Search Results (510)

Background/Objectives: Malnutrition in older adults is both preventable and treatable, yet its detection and etiology remain complex. Therefore, the aim of this study was to evaluate the prevalence of malnutrition and various factors involved in the etiology of malnutrition in community-dwelling individuals aged 65 years and older. Methods: This cross-sectional study was conducted with community-dwelling individuals aged 65 years and older in a health center in Ağrı, Türkiye. The nutritional status of older adults was measured using the Mini Nutritional Assessment (MNA). Data were collected through face-to-face interviews and a series of validated instruments, including the Standardized Mini Mental Examination (MMSE), body composition measurements (BIA), dietary intake records, and physical performance tests such as hand grip strength, chair stand, and Timed ‘Up & Go’ (TUG) Test. Statistical analyses included chi-square and Mann-Whitney U tests for group comparisons and logistic regression to investigate independent factors associated with risk of malnutrition. Results: A total of 182 participants were included in the study. The mean age of the participants was 72.1 ± 6.0 years. Of the participants, 59.3% were male. 1.6% of the participants were malnourished, and 25.3% were at risk of malnutrition. Perceived health status compared to peers (OR: 1.734, 95% CI: 1.256–2.392, p = 0.001), lower appetite status (OR: 1.942, 95% CI: 1.459–2.585, p < 0.001) and lower waist circumference (OR: 1.089, 95% CI: 1.040–1.140, p < 0.001) were independent predictors of malnutrition risk. Conclusions: The risk of malnutrition was higher among individuals with lower appetite, poorer self-perceived health status compared to peers, and smaller waist circumference. Reduced physical function and strength were also associated with an increased risk of malnutrition. Full article

Background/Objectives: Pain assessment scales provide a clear clinical benefit in patients who are unable to self-report. The Nociception Coma Scale-Revised—adapted for Intubated patients (NCS-R-I) was developed to assess pain in patients with acquired brain injury who are unable to self-report. However, this instrument has not yet been translated and validated for use in Spain. The objective was to translate the Nociception Coma Scale-Revised—adapted for Intubated patients (NCS-R-I) into Spanish and to assess the reliability and validity of the Spanish version in patients with brain injury. Methods: This study was carried out in two phases. First, the scale was translated into Spanish. Next, a psychometric analysis was performed to determine the reliability and validity of the Spanish version of the NCS-R-I in 207 critically ill patients with acquired brain injury and disorders of consciousness. Two blinded observers administered the scale at three time points: 5 min before, during, and 15 min after a series of nociceptive and non-nociceptive procedures. Results: The internal consistency of the NCS-R-I was acceptable (ordinal alpha = 0.60–0.90). Interobserver agreement was good (kappa = 0.80; intraclass correlation coefficient = 0.90). In terms of discriminant validity, the AUC was 0.952 (95% CI: 0.931–0.973). NCS-R-I scores increased significantly during performance of nociceptive procedures compared to scores obtained before and after these procedures, confirming the scale’s sensitivity to change. Similarly, during the performance of nociceptive procedures, scores on the NCS-R-I were significantly higher (p < 0.001) than those observed during non-nociceptive procedures. Conclusions: The results of this study demonstrate that the NCS-R-I is a valid, reliable tool for the assessment of pain in patients with acquired brain injury who are unable to self-report. Full article

The real-time acquisition of an accurate underwater sound velocity profile (SSP) is crucial for tracking the propagation trajectory of underwater acoustic signals, making it play a key role in ocean communication positioning. SSPs can be directly measured by instruments or inverted leveraging sound field data. Although measurement techniques provide a good accuracy, they are constrained by limited spatial coverage and require a substantial time investment. The inversion method based on the real-time measurement of acoustic field data improves operational efficiency but loses the accuracy of SSP estimation and suffers from limited spatial applicability due to its stringent requirements for ocean observation infrastructures. To achieve accurate long-term ocean SSP estimation independent of real-time underwater data measurements, we propose a semi-transformer neural network (STNet) specifically designed for simulating sound velocity distribution patterns from the perspective of time series prediction. The proposed network architecture incorporates an optimized self-attention mechanism to effectively capture long-range temporal dependencies within historical sound velocity time-series data, facilitating an accurate estimation of current SSPs or prediction of future SSPs. Through the architectural optimization of the transformer framework and integration of a time encoding mechanism, STNet could effectively improve computational efficiency. For long-term forecasting (using the Pacific Ocean as a case study), STNet achieved an annual average RMSE of 0.5811 m/s, outperforming the best baseline model, H-LSTM, by 26%. In short-term forecasting for the South China Sea, STNet further reduced the RMSE to 0.1385 m/s, demonstrating a 51% improvement over H-LSTM. Comparative experimental results revealed that STNet outperformed state-of-the-art models in predictive accuracy and maintained good computational efficiency, demonstrating its potential for enabling accurate long-term full-depth ocean SSP forecasting. Full article

