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Volume hyposensitivity resulting from impaired sympathetic detrusor relaxation during bladder filling contributes to detrusor underactivity (DU) associated with aging. Detrusor tension regulation provides an adaptive sensory input of bladder volume to the brainstem and is challenged by physiological stressors superimposed upon biological aging. We recently showed that HCN channels have a stabilizing role in detrusor sympathetic relaxation. While mature mice maintain homeostasis in the face of stressors, old mice are not always capable. In old mice, there is a dichotomous phenotype, in which resilient mice adapt and maintain homeostasis, while non-resilient mice fail to maintain physiologic homeostasis. In this DU model, we used cystometry as a stressor to categorize mice as old-responders (old-R, develop a filling/voiding cycle) or old-non-responders (old-NR, fail to develop a filling/voiding cycle; fluctuating high pressures and continuous leaking), while also assessing functional and molecular differences. Lamotrigine (HCN activator)-induced bladder relaxation is diminished in old-NR mice following HCN-blockade. Relaxation responses to NS 1619 were reduced in old-NR mice, with the effect lost following HCN-blockade. However, RNA-sequencing revealed no differences in HCN gene expression and electrophysiology studies showed similar percentage of detrusor myocytes expressing HCN (I(h)) current between old-R and old-NR mice. Our murine model of DU further defines a role for HCN, with failure of adaptive recalibration of HCN participation and intensity of HCN-mediated stabilization, while genomic studies show upregulated myofibroblast and fibrosis pathways and downregulated neurotransmitter-degradation pathways in old-NR mice. Thus, the DU phenotype is multifactorial and represents the accumulation of age-associated loss in homeostatic mechanisms.

The topic sentiment analysis is like a buzz word among researchers with the advancements in business and social network analysis. Sentiment analysis is the process of recognizing, grouping and classifying the sentiments or opinions conveyed over the social networks creating an immense measure of emotions with rich information as tweets, announcements, blog entries and more. Sentiment analysis considered to be an exceptionally valuable technique in artificial intelligence and is widely used for opinion mining and parts of speech (POS) tagging. Twitter is one among the social network with large number users expressing their thoughts or opinions in a precise and simple way. Analysis of Twitter data is complex compared to other social network data with the existence of slang words and incorrect spellings in a short sentence format. Twitter only permits a maximum of 280 characters per tweet. There were multiple approach such as knowledge based and Deep learning based approach for sentiment analysis using text data. POS is considered as one the required tools in natural language processing (NLP) and Deep learning applications. In this paper, we analyze the tweets of the individual person using hybrid deep learning (HDL) techniques. The proposed system preprocesses the input data before applying HDL techniques. Sentiment analysis in this research is applied using the five-point scale classification as highly negative, negative, neutral, positive and highly positive. The proposed work results in better accuracy and takes less time with a greater number of tweets in comparison with other extensively used models like Random forest, Naive Bayes, and decision tree classifiers. By analyzing various classifiers results in terms of accuracy and precision, ANN achieved 92% accuracy and 91.3% precision, its quite improved results than the other classifiers.

Chalcone derivatives (7a–k) have been synthesized and characterized by 1H-NMR, 13C-NMR, mass, and elemental analysis. The synthesized compounds 7a, 7d, and 7g have been examined and it is confirmed that the most promising cytotoxicity and also cell morphology analysis exhibited good apoptotic activity against lung cancer A549 cell. The free energy binding of compound 7d exhibits − 8.96 kcal/mol with five hydrogen bonding Asn1254, Arg1253, Asp1249, and Gly1123 amino acids of ALK receptors. The LUMO of the electron density present in α, β-double bond and influence the anticancer activity. The Mulliken atomic charges and MEPs are scrutinizing the ligand interaction with the amino acid binding of ALK receptors. UV-visible and photoluminescence spectra showed that the properties of chalcone derivatives have a significant effect on the visible absorption and emission maxima (531–535 nm) red shift in the emission spectra which also systematically investigated electrochemical in various solvents with increasing solvent polarity.

