Background Mucuna giganteais a traditional plant reported in the management of nervous disorders, male infertility, etc., and also exhibits aphrodisiac, anti-oxidant, and anti-diabetic properties. Very few studies are conducted on Mucuna gigantea. It has not been pharmacologically evaluated for rheumatoid arthritis (RA). In RA, the body's natural defence mechanism gets confused and begins to target the healthy tissues in the body, which leads to joint pain, swelling, bone erosion, and joint stiffness. It is a condition that is classified as an auto-immune disorder. Methods In-silico docking depicted that beta-sitosterol is present in Mucuna gigantea out of ligand library prepared based on a literature survey using computational analysis. Inflammation was induced by carrageen and chronic inflammation was induced by Freund's complete adjuvant in the plantar surface of the rats. The petroleum ether, ethanolic and aqueous extracts in three divided doses (75, 150, and 300 mg/kg) were administered orally. Diclofenac sodium (10 mg/kg), prednisolone (5 mg/kg), and methotrexate (0.5 mg/kg) were used as standard. The statistical significance between means was analyzed using one-way ANOVA, followed by Dunnett's multiple range test. The values are expressed as mean ± SD for each group (n=6), and aP<0.0001, bP<0.001, and cP<0.05 were compared with a negative control group. Results Ethanolic and petroleum ether extracts showed a statistically significant aP<0.0001 effect at 3hr with 300mg/kg effect in analgesic activity, whereas aqueous extracts showed statistically significant aP<0.0001 effect at 1.5hr with 150 and 300mg/kg. In the carrageen-induced model, all three extracts at 300 mg/kg showed a statistically significant aP<0.0001 effect from 2- 4hr. In Freund's adjuvant model, all three extracts at all doses showed a statistically significant aP<0.0001 effect. Also, Mucuna gigantea remarkably ameliorated altered WBCs, rheumatoid factor, and positively modified radiographic and histopathological changes. Conclusion Taken together, these results support the traditional use of Mucuna gigantea as a potent anti-inflammatory and anti-arthritic agent that may be proposed for rheumatoid arthritis treatment.

Background: Rheumatoid arthritis is a progressive disease of human joints characterized by severe pain, stiffness, and tissue damage at the local site. Bone and cartilaginous tissue damage at the synovial joints is initiated by the production of autoantibody induced by inflammatory signaling through cytokines. Objective: This study aimed to evaluate the efficacy of Garcinia travancorica against acute and chronic inflammation in a rat model after designing the ligand library and target identification using computational analysis. Methods: Acute inflammation was induced by carrageen, and chronic inflammation was induced by Freund’s complete adjuvant in the plantar surface of the rats. The petroleum ether, ethanolic, and aqueous extracts in three divided doses (75 mg/kg, 150 mg/kg, and 300 mg/kg) were administered orally. Diclofenac sodium (10 mg/kg), prednisolone (5 mg/kg), and methotrexate (0.5 mg/kg) were used as standard. Various parameters were evaluated, and statistical significance between means was analyzed using one-way ANOVA, followed by Dunnett’s multiple range test. Results: Docking-based in-silico screening of the ligand library has revealed the potential of Polyanxanthone-C as an anti-rheumatoid agent, which is supposed to deliver its therapeutic effect by synergistic targeting of interleukin-1, interleukin-6, and tumor necrosis factor receptor type-1. Conclusion: This plant has the potential to be used in the treatment of arthritis-related disorders.

Researchers employ a variety of metrics to assess the intrusion detection system (IDS) model’s performance quantitatively. These metrics help gauge an IDS’s ability to differentiate between normal network traffic and malicious activities and the performance of IDS models. Most researchers evaluate IDS model performances based on conventional metrics, which does not explore minor differences immensely due to their range that lies between 0 and 1. The present study introduces a new performance metric that distinguishes differences in the classification performance of the machine learning-based classification model, especially in scenarios where performance differences are minimal. The present study shows that an ensemble boosted tree with a TPFC value of 1134.4 is the IDS model with high conventional metrics-based values.

