Evasion of Host Defence by Leishmania donovani: Subversion of Signaling Pathways

Protozoan parasites of the genus Leishmania are responsible for causing a variety of human diseases known as leishmaniasis, which range from self-healing skin lesions to severe infection of visceral organs that are often fatal if left untreated. Leishmania donovani (L. donovani), the causative agent of visceral leishmaniasis, exemplifys a devious organism that has developed the ability to invade and replicate within host macrophage. In fact, the parasite has evolved strategies to interfere with a broad range of signaling processes in macrophage that includes Protein Kinase C, the JAK2/STAT1 cascade, and the MAP Kinase pathway. This paper focuses on how L. donovani modulates these signaling pathways that favour its survival and persistence in host cells

ZOLPIDEM IS AN EFFECTIVE OPTION WITH A REDUCED RISK FOR DEPENDENCE IN THE TREATMENT OF INSOMNIA

Insomnia is a highly prevalent sleep disorder that frequently occurs in its acute form and occurs at a rate of approximately 10 per cent in its chronic form in many countries. There is a high prevalence of insomnia in a variety of medical and psychiatric conditions for which insomnia often serves as a risk factor. There are various types of insomnia which are categorized in terms of how it affects sleep it has been shown to negatively affect many physiological, cognitive, and behavioural measures within the body. Recent years have observed that there is sudden increase of various diseases like hypertension, Heart attack, Obesity, Diabetes etc which occurs as a result of insomnia. Hence its impact on financial, social and psychological status of patients and their caregivers cannot be ignored. Thus finding a novel way to tackle these health problems is the need of present times. The most commonly prescribed medications for insomnia are the benzodiazepines (BZP) such as temazepam and diazepam. Although these medications are efficacious, they are associated with tolerance, dependence, residual daytime sedative effects, cognitive and psychomotor impairment, and discontinuation syndromes including rebound insomnia and withdrawal symptoms. For this reason, BZD use should be judicious and is replaced by Zolpidem, a novel non-benzodiazepine hypnotics of Imidazopyridine class that has various advantages over benzodiazepines. Chronic administration of zolpidem produces neither tolerance to its sedative effects nor signs of withdrawal when the drug is discontinued. Also it has little effect on the stages of sleep in normal human subjects. The drug is as effective as benzodiazepines in shortening sleep latency and prolonging total sleep time in patients with insomnia. Tolerance and physical dependence develop only rarely and under unusual circumstances. Keywords: Insomnia, sleep disorder, benzodiazepines, tolerance, dependence, zolpidem, ImidazopyridineÂ

Navigating the Ocean with DRL: Path following for marine vessels

Human error is a substantial factor in marine accidents, accounting for 85% of all reported incidents. By reducing the need for human intervention in vessel navigation, AI-based methods can potentially reduce the risk of accidents. AI techniques, such as Deep Reinforcement Learning (DRL), have the potential to improve vessel navigation in challenging conditions, such as in restricted waterways and in the presence of obstacles. This is because DRL algorithms can optimize multiple objectives, such as path following and collision avoidance, while being more efficient to implement compared to traditional methods. In this study, a DRL agent is trained using the Deep Deterministic Policy Gradient (DDPG) algorithm for path following and waypoint tracking. Furthermore, the trained agent is evaluated against a traditional PD controller with an Integral Line of Sight (ILOS) guidance system for the same. This study uses the Kriso Container Ship (KCS) as a test case for evaluating the performance of different controllers. The ship's dynamics are modeled using the maneuvering Modelling Group (MMG) model. This mathematical simulation is used to train a DRL-based controller and to tune the gains of a traditional PD controller. The simulation environment is also used to assess the controller's effectiveness in the presence of wind.Comment: Proceedings of the Sixth International Conference in Ocean Engineering (ICOE2023

A CROSS-SECTIONAL STUDY OF STRESS AMONG UNDERGRADUATE MEDICAL STUDENTS IN A TERTIARY CARE TEACHING INSTITUTE, JHARKHAND.