Texture analysis is a very predominant scope in the area of computer vision and associated fields. In this work, edge-enhanced dominant valley and discrete Tchebichef (EDV-DT) method is presented to eradicate noise and segment image into number of partitions with higher accuracy and lesser time. In EDV-DT method, an edge-enhancing anisotropic diffusion filtering technique is used to perform the preprocessing for MRI, CT and texture features. The adaptive anisotropic diffusion creates scale space and reduces the image noise without removing the texture image content (i.e., edges, lines) that is found to be essential for texture image segmentation. Followed by preprocessing, histogram dominant peak valley segmentation technique is applied to segment the localization of region of interest. Valleys in histogram for the preprocessed images help in segmenting the texture image into equal-sized texture regions. Finally, with the segmented images, discrete Tchebichef moment feature extraction is applied to extract relevant features from the segmented texture image for reducing the dimensionality. This in turn helps in improving the feature extraction rate. Further a deep convolution multinomial logarithmic-based image classification (DCML-IC) model is presented for predicting results via positive and negative fact classification. The proposed system provides the better prediction of accuracy and the prediction of time to compare the other existing methods.

An acriflavine-graphene oxide (GAF) supramolecular assembly has been prepared from water-soluble graphene oxide (GO) and a fluorescent dye, acriflavine (AF). Upon binding this non-covalently to the GO, the fluorescence of acriflavine has been "turned off" effectively, competitive binding potential of the sensor substrates such as ATP, ADP, AMP and the pyrophosphate weakens the supramolecular assembly of GAF, which allows the release of acriflavine quantitatively, which also "turns-on" the fluorescence of the dye under UV irradiation. Interestingly, GAF displayed the highest sensitivity towards ATP within the family of adenosine phosphates. We have developed a naked eye detection method for the adenosine phosphates biomolecules. For the first time, acriflavine has been utilized for the sensing of adenosine phosphates in combination with GO, which can be useful for the detection of other biomolecules.

This research work focuses to develop a fuzzy classifier model, to know the sustainability of aquatic animals and/or plants by assessing the aqua pond water quality. This model categorizes the water quality of aqua pond into four levels like as normal, acceptable, abnormal, and dangerous based on the numerical values of physical limits. The developed model is useful to forecast the pond water quality by the aqua farmers to keep up within the acceptable limits at the earliest. Data collected from five ponds are used to develop the fuzzy classifier model. The output of this model is validated using a known set of sample data. This model yields high classification performance against variation in aqua pond water quality parameters and also provides the status of pond water continuously along with a remedy to keep up the water quality.

Image clustering is one of the key technologies for image processing. Most image clustering methods based on density algorithms encountered with challenges including robust salient region extraction, cluster centre identification and noise. To address these issues, different density-based clustering methods were used. To accommodate this constraint, this paper proposes a method named Kernalized Average Entropy and Density-based Spatial Clustering (KAE-DSC). The KAE-DSC method efficiently extracts the robust salient region for texture and image database using Spatial Candidate Region Detection. Finally, Spatial Density-based Clustering with Noise is used to differentiate between core, non-core and noisy region for grouping similar region. By identifying the three different regions, efficient prediction is said to be made for the given texture and medical images. KAE-DSC method is compared with several other methods based on several evaluation indexes to testify that the proposed KAE-DSC is outperformed. Abundant experimental results proved that KAE-DSC is robust to parameters, which can automatically determine the number of clustering and improve the accuracy of clustering with minimum time complexity.

In this study, potential of the native Bacillus thuringiensis Berliner was investigated against the root knot nematode, Meloidogyne incognita (Kofoid and White) under laboratory and greenhouse conditions. Fourteen out of 50 Bt isolates obtained from root zone of vegetable crops of north western zone of Tamil Nadu, India, were found to be encoded with nematicidal cry genes, confirmed by gene-specific PCR. Nine different Cry protein profiles were obtained from native Bt. Spore-crystal mixtures of 6 isolates out of 14 (at 0.5%) showed 100% inhibition to J2 juveniles emergence from egg masses of M. incognita within 72 h of treatment. Analysis by SEM revealed that fluffy egg masses were observed in untreated samples due to hatching, whereas egg masses were covered by gelatinous matrix, when treated with spore-crystal mixture of nematicidal Bt. Two (BC and BD) of the 6 isolates were selected based on their highest nematicidal activity against J2 of M. incognita with LC50 values of 0.12 and 0.23 μg/ml of protein. The spore-crystal mixtures of isolates BC and BD when applied to tomato plants under greenhouse conditions exhibited the enhanced biocontrol potential by suppressing number of egg masses, reduction of female population and decreased root gall index, when compared to control and chemical treatments.

