Enhancing the Efficiency of Attack Detection System Using Feature selection and Feature Discretization Methods

Intrusion detection technologies have grown in popularity in recent years using machine learning. The variety of new security attacks are increasing, necessitating the development of effective and intelligent countermeasures. The existing intrusion detection system (IDS) uses Signature or Anomaly based detection systems with machine learning algorithms to detect malicious activities. The Signature-based detection rely only on signatures that have been pre-programmed into the systems, detect known attacks and cannot detect any new or unusual activity. The Anomaly based detection using supervised machine learning algorithm detects only known threats. To address this issue, the proposed model employs an unsupervised machine learning approach for detecting attacks. This approach combines the Sub Space Clustering and One Class Support Vector Machine algorithms and utilizes feature selection methods such as Chi-square, as well as Feature Discretization Methods like Equal Width Discretization to identify both known and undiscovered assaults. The results of the experiments using proposed model outperforms several of the existing system in terms of detection rate and accuracy and decrease in the computational time

Effect of cadmium stress on seed germination and seedling morpho-physiological growth parameters of barnyard millet (Echinochloa frumentacea Link)

Cadmium (Cd) is a heavy metal, which is seen in the contaminated soils and severely affects the growth and development of plants in recent years. The study on the seed germination and morpho-physiological growth characteristics of barnyard millet (Echinochloa frumentacea) cultivar CO (KV) 2 treated with different concentrations (50, 100, 150, 200, and 250 mg/kg of soil) of Cd were evaluated at 15th, 30th, and 45th day of interval. The findings of this research demonstrate that the maximum dosage of Cd (250 mg/kg of soil) affects the germination percentage (65%) of barnyard millet. Seedling vigor index has been negatively influences a drop in germination percentage. Increasing concentrations of Cd reveals the growth of root and shoot length and the quantity of fresh and dry weight affected. The phytotoxicity percentage of roots and shoots also increases with increasing concentrations of Cd, whereas the tolerance index level decreases with increasing concentrations of Cd. In root and shoot, the relative growth index was reduced in higher concentration of Cd. The relative water content remains high in the initial stages of leaf development and declines when the leaf matures. From this study, it was found that the increase in the concentration of Cd leads to decrease the germination percentage and morpho-physiological growth parameters as compared to control

Improving Performance of Quantum Heat Engines by Free Evolution

The efficiency of a quantum heat engine is maximum when the unitary strokes are adiabatic. On the other hand, this may not be always possible due to small energy gaps in the system, especially at the critical point where the gap vanishes. With the aim to achieve this adiabaticity, we modify one of the unitary strokes of the cycle by allowing the system to evolve freely with a particular Hamiltonian till a time so that the system reaches a less excited state. This will help in increasing the magnitude of the heat absorbed from the hot bath so that the work output and efficiency of the engine can be increased. We demonstrate this method using an integrable model and a non- integrable model as the working medium. In the case of a two spin system, the optimal value for the time till which the system needs to be freely evolved is calculated analytically in the adiabatic limit. The results show that implementing this modified stroke significantly improves the work output and efficiency of the engine, especially when it crosses the critical point.Comment: 8 pages, 8 figure

Diagnostic circulating biomarkers to detect vision-threatening diabetic retinopathy: Potential screening tool of the future?

With the increasing prevalence of diabetes in developing and developed countries, the socio-economic burden of diabetic retinopathy (DR), the leading complication of diabetes, is growing. Diabetic retinopathy (DR) is currently one of the leading causes of blindness in working-age adults worldwide. Robust methodologies exist to detect and monitor DR; however, these rely on specialist imaging techniques and qualified practitioners. This makes detecting and monitoring DR expensive and time-consuming, which is particularly problematic in developing countries where many patients will be remote and have little contact with specialist medical centres. Diabetic retinopathy (DR) is largely asymptomatic until late in the pathology. Therefore, early identification and stratification of vision-threatening DR (VTDR) is highly desirable and will ameliorate the global impact of this disease. A simple, reliable and more cost-effective test would greatly assist in decreasing the burden of DR around the world. Here, we evaluate and review data on circulating protein biomarkers, which have been verified in the context of DR. We also discuss the challenges and developments necessary to translate these promising data into clinically useful assays, to detect VTDR, and their potential integration into simple point-of-care testing devices

Deep Learning

Deep Learning was developed as a Machine learning approach to influence advanced input-output mappings. It had been for learning concerning multiple levels of illustration and abstraction to create sense of the information such as images, text and sound. Deep learning excels at distinguish patterns in unstructured information, that most of the people grasp as media like images, sound, video and text

PORPHYSOMES-A PARADIGM SHIFT IN TARGETED DRUG DELIVERY

A novel drug delivery system is the one that ensures optimum dose at the right time, at the right location. Porphysomes are among those drug delivery systems. Porphysomes are a means of vesicular drug delivery systems. They are liposome-like structures composed completely of porphyrin lipid. The porphysomes encapsulates the active medicament in vesicular structure. They are having an aqueous core which can be loaded with the medicament. They have the capacity to destroy the disease tissues. They absorb the heat in the near infrared region and release this heat to destroy the diseased tissues. Porphysomes are having immense applications in the field of positron-electron therapy (PET), photoacoustic imaging, photothermal therapy etc. This review article discusses regarding the Porphysome-the drug delivery system, its advantages and disadvantages, composition, method of preparation, applications and various aspects related to the porphysomal drug delivery

