Watching the international COVID-19 epidemics unfold during February and early March 2020, we began to highlight how outbreaks in care homes were inevitable, given the vulnerable patients in close proximity, and pressures on social care to help relieve pressure on the NHS. We suggested public health measures would significantly impact on care homes. Specifically we felt all homes would have multiple individuals isolated within days of introduction of guidance requiring isolation of new cough (or fever), and that a clear definition of an outbreak would be needed that differentiated COVID19 from influenza. We share the experiences of a GP practice looking after 900 nursing or dual registration care homes in the London Borough of Ealing in the early stages of the COVID19 Pandemic 2020. We believe that the altered presentation of cases of COVID19 in care homes contributed to the size of outbreaks, and that keeping COVID19 out of homes is the only way to manage this disease, with early isolation and complete segregation of positive and negative cases. We have seen over 300 suspected cases resulting in four fold (n=175) average monthly death rates, three fold usual issue of anticipatory medications, and approximately 32% mortality rate (up to 43% in over 90’s). Discharge pathways from hospital and admissions to care homes must be clear and robust. COVID19 naïve patients should not be admitted to units with outbreaks and COVID19 positive patients should not be admitted to anything other than a designated “hot” home until risk of contagion is passed. Some patients are testing positive at over 30 days since initial mild symptoms.

Background: the primary care service in Catalonia has operated an asynchronous teleconsulting service between GPs and patients since 2015 (eConsulta), which has generated some 500,000 messages. New developments in big data analysis tools, particularly those involving natural language, can be used to accurately and systematically evaluate the impact of the service. Objective: the study was intended to examine the predictive potential of eConsulta messages through different combinations of vector representation of text and machine learning algorithms and to evaluate their performance. Methodology: 20 machine learning algorithms (based on 5 types of algorithms and 4 text representation techniques)were trained using a sample of 3,559 messages (169,102 words) corresponding to 2,268 teleconsultations (1.57 messages per teleconsultation) in order to predict the three variables of interest (avoiding the need for a face-to-face visit, increased demand and type of use of the teleconsultation). The performance of the various combinations was measured in terms of precision, sensitivity, F-value and the ROC curve. Results: the best-trained algorithms are generally effective, proving themselves to be more robust when approximating the two binary variables "avoiding the need of a face-to-face visit" and "increased demand" (precision = 0.98 and 0.97, respectively) rather than the variable "type of query"(precision = 0.48). Conclusion: to the best of our knowledge, this study is the first to investigate a machine learning strategy for text classification using primary care teleconsultation datasets. The study illustrates the possible capacities of text analysis using artificial intelligence. The development of a robust text classification tool could be feasible by validating it with more data, making it potentially more useful for decision support for health professionals.

This paper investigates the role of English language proficiency (ELP) as a measure of cultural integration on U.S. immigrant families’ economic integration, as measured by annual earnings, and health care market integration, as captured by annual medical care spending. Bayesian Markov Chain Monte Carlo (MCMC) estimation of a mixed bivariate ordered probit (MBOP) model of annual earnings and medical care spending is conducted using a nationally representative pooled cross-sectional sample data from the U.S. National Health Interview Surveys (NHIS). The results reveal that limited English proficiency is associated with lower marginal earnings propensities (-$44.83, -$50.66, and -$56.97), and higher marginal medical care spending propensities ($8.09, $6.09, and $4.32) for each of the three decreasing levels of ELP. Furthermore, we find a small yet statistically significant positive 7.2% correlation between immigrant families’ annual earnings and medical care spending propensities. Therefore investing to raise immigrants’ families ELP in the U.S. would not only contribute to more effective socio-economic integration, but also strengthen the U.S. workforce and economy for decades to come.

Background User fee exemption for maternal and child health care service policy was introduced with a focus on providing free caesarean sections (CS) in Nigeria from 2011 to 2015. This policy had a positive impact on access to facility-based delivery, but its effect on socioeconomic and geographical inequality remains unclear. This study’s main objective is to examine access to birth by CS in the context of free maternal health care. Specifically, the study examines socio-demographic and geographical inequality in access to birth by CS among women who gave birth between 2011 and 2015 under the free maternal health care policy using a population-based survey data obtained from two of the six main regions of the country. Methods Data were obtained from 1227 women who gave birth during the period the policy was in operation selected using cluster random sampling between May and August 2016. Adjusted and unadjusted binary logistic regression models were used to examine whether there is socio-demographic and geographical inequality in access to birth by caesarean section. Results The overall caesarean section rate of 6.1% was found but varies by income (14.1% in monthly income of over $150 versus 4.9% in income of $150 and below), education (11.8% in women with higher education versus 3.9% among women with secondary education and less) and place of residence (7.8% in urban areas versus 3.6% in rural areas). Women who earn a monthly income of $150 or less were 48% less likely to have a birth by CS compared to those who earn more. Compared to women who were educated to tertiary level, women who had secondary education or less were 54% less likely to have birth by caesarean section. Conclusion This study shows that inequality in access to CS persists despite the implementation of free maternal health care services. Given the poor access to facilities with capabilities to offer CS in most rural areas, free maternal healthcare policy is not enough to make birth by CS universally accessible to all pregnant women in Nigeria.

This study evaluates inequalities in the use of dental services according to place of birth before and after the economic crisis in Spain. A cross-sectional study was performed in the population aged 18 to 65 years in Spain. We used data from three Spanish National Health Surveys for years 2006 (before the crisis), 2014 and 2017 (after the crisis). Log-binomial regression was used to quantify the association between region of origin and use of dental care services before and after controlling for the selected covariates. In 2006, we found a greater probability of not using dental care services in immigrants from Asia (PR:1.36, 95% CI:1.10–1.67) and Africa (PR:1.16; 95% CI:1.05–1.28) compared to the natives. For 2014, the probability of not using dental care services was greater for all immigrants compared to the natives, with the greatest odds for those from Africa (PR:1.71; 95% CI:1.46–2.01) and Asia (PR:1.3; 95% CI:1.23–1. 47). The associations for 2017 were weaker in magnitude than the ones observed for 2014, although stronger than for 2006. This study suggests that the economic recovery did not have the same impact for natives and immigrants regardless of regions of origin, given the observed inequalities in use of dental services.

