Human Skin Detection Using RGB, HSV and YCbCr Color Models

Human Skin detection deals with the recognition of skin-colored pixels and regions in a given image. Skin color is often used in human skin detection because it is invariant to orientation and size and is fast to process. A new human skin detection algorithm is proposed in this paper. The three main parameters for recognizing a skin pixel are RGB (Red, Green, Blue), HSV (Hue, Saturation, Value) and YCbCr (Luminance, Chrominance) color models. The objective of proposed algorithm is to improve the recognition of skin pixels in given images. The algorithm not only considers individual ranges of the three color parameters but also takes into ac- count combinational ranges which provide greater accuracy in recognizing the skin area in a given image.Comment: ICCASP/ICMMD-2016. Published by Atlantic Press. Part of series: AISR ISBN: 978-94-6252-305-0 ISSN: 1951-685

Prolongation of a pregnancy with second trimester severe oligohydramnios to term: a case report

The occurrence of oligohydramnios complicating a pregnancy is seen in 0.8 to 5.5 % of pregnancies. Severe Oligohydramnios, though not clearly defined, but clinically with an AFI of less than 5 cm appears to be an important predictor for an abnormal fetal outcome. In general, the prognosis of mid trimester oligohydramnios is still poor. Hence we report a case with a very favourable neonatal outcome following severe oligohydramnios documented in early pregnancy. The aim of this case report is to add our experience to the currently limited literature regarding the best treatment of this unique obstetrical problem

Observations on the distribution of plankton at six inshore stations in the Gulf of Manaar

It has long been recognised that the distribution of plankton may be very patchy, especially in the coastal regions because near the land the sea may be frequently disturbed over small areas by the mixing of coastal and oceanic waters, tidal streams and Ibe upwelling of the lower layers of water against ceastal banks. This is further complicated by the sporadic outbursts of larva I forms from the littoral fauna and the shallow water benthos

Energy Efficient UAV-Assisted Emergency Communication with Reliable Connectivity and Collision Avoidance

Emergency communication is vital for search and rescue operations following natural disasters. Unmanned Aerial Vehicles (UAVs) can significantly assist emergency communication by agile positioning, maintaining connectivity during rapid motion, and relaying critical disaster-related information to Ground Control Stations (GCS). Designing effective routing protocols for relaying crucial data in UAV networks is challenging due to dynamic topology, rapid mobility, and limited UAV resources. This paper presents a novel energy-constrained routing mechanism that ensures connectivity, inter-UAV collision avoidance, and network restoration post-UAV fragmentation while adapting without a predefined UAV path. The proposed method employs improved Q learning to optimize the next-hop node selection. Considering these factors, the paper proposes a novel, Improved Q-learning-based Multi-hop Routing (IQMR) protocol. Simulation results validate IQMRs adaptability to changing system conditions and superiority over QMR, QTAR, and QFANET in energy efficiency and data throughput. IQMR achieves energy consumption efficiency improvements of 32.27%, 36.35%, and 36.35% over QMR, Q-FANET, and QTAR, along with significantly higher data throughput enhancements of 53.3%, 80.35%, and 93.36% over Q-FANET, QMR, and QTAR.Comment: 13 page

Delayed interval twin delivery of a fetus with a favourable neonatal outcome after a preterm delivery of the first twin: a case report

Assisted reproductive techniques have proved to be a boon for infertile couples. With advent of newer techniques, the incidence of successful multiple pregnancies has also risen. Considering the emotional and financial aspects of the treatment and the risk of preterm delivery in such cases, our intent is not only to salvage one of the twins in case of unfortunate preterm delivery of the other but also to deliver a viable second twin with better chance of survival and favourable neonatal outcome. The current case describes a 34-year woman with previous 2 failed IVF conceptions, on external progesterone support, carrying a twin gestation in preterm labour. Upon the inadvertent delivery of the first twin, a cervical cerclage was done, and she was given conservative management, including bed rest and head low position in view of short cervix, with an aim to delay the delivery of the other. An interval of 66 days was achieved with surgical as well as medical management, following which a healthy second twin was born

Network connectivity during mergers and growth: optimizing the addition of a module

The principal eigenvalue $\lambda$ of a network's adjacency matrix often determines dynamics on the network (e.g., in synchronization and spreading processes) and some of its structural properties (e.g., robustness against failure or attack) and is therefore a good indicator for how ``strongly'' a network is connected. We study how $\lambda$ is modified by the addition of a module, or community, which has broad applications, ranging from those involving a single modification (e.g., introduction of a drug into a biological process) to those involving repeated additions (e.g., power-grid and transit development). We describe how to optimally connect the module to the network to either maximize or minimize the shift in $\lambda$, noting several applications of directing dynamics on networks.Comment: 7 pages, 5 figure

Bioactive Components of Magical Velvet Beans

The plant Mucuna is an annual climbing shrub with long vines that can reach over fifteen meters in length. About 100–150 Mucuna species are found in the tropic and subtropic regions of both hemispheres of the earth. The genus Mucuna belongs to the family Leguminosae. It is commonly known as Kewanch, velvet bean, cowhage and kappikachhu and is found widely in India as a hardy, herbaceous, vigorous, twining annual plant. The size and dimension of the Mucuna seeds, pods, platelets and leaves change from species to species. The hair present on pods is anthelmintic, which causes itching. People are seeking great attention towards Mucuna due to its several medicinal properties, including L-DOPA (L-3, 4-dihydroxyphenylalanine) along with supplementary antioxidants that are used for treating Parkinson’s disease and many neurodegenerative diseases. Thus it is being used in about 200 medicinal formulations. The current chapter outlines the work that determines the influence of different nutritional, anti-nutritional and medicinal values and bioactive agents from different parts of the Mucuna species present in India and its importance in medicine

