Characterisation of an RPC prototype with moderate resistivity plates using tetrafluoroethane (C2H2F4C_2H_2F_4)

Keeping in mind the requirements of high rate capable, cost effective, large area detectors to be used in future high energy physics experiments, commercially available bakelite plates having moderate bulk resistivity are used to build an RPC module. The chamber is tested with cosmic rays in the avalanche mode using 100\% Tetrafluoroethane ($C_2H_2F_4$). Standard NIM electronics are used for this study. The efficiency, noise rate and time resolution are measured. The detailed method of measurement and the first test results are presented.Comment: 6 pages, 5 figures, XV Workshop on Resistive Plate Chambers and Related Detectors - RPC2020 (Accepted manuscript

Host-to-host variation of ecological interactions in polymicrobial infections

Host-to-host variability with respect to interactions between microorganisms and multicellular hosts are commonly observed in infection and in homeostasis. However, the majority of mechanistic models used in analyzing host-microorganism relationships, as well as most of the ecological theories proposed to explain co-evolution of host and microbes, are based on averages across a host population. By assuming that observed variations are random and independent, these models overlook the role of inter-host differences. Here we analyze mechanisms underlying host-to-host variations, using the well-characterized experimental infection model of polymicrobial otitis media (OM) in chinchillas, in combination with population dynamic models and a Maximum Entropy (MaxEnt) based inference scheme. We find that the nature of the interactions among bacterial species critically regulates host-to-host variations of these interactions. Surprisingly, seemingly unrelated phenomena, such as the efficiency of individual bacterial species in utilizing nutrients for growth and the microbe-specific host immune response, can become interdependent in a host population. The latter finding suggests a potential mechanism that could lead to selection of specific strains of bacterial species during the coevolution of the host immune response and the bacterial species.Comment: 39 Pages 6 figure

Maximum Entropy estimation of probability distribution of variables in higher dimensions from lower dimensional data

A common statistical situation concerns inferring an unknown distribution Q(x) from a known distribution P(y), where X (dimension n), and Y (dimension m) have a known functional relationship. Most commonly, n<m, and the task is relatively straightforward. For example, if Y1 and Y2 are independent random variables, each uniform on [0, 1], one can determine the distribution of X = Y1 + Y2; here m=2 and n=1. However, biological and physical situations can arise where n>m. In general, in the absence of additional information, there is no unique solution to Q in those cases. Nevertheless, one may still want to draw some inferences about Q. To this end, we propose a novel maximum entropy (MaxEnt) approach that estimates Q(x) based only on the available data, namely, P(y). The method has the additional advantage that one does not need to explicitly calculate the Lagrange multipliers. In this paper we develop the approach, for both discrete and continuous probability distributions, and demonstrate its validity. We give an intuitive justification as well, and we illustrate with examples.Comment: in revie

Physicochemical analysis of hot water springs of Sikkim-Polok Tatopani, Borong Tatopani and Reshi Tatopani

Fenced by the geo-political features all around, Sikkim sits magnificently in the lap of The Himalayas with Mount Khanchengdzonga signifying the peaks of divinity and cultural proximity. Sikkim is the natural ecological host to many Hot springs of geothermal characteristics. Hot Springs of Sikkim are regarded as ethical and holistic elements having importance of locale panacea. Hot springs are any natural geothermal spring or a natural discharge of groundwater with elevated temperature with respect to the surrounding. The characteristics or the suitability of these hot springs for human use is determined by its chemical constituents. Most of the Hot Springs is rich in several kinds of chemicals and minerals. Presence of these chemicals and minerals along with higher temperature of these hot springs determine its balneotherapeutic properties. The average temperature of the studied Hot springs being 60&deg;C according to Kent classification as &ldquo;Scalding&rdquo; can be regarded as the best ecological niche for thermophilic microorganisms. These Hot springs are supposed to cure off many bone related diseases like arthritis and is also equivalently used in treatment of skin infections and diseases. For curing the Gastrointestinal and bowel associated diseases, water from these hot springs is also drunk. Hence a complete detailed study of the chemicals and the physical properties of the three Hot springs of Sikkim were studied. 30 different physicochemical parameters of the water samples collected from these study areas were analyzed using the ICPMS Spectroscopic methods and Kit method. Physical properties like colour, conductivity, turbidity etc. and chemical parameters like the quantification of anions, cations, trace elements and other chemical constituents of the Tatopani were analysed. A comparison with W.H.O. standards showed that the water sample of Polok and Borong Tatopani water is suitable for drinking purposes whereas Reshi Tatopani water showed higher concentration of TDS (i.e. 608mg/l)

Active Preference Optimization for Sample Efficient RLHF

Reinforcement Learning from Human Feedback (RLHF) is pivotal in aligning Large Language Models (LLMs) with human preferences. Although aligned generative models have shown remarkable abilities in various tasks, their reliance on high-quality human preference data creates a costly bottleneck in the practical application of RLHF. One primary reason is that current methods rely on uniformly picking prompt-generation pairs from a dataset of prompt-generations, to collect human feedback, resulting in sub-optimal alignment under a constrained budget, which highlights the criticality of adaptive strategies in efficient alignment. Recent works [Mehta et al., 2023, Muldrew et al., 2024] have tried to address this problem by designing various heuristics based on generation uncertainty. However, either the assumptions in [Mehta et al., 2023] are restrictive, or [Muldrew et al., 2024] do not provide any rigorous theoretical guarantee. To address these, we reformulate RLHF within contextual preference bandit framework, treating prompts as contexts, and develop an active-learning algorithm, $\textit{Active Preference Optimization}$ ($\texttt{APO}$), which enhances model alignment by querying preference data from the most important samples, achieving superior performance for small sample budget. We analyze the theoretical performance guarantees of $\texttt{APO}$ under the BTL preference model showing that the suboptimality gap of the policy learned via $\texttt{APO}$ scales as $O(1/\sqrt{T})$ for a budget of $T$. We also show that collecting preference data by choosing prompts randomly leads to a policy that suffers a constant sub-optimality. We perform detailed experimental evaluations on practical preference datasets to validate $\texttt{APO}$'s efficacy over the existing methods, establishing it as a sample-efficient and practical solution of alignment in a cost-effective and scalable manner.Comment: New experimental results added. Some reorganizatio

Induced abortion practices in Bengali-speaking communities: a preliminary study

Background: Abortion is termed as ‘medical termination of a pregnancy’ (MTP). In India, abortion can be performed until 24 weeks of pregnancy according to the MTP Amendment Act 2021 which came into effect on 24th September 2021. The topic of abortion is still hotly debated in India and considered taboo in numerous circles. There has been a recent surge in liberal outlook when it comes to perspectives on social issues. However, creases of worry appear on the forehead when a woman faces the issue of making a decision in such matter. The hindrance comes from reasons such as: abortion is illegal, religious beliefs are against abortion, social taboo against abortion, and other factors.Methods: A mixed-method study was conducted using a systematic random sampling method at the Family Planning Hospital, Park Circus, Kolkata. Reproductive histories were collected from 120 women, belonging to reproductive age 20-50 years. Using structured schedule, individual face-to-face and in-depth interviews were conducted.Results: We were confronted with four recurring factors that negatively impacted on their family planning processes which led to an increased rate of abortion. We also found that abortion has a significant relationship with maternal age, education of the mother, family income, and number of parity.Conclusions: Maternal age, religious beliefs, education, family income, number of parity and also knowledge on legal abortion ware the major decisive factor associated with abortion. Poorest, younger, uneducated, women who had tendency to minimize family size were more likely to undergo abortion