Background: This study aims to compare the impact of early and late post-discharge cardiopulmonary rehabilitation on the outcomes of intensive care unit (ICU) survivors. Methods: The retrospective, cohort study used a sub-database of the Taiwan National Health Insurance Research Database (NHIRD) that contains information of all patients had ICU admission between 2000 and 2012. Early group was defined if patients had received cardiopulmonary rehabilitation within 30 days after ICU discharge, and late group was define as if patients had received cardiopulmonary rehabilitation between 30 days and one year after ICU discharge. The end points were mortality and re-admission during the 3-year follow-up. Results: Among 2136 patients received cardiopulmonary rehabilitation after ICU discharge, 994 was classified early group and other 1142 patients were classified as late group. Overall, early group had a lower mortality rate (6.64% vs 10.86%, p = 0.0006), and a lower ICU readmission rate (47.8% vs 57.97%, p < 0.0001) than late group after 3-year follow-up. Kaplan-Meier analysis showed that early group had significantly lower mortality (p=0.0009) and readmission rate (p<0.0001) than late group. In multivariate analysis, the risk of ICU readmission was found to be independently associated with late group (HR, 1.28; 95% CI, 1.13-1.47). Conclusions: Early post-discharge cardiopulmonary rehabilitation among ICU survivors has the long-term survival benefit and significantly decreases the readmission rate.

High-Level Synthesis (HLS) tools have revolutionized FPGA application development by providing a more efficient and streamlined approach, significantly impacting digital design methodologies. Despite the capability of FPGAs to customize numerical representations in data paths, most HLS projects have focused on fixed-point precision, while floating-point representations remain limited to vendor-provided single, double, and half-precision formats. This paper proposes a customized floating-point library compatible with HLS to address these limitations. This library allows programmers to define the number of exponent and mantissa bits at compile time, providing greater flexibility and enabling the use of mixed precision. Moreover, this library includes optimized implementations of common components such as vector summation (VSUM), dot-product (DP), and matrix-vector multiplication (MVM). Results demonstrate that the proposed library reduces latency and resource utilization compared to vendor IP blocks, particularly in VSUM, DP, and MVM operations. For example, the MVM operation involving a 32x32 matrix, using vendor IP requires 22 clock cycles, whereas CuFP completes the same task in just 7 clock cycles, using approximately 60% fewer DSPs, 10% fewer LUTs, and 60% fewer FFs.

The complex progression, specialized care, and comorbidities of chronic diseases place a financial and health burden on society. In some instances, the high hospital readmission rate is also a result of chronic diseases. The readmission rates can be decreased if the quality of life for patients is increased and healthcare costs are reduced through effective management and preventive measures. As a result, healthcare professionals, service providers, and policy-makers are looking for innovative approaches to reduce healthcare costs while enhancing the quality of care. There is an emerging trend in deploying technological advancements like artificial intelligence (AI), the Internet of Things (IoT), sensors, wearables, social media, mobile apps, and genomics to decrease hospital readmissions. In some instances, predictive analytics, early warning systems, personal-ized care management, remote monitoring and Telehealth, decision support systems, patient education and engagement, and other areas of artificial intelligence and machine learning have outperformed traditional approaches in lowering hospital readmissions. Although AI effectively reduces readmission, there are potential risks if it is not combined with efficient interventions. Therefore, real-time monitoring and intervention are required for AI systems to increase patient safety and decrease hospital readmissions. To achieve autonomy, prevent harm, achieve fairness, and achieve explicability, the ethical principles relating to AI systems should be taken into ac-count. This study examines the significant impact on health and the economy of hospital read-missions for chronic diseases and the role of AI in reducing readmissions.

Online digital mental health communities can contribute to users’ mental health positively and negatively. Yet the measurement of outcomes and impact relating to digital mental health communities is difficult to capture. In this paper we demonstrate the development of an online experience measure for a specific children and young people’s community inside a digital mental health service. The development is informed by three phases: (i) item reduction through Estimate-Talk-Estimate modified Delphi methods, (ii) user testing with participatory action research and (iii) a pilot within the digital service community to explore its use. Rounds of experts talks help to reduce the items. User experience workshops helped to inform the usability and appearance, wording, and purpose of the measure. Finally, the pilot results highlight completion rates, difference in scores for age and community roles and a preference to ‘relate to others’; as a mechanism of support. Outcomes frequently selected in the measure show the importance of certain aspects of the community, such as safety, connection, and non-judgment previously highlighted in the literature. Self-reported helpfulness scales like this one could be used as indicators of meaningful engagement within the community and its content but further research is required to ascertain its acceptability and validity. Phased approaches involving stakeholders and participatory action research enhances the development of digitally enabled measurement tools.

Pipelines extend thousands of kilometers to transport and distribute oil and gas. Given the challenges often faced with corrosion, fatigue, and other issues on steel pipes, the demand for glass fiber reinforced plastics (GFRP) pipes is increasing in the oil and gas gathering and transmission systems. However, the medium transported through these pipelines contains multiple acid gases such as CO2 and H2S, as well as ions including Cl-、Ca2+、Mg2+、SO42-、CO32- and HCO3-. These substances can cause a series of problems, such as aging, debonding, delamination, and fracture. In this study, a series of aging damage experiments were conducted on V-shaped GFRP pipes with depths of 2mm and 5mm. The aging and failure of GFRP were studied under the combined effects of external force and acidic solution using acoustic emission (AE) techniques. It was found that the acidic aging solution promoted matrix damage, fiber/matrix desorption, and delamination damage in GFRP pipes over a short period. However, the overall aging effect was relatively weak. Based on the experimental data, the SSA-LSSVM algorithm was proposed and applied to the damage pattern recognition of GFRP. An average recognition rate of up to 90% was achieved, indicating that this method is highly suitable for analyzing AE signals related to GFRP damage.

This paper presents a novel segmentation algorithm specially developed for applications in 3D point clouds with high variability and noise, particularly suitable for heritage building 3D data. The method can be categorized within the segmentation procedures based on edge detection. In addition, it uses a graph-based topo-logical structure generated from the supervoxelization of the 3D point clouds, which is used to make the clo-sure of the edge points and to define the different segments. The algorithm provides a valuable tool for generating results that can be used in subsequent classification tasks and broader computer applications dealing with 3D point clouds. One of the characteristics of this segmentation method is that it is unsupervised, which makes it particularly advantageous for heritage applications where labelled data is scarce. It is also easily adaptable to different edge point detection and supervoxelization algorithms. Finally, the results show that the 3D data can be segmented into different architectural elements, which is important for further classification or recognition. Extensive testing on real data from historic buildings demonstrates the effectiveness of the method. The results show superior performance compared to three other segmentation methods, both globally and in the segmentation of planar and curved zones of historic buildings.

