Revisiting mass-radius relationships for exoplanet populations: a machine learning insight

The growing number of exoplanet discoveries and advances in machine learning techniques have opened new avenues for exploring and understanding the characteristics of worlds beyond our Solar System. In this study, we employ efficient machine learning approaches to analyze a dataset comprising 762 confirmed exoplanets and eight Solar System planets, aiming to characterize their fundamental quantities. By applying different unsupervised clustering algorithms, we classify the data into two main classes: 'small' and 'giant' planets, with cut-off values at $R_{p}=8.13R_{\oplus}$ and $M_{p}=52.48M_{\oplus}$. This classification reveals an intriguing distinction: giant planets have lower densities, suggesting higher H-He mass fractions, while small planets are denser, composed mainly of heavier elements. We apply various regression models to uncover correlations between physical parameters and their predictive power for exoplanet radius. Our analysis highlights that planetary mass, orbital period, and stellar mass play crucial roles in predicting exoplanet radius. Among the models evaluated, the Support Vector Regression consistently outperforms others, demonstrating its promise for obtaining accurate planetary radius estimates. Furthermore, we derive parametric equations using the M5P and Markov Chain Monte Carlo methods. Notably, our study reveals a noteworthy result: small planets exhibit a positive linear mass-radius relation, aligning with previous findings. Conversely, for giant planets, we observe a strong correlation between planetary radius and the mass of their host stars, which might provide intriguing insights into the relationship between giant planet formation and stellar characteristics.Comment: Accepted for publication in MNRAS. 17 pages, 18 figure

Coordinated Demand Response and Distributed Generation Management in Residential Smart Microgrids

Nowadays with the emerging of small-scale integrated energy systems (IESs) in form of residential smart microgrids (SMGs), a large portion of energy can be saved through coordinated scheduling of smart household devices and management of distributed energy resources (DERs). There are significant potentials to increase the functionality of a typical demand-side management (DSM) strategy, and typical implementation of building-level DERs by integrating them into a cohesive, networked package that fully utilizes smart energy-efficient end-use devices, advanced building control/automation systems, and an integrated communications architecture to efficiently manage energy and comfort at the end-use location. By the aid of such technologies, residential consumers have also the capability to mitigate their energy costs and satisfy their own requirements paying less attention to the configuration of the energy supply system. Regarding these points, this chapter initially defines an efficient framework for coordinated DSM and DERs management in an integrated building and SMG system. Then a working energy management system (EMS) for applications in residential IESs is described and mathematically modeled. Finally, the effectiveness and applicability of the proposed model is tested and validated in different operating modes compared to the existing models. The findings of this chapter show that by the use of an expert EMS that coordinates supply and demand sides simultaneously, it is very possible not only to reduce energy costs of a residential IES, but also to provide comfortable lifestyle for occupants

Melting of Major Glaciers in Himalayas: Role of Desert Dust and Anthropogenic Aerosols

The Himalayan and Tibet Glaciers, that are among the largest bodies of ice and fresh water resource outside of the polar ice caps, face a significant threat of accelerated meltdown in coming decades due to climate variability and change. The rate of retreat of these glaciers and changes in their terminus (frontal dynamics) is highly variable across the Himalayan range. These large freshwater sources are critical to human activities for food production, human consumption and a whole host of other applications, especially over the Indo-Gangetic (IG) plains. They are also situated in a geo-politically sensitive area surrounded by China, India, Pakistan, Nepal and Bhutan where more than a billion people depend on them. The major rivers of the Asian continent such as the Ganga (also known as Ganges), Brahmaputra, Indus, Yamuna, Sutluj etc., originate and pass through these regions and they have greater importance due to their multi-use downstream: hydro power, agriculture, aquaculture, flood control, and as a freshwater resource. Recent studies over the Himalayan Glaciers using ground-based and space-based observations, and computer models indicate a long-term trend of climate variability and change that may accelerate melting of the Himalayan Glaciers.https://digitalcommons.chapman.edu/sees_books/1001/thumbnail.jp

Estimating regional evapotranspiration from remotely sensed data by surface energy balance models

Spatial and temporal variations of surface radiative temperatures of the burned and unburned areas of the Konza tallgrass prairie were studied. The role of management practices, topographic conditions and the uncertainties associated with in situ or airborne surface temperature measurements were assessed. Evaluation of diurnal and seasonal spectral characteristics of the burned and unburned areas of the prairie was also made. This was accomplished based on the analysis of measured spectral reflectance of the grass canopies under field conditions, and modelling their spectral behavior using a one dimensional radiative transfer model

