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Abstract Retraction: [Nitin Nandkumar Sakhare, Imambi S. Shaik, Suman Saha, Prediction of stock market movement via technical analysis of stock data stored on blockchain using novel History Bits based machine learning algorithm, IET Software 2023 (https://doi.org/10.1049/sfw2.12092)]. The above article from IET Software, published online on 12 January 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor‐in‐Chief, Hana Chockler, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal’s peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.

Bioactive glass (BG) occupies a significant position in the field of hard and soft tissue regeneration. Different processing techniques and formulas have been introduced to expand their regenerative, angiogenic, and antibacterial properties. In the present study, a new formula of bborosilicate bioactive glass nanofibers was prepared and tested for its wound-healing efficacy in a rabbit animal model. The glass formula ((1–2) mol% of B2O3 (68–69) mol% of SiO2, and (29–30) mol% of CaO) was prepared primarily by the sol-gel technique followed by the electrospinning technique. The material was characterized for its ultrastructure using scanning electron microscopy, chemical composition using FTIR, and its dynamic in vitro biodegradability using ICP-AES. Twelve rabbits were subjected to surgical induction of full-thickness skin defects using a 1 cm2 custom-made stainlessteel skin punch. The bioactive glass nanofibers were used as a grafting material in 6 experimental rabbits, while the defects in the remaining rabbits were considered as the negative control samples. All defects were assessed clinically for the decrease in wound size and clinical signs of healing and histologically for angiogenesis, collagen density, inflammatory response, cell recruitment, epithelial lining, and appendages at 1,2 and 3 weeks following the intervention. Structural analysis of the glass fibers confirmed their nano-size which ranged from 150 to 700 nm. Moreover, the chemical analysis confirmed the presence of SiO2 and B2O3 groups within the structure of the nanofibers. Additionally, dynamic biodegradation analysis confirmed the rapid degradation of the material starting from the first 24 h and rapid leaching of calcium, silicon, and boron ions confirming its bioactivity. The wound healing study of the nanofibrous scaffold confirmed its ability to accelerate wound healing and the closure rate in healthy rabbits. Histological analysis of the defects confirmed the angiogenic, regenerative and antibacterial ability of the material throughout the study period. The results unveil the powerful therapeutic properties of the formed nanofibers and open a new gate for more experimental and clinical applications.

Precise physical properties of the known transiting exoplanets are essential for their precise atmospheric characterization using modern and upcoming instruments. Leveraging the large volume of high-signal-to-noise-ratio photometric follow-up data from TESS, highly precise physical properties can be estimated for these systems, especially for those discovered using ground-based instruments prior to the TESS mission. In this work, I have used the publicly available TESS follow-up data for 28 transiting systems with 10 < V _mag < 10.5, with an aim to update their known physical properties. The observed lightcurves have been analyzed by implementing a state-of-the-art critical noise treatment algorithm to effectively reduce both time-correlated and uncorrelated noise components, using sophisticated techniques like wavelet denoising and Gaussian-process regression. Compared with the previous studies, the estimated transit parameters are found to be more precise for most of the targets, including a few cases where a larger space-based instrument like Spitzer, Kepler, or CHEOPS has been used in the previous study. The large volume of transit observations used for each target has also resulted in a more accurate estimation of the physical properties, as this overcomes any error in parameter estimations from bias present in a smaller volume of data. Thus, comparing with the literature values, statistically significant improvements in the known physical properties of several targeted systems have been reported from this work. The large volume of transit-timing information from the analyses was also used to search for transit-timing variation trends in these targets, which has resulted in no significant detection.

We present the results from the first two years of the Planet Hunters Next Generation Transit Survey (NGTS) citizen science project, which searches for transiting planet candidates in data from the NGTS by enlisting the help of members of the general public. Over 8000 registered volunteers reviewed 138,198 light curves from the NGTS Public Data Releases 1 and 2. We utilize a user weighting scheme to combine the classifications of multiple users to identify the most promising planet candidates not initially discovered by the NGTS team. We highlight the five most interesting planet candidates detected through this search, which are all candidate short-period giant planets. This includes the TIC-165227846 system that, if confirmed, would be the lowest-mass star to host a close-in giant planet. We assess the detection efficiency of the project by determining the number of confirmed planets from the NASA Exoplanet Archive and TESS Objects of Interest (TOIs) successfully recovered by this search and find that 74% of confirmed planets and 63% of TOIs detected by NGTS are recovered by the Planet Hunters NGTS project. The identification of new planet candidates shows that the citizen science approach can provide a complementary method to the detection of exoplanets with ground-based surveys such as NGTS.