This paper introduces a novel method for accurately calculating the upper biomass of single trees using Light Detection And Ranging (LiDAR) point cloud data. The proposed algorithm involves classifying the tree point cloud into two distinct ones: the trunk point cloud and the crown point cloud. Each part is then processed using specific techniques to create a 3D model and determine its volume. The trunk point cloud is segmented based on individual stems, with each stem further divided into slices that are modeled as cylinders. On the other hand, the crown point cloud is analyzed by calculating its footprint and gravity center. The footprint is further divided into angular sectors, with each being used to create a rotating surface around the vertical line passing through the gravity center. All models are represented in a matrix format, simplifying the process of minimizing and calculating the tree’s upper biomass, consisting of crown biomass and trunk biomass. To validate the proposed approach, both terrestrial and airborne datasets are utilized. A comparison with existing algorithms in the literature confirms the effectiveness of the new method. The study shows that the proposed algorithm achieves an average fit between 0.01 m and 0.49 m for individual trees.

This research focuses on the Hopf bifurcation occurring at a singular point with high-order degeneracy in a class of three-dimensional systems. Based on center manifold theorem, by expanding the technique for determining singular point values of degenerate singularities in two-dimensional systems, the formal series method to determine the singular point values at the high-order degenerate critical point is discussed. Furthermore, a class of specific three-dimensional differential systems with high-order degenerate singularities is explored. By computing the singular point values and determining center conditions, we proved that a minimum of 5 small-amplitude limit cycles in the vicinity of the origin. This research provides new perspectives on the center problem and limit cycle bifurcation in high-dimensional systems with high-order degenerate singular points.

Interactions between mobile robots and human operators in common areas require a high safety especially in terms of trajectory planning, obstacle avoidance and mutual cooperation. In this connection the crossings of planned trajectories, their uncertainty based on model fluctuations, system noise and sensor noise,play an outstanding role. This paper discusses the calculation of expected areas of interactions du ring human-robot navigation with respect to fuzzy and noisy information. Expected crossing points of possible trajectories are nonlinearily associated with positions and orientations of robot and human. The nonlinear transformation of a noisy system input, such as directions of motion of human and robot, to a system output, the expected area of intersection of their trajectories, is done by two methods: statistical linearization and the sigma-point-transformation. For both approaches fuzzy approximations are presented and the inverse problem is discussed where the input distribution parameters are computed from given output distribution parameters.

Point defects induced by doping rare earth elements RE (Nd, Er) into the magnesium oxide host were investigated by classical atomistic simulations utilising the General Utility Lattice Program (GULP). Formation and association energies were calculated for the potential defect structures. Both isolated defects and defect complexes were considered. The most energetically favourable structures of defect complexes were found for rare earth doped and Li co-doped systems. The correlation between the association energy and the structure of the defect complex was investigated. The influences of Li were revealed with respect to energy and structure. The simulation results contribute to the understanding of the point defects of doped MgO and how Li influences the doping of rare earth elements in the MgO host.

Accurate classification of objects in 3D point clouds is a significant problem in several applications, such as autonomous navigation and augmented/virtual reality scenarios, which has become a research hot spot. In this paper, we presented a deep learning strategy for 3D object classification in augmented reality. The proposed approach is a combination of the GRU and LSTM. LSTM networks learn longer dependencies well, but due to the number of gates, it takes longer to train; on the other hand, GRU networks have a weaker performance than LSTM, but their training speed is much higher than GRU, which is The speed is due to its fewer gates. The proposed approach used the combination of speed and accuracy of these two networks. The proposed approach achieved an accuracy of 0.99 in the 4,499,0641 points dataset, which includes eight classes (unlabeled, man-made terrain, natural terrain, high vegetation, low vegetation, buildings, hardscape, scanning artifacts, cars). Meanwhile, the traditional machine learning approaches could achieve a maximum accuracy of 0.9489 in the best case.

Precise individual tree or sample-based inventories derived from 3D point cloud data of mobile laser scanning can improve our comprehensive understanding of the structure, function, resilience, biodiversity, and ecosystem services of urban forests. This study assessed the performance of a hand-held laser scanning system for the extraction of tree position, diameter at breast height (DBH) and tree height (H) in an urban area. A total of 2083 trees of 13 species from 34 plots were analyzed. The results showed that the registration of tree positions using ground control points (GCPs) demonstrated high accuracy, with errors consistently below 0.4 m, except for a few instances. The extraction accuracy of DBH for all trees and individual species remained consistently high, with a total root mean square error (RMSE) of 2.06 cm (6.89%) and a bias of 0.62 cm (2.07%). Notably, broad-leaved trees outperformed coniferous trees, with RMSE and bias values of 1.86 cm (6%) and 0.76 cm (2.46%) compared to 2.54 cm (9.46%) and 0.23 cm (0.84%). Tree height extraction accuracy varied significantly among different species, with R2 values ranging from 0.65 to 0.92. Generally, both DBH and height were underestimated. Linear mixed effects models (LME) were applied to evaluate factors affecting the performance of HLS with the plot as a random factor. LME analysis revealed that plant type and terrain significantly influenced the accuracy of DBH and H derived from HLS data. Other fixed factors of plot area, tree density and trajectory length didn’t have significance. With a large sample size, we concluded that the HLS demonstrated sufficient accuracy in extracting individual tree parameters in urban forests.

The most commonly used real-time augmentation services in China are International GNSS Service (IGS) real-time service, PPP-B2b service, and BeiDou Satellite-Based Augmentation System (BDSBAS) dual-frequency augmentation service. However, the research on the performance evaluation, comparison and application scope of these three products is still unknown and unrevealed. This article introduces methods for obtaining real-time augmentation information and real-time orbit and clock offset recovery. Based on real-time orbit and clock offset accuracy, positioning accuracy, and positioning availability, it systematically evaluates the performance of CNES, PPP-B2b, and BDSBAS augmentation information. The results indicate that the radial accuracy of CNES and PPP-B2b real-time orbit products is consistent, and the Root Mean Square (RMS) is better than 5 cm. CNES can achieve centimeter-level accuracy in both along-track and cross-track components, surpassing the decimeter-level accuracy of PPP-B2b. Both services demonstrate consistent accuracy in real-time clock offset, with PPP-B2b showing similar standard deviations (STD) of 0.16 ns for different satellites. However, for CNES, the STD of real-time clock offset varies for GPS, BDS-3 MEO, and BDS-3 IGSO satellites, with values of 0.10 ns, 0.19 ns, and 0.60 ns, respectively. The accuracy and availability of the two PPP services exhibit the same levels, with centimeter-level accuracy achieved after convergence and positioning availability exceeding 99%. Therefore, the difference between the two services in application areas depends on the acquisition of augmentation information. However, BDSBAS, which concentrates on code observations, demonstrates lower accuracy in real-time orbit and clock offset, positioning accuracy, and positioning availability compared to the other two services. Its primary application is in the aviation and maritime domains, where there is a greater need for service integrity, continuity, and reliability.