Background Medical students are more exposed to stressful situations due to their academic pressure, difficult learning environment, and challenging competency-based medical education design that does not provide enough time for their personal life events. So, chronic stress among medical students results in depression, substance abuse, and even suicide. This study aims to determine the prevalence of stress among undergraduate medical students of RIMS, Ranchi, Jharkhand, India. Methodology  This was a cross-sectional study conducted among 258 undergraduate medical students of RIMS, Ranchi from January 2022 to December 2022. Perceived Stress Scale-10 was used to evaluate the degree of stress among undergraduate medical students. Data obtained was analyzed using MS Excel and SSS based on SPSS and Minitab (2018).  Results A total of 258 undergraduate medical students participated in the study of which 41.4% were male and 58.52% were female. Although a moderate stress rate of 68.9% was registered in most participants, 22.48% were affected by high stress. Participants in the 4th professional MBBS are more likely to experience high stress (45.06%) as compared to students in the 2nd professional MBBS, 1st professional MBBS, and 3rd professional MBBS respectively. The difference in stress severity was statistically significant at p <0.05. Conclusion Most undergraduate medical students (68.99%) have moderate stress. Female (29.8%) are more likely to have high stress. The final professional MBBS students (44.06%) have more high stress.  Recommendation Counseling services to medical college students are strongly recommended to address the stress

Comparative Analysis of Original Wave and Filtered Wave of EEG signal Used in the Prognostic of Bruxism medical Sleep syndrome

The bruxism is a medical sleep syndrome it is the remedial span for crushing the tines and gritting the jowl. Human rarely chore their tines and jowl, slightly than crushing their teeth lacking it producing any signals. The symptoms of bruxism are arduousness in the jowl joint, breakable teeth, headache, earache and difficulty in open in mouth etc. The causes of bruxism are snooze sickness, pressure and nervousness. The REM is a rapid eye movement its a stages of sleep. The EEG signal are used in the measurement of neuron, the alpha, beta, gamma, theta and delta wave are used in the prognostic of bruxism syndrome. Its used in MATLAB coding by the six steps in prognostic in bruxism. Md Belal Bin Heyat | Faijan Akhtar | Shadab Azad "Comparative Analysis of Original Wave & Filtered Wave of EEG signal Used in the Prognostic of Bruxism medical Sleep syndrome" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-1 , December 2016

Convergence properties of the El Farol bar problem with social learning

The El Farol Bar problem proposed by Arthur in [1] is a study of economic system. Though Arthur's main objective was to highlight how humans are more apt in making inductive reasoning for complex decision making process rather than deductive reasoning; the model has been widely used in analysis of economic systems, particularly when congestion issues arise. The original model is described as follows. A population of agents have to decide every week whether to go to the El Farol bar or not. If many agents attend the bar, for example more that 60%, it will be overcrowded and that results unpleasant experience for the attendees. The decision made by each agent is purely individual and based on a random subset of predictors. Arthur's simulation results showed that the system kept fluctuating near the 60% threshold and the agents divided themselves into a 60/40 ratio of bar attendance. In this research, we are interested in interaction-based decision making processes, which are lacking in Arthur's model. Several attempts have been made in the literature to introduce such interaction processes or communication mechanisms to the original model. Those extended models often involve a xed network/neighborhood structure over the agents and the system dynamics were mainly studied with computer simulations [4, 6, 7]. Our contribution is a novel mechanism of information exchange and decision making among the agents, resulting an extended model for the El Farol 1 bar problem. The idea is similar to social communication. Each agent randomly communicates with two other agents within the population to obtain information about the last bar attendance. Based on this information the agent makes a stochastic decision to go to the bar. The aim of the study is to experimentally and rigorously analyse how such a system behaves, in particular how the bar attendance varies. The first part of this thesis is dedicated to simulation results. We first investigate the system settings for which an equilibrium corresponding to the threshold of the bar can be reached. The behaviours of the system related to the initial state of below and above the threshold are discussed. From the perspective of individual attendance, we also address the formation of structures within the population. With the proposed model, the population of agents eventually divides into two groups of attendees: regulars and casuals. In the second part, we show that the dynamics of the proposed system can be analyzed by mean of rigorous mathematics, and the expected time for the system to reach the equilibrium can be proved. For this purpose, we use Drift Analysis as the main tool. Note that Drift Analysis is widely used in Evolutionary Computation to compute expected runtime of Randomised Search Heuristics (see Lehre [8]). Due to the nature of the system that the bar attendance can wamble around the threshold, the importance of analyzing the reduction in the variance is further detailed. The proof of the runtime is shown in Chapter 4 followed by further discussion in Chapter 5. In summary, this study investigate a novel model of the El Farol Bar problem from a social coordination perspective. We show that with the right settings, the system eventually converges to the equilibrium associated with the threshold of the bar. A rigorous analysis of the system dynamics is initiated using advanced probability tools

AI on the Water: Applying DRL to Autonomous Vessel Navigation

Human decision-making errors cause a majority of globally reported marine accidents. As a result, automation in the marine industry has been gaining more attention in recent years. Obstacle avoidance becomes very challenging for an autonomous surface vehicle in an unknown environment. We explore the feasibility of using Deep Q-Learning (DQN), a deep reinforcement learning approach, for controlling an underactuated autonomous surface vehicle to follow a known path while avoiding collisions with static and dynamic obstacles. The ship's motion is described using a three-degree-of-freedom (3-DOF) dynamic model. The KRISO container ship (KCS) is chosen for this study because it is a benchmark hull used in several studies, and its hydrodynamic coefficients are readily available for numerical modelling. This study shows that Deep Reinforcement Learning (DRL) can achieve path following and collision avoidance successfully and can be a potential candidate that may be investigated further to achieve human-level or even better decision-making for autonomous marine vehicles.Comment: Proceedings of the Sixth International Conference in Ocean Engineering (ICOE2023

A smart phone based multi-floor indoor positioning system for occupancy detection

At present there is a lot of research being done simulating building environment with artificial agents and predicting energy usage and other building performance related factors that helps to promote understanding of more sustainable buildings. To understand these energy demands it is important to understand how the building spaces are being used by individuals i.e. the occupancy pattern of individuals. There are lots of other sensors and methodology being used to understand building occupancy such as PIR sensors, logging information of Wi-Fi APs or ambient sensors such as light or CO2 composition. Indoor positioning can also play an important role in understanding building occupancy pattern. Due to the growing interest and progress being made in this field it is only a matter of time before we start to see extensive application of indoor positioning in our daily lives. This research proposes an indoor positioning system that makes use of the smart phone and its built-in integrated sensors; Wi-Fi, Bluetooth, accelerometer and gyroscope. Since smart phones are easy to carry helps participants carry on with their usual daily work without any distraction but at the same time provide a reliable pedestrian positioning solution for detecting occupancy. The positioning system uses the traditional Wi-Fi and Bluetooth fingerprinting together with pedestrian dead reckoning to develop a cheap but effective multi floor positioning solution. The paper discusses the novel application of indoor positioning technology to solve a real world problem of understanding building occupancy. It discusses the positioning methodology adopted when trying to use existing positioning algorithm and fusing multiple sensor data. It also describes the novel approach taken to identify step like motion in absence of a foot mounted inertial system. Finally the paper discusses results from limited scale trials showing trajectory of motion throughout the Nottingham Geospatial Building covering multiple floors

Comparison of path following in ships using modern and traditional controllers

Vessel navigation is difficult in restricted waterways and in the presence of static and dynamic obstacles. This difficulty can be attributed to the high-level decisions taken by humans during these maneuvers, which is evident from the fact that 85% of the reported marine accidents are traced back to human errors. Artificial intelligence-based methods offer us a way to eliminate human intervention in vessel navigation. Newer methods like Deep Reinforcement Learning (DRL) can optimize multiple objectives like path following and collision avoidance at the same time while being computationally cheaper to implement in comparison to traditional approaches. Before addressing the challenge of collision avoidance along with path following, the performance of DRL-based controllers on the path following task alone must be established. Therefore, this study trains a DRL agent using Proximal Policy Optimization (PPO) algorithm and tests it against a traditional PD controller guided by an Integral Line of Sight (ILOS) guidance system. The Krisco Container Ship (KCS) is chosen to test the different controllers. The ship dynamics are mathematically simulated using the Maneuvering Modelling Group (MMG) model developed by the Japanese. The simulation environment is used to train the deep reinforcement learning-based controller and is also used to tune the gains of the traditional PD controller. The effectiveness of the controllers in the presence of wind is also investigated.Comment: Proceedings of the Sixth International Conference in Ocean Engineering (ICOE2023

Potency test of a rape accused in India – Rationale, problems and suggestions in light of the Criminal Law (Amendment) Act, 2013

AbstractIndian legal system makes it mandatory to medically examine any accused of rape as well as other forms of sexual assault. Accused is brought in the police custody for conducting medical examination which includes general physical examination, potency test and evidence collection. The medical examination report of the accused is labeled as the “POTENCY TEST REPORT”. As per the changed definition of rape after Criminal Law (Amendment) Act, 2013, potency test stands irrelevant in rape cases because the changed law does not require peno-vaginal intercourse to call it as rape. However, even after the change in definition of rape and laws related to it, potency test is still a mandatory part of medical examination of accused. Displeasure about the same has also been raised by a fast track court of Delhi. In this paper, we have discussed the rationale of potency test of sexual assault in light of Criminal Law Amendment Act (2013), court judgment and other available literature