Search Results (490)

We present a staircase-shaped transmissive metasurface for linear-to-circular (LTC) polarization conversion, achieving an axial ratio bandwidth (ARBW) of about 41% and covering the entire X band (8–12 GHz). Unlike designs based on discrete resonators, the proposed structure is based on meander-line conductive elements with electrical continuity across unit cells. This promotes distributed surface currents that contribute to a broader operational bandwidth. The metasurface operates in transmission mode and enables switching between right- and left-handed circular polarization (RHCP/LHCP) through a simple 90° mechanical rotation. In addition, the LTC response remains robust under oblique incidence, with the ARBW remaining above 33% for incidence angles up to 45${}^{\circ }$. Experimental results are in very good agreement with simulations and confirm stable handedness switching. Owing to its geometrical nature, the operating frequency can be easily scaled by adjusting the unit-cell dimensions. As a proof of concept, a Ku-band (12–18 GHz) design achieving comparable broadband performance is also demonstrated. These results highlight the potential of continuous, distributed-current-based metasurfaces for compact and broadband polarization control in microwave systems. Full article

Chloroidium saccharophilum is a resilient green microalga with a broad ecological distribution and an increasing biotechnological interest due to its tolerance of extreme environmental conditions. In this study, a sample of C. saccharophilum from the Laguna Blanca aquifer (Magallanes, southern Chile) was physiologically and phylogenetically characterized. This is the first confirmed evidence of this strain in the Southern Cone. Molecular identification based on ITS rDNA sequencing and ITS2 secondary structure analysis confirmed its taxonomic location, showing high similarity with reference strains and no compensatory base changes. Growth performance was analyzed under controlled laboratory conditions and under outdoor desert cultivation in the Atacama Desert, focusing on temperature, salinity, nutrients limitation, and high solar irradiance operational conditions. The strain exhibited optimal growth at 22 °C under laboratory conditions and demonstrated a strong tolerance to high salinity (150 g L⁻¹ NaCl). Outdoor raceways cultivation revealed a negative relationship between temperatures above 25 °C and biomass accumulation, while nutrients depletion and strong irradiance caused moderate carotenoid accumulation. However, the low amount of carotenoid yields remained constant, even under combined stress conditions. In general, the results highlight the ecological adaptability and the stress tolerance of C. saccharophilum, supporting its potential application in saline bioprocesses and bioremediation. Nevertheless, the limited production of carotenoid synthesis suggests that additional or combined stress strategies will be required to enhance the production of high-value metabolites. This study expands the biogeographical knowledge of C. saccharophilum and provides a physiological baseline for future optimization studies in extreme and Mars-analog environments. Full article

The design of near-surface crown pillars involves the interaction between excavation geometry, rock mass quality, and the in situ stress state. This study proposes a formulation that integrates numerical modeling and empirical criteria to construct a unified framework for stability interpretation. The Modeled Span index is introduced as a hybrid measure that incorporates geometric relationships and the pre-mining stress state, which, when compared with rock mass quality, allows the definition of a probabilistic stability boundary. The results show that the design tool enables the establishment of a consistent classification within the domain represented by the dataset. The Modeled Span chart complements traditional stability assessment approaches and is intended for application in conceptual and prefeasibility studies of crown pillars in Sublevel Open Stoping mining. Full article

Background/Objectives: University life is often accompanied by unhealthy lifestyle behaviors, reduced physical activity, lower fitness levels, and a high prevalence of mental health symptoms. Daily step count has emerged as a practical indicator of habitual physical activity; however, evidence on its association with cardiorespiratory fitness and symptoms of depression, anxiety, and stress in university students remains limited. Therefore, this study examined the association of daily step count with cardiorespiratory fitness and symptoms of depression, anxiety, and stress in university students. Methods: This cross-sectional association study included a convenience sample of 120 students aged 18 to 25 years from a single university. Daily step count was assessed over seven consecutive days using a Xiaomi Mi Band 9. Cardiorespiratory fitness was evaluated with the 20 m shuttle run test, and symptoms of depression, anxiety, and stress were measured using the Depression, Anxiety and Stress Scale-21 Items (DASS-21). Partial correlations, ANCOVA, MANCOVA, binary logistic regression, and restricted cubic spline models were performed after adjustment for sex, age, and socioeconomic status. Results: Higher daily step count was associated with greater cardiorespiratory fitness and with lower symptoms of depression, anxiety, and stress, although the associations with mental health symptoms were weak and not uniform across outcomes. Restricted cubic spline models showed inverse non-linear associations for mental health symptoms, with steeper inverse gradients at lower step-count levels and a tendency to level off at higher volumes, approximately around 9000 steps/day. For cardiorespiratory fitness, the association was positive across the step-count range. Step counts around 7500 steps/day were associated with lower odds of elevated symptoms of depression, anxiety, and stress. Conclusions: A higher daily step count was associated with more favorable mental health symptom profiles and greater cardiorespiratory fitness in this sample of university students. Full article