We investigate the affine term structure models (ATSMs) with unspanned stochastic volatility (USV). Our aim is to test their ability to generate accurate cross-sectional behavior and time-series dynamics of bond yields. Comparing the restricted models and those with USV, we test whether they produce both reasonable estimates for the short rate variance and cross-sectional fit. Essentially, a joint approach from both time series and options data for estimating risk-neutral dynamics in ATSMs should be followed. Due to the scarcity of derivative data in emerging markets, we estimate the model using only time-series of bond yields. A Bayesian estimation approach combining Markov Chain Monte Carlo (MCMC) and the Kalman filter is employed to recover the model parameters and filter out latent state variables. We further incorporate macro-economic indicators and GARCH-based volatility as external validation of the filtered latent volatility process. The $A_1\left(4\right)$USV performs better both in and out of sample, even though the issue of a tension between time series and cross-section remains unresolved. Our findings suggest that even without derivative instruments, it is possible to identify and interpret risk-neutral dynamics and volatility risk using observable time-series data. Full article

Over recent years, ultrasonic atomization, especially with regard to liquid metals, has become an object of increased interest, mainly from industry, for additive manufacturing, but also from investigators, for research purposes. A strong correlation between the average particle size, distribution of particle sizes, and other process parameters like frequency and vibration amplitude was noted based on the analysis of available theoretical studies, simulations and experiments. The influence of parameters of the atomized fluid-like viscosity and surface tension on process parameters was also mentioned. The objective of this study is further research on the feasibility of using ultrasonic atomization to examine the properties of liquids, especially metals in liquid state. It attempts to close a gap in existing knowledge in searching for a new, possibly simple and cost-effective method to study the properties of liquid metals and further clarify the relationship between ultrasonic atomization parameters (amplitude, frequency, characteristics of metal being spilled on a vibrating surface) and obtained atomization results meant by average particle size and atomization time. Using numerical modeling (finite element method and computational fluid dynamics) as a methodology, combined with tests of using ultrasonic atomization as an instrument to determine properties of liquid metals, was considered as an introduction to a series of experiments. These tests were followed by real experiments that are also presented. At the first stage, numerical modeling was applied to a case of a specific liquid being spilled over a vibrating surface of different angles of inclination and specified, constant frequency and amplitude. The results of the simulation are in line with the current state of knowledge about ultrasonic atomization. Moreover, they can provide some more information on scalability, thus easing the comparison of the results of other experiments presented in the available literature. As a result, the relationship between fluid properties and the average size of atomized particles was demonstrated independently of the surface inclination angle. In the same way, the dependence of successful atomization on a sufficiently thin layer of a liquid was demonstrated. Thirdly, a correlation between the aforementioned layer thickness and the value of vibration amplitude has also been shown. Taking all the above into consideration, ultrasonic atomization can also be considered a research method and can be applied to study the properties of liquid metals. Further research, simulations and experimentation will be conducted to verify, develop and describe this method in full. Full article

