Search

Triple-negative breast cancer (TNBC) poses a significant global health challenge due to its highly aggressive nature and invasive characteristics. Dysregulation of the Hippo pathway, a key regulator of various biological processes, is observed in TNBC, and its inhibition holds promise for impeding cancer growth. This in-silico analysis investigates the role of Transcriptional Enhanced Associate Domain 4 (TEAD4) in TNBC and its interaction with Yes Associated Protein (YAP) in cancer progression. Our results demonstrate that TEAD4 upregulation is linked to poor prognosis in TNBC, emphasizing its critical role in the disease. Moreover, we identify CID44521006, an analog of Flufenamic acid, as a potential therapeutic compound capable of disrupting the TEAD4-YAP interaction by binding to the YAP-binding domain of TEAD4. These findings underscore the significance of TEAD4 in TNBC and propose CID44521006 as a promising candidate for therapeutic intervention. The study contributes valuable insights to advance treatment options for TNBC, offering a potential avenue for the development of targeted therapies against this aggressive form of breast cancer. [ABSTRACT FROM AUTHOR]

The demand for reliable and efficient gas sensors is increasing due to the growing emphasis on safety in both residential and workplace environments. This study presents a unique approach to improving the effectiveness of liquefied petroleum gas (LPG) sensors. It involves utilizing a composite material consisting of graphene modified with iron nanoparticles (FeNPs) as the gas-sensing material. Main objective of the proposed work is to synthesis Fe-modified Graphene nanoparticles by chemical route synthesis method for different molar concentrations of Fe using a fast and a simple method and to Study the influence of Graphene decorated with Fe nanoparticles with the help of the sensor specification characteristics of this material for different gases and different characterization techniques. This study employs the modified Hummers method to fabricate graphene with exceptional electrical conductivity. Furthermore, a chemical synthesis route has been employed to produce graphene sensors that are modified with Fe NPs at various molar concentrations. The confirmation of the successful integration of Fe NP-modified graphene composite was assessed through the utilization of sophisticated methodologies including scanning electron microscopy (SEM), X-ray diffraction pattern (XRD), Fourier transform infrared spectroscopy (FTIR), Ultraviolet–visible spectroscopy (UV–Vis), and photoluminescence spectroscopy, respectively. This study investigates the gas-sensing capabilities of Fe-modified graphene for LPG at different concentrations and temperatures. At a temperature of 310 K, the 2.0 M Fe-modified graphene pellet exhibited a peak response of 65% when exposed to LPG with a concentration of 500 ppm. The graphene sensor, modified with Fe, demonstrates exceptional selectivity for LPG gas and possesses remarkable repeatability, stability, and rapid response time. The findings indicate that the suggested graphene-based LPG sensor, modified with Fe NPs, exhibits significant promise in fulfilling the growing demand for advanced gas detection technologies in both residential and commercial environments. Additional research endeavors could concentrate on enhancing the design of the sensor, exploring novel metal combinations, and extending its application to other gas detection applications. [ABSTRACT FROM AUTHOR]

The present study was aimed at the identification of population stratifying markers from the commercial porcine SNP 60K array and elucidate the genome-wide selective sweeps in the crossbred Landlly pig population. Original genotyping data, generated on Landlly pigs, was merged in various combinations with global suid breeds that were grouped as exotic (global pig breeds excluding Indian and Chinese), Chinese (Chinese pig breeds only), and outgroup pig populations. Post quality control, the genome-wide SNPs were ranked for their stratifying power within each dataset in TRES (using three different criteria) and FIFS programs and top-ranked SNPs (0.5K, 1K, 2K, 3K, and 4K densities) were selected. PCA plots were used to assess the stratification power of low-density panels. Selective sweeps were elucidated in the Landlly population using intra- and inter-population haplotype statistics. Additionally, Tajima's D-statistics were calculated to determine the status of balancing selection in the Landlly population. PCA plots showed 0.5K marker density to effectively stratify Landlly from other pig populations. The A-score in DAPC program revealed the Delta statistic of marker selection to outperform other methods (informativeness and FST methods) and that 3000-marker density was suitable for stratification of Landlly animals from exotic pig populations. The results from selective sweep analysis revealed the Landlly population to be under selection for mammary (NAV2), reproductive efficiency (JMY, SERGEF, and MAP3K20), body conformation (FHIT, WNT2, ASRB, DMGDH, and BHMT), feed efficiency (CSRNP1 and ADRA1A), and immunity (U6, MYO3B, RBMS3, and FAM78B) traits. More than two methods suggested sweeps for immunity and feed efficiency traits, thus giving a strong indication for selection in this direction. The study is the first of its kind in Indian pig breeds with a comparison against global breeds. In conclusion, 500 markers were able to effectively stratify the breeds. Different traits under selective sweeps (natural or artificial selection) can be exploited for further improvement. [ABSTRACT FROM AUTHOR]

