregating the training samples. The proposed method is validated on AT&T, FERET face databases to show its supremacy over the single SVM-based methods.

Application of transition metal-catalyzed C H activation reactions to natural product synthesis is an emerging and exciting area of research that not only obviates the need for prefunctionalization of the substrates, but also bypasses multistep sequences providing opportunities for designing new retrosynthetic paradigms. The key challenges associated with this field are the compatibility and selectivity issues with polyfunctionalized substrates. Palladium-catalyzed directed functionalization of C H bonds is gaining a lot of attention as a new synthetic strategy maximizing the atom- and step-economy, and has found application in the planned synthesis of many natural products and biologically active compounds. In this chapter, we aim to highlight the recent applications of palladium-catalysis for the synthesis of complex molecular frameworks wherein C H activation was employed as a key step.