The Flexible Combined Imager (FCI) instrument aboard the Meteosat Third Generation (MTG-I) geostationary satellite, launched in December 2022 and operational since September 2024, by providing shortwave infrared (SWIR), medium infrared (MIR) and thermal infrared (TIR) data, with an image refreshing time of 10 min and a spatial resolution ranging between 500 m in the high-resolution (HR) and 1–2 km in the normal-resolution (NR) mode, may represent a very promising instrument for monitoring thermal volcanic activity from space, also in operational contexts. In this work, we assess this potential by investigating the recent Mount Etna (Italy, Sicily) eruption of February–March 2025 through the analysis of daytime and night-time SWIR observations in the NR mode. The time series of a normalized hotspot index retrieved over Mt. Etna indicates that the effusive eruption started on 8 February at 13:40 UTC (14:40 LT), i.e., before information from independent sources. This observation is corroborated by the analysis of the MIR signal performed using an adapted Robust Satellite Technique (RST) approach, also revealing the occurrence of less intense thermal activity over the Mt. Etna area a few hours before (10.50 UTC) the possible start of lava effusion. By analyzing changes in total SWIR radiance (TSR), calculated starting from hot pixels detected using the preliminary NHI algorithm configuration tailored to FCI data, we inferred information about variations in thermal volcanic activity. The results show that the Mt. Etna eruption was particularly intense during 17–19 February, when the radiative power was estimated to be around 1–3 GW from other sensors. These outcomes, which are consistent with Multispectral Instrument (MSI) and Operational Land Imager (OLI) observations at a higher spatial resolution, providing accurate information about areas inundated by the lava, demonstrate that the FCI may provide a relevant contribution to the near-real-time monitoring of Mt. Etna activity. The usage of FCI data, in the HR mode, may further improve the timely identification of high-temperature features in the framework of early warning contexts, devoted to mitigating the social, environmental and economic impacts of effusive eruptions, especially over less monitored volcanic areas. Full article

Reliable coastal and offshore sediment transport data is a requirement for many engineering and environmental projects including port and harbour design, dredging and beach nourishment, sea shoreline protection, inland navigation, marine pollution monitoring, benthic habitat mapping, and offshore renewable energy (ORE). Novel sediment transport numerical modelling approaches allow engineers and scientists to investigate the physical interactions involved in these projects both in the near and far field. However, a lack of confidence in simulated sediment transport results is evident in many coastal and offshore studies, mainly due to limited access to validation datasets. This study addresses the need for cost-effective sediment validation datasets by investigating the applicability of four new suspended load validation techniques to a 2D model of the south-western Irish Sea. This involves integrating an estimated spatial time series of suspended solids concentration (${SSC}_{solids}$) derived from acoustic Doppler current profiler (ADCP) acoustic backscatter with several in situ water sample-based ${SSC}_{solids}$ datasets. Ultimately, a robust spatial time series of ADCP-based ${SSC}_{solids}$ was successfully calculated in this offshore, tidally dominated setting, where the correlation coefficient between estimated ${SSC}_{solids}$ and directly measured ${SSC}_{solids}$ is 0.87. Three out of the four assessed validation techniques are deemed advantageous in developing an accurate 2D suspended sediment transport model given the assumptions of the depth-integrated approach. These recommended techniques include (i) the validation of 2D modelled suspended sediment concentration (${SSC}_{sediment}$) using water sample-based ${SSC}_{solids}$, (ii) the validation of the flood–ebb characteristics of 2D modelled suspended load transport and ${SSC}_{sediment}$ using ADCP-based datasets, and (iii) the validation of the 2D modelled peak ${SSC}_{sediment}$ over a spring–neap cycle using the ADCP-based ${SSC}_{solids}$. Overall, the multi-disciplinary method of collecting in situ metocean and sediment dynamic data via acoustic instruments (ADCPs) is a cost-effective in situ data collection method for future ORE developments and other engineering and scientific projects. Full article