The use of hygienic materials (sanitary napkins, locally prepared napkins, tampons, and menstrual cups) during menstruation among adolescent women in India has improved over the years, yet a significant rural–urban gap in the usage persists at the national level. This study investigates how this rural-urabn gap varies across different states and union territories (UTs) of India and uses Fairlie decomposition to quantify the contribution of various factors to this gap. The study uses data on 114,805 adolescent women (aged 15–19 years) from the fifith round of National Family Health Survey (2019–21). The utilization of hygienic materials during menstruation among adolescent women in rural India stood at 43%, whereas in urban areas, it was 68%, indicating a significant 25 percentage point (pp) difference between the two. The rural–urban gap in the hygienic material use varied significantly across Indian states and UTs. The gap exceeded 20 pp in Madhya Pradesh (36 pp), Odisha (26 pp), Jammu and Kashmir (25 pp), Assam (25 pp), Uttar Pradesh (23 pp), Jharkhand (22 pp), Chhattisgarh (21 pp), and Rajasthan (21 pp). In contrast, the gap in Tamil Nadu, Himachal Pradesh, and Telangana was less than 10 pp. The decomposition analysis of the rural–urban gap (25 pp) revealed that the variables included in the anlaysis explained about 70% of the gap. The difference in the household wealth between rural and urban areas contributed about 69% of the explained gap. Other significant contributors to the explained gap were 'transportation to health facility' (5.6%), 'mass-media exposure' (4.9%), and 'level of education (4.4%). The findings underscore the necessity for state-specific interventions aimed at vulnerable groups, particularly individuals from economically disadvantaged backgrounds, those with lower levels of education, and limited exposure to mass media, in order to reduce the existing rural–urban disparity in hygienic material use among adolescent women. [ABSTRACT FROM AUTHOR]

Plant ATP-binding cassette (ABC) protein family is the largest multifunctional highly conserved protein superfamily that transports diverse substrates across biological membranes by the hydrolysis of ATP and is also the part of the several other biological processes like cellular detoxification, growth and development, stress biology, and signaling processes. In the agriculturally important legume crop Cajanus cajan, a genome-wide identification and characterization of the ABC gene family was carried out. A total of 159 ABC genes were identified that belong to eight canonical classes CcABCA to CcABCG and CcABCI based on the phylogenetic analysis. The number of genes was highest in CcABCG followed by CcABCC and CcABCB class. A total of 85 CcABC genes were found on 11 chromosomes and 74 were found on scaffold. Tandem duplication was the major driver of CcABC gene family expansion. The dN/dS ratio revealed the purifying selection. The phylogenetic analysis revealed class-specific eight superclades which reflect their functional importance. The largest clade was found to be CcABCG which reflects their functional significance. CcABC proteins were mainly basic in nature and found to be localized in the plasma membrane. The secondary structure prediction revealed the dominance of α-helix. The canonical transmembrane and nucleotide binding domain, signature motif LSSGQ, Walker A, Walker B region, and Q loop were also identified. A class-specific exon-intron pattern was also observed. In addition to core elements, different cis-acting regulatory elements like stress, hormone, and cellular responsive were also identified. Expression profiling of CcABC genes at various developmental stages of different anatomical tissues was performed and it was noticed that CcABCF3, CcABCF4, CcABCF5, CcABCG66, and CcABCI3 had the highest expression. The results of the current study endow us with the further functional analysis of Cajanus ABC in the future. [ABSTRACT FROM AUTHOR]

