Variability Of Parameters Research Articles

Diagnostic utility of electrocardiogram for screening of cardiac injury on cardiac magnetic resonance in post-hospitalised COVID-19 patients: a prospective multicenter study

BackgroundThe role of ECG in ruling out myocardial complications on cardiac magnetic resonance (CMR) is unclear. We examined the clinical utility of ECG in screening for cardiac abnormalities on CMR among post-hospitalised COVID-19 patients. MethodsPost-hospitalised patients (n = 212) and age, sex and comorbidity-matched controls (n = 38) underwent CMR and 12‑lead ECG in a prospective multicenter follow-up study. Participants were screened for routinely reported ECG abnormalities, including arrhythmia, conduction and R wave abnormalities and ST-T changes (excluding repolarisation intervals). Quantitative repolarisation analyses included corrected QT (QTc), corrected QT dispersion (QTc disp), corrected JT (JTc) and corrected T peak-end (cTPe) intervals. ResultsAt a median of 5.6 months, patients had a higher burden of ECG abnormalities (72.2% vs controls 42.1%, p = 0.001) and lower LVEF but a comparable cumulative burden of CMR abnormalities than controls. Patients with CMR abnormalities had more ECG abnormalities and longer repolarisation intervals than those with normal CMR and controls (82% vs 69% vs 42%, p < 0.001). Routinely reported ECG abnormalities had poor discriminative ability (area-under-the-receiver-operating curve: AUROC) for abnormal CMR, AUROC 0.56 (95% CI 0.47–0.65), p = 0.185; worse among female than male patients. Adding JTc and QTc disp improved the AUROC to 0.64 (95% CI 0.55–0.74), p = 0.002, the sensitivity of the ECG increased from 81.6% to 98.0%, negative predictive value from 84.7% to 96.3%, negative likelihood ratio from 0.60 to 0.13, and reduced sex-dependence variabilities of ECG diagnostic parameters. ConclusionPost-hospitalised COVID-19 patients have more ECG abnormalities than controls. Normal ECGs, including normal repolarisation intervals, reliably exclude CMR abnormalities in male and female patients.

Analysis on Spatial Variability of Hydrochemical Characteristics and Control Factors of Jinan Baotu Spring Area

To understand the karst groundwater hydrochemical characteristics and ion sources of the Jinan Baotu Spring area, this study focused on the three functional zones as an indirect recharge area, direct recharge area, and discharge area. Through water sample collection and testing, the spatial variability of groundwater chemical characteristics in different functional zones and the formation mechanism were analyzed using hydrochemistry parameter statistics, multivariate statistics, self-organizing map, hydrochemistry graphical analysis, ion ratios, and other methods, guided by the theory of groundwater flow system and combined with regional physical geography and hydrogeological conditions. The results showed that： the groundwater of each functional zone was alkaline as is typical in the dissolution of carbonate minerals. Owing to the different groundwater runoff pathways, the variability of water chemistry parameters in different functional areas was obvious. The groundwater of the discharge area was recharged by both the direct recharge area and the indirect recharge area. The hydrochemistry type changed from HCO3-Ca type to HCO3·SO4-Ca type through the indirect recharge area to the discharge area. The presence of a small amount of gypsum dissolution within the aquifer generated Ca2+ and SO42-. The ions in groundwater mainly came from the dissolution and filtration of aquifer rock minerals, and at the same time, they were affected by cation exchange, mineral dissolution equilibrium, and the combined effects of human activities. The groundwater in the Baotu Spring area was greatly influenced by human activities, which to some extent affected the evolution of groundwater hydrochemistry in the spring area.

Analytical Study of R C C Deck Slab Bridge with Variable Parameters

Bridges ware always proved to be the key elements for the infrastructural development of country .While designing the bridges ,three major aspects were always to be considered. These three factors were strength , stability and cost effectiveness .It was observed that cost economy was based on width to span ratio of bridge. Another important aspect of economics of bridge was the thickness of deck slab. The length/span of bridge was kept constant and magnitude of width was selected as variable parameter. Four different width to span ratio were taken as 0.75,1, 1.5 and 2.0 respectively. Keeping the same width to span ratios , design calculations were carried out for 0.6 m and 0.7 m deck slab thickness Design was carried out for Mix M-30 and steel as Fe -415. Total eight cases were studied to observe an economy of deck slab bridge Four cases were considered for different parameters of design of deck slab . For all the four width to span ratios ,mentioned above for 0.6 m deck slab thickness and four cases for 0.7 m deck slab thickness were attempted. It was concluded that for width to span ratio=1.0 , was suitable for minimum cost . The results thus obtained were shown in tabular form .The results thus shown were useful for optimizing the design of deck slab bridges . This analysis is extremely useful to civil engineers, practicing engineers, contractors, research scholars and budding engineers.

Estimates of the Fugacity of CO2 in the Vridi Channel (Côte d’Ivoire)

From July to November 2023 and in April 2024, surface waters were collected at three separate sampling sites within the Vridi channel, to measure physical and chemical parameters such as salinity, temperature, pH, Dissolved Inorganic Carbon (DIC). The fCO2 and Total Alkalinity were calculated from pH and DIC. These surface waters were sampling during 4 seasons to study the variability of the carbonate system parameters. Low salinity and low temperature were observed in July -August because this period corresponded to high precipitation inducing salinity dilution and the appearance of coastal upwelling. High salinity and temperature were observed in a great dry season. In the whole, salinity and temperature have same trends of variability. Whatever the season, surface waters were oversaturated in fCO2 with respect to atmospheric equilibrium in the Vridi channel except in dry season. On average the fCO2 decreased from the great cold season to the hot season following marine season. Indeed, the high coastal upwelling appeared in July and disappeared in October. The variability of the channel fCO2 followed the upwelling events along the coastal areas. Moreover, parameters such as Total Alkalinity (TA), Dissolved Inorganic Carbon and pH undergone the influence of coastal upwelling as fCO2 in the Vridi channel.

The Ex-Timing trial: evaluating morning, afternoon, and evening exercise on the circadian clock in individuals with type 2 diabetes and overweight/obesity—a randomized crossover study protocol

BackgroundExercise is known to provide multiple metabolic benefits such as improved insulin sensitivity and glucose control in individuals with type 2 diabetes mellitus (T2DM) and those at risk. Beyond the traditional exercise dose, exercise timing is perceived as a contemporary hot topic, especially in the field of T2DM; however, the number of intervention studies assessing exercise timing and glucose metabolism is scarce. Our aim is to test the effect of exercise timing (i.e., morning, afternoon, or evening) on the inter-individual response variability in glycemic control and related metabolic health parameters in individuals with T2DM and those at risk during a 12-week intervention.MethodsA randomized crossover exercise intervention will be conducted involving two groups: group 1, individuals with T2DM; group 2, age-matched older adults with overweight/obesity. The intervention will consist of three 2-week blocks of supervised post-prandial exercise using high-intensity interval training (HIIT). Between each training block, a 2-week washout period, where participants avoid structured exercise, will take place. Assessments will be conducted in both groups before and after each exercise block. The primary outcomes include the 24-h area under the curve continuous glucose monitoring-based glucose. The secondary outcomes include body composition, resting energy expenditure, insulin response to a meal tolerance test, maximal aerobic capacity, peak power output, physical activity, sleep quality, and insulin and glucose levels. All primary and secondary outcomes will be measured at each assessment point.DiscussionOutcomes from this trial will provide us additional insight into the role of exercise timing on the inter-individual response variability in glycemic control and other related metabolic parameters in two distinct populations, thus contributing to the development of more effective exercise prescription guidelines for individuals with T2DM and those at risk.Trial registrationClinicalTrials.gov NCT06136013. Registered on November 18, 2023.

Turbulent Exchange in Unsteady Air-Sea Interaction at Small and Submesoscales

An adequate description of the interaction between the atmosphere and ocean remains one of the most important problems of modern oceanology and climatology. An extremely wide variety of physical processes occurring in the coupled layers, a large range of scales, a moving boundary, all this factors significantly complicates the creation of models that would allow calculating the physical characteristics in both media with the necessary accuracy. In this paper the temporal variability of dynamic parameters in the driving layer of the atmosphere and in the near-surface layer of the sea on small and sub-mesoscales from one to several tens of hours is considered. The collected experimental data show a very high correlation between the dynamic wind speed and turbulence intensity in the upper sea layer on all scales recorded. An important distinguishing feature of all measured physical quantities in both media is the presence of quasi-periodic oscillations with different periods. For a more accurate description of momentum and energy fluxes from the atmosphere a non-stationary model of turbulent exchange in the near-surface layer of the sea is proposed. The model takes into account quasi-periodicity in the intensity of dynamic interaction between the atmosphere and the sea at these scales. In the model we use the equations of momentum and turbulent energy balance, the system of equations is solved numerically, the calculation results are compared with other models and with experimental data. It is shown that taking into account the non-stationarity of the wind strain improves the correspondence between the calculations and the experimental data. It is noted that in the nonstationary case, the energy and momentum flux from the atmosphere and the turbulence intensity increases compared to the action of a constant average wind of the same duration. Therefore, the strong averaging often used in global models may markedly underestimate the intensity of the dynamic interaction between the atmosphere and ocean.

Computational-Aided Approach for the Optimization of Microfluidic-Based Nanoparticles Manufacturing Process.

In the last few years, the microfluidic production of nanoparticles (NPs) is becoming a promising alternative to conventional industrial approaches (e.g., nanoprecipitation, salting out, and emulsification-diffusion) thanks to the production efficiency, low variability, and high controllability of the production parameters. Nevertheless, the development of new formulations and the switching of the production process toward microfluidic platforms requires expensive and time-consuming number of experiments for the tuning of the formulation to obtain NPs with specific morphological and functional characteristics. In this work, we developed a computational fluid dynamic pipeline, validated through an ad hoc experimental strategy, to reproduce the mixing between the solvent and anti-solvent (i.e., acetonitrile and TRIS-HCl, respectively). Moreover, beyond the classical variables able to describe the mixing performances of the microfluidic chip, novel variables were described in order to assess the region of the NPs formation and the changing of the amplitude of the precipitation region according to different hydraulic conditions. The numerical approach proved to be able to capture a progressive reduction of the nanoprecipitation region due to an increment of the flow rate ratio; in parallel, through the experimental production, a progressive increment of the NPs size heterogeneity was observed with the same fluid dynamic conditions. Hence, the preliminary comparison between numerical and experimental evidence proved the effectiveness of the computational strategy to optimize the NPs manufacturing process.

Advancing credit risk modelling with Machine Learning: A comprehensive review of the state-of-the-art

Ensuring financial stability necessitates responsible credit granting, so lending institutions maintain sufficient regulatory capital to withstand losses from defaults. Classification methods like Logistic Regression (LR) have long been the standard for estimating default likelihood, but they struggle with increasing operational demands and regulatory standards. Advances in Machine Learning (ML) now allow models to handle larger datasets with greater predictive power. Algorithms such as Decision Trees (DT), Support Vector Machines (SVM), and Neural Networks (NN), though not readily transferable to practical applications, have the potential to enhance the credit risk modelling process. While much of the literature on ML in credit risk focuses on sophisticated, experimental algorithms not yet ready for commercial use, few address the steps and nuances of model development. Our article fills this gap by systematically reviewing the literature on ML in consumer credit risk modelling, highlighting the current state of scientific knowledge. We analyze the frequent steps involved and demonstrate how ML's strengths can be leveraged throughout them. From pre-processing steps like data cleaning, transformation, and reduction, to variable selection and parameter optimization, our findings indicate that ML is becoming increasingly important in financial risk management. However, standardized modelling procedures are needed before complex ML classifiers can be commercially deployed. Meanwhile, although relatively interpretable ML models built around DTs and Random Forests (RF) do showcase increased performance in popular credit risk datasets, it is clear that the potential to benefit from ML spans further, with complex models enabling increased performance by aiding simpler, explainable classification algorithms.

Using Precision Medicine to Disentangle Genotype-Phenotype Relationships in Twins with Rett Syndrome: A Case Report.

Rett syndrome (RTT) is a paediatric neurodevelopmental disorder spanning four developmental stages. This multi-system disorder offers a unique window to explore genotype-phenotype relationships in a disease model. However, genetic prognosticators of RTT have limited clinical value due to the disorder's heterogeneity on multiple levels. This case report used a precision medicine approach to better understand the clinical phenotype of RTT twins with an identical pathogenic MECP2 mutation and discordant neurodevelopmental profiles. Targeted genotyping, objective physiological monitoring of heart rate variability (HRV) parameters, and clinical severity were assessed in a RTT twin pair (5 years 7 months old) with an identical pathogenic MECP2 mutation. Longitudinal assessment of autonomic HRV parameters was conducted using the Empatica E4 wristband device, and clinical severity was assessed using the RTT-anchored Clinical Global Impression Scale (RTT-CGI) and the Multi-System Profile of Symptoms Scale (MPSS). Genotype data revealed impaired BDNF function for twin A when compared to twin B. Twin A also had poorer autonomic health than twin B, as indicated by lower autonomic metrics (autonomic inflexibility). Hospitalisation, RTT-CGI-S, and MPSS subscale scores were used as measures of clinical severity, and these were worse in twin A. Treatment using buspirone shifted twin A from an inflexible to a flexible autonomic profile. This was mirrored in the MPSS scores, which showed a reduction in autonomic and cardiac symptoms following buspirone treatment. Our findings showed that a combination of a co-occurring rs6265 BDNF polymorphism, and worse autonomic and clinical profiles led to a poorer prognosis for twin A compared to twin B. Buspirone was able to shift a rigid autonomic profile to a more flexible one for twin A and thereby prevent cardiac and autonomic symptoms from worsening. The clinical profile for twin A represents a departure from the disorder trajectory typically observed in RTT and underscores the importance of wider genotype profiling and longitudinal objective physiological monitoring alongside measures of clinical symptoms and severity when assessing genotype-phenotype relationships in RTT patients with identical pathogenic mutations. A precision medicine approach that assesses genetic and physiological risk factors can be extended to other neurodevelopmental disorders to monitor risk when genotype-phenotype relationships are not so obvious.

Glycemic Control and Cardiometabolic Risk in Black Zimbabweans with Type 2 Diabetes Mellitus.

Type 2 diabetes mellitus (T2DM) frequently presents with modified cardiometabolic risk profiles, indicative of an elevated susceptibility to cardiovascular disease (CVD). Cardiometabolic risk factors such as obesity, hyperglycemia, hypertension, insulin resistance and dyslipidemia are known contributors to increased CVD hazard in individuals with T2DM. This study evaluated the glycemic control-based cardiometabolic risk profiles of black Zimbabweans with T2DM. A cross-sectional study of 116 T2DM patients recruited from diabetic clinics at Parirenyatwa and Sally Mugabe Hospitals, Harare, Zimbabwe, was conducted. Blood samples were collected for glycated hemoglobin (HbA1c) and lipid profile assessment. The Framingham risk scores (FRS) based on body mass index (BMI) and lipid profile were used to determine CVD risk. Parametric variables were analyzed using one-way analysis of variance (ANOVA) with post hoc Bonferroni correction, while non-parametric variables were compared using the Kruskal-Wallis test with post hoc Dunn test for multiple comparisons. The overall frequency of dyslipidemia was 83.6% (n=97) and hypoalphalipoproteinemia was the most prevalent dyslipidemia (79.3%). Median HDLC levels were significantly lower in participants with poor glycemic control (1.12 mmol/L) compared to those with good glycemic control group (1.37 mmol/L) (p=0.011). Despite lack of significant variations in Framingham Risk Scores, there was a trend towards lower FRS-BMI in the good control group (29.8%) compared to the inadequate control (35.4%) and poor control (32.7%) groups (p=0.078). Duration since DM diagnosis was observed to be an important risk factor for poor glycemic control being significantly shorter in those with good glycemic control compared to those with inadequate and poor control. Overall, there was no significant difference in HbA1c status by age but individuals with poor glycemic control were significantly older than those with good control. The most prevalent dyslipidemia among the study participants was hypoalphalipoproteinemia which is reportedly associated with genetic predisposition, warranting further investigations.

Appropriate analysis on properties of various compositions on fluids with and without additives for liquid insulation in power system transformer applications

Transformer is a well-known power system apparatus utilized in conjunction with solid insulations such as paper and press board, as well as liquid insulations like mineral oil, a petroleum-based fluid. Despite the notable drawbacks associated with mineral oil, such as limited resources for future generations and its non-eco-friendly nature, its usage remains ubiquitous. There is a growing imperative to explore alternative fluids that surpass mineral oil in terms of environmental impact and performance. Amidst the global shift towards green energy, this study focuses on vegetable seed oils such as corn oil, soybean oil, mustard oil, and rice bran oil as potential substitutes. The research evaluates these oils based on key transformer properties including breakdown voltage, water content, interfacial tension, viscosity, acidity, flash point, and fire point. Interestingly, rice bran oil and soybean oil exhibit promising characteristics that suggest they could effectively replace petroleum-based fluids in transformers. Furthermore, the study extends to blending mineral oil with vegetable seed oils in various compositions, incorporating natural and synthetic antioxidant additives ranging from 0 to 1%. Comparative analyses between samples with and without additives reveal that the inclusion of 1% propyl gallate yields outstanding performance improvements. For instance, a blend comprising 25 ml of mineral oil and 25 ml of soybean oil, supplemented with 1% propyl gallate, demonstrates 90% higher effectiveness compared to other blends and additives tested. Moreover, the research employs statistical regression analysis to establish relationships between different parameter variables, providing deeper insights into the performance and compatibility of these blended oils in transformer applications. This comprehensive investigation underscores the potential of vegetable seed oils as viable alternatives to mineral oil, contributing to the advancement of eco-friendly solutions in power systems.

Understanding water dynamics in Dal Lake: a comprehensive analysis of physiological parameters and seasonal variations.

Maintaining the standard of water quality in an aquatic habitat necessitates continual assessment of its physicochemical properties. The purpose of this study was to evaluate physicochemical properties and to discuss the causes of spatiotemporal variability in key physicochemical parameters at five different locations of Dal Lake. Water samples were collected in four seasons for 3 years (i.e., January 2019-December 2021) to evaluate various physicochemical properties using standard methods. The analysis shows that the macrophytic development has increased due to organic and inorganic load, leading to the Lake's deterioration. The analysis indicates positive and negative correlations among various parameters across five sampling sites. Principal component analysis shows that two components (PC1 and PC2) explain 47.35, 47.54, and 48.11% of the variability in the years 2019, 2020, and 2021, respectively. From 2019 to 2021, the continuous decrease in dissolved oxygen and increased levels of magnesium, conductivity, alkalinity, total hardness, calcium hardness, total phosphorus, and nitrate-nitrogen suggest a trend toward eutrophication in the lake.

Random field of homogeneous and multi-material structures by the smoothed finite element method and Karhunen–Loève expansion

A random field of homogeneous and multi-material structures with uncertain scenarios is addressed by constructed the generalized stochastic cell-based smoothed finite element model. Smoothed finite element method (S-FEM) is “Jacobian-free”, which is not only overcomes the limitations of “overly-stiff” and low accuracy of the standard FEM, but also demonstrates strong resistance to mesh distortion. This paper proposes an efficient non-intrusive stochastic smoothed finite element method (SS-FEM) based on cell-based smoothing domains (SD) for the stochastic analysis of elastic problems, which describe much more realistically real physical systems under uncertain scenarios. This SS-FEM starts from the Gaussian random field based on representation related to the spatial variability in material parameters based on the Karhunen-Loève (KL) expansion, and then establishes the basic formulation that considers the effects of uncertainties. A generalized solving framework based on numerical integration is further developed. The non-intrusive dimension reduction method is also adopted to obtain the statistical moments and probability density function. The proposed SS-FEM can capture the structural stochastic responses under uncertainty condition by combining gradient smoothing technology and uncertainty quantification. A number of engineering examples are compared with the solution of Monte Carlo simulation to demonstrate both the accuracy and the efficiency of the proposed method.

Analysis of variable fluidic properties with varying magnetic influence on an unsteady radiated nanofluid flow on the stagnant point region of a spinning sphere: a numerical exploration

Abstract The purpose of this article is to invent the impact of inconstant properties of fluids on the nanofluidic stream towards the stagnation area of a revolving sphere. The motion is treated as an unsteady radiated flow with a nonlinear sort of heat radiation. It is presumed to have Brownian motion &amp; thermophoretic impact in our flow model. Additionally, a variable magnetic influence is addressed perpendicularly on the spherical surface. A suitable alteration has been applied to make dimensionless of our prime flow profiles. The translated equations and the limiting restrictions are solved through a numerical approach. The well established method RK4 Shooting technique is utilized here with Maple 2017 software. In the exploration of the consequences of requisite parameters on thermal, concentration, and flow features, numerous schematics are involved. The nature of physical quantities like Nusselt numbers, friction coefficients, and Sherwood numbers is stated in a tabular manner. It is perceived from the outcomes that the fluid velocity towards the x-direction is reduced for the variable viscosity parameter, whereas the unsteadiness parameter promotes it. The enhancement of inconstant thermal conductivity brings a positive influence on the thermal profile of fluid. Nusselt number drops against the thermal radiation &amp; variable viscosity with a rates 4.50% and 25.88% correspondingly.

Autonomic Imbalance and Elevated Inflammatory Cytokines in Long COVID: A Cross-Sectional Study.

Following an infection with SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), many individuals fully recover. On the other hand, a few have symptoms that last for weeks, months, or even years after their initial diagnosis. Symptoms of COVID-19 persisting for four weeks and more are termed long COVID. To assess the long-term cardiovascular morbidity by battery of cardiac autonomic function tests as well as the persistence of inflammation in COVID-recovered patients three months after initial infection. Methodology: 150 patients were selected who had recovered from COVID-19 at least three months prior to the study. After obtaining informed written consent, a throat swab was tested for COVID-19, and those with negative reverse transcription polymerase chain reaction (RT-PCR) results were subjected to autonomic function testing. Serum interleukin-6 and C-reactive protein levels were determined by enzyme-linked immunosorbent assay (ELISA) test. Out of 150 subjects 36 were found to have autonomic dysfunction graded according to Ewing's criteria. Individuals with autonomic dysfunction also had significantly increased inflammatory biomarker levels. There was also significant correlation between inflammatory markers and autonomic function test and heart rate variability parameters. Even years after the COVID-19 pandemic was declared, new symptom patterns and syndromes such as 'long COVID' are appearing.A better understanding of the pathophysiological mechanisms of post-COVID manifestations that affect the autonomic nervous system, as well as customized therapeutic care, should help reduce COVID-19 sequelae, particularly if we act early in the disease.

Probabilistic analysis of near-field blast loads considering fireball surface instabilities and stochastic detonator location

High speed video analysis of near-field explosive detonations displays distinct stages of emergent hydrodynamic instabilities in the fireball/shock-air interface. Typically, beyond 10 charge radii, the instabilities experienced large growths giving rise to more chaotic behaviour of the interface and thus an increasing uncertainty in surface velocity. These surface instabilities are suggested as the primary cause of blast parameter variability in the near-field. However, as a deterministic tool, numerical simulation of the detonation process and subsequent blast wave propagation is not able to replicate the stochastic nature of fireball surface instabilities and hence near-field blast parameter variability. Therefore, it is necessary to develop new methods to simulate and characterise the stochastic features of the fireball/shock-air interface. This paper proposes an algorithm to generate an explosive charge element with random shape in finite element model in order to simulate irregularities in the fireball/shock-air interface, and therefore produce variabilities comparable to those from direct observation. The effect of chaotic fireball/shock-air interface on near-field loading is explored through a large number of numerical simulations in order to investigate the statistical distribution of parameters including peak overpressure and impulse. Subsequently, the effect of stochastic detonator location is explored in a similar manner. A computational procedure based on the Monte Carlo Method is proposed to establish a probabilistic model of near-field blast loads, termed PSL-Blast. The reliability of design blast loads calculated using the UFC 3-340-02 design manual is then estimated using PSL-Blast, which suggests that reliability decreases with decreasing scaled distance. Finally, reliability-based safety factors of blast loads are calculated based on different blast settings.

Affective Implications of Human-Animal Relationship on Pig Welfare: Integrating Non-Linear Heart Rate Variability Measures.

The human-animal relationship is crucial for animal welfare. Gentle handling enhances pigs' comfort while rough handling causes fear and stress. This study examined how different human-animal relationship qualities affect the behavior and heart rate variability (linear and non-linear parameters) of 36 nursery pigs. Over six weeks, pigs experienced positive (n = 12), minimal (n = 12), or negative (n = 12) human handling. Their responses to handlers were then assessed in an experimental arena with four phases: habituation, exposure to the handler standing and sitting, and forced interaction. Pigs subjected to negative handling exhibited increased fear-related behaviors, spending less time in contact with the handler. They also exhibited heightened stress responses, with greater LF/HF ratio and Lmean values compared with positively handled pigs. Conversely, gently handled pigs displayed affiliative behaviors, accepting more strokes, and higher parasympathetic activation, indicated by greater RMSSD/SDNN and SampEn values, suggesting a more positive affective state. Minimally handled pigs exhibited some behavioral similarities to gently handled pigs, although physiological data indicated that the interaction was likely more rewarding for the gently handled pigs. These results emphasize the impact of human-animal relationships on pig welfare and highlight the value of incorporating non-linear heart rate variability parameters in such evaluations.

A low-mass sub-Neptune planet transiting the bright active star HD 73344

Context. Planets with radii of between 2 and 4 R⊕ closely orbiting solar-type stars are of significant importance for studying the transition from rocky to giant planets, and are prime targets for atmospheric characterization by missions such as JWST and ARIEL. Unfortunately, only a handful of examples with precise mass measurements are known to orbit bright stars. Aims. Our goal is to determine the mass of a transiting planet around the very bright F6 star HD 73344 (Vmag = 6.9). This star exhibits high activity and has a rotation period that is close to the orbital period of the planet (Pb = 15.6 days). Methods. The transiting planet, initially a K2 candidate, is confirmed through TESS observations (TOI 5140.01). We refined its parameters using TESS data and rule out a false positive with Spitzer observations. We analyzed high-precision radial velocity (RV) data from the SOPHIE and HIRES spectrographs. We conducted separate and joint analyses of K2, TESS, SOPHIE, and HIRES data using the PASTIS software. Given the star’s early type and high activity, we used a novel observing strategy, targeting the star at high cadence for two consecutive nights with SOPHIE to understand the short-term stellar variability. We modeled stellar noise with two Gaussian processes: one for rotationally modulated stellar processes, and one for short-term stellar variability. Results. High-cadence RV observations provide better constraints on stellar variability and precise orbital parameters for the transiting planet: a radius of Rb = 2.88−0.07+0.08 R⊕ and a mass of Mb = 2.98−1.90+2.50 M⊕ (upper-limit at 3σ is &lt;10.48 M⊕). The derived mean density suggests a sub-Neptune-type composition, but uncertainties in the planet’s mass prevent a detailed characterization. In addition, we find a periodic signal in the RV data that we attribute to the signature of a nontransiting exoplanet, without totally excluding the possibility of a nonplanetary origin. This planetary candidate would have a minimum mass of about Mc sin ic = 116.3 ± −13.0+12.8 M⊕ and a period of Pc = 66.45−0.25+0.10 days. Dynamical analyses confirm the stability of the two-planet system and provide constraints on the inclination of the candidate planet; these findings favor a near-coplanar system. Conclusions. While the transiting planet orbits the bright star at a short period, stellar activity prevented us from precise mass measurements despite intensive RV follow-up. Long-term RV tracking of this planet could improve this measurement, as well as our understanding of the activity of the host star. The latter will be essential if we are to characterize the atmosphere of planets around F-type stars using transmission spectroscopy.

Uncertainty in the embodied energy assessment of buildings: a case of EWS type low-cost house in India

Studies on embodied energy of buildings often present results as a single-point estimate without considering the variability in input parameters and the uncertainty it poses on results. Uncertainty analysis is useful to improve the reliability of results. This study examines uncertainty in the embodied energy of a single-storey EWS type residential building due to variability in the embodied energy intensity of materials and material wastage factors. Data quality indicator (DQI) based semi-qualitative method is used for modelling the variability in input parameters. Monte Carlo Simulation is used for uncertainty propagation. The building embodied energy is found to vary from 4 to 9 GJ/m2 based on variation in input data. The mean building embodied energy is found to be 6.3 GJ/m2. The embodied energy intensity of materials is found to cause more variation in building embodied energy in comparison with mass of materials. 'Brick’ is identified as the significant key parameter based on the relative contribution to uncertainty and embodied energy at the building level. Cement and rebar are identified as key parameters. The DQI based methodology presented in this study is useful for Life Cycle Assessment practitioners to evaluate uncertainty in the embodied energy assessment of residential buildings.

Сопоставление разноуровневых признаковых пространств романов Р. Брэдбери «Вино из одуванчиков» и «Лето, прощай»

The aim of the study is to determine the similarities and differences of the multilevel semantic spaces formed by the signs of English verbal nouns in the works of Ray Bradbury "Dandelion Wine" and "Farewell Summer". The author provides a definition of the term "feature space", identifies three parameters of variability (feature, level, cluster variability of levels) for a comparative analysis of the feature spaces of the studied works. The article examines the signs of five linguistic levels: phonetic, morphological, diachronic, etymological and semantic. The scientific novelty of the study lies in the fact that in this work the feature space is considered as a certain set of multi-level features related by statistically relevant relationships. In this context, it is first demonstrated in relation to works of art. The results revealed that the novel "Dandelion Wine" contains a higher number of English verbal nouns, with the multilevel characteristics of these nouns forming fewer clusters. On the other hand, the novel "Farewell Summer" contains twice as few English lexical units, but with more clusters. Thus, we can state that the "Farewell Summer" feature space is significantly more differentiated and, accordingly, there will be much more oppositions between the features.