This paper uses a conceptual framework, the I3 Model (pronounced the ‘I-Cubed Model’), for understanding the influence of external and internal factors on eating behavior. According to the I3 Model (Instigation, Impellance and Inhibition), three processes can explain how overeating can occur. This paper provides support for the I3 Model through a field experiment and two laboratory experiments. The I3 Model sheds light on the nature of overeating when a perfect storm arises in which instigation and impellance are strong and inhibition is weak. The identification of this perfect-storm condition suggests that consumers who are seeking to avoid overeating should attune themselves to both external and internal factors and avoid these conditions of the perfect storm. Such insight boosts theoretical understanding for the phenomenon of overeating and suggests further research into the effects of situational cues in overeating.

Food waste is an important social and environmental issue that the current society faces, where one third of the total food produced is wasted or lost every year while more than 820 million people around the world do not have access to adequate food. However, as we move towards a decentralized Web 3.0 enabled smart city, we can utilize cutting edge technologies such as blockchain, artificial intelligence, cloud computing and many more to reduce food waste in different phases of the supply chain. In this paper, we propose SmartNoshWaste—a blockchain based multi-layered framework utilizing cloud computing, QR code and reinforcement learning to reduce food waste. We also evaluate SmartNoshWaste on real world food data collected from the nosh app to show the efficacy of the proposed framework and we are able to reduce food waste by 9.46% in comparison to the originally collected food data based on the experimental evaluation.

Geopolymer composites provide an environmentally friendly alternative to cement-based composites in the construction industry. Due to their distinctive material composition, geopolymers also exhibit electrically conductive properties, which permit their application as a functional material. The current work aims to study the distinctive electrical properties of fly-ash-based geopolymer composites. Varying dosages of graphene oxide (i.e., 0, 0.1, 0.2, 0.3, 0.4% (by wt. of binder)) were introduced into the geopolymer matrix to enhance electrical conductivity. While GO (graphene oxide) is typically less conductive, the interaction of GO sheets with the alkaline solution during geopolymerisation reduced the functional groups and produced cross-linked rGO (reduced graphene oxide) sheets with increased mechanical and electrical conductivity properties. Solid-state impedance spectroscopy was used to characterize the electrical properties of geopolymer composites in terms of several parameters, such as impedance, electrical conductivity and dielectric properties, within the frequency ranging from 101 to 105 Hz. The relationship between the electrical properties and graphene oxide reinforcement can effectively establish geopolymer composite development as smart materials with desirable functionality. The results suggest an effective enhancement in electrical conductivity of up to 7.72 × 10−13 Ω⋅mm−1 and the dielectric response performance of graphene-reinforced fly-ash-based geopolymer composites.

Traditional stock movement prediction tasks are formulated as either classification or regression task, and the relation between stocks are not considered as an input of prediction. The relative order or ranking of stocks is more important than the price or return of a single stock for making proper investment decisions. Stock ranking performance can be improved by incorporating the stock relation information in the prediction task. We employ a graph-based approach for stock ranking prediction and use the stock relation information as the input of the machine learning model. Investors might be interested in the prediction performance of top- $k$ stocks as they would be more profitable than the others. Thus, the performance measure for stock ranking prediction should be top-weighted and bounded for any value of $k$ . Existing evaluation measures lack these properties, and we propose a new measure named normalized rank biased overlap for top- $k$ ( $NRBO\text{@}k$ ) stocks for stock ranking prediction. $NRBO\text{@}k$ -based investment strategy generates 0.281% to 4.928% higher relative investment gain than the topmost stock-based strategy. We show that the list-wise loss function can improve the stock ranking performance significantly in a graph-based approach. It generates better $NRBO\text{@}10$ than the combination of point-wise and pair-wise loss in three out of four cases. Node embedding techniques such as Node2Vec can reduce the training time of graph-based approaches for stock ranking prediction significantly. Additionally, we improve the prediction performance through hyperparameter tuning of Node2Vec when a sparse stock relation graph is applied.

Autism is a group of neurodevelopment disorders characterized by impaired communication, impaired social interaction and restricted, repetitive and stereotyped patterns of behaviours or interests in the first 3 years of life. It shows a strong male bias and found four times more in males than in females. According to a study in the US, in 2014, overall 1.68% of victims were reported to have Autism Spectrum Disorder (ASD), whereas the percentage was increased by 15% and 150% respectively over the year 2012 and 2000. Numerous genes have been discovered that have roles in ASD but still a good understanding of the pathophysiological process of ASD is not established. ASD costs are estimated to be approximately $250 billion annually in the U.S. Moreover, it is suggested that by 2025, ASD costs will rise to over $450 billion. Thus, the financial burden on families is increasing. There is no effective screening tool for proper diagnosis is available. Based on Infant Toddler Checklist (ITC) and Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5) some tests like ADOS-G, ADI-R, CARS etc. are used for diagnosis. There are medications to cure symptoms but no single medication for ASD. However, some therapies (like ABA- Applied Behavioural Analysis, DTT- Discrete Trial Training, and Symptomatic treatments, etc.) are there that show positive responses towards improvement from a disease state. Some crucial advancement has been achieved in the last decades. Here in the work we have focused on the diagnostic methods and treatment available for the symptoms of Autism. So, it can be said that the day is not too far away when the remedy to cut the curse of autism will be in our hands.

The Transiting Exoplanet Survey Satellite (TESS) follow-up of a large number of known transiting exoplanets provides a unique opportunity to study their physical properties more precisely. Being a space-based telescope, the TESS observations are devoid of any noise component resulting from the interference of Earth’s atmosphere. TESS also provides a greater probability to observe subsequent transit events owing to its longer uninterrupted time-series observations compared to ground-based telescopes. For the exoplanets around bright host stars in particular, TESS time-series observations provide high signal-to-noise ratio (S/N) lightcurves, which can be used for higher-precision studies for these exoplanets. In this work, I have studied the TESS transit photometric follow-up observations of 28 exoplanets around bright stars with V _mag ≤ 10. The already high-S/N lightcurves from TESS have been further processed with a critical noise-treatment algorithm, using the wavelet-denoising and the Gaussian-process regression techniques, to effectively reduce the noise components, both correlated and uncorrelated in time, which were then used to estimate the physical properties of these exoplanets. The study has resulted in very precise values for the physical properties of the target exoplanets, with the improvements in precision being significant for most of the cases compared to the previous studies. Also, since a comparatively large number of transit lightcurves from TESS observations were used to estimate these physical properties for each of the target exoplanets, which removes any bias due to the lack of sufficient data sets, these updated physical properties can be considered extremely accurate and reliable for future studies.

Acute interface infectious keratitis (AIIK) is a rare and devastating complication following lamellar keratoplasty. Here, we report a case of AIIK following deep anterior lamellar keratoplasty (DALK) caused by double gram-negative bacilli and required urgent therapeutic penetrating keratoplasty (TPK). Microbiology revealed co-infection with Klebsiella and E. Coli sensitive only to colistin. Donor rim culture also grew Klebsiella. TPK was successful in controlling the infection and the patient responded to topical fortified amikacin and ciprofloxacin. Since optical quality tissue was used, the patient regained 20/40 vision postoperatively. This report highlights that immediate TPK and intense antimicrobial therapy can salvage these eyes with good visual outcome.

Instead of tremendous advancements in drug delivery, the oral route remains the most preferred route for the administration of therapeutic agents because of the low cost of therapy and ease of administration that leads to high levels of patient concordance. Incorporating an existing medicine into Newer Drug Delivery System (NDDS) are gaining popularities. One such approach is to formulate Immediate Release Tablet, which dissolve or disintegrate rapidly in saliva without the need of water within few seconds due to action of superdisintegrant in the formulation or other novel manufacturing technique. The demand for orally disintegrating tablets has enormously increased during the last decade over the other oral dosage forms (such as tablets, capsules, dry syrups, chewing gums, chewable tablets etc.) particularly for geriatrics and pediatrics, travelers, dysphasics, psychotics and non-cooperative patients. Considering the advantages of Immediate Release Tablet and its growing demand, an attempt has been made through this article to give an overview of preparation and new methodologies for the Immediate Release Tablet followed currently and in past including some patient information.

Most modern mobile cyber-physical systems such as smartphones come equipped with multi-processor systems-on-chip (MPSoCs) with variant computing capacity both to cater to performance requirements and reduce power consumption when executing an application. In this paper, we propose a novel approach to dynamic voltage and frequency scaling (DVFS) on CPU, GPU and RAM in a mobile MPSoC, which caters to the performance requirements of the executing application while consuming low power. We evaluate our methodology on a real hardware platform, Odroid XU4, and the experimental results prove the approach to be 26% more power-efficient and 21% more thermal-efficient compared to the state-of-the-art system.

This study is about a tablet, which disintegrates or dissolves quickly when placed in the oral cavity. Studies on formulation development of Salbutamol Sulphate Immediate Release Tablet, suitable for manufacturing by direct compression have been carried out. Trial formulations using various excipients were developed and evaluated for various qualities like hardness, friability, disintegration time, content uniformity and dissolution. Study concluded that Immediate Release Tablet of Salbutamol Sulphate can be prepared successfully with added patient benefit and increased consumer satisfaction.

Glioblastoma multiform (GBM) is a heterogeneous group of primary neoplasm resistant to conventional therapies. Due to their infiltrative nature it not fully isolated by aggressive surgery, radiation and chemotherapy showing poor prognosis in glioma patients. Unfortunately, diagnosed patients die within 1.5-2 year treatment schedule. Currently temozolomide (TMZ) is the first choice for the prognosis of GBM patients. TMZ metabolites methyl triazen imidazol carboxamide form complex with alkyl guanine alkyl transferase (O6 MGMT- DNA repair protein) induced DNA damage following resistance properties of TMZ and inhibit the overall survival of the patients. Last few decades different TMZ conjugated strategy is developed to overcome the resistance and enhance the chemotherapy efficacy. The main aim of this review is to introduce the new promising pharmaceutical candidates that significantly influence the therapeutic response of the TMZ in context of targeted therapy of glioblastoma patients. It is hoped that this proposed strategy are highly effective to overcome the current resistance limitations of TMZ in GBM patients and enhance the survival rate of the patients.

In ecological landscapes, species tend to migrate between nearby patches in search of a better survivability condition. By this dispersal process, they form connectivity between the patches and thereby may develop various correlated or partially correlated population dynamics among species living in the patches. We explore various possible emergent collective population patterns using a simple ecological network model of all-to-all connected patches where we use a particular type of dispersal process that is controlled by a weighted mean-field diffusion to include the failed migration between the interacting patches. We represent the population dynamics of both the predator and prey in each patch by a modified Rosenzweig-MacArthur (mRM) model that incorporates an additional effect of habitat complexity. Our theoretical investigations on the network dynamics, using numerical and to some extent, analytical techniques, show various complex patterns, namely, 2-cluster, 3-cluster and multicluster states, and chimera states, besides synchrony (1-cluster) and homogeneous steady states (HSS) in a migrating metapopulation. An important observation is that addition of habitat complexity in the Rosenzweig-MacArthur (RM) model makes qualitative changes in the collective behaviors. Especially to mention that it shrinks the region of synchrony and broadens the region of HSS, in parameter space and, thereby leads to better survival probabilities and increased population persistence in a natural ecosystem.

Notable research in drug delivery started in 1950’s with the advent of polyclonal antitumor antibodies developed for targeting. Bangham et. Al. discovered liposomes in early 1960’s. In this review article we are discussing about the liposome, methods of the liposome preparation advantages and their different application of the liposome. Liposomes are artificially prepared vesicles made of lipid bilayer. Liposomes can be filled with drugs, and used to deliver drugs for cancer and other diseases. Liposome is used for the targeted drug delivery system and increase the bioavailability and half life of the any drugs. Liposomes are surfactants, sphingolipids, glycol-lipids, long chain fatty acids and even membrane proteins and drug molecules or it is also called vesicular system. Liposomes have been extensively investigated for drug delivery, drug targeting, controlled release and increased solubility.

We report our investigation and success story, to an extent, on the prediction of spiking and bursting dynamics in globally coupled networks, using echo state network/reservoir computing-based learning procedure. Two exemplary dynamical models, Josephson junctions and Hindmarsh-Rose neurons, are used to construct two separate networks and thereby illustrate the efficacy of our strategy. In the absence of coupling, the networks consist of mixed populations in which few nodes are oscillatory (self-sustained spiking) and the rest of the nodes maintain a quiescent state. When single-input data from one oscillatory node of a network (under stronger interactions between the nodes) is used for learning, the ESN is able to predict the key dynamical features (spiking and bursting) of the other nodes. In comparison, the machine performs with improved predictions if it is fed with two inputs: one from the oscillatory population and another from an excitable population. The machine's leaking parameter plays a crucial role, which can be tuned appropriately to enhance prediction. Furthermore, a cluster synchronization in the mixed population is confirmed from the machine-generated output signals. Our work is expected to be useful as a burst predictor.

Gallbladder malignancy is frequently found in Indian population. Most of them are adenocarcinoma variety whereas carcinosarcoma variety is quite rare. It is typically characterised by presence of both epithelial and mesenchymal components. The prognosis of this variety is poorer because of its aggressive nature and delayed diagnosis. Here we report a case of Carcinosarcoma of Gallbladder (CSGB) in a 40-year-old lady presenting to us with features of acute cholecystitis and gallbladder mass. She was treated with radical cholecystectomy, bile duct excision and Roux-en-Y Hepaticojejunostomy (RYHJ). Histopathological examinations reveal pleomorphic spindle cells as well as epitheloid cell. In postoperative period she received adjuvant chemotherapy. Despite all these treatment she developed recurrence at seven months follow up.

Community detection in a complex network is an important problem of much interest in recent years. In general, a community detection algorithm chooses an objective function and captures the communities of the network by optimizing the objective function, and then, one uses various heuristics to solve the optimization problem to extract the interesting communities for the user. In this article, we demonstrate the procedure to transform a graph into points of a metric space and develop the methods of community detection with the help of a metric defined for a pair of points. We have also studied and analyzed the community structure of the network therein. The results obtained with our approach are very competitive with most of the well-known algorithms in the literature, and this is justified over the large collection of datasets. On the other hand, it can be observed that time taken by our algorithm is quite less compared to other methods and justifies the theoretical findings.

The purpose of the present work was to develop optimized novel enteric microcapsules containing diclofenac sodium, a non steroidal anti inflammatory drug (NSAID) used for rheumatoid arthritis, for improved delivery and to diminish its adverse effect after oral administration. The microcapsule was prepared by using different polymers and the enteric coating was provided by using an innovative technique combining wet granulation method and thermal change method. This work also investigated different levels of enteric polymers like cellulose acetate phthalate (CAP) (X1) and ethyl cellulose (EC) (X2) and the stirring speed during coating ethyl cellulose (X3), by using 23 full factorial design. The dependent variables assessed were % yield (Y1), Q8 (% drug released after 8 hour) (Y2), n (Diffusion coefficient) (Y3), DEE (Drug entrapment efficiency) (Y4). The main effect and interaction terms were quantitatively evaluated using a mathematical model. The prepared microcapsules were evaluated for percentage drug dissolved, scanning electron microscopy, drug excipient interaction, angle of repose, particle size. Mean dissolution time (MDT) was used to compare dissolution patterns obtained. The results showed that X1 and X2 significantly affected the release properties.

More than 40 percent of newly discovered drugs have little or no water solubility thus the present research aimed at the study of improvement of solublisation on dissolution by addition of different solublising agents and modification of methods. Irbesartan is the drug of choice. Effect of Solubility on dissolution was studied with some solubilizing agents like β-Cyclodextrins, PEG-6000, Polysorbate-80, Cremophore and Resins (Doshion). It was seen that Irbesartan give 90 percent release in 1hr with polysorbate-80 where cremophore containing tablets showed 97 % release in 1 hr in case of solid dispersion technique and in case of complexation technique respectively. Thus the present study concluded that, dissolution rate of poorly soluble drug can be increases by using solubilizing agent as well as using different techniques

The main objective of this review article is to overcome or to improve the problems related with curcumin with the help of new technologies or modifications to make a promising therapeutic agent which gives a good therapeutic response. Curcumin, a known natural polyphenolic compound obtained from dietary spice turmeric, possesses pharmacologic effects including anti-inflammatory, antioxidant, and many other activities. Clinical trials on curcumin have shown its safety and efficacy even at high doses in humans. But inspite of that it shows poor bioavailability (oral bioavailability) which is one of the major problems regarding curcumin. There are other reasons contributing to the low plasma and tissue levels of curcumin appear to be due to poor absorption, rapid metabolism, and rapid systemic elimination. To improve the bioavailability of curcumin, numbers of approaches have been undertaken. These approaches involve, first, the use of adjuvant like piperine that interferes with glucuronidation; second, the use of liposomal curcumin; third, curcumin nanoparticles; fourth, the use of curcumin phospholipids complex; and fifth, the use of structural analogues of curcumin.

Rhodotorula mucilaginosa rarely cause keratitis in immunocompromised individuals. A 30 year old male with history of minor trauma presented with cotton wool like stromal infiltration and hypopyon in left eye. Microbiological examination of corneal scraping showed fungal hyphae and yeast cells in direct smear. Molecular identification of the organism was performed which showed 100% homology with Rhodotorula mucilaginosa. Management of these cases is difficult often necessitating surgical procedures. However further reports are necessary to understand the disease and establish a treatment protocol.

Background: Microsporidia are intracellular parasites responsible for human infections. Recently, there has been an increase in the incidence of microsporidial keratoconjunctivitis (MKC) affecting normal individuals worldwide. Aim: To determine the characteristics of MKC in an Indian cohort. Materials and Methods: This is a retrospective, noncomparative, observational case series, involving patients with MKC between June and September 2009. Of the 24 patients identified, microbiological confirmation in direct smear was obtained in 22 cases and selected. Standard microbiological workup was performed in all the cases. We studied the demographics, predisposing conditions, antecedent treatment received before presentation, clinical characteristics, treatment offered, and resolution time with sequel. The management consisted of simple debridement and application of chloramphenicol ointment (1%) two times a day. Results: Mean age of onset was 18.7 years (95% CI, 15.7-21.7; range, 11-36s years). All patients gave history of prior outdoor activity and exposure to rain water/mud. Antecedent treatment comprised of Acyclovir eye ointment (45.4%) and antibiotic eye drop (27.3%) most commonly. Microsporidia were identified in Gram stain (81.8%), 10% potassium hydroxide mount (72.7%), modified Ziehl-Neelsen staining (36.4%), and Giemsa (18.2%). Majority presented as unilateral superficial keratoconjunctivitis with punctate epithelial keratitis. Mean resolution time was 9 days (95%CI, 7.9-10.2). Conclusions: MKC can occur in normal patients with exposure to rain and mud, related to outdoor activity often misdiagnosed as viral ocular infections. Strong clinical suspicion with proper microbiological evaluation helps to diagnose this commonly misdiagnosed condition.

Background : Corneal diseases are one of the major causes of visual loss and blindness, second only to cataract. Amongst corneal diseases, microbial keratitis is a major blinding disease. In some countries, fungal keratitis accounts for almost 50% of patients with culture-proven microbial keratitis. Aim : This study was conducted to determine the epidemiological characteristics of fungal keratitis in an urban population of West Bengal and identify the specific pathogenic organisms. Methods : The charts of patients with microbial keratitis who attended the Cornea Services of Priyamvada Birla Aravind Eye Hospital from January to December 2008 were retrospectively reviewed. Records of patients with 10% KOH mount and culture positive fungal keratitis were analyzed for epidemiological features, laboratory findings and treatment outcomes. Results : Of the 289 patients of microbial keratitis included in the study, 110 patients (38.06%) were diagnosed with fungal keratitis (10% KOH mount positive). Of the 110 patients, 74 (67.27%) fitted the study inclusion criteria (10% KOH mount and culture positive). Forty five of 74 patients (60.81%) in the study group were in the older age group (>50 years). Ocular trauma in 35 cases (47.29%) was identified as a high risk factor and vegetative injuries in 17 cases (22.97%) were identified as a significant cause for fungal keratitis. Maximum organism source was from corneal scrapings in 41 cases (55%). The predominant fungal species isolated was Aspergillus sp (55.40%) followed by Candida albicans 14 cases (18.91%) and Fusarium sp. in 8 cases (10.81%). Agricultural activity related ocular trauma was the principal cause of mycotic keratitis and males were more commonly affected. Thirty of 74 cases (40.55%) of the culture positive patients healed with corneal scar formation with medical treatment whereas 44 cases (59.45%) required therapeutic keratoplasty. Conclusion : Fungal keratitis is an important cause of microbial keratitis with injury to the cornea being a leading predisposing factor. Although Aspergillus sp. was implicated in most of the patients in our study population, Candida sp. were found in higher numbers than previously reported. Keratitis caused by filamentous fungi responds adequately to medical management. Therapeutic keratoplasty continues to remain an important treatment modality in infections with Candida sp. Early diagnosis with prompt identification of the pathogenic organism is mandatory to initiate appropriate therapy and thereby reduce morbidity.

Keratitis treatment has become more complicated due to the emergence of bacterial or fungal pathogens with enhanced antibiotic resistance. The pharmaceutical applications of N-heterocyclic carbene complexes have received remarkable attention due to their antimicrobial properties. In this paper, the new precursor, 3,3'-(p-phenylenedimethylene) bis{1-(2- methyl-allyl)imidazolium} bromide (1a) and its analogous PF6 salt (1b) were synthesized. Furthermore, silver(I) and gold(I) -N-heterocyclic carbene (NHC) complexes [Ag2LBr2/Au2LBr2; 2a/3a], [(Ag2L2)(PF6)2/(Au2L2)(PF6)2; 2b/3b] were developed from their corresponding ligands. All compounds were screened for their antimicrobial activities against multiple keratitis-associated human eye pathogens, including bacteria and fungi. Complexes 2a and 3a showed highest activity, and the effectiveness of 3a was also studied, focusing eradication of pathogen biofilm. Furthermore, the structures of 1a, 2a and 3b were determined using single crystal X-ray analysis, 2b and 3a were optimized theoretically. The mechanism of action of 3a was evaluated by scanning electron microscopy and docking experiments, suggesting that its target is the cell membrane. In summary, 3a may be helpful in developing antimicrobial therapies in patients suffering from keratitis-associated eye infections caused by multidrug-resistant pathogens.

We report here a case of a 32-year old female with a history of minor trauma presented with total corneal ulcer and hypopyon in the left eye. Microbiological examination of corneal scraping showed refractile hyphae with asepted branching filaments and black pigmented colonies in multiple solid agar medium. Identification of the organism was made from culture using D1/D2 region of Large Sub Unit (28S rDNA) based molecular technique. Polymerase chain reaction amplified a band with a sequence that was 100% homologous with Lasiodiplodia theobromae. The organism was sensitive to amphotericin B and voriconazole, and demonstrated resistance to itraconazole and fluconazole. Therapeutic keratoplasty was performed followed by recurrence in graft controlled with topical voriconazole and intracameral amphotericin B. Graft failure was reported after three months.

The objective of this article is to bridge the gap between two important research directions: (1) nearest neighbor search, which is a fundamental computational tool for large data analysis; and (2) complex network analysis, which deals with large real graphs but is generally studied via graph theoretic analysis or spectral analysis. In this article, we have studied the nearest neighbor search problem in a complex network by the development of a suitable notion of nearness. The computation of efficient nearest neighbor search among the nodes of a complex network using the metric tree and locality sensitive hashing (LSH) are also studied and experimented. For evaluation of the proposed nearest neighbor search in a complex network, we applied it to a network community detection problem. Experiments are performed to verify the usefulness of nearness measures for the complex networks, the role of metric tree and LSH to compute fast and approximate node nearness and the the efficiency of community detection using nearest neighbor search. We observed that nearest neighbor between network nodes is a very efficient tool to explore better the community structure of the real networks. Several efficient approximation schemes are very useful for large networks, which hardly made any degradation of results, whereas they save lot of computational times, and nearest neighbor based community detection approach is very competitive in terms of efficiency and time.