Background: The arial part of Asparagus officinalis (A.O.) (Family: Asparagus) stem and seeds, leaf parts of Mucuna gigantea (M.G.) (Family: Fabaceae) and fruit rinds and arial part of Garcinia travancorica (G.T.) (Family: Clusiaceae) have long been used to treat joint pain. However, its preclinical efficacy for rheumatoid arthritis has not been pharmacologically evaluated. In the current study, extracts of A.O., M.G., and G.T. from petroleum ether, ethanolic extract, and aqueous extract were examined for their analgesic, anti-inflammatory, anti-arthritic, and phytochemical properties. Materials and Methods: Rats' tail flick method was used to assess analgesic activity, carrageenan-induced paw oedema model was used to assess anti-inflammatory activity, and protein Complete Freund's Adjuvant (CFA)-induced arthritis model was used to assess anti-arthritic potential. Results: We observed that many extracts had anti-inflammatory and anti-arthritic effects, and to a lesser extent, analgesic activities corresponding to the administered dose. The CFA model's findings showed improved defence against arthritic lesions and changes in body weight. Additionally, rheumatoid factor, altered WBCs count, and histological and radiographic changes were all markedly improved by M.G., G.T., and A.O. Conclusion: All the three plants extract when given together, supports traditional combinatorial use of M.G., G.T. and A.O. as potent analgesic, a potential anti-inflammatory and anti-arthritic polypharmacy for the treatment of rheumatoid arthritis.

Background: To treat the joint pain arial part of Asparagus officinalis (asparagus) has historically been used. However, its efficacy for rheumatoid arthritis has not been pharmaceutically evaluated. We explore the phytochemical analysis anti-inflammatory, analgesic and anti-arthritic activity of petroleum ether, ethanol and aqueous extracts of Asparagus officinalis aerial part. Materials and Methods: Tail-flick method was used to evaluate the analgesic activity anti-inflammatory activity was carried out using paw oedema induced with carrageenan and CFA induced arthritic model was used to evaluate the potential in anti-arthritic activity in rats. The Petroleum ether, ethanolic and aqueous extracts were dosed orally in three divided doses (75, 150 and 300 mg/ kg). For anti-inflammatory and analgesic activity diclofenac sodium at 10 mg/kg was used as standard, whereas in anti-arthritic model prednisolone at 5 mg/kg and methotrexate at 0.5 mg/ kg were used as standard. One-way ANOVA followed by Dunnett's multiple range test were used to analyse statistical significance between means. Results: The results revealed a dose -controlled anti-inflammatory, anti-arthritic effect with different extracts whereas at some extent analgesic activity was observed. Four compounds were present and confirmed by LCMS/MS. The CFA model's findings showed improved defence against arthritic lesions and changes in body weight. Additionally, Asparagus officinalis significantly improved rheumatoid factor, changed WBCs, and favourably altered radiographic and histological alterations. Conclusion:The findings indicate that Asparagus officinalis is a strong anti-arthritic and anti-inflammatory compound that may be suggested for the treatment of both chronic and acute inflammation.

Network Intrusion detection systems (NIDS) detect malicious and intrusive information in computer networks. Presently, commercial NIDS is based on machine learning approaches that have complex algorithms and increase intrusion detection efficiency and efficacy. These machine learning-based NIDS use high dimensional network traffic data from which intrusive information is to be detected. This high-dimensional network traffic data in NIDS needs to be preprocessed and normalized to make it suitable for machine learning tools. A machine learning approach with appropriate normalization and prepossessing increases NIDS performance. This paper presents an empirical study on various normalization methods implemented on a benchmark network traffic dataset, KDD Cup’99, that has been used to evaluate the NIDS model. The present study shows decimal normalization has a better prediction performance than non-normalized traffic data categorized into ‘normal’ or ‘intrusive’ classes.

Isolated oculomotor nerve involvement in a posterior draining CCF is relatively rare. We present the case of a 70-year-old female with complaints of painful left-sided ophthalmoplegia and ptosis. She was detected to have a pupil involving third nerve palsy on the left side. We asked for neuroimaging in the form of MRI and MRA which showed a left-sided low-flow CCF compressing the cavernous and the extra-cavernous portion of the oculomotor nerve. This report stresses the importance of keeping low-flow CCF as a differential diagnosis as early detection can be life-saving.

Background: Plumeria obtusa L., a potential medicinal plant, is still unexplored for its anti-diabetic effect. The objective of this study was to examine the protective effect of Plumeria obtusa leaves extracts on insulin-resistance diabetic rat model. Materials and Methods: Male Wistar rats were distributed into twelve groups. Dexamethasone was used to induce insulin-resistance diabetes mellitus. Three different doses of each extract (petroleum ether, ethanol and aqueous) were orally administered for 45 days. Biochemical estimations, as well as histological and scanning electron microscopy examinations, were done on the 45th day. Results: Statistically significant improvement in serum levels of glucose, glycosylated haemoglobin and insulin, as well as lipid profiles, were observed specifically with ethanol and aqueous extracts in comparison to the positive control group. Conclusion: The histological and scanning electronic microscopy studies revealed a significant improvement in various organs. Hence, this plant needs to be explored at the molecular level.