Rational delineation of urban–rural boundaries is a foundational prerequisite for holistic urban and rural development planning and rational resource allocation. However, the results of division of urban–rural boundaries extracted using a single data source are non-comprehensive. To address this problem, the present study proposes a method for using multiple sources such as population data, nighttime light data, land use, and points of interest (POI) data to extract urban–rural boundaries. Considering Guizhou Province for a case study, we here present a two-step method for identifying urban–rural boundaries. First, the random forest model was combined with the dasymetric mapping method to obtain the population spatialization data with a 30-m resolution in the studied province. Second, using the breaking point method, we extracted the urban–rural boundary for Guizhou Province in 2020 based on the spatialized population. This method fully integrated the benefits of various data and judiciously extracted the boundaries of the main urban areas and small- and medium-sized towns of each city in the study province at the same spatial scale. The stratified random sampling method revealed that the average overall accuracy was 88.05%. The method proposed has certain universality and application value and allows identifying the urban–rural boundaries more accurately and practically.

The management and classification of solid waste is one of the most important challenges around the world, in order to sustain economic growth and preserve the environment. The objective is to propose the use of Smart Ecological Points as a strategy to address the problem related to the solid waste management system at the source, which has become one of the biggest problems globally and Colombia is no exception. The article describes the current state of the problem in the country and in turn, presents the possibility of developing a prototype corresponding to a low-cost Smart Ecological Point supported by the use of an experimental capacitive sensor and Machine Learning algorithms, which will reduce the time necessary for the classification of recyclable and non recyclable waste, minimizing the health risks and increasing the percentage of waste that can be reused, by reducing the probability of being contaminated at the source, an aspect that is very common when done manually. According to the results obtained, it was evident that the proposed prototype made an adequate classification of waste, generating the possibility of being manufactured with existing technology in the environment, in order to promote adequate waste classification at the source.

High-precision ground point cloud data has a wide range of applications in various fields, and the separation of ground points from non-ground points is a crucial preprocessing step. Therefore, designing an efficient, accurate, and stable ground extraction algorithm is of great significance for improving the processing efficiency and analysis accuracy of point cloud data. The study area in this article was a Park in Guilin, Guangxi, China. The point cloud was obtained by utilizing the UAV platform. In order to improve the stability and accuracy of the Filter algorithm, this article proposed a triangular grid filter based on Slope Filter, found violation points by the spatial position relationship within each point in the triangulation network, improved KD-Tree-Based Euclidean Clustering, and applied it to the non-ground points extraction, this method has good accuracy, stability and achieves good results in separating ground points from non-ground points. At first, using Slope Filter to remove some non-ground points, to reduce the error of taking ground points as non-ground points; Secondly, established a triangular grid based on the triangular relationship between each point, the violation-triangle can determin through the grid, and then the corresponding violation points were found in the violation-triangle; Thirdly, according to the three-point collinear method to extract the regular points, used these points to extract the regular landmarks by KD-Tree-Based Euclidean Clustering and Convex Hull Algorithm; Finally, removed disperse points and irregular landmarks by Clustering Algorithm. In order to confirm the superiority of this algorithm, this article compared the filter effects of various algorithms on the study area and filtered the 15 sample data provided by ISPRS, and obtained an average error of 3. 46%. The results showed that the algorithm in this article have a high processing efficiency and accuracy, which can greatly improve the processing efficiency of point cloud data in practical applications.

3D point cloud classification tasks have been a hot topic in recent years. Most existing point cloud processing frameworks lack context-aware features due to the deficiency of sufficient local feature extraction information. Therefore, we design an augmented sampling and grouping (ASG) module to efficiently obtain fine-grained features from the original point cloud. In particular, this method strengthens the domain near each centroid and makes reasonable use of the local mean and global standard deviation to mine point cloud’s local and global features. In addition to this, inspired by the transformer structure UFO-ViT in 2D vision tasks, we first try to use a linearly-normalized attention mechanism in point cloud processing tasks, investigating a novel transformer-based point cloud classification architecture UFO-Net. An effective local feature learning module is adopted as a bridging technique to connect different feature extraction modules. Importantly, UFO-Net employs multiple stacked blocks to better capture feature representation of the point cloud. Extensive ablation experiments on public datasets show that our method outperforms other state-of-the-art methods. For instance, our network performed with 93.7% overall accuracy on the ModelNet40 dataset, which was 0.5% higher than PCT. Our network also archived 83.8% overall accuracy on the ScanObjectNN dataset, which is 3.8% better than PCT.

The paper's main goal is to introduce a novel type of interpolative convex contraction and build up some fresh findings for it using the interpolative convex contractions' progressive approach. We have established certain conclusions using orbitally S-complete and Suzuki type contractions in F-metric spaces. My research aims to examine the fixed point method's efficacy in solving fractional differential equation with boundary conditions.

Spatial approach based on the deformation measurement of volcanic dome and crater rim is key to evaluate the activity of a volcano, such as Merapi volcano where associated disaster risk is regularly taking lives. Within this framework, this study aime to detect localized deformation and change in the summit area that has occurred concomitantly with the dome growth and explosion reported. The methodology was focused on two sets of data, one LiDAR-based dataset of 2012 and one UAV-dataset of 2014. The results show that during the period 2012-2014, the crater walls are 100 m to 120 m high above the crater floor at its maximum (North to East-South-East sector), while the West and North sector presents a topographic range of 40 to 80 m. During the period 2012 – 2014, the evolution of the crater rim around the dome is generally stable (no large collapse). The opening of a new vent on the surface of the dome has displaced an equivalent volume of 2.04 E+04 m3 corresponding to a maximum -9 m (+/- 0.9 m) vertically. This concludes that during the period 2012 – 2014 when the dome of Merapi experienced phreatic or phreatomagmatic explosions, the topography around the dome rose. This rise does not seem to be related to large wall collapses, and it is likely that modification in the subsurface have triggered those changes.

