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Background: Pityriasis alba (PA) is a common, self-limiting skin disease of childhood. Several micronutrient deficiencies have been attributed to causing PA. Few studies have found a decreased level of serum zinc to be associated with PA, whereas other studies have found a deficiency of serum copper, magnesium, ferritin, and Vitamin D3 to be associated with PA. Aims and Objectives: The objective of the study was to estimate the serum levels of micronutrients (zinc, copper, magnesium, and ferritin), hemoglobin (Hb), serum albumin, and Vitamin D3 in patients of PA and compare the same with that of controls. Materials and Methods: A total of 36 patients with PA and 36 controls were enrolled in the study. Five milliliters of venous blood will be obtained from both cases and controls to conduct the investigations. The serum levels of zinc, ferritin, magnesium, copper, Vitamin D3, hemoglobin, and serum albumin levels were detected. The data were analyzed statistically. Results: In this study, we observed a low serum level of zinc associated with PA patients, when compared to healthy controls with P < 0.042. The serum levels of magnesium in cases were significantly low compared to controls with P < 0.002, which was statistically significant. Vitamin D and Hb levels were also significantly reduced in the PA patients. However, we did not find statistical significance between serum levels of copper, albumin, and ferritin in cases and controls with P = 0.408, P = 0.055, and P = 0.082, respectively. Conclusion: PA is a multifactorial etiological condition, in which micronutrient deficiency is an important cause and supplementation of micronutrients among these patients may be beneficial.

Nanotechnology offers a promising solution to address the nutrient demands of cereals, which are nutrient-intensive crops typically reliant on large amounts of inorganic fertilizers. These large quantities of nutrients are supplied to the crop by applying a huge amount of inorganic fertilizer as a soil application led to a decline in environmental systems, particularly affecting the soil health, lesser use efficiency of fertilizers and water resources contamination. In this context, nanotechnology serves as a potential solution. The huge demand for nutrients in cereal crops is met by nano-fertilizers. The nano-fertilizers are now playing a promising role in fulfilling the nutrient requirement of the crops by replacing the normal conventional fertilizers not only for cereals but also for other agricultural crops. The mechanism of action of nano-fertilizers is that they are smaller than the pore size of plant cell walls, allowing them to easily enter and reach the plasma membrane. Nano-fertilizers have 100 times greater surface area than conventional fertilizers, allowing them to easily interact with plant surfaces and increase the absorption of nutrients. Therefore, the nutrient-use efficiency of the crop is increased and shown a positive effect on the physiological and growth parameters of cereal crops, resulting in enhanced yield and improved drought tolerance. This review discussed, the effects and efficiency of nano-fertilizers on cereal crop growth and the correlation between physiological, qualitative, quantitative traits with nano-form of application in detailed manner. This review concludes that nano-fertilizers are the potential nutrient source for cereal crops like rice (Oryza sativa L.), wheat (Triticum aestivum L.), maize (Zea mays) etc. and they are going to be a promising resource for nutrient management in agricultural crops.

Agriculture is the most significant and stable economic sector in the world because it both directly and indirectly produces and supplies food for people. The demands of a growing population are beyond the capacity of global agriculture production to meet. The world has experienced varying degrees of food crises at different times. To ensure food security and meet the demands of an expanding population, pressure is being applied to the agriculture sector. Chemical fertilizers are therefore viewed as an essential source of plant nutrition for improving crop yields. Farmers began to believe that applying more chemical fertilizers results in increased crop yield. However, less than half of the fertilizer applied will be absorbed by the crop, with the surplus either leaching into water sources or becoming immobilized in the soil. With innovative nano-technological strategies that enhance precision farming methods, improve plant nutrient absorption, support land and water conservation, boost crop yield, and develop uses for nano-fertilizers (NFs), nanotechnology has enormous potential to improve agricultural practices. [ABSTRACT FROM AUTHOR]

This article explores the use of microbial methods to remove heavy metals from industrial effluent in the pharmaceutical industry. The effluent contains metallic cations that can contaminate the soil and food chain. Traditional treatments for metal-containing waste have limitations, so researchers are investigating alternative biological methods involving bacteria and bio surfactants. The article also presents a study on the effects of microbial treated and untreated tannery effluent on the growth of green gram. The study concludes that bacteria are effective in removing heavy metals from pharmaceutical effluent. [Extracted from the article]