Network threats and hazards are evolving at a high-speed rate in recent years. Many mechanisms (such as firewalls, anti-virus, anti-malware, and spam filters) are being used as security tools to protect networks. An intrusion detection system (IDS) is also an effective and powerful network security system to detect unauthorized and abnormal network traffic flow. This article presents a review of the research trends in network-based intrusion detection systems (NIDS), their approaches, and the most common datasets used to evaluate IDS Models. The analysis presented in this paper is based on the number of citations acquired by an article published, the total count of articles published related to intrusion detection in a year, and most cited research articles related to the intrusion detection system in journals and conferences separately. Based on the published articles in the intrusion detection field for the last 15 years, this article also discusses the state-of-the-arts of NIDS, commonly used NIDS, citation-based analysis of benchmark datasets, and NIDS techniques used for intrusion detection. A citation and publication-based comparative analysis to quantify the popularity of various approaches are also presented in this paper. The study in this article may be helpful to the novices and researchers interested in evaluating research trends in NIDS and their related applications.

The cassette dosing technique is employed in the drug discovery stage of non-clinical studies to obtain pharmacokinetic data from multiple drug candidates in a single experiment. The objective of the current investigation was to evaluate the effect of sex and food on the selected pharmacokinetic parameters of four biopharmaceutical classification system (BCS) drugs (BCS-I: propranolol, BCS-II: diclofenac, BCS-III: atenolol, and BCS-IV: acetazolamide) utilizing cassette dosing in male and female rats under fed and fasting conditions. Different animal groups were dosed intravenous (i.v) and oral at 1 and 10 mg/kg, respectively, in the form of cassette at a dose of 5 mL/kg. Blood samples were analyzed by liquid chromatography-tandem mass spectrometry. Pharmacokinetics parameters were calculated using Phoenix software version 8.1. A significant increase (p < 0.05) of the area under the plasma concentration-time (AUC0-last) was observed for diclofenac and acetazolamide in females over males after i.v dosing. Additionally, acetazolamide showed greater instantaneous concentration at the time of dosing, and clearance in females (p < 0.05) compared to males after i.v administration. After oral dosing, propranolol exhibited significant variations (p < 0.05) in the maximum drug concentration (Cmax), AUC0-last, the volume of distribution (Vd), and bioavailability in females as compared to males under fed state. Diclofenac showed significant changes (p < 0.05) in AUC0-last, and clearance (Cl) in females as compared to males under fasting and fed state. However, acetazolamide exhibited a significant enhancement (p < 0.05) in AUC0-last, Vd, and Cl in fasting females than the males. The data here illustrates that there is an appreciable difference in AUC and Cmax values exist in male and female rats under fed and fasting conditions administered with the cassette dosing of tested BCS class drugs.

Bittergourd rings were dried to a moisture level of 0.1 g water/g dry matter using a multilayer-cummicrowave drying technique. Response surface methodology was used to optimize the drying conditions based on specific energy consumption and quality of dried bittergourd viz. change in color, rehydration ratio, shrinkage ratio, ascorbic acid content and hardness of texture. A second-order polynomial model fitted well to all responses and high R2 values (>0.8) were observed in all cases. The change in color of the dried bittergourd was found higher at high microwave power and exposure time combination, whereas 80% retention of ascorbic acid and maximum rehydration ratio was observed at 504W. The specific energy consumption decreased with an increase in microwave power due to reduced drying time. The optimum operating conditions for drying bittergourd were PL: 504W and ET:24s, resulting in dried product with maximum rehydration ratio, ascorbic acid retention, overall acceptability, minimum shrinkage ratio, hardness and color change. The overall desirability was 0.725. Use of microwave application in the last stage of drying saved 39% energy. Therefore, microwave-assisted drying should be considered for improved heat and mass transfer and produce dried bittergourd with better quality.

Knowledge Discovery and Data Mining Tools Competition (KDD Cup’99) has been used on prior choice by researchers for the purpose of research and simulation for network intrusion detection system (NIDS) as well as intrusion prevention system (IPS) in network security. In this paper, a statistical analysis on the KDD Cup’99 dataset has been done for the objective of better understanding of structural and organizational view of the features/attributes of network traffic data. This analysis is required for evaluating various predictions on the attributes of the network traffic by taking consideration of different statistical aspects of KDD Cup’99 dataset.