The (E)-2-(benzo[d]thiazol-2-yl)-3-(5-(4-(diphenylamino) phenyl) thiophen-2-yl) acrylonitrile TP1 dye has been investigated as new fluorescent chemosensor for cyanide anions. The dye TP1 acted as strong turn on fluorescent sensor after addition of the cyanide anions. Upon addition of cyanide anions to dye TP1 solution induced a change in the solution color from red to green color under the naked-eye detection. While no color change could be observed in presence of other common-anions. The detection limit of dye TP1 for cyanide anions was found to be 4.24 × 10−8 M.

Jaggery (Gur) is a natural sweetener made by concentration of sugarcane juice, contains all minerals and vitamins present in sugarcane juice. In order to utilise jaggery in place of sugar, muffins were prepared by replacing 84% sugar with 42, 63 and 84% jaggery. Different levels of eggs namely 42, 63 and 84% were also tried for jaggery muffins. The results showed that muffins prepared with 84% each of jaggery and eggs had acceptable quality characteristics. Effect of jaggery in comparison with sugar on the pasting characteristics of wheat flour, physico-sensory and storage characteristics of muffins were studied. Addition of jaggery and sugar increased pasting temperature and peak viscosity. Higher increase in pasting temperature with jaggery and in peak viscosity with sugar were observed indicating differential influence on pasting characteristics of wheat flour. The muffins with jaggery had lower pH, overall quality score and higher a(w) than muffins with sugar. During 21 days storage period, pH and a(w) decreased and titratable acidity increased for both the muffins. Even though the muffins with jaggery were less soft, showed lower overall quality score than the muffins with sugar, muffins with jaggery were acceptable and both the muffins were found to be microbiologically safe, as shown by the microbial load (total mesophilic count and yeast and mold count) in the range of 66–89 CFU/g. Hence, it can be concluded that it is possible to replace sugar with jaggery in muffins without affecting the properties of the product.

Extraction process employing Supercritical fluid carbon dioxide (SCF) yields bioactive compounds near natural forms without any artifact formation. Neem seed was subjected to SCF at different temperatures and pressure conditions. These extracts were partitioned to separate volatile fraction and were analyzed by Gas Chromatography-Mass spectroscopy along with the volatiles extracted by the hydro-distillation method. Experimental results show that there is a significant effect of pressure and temperature on isolation of a number of volatile compounds as well as retention of biologically active compounds. Twenty-five volatile compounds were isolated in the Hydro-distillate compare to the SCF extract of 100 bar, 40 °C which showed forty volatile compounds corresponds to 76.38 and 92.39% of total volatiles respectively. The majority of bioactive compounds such as Terpinen-4-ol, 1,2,4-Trithiolane, 3,5-diethyl, allyl isopropyl sulphide, Cycloisolongifolene, á-Bisabolene, (-)-α-Panasinsen, Isocaryophyllene, trans-Sesquisabinene hydrate, 1-Naphthalenol, were identified in the extract when isolated at 100 bar and 40 °C.

Cognitive radio networks being a widespread disruptive technology where idle spectrum are being analysed and made available to the unlicensed secondary users (SU) from licensed primary users (PU). During this battle of allocation of spectrum to the SU, the attackers can masquerade the network and disrupt the channels. The vulnerability attacks are more often happened based on the nature of usage of the spectrum in PU and they collect those information from secondary agent cluster, one among them is the Spectrum Sensing data falsification attack. In heterogeneous network, the vulnerabilities affect the utility of the channel and changes the information in fusion centre, where the sensing reports are might be corrupted during transmission. The paper focus on assigning the idle spectrum to be allocated based on binary stage honest based winner determination using greedy approach and the broadcasted information is secured using two phase cryptography. Besides, a rational player approach has been proposed to make the network to be susceptible to the idle environment using stochastic game modeling to prevent the attack, where a optimal solution is being estimated with nash equilibrium to identify the best response for the user to exploit the attack. The proposed mechanism is much more significantly improved duly compared with traditional mechanism and it highly improves the network performance in monitoring the induced attack and allocating the spectrum with error free transmission.