For a sustainable nuclear energy program using fission reactors, the reduction or elimination of long-lived radioactive waste is essential. The hazardous Long-Lived Fission Products (LLFP), which are by-products of the operation of nuclear reactors, need to be converted to short-lived or stable nuclei. For nuclear transmutation, the knowledge of reaction cross-sections is important. The cross-section and half-life for the proton-induced transmutation of the LLFP, 1 2 6 Sn, produced as nuclear waste from the reactor have been calculated. The cross-section for the (p,n) reaction on unstable 1 2 6 Sn has been calculated using phenomenological as well as microscopic models of optical potentials and level densities in the framework of the statistical nuclear model using the latest version of the code TALYS-1.96. The Koning–Delaroche (KD) and Jeukenne–Lejeune–Mahaux–Bruyeres (JLMB) optical models, as well as back-shifted Fermi gas model (BFM) and Hartree–Fock (HF) level density, based on the Skyrme force from Gorielys tables, have been used. The renormalized optical model parameters and level density models obtained by comparing cross-sections with data for protons incident on stable 1 1 2 , 1 1 4 , 1 1 5 , 1 1 6 , 1 1 7 , 1 1 8 , 1 1 9 , 1 2 0 , 1 2 2 , 1 2 4 Sn isotopes were extended to make a prediction of (p,n) cross-section on unstable 1 2 6 Sn isotope. The excitation function obtained using JLMB-HF calculation for 1 2 6 Sn reveals a peak at an incident proton energy of 8.5 MeV with a corresponding cross-section of 269 mb. It would be of interest to perform experiments for measurements of cross-section where data are unavailable, especially in the peak regions and beyond, to validate the predictions of this work. It is found that for a proton flux of 6. 2 5 × 1 0 1 4 s − 1 cm − 2 , and a peak cross-section calculated using JLMB-HF calculation, the effective half-life of transmutation of 1 2 6 Sn is about 65 years, thus justifying its feasibility. [ABSTRACT FROM AUTHOR]

The goal of the present research is to comprehend the existing state of health among residents of Anaikatti village in the Coimbatore district. The most prevalent diseases and signs of health problems have been covered. The public' perceptions of health concerns and their causes are also examined. The study takes a qualitative method. The research is based on real- time data gathered from a poll of Anaikatti Village inhabitants. Convenience sampling was used to choose the respondents. The research included 168 participants in all. To analyse primary data, statistical techniques such as percentage analysis, descriptive statistics, and ANOVA are applied. The findings show that some areas of the neighbourhood have inadequate drinking water and sanitary care. Legislators and healthcare practitioners, with the help of non-governmental organisations, must take adequate actions to ensure safe drinking water and sanitary facilities. Frequent health camps, free distribution of medications for common symptoms, actions to increase the nutritional content of food consumed, distribution of nutritional supplements, and frequent doctor visits may aid in the identification of previously undiagnosed illnesses and improve overall health. An in-depth research into prevalent genetic disorders is also recommended, while immunisations against seasonal diseases may aid in boosting immunity against seasonal sickness in toddlers and the elderly. [ABSTRACT FROM AUTHOR]

The diagnostic interpretation of dermoscopic images is a complex task as it is very difficult to identify the skin lesions from the normal. Thus the accurate detection of potential abnormalities is required for patient monitoring and effective treatment. In this work, a Two-Tier Segmentation (TTS) system is designed, which combines the unsupervised and supervised techniques for skin lesion segmentation. It comprises preprocessing by the median filter, TTS by Colour KMeans Clustering (CKMC) for initial segmentation and Faster Region based Convolutional Neural Network (FR-CNN) for refined segmentation. The CKMC approach is evaluated using the different number of clusters (k = 3, 5, 7, and 9). An inception network with batch normalization is employed to segment melanoma regions effectively. Different loss functions such as Mean Absolute Error (MAE), Cross Entropy Loss (CEL), and Dice Loss (DL) are utilized for performance evaluation of the TTS system. The anchor box technique is employed to detect the melanoma region effectively. The TTS system is evaluated using 200 dermoscopic images from the PH² database. The segmentation accuracies are analyzed in terms of Pixel Accuracy (PA) and Jaccard Index (JI). Results show that the TTS system has 90.19% PA with 0.8048 JI for skin lesion segmentation using DL in FR-CNN with seven clusters in CKMC than CEL and MAE. [ABSTRACT FROM AUTHOR]

Summary: In general, heart disease is considered as the most severe disease that results in high mortality rate globally. An arrhythmia is one type of heart disease caused due to asymmetrical heartbeat rhythm rate (i.e., heartbeat will be too slow or too fast). The generation of IoT devices as well as ECG signals is capable of tracking the heart rhythm of the patients consistently. Even though, analyzing ECG signals using cloud‐based techniques achieves a certain accuracy level with high latency. Then by evaluating the ECG signals with fog‐based approaches minimizes the latency but the computing capability is minimum. Therefore, wearable devices and fog devices are linked directly to attain high service quality with minimum latency. To conquer such drawbacks, this article proposes a novel AdaBoost kernel support vector machine‐based remora optimization (AKSVM based RO) algorithm to analyze the ECG signals and to initiate the crisis with minimum time delay. The proposed approach predicts the ECG signals of arrhythmia affected persons from an IoT wearable device. In addition to this, the proposed AKSVM‐RO approach is more feasible to deploy in fog environment. Also, it assists in optimizing the time delay in calling the ambulance service during emergency situations. Finally, the experimental investigations are conducted for various approaches with respect to simulation measures to minimize the latency and accuracy of the proposed system. [ABSTRACT FROM AUTHOR]

Osteomyelitis of the maxillofacial skeleton is a rare condition in recent times. The combination of antibiotic therapy and surgical debridement is effective in the treatment of chronic suppurative osteomyelitis (CSO). This case report describes the successful surgical treatment of CSO of the mandible in an 18-year-old adult. Treatment included a pre-surgical course of antibiotics followed by sequestrectomy, resection of the coronoid process and removal of the pathologically fractured condylar process of the left side of the mandible. On post-operative clinical review at 1 week, the extra oral draining sinus healed with improved mouth opening.