The ACC feature when activated augments the engine performance in real-time. This article presents a novel methodology to predict the optimal adaptive cruise control set speed profile (ACCSSP) by considering all the effecting parameters. This paper investigates engine operating conditions (EOC) criteria to develop a predictive model of ACCSSP in real-time. We developed a deep learning (DL) model using the NARX method to predict engine operating point (EOP) mapping the vehicle-level vectors (VLV). We used real-world field data obtained from Cadillac test vehicles driven by activating the ACC feature for developing the DL model. We used a realistic set of assumptions to estimate the VLV for the future time steps for the range of allowable speed values and applied them at the input of the developed DL model to generate multiple sets of EOP’s. We imposed the defined EOC criteria on these EOPs, and the top three modes of speeds satisfying all the requirements are derived for each second. Thus three eligible speed values are estimated for each second, and an additional criterion is defined to generate a unique ACCSSP for future time steps. Performance comparison between predicted and constant ACCSSPs indicates that the predictive model outperforms constant ACCSSP.

General relativity is a theory for gravitation based on Riemannian geometry, difficult to compatibilize with quantum mechanics. This is evident in relativistic problems in which quantum effects cannot be discarded. For example in quantum gravity, gravitation of zero-point energy or events close to a black hole singularity. Here, we set up a mathematical model to select general relativity geodesics according to compatibility with the uncertainty principle. To achieve this, we derived a geometric expression of the uncertainty principle (GeUP). This formulation identified proper space-time length with Planck length by a geodesic-derived scalar. GeUP imposed a minimum allowed value for the interval of proper space-time which depended on the particular space-time geometry. GeUP forced the introduction of a “zero-point” curvature perturbation over flat Minkowski space, caused exclusively by quantum uncertainty but not to gravitation. When applied to the Schwarzschild metric and choosing radial-dependent geodesics, our mathematical model identified a particle exclusion zone close to the singularity, similar to calculations by loop quantum gravity. For a 2 black hole merger, this exclusion zone was shown to have a radius that cannot go below a value proportional to the energy/mass of the incoming black hole multiplied by Planck length.

In this paper, by using the variational method, a sufficient condition for the unique existence of the stationary solution of the reaction-diffusion ecosystem is obtained, which directly leads to the global asymptotic stability of the unique equilibrium point. Besides, employing impulse control technique derives the globally exponential stability criterion of delayed feedback ecosystem.And numerical examples illuminate the effectiveness of impulse control, which has a certain enlightening effect on the actual epidemic prevention work . That is, in the face of the epidemic situation, taking a certain frequency of positive and effective epidemic prevention measures is conducive to the stability and control of the epidemic situation. particularly, the newly-obtained theorems quantifies this feasible step.

This paper introduces a method for tunnel point cloud and BIM model integration and cross-section monitoring, providing information to analyse tunnel cross-sections and surrounding rock deformation, and support for tunnel maintenance and reconstruction. Three types of data are processed for the integration: laser scanning point cloud, BIM tunnel model and terrain model from oblique photogrammetry. An adaptive BIM modelling scheme is proposed for tunnels with alien structures. Precise spatial registration of the data sets is conducted by applying singular value decomposition (SVD) algorithm to calculate transformation parameters from the point cloud model to the BIM model. Since the tunnel central line has high-order derivability, a cross-section calculation method based on tangent vector is proposed to obtain the cross-sectional profile of tunnels at any mileage. The proposed method has been verified by applying it to a tunnel reconstruction project. The experiment results show that the tunnel point cloud and the BIM model were highly coincident after the integration. The developed program can effectively get the cross-section of the tunnel at any mileage, and correctly express the spatial relationship between the BIM tunnel, the point cloud of tunnel and the external mountainous terrain.

Background: In recent years, the abusive use of the smartphone has reached a situation that could be considered pathological, although there is no such classification in the DSM-IV. In this sense, different instruments to assess this problematic use or addiction to the smartphone are used. Among them, we found the SPAI, which has been validated in the Spanish language. The main difficulty of these scales is to establish a cut-off point that determines such mobile addiction. On the other hand, self-perception has been used in different addictions as a predictor of the problem. Aim: The objective of this study is to establish the cutting point in the scores of the SPAI scale validated in Spanish, using as a referent the self-perception of addiction values. Methods: A receiver operating characteristics (ROC) analysis was carried out, establishing as the cut-off point the one that presented a higher value of Youden J, indicative of its sensitivity and specificity. Results: 2598 participants from the university community completed the SPAI-Spain questionnaire. When using the self-perception of smartphone addiction as the benchmark value, a score of 44 has been established as the cutting point of the SPAI questionnaire, with a Youden J corresponding to 0.416. Conclusions: The implementation of a cut-off point of the SPAI questionnaire makes it an instrument that allows early identification of those individuals at risk of addiction as well as the establishment of preventive and/or intervention measures.

We present an improved algorithm for fast calculation of the inverse square root for single-precision floating-point numbers. The algorithm is much more accurate than the famous fast inverse square root algorithm and has a similar computational cost. The presented modification concern Newton-Raphson corrections and can be applied when the distribution of these corrections is not symmetric (for instance, in our case they are always negative).

To determine the photon emission or absorption probability for a diatomic system in the context of the semiclassical approximation it is necessary to calculate the characteristic canonical oscillatory integral which has one or more saddle points. Integrals like that appear in a whole range of physical problems, e.g. the atom-atom and atom-surface scattering and various optical phenomena. A uniform approximation of the integral, based on the stationary phase method is proposed, where the integral with several saddle points is replaced by a sum of integrals each having only one or at most two real saddle points and is easily soluble. In this way we formally reduce the codimension in canonical integrals of "elementary catastrophes" with codimensions greater than 1. The validity of the proposed method was tested on examples of integrals with three saddle points ("cusp" catastrophe) and four saddle points ("swallow-tail" catastrophe).

The aim of this article is to extend the local as well as the semi-local convergence analysis of multi-point iterative methods using center Lipschitz conditions in combination with our idea, of the restricted convergence region. It turns out that this way a finer convergence analysis for these methods is obtained than in earlier works and without additional hypotheses. Numerical examples favoring our technique over earlier ones completes this article.

We consider Pisot family substitution tilings in $\R^d$ whose dynamical spectrum is pure point. There are two cut-and-project schemes(CPS) which arise naturally: one from the Pisot family property and the other from the pure point spectrum respectively. The first CPS has an internal space $\R^m$ for some integer $m \in \N$ defined from the Pisot family property, and the second CPS has an internal space $H$ which is an abstract space defined from the property of the pure point spectrum. However it is not known how these two CPS's are related. Here we provide a sufficient condition to make a connection between the two CPS's. In the case of Pisot unimodular substitution tiling in $\R$, the two CPS's turn out to be same due to [5, Remark 18.5].