The actinobacterial strain DEC002 was isolated recently from volcanic soils of Deception Island. Its taxonomic identity was resolved through a polyphasic strategy integrating morphology, physiological profiling, multilocus phylogeny, and genome-wide comparisons to resolve its identity. Concatenated core gene trees together with average nucleotide identity and digital DNA–DNA hybridization values place DEC002 within Actinacidiphila fildesensis with robust support. This is the first molecular confirmation of the species beyond King George Island and secures a second verified locality within the South Shetland Archipelago. Growth at low temperature with tolerance to moderate salinity indicates a psychrotolerant lifestyle. Cell-free supernatants inhibited representatives of foodborne Gram-negative and Gram-positive bacteria, including representatives of Enterobacteriaceae, Vibrio, Staphylococcus and Streptococcus. Genome analysis revealed enrichment in multiple biosynthetic gene clusters for nonribosomal peptides, polyketides, terpenes, and ribosomally synthesized and post-translationally modified peptides (RiPPs), supporting the biosynthetic potential of the strain. Functional annotations emphasize replication and repair modules, mobile element-associated proteins, helix–turn–helix regulators, and versatile transport systems, features coherent with cold stress and oligotrophic soils. Antibiotic susceptibility assays indicate a broad resistance phenotype under the experimental conditions tested, together with extracellular antimicrobial activity. These data refine the biogeography of A. fildesensis and indicate DEC002 as a credible Antarctic source of specialized metabolites with antimicrobial promise. Full article

Chroococcidiopsis sp. was isolated from the endolithic habitat of the Atacama Desert (northern Chile), one of the most challenging-to-life polyextreme environments on Earth. The photosynthetic machinery of microorganisms inhabiting this environment is supposed to be highly adapted to cope with the intense solar radiation of the area. Thus, PAR-red light ranging from 100 to 900 µmol photon·m⁻²·s⁻¹ has been investigated as a strategy to enhance culture productivity and stimulate the synthesis of bioactive molecules in Chroococcidiopsis sp. A control culture was maintained under white light at 100 µmol photon·m⁻²·s⁻¹. The results revealed that red light was utilized more efficiently than white light of similar irradiance, and its modulation enhanced both growth and photosynthetic activity of the cyanobacterium. Furthermore, Chroococcidiopsis sp. appeared to activate mechanisms to mitigate photooxidative stress produced by excess light energy. Specifically, increasing light irradiance induced photoacclimation responses, characterized by a decrease in chlorophyll content and a concomitant increase in carotenoid accumulation, likely aimed at reducing photon flux transduced to photosynthesis. Additionally, scytonemin synthesis was enhanced under high irradiances, contributing to dissipating excess light energy. Overall, this study demonstrates that modulation of red-light irradiance effectively improves the growth of Chroococcidiopsis sp. while promoting the accumulation of antioxidant compounds—primarily carotenoids and, to a lesser extent, scytonemin. Full article