To determine the characteristics and risk factors for the development of glaucoma after cataract surgery in children seen at a major referral tertiary eye centre in South India. This is a retrospective review of the medical records of consecutive patients seen at the glaucoma/paediatric eye clinic of the centre, with a diagnosis of glaucoma secondary to aphakia/pseudophakia over a 5-year period. There were 21 eyes of 14 children that developed glaucoma and 23 eyes of 12 children were selected as control. The mean age (standard deviation SD) at the time of cataract surgery for the glaucoma group was 7.4 (± 10.1) months and 39.13 (± 41.2) months for the control. The mean follow-up (SD) period was 114.29 (± 61.9) months and 97.61 (± 43.5) months for the glaucoma and control, respectively. The mean duration from cataract surgery to onset of glaucoma was 81.19 (± 52.4) months (median 66 months, range 21–172 months). Multivariate analysis detected age at surgery younger than 12 months (OR 10.45, 95%CI 1.76–62.03, p = 0.010) and ocular anomalies mainly microcornea (OR 7.11, 95%CI 1.14–44.46, p = 0.036) as risk factors for development of glaucoma after paediatric cataract surgery. Glaucoma can develop several years after childhood cataract surgery. Surgery in the first year of life and microcornea are risk factors for the development of glaucoma post-surgery. Signs of glaucoma should specifically be looked for during follow-up visits.

Novel porous structured spinel LiNi0.5Mn1.5O4 (LNMO) microcubes have been synthesized and applied as energy storage materials for Li-ion batteries and supercapacitors. These materials are excellent candidate to replace the existing LiMn2O4 used in the commercially available lithium-ion batteries. In this report, a systematic work has been performed to study the structural and electrochemical performance of the novel porous LNMO microcubes synthesized by facile precipitation routine. Structural stability of the porous LNMO microcubes was confirmed using thermogravimetric analysis and X-ray diffraction studies. Field emission scanning electron microscopic images revealed the LNMO microcubes were uniformly distributed with an average size of ~ 163 nm. Transmission electron microscopic images were confirmed the porous LNMO microcubes morphology and Brunauer–Emmett–Teller analysis showed the specific surface area of the synthesized LNMO, which was 36.42 m2 g−1 with an excellent pore volume of 3.62 cm3 g−1 and an average pore size of 1.41 nm. Cyclic voltammetry, electrochemical impedance and charge–discharge studies were performed on the LiNi0.5Mn1.5O4 to investigate the potential application of porous LNMO microcubes in lithium-ion battery and supercapacitors. As positive electrode in Li-ion cell, the porous LNMO microcubes exhibit an excellent discharge capacity of 138.4 mA h g−1 at 1 C rate. The porous LNMO microcubes in supercapacitor was exhibited a maximum specific capacity of 294 F g−1 at 0.75 A g−1 with an excellent specific capacitance retention of 97% after 1000 cycles. The described porous LNMO microcubes are highly suitable electrode material for energy storage applications.

Thermolysis of [Cp*Ru(µ-H)BH(L)2] (Cp* = η5-C5Me5, L = C7H4NS2), (1) with [Mn2(CO)10] led to the formation of a transmetallated complex [Mn(CO)3(µ-H)BH(L)2], (2) and a ruthenium-thiolate complex [(Cp*RuCO)2(L)2], (3) in moderate yields. Compound 2 can also be generated from a direct reaction of [Mn2(CO)10] and [NaBt] (Bt = dihydrobis(2-mercaptobenzthiazolyl)borate). Although all of our attempts to generate [M(CO)3(µ-H)2BHL] (M = Mn or Re) from the bis(σ-borate) complex [Cp*Ru(µ-H)2BHL] (L = C7H4NS2), (4) were failed, thermolysis of 4 with [Mn2(CO)10] yielded a σ-borane complex [Cp*RuCO(µ-H)BH2L], (5) and a mixed-metal thiolate complex [(Cp*RuCO)2(µ3-S)Mn(CO)3L], (6). Further, the reaction of compound 5 with [Mn2(CO)10] yielded heterocyclic thiolate complex [Cp*Ru(CO)2L)], (7). Thermolysis of 4 with [Re2(CO)10] does not yield any products. However, under photolytic conditions it led to the formation of mixed-metal thiolate complex [(Cp*RuCO)Re(CO)3(L)2], (8). All the compounds have been characterized by mass spectrometry, IR, 1H, 13C spectroscopy, and the X-ray structures of 2–3 and 5–8 were unequivocally established by crystallographic analysis.