Universal quantum computation can be realised using both continuous-time and discrete-time quantum walks. We present a version based on single particle discrete-time quantum walk to realize multi-qubit computation tasks. The scalability of the scheme is demonstrated by using a set of walk operations on a closed lattice form to implement the universal set of quantum gates on multi-qubit system. We also present a set of experimentally realizable walk operations that can implement Grover's algorithm, quantum Fourier transformation and quantum phase estimation algorithms. An elementary implementation of error detection and correction is also presented. Analysis of space and time complexity of the scheme highlights the advantages of quantum walk based model for quantum computation on systems where implementation of quantum walk evolution operations is an inherent feature of the system. [ABSTRACT FROM AUTHOR]

Purpose: Essential metals may be crucial in obesity and type 2 diabetes (T2DM); diabesity pathogenesis and consequences. This study aimed to determine the metal levels in obese and non-obese patients with and without T2DM and their relationships with fetuin-A(Fet-A) levels, insulin sensitivity, and insulin resistance. Methods: A total of 314 participants were enrolled, with 160 newly diagnosed T2DM patients and 154 non-T2DM subjects categorized into diabetic obese (n = 57), diabetic non-obese (n = 103), non-diabetic obese (n = 48), and non-diabetic non-obese (n = 106) subgroups. Fet-A, insulin sensitivity (QUCKI)/resistance (HOMA-IR), fasting glucose, and body mass index (BMI) were assessed. The essential metals were measured using inductively coupled plasma mass spectroscopy (ICP-MS). Results: Fet-A levels were 3-fold higher (1391.4 ± 839.8 ng/ml) in T2DM patients than in non-T2DM (2165.6 ± 651.9 vs. 424.3 ± 219.1 ng/ml, p < 0.0001). Fet-A levels were 2.3-fold higher in the diabetic obese group than in the diabetic non-obese group (p < 0.0001). Fet-A levels were 2.0-fold higher in the diabetic non-obese group than in the non-diabetic obese group (p < 0.0001). Fet-A levels were positively correlated with insulin resistance (HOMA-IR) (r = 0.34, p < 0.0001) and negatively correlated with insulin sensitivity (QUIKI) (r = −0.41, p < 0.0001). Cu, Se, Zn, and Fe levels were significantly lower in diabetic patients than in non-diabetic patients (p < 0.05). Se and Zn were significantly correlated with Fet-A (r = −0.41, p = 0.049 and r = −0.42, p = 0.001, respectively). Se and Zn were also correlated with insulin resistance (HOMA-IR) (r = −0.45, p = 0.049 and r = −0.36, p = 0.012, respectively) and insulin sensitivity (QUIKI) (r = 0.49, p = 0.042 and r = 0.30, p = 0.003, respectively). Similarly, Fe was negatively correlated with insulin levels (r = −0.33, p = 0.04) and insulin sensitivity (r = −0.34, p = 0.30). However, Mn was significantly correlated with Fet-A (r = 0.37, p = 0.001) and insulin resistance/sensitivity (r = 0.24, p = 0.026 and r = −0.24, p = 0.041) respectively in the diabetic obese group. Mg was an independent predictor of diabesity. Conclusions: Mg play a significant role in obesity-related T2DM pathogenesis and complications via Fet-A, insulin sensitivity, and resistance modifications. [ABSTRACT FROM AUTHOR]

Immune dysregulation is a key feature of the coronavirus disease-2019 (COVID-19). However, disparities in responses across ethnic groups are underappreciated. This study aimed to determine the relationship between chemokines and cytokines and the severity of COVID-19. Multiplex magnetic bead-based Luminex-100 was used to assess chemokine and cytokine levels in COVID-19 patients at admission (day-1) and after 4 days. The mean age of the patients recruited was 54.3 years, with 19 (63.3%) males. COVID-19 patients had significantly lower lymphocyte, monocyte, hemoglobin and eosinophil levels than controls (p < 0.05). COVID-19 patients showed significantly higher neutrophil levels than controls (p < 0.05). The baseline levels of IL-2, IL-6, IL-8, IL-10, and IFN-α/γ significantly increased in COVID-19 patients (p < 0.05). Chemokine levels (IP-10, MCP-1, MIG, and CCL-5) were significantly in COVID-19 patients. IL-8, IP-10, and MIG levels were significantly higher in the patients with severe COVID-19 (p < 0.05). Individuals with mild COVID-19 showed significantly higher levels of INF-α, IL-2, IL-6, and IL-8, whereas IL-10 levels were significantly lower (p < 0.05). TNF-levels decreased significantly in individuals with severe COVID-19, whereas IL-6, IL-8, and MIG levels increased (p < 0.05). After 4 days, INFα-, IL-2, IL-6, IL-8, IP-10, and MIG levels were significantly higher in patients with mild disease, whereas IL-6, MIG, and TNF-αlevels were significantly higher in patients with severe disease (p < 0.05). Thus, we conclude that COVID-19 is characterized by INF-α/γ, IL-6, IL-10, IP-10, MCP-1, MIG, and CCL5 dysregulation. IL-8, MIG, and IP-10 levels distinguish between moderate and severe COVID-19. Changes in INF-α, IL-2, IL-6, IL-8, IP-10, and MIG levels can be used to monitor disease progression. [ABSTRACT FROM AUTHOR]

The idea of greening the chemical industry as a solution to pollution prevention has gained much popularity over the past few decades. The development of alternative green and sustainable processes has significantly contributed to reducing risks and hazards associated with the practice of chemistry. In this context, the Green Chemistry Challenge Awards, an annual award instituted by the US Environmental and Protection Agency (US EPA) along with the American Chemical Society Green Chemistry Institute, has, over the years, encouraged and recognized chemical technologies that incorporate the various principles of green chemistry. The award has successfully recognized novel solutions to real-world environmental problems and thereby has significantly contributed to greener approaches to the design, manufacture and use of chemicals. [ABSTRACT FROM AUTHOR]

Sesame (Sesamum indicum L.), an ancient oilseed crop being cultivated across geographical locations in the tropics, is known for its high-quality oil with a longer shelf life. India, being the center of diversity for this crop, understanding the genetic variability of sesame germplasm being conserved in the national Genebank (NGB) of ICAR-NBPGR, will help identify genotypes for its potential use in broadening the genetic base of the cultivars for sesame crop improvement. We report here the molecular diversity analysis performed using SSR markers on a set of 2,496 sesame germplasm. Hence, the derived data was also subjected to population structure analysis, and a molecular core was generated to assess its phenotypic variability. Parallelly, they were phenotypically characterized for important qualitative and quantitative traits as per the standard descriptor developed by IPGRI, and accessions exhibiting desirable traits were identified. The sesame germplasm used in our study represents collections from 17 countries across the globe and 26 states in India. A total of 140 alleles were obtained using seven polymorphic SSR markers selected from an initial screening comprising 43 SSR markers. The observed heterozygosity was less than the expected heterozygosity since it is a self-pollinated crop (up to 35% outcrossing is reported, categorized as often cross-pollinated). The molecular diversity analysis grouped 2496 accessions into six clusters, while the population structure analysis grouped them into three major clusters or populations. A molecular core developed using the PowerCore software identified 196 accessions, representing all the alleles from the entire 2496 accessions, that can be utilized in breeding programs after phenotypic validation. This study contributes to genetic diversity assessment for sesame germplasm, identifying genetically diverse accessions, and establishing a core set that encapsulates the genetic variability of the sesame germplasm collection. These findings hold relevance for addressing agricultural challenges and enhancing the resilience and productivity of sesame crops in various environmental conditions. [ABSTRACT FROM AUTHOR]

Background: Bacterial biofilms are aggregation or collection of different bacterial cells which are covered by self-produced extracellular matrix and are attached to a substratum. Generally, under stress or in unfavorable conditions, free planktonic bacteria transform themselves into bacterial biofilms and become sessile. Main body: Various mechanisms involving interaction between antimicrobial and biofilm matrix components, reduced growth rates, and genes conferring antibiotic resistance have been described to contribute to enhanced resistance. Quorum sensing and multi-drug resistance efflux pumps are known to regulate the internal environment within the biofilm as well as biofilm formation; they also protect cells from antibiotic attack or immune attacks. This review summarizes data supporting the importance of exopolysaccharides during biofilm formation and its role in antibiotic resistance. Conclusions: Involvement of quorum sensing and efflux pumps in antibiotic resistance in association with exopolysaccharides. Also, strategies to overcome or attack biofilms are provided. [ABSTRACT FROM AUTHOR]