SAG grinding mills represent critical energy-intensive operations in copper concentrators, accounting for 30%–50% of total plant energy consumption. The accurate prediction of mill power draw and production rate under varying operational conditions is essential for real-time control, production planning, and energy management. This study presents a comprehensive comparison of ML algorithms for modeling Production and Power in a Chilean copper mining industry. Deterministic and stochastic models were fitted and validated using industrial data from a Chilean copper operation. More representative models were re-estimated and subsequently evaluated under different operating regimes to examine their predictive performance under aggregated conditions of the feeding variables. This procedure allowed for the identification of the modeling approaches that provide the most robust performance across varying operational regimes. The results show that XGB achieved the best predictive performance, with test RMSE and R² values of 87.98 and 97.35% for SAG Production, and 431.11 and 95.11% for SAG Power, respectively. Stochastic approaches provided complementary uncertainty quantification, supporting risk-informed decision making under variable operating conditions. The analysis by operational regime indicates that XGB presents better fit in the Thick hydraulic regime, for both responses’ variables, which could be explained why a dense pulp operation provides more predictable grinding dynamics. The comparative analysis reveals trade-offs between model complexity, interpretability, computational requirements, and predictive performance, offering practical guidance for selecting appropriate modeling frameworks based on specific operational objectives and data availability in mineral processing applications. Full article

Background/Objectives: This study aimed to examine the association between 24-h movement behavior composition and estimate cardiorespiratory fitness in school-aged children using compositional data analysis, and to model the theoretical differences in estimated cardiorespiratory fitness associated with isotemporal reallocations of time between movement behaviors. Methods: A cross-sectional study was conducted in 222 schoolchildren aged 8 to 12 years (mean age 9.94 ± 0.69 years), with most participants aged 10 years. Twenty-four-hour movement behaviors were assessed objectively using wrist-worn accelerometers, and cardiorespiratory fitness was estimated from the 20 m shuttle run test using the Léger equation. Daily time-use composition was analyzed using isometric log-ratio coordinates and adjusted linear regression models were fitted. Estimated differences in cardiorespiratory fitness associated with 30-min isotemporal reallocations between behaviors were then modeled. Results: The 24-h movement behavior composition was significantly associated with estimated cardiorespiratory fitness. In isotemporal models, reallocating 30 min from sedentary behavior to sleep was associated with the largest modeled difference in estimated cardiorespiratory fitness, whereas other reallocations showed smaller estimated differences depending on the behavior displaced. Age was positively associated with estimated cardiorespiratory fitness, while sex showed a limited association. Bivariate analyses revealed weak or inconsistent associations, supporting the value of the compositional approach for capturing the interdependent nature of daily time use. Conclusions: Twenty-four-hour movement behavior composition was associated with estimated cardiorespiratory fitness in school-aged children. These findings support the use of compositional approaches to examine sleep, sedentary behavior, and physical activity jointly. However, given the cross-sectional design and the modeled nature of the reallocations, the estimated differences should be interpreted cautiously and not as direct causal or physiological effects. Full article

Physical inactivity remains a major modifiable risk factor for non-communicable diseases and continues to exhibit marked socioeconomic and gender disparities in Latin America. Identifying robust and interpretable predictors of inactivity in nationally representative datasets is essential for informing public health strategies. This study compared a survey-weighted logistic regression model and an explainable machine learning approach (XGBoost) to predict physical inactivity among Chilean adults using data from the 2024 National Physical Activity and Sports Survey (ENAFyD; n = 5248). Models were evaluated on a stratified held-out test set (n = 1050) using weighted and unweighted area under the ROC curve (AUC), Brier scores, and calibration curves. Survey-weighted logistic regression achieved a weighted AUC of 0.801, while XGBoost achieved 0.797, demonstrating comparable discrimination. XGBoost showed marginally lower Brier scores, indicating slightly improved probabilistic calibration. Low socioeconomic status, female sex, lower monthly physical activity expenditure, limited facility access, and lower engagement with digital resources were consistently associated with higher inactivity risk. SHAP-style contribution analysis provided additional insight into feature-level influence within the machine learning framework. Overall, both approaches demonstrated similar predictive capacity, supporting the complementary use of classical regression and explainable machine learning for population-level physical inactivity research. Full article