The provision of food in pre-Inca/Inca cultures (1000 BC–≈1532 AD) in environments near Lake Titikaka (approximately 4000 m above sea level) was possible through an agricultural technique called “Waru-Waru”, which consists of filling the space (volume) between rows of land containing plants that are cultivated (a series of earth platforms surrounded by water canals) with water, using water as thermal energy storage to store energy during the day and to regulate the temperature of the soil and crop atmosphere at night. The problem is that these cultures left no evidence in written documents that have been preserved to this day indicating the mathematical models, the physics involved, and the experimental part they performed for the research, development, and innovation of the “Waru-Waru” technique. From a review of the existing literature, there is (1) bibliography that is devoted to descriptive research (about the geometry, dimensions, and shapes of the crop fields (and more based on archaeological remains that have survived to the present day) and (2) studies presenting complex mathematical models with many physical parameters measured only with recently developed instrumentation. The research objectives of this paper are as follows: (1) develop a mathematical model that uses finite differences in fluid mechanics, thermodynamics, and heat transfer to explain the experimental and theory principles of this pre-Inca/Inca technique; (2) the proposed mathematical model must be in accordance with the mathematical calculation tools available in pre-Inca/Inca cultures (yupana and quipu), which are mainly based on arithmetic operations such as addition, subtraction, and multiplication; (3) develop a mathematical model in a sequence of steps aimed at determining the best geometric form for thermal energy storage and plant cultivation and that has a simple design (easy to transmit between farmers); (4) consider the assumptions necessary for the development of the mathematical model from the point of view of research on the geometry of earth platforms and water channels and their implantation in each cultivation area; (5) transmit knowledge of the construction and maintenance of “Waru-Waru” agricultural technology to farmers who have cultivated these fields since pre-Hispanic times. The main conclusion is that, in the mathematical model developed, algebraic mathematical expressions based on addition and multiplication are obtained to predict and explain the evolution of soil and water temperatures in a specific crop field using crop field characterization parameters for which their values are experimentally determined in the crop area where a “Waru-Waru” is to be built. Therefore, the storage of thermal energy in water allows crops to survive nights with low temperatures, and indirectly, it allows the interpretation that the Inca culture possessed knowledge of mathematics (addition, subtraction, multiplication, finite differences, approximation methods, and the like), physics (fluids, thermodynamics, and heat transfer), and experimentation, with priority given to agricultural techniques (and in general, as observed in all archaeological evidence) that are in-depth, exact, practical, lasting, and easy to transmit. Understanding this sustainable energy storage technique can be useful in the current circumstances of global warming and climate change within the same growing areas and/or in similar climatic and environmental scenarios. This technique can help in reducing the use of fossil or traditional fuels and infrastructure (greenhouses) that generate heat, expanding the agricultural frontier. Full article

This observational pilot study investigated neurocardiovascular responses to an active stand test using continuous physiological monitoring and functional data analysis (FDA) in older women. A sample of 25 community-dwelling female adults aged 59–78 years (mean age: 70.3 years) participated. Participants were dichotomized into comparison groups based on five factors: age (<70 vs. ≥70 years); the presence of initial orthostatic hypotension (IOH, yes/no); body mass index (BMI < 25 vs. ≥25 kg/m²); antihypertensive medication use (yes/no); and physical frailty status assessed by the Survey of Health, Ageing and Retirement in Europe—Frailty Instrument (SHARE-FI score < −0.5 vs. ≥−0.5). Each participant completed an active stand test during which six physiological signals were continuously recorded: systolic (sBP) and diastolic (dBP) blood pressure and heart rate (HR) via digital artery photoplethysmography and left frontal oxygenated hemoglobin (O₂Hb), deoxygenated hemoglobin (HHb), and tissue saturation index (TSI) via near-infrared spectroscopy (NIRS). The signal analysis focused on a standardized 200 s window spanning 50 s before to 150 s after the stand, with all signals resampled and synchronized at 5 Hz. FDA was used to statistically compare the full time series between groups for each signal. Group-level differences revealed that younger participants (<70 years) exhibited significantly higher HR in multiple periods following the stand (~10 s, ~30 s, ~90 s, and ~140 s post-stand) compared to their older counterparts. Participants with IOH demonstrated significantly lower sBP at ~10 s, ~80 s, and ~130 s post-stand and lower dBP at ~10 s post-stand. Among participants classified as overweight/obese (BMI ≥ 25 kg/m²), significantly lower levels of HHb were observed at ~10 s, ~30–50 s, and ~60 s post-stand, while O₂Hb levels were reduced at ~50 s, ~60 s, ~70–110 s, ~130 s, and ~140 s post-stand. No statistically significant group-level differences were observed based on antihypertensive medication use or frailty status. These findings demonstrate the utility of FDA in detecting subtle, time-dependent physiological variations during orthostatic challenge and underscore the value of continuous neurocardiovascular monitoring in assessing orthostatic tolerance in aging populations. Full article

This case series investigates whether traditional machine learning (ML) and convolutional neural network (CNN) models trained on wrist-worn accelerometry data collected in a laboratory setting can accurately predict real-world functional hand use in individuals with chronic stroke. Participants (N = 4) with neuroimaging-confirmed chronic stroke completed matched activity scripts—comprising instrumental and basic activities of daily living—in-lab and at-home. Participants wore ActiGraph CenterPoint Insight watches on the impaired and unimpaired wrists; concurrent video recordings were collected in both environments. Frame-by-frame annotations of the video, guided by the FAABOS scale (functional, non-functional, unknown), served as the ground truth. The results revealed a consistent capacity–performance gap: participants used their impaired hand more in-lab than at-home, with the largest discrepancies in patients with moderate to severe impairment. Random forest ML models trained on in-lab accelerometry accurately classified at-home hand use, with the highest performance in mildly and severely impaired limbs (accuracy = 0.80–0.90) and relatively lower performance (accuracy = 0.62) in moderately impaired limbs. CNN models showed comparable accuracy to random forest classifiers. These pilot findings demonstrate the feasibility of using lab-trained ML models to monitor real-world hand use and identify emerging patterns of learned non-use—enabling timely, targeted interventions to promote recovery in outpatient stroke rehabilitation. Full article

To ensure the long-term consistency of sunspot group data, it is essential to harmonize measurements from SOHO/MDI and SDO/HMI, two major solar observatories with overlapping coverage. In our analysis, we use two complementary sets of data: SOHO/MDI–Debrecen Sunspot Data (SDD) and SDO/HMI–Debrecen Sunspot Data (HMIDD). Our objective is to identify systematic differences between their recorded parameters and to assess whether their data can be combined into a coherent time series. While the overlap between the datasets spans only about one year, this period allows for a direct statistical comparison without the need for additional image processing. Though the two instruments do not measure identical area values, our results reveal a strong linear relationship between them, which is in line with earlier studies. On the other hand, a systematic discrepancy in their magnetic field strength measurements was observed. Contrary to previous findings, SDO/HMI magnetic field values tend to be higher than those from SOHO/MDI. These differences may arise from the use of different calibration procedures and measurement techniques, or from the physical characteristics of the sunspot groups themselves. These results highlight the challenges involved in unifying data from multiple solar instruments that have been captured over extended time periods. While broad consistencies are observable, the differences between sunspot groups and measurement parameters demonstrate the importance of using careful, instrument-aware calibration approaches when combining such datasets. Full article

During a research expedition to the Kanchenjunga Conservation Area (KCA), eastern Nepal, in April–June 2024, local concern was expressed about the rapid development of meltwater ponds upon the terminus of the Kanchenjunga glacier since 2020, especially in terms of the possible formation of a large and potentially dangerous glacial lake. Our resultant study of the issue included informal interviews with local informants, comparison of time series satellite composite images acquired by Sentinel-2 Multispectral Instrument, and modeling of different lake development, outburst flood scenarios, and prospective downstream impacts. Assuming that the future glacial lake will be formed by the merging of present-day supraglacial ponds, filling the low-gradient area beneath the present-day glacier terminal complex, we estimated the potential volume of a Kanchenjunga proglacial lake to be 33 × 10⁶ m³. Potential mass movement-triggered outburst floods would travel downstream distances of almost 120 km even under the small magnitude scenario, and under the worst-case scenario would reach the Indo-Gangetic Plain and cross the border into India, exposing up to 90 buildings and 44 bridges. In response, we suggest that the lower Kanchenjunga glacier region be regularly monitored by both local communities and Kathmandu-based research entities over the next decade. The development of user-friendly early warning systems, hazard mapping and zoning programs, cryospheric hazards awareness building programs, and construction of locally appropriate flood mitigation measures are recommended. Finally, the continued development and refinement of the models presented here could provide governments and remote communities with a set of inexpensive and reliable tools capable of providing the basic information needed for communities to make informed decisions regarding hazard mitigation, adaptive, and/or preventive measures related to changing glaciers. Full article