Quantum walk has been regarded as a primitive to universal quantum computation. In this paper, we demonstrate the realization of the universal set of quantum gates on two- and three-qubit systems by using the operations required to describe the single particle discrete-time quantum walk on a position space. The idea is to utilize the effective Hilbert space of the single qubit and the position space on which it evolves in order to realize multi-qubit states and universal set of quantum gates on them. Realization of many non-trivial gates and engineering arbitrary states is simpler in the proposed quantum walk model when compared to the circuit based model of computation. We will also discuss the scalability of the model and some propositions for using lesser number of qubits in realizing larger qubit systems. [ABSTRACT FROM AUTHOR]

Ensets (Ensete spp., family Musaceae), are multipurpose plants with great versatility and potential as a food security crop, although they are cultivated only in Ethiopia and few other regions of Africa. Currently due to loss of habitat, intensification of agriculture, genetic diversity of both wild and domestic ensets is at high risk of erosion. Ensete glaucum (Roxb.) Cheesman, a less-known and under-utilized crop wild relative of banana, is found as natural strands in North-eastern regions of India. No report exists on seed conservation or cryopreservation of E. glaucum and the present work was undertaken to fill this knowledge gap. Mature fruits of two seeded accessions of E. glaucum (MZU-DBT-T15 and HSB-8) were collected from plants in natural populations from two geographically distinct North-eastern region of India. Seed morphology, moisture content (MC) of seed and embryo, viability and germination of excised embryos, desiccation and cryosensitivity were studied. Fresh seed (31% MC) viability measured through in vitro germination of excised embryos was not significantly different in both accessions (87–89%). Seeds could tolerate desiccation up to 5–10% MC without significant loss in germination potential (83–84%) and safely stored up to 1 year at room temperature (RT), without loss of viability. Air dehydrated seeds (10 ± 2% MC) and embryos (12 ± 2% MC) were cryopreserved (in liquid and vapour phase of liquid nitrogen). High post-thaw recovery was achieved in both tissues i.e. seeds (80.2 ± 2.2%) and embryos (83.1 ± 2.6%) by in vitro culture of excised embryos on MS medium + 2 µM gibberellic acid + 1 µM 6-benzyl amino purine (BAP) + 1 µM ascorbic acid. The seedlings converted into multiple shoots (15–20 shoots/explant) within 2 months of culture on medium with MS salts + 10 µM BAP + 1 µM indole-3-acetic acid (IAA) + 1 µM ascorbic acid. This study is the first successful report of cryopreservation of E. glaucum using simple air dehydration. Using the method devised, seeds and zygotic embryos of the two accessions of E. glaucum are safely conserved in the Cryogenebank, while in vitro plantlets are maintained in the In Vitro Genebank of ICAR-NBPGR, New Delhi, India. Key message: This study is the first successful report of cryopreservation of Ensete glaucum using seeds and zygotic embryos [ABSTRACT FROM AUTHOR]

The quantum walk formalism is a widely used and highly successful framework for modeling quantum systems, such as simulations of the Dirac equation, different dynamics in both the low and high energy regime, and for developing a wide range of quantum algorithms. Here we present the circuit-based implementation of a discrete-time quantum walk in position space on a five-qubit trapped-ion quantum processor. We encode the space of walker positions in particular multi-qubit states and program the system to operate with different quantum walk parameters, experimentally realizing a Dirac cellular automaton with tunable mass parameter. The quantum walk circuits and position state mapping scale favorably to a larger model and physical systems, allowing the implementation of any algorithm based on discrete-time quantum walks algorithm and the dynamics associated with the discretized version of the Dirac equation. Implementations of quantum walks on ion trap quantum computers have been so far limited to the analogue simulation approach. Here, the authors implement a quantum-circuit-based discrete quantum walk in one-dimensional position space, realizing a Dirac cellular automaton with tunable mass parameter. [ABSTRACT FROM AUTHOR]