Desertification is one of the main threats to high Andean ecosystems, particularly in arid and semi-arid regions subject to increasing climatic and anthropogenic pressures. This study evaluated the spatial-temporal dynamics of desertification in the province of Candarave (Tacna, Peru) by integrating the Remote Sensing-based Desertification Index (RSDI), constructed from a principal component analysis incorporating four biophysical indicators: vegetation greenness, surface moisture, soil grain size, and fraction of solar radiation reflected (albedo), derived from Landsat 5 and 8 satellite images processed in Google Earth Engine. Temporal trends were analyzed using the Mann–Kendall test, while system stability was evaluated using the coefficient of variation, allowing different degrees of stability and environmental degradation to be characterized during the period 2010–2025. The results show that moderate and severe desertification classes predominate in higher altitude areas, covering approximately 92% of the study area, and are characterized by insignificant to weakly significant negative trends associated with high to relatively high temporal volatility. In contrast, stable areas with no significant changes represent 5.3% of the territory, while restoration processes occupy a small proportion, close to 2.7%. The high variability observed in the high Andean sectors is mainly linked to the interaction between reduced water availability, climate variability, and extreme events, as well as anthropogenic pressures, particularly overgrazing and aquifer exploitation. This multitemporal analysis allows us to anticipate the evolution of desertification and highlights the need to strengthen conservation planning in order to reduce the degradation of strategic high Andean ecosystems in the Tacna region. Full article

Background/Objectives: Long-term chronic intermittent hypobaric hypoxia (CIHH) is a common occupational exposure among high-altitude workers, particularly miners in northern Chile. This condition consists of working several days above 2500 m followed by rest at sea level, maintaining this cycle for years, which generates physiological alterations. This study analyzed associations among anthropometric indices and biomedical conditions in miners chronically exposed to long-term CIHH. Methods: This study was a cross-sectional analysis of 120 healthy Chilean male miners working at altitudes above 4400 m under a 7-day work/7-day rest schedule. Eligibility required ≥5 years of CIHH exposure and absence of cardiopulmonary disease, hypertension, diabetes, or oxygen therapy use. The assessments at altitude included oxygen saturation (SpO₂), blood pressure, heart rate, hematological parameters, metabolic parameters, and waist-to-hip ratio (WHR); measurements were obtained 18 h after arrival at altitude. WHR, BMI, SpO₂, and biomedical variables were collected following standardized procedures. Descriptive statistics and group comparisons were performed with Student’s t-test or the Wilcoxon test, with statistical significance set at p < 0.05. Normality assumption was assessed using the Shapiro–Wilk test. The association between WHR and SpO₂ was estimated using linear regression, with WHR scaled so that one unit corresponds to a 0.1-unit increase. Adjusted models included BMI, age, and years working under CIHH. Effect sizes and 95% confidence intervals (CIs) were reported. All statistical analyses were performed in the R programming language. Results: Mean SpO₂ was 89.07 ± 0.50% and mean WHR was 0.94 ± 0.01. In unadjusted comparisons, workers with WHR > 0.94 had lower SpO₂ than those below the threshold (88.8 ± 0.54 vs. 90.41 ± 0.50; p = 0.031). In adjusted models, the WHR–SpO₂ association was small and imprecise (β per 0.1-unit WHR = −0.67 pp; 95% CI −2.08 to 0.74). Hemoglobin showed an independent association with SpO₂, while other metabolic variables did not materially contribute. Conclusions: SpO₂ showed a modest inverse association with WHR in long-term CIHH workers. Even small saturation decreases may matter at high altitude. Combined WHR–SpO₂ monitoring may aid occupational surveillance, though longitudinal studies are needed to establish meaningful risk thresholds. Full article

We introduce the one-parameter bounded p-exponential distribution on $(0, p+1)$, which includes the uniform model as a special case and converges pointwise to the exponential law as $p\to \infty$. Closed-form expressions are derived for the CDF and PDF, the survival function, an explicit increasing-failure-rate hazard function, the quantile function (enabling inversion-based simulation), moments, and entropy, along with a constructive scaled beta or Kumaraswamy representation. We also establish stochastic ordering with respect to p in stop-loss and increasing convex order, formalizing how dispersion varies with the parameter while preserving the mean scale. Inference is discussed under parameter-dependent support, a non-regular setting, and we develop and compare several estimation procedures, including a likelihood-based boundary MLE, a variance-matching method-of-moments estimator, and Bayesian estimation under a gamma prior implemented via numerical quadrature or MCMC. Monte Carlo simulation studies evaluate finite-sample performance and interval behavior, and two real-world applications in survival and reliability analysis illustrate competitive goodness-of-fit relative to standard benchmark models. Full article

We introduce the discrete asymmetric double Lindley distribution, a new two-parameter family on the integer line designed to model signed counts and net changes with flexible asymmetric tail behavior. This statistical model is obtained by merging two Lindley-type linear-geometric kernels on the negative and non-negative half-lines, with tail decay rates that are coupled through a simple two-parameter mechanism. This construction yields an analytically tractable probability mass function with an explicit normalizing constant, as well as closed-form expressions for the cumulative distribution function and one-sided tail probabilities. We further provide a transparent stochastic representation based solely on Bernoulli and geometric random variables, leading to an exact and efficient simulation algorithm that is convenient for Monte Carlo studies and validating numerical likelihood routines. Graphical illustrations highlight the role of the asymmetry parameter in controlling the imbalance between the two tails and the resulting skewness on $\mathbb{Z}$. The proposed family offers a practical and interpretable alternative to existing integer-line models for asymmetric discrete data, with direct applicability to likelihood-based inference and real-world datasets. Full article

Arsenic (As) and mercury (Hg) are trace elements of major environmental and public health concern. Their relevance is due to their well-documented toxicological effects. In rapidly urbanizing port-industrial cities, soil contamination by these elements represents a critical challenge. This situation compromises sustainable urban development and environmental governance. This study had three main objectives: First, to evaluate the contamination status of As and Hg in urban soils using multiple geochemical indices; Second, to assess the potential human health risks associated with exposure in the urban environment of Talcahuano; Third, to identify the relative contributions of geogenic and anthropogenic sources based on spatial distribution patterns. A total of 420 soil samples were collected. These included 140 topsoil samples (TS; 0–10 cm), 140 subsoil samples (SS; 10–20 cm), and 140 deep-soil samples (DS; 150 cm). Arsenic concentrations were determined using hydride-generation atomic absorption spectrometry (HG-AAS). Mercury concentrations were measured by cold-vapour atomic absorption spectrometry (CV-AAS). Median As concentrations were 2.7 mg kg⁻¹ in TS, 3.1 mg kg⁻¹ in SS, and 2.5 mg kg⁻¹ in DS. The corresponding median Hg concentrations were 0.2 mg kg⁻¹ in TS and 1.4 mg kg⁻¹ in both SS and DS. Spatial distribution maps were generated through ordinary kriging interpolation. Geochemical baseline values were calculated using the median + 2 × MAD approach. The resulting baseline values were 7.8 mg kg⁻¹ for As and 3.6 mg kg⁻¹ for Hg. Contamination assessment was conducted using the geoaccumulation index (Igeo), enrichment factor (EF), and contamination factor (Cf). Results indicate that most soils are classified as uncontaminated. Enrichment levels were minimal and contamination factors were low. Nevertheless, isolated outliers were identified. These included one significantly enriched As sample and several moderately enriched or slightly contaminated Hg samples. Human health risk assessment incorporated the Hazard Index (HI) and Total Carcinogenic Risk (TCR). Results indicate that neither non-carcinogenic nor carcinogenic risks exceed acceptable thresholds at any investigated soil depth. Spatial analysis suggests that anthropogenic activities are the dominant sources of As and Hg in the study area. Traffic emissions and industrial activities appear to be the primary contributors. Full article

The study of microorganisms inhabiting extreme environments offers a valuable opportunity to explore their potential ecological roles. This study aimed to reveal and compare the microbial taxonomic diversity of largely unexplored permafrost regions located in different climatic zones (dry and wet) in the Chilean Andes, separated by thousands of kilometers. Permafrost active layer samples were collected from the Ojos del Salado (Atacama Desert) and the Torres del Paine (Patagonia) from different sampling depths. Illumina 16S rRNA gene-based amplicon sequencing revealed that the Andean permafrost active layer provides diverse habitats for distinct microbial communities, with higher taxonomic diversity of Bacteria than Archaea. The wet Patagonian Andes samples showed higher diversity, with a greater abundance of Chloroflexota and Bacteroidota, while the dry Ojos del Salado samples were dominated by Actinomycetota, indicating desiccation stress. Archaea were classified as ammonia-oxidizing members of the Thermoproteota phylum. Beta-diversity analyses suggested that differences in environmental conditions (mainly available moisture) contributed more to community structure differentiation than geographical distances. Nevertheless, the effect of sampling depth on microbial diversity was insignificant. Full article