Congenital syphilis (CS) is an important infectious cause of miscarriage, stillbirth, and neonatal morbidity and mortality. Despite the advances in diagnosis and treatment, CS continues to challenge health systems with increasing incidence and mortality rates in recent years worldwide. Given this, the present study aims to comparatively analyze the temporal trends in CS incidence and mortality in Brazil’s Southeast Region from 2008 to 2022. This is an ecological time-series study using secondary data on congenital syphilis from the states of Espírito Santo, Minas Gerais, Rio de Janeiro, and São Paulo. The data was extracted from the Brazilian Health System Informatics Department. Incidence and mortality rates were calculated per 100,000 live births. Joinpoint regression models were employed to identify trends in annual percentage change and average annual percentage change with 95% confidence intervals. The temporal trend of CS incidence in Brazil’s Southeast Region increased 12.8% between 2008 and 2022. Minas Gerais, São Paulo, Espírito Santo, and Rio de Janeiro showed increasing temporal trends of 21.4%, 14.1%, 14.0%, and 10.9%, respectively. The temporal trend of CS mortality in Brazil’s Southeast Region rose 11.9% between 2008 and 2022. Minas Gerais, São Paulo, and Rio de Janeiro exhibited increasing mortality temporal trends of 21.9%, 20.8%, and 10.1%, respectively. In contrast, Espírito Santo showed reduced mortality, with no deaths in 2021 and 2022. The temporal trend of CS incidence increased in all states of Brazil’s Southeast Region between 2008 and 2022, highlighting the need to reassess control measures. The temporal trend of CS mortality also increased during the same period, except in Espírito Santo. Considering that CS is preventable with adequate prenatal care and low-cost measures, these findings can serve as instruments to support strengthening public health policies. Full article

Superior electricity-optimized business ecosystems (EOBEs) have evolved into pivotal determinants in catalyzing industrial–commercial prosperity. The access to electricity index (AEI) constitutes a valid instrument for assessing the EOBE. To realize the accurate evaluation of EOBE and the root cause tracing of its changes, this paper constructs a new analytical model for evaluating and monitoring changes in EOBE. First, this paper constructs a new evaluation model of EOBE based on the Business Ready (B-READY) evaluation system, considering three factors: the power regulatory quality, the public service level, and the enterprises’ gain power efficiency. Then, the model uses the raw data collected to calculate a score for AEI to enable an accurate assessment of EOBE. Next, this paper uses a priori assessment to extract the coupling features of indicators and combines the time series features and policy features to construct the feature matrix. Finally, the characteristic contribution was analyzed using support vector regression (SVR) and Shapley’s additive interpretation (SHAP) value. The experiment shows that the factors affecting the change in AEI are time series features, policy features, and coupling features in decreasing order of importance. This study provides reference cases and improvement ideas for the assessment and optimization of EOBE. Full article

Background and Objectives: Reverse shoulder arthroplasty (RSA) is an effective surgical procedure for treating end-stage rotator cuff arthropathy, but it is burdened by a relatively high complication rate, mainly due to glenoid component failure. Preoperative planning and intraoperative navigation based on three-dimensional computed tomography (3D CT) scans have proven to be efficient tools for improving the accuracy and stability of the glenoid component. However, this technology is still developing, and there is currently little available research on the subject, especially where clinical outcomes are concerned. The purpose of this retrospective observational study is to report the radiographic and clinical outcomes of a consecutive series of patients that underwent RSA with the use of these new technologies, compared to a standard procedure. Materials and Methods: A consecutive series of 80 patients underwent RSA for shoulder osteoarthritis by a single surgeon at a single institution with a mean follow-up of 41.9 ± 23.6 months (range 24–108) and were divided into two groups according to the surgical technique employed (conventional or navigated surgery), and they were clinically and radiographically assessed at 1, 3, 6, and 12 months after surgery, and then annually. Results: No statistically significant differences were highlighted among the two groups according to complication rate, radiographical glenoid notching, and clinical outcomes. However, a statistically significant difference was observed in screw number and length and surgical time. In the navigated group, fewer screws with longer lengths had been implanted, with a longer surgical time. Conclusions: The use of 3D CT-based preoperative planning and intraoperative navigation is a safe procedure and produces comparable results with respect to standard instrumentation, without an increased risk of complications. It allowed to achieve higher stability of the implant, saving bone stock due to the use of fewer and longer screws than in a conventional procedure. This could also eventually result in a higher longevity of the implant itself. Full article