Equal Weight Research Articles

Selecting and weighting dynamical models using data-driven approaches

Abstract. In geosciences, multi-model ensembles are helpful to explore the robustness of a range of results. To obtain a synthetic and improved representation of the studied dynamic system, the models are usually weighted. The simplest method, namely the model democracy, gives equal weights to all models, while more advanced approaches base weights on agreement with available observations. Here, we focus on determining weights for various versions of an idealized model of the Atlantic Meridional Overturning Circulation. This is done by assessing their performance against synthetic observations (generated from one of the model versions) within a data assimilation framework using the ensemble Kalman filter (EnKF). In contrast to traditional data assimilation, we implement data-driven forecasts using the analog method based on catalogs of short-term trajectories. This approach allows us to efficiently emulate the model's dynamics while keeping computational costs low. For each model version, we compute a local performance metric, known as the contextual model evidence, to compare observations and model forecasts. This metric, based on the innovation likelihood, is sensitive to differences in model dynamics and considers forecast and observation uncertainties. Finally, the weights are calculated using both model performance and model co-dependency and then evaluated on averages of long-term simulations. Results show good performance in identifying numerical simulations that best replicate observed short-term variations. Additionally, it outperforms benchmark approaches such as strategies based on model democracy or climatology when reconstructing missing distributions. These findings encourage the application of the proposed methodology to more complex datasets in the future, like climate simulations.

Kraje Unii Europejskiej a ubóstwo, przed i po kryzysie COVID-19

The purpose of the paper is to evaluate and present the position of the European Union countries according to the poverty level before and after the COVID-19 crisis, combining five individual indicators. The GRA (Grey Relational Analysis) method was used to calculate the composite poverty indicator. To assess poverty, the study uses criteria from the official database of the European Commission and calculates the aggregate index for 2019 and 2022. All criteria in the model have the same relative importance because the method of equal weight coefficients is applied. The paper proved that the Czech Republic and Slovenia had the most favourable indicators of poverty in both periods, while Greece, Romania, Bulgaria, and Latvia occupied a critical position. In general, the countries of Southern Europe and the Baltic countries have poor poverty indicators. Compared to 2019, according to the country rankings, the poverty level is significantly higher in Finland, Germany, and Hungary, while after the pandemic, the following countries made considerable progress in reducing poverty: Poland, Belgium, Luxembourg, and Cyprus. The presented results can be useful to decision-makers at the macro level in the field of economic, social, and sustainable development policy.

Carnegie Supernova Project I and II: Measurements of H 0 Using Cepheid, Tip of the Red Giant Branch, and Surface Brightness Fluctuation Distance Calibration to Type Ia Supernovae* *This paper includes data gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile.

We present an analysis of Type Ia supernovae (SNe Ia) from the Carnegie Supernova Project I and II and extend the Hubble diagram from optical to near-infrared wavelengths (uBgVriYJH). We calculate the Hubble constant, H 0, using various distance calibrators: Cepheids, the tip of the red giant branch (TRGB), and surface brightness fluctuations (SBFs). Combining all methods of calibration, we derive H 0 = 71.76 ± 0.58 (stat) ± 1.19 (sys) km s−1 Mpc−1 from the B band and H 0 = 73.22 ± 0.68 (stat) ± 1.28 (sys) km s−1 Mpc−1 from the H band. By assigning equal weight to the Cepheid, TRGB, and SBF calibrators, we derive the systematic errors required for consistency in the first rung of the distance ladder, resulting in a systematic error of 1.2 ∼ 1.3 km s−1 Mpc−1 in H 0. As a result, relative to the statistics-only uncertainty, the tension between the late-time H 0 we derive by combining the various distance calibrators and the early-time H 0 from the cosmic microwave background is reduced. The highest precision in SN Ia luminosity is found in the Y band (0.12 ± 0.01 mag), as defined by the intrinsic scatter (σ int). We revisit SN Ia Hubble residual-host mass correlations and recover previous results that these correlations do not change significantly between the optical and near-infrared wavelengths. Finally, SNe Ia that explode beyond 10 kpc from their host centers exhibit smaller dispersion in their luminosity, confirming our earlier findings. A reduced effect of dust in the outskirts of hosts may be responsible for this effect.

Analysis of Morphological and Elemental Composition in Rice, Beans, and Groundnut Husk

The morphological characteristics and elemental composition of these agricultural products provides insights into their nutritional value, chemical properties, and potential industrial applications, contributing to advancements in food science, agriculture, and environmental sustainability. The comprehensive analysis of the morphological and elemental composition of three widely consumed agricultural products: rice, beans, and groundnut husk as a partial substitute for sand due to its high content of calcium, silicon, aluminum, iron, and other elements when properly controlled. Transforming them into practical materials in order to reduce their detrimental impact on the environment. An equal weight of 50 g of Rice husk, 25 g of bean husk, and 25 g of groundnut shell were measured out of 100 g of untreated samples and oven dried at 1000C for 4 hours. The samples were the crushed to fine particle and sieve, which was burned at a temperature of 5500C in an electric furnace for 4 hours. The result obtained microscopic techniques such as Scanning Electron Microscope (SEM) with Energy Disperse X-ray fluorescence (EDXRF) and X-ray diffraction (XRD), were used to observe the surface and element presence in RBGH. The result among other things shows that untreated RBGH atomic concentration of Si is 65.79%, K is 16.01.53%, P is 5.14% Ca is 3.36% and Mg is 3.35% respectively, and the SEM shows that it has a porous cellular structure and consists of irregular-shape particles. The findings shed light on the potential industrial applications of these agricultural byproducts

Urban sustainability assessment: An analysis of how weighting and aggregating coefficient system was used in the development of SUCCEED assessment tool for developing countries

The development of a weighting and aggregating coefficient system used in urban sustainability assessment tools is a process that needs well-defined procedures using a series of steps, methodology, and a systematic approach in its development. The development of assessment tools has been successful in developed countries but developing countries would need to have a structured process that will assist in the development of an assessment tool that is tailored to its environs. This paper aims to understand the various weighting and aggregating coefficient systems employed in the development of sustainability assessment tools. Alongside using these findings to understand how these weighting and aggregating coefficients can be adopted in the development of sustainability assessment tools for developing countries based on their differences, advantages, and disadvantages. Qualitative Content Analysis based on a systematic review of existing literature was used in this study to understand various weighting and aggregating coefficients. It is imperative to note that this research will focus on how assessment tools are developed with a clear focus on sustainability assessment weighting and aggregating. The study also further analyses how a case study SUCCEED (Sustainable Composite Cities Environmental Evaluation and Design Tool) has benefited from the adoption of equal weighting and additive aggregation methods based on validation carried out. The findings of this research show that the selection of weighting and aggregating systems is defined by the relevance, importance, and purpose of the assessment tool. It also develops a guide/recommendations on the process utilised in the development of assessment tools for developing countries.

Portfolio Analysis of Multi-Factor Stock Selection Model Based on Investor Sentiment

Since 1990, China's securities market has been gradually improved. Domestic and foreign scholars have proposed many theoretically perfect investment models, but not many of them have been applied in practice because the market cannot satisfy the strict assumption conditions of the models. Foreign quantitative investment models are not necessarily effective in the Chinese market. Based on this, this paper takes the portfolio theory as a guide, uses the scoring method to construct a multi-factor stock selection model, and selects the relevant factors in combination with the characteristics of the Chinese market. Through empirical analyses, the validity of the multi-factor stock selection model with equal weight allocation in China's market is verified. In addition, this paper innovatively constructs an investor sentiment factor, combines the sentiment timing with the multi-factor stock selection model, optimises the timing on the basis of the multi-factor stock selection model, and proposes an investment strategy to obtain excess returns stably.

Effect of Dietary Supplementation of Tejpatta (Cinnamomum tamala) Leaf Powder as Feed Additive on Growth Performance and Haemato-biochemical Parameters of Broilers

Background: Tejpatta leaves are well known for their use as spice in food for taste and aromatic purposes. It is mainly used for flavoring food and widely used in pharmaceutical preparation because of its hypoglycemic, stimulant, carminative, antidiabetic, antibacterial, antioxidant, anti-ulcer and antimicrobial properties. Keeping the aforementioned properties in view, the present study was to evaluate the effect of dietary supplementation of Tejpatta leaf powder on growth performance and haemato-biochemical parameters of broilers for boosting poultry industry production. Methods: Two hundred and twenty five day-old chicks were randomly assigned into five dietary treatment groups (T1-T5) using CRD, each consisting of 45 chicks with roughly equal average body weights. Each group of 45 chicks was subdivided into three replicates (R1, R2 and R3) having 15 chicks per replicate. The T1 group fed basal diet only, while T2, T3, T4 and T5 groups were fed Tejpatta leaf powder @ 0.25%, 0.75%, 1.25% and 1.75%, respectively, along with basal diet. Result: Significant (P less than 0.01) effect on growth characteristics was noticed in broiler chicks due to dietary supplementation of Tejpatta leaf powder. Significantly (P less than 0.01) higher body weight, weekly body weight gain, average daily body weight gain and performance index was noticed in T4 group and lowest was observed in T1 group. Significantly (P less than 0.01) higher feed intake was observed in T5 group and lowest was in T1 group. Lowest feed conversion ratio was observed in T4 group and highest in T1 group. Non-significant effect on hemoglobin, packed cell volume, red blood corpuscle count, serum glucose, total protein and cholesterol and creatinine levels was observed in various treatment groups. It was concluded that supplementing broiler diet with Tejpatta leaf powder @ 1.25% could be beneficial for improving broiler chick growth performance and hemato-biochemical parameters while having no adverse effects on broiler chicks.

Ionic Liquid-Based Immunization Patch for the Transdermal Delivery of Antigens.

Herein, we report a transdermal patch prepared using an ionic liquid-based solid in oil (IL-S/O) nanodispersion and a pressure-sensitive adhesive (PSA) to deliver the macromolecular antigenic protein, ovalbumin (OVA). The IL-S/O nanodispersion and a PSA were first mixed at an equal weight ratio, then coated onto a release liner, and covered with a support film. To evaluate the effect of the PSA, three types of PSAs, DURO-TAK 87-4098, DURO-TAK 87-4287, and DURO-TAK 87-235A, were used to obtain the corresponding IL-S/O patches SP-4098, SP-4287, and SP-235A, respectively. The prepared IL-S/O patches were characterized for surface morphology, viscoelasticity, and moisture content. In vitro skin penetration and in vivo immunization studies of the IL-S/O patches were performed using Yucatan micropig skin and the C57BL/6NJc1 mice model, respectively. The SP-4098 and SP-4287 delivered 5.49-fold and 5.47-fold higher amounts of drug compared with the aqueous formulation. Although both patches delivered a similar amount of drug, SP-4287 was not detached fully from the release liner after 30 days, indicating low stability. Mice immunized with the OVA-containing SP-4098 produced a 10-fold increase in anti-OVA IgG compared with those treated with an aqueous formulation. These findings suggested that the IL-S/O patch may be a good platform for the transdermal delivery of antigen molecules.

Optimising desired gain indices to maximise selection response.

In plant breeding, we often aim to improve multiple traits at once. However, without knowing the economic value of each trait, it is hard to decide which traits to focus on. This is where "desired gain selection indices" come in handy, which can yield optimal gains in each trait based on the breeder's prioritisation of desired improvements when economic weights are not available. However, they lack the ability to maximise the selection response and determine the correlation between the index and net genetic merit. Here, we report the development of an iterative desired gain selection index method that optimises the sampling of the desired gain values to achieve a targeted or a user-specified selection response for multiple traits. This targeted selection response can be constrained or unconstrained for either a subset or all the studied traits. We tested the method using genomic estimated breeding values (GEBVs) for seven traits in a bread wheat (Triticum aestivum) reference breeding population comprising 3,331 lines and achieved prediction accuracies ranging between 0.29 and 0.47 across the seven traits. The indices were validated using 3,005 double haploid lines that were derived from crosses between parents selected from the reference population. We tested three user-specified response scenarios: a constrained equal weight (INDEX1), a constrained yield dominant weight (INDEX2), and an unconstrained weight (INDEX3). Our method achieved an equivalent response to the user-specified selection response when constraining a set of traits, and this response was much better than the response of the traditional desired gain selection indices method without iteration. Interestingly, when using unconstrained weight, our iterative method maximised the selection response and shifted the average GEBVs of the selection candidates towards the desired direction. Our results show that the method is an optimal choice not only when economic weights are unavailable, but also when constraining the selection response is an unfavourable option.

Integrating behavioural thermoregulatory strategy into the animal personality framework using the common lizard, Zootoca vivipara as a model

The study of consistent between-individual behavioural variation in single (animal personality) and across two or more behavioural traits (behavioural syndrome) is a central topic of behavioural ecology. Besides behavioural type (individual mean behaviour), behavioural predictability (environment-independent within-individual behavioural variation) is now also seen as an important component of individual behavioural strategy. Research focus is still on the ‘Big Five’ traits (activity, exploration, risk-taking, sociability and aggression), but another prime candidate to integrate to the personality framework is behavioural thermoregulation in small-bodied poikilotherms. Here, we found animal personality in thermoregulatory strategy (selected body temperature, voluntary thermal maximum, setpoint range) and ‘classic’ behavioural traits (activity, sheltering, risk-taking) in common lizards (Zootoca vivipara). Individual state did not explain the between-individual variation. There was a positive behavioural type—behavioural predictability correlation in selected body temperature. Besides an activity—risk-taking syndrome, we also found a risk-taking—selected body temperature syndrome. Our results suggest that animal personality and behavioural syndrome are present in common lizards, both including thermoregulatory and ‘classic’ behavioural traits, and selecting high body temperature with high predictability is part of the risk-prone behavioural strategy. We propose that thermoregulatory behaviour should be considered with equal weight to the ‘classic’ traits in animal personality studies of poikilotherms employing active behavioural thermoregulation.

Incorporation of RCM-simulated spatial details into climate change projections derived from global climate models

Regional climate models (RCMs) exhibit greater potential than global models (GCMs) in capturing geographical details of climate change arising from orography and land–water distribution, but dynamical downscalings are only available for a limited number of GCMs. The full GCM ensembles are much more representative. Furthermore, the current EURO-CORDEX RCM runs most likely underestimate future warming. Thus, neither GCMs nor RCMs as such constitute an ideal tool for preparing reliable spatially detailed climate projections. This study introduces an easy-to-use GCM-RCM hybrid method that takes advantage of the best properties of both model categories. The large-scale response is adopted from GCM simulations, but the pattern is enriched with RCM-simulated details. For temperature projections, the procedure resembles the conventional pattern-scaling technique. However, the spatial averages of temperature change used for scaling are calculated over an area surrounding each grid point, either by giving an equal weight to the entire area or by taking into account the land–sea distribution. For precipitation, a linearised version of the method has been formulated. The method is demonstrated by integrating spatial details from 12 EURO-CORDEX RCM simulations with the CMIP6 multi-GCM mean projection. The resulting temperature responses include RCM-generated spatial details of up to ∼\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim$$\\end{document} 1 ∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\circ$$\\end{document}C while effectively correcting the general tendency of RCMs to underestimate warming in Europe. For precipitation, geographical details originating from the different CORDEX runs tend to diverge, resulting in a low signal-to-noise ratio. This probably reflects the substantial impact of internal variability on small-scale changes in precipitation.

Closing the Loop between Waste-to-Energy Technologies: A Holistic Assessment Based on Multiple Criteria

This paper puts forward a generic methodological framework to holistically assess WtE technologies based on the PROMETHEE approach. In addition to environmental and economic aspects, the method focuses on large-scale applicability and social preference, thus adopting economic, environmental, social, and technological criteria. Three data sources are selected, namely the scientific literature, a public survey, and an experts’ opinion survey, which is a novel combination with the aim to cover public consensus, technological applicability, and to provide alternative data sources for the economic and environmental criteria, thus enriching the methodology with the input of location specific data. The demonstration of the applicability of the proposed methodology is realized at a national level for the case of Greece. Anaerobic Digestion is shown to be the most preferable choice, recognized for its cost-effectiveness and lower environmental burden to other WtE technologies (i.e., gasification, pyrolysis, incineration). When all criteria are evaluated with equal weights, anaerobic digestion greatly outperforms incineration (net flow 0.833 versus 0.1667), while incineration only becomes the most preferred choice if the social criterion is in high focus (i.e., over 63% weight).

Deciphering genotype-by-environment interaction of grass pea genotypes under rain-fed conditions and emphasizing the role of monthly rainfall

Rainfed regions have inconsistent spatial and temporal rainfall. So, these regions could face water deficiency during critical stages of crop growth. In this regard, multi-environment trials could play a key role in introducing stable genotypes with good performance across several rainfed regions. Grass pea, as a potential forage crop, is a resilient plant that could grow in unsuitable circumstances. In this study, agro-morphological attributes of 16 grass pea genotypes were examined in four semi-warm rain-fed regions during the years 2018–2021. The MLM analysis of variance showed a significant genotype-by-environment interaction (GEI) for dry yield, seed yield, days to maturity, days to flowering, and plant height of grass pea. The PLS (partial least squares) regression revealed that rainfall in the grass pea establishment stage (October and November) is meaningful. For grass pea cultivation, monthly rainfall during plant growth is important, especially in May, with an aim for seed yield. Regarding dry yield, G5, G10, G11, G12, G13, and G15 were selected as good performers and stable genotypes using DY × WAASB biplots, while SY × WAASB biplot manifested G2, G3, G12, and G13 as superior genotypes with stable seed yield. Considering equal weights for yield as well as the WAASB stability index (50/50), G13 was selected as the best one. Among test environments, E2 and E11 played a prominent role in distinguishing the above genotypes from other ones. In this study, MTSI (multi-trait stability index) analysis was applied to select a stable genotype, considering all measured agro-morphological traits simultaneously. Henceforth, the G5 and G15 grass pea genotypes were discerningly chosen due to their commendable performance in the WAASBY plot. In this context, G13 did not emerge as the winner based on MTSI; however, it exhibited an MTSI value in close proximity to the outer boundary of the circle. Consequently, upon comprehensive consideration of all traits, it is deduced that G5, G13, and G15 can be appraised as promising superior genotypes with stability across diverse environmental conditions.

Adequate Levels of Zinc and Copper on Turkey Poult Performance, Immunological Response, and Skeletal Health.

In this study, the impact of varying dietary zinc (Zn) and copper (Cu) levels on the growth, immunological response, and skeletal health of developing turkey poults was investigated. For 0-4 and 5-8 weeks of age, respectively, three Zn levels of 50, 70, and 90mg/kg and 45, 65, and 85mg/kg were employed. Three Cu levels, namely 8, 12, and 16mg/kg for 0-8 weeks of age, were also utilized. There were 288 (9 × 4 × 8) day-old turkey poults with equal body weight that were randomly assigned to 9 treatments, each consisting of 4 replicates and 8 poults per replicate. In comparison to other dietary combinations, there was a significant (P ≤ 0.05) increase in body weight gain observed in the 90 and 85mg Zn/kg with 16mg Cu/kg diet during 0-4 and 0-8 weeks of age, respectively, and the 70 and 65mg Zn with 16mg Cu /kg diet during 0-4 and 0-8 weeks of age, respectively. When compared to low levels of zinc in the diet at 5-8 and 0-8 weeks of age, respectively, feed conversion ratio was shown to be significantly (P ≤ 0.01) better with 90 and 85mg Zn/kg diet. In a similar pattern, feed utilization efficiency was considerably (P ≤ 0.01) higher at 16mg Cu/kg diet than it was at lower Cu levels in the diets given to the animals over the 0-4 week period. Compared to other dietary combinations, there was a substantial (P ≤ 0.01) improvement in cell-mediated immune response (foot web index to PHAP) and humoral immune response (HA titer to SRBC) when 85mg zinc and 16mg copper/kg diet was consumed at 0-4 and 5-8 weeks of age. At greater dietary Zn and Cu levels than its lower values, the weight of the spleen and thymus was considerably (P ≤ 0.05) higher. In a dietary combination of 90mg Zn with 16mg Cu/kg during 0-4 and 85mg Zn with 16mg Cu/kg diet during 5-8 weeks of age, respectively, there were significantly (P ≤ 0.05) greater bone width (proximal and distal), tibia bone ash, calcium, and phosphorus detected respectively. Significantly (P ≤ 0.01) greater Zn and Fe contents were found in the tibia bone at 90 and 85mg Zn/kg diet, respectively, compared to values obtained at other Zn levels in the diet throughout 0-4 and 5-8 weeks of age. During the first 8 weeks of life, a diet containing 12mg of copper per kilogram was shown to have a significantly (P ≤ 0.05) increased Zn and Fe content in the tibia bone compared to other levels. It is possible to draw the conclusion from the data that, for growing turkey poults, dietary combinations of 90mg Zn/kg with 16mg Cu/kg diet and 85mg Zn with 16mg Cu/kg diet between 0 and 4 and 5-8 weeks of age, respectively, were sufficient for optimum development, immunity, and skeletal health indices.

Targeting the long non-coding RNA MIAT for the treatment of fibroids in an animal model.

Our previous studies indicated that there is overexpression of MIAT in fibroids and MIAT is a sponge for the miR-29 family in these tumors. The objective of the present study was to determine if the knockdown of MIAT in fibroid xenografts will increase miR-29 levels and reduce the expression of genes targeted by this miRNA such as collagen and cell cycle regulatory proteins in a mouse model for fibroids. Ovariectomized CB-17 SCID/Beige mice bearing estrogen/progesterone pellets were implanted subcutaneously in the flank with equal weight of fibroid explants which had been transduced by lentivirus for either control (empty vector) or MIAT knockdown for four weeks (n=7). Knockdown of MIAT in fibroid xenografts resulted in a 30% reduction of tumor weight and a marked increase in miR-29a, -b, and -c levels in the xenografts. There was reduced cell proliferation and expression of cell cycle regulatory genes CCND1, CDK2, and E2F1 and no significant changes in apoptosis. The xenografts with MIAT knockdown expressed lower mRNA and protein levels of FN1, COL3A1, and TGF-β3, and total collagen protein. Targeting MIAT, which sponges the pro-fibrotic miR-29 family, is an effective therapy for fibroids by reducing cell proliferation and thereby, tumor growth and accumulation of ECM, which is a hallmark of these benign gynecologic tumors.

Growth, Fatty Acid Profile and Malondialdehyde Concentration of Meagre Argyrosomus regius Fed Diets with Different Lipid Content

The aim of the study was to evaluate the growth, fatty acid profile and concentration of malondialdehyde of muscle tissue of meagre Argyrosomus regius fed diets with different lipid content. The long-term experiment was conducted in three feeding groups: A (CP = 52.0; CL = 21.0), B (CP = 56.0; CL = 18.0), C (CP = 48.0; CL = 16.0) with two replicates in marine net cages on Bisage Island, Adriatic Sea over 20 months. At the beginning of the experiment, fish were of equal weight (6.83 ± 1.03 g) and length (8.57 ± 0.49 cm) and were fed to satiation during the experiment. At the end of the experiment, the fish from each feeding group (n = 110) were measured and muscle tissue was collected (n = 60) and stored at −80 °C until analysis. The final weight and condition factor were significantly different (p < 0.05) between the groups. The highest ratio of crude fats and n-3/n-6-fatty acids was found in the muscle tissue of group A. Fish fed diet A also exhibited higher MDA levels compared to fish in the other feeding groups, indicating elevated levels of lipid peroxidation in muscle tissues. Experimental feeding group A showed better growth performance, a higher content of the beneficial fatty acids EPA and DHA and a more favorable n-3/n-6 ratio than feeding groups B and C. Continuously monitoring and adjusting feeding protocols in accordance with lipid content and fatty acid composition could maximize growth and health outcomes in meagre farming.

Assessing the Quality of Life of Regional Centres in Poland in the Context of Smart and Sustainable Cities

Abstract The article addresses the issue of quality of life in cities based on developed methodology. A multidimensional approach was adopted, namely 28 subindices characterizing seven dimensions affecting the quality of life in 18 provincial cities in Poland. The developed methodology consisted of two stages. In the first stage, using the indicators, the values of quality-of-life indices for the studied dimensions were determined. In the second stage, using these results, the values of the total quality-of-life indices in the studied cities were measured. Then, rankings for the cities in question were created. In addition, based on the values of the dimension indices and total indices, the levels of quality of life were determined. Relationships between parameters characterizing the sizes of studied cities and their wealth and the determined quality of life were also measured. The Gray Rational Analysis method was used for ranking, and three objective analytical methods were used to determine index weights: Equal weight, Entropy and CRITIC, and the Laplace’s criterion. The results indicate that living standards in the studied cities vary widely, both in terms of the value of the total index and the indices of individual dimensions. The best living conditions were found in Warsaw (the capital of Poland), Białystok and Olsztyn, and the worst in Kielce and Szczecin.

Empirical Assessment of the Efficiency of Poland’s Energy Transition Process in the Context of Implementing the European Union’s Energy Policy

This article addresses one of the contemporary economy’s most challenging endeavors: the energy transition. Specifically, the aim of the study was to assess the effectiveness of Poland’s energy transition process between 2004 and 2021. A comprehensive approach is employed to analyze Poland’s energy transition process, focusing on the effectiveness of implementation through the Energy Transition Effectiveness Index. This methodology incorporates four dimensions, namely energy security, economic considerations, climate impact, and social aspects, each characterized by 22 sub-indices. The research methodology employs a two-tiered approach based on the multi-criteria decision making methodology. The EDAS method is utilized to determine the indices’ values, while the CRITIC, equal weights, and statistical variance methods and Laplace’s criterion are employed to ascertain sub-indices values and dimension weights, particularly useful for decision making under uncertainty. Moreover, the relationship between these indices, the Energy Transition Effectiveness Index, and Poland’s Gross Domestic Product is explored. By evaluating Poland’s energy transition effectiveness from 2004 to 2021 and comparing the results with other European Union countries, it becomes evident that the effectiveness varies over time. Despite encountering economic and social challenges during the energy sector’s transformation, Poland exhibits positive progress in its energy transition efforts, outperforming certain European Union counterparts. However, there is a pressing need to intensify efforts to curtail emissions and enhance renewable energy utilization. The European Union’s support and coordination are deemed crucial in facilitating these endeavors, alongside fostering the wider adoption of best practices among member states. The developed methodology stands as a valuable tool for ongoing evaluation of transformation processes across European Union nations.

3D large-scale forward modeling of gravitational fields using triangular spherical prisms with polynomial densities in depth

To take the sphericity of the Earth into account, tesseroids are often utilized as grid elements in large-scale gravitational forward modeling. However, such elements in a latitude–longitude mesh suffer from degenerating into poorly shaped triangles near poles. Moreover, tesseroids have limited flexibility in describing laterally variable density distributions with irregular boundaries and also face difficulties in achieving completely equivalent division over a spherical surface that may be desired in a gravity inversion. We develop a new method based on triangular spherical prisms (TSPs) for 3D gravitational modeling in spherical coordinates. A TSP is defined by two spherical surfaces of triangular shape, with one of which being the radial projection of the other. Due to the spherical triangular shapes of the upper and lower surfaces, TSPs enjoy more advantages over tesseroids in describing mass density with different lateral resolutions. In addition, such an element also allows subdivisions with nearly equal weights in spherical coordinates. To calculate the gravitational effects of a TSP, we assume the density in each element to be polynomial along radial direction so as to accommodate a complex density environment. Then, we solve the Newton’s volume integral using a mixed Gaussian quadrature method, in which the surface integral over the spherical triangle is calculated using a triangle-based Gaussian quadrature rule via a radial projection that transforms the spherical triangles into linear ones. A 2D adaptive discretization strategy and an extension technique are also combined to improve the accuracy at observation points near the mass sources. The numerical experiments based on spherical shell models show that the proposed method achieves good accuracy from near surface to a satellite height in the case of TSPs with various dimensions and density variations. In comparison with the classical tesseroid-based method, the proposed algorithm enjoys better accuracy and much higher flexibility for density models with laterally irregular shapes. It shows that to achieve the same accuracy, the number of elements required by the proposed method is much less than that of the tesseroid-based method, which substantially speeds up the calculation by more than 2 orders. The application to the tessellated LITHO1.0 model further demonstrates its capability and practicability in realistic situations. The new method offers an attractive tool for gravity forward and inverse problems where the irregular grids are involved.

Regional disparity in energy poverty: A spatial analysis of Odisha

Energy poverty is one of the major deprivations that has direct effect on the well-being of a household at micro level. At macro level, it also has significant effect and hinders the sustainable development of a nation. The binary measurement, commonly used to identify the energy poor population, has major drawbacks as it only takes accessibility of the services into consideration, whereas, in the contemporary period more emphasis should be on the affordability, quality, reliability and legal implications of energy services. The present study, therefore, tries to estimate the energy poverty condition by following a multi-dimensional approach and also tries to identify the actual energy poor by analysing the spatial disparity prevalent in the state of Odisha. A multidimensional framework is used to capture different aspects of energy provisioning at household level and an energy poverty index is constructed by assigning equal weights for the parameters. Spatial disparity is measured by considering proxies for the social parameters and following Gini’s coefficient of disparity measurement. The results indicated persistence of disparity in energy poverty at regional, inter and intra-district levels.