Complex and real unconventional Bose-Einstein condensations in high orbital bands

We perform the theoretical study on the unconventional Bose-Einstein condensations (UBEC) in the high bands of optical lattices observed by Hemmerich's group. These exotic states are characterized by complex-valued condensate wavefunctions with nodal points, or real-valued ones with nodal lines, thus are beyond the {\it "no-node"} paradigm of the conventional BECs. A quantum phase transition is driven by the competition between the single particle band and interaction energies. The complex UBECs spontaneously break time-reversal symmetry, exhibiting a vortex-antivortex lattice structure.Comment: 4.2 page

Hierarchical amino acid utilization and its influence on fermentation dynamics: rifamycin B fermentation using Amycolatopsis mediterranei S699, a case study

BACKGROUND: Industrial fermentation typically uses complex nitrogen substrates which consist of mixture of amino acids. The uptake of amino acids is known to be mediated by several amino acid transporters with certain preferences. However, models to predict this preferential uptake are not available. We present the stoichiometry for the utilization of amino acids as a sole carbon and nitrogen substrate or along with glucose as an additional carbon source. In the former case, the excess nitrogen provided by the amino acids is excreted by the organism in the form of ammonia. We have developed a cybernetic model to predict the sequence and kinetics of uptake of amino acids. The model is based on the assumption that the growth on a specific substrate is dependent on key enzyme(s) responsible for the uptake and assimilation of the substrates. These enzymes may be regulated by mechanisms of nitrogen catabolite repression. The model hypothesizes that the organism is an optimal strategist and invests resources for the uptake of a substrate that are proportional to the returns. RESULTS: Stoichiometric coefficients and kinetic parameters of the model were estimated experimentally for Amycolatopsis mediterranei S699, a rifamycin B overproducer. The model was then used to predict the uptake kinetics in a medium containing cas amino acids. In contrast to the other amino acids, the uptake of proline was not affected by the carbon or nitrogen catabolite repression in this strain. The model accurately predicted simultaneous uptake of amino acids at low cas concentrations and sequential uptake at high cas concentrations. The simulated profile of the key enzymes implies the presence of specific transporters for small groups of amino acids. CONCLUSION: The work demonstrates utility of the cybernetic model in predicting the sequence and kinetics of amino acid uptake in a case study involving Amycolatopsis mediterranei, an industrially important organism. This work also throws some light on amino acid transporters and their regulation in A. mediterranei .Further, cybernetic model based experimental strategy unravels formation and utilization of ammonia as well as its inhibitory role during amino acid uptake. Our results have implications for model based optimization and monitoring of other industrial fermentation processes involving complex nitrogen substrate

Development of a multivariable risk model integrating urinary cell DNA methylation and cell-free RNA data for the detection of significant prostate cancer

Background: Prostate cancer exhibits severe clinical heterogeneity and there is a critical need for clinically implementable tools able to precisely and noninvasively identify patients that can either be safely removed from treatment pathways or those requiring further follow up. Our objectives were to develop a multivariable risk prediction model through the integration of clinical, urine-derived cell-free messenger RNA (cf-RNA) and urine cell DNA methylation data capable of noninvasively detecting significant prostate cancer in biopsy naïve patients. Methods: Post-digital rectal examination urine samples previously analyzed separately for both cellular methylation and cf-RNA expression within the Movember GAP1 urine biomarker cohort were selected for a fully integrated analysis (n = 207). A robust feature selection framework, based on bootstrap resampling and permutation, was utilized to find the optimal combination of clinical and urinary markers in a random forest model, deemed ExoMeth. Out-of-bag predictions from ExoMeth were used for diagnostic evaluation in men with a clinical suspicion of prostate cancer (PSA ≥ 4 ng/mL, adverse digital rectal examination, age, or lower urinary tract symptoms). Results: As ExoMeth risk score (range, 0-1) increased, the likelihood of high-grade disease being detected on biopsy was significantly greater (odds ratio = 2.04 per 0.1 ExoMeth increase, 95% confidence interval [CI]: 1.78-2.35). On an initial TRUS biopsy, ExoMeth accurately predicted the presence of Gleason score ≥3 + 4, area under the receiver-operator characteristic curve (AUC) = 0.89 (95% CI: 0.84-0.93) and was additionally capable of detecting any cancer on biopsy, AUC = 0.91 (95% CI: 0.87-0.95). Application of ExoMeth provided a net benefit over current standards of care and has the potential to reduce unnecessary biopsies by 66% when a risk threshold of 0.25 is accepted. Conclusion: Integration of urinary biomarkers across multiple assay methods has greater diagnostic ability than either method in isolation, providing superior predictive ability of biopsy outcomes. ExoMeth represents a more holistic view of urinary biomarkers and has the potential to result in substantial changes to how patients suspected of harboring prostate cancer are diagnosed