As technology rapidly advances, learning dynamicsLearning dynamics also evolve in terms of curricula, pedagogyPedagogy and teacher–student dynamicsTeacher- student dynamics. Education technologiesEducation Technology (EdTech) that emerged over the course of the last couple of decades enable teachers to make instruction and learning more efficient and effective. EdulasticEdulastic, for example, is an online assessment toolOnline assessment tool with interactive question types that provides teachers real-time dataReal-time data. on student understanding of the lessons.

In the present paper, drying kinetics of button mushroom slices affected by three different independent parameters, including temperature (45-65 0C), air velocities (1.0-5.4 m/s), and loading densities (26-52 kg/m2) were investigated at 3 levels each. Four different dying models were applied to describe the drying kinetics of multilayer drying. Single layer drying was kept as control. The results indicated logarithmic model as the best model to characterize the drying kinetics of mushroom in both Multi and Single layer drying. The logarithimic model had the lowest root mean square error (RMSE), mean bias error (MBE) and chi-square. The highest effective moisture diffusivity (Deff) of 4.92×10-06 and 5.40×10-06 m2/s was observed for multi and single layer drying respectively.

Agriculture is the primary occupation of our country. With the technological advancement in all spheres, agriculture has also witnessed developments with the introduction of robotics and automation. Agricultural robot or "Agribot" is a robot used for agricultural purposes. The advent of robots in agriculture drastically increased the productivity and output of agriculture in several countries. Further, the usage of robots in agriculture reduced the operating costs and lead time of agriculture. The current paper reviews the various applications of robotic agriculture in different areas of agriculture. The work also throws light on the future scope of robotic agriculture.

Haemodynamic changes and oxygen saturation during general anaesthesia in smokers and non-smokers - IJCA- Print ISSN No: - 2394-4781 Online ISSN No:- 2394-4994 Article DOI No:- 10.18231/j.ijca.2019.076, Indian Journal of Clinical Anaesthesia-Indian J Clin Anaesth

Plant, Plecranthus amboinicus (Lour.) Spreng, belonging to the family Lamiaceae, commonly known as 'Karpuravalli' in Tamil language is widely used in folk medicine to treat conditions like cold, asthma, constipation, headache, cough, fever and skin diseases. The present study aimed to evaluate antipsoriatic effect of the ethanol extract of Plecranthus amboinicus root. Ointment containing ethanolic extract of Plecranthus amboinicus root was prepared and evaluated for antipsoriatic activity using complete Freund's adjuvant (CFA) and formaldehyde induced animal model. Psoriasis is induced by applying mixture of 0.1 mL of prepared CFA and formaldehyde mixture (1:10 ratio) topically for 7 days on the dorsum surface of the skin of Swiss albino mice. Antipsoriatic effect of 0.5% and 1.0% (w/w) ointments containing ethanolic extract of Plecranthus amboinicus root was evaluated in terms of Psoriasis severity index (PSI) by the phenotypic features (redness, scales and erythema) and histological features (epidermal thickness). The result showed that there was a significant increase in the orthokeratinocyte layer and a significant reduction in the epidermal layer of skin in the in vivo mice model with a progressive reduction (p**<0.01) in the severity of psoriatic lesions (redness, erythema, and scales) from day 7 to 21st day and significant (p*<0.05) decreased epidermal thickness and increased orthokeratotic regions in animals treated with 0.5% and 1.0% (w/w) ointments of Plecranthus amboinicus root. The present investigations revealed that Plecranthus amboinicus root possess potent antipsoriatic activity, confirming their traditional use in skin disorders.

Due to the advancements in Wireless Sensor network, smart sensors are used in various new and upcoming applications such as smart home appliances, water & air quality application and extensively in automobiles. In Automobiles, WSN and smart sensors are used for many applications such as Vehicle Security & Locking. Earlier, the most security the vehicles had was a locked door, but now days they are equipped with the electronic security system which consists of alert systems and theft alarm system. This paper is an attempt to show how sensors have replaced use of switches in car doors and its limitations to alert the person. The simulation work demonstrates the efficiency of sensors in securing vehicles in case of recklessness. Sensors are also used in the Automobile electronic injection system, in this the sensors used in the fuel injection system determine the exact time the fuel should be injected and the exact amount that is to be injected, due to this the emission gases have reduced by 50%, fuel economy and the power output has increased by about 45-65% and 30-55% respectively. Another use of sensors is in Advanced Headlight Technology, in this there are different electronic and reflecting technologies used that can adjust and even bend light along curved path for better visibility during night time, etc. This paper also explains smart sensors and some of its applications in automobile as listed above.