Reactivity of [Cp*Mo(CO) 3Me], 1 with various chalcogenide ligands such as Li[BH 2 E 3] and Li[BH 3EFc] (E = S, Se or Te; Fc = (C 5 H 5-Fe-C 5 H 4)) has been described. Room temperature reaction of 1 with Li[BH 2 E 3] (E = S and Se) yielded metal chalcogenide complexes [Cp*Mo(CO) 2(η 2-S 2 CCH 3)], 2 and [Cp*Mo(CO) 2(η 1-SeC 2 H 5)], 3. In compound 2, {Cp*Mo(CO) 2} fragment adopts a four-legged piano-stool geometry with a η 2-dithioacetate moiety. In contrast, treatment of 1 with Li[BH 3(EFc)] (E = S, Se or Te; Fc = C 5 H 5-Fe-C 5 H 4) yielded borate complexes [Cp*Mo(CO) 2(μ-H)(μ-EFc)BH 2], 4-6 in moderate yields. Compounds 4-6 are too unstable and gradual conversion to [{Cp*Mo(CO) 2} 2(μ-H)(μ-EFc] (7: E = S; 8: Se) and [{Cp*Mo(CO) 2} 2(μ-TeFc) 2], 9 happened by subsequent release of BH 3. All the compounds have been characterized by mass spectrometry, IR, multinuclear NMR spectroscopy and structures were unequivocally established by crystallographic analysis for compounds 2, 3 and 7.

Many bridge abutments suffered severe damages due to pounding of superstructure elements of the bridge during seismic excitation. Collision of the girder is resisted by passive pressures mobilised in the backfill soils. Seismic load on the bridge structure causes the bridge abutments to undergo lateral translation (Δ) and rotation. The present study focuses on the evaluation of passive force (Pp) developed in the reinforced backfills of the geosynthetic-reinforced soil (GRS) bridge abutments. The GRS abutments of nine configurations with three different geogrid spacing and three different geogrid lengths are modelled using finite element (FE) approach under lateral push. Hypoplastic soil constitutive model with inter-granular strain concept is used to model the soil behaviour. User material subroutine, VUMAT is developed to simulate the soil behaviour in Abaqus. The maximum passive resistance (Pp,ult) increases by 12% in the GRS abutments with closer geogrid spacing.

One of the design challenges in Wireless sensor network (WSN) is to save limited energy resource to prolong the lifetime of the network without affecting their communication connectivity or sensing coverage . In dense WSN, the sensing areas of sensor node may overlap with each other. In general, the larger the overlap of the sensing range, the more redundant data will be generated with more energy consumption. In WSN, connected dominating set (CDS) has been used for energy efficient topology control, where a virtual backbone is formed, which allows communication between any arbitrary pair of nodes in the network. Nodes which are not in CDS can go to sleep state for energy conservation. Applications related to security and reliability require a certain amount of active nodes to ensure desired level of coverage at all time. These active nodes should be connected to reduce the delay during the communication. Therefore, it is necessary to construct a fault-tolerant CDS that continues to function during node or link failure, for both coverage and connectivity requirements of WSN. In this paper, we propose k-coverage connected dominating set (k-CCDS) for connected area coverage. We also propose a weight metric named weighted coverage cost (WCC), which consists of energy of sensing neighbors. The proposed protocol selects a CDS based on WCC to ensure that every non-dominating node is connected with the CDS even if $$k-1$$k-1 dominating nodes are dead. This CDS is named k-CCDS, in which every non-dominating node is covered by atleast k dominating nodes. Simulation results show that it performs better when comparing with A3Cov in terms of CDS size, coverage, energy consumption and lifetime of the network.

Disasters create emergency situations and the services provided must be coordinated quickly via a communication network. Mobile adhoc networks (MANETs) are suited for ubiquitous communication during emergency rescue operations, since they do not rely on infrastructure. The route discovery process of on-demand routing protocols consumes too much bandwidth due to high routing overhead. Frequent route changes also results in frequent route computation process. Energy efficiency, quick response time, and scalability are equally important for routing in emergency MANETs. In this paper, we propose an energy efficient reactive protocol named Weighted-CDSR for routing in such situations. This protocol selects a subset of network nodes named Maximum Weighted Minimum Connected Dominating Set (MWMCDS) based on weight, which consists of link stability, mobility and energy. The MWMCDS provides the overall network control and data forwarding support. In this protocol, for every two nodes u and v in the network there exists a path between u and v such that all intermediate nodes belong to MWMCDS. Incorporating route stability into routing reduces the frequency of route failures and sustains network operations over an extended period of time. With fewer nodes providing overall network control and data forwarding support, the proposed protocol creates less interference and consumes less energy. The simulation results show that the proposed protocol is superior to other protocols in terms of packet delivery ratio, control message overhead, transmission delay and energy consumption.

Recently we described the synthesis and structural characterization of various dimetallaherteroborane clusters, namely nido-[(Cp?Mo)2B4ECl x H6-x ], 1-3; (1: E = S, x = 0; 2: E = Se, x = 0; 3: E = Te, x = 1). A combined theoretical and experimental study was also performed, which demonstrated that the clusters 1-3 with their open face are excellent precursors for cluster growth reaction. In this investigation process on the reactivity of dimetallaheteroboranes with metal carbonyls, in addition to [(Cp?Mo)2B4H6EFe(CO)3] (4: E = S, 6: E = Te) reported earlier, reaction of 2 with [ Fe2(CO)9] yielded mixed-metallaselenaborane [(Cp?Mo)2B4H6SeFe(CO)3], 5 in good yield. The quantum chemical calculation using DFT method has been carried out to probe the bonding, NMR chemical shifts and electronic properties of dimolybdaheteroborane clusters 4-6. [Figure not available: see fulltext.] � 2014 Indian Academy of Sciences.

Via the green chemistry route, a new class of Mn3O4 nanoparticles has been synthesized using 1-n-butyl-3-methylimidazolium trifluoromethane sulfonate [BMIM][TfO] ionic liquid, which serves as a capping agent. The thermal behavior, phase structure, morphology, and magnetic properties of the samples are characterized by thermogravimetric analysis (TGA), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), Field emission scanning electron microscopy (FE-SEM), and Vibrating sample magnetometer (VSM) studies. The phase-pure Mn3O4 nanocrystals with 40-nm narrow particle size distribution are obtained with the significant influence of ionic liquid. The synthesized Mn3O4 nanoparticles show the superparamagnetic behavior.

For the first time, solid solutions of LiMn2–X Mo X O4 nanoparticles were synthesized by combustion method at 700 °C in air. The synthesized LiMn2–X Mo X O4 (X = 0.0–0.2) nanoparticles were characterized by X-ray powder diffraction, Fourier transform infrared spectroscopy (FT-IR), Field emission-scanning electron microscopy, and Particle size analysis. The unit-cell constant is increasing from 8.237 to 8.293 A with the increase of Mo, the presence of Mo at X ≤ 0.05 in LiMn2–X Mo X O4 nanoparticles retained the spinel structure (Fd-3m), whereas on increasing the Mo (X ≥ 0.05 %), the ordering of Li+ ions in both octahedral and tetrahedral cationic position leads to the lowering of symmetry (P4132). On increasing the Mo content, prominent peak splitting and broadening are observed at 600–500 and 830 cm−1 for Li–Mn–O and Mo–O respectively in the FT-IR spectra. The TG/DTA spectrum reveals that the convenient formation of Li mangano-molybdate is at 700 °C. The voltammograms of all the samples show two redox peaks centered around 4 V except for the sample with higher Mo doping (X = 0.2). The sample with X = 0.03 shows higher redox peak current values. A marginal increase of 146 Ω R ct value was found for the LiMn1.97Mo0.03O4 nanomaterial after 10th cycle which is rather high for the rest of the materials. A discharge capacity retention of 88 % at 50th cycle is observed for X = 0.03 sample, while the other samples exhibit drastically reduced capacity. The LiMn1.97Mo0.03O4 nanoparticle can able to deliver higher and constant discharge capacity, and it may be a good alternative for the existing cathode materials.