Deductive synthesis of recursive plans in linear logic

Linear logic has previously been shown to be suitable for describing and deductively solving planning problems involving conjunction and disjunction. We introduce a recursively defined datatype and a corresponding induction rule, thereby allowing recursive plans to be synthesised. In order to make explicit the relationship between proofs and plans, we enhance the linear logic deduction rules to handle plans as a form of proof term

Effect of Drilling Fluid Properties on Rate of Penetration

Zadaća ovoga rada je odrediti učinak svojstava bušačih fluida na brzinu bušenja u ležištu koristeći dnevne izvještaje bušenja. Na osnovi naših studija na terenu, slijedeća svojstva bušačih fluida u nejednakom omjeru utječu na brzinu bušenja: težina isplake, plastična viskoznost i koncentracija krutih čestica. Rezultat ove studije pokazuje da je čisti učinak svojstava bušačeg fluida na brzinu bušenja manji no što se smatralo. Brzina bušenja smanjuje se povećanjem plastične viskoznosti, koncentracije krutih čestica i težine isplake. Smanjenje brzine bušenja više se pripisuje povećanju dubine, zato što se povećanjem dubine povećava čvrstoća stijene i smanjuje poroznost.The scope of this work is to determine the effect of drilling fluid properties on penetration rate in a field using daily drilling reports. Based on our field studies the following drilling fluid properties affect penetration rate to varying degrees: mud weight, plastic viscosity and solid content. The result of this study shows that the net effect of drilling fluid properties on penetration rate is less than what it thought to be. Penetration rate is decreased by increasing plastic viscosity, solid content and mud weight. Decreasing the penetration rate is more attributed to increase of depth, because by increasing the depth, rock strength increases and porosity decreases

An optimized direct control method applied to multilevel inverter for microgrid power quality enhancement

Multifunctional DGs and active power filters have become a mature technology in recent years, so in this paper, an optimized current control method for a multilevel converter is proposed. The control method will overcome harmonic current tracking inefficiency of previous control methods in online harmonic compensation applications in microgrids. This control method is applicable for grid-connected inverter-based multi-functional Distributed Generation (DG) converters. It could also be used in active power filter applications which need high-speed reference tracking ability. Having the advantages of current control methods like hysteresis band control, proportional-integral (PI) and proportional-resonant (PR) control methods, the proposed approach overcomes disadvantages of these methods especially in harmonic reference tracking as it will be discussed in detail. The main advantages of this method are the simplicity of implementation, calculation delay compensation and its fast response to changes. The power electronic circuit, operating principles, two-horizon predicted switching states of multilevel inverter, experimental results and applications of this control method will be discussed in the paper. For studying the feasibility of the control method, an experimental prototype is tested in a microgrid platform

Brightest group galaxies-II : the relative contribution of BGGs to the total baryon content of groups at z <1.3

We performed a detailed study of the evolution of the star formation rate (SFR) and stellar mass of the brightest group galaxies (BGGs) and their relative contribution to the total baryon budget within $R_{200}$ ($f^{BGG}_{b,200}$). The sample comprises 407 BGGs selected from X-ray galaxy groups ($M_{200}=10^{12.8}-10^{14} \;M_{\odot}$) out to $z\sim1.3$ identified in the COSMOS, XMM-LSS, and AEGIS fields. We find that BGGs constitute two distinct populations of quiescent and star-forming galaxies and their mean SFR is $\sim2$ dex higher than the median SFR at $z 2$ dex. The mean (median) of stellar mass of BGGs has grown by $0.3$ dex since $z=1.3$ to the present day. We show that up to $\sim45\%$ of the stellar mass growth in a star-forming BGG can be due to its star-formation activity. With respect to $f^{BGG}_{b,200}$, we find it to increase with decreasing redshift by $\sim0.35$ dex while decreasing with halo mass in a redshift dependent manner. We show that the slope of the relation between $f^{BGG}_{b,200}$ and halo mass increases negatively with decreasing redshift. This trend is driven by an insufficient star-formation in BGGs, compared to the halo growth rate. We separately show the BGGs with the 20\% highest $f^{BGG}_{b,200}$ are generally non-star-forming galaxies and grow in mass by processes not related to star formation (e.g., dry mergers and tidal striping). We present the $M_\star-M_h$ and $M_\star/M_h-M_h$ relations and compare them with semi-analytic model predictions and a number of results from the literature. We quantify the intrinsic scatter in stellar mass of BGGs at fixed halo mass ($\sigma_{log M_{\star}}$) and find that $\sigma_{log M_{\star}}$ increases from 0.3 dex at $z\sim0.2$ to 0.5 dex at $z\sim1.0$ due to the bimodal distribution of stellar mass