Databases obtained from different search engines, market data, patients' symptoms and behaviours, etc., are some common examples of set-valued data, in which a set of values are correlated with a single entity. In real-world data deluge, various irrelevant attributes lower the ability of experts both in speed and in predictive accuracy due to high dimension and insignificant information, respectively. Attribute selection is the concept of selecting those attributes that ideally are necessary as well as sufficient to better describe the target knowledge. Rough set-based approaches can handle uncertainty available in the real-valued information systems after the discretization process. In this paper, we introduce a novel approach for attribute selection in set-valued information system based on tolerance rough set theory. The fuzzy tolerance relation between two objects using a similarity threshold is defined. We find reducts based on the degree of dependency method for selecting best subsets of attributes in order to obtain higher knowledge from the information system. Analogous results of rough set theory are established in case of the proposed method for validation. Moreover, we present a greedy algorithm along with some illustrative examples to clearly demonstrate our approach without checking for each pair of attributes in set-valued decision systems. Examples for calculating reduct of an incomplete information system are also given by using the proposed approach. Comparisons are performed between the proposed approach and fuzzy rough-assisted attribute selection on a real benchmark dataset as well as with three existing approaches for attribute selection on six real benchmark datasets to show the supremacy of proposed work. [ABSTRACT FROM AUTHOR]

This study investigates the genetic variations in FcεR1β-109 C/T (rs512555) and TNF-α-308 G/A (rs1800629) genes and examines whether the mosquito repellent transfluthrin (TFT) modifies the risk for asthmatic children. A case–control study was conducted involving 130 asthmatic children and 123 age-sex matched controls. Differential leukocyte counts, IgE, and hs-CRP levels were estimated using a five-part haematology analyzer and Beckman Coulter (AU480), respectively. Genetic variations in FcεR1β-109 and TNF-α-308 were analysed using restriction fragment length polymorphism. Serum TFT levels were measured using gas chromatography-tandem mass spectrometry. Asthmatic children had significantly increased total leukocyte, neutrophil, lymphocyte, eosinophil, and basophil counts (p < 0.0001), while their monocyte counts were lower compared to controls (p < 0.0001). TFT levels were higher in asthmatic children (1.38 ± 0.91 vs. control 0.69 ± 0.41µg/L, p < 0.0001), which predominantly induced wheezing. Elevated TFT levels were associated with an increased risk of childhood asthma (OR: 3.08, p < 0.0001). Children with the FcεRIβ TT (OR: 2.39, p < 0.017) and TNF-α GG genotypes (OR: 7.17, p < 0.0001) were more susceptible to asthma. TFT synergistically enhanced the risk of asthma in both FcεRIβ-109 TT (OR: 5.3, p = 0.001) and TNF-α-308 GG (OR: 17.18, p < 0.0001) genotypes. TFT levels were correlated with IgE (r = 0.363; p = 0.006), hs-CRP (r = 0.324; p = 0.049) and eosinophil (r = 0.300; p = 0.038), respectively. IgE and eosinophils were correlated (r = 0.599, p = 0.001) in the FcεRIβ TT genotype-carrying asthmatic children. Similarly, neutrophils and hs-CRP were correlated (r = 0.768, p < 0.0001) in asthmatic children with TNF-α GG genotype. The risk of asthma is inherently higher in children with FcεRIβ TT and TNF-α GG variants. TFT exposure amplifies the risk of asthma in children among all the subgenotypes of both genes. TFT influences IgE and eosinophil in FcεRIβ TT genotype while it influences neutrophils and hs-CRP in TNF-α GG genotypes. [ABSTRACT FROM AUTHOR]