CRYPTOSOMES: A REVOLUTIONARY BREAKTHROUGH IN NOVEL DRUG DELIVERY

The vesicular drug delivery systems are promising approaches to overthrown the problems of drugs having lesser bioavailability and rapid elimination from the body. The four type of lipid based drug delivery systems are: solid-lipid particulate system, emulsion based system, solid lipid tablet and vesicular system. Cryptosomes, a novel emerging vesicular drug delivery system which can overcome the disadvantages associated with conventional drug delivery systems like high stability, increased bioavailability, sustained release, decreased elimination of rapidly metabolizable drugs etc. The word Cryptosome was orginated from Greek word ‘’Crypto’’ means hidden and ‘’Soma’’ means body. It is formed from the mixture of phospholipids like distearoyl phosphatidyl ethanolamine-polyethylene glycol (DSPE-PEG) with distearoylphosphatidylcholine. These entire information regarding its origin and formation is explained in Dinesh Kumar et al. Vesicular systems symbolizes the use of vesicles in the different fields as carrier system or additives. This review disclose various vesicular drug delivery system and point out the advancement of cryptosome in the world of drug delivery. This review would help researchers involved in the field of vesicular drug delivery

FORMULATION AND EVALUATION OF LORAZEPAM ENCAPSULATED COLLAGEN/PECTIN BUCCAL PATCH

Objective: To formulate and characterize Lorazepam loaded buccal patches using mucoadhesive, biodegradable, natural polymers-pectin (hydrophilic) and collagen (lipophilic) for treating epileptic seizures. Methods: Lorazepam loaded buccal patches were prepared by solvent casting method and were subjected to various Physico-chemical evaluation parameters to find the optimized buccal patch. The in vitro drug release study and ex vivo permeation study was carried out. The stability study and histopathological study of optimized Lorazepam loaded buccal patch was also carried out. Results: From in vitro drug release study, it was found that Lorazepam loaded buccal patch (B4) exhibited maximum drug release of 96.16 %±0.07 than other formulations at the end of 4 h, indicating an initial burst release followed by sustained release with release kinetics as Higuchi diffusion model. Based on the in vitro drug release, % drug content, % swelling index, folding endurance, B4 formulation was considered as optimised formulation and was further characterized. Ex vivo permeation study revealed that the cumulative amount of drug permeated from optimised Lorazepam loaded buccal patch (B4) was higher (3831.4±0.21µg/cm2) than marketed Midazolam buccal solution (1724±0.12 µg/cm2) and control drug solution (895.42±0.07 µg/cm2) with an enhancement ratio of 4.8. B4 formulation also showed a higher flux value (12.52±0.02µg/cm2/hr) compared to marketed formulation (5.732±0.01 µg/cm2) and control drug solution (2.563±0.03 µg/cm2) of P<0.05. The histopathological study using bovine buccal mucosa revealed that the B4 formulation is safe for buccal application. The stability study confirmed that B4 formulation is stable in both room and refrigeration conditions. Hence the formulated Lorazepam loaded buccal patch seems to be a promising carrier for the enhanced buccal delivery of Lorazepam in treating epileptic seizures. Conclusion: The formulated Lorazepam loaded collagen/pectin buccal patch was found to be an efficient and stable route for the buccal delivery of Lorazepam in treating acute epileptic seizures which could be further explored scientifically

Frequency of polymorphic variants in corticotropin releasing hormone receptor 1, glucocorticoid induced 1 and Fc fragment of IgE receptor II genes in healthy and asthmatic Tamilian population

Background: Asthma is a chronic airway inflammatory disease characterized by increased hyper-responsiveness and recurrent episodes of reversible obstructions. Asthma pharmacogenomic studies report significant association of single nucleotide polymorphisms (SNPs) in genes corticotropin releasing hormone receptor 1 (CRHR1), Fc fragment of IgE receptor II (FCER2) and glucocorticoid induced 1 (GLCCI1) with inhaled corticosteroid (ICS) response. The present study was aimed to establish the allelic and genotypic frequencies of polymorphisms rs242941, rs28364072 & rs37972 in CRHR1, FCER2 and GLCCI1 genes, respectively in Tamilian healthy population and asthma patients and to compare with established frequencies of global populations.Methods: The study groups consisted of healthy volunteers and persistent asthma patients who were drug naïve or without ICS treatment in the last ≥2 months, attending JIPMER hospital (n=111 and 78, respectively). SNP genotyping was done using PCR-RFLP (polymerase chain reaction-restriction fragment length polymorphism) and real time-PCR methods.Results: Allelic and genotypic frequencies for all the studied variants found to be in hardy-weinberg equilibrium with minor allele frequencies (MAF) of rs 242941, rs 28364072 and rs 37972 at 0.51, 0.33 and 0.38, respectively, in healthy population. No significant difference in gene frequencies was obtained between healthy control and asthma patient groups. Significant difference in allele frequencies was observed between Tamilian healthy and specific global populations. West African frequency was found to be significantly different for all 3 SNPs (p<0.0001).Conclusions: MAF of rs 242941, rs 28364072 and rs 37972 were 0.51, 0.33 and 0.38, respectively in Tamilian population which were significantly different from various global populations. The frequency distribution found helps to further with ICS response association studies in larger cohorts of asthma patients