Traditional rice varieties having high flavonoids and anthocyanin traits were hybridized to high-yielding quality cultivars to assess their combining ability. Significant variation was observed among parents and hybrids for the traits studied. The predominance of non-additive gene action was observed for single plant yield, total flavonoid content, amylose content, whereas, trait anthocyanin registered additive gene action in the study. The genotypes ADT 37 and ADT (R) 45 were found to be good general combiners for flavonoids and anthocyanin content. The hybrid ADT (R) 45 x IG6 exhibited significant sca for flavonoids, anthocyanin and amylose per cent. The hybrid ADT (R) 45 x Mikkuruvai exhibited significant per se and sca for single plant yield and flavonoid content. [ABSTRACT FROM AUTHOR]

In the present study, Lactobacillus plantarum-HDS27 strain isolated from bovine milk was used for the enhanced production of riboflavin. Production medium was optimized by one factor at a time with different parameters. Statistical optimization by Response surface methodology (RSM), central composite design was used to optimize variables such as pH, temperature, glucose, and yeast extract. The present study reveals the maximum riboflavin production by one factor at a time was obtained under the culture conditions; glucose, yeast extract, pH 6, the temperature at 40 °C, and 3% of inoculum size. In RSM, analysis of variance for the responses was calculated. Among the tested variables, pH, yeast extract, and temperature showed significant impact on riboflavin production. Maximum amount of yeast extract in production medium resulted in increased riboflavin production. The riboflavin production after 24 h with the optimal condition was found to be 12.33 mg/L. It was found proximate to the expected value (12.29 mg/L) achieved by the RSM model. The yield of riboflavin was increased to 3.66-fold after 24 h with the optimized parameters. The current research, emphasizes that the Lactobacillus plantarum-HDS27 could be an excellent strain for the largescale industrial production of riboflavin. [ABSTRACT FROM AUTHOR]

Finding motif in biosequences is the most important primitive operation in computational biology. There are many computational requirements for a motif discovery algorithm such as computer memory space requirement and computational complexity. To overcome the complexity of motif discovery, we propose an alternative solution integrating genetic algorithm and Fuzzy Art machine learning approaches for eliminating multiple sequence alignment process. Problem statement: More than a hundred methods had been proposed for motif discovery in recent years, representing a large variation with respect to both algorithmic approaches as well as the underlying models of regulatory regions. The aim of this study was to develop an alternative solution for motif discovery, which benefits from both data mining and genetic algorithm, and which at the same time eliminates the cost caused by use of multiple sequence alignment. Approach: Genetic algorithm based probabilistic Motif discovery model was designed to solve the problem. The proposed algorithm was implemented using Matlab and also tested with large DNA sequence data sets and synthetic data sets. Results: Results obtained by the proposed model to find the motif in terms of speed and length are compared with the existing method. Our proposed method finds Length of 11 in 18 sec and length of 15 in 24 sec but the existing methods finds length of 11 in 34 sec. Compare to other techniques the proposed one was outperforms the popular existing method. Conclusion: In this study, we proposed a model to discover motif in large set of unaligned sequences in considerably minimum time. Length of motif was also long. The proposed algorithm will be implemented using Matlab and was tested with large DNA sequence data sets and synthetic data sets. Key words: Bioinformatics, genetic algorithm, motif, DNA sequence, multiple unaligned, INTRODUCTION Modern growths in bioinformatics have stimulated many researchers' attention to this area. Biologists, computer scientists, and others from various fields have contributed different researches planning to benefit more from [...]

Nuclear matter densities and charge radii for even 46−62Cr isotopes have been calculated using relativistic Hartree-Bogoliubov model based on density-dependent meson-exchange relativistic energy density functional. The calculated root-mean-square charge radii agree well with corresponding data and the kink at N=28 is reproduced by the calculation. The calculated target matter densities are folded with the Jeukenne, Lejeune, and Mahaux-Bruyéres inter-nucleon interaction to obtain semi-microscopic optical model potentials for incident protons of 65 MeV on even 46−62Cr isotopes. The elastic scattering differential cross sections calculated using the proton optical potentials reproduce corresponding data for stable isotopes. The optical model potential parameters required for prediction of differential and total reaction cross sections for unstable even isotopes have been obtained.