Nowadays, databases expand rapidly due to electronically generated information from different fields like bioinformatics, census data, social media, business transactions, etc. Hence, feature selection/attribute reduction in databases is necessary in order to reduce time, cost, storage and noise for better accuracy. For this purpose, the rough set theory has been played a very significant role, but this theory is inefficient in case of real-valued data set due to information loss through discretization process. Hybridization of rough set with intuitionistic fuzzy set successfully dealt with this issue, but it may radically change the outcome of the approximations by adding or ignoring a single element. To handle this situation, we reconsider the hybridization process by introducing intuitionistic fuzzy quantifiers into the idea of upper and lower approximations. Supremacy of intuitionistic fuzzy quantifier over VPRS and VQRS is presented with the help of some examples. A novel process for feature selection is given by using the degree of dependency approach with intuitionistic fuzzy quantifier-based lower approximation. A greedy algorithm along with two supportive examples is presented in order to demonstrate the proposed approach. Finally, proposed algorithm is implemented on some benchmark datasets and classification accuracies for different classifiers are compared. [ABSTRACT FROM AUTHOR]

The demand for reliable critical software system is increasing in exponential way. In critical software system reliability is considered as an important quality factor. Reliability itself depends on various factors. To develop reliable critical software system it is very important to evaluate reliability in active and efficient manner. Soft Computing techniques are effective in assessment of models. The main objective of this study is to develop a reliability model that is based on important factors. The secondary objective is to evaluate the model by using fuzzy logic/soft computing. Since multiple factors have impact on reliability so fuzzy logic will help to provide specific solution for imprecise and ambiguous concepts by converting vague information into a good judgmental model Critical software system selection is a complex task. Four factors are considered to evaluate the reliability. Then the evaluation results are validated by using defuzzification. The proposed model can be implemented for various applications in an effective manner. [ABSTRACT FROM AUTHOR]

Plant growth and development are greatly affected due to changes in environmental conditions and become a serious challenge to scientific people. Therefore, present study was conducted to determine the role of secondary metabolites on the growth and development of maize under abiotic stress conditions. Cinnamic acid (CA) is one of the basic phenylpropanoid with antioxidant activity, produced by plants in response to stressful conditions. Response of maize seeds to the presoaking treatment with 0.5 mM CA was studied under different concentrations of NaCl stress. Exogenous CA increased growth characteristics in saline and non-saline conditions, while effects of CA were more significant under saline conditions in comparison to non-saline conditions in maize plants. CA also reduced oxidative damage through the induction of ROS scavenging enzymes such as supperoxide dismutase (SOD) (EC 1.15.1.1), peroxidase (POD) (EC 1.11.1.7), while the activity of enzyme catalase (CAT) (EC 1.11.1.6) was decreased. The content of malondialdehyde (MDA) was reduced significantly in maize leaf under CA treatment. Changes in protein banding patterns in the maize leaves showed a wide variation in response to NaCl-stress, while in the presence of CA salt-induced expression of polypeptides was reduced significantly. Present study clearly reports the alleviative effects of CA in response to salinity stress on growth, metabolic activity and changes in protein profile of 21 days old maize plants. [ABSTRACT FROM AUTHOR]

Bismuth silicon oxide (BiSiO, BSO ) nano crystalline powder was prepared by sol-gel technique using bismuth nitrate and tetraethyl orthosilicate as starting materials. The prepared samples were sintered at various temperatures (750 °C maximum) and characteristic sillenite single cubic phase with crystallite size ~38 nm (calculated from room temperature powder XRD measurements) was realized at 750 °C sintering temperature. SEM analysis showed that the powder contains the nano-sized particles with almost spherical morphology. The observed frequencies in room temperature FTIR spectrum could be assigned to Bi-O, Si-O and Bi-O-Si bonds. The FWHM (full width at half maximum) of the diffraction peaks decreased while the intensity of FTIR absorption lines increased with the increase in the sintering temperature indicating better bond formation and crystallization. The thermograph of the samples recorded in the temperature range 50-1,000 °C showed almost no weight loss after ~575 °C further confirmed the conclusion arrived at from XRD and FTIR analysis. The samples sintered at 750 °C showed about 50% absorbance in 400-600 nm region which was consistent with the pale yellow color of the sample. Broad blue emission centered ~478 nm was observed when excited by 350 nm radiation from a Xe-lamp. The intensity of this broad emission band increased while its FWHM decreased with the increase in sintering temperature. Self-trapped excitons could be responsible for this emission. [ABSTRACT FROM AUTHOR]