In this paper, we introduced many new notions and new contraction named as S-weakly contraction after that we obtained the p-common best proximity point theorems for different types of contractions in the setting of complete metric spaces by using weak P_p-property and proved the uniqueness of these points. Also we presented some examples to prove the validity of our results.

Filamentous fungi such as Aspergillus spp. are opportunistic pathogens, which cause highly invasive infections, especially in immunocompromised individuals. Control of such fungal pathogens is increasingly problematic due to the small number of effective drugs available for treatment. Moreover, the increased incidence of fungal resistance to antifungal agents makes this problem a global human health issue. The cell wall integrity system of fungi is the target of antimycotic drugs echinocandins, such as caspofungin (CAS). However, echinocandins cannot completely inhibit the growth of filamentous fungal pathogens, which results in survival/escape of fungi during treatment. Chemosensitization was developed as an alternative intervention strategy, where co-application of CAS with the intervention catalyst octyl gallate (OG; chemosensitizer) greatly enhanced CAS efficacy, thus achieved ≥ 99.9% elimination of filamentous fungi in vitro. Based on hypersensitive responses of Aspergillus antioxidant mutants to OG, it is hypothesized that, besides destabilizing cell wall integrity, the redox-active characteristic of OG may further debilitate fungal antioxidant system.

The safe and reliable operation of autonomous vehicles in complex and dynamic environments is heavily dependent upon exteroceptive and proprioceptive sensors. A LiDAR system generates accurate 3D point clouds, which are crucial for the detection, classification, and tracking of multiple targets. LiDAR data, however, presents significant challenges due to its density, noise, and varying sampling rates. In this study, various clustering and MTT techniques for LiDAR point clouds will be identified and classified within the context of autonomous driving to assess the state-of-the-art methods’ key challenges and their performances. We have categorized clustering and MTT methods used in AV applications, identified research gaps and challenges and analyzed existing algorithms and their challenges in detail. Researchers and practitioners in the field of autonomous driving will find this review to be a valuable resource.

Abstract: Background: The optimal strategy for the microelimination of HCV within community settings remains ambiguous. We evaluated the percentage of participants who achieved linkage to care (LTC) following the conclusion of the screening campaign, and examined the diverse factors influencing LTC among these individuals. The effectiveness of recall intervention for the non-LTC population and its barriers were analyzed. Methods: We initiated an HCV patients recall program to identify the HCV participants who might not be treated after the HCV screening campaign. A program staff recalled HCV participants who lost to follow-up through the telephone from March 2019 to June 2019. They were informed of HCV treatment's importance, efficacy, availability, and safety. Result: Among 185 HCV-infected participants, 109 (58.9%) HCV-infected participants had obtained LTC. Compared with those who had LTC, those without LTC were older, lower education levels, were less aware of their HCV infection, less frequently lived in urban areas, and had less health insurance. At the end of the recall program, 125 (67.6 %) persons had liked to care. The proportion of LTC increased by 8.7 %. 119 persons had an HCV RNA test, and 82 (68.9%) had viremia. Of 82 patients with viremia, 78 (95.1%) received antiviral therapy. 76 (97.4 %) of them achieved a sustained virological response. Conclusion: After a community screening campaign, 59 % of participants with anti-HCV positive had LTC. The recall program can increase by 9 %. However, there were still 32% of HCV participants who couldn't be linked to care. Outreach care for non-LTC patients is a way worth trying to achieve micro-elimination of HCV in the rural community.

Background: Electrical Impedance Tomography (EIT), combined with variable ventilation strate-gies and Artificial Intelligence (AI), is poised to revolutionize critical care by transitioning from reactive to predictive approaches. This integration aims to enhance patient outcomes through personalized interventions and real-time monitoring. Methods: This narrative review explores the principles and applications of EIT, variable ventilation, and AI in critical care. EIT’s impedance sensing creates dynamic images of internal physiology, aiding in the management of conditions like Acute Respiratory Distress Syndrome (ARDS). Variable ventilation mimics natural breathing variability to improve lung function and minimize ventilator-induced lung injury. AI enhances EIT through advanced image reconstruction techniques, neural networks, and digital twin technology, offering more accurate diagnostics and tailored therapeutic interventions. Conclu-sions: The confluence of EIT, variable ventilation, and AI represents a significant advancement in critical care, enabling a predictive, personalized approach. EIT provides real-time insights into lung function, guiding precise ventilation adjustments and therapeutic interventions. AI inte-gration enhances EIT's diagnostic capabilities, facilitating the development of personalized treatment plans. This synergy fosters interdisciplinary collaborations and sets the stage for in-novative research, ultimately improving patient outcomes and advancing the future of critical care.

Background: The aim of the current study is to evaluate the effects of inflammation markers, on infection and mortality in patients over 65 years of age monitored in the intensive care unit. In the study, the significance of pan-immune inflammation (PIV), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), monocyte-lymphocyte ratio (MLR), systemic immune-inflammatory index (SII), systemic immune response index (SIRI), multi-inflammatory index (MII) 1-2-3, and CRP/albumin ratios, new biomarkers, were attempted to be determined as prognostic and mortality markers in patients over 65 years of age monitored in the ICU. Methods: This multicenter, retrospective cohort study was conducted in two tertiary-level ICUs with patients aged 65 and over who were admitted. Patients with cirrhosis, bone marrow transplantation, hematologic malignancy, undergoing chemotherapy, and neutropenia at admission to the ICU were excluded from the study. Results: A total of 333 patients were included in the study. The 28-day mortality was found to be 31.8%. When each inflammatory marker associated with 28-day mortality was examined the CRP/albumin ratio performed better than both NLR and SIRI, and the results were statistically significant (AUC: 0.665, 95% CI: 0.604-0.726 and p <0.001). NLR had a moderate discriminative ability in distinguishing mortality risk (AUC: 0.593, 95% CI: 0.526-0.660 and p = 0.006). Although SIRI was lower than NLR, it had a statistically significant result (AUC: 0.580, 95% CI: 0.514-0.646 and p = 0.019). CRP/albumin ratio was the most effective inflammatory marker in predicting mortality risk in geriatric patients admitted to the ICU.

Prostate Cancer remains a prevalent health concern, emphasizing the critical need for early diagnosis and precise treatment strategies to mitigate mortality rates. Accurate prediction of cancer grade is paramount for timely interventions. This paper introduces an approach to prostate cancer grading, framing it as a classification problem. Leveraging ResNet models on multi-scale patch-level digital pathology and the Diagset dataset, the proposed method demonstrates notable success, achieving an accuracy of 0.999 in identifying clinically significant prostate cancer. The study contributes to the evolving landscape of cancer diagnostics, offering a promising avenue for improved grading accuracy and, consequently, more effective treatment planning. By integrating innovative deep-learning techniques with comprehensive datasets, our approach presents a step forward in the pursuit of personalized and targeted cancer care.

Background: Assessing the impact of bone health clinical management in breast cancer (BC) patients receiving adjuvant endocrine therapy and designing a personalized clinical pathway to reduce bone loss, in an Italian research hospital. Methods: The primary endpoint was to assess (through the process improvement organizational method) the clinical pathway that post-surgical BC patients prescribed with endocrine therapy undergo to prevent bone loss. The secondary endpoint was to design a personalized clinical pathway for a prompt implementation of guidelines, to assess and possibly prescribe antiresorptive therapy. Results: During the first year of the new diagnostic therapeutic assistance pathway execution, an 60% increase in Dual-Energy X-ray Absorptiometry evaluations within 30 days and a 39.5% increase in antiresorptive therapy prescription within 90 days (since prescription of endocrine therapy) were shown, thus increasing patients’ compliance. Conclusion: Case managers and bone health specialists in this context can improve patients’ adherence to therapies and bone health, helping physicians to expand their collaboration.

Background: The adoption of self-care behaviors among patients with congestive heart failure (CHF) is essential for the management of their health condition. However, there is a lack of tools for estimating self-care in CHF patients. We aim to develop and validate the Hippocratic heart failure self-care scale (HHFSCS). Methods: the scale includes 22 items which are reviewed by a committee of experts. Individuals indicate the frequency at which they follow each self-behavior on a five-point Likert scale. Adult patients with CHF (n=250) from a General Hospital, in Athens, were participated in the study from June 2020 to March 2021. Reliability coefficients and Explanatory Factor Analysis (EFA), using a Varimax rotation and the Principal Components Method were used to assess the psychometric measurements. Results: The Cronbach’s alpha coefficient of the HHFSCS was 0.807. The exploratory factor analysis identified two domains that accounted for 88.44% of the variance of the scale items; however, each sub-scale could not be used as an independent scale. Finally, the test-retest showed a significant strong correlation (r=0.973, p&lt;0.001). Conclusions: The HHFSCS is a reliable and valid tool for assessing self-behaviors in CHF patients. Health professionals can use it in their clinical practice to improve the management of patient’s health conditions.

The experiment assessed the impact of the interaction of two care treatments on the growth and flowering of two varieties of Panicle Hydrangea bushes. The first treatment considered was plant pruning. The second simultaneous treatment was one of the three mentioned, root application of Trichoderma atroviride and BlackJak biostimulator and foliar application of a multi-component fertilizer. The strongest impact on improving the length of hydrangea shoots compared to the control (18%) had their simultaneous pruning and inoculation of the plants with Trichoderma atroviride mycelium. These two treatments used together also increased the number of flowers (16-47% depending on the variety) and the fresh weight of plants (10-28%) compared to the control. The application of T. atroviride alone improved the number of flowers in both varieties (19-24%) and the diameter of inflorescences in the 'Silver Dollar' one (17%). Foliar nutrition in particular increased the mass of plants, depending on the variety and pruning, from 7 to 57%, as well as the diameter and number of inflorescences, but only in one of the varieties considered. Combined with pruning, it intensified the growth of shoots of both varieties (5-10%). The use of the BlackJak biostimulator gave ambiguous results. When pruning plants, the length of shoots improved (15%) for one of the tested varieties and the fresh weight for the other (18%). Without pruning, it increased the number of flowers (16%) and the diameter of inflorescences (9%) in one of the varieties considered, as well as the fresh weight of plants in both varieties (19-21%). Pruning the plants, regardless of the other treatments used, increased the length of the shoots and the fresh mass of the plants. On the other hand, it reduced the number of flowers and their diameter. In most cases, positive effects of the use of biostimulants and foliar fertilization on improving the growth and flowering of plants were obtained. After their use in combination with plant pruning, an improvement in the growth of hydrangea bushes was observed, while the number and diameter of flowers were reduced. The most beneficial care treatments for the growth and flowering of panicle hydrangea were the simultaneous application of T. atroviride and pruning of plants during container cultivation in a nursery.

Background: There is a lack of knowledge about how nurses and general practitioners (GPs) collaborated during the COVID-19 pandemicin primary care settings. Our study examined the roles of primary care nurses during the pandemic’s first wave, between March and June 2020, in Switzerland. Methods: The study involved all eight general practices implementing of a nursing role to the practice’s team. Primary care practice staff members (nurses, GPs and medical assistants) have been involved on the development of a new organizational model. A mixed-methods design study collected quantitative data using daily activity monitoring and an electronic survey. Additionally, eight nurses and nine GPs participated in a focus group discussion and individual interviews. Results: GPs recognized the substantial contributions, versatility, and autonomy of the primary care nurses in their practices during the pandemic. Those nurses experienced their involvement positively, mainly thanks to their perceived autonomy. The distribution of activities between primary care practice professionals was heterogenous due to extrinsic and intrinsic factors. Conclusion: Both nurses and GPs agreed that there was added value in having primary care nurses ingeneral practices in time of crisis, and this agreement will bolster plans to integrate this workforce across the canton. The development of nurses’ roles in primary care during the pandemic was reliant on many factors, including practice organization and Switzerland’s healthcare reimbursement and payment system

Introduction: Physiotherapy exercises administered to preterm infants in the NICU can enhance motor skills and expedite the discharge process for infants born before 30 weeks of gestational age. The research delves into the influence of physiotherapy programs on these preterm infants' activity and participation levels. Methods: The intervention group received a one-month physiotherapy program including massage around the mouth, mobilization and weight-bearing exercises, and massage therapy for the extremities, while the control group did not. The motor skills were evaluated by the Test of Infant Motor Performance (TIMP), Dubowitz Neurological examination, and Preterm Oral Feeding Readiness Scales (POFRAS). Results: There was a significant difference in The TIMP, Dubowitz Optimal Score, Type of Non-Invasive Ventilation, TIMP Range, and POFRAS scores in the physiotherapy group rather than the control group (p<0.05). There were no differences in the length of stay in the NICU, respiration rate, heart rate, body temperature, oxygen saturation, body weight on the evaluation day, body weight at discharge, head circumference at discharge between the groups (p>0.05) Discussion: We conclude that physiotherapy in NICU improves the motor outcomes, activity and participation in preterm infants rather than the body functions and structure like vital signs and infants’ body weight.

Managing severe bleeding, particularly in soft tissues and visceral injuries, remains a significant challenge in trauma and surgical care. Traditional hemostatic methods often fall short in wet and dynamic environments. This study addresses the critical issue of severe bleeding in soft tissues, proposing an innovative solution using a Polyethylene Glycol (PEG)-based hydrogel combined with zinc oxide (ZnO). The developed hydrogel forms a dual-network structure through amide bonds and metal ion chelation, resulting in enhanced mechanical properties and adhesion strength. The hydrogel, exhibiting excellent biocompatibility, is designed to release zinc ions, promoting coagulation and accelerating hemostasis. Comprehensive characterization, including gelation time, rheological properties, microstructure analysis, and swelling behavior, demon-strates the superior performance of the PEG/ZnO hydrogel compared to traditional PEG hydro-gels. Mechanical tests confirm increased compression strength and adhesive properties, crucial for withstanding tissue dynamics. In vitro assessments reveal excellent biocompatibility and en-hanced procoagulant ability attributed to ZnO. Moreover, in vivo experiments using rat liver and tail bleeding models demonstrate the remarkable hemostatic performance of the PEG/ZnO hy-drogel, showcasing its potential for acute bleeding treatment in both visceral and peripheral sce-narios.

Research is scarce regarding antimicrobial use and antimicrobial resistance (AMR) for specific localities in Northern Ireland (NI). Additionally, the effects of COVID-19 on antimicrobial pre-scribing patterns and AMR are unknown. Between the European Union (EU) and United States (US), AMR causes approximately 68,000 deaths annually. This study will provide a better understanding of antimicrobial use and prescribing patterns in Belfast and link with AMR. An electronic survey was developed and distributed to eighty-five community pharmacists in Belfast. Yearly and monthly prescription data was gathered from the Business Services Organisation and COVID-19 statistics from Gov.uk. All data was analysed on Microsoft Office Excel® and IBM® SPSS® Statistics 25. Overall response rate was 46%. Most pharmacists (82%) failed to address prescriber non-compliance with guidelines and antimicrobial dosing errors (59%). The most common in-dication for antibiotics was upper respiratory tract infections (URTIs). Overprescribing of anti-biotics was perceived as the leading cause of AMR, therefore 69% of pharmacists indicated in-creased General Practitioner (GP) compliance with guidelines would reduce AMR. Pharmacists’ are in an ideal position to reduce AMR through patient education however, it is demonstrated that pharmacists failed to adequately counsel patients on antibiotic use. All GP practices demonstrated inappropriate antibiotic use, especially for URTIs which suggests antibiotic appropriateness should be reviewed. Many patients avoided contact with GP’s during COVID-19 which may have resulted in reduced antibiotic use. This research established amoxicillin as the most commonly prescribed antibiotic, which is contributing to increased AMR with its broad-spectrum activity and has recognised a decrease in antibiotic prescribing during COVID-19. Based on the results found and a critical review of the literature it is recommended antimicrobial guidelines should be re-viewed and improved, enhanced training should be provided to pharmacists and the antibiotic guardian (AG) campaign should be reenergised.

Although child-centred care is increasingly referred to within the nursing literature, a clear definition of child-centred care and clarity around the concept is yet to be achieved. The objectives of this review were to examine: 1) What constitutes the concept of child-centred care in healthcare? 2) How has the concept of child-centred care developed? 3) What is the applicability of child-centred care and what are its limitations? and 4) How does the concept of child-centred care benefit and inform children’s healthcare? In total, 2984 papers were imported for screening, following removal of duplicates and screening, 21 papers were included in the scoping review.The findings suggest that child-centred care is an emerging, ambiguous, poorly defined concept; no clear consensus exists about what constitutes child-centred care. Although it seems antithetical to argue against child-centred care, little robust evidence was identified that demonstrates the impact of, and benefit from, child-centred care. If child-centred care is to be a sustainable, convincing model to guide practice and compete with other models of care it needs to establish robust evidence of its effectiveness, impact on children and their families as well as the wider impacts on the healthcare system.

Background: Two types of medicinal systems are available in Korea: Western and oriental. These exist as separate services that independently provide medical care to patients. We determined the utility and benefits of compressive and integrated medical services (CIMS) comprising 12 sessions of acupuncture and healing programs over 6 weeks. Methods: In this two-group parallel single-center randomized controlled assessor-blinded trial, 24 participants were assigned to either the experimental (conventional medical treatment plus CIMS, n = 12) or control (conventional medical treatment, n = 13) group. Spinal nerve root block was performed on the compressed spinal nerve root (identified using magnetic resonance imaging) when no improvement was observed after the initial treatment. The experimental group received 12 cycles of acupuncture and manual therapy for 6 weeks; the control group received conventional medical treatment alone. Results: The average age of participants in the experimental and control groups was 70.73 ± 5.95 and 67.33 ± 8.89 years, respectively. There were no significant differences between the groups in terms of age, body mass index, Leeds Assessment of Neuropathic Symptoms and Signs, sex, and current medical history. We found high compliance for both programs (acupuncture and healing). On exclusion of between-group effects, the visual analog scale (VAS) score improved significantly over time (p = 0.045). Further, comparison of the groups after excluding the effects of visits revealed significantly lower VAS scores in the experimental group than in the control group (p = 0.000). Conclusions: Patients with degenerative lumbar spinal stenosis who mainly complain of radiating pain in the lower leg may benefit from CIMS after spinal nerve root block for ≤3 months after treatment. Our study findings suggest that this treatment improves spinal function and Oswestry Disability Index score. However, CIMS did not improve QoL.

Multi-cancer early detection (MCED) tests are being developed, but little is known about patient receptivity to their use for cancer screening. The current study assessed patient interest in such testing. Our team conducted a prospective, observational study among primary care patients in a large, urban health system. They were asked to complete a telephone survey that briefly described a new blood test in development to identify multiple types of cancer, but was not currently recommended or covered by insurance. The survey included items to assess respondent background characteristics, perceptions about MCED testing, and interest in having such an MCED test. We also used multivariable analyses to identify factors associated with patient interest in test use. In 2023, we surveyed 159 (32%) of 500 identified patients. Among respondents, 125 (79%) reported a high level of interest in having an MCED test. Interest was not associated with personal background characteristics, but was positively associated with the following expectations: testing would be recommended for cancer screening, be convenient, and be effective in finding early-stage disease (OR=11.70, 95% CI: 4.02, 34.04, p < 0.001). Research is needed to assess patient interest and actual uptake when detailed information on testing is presented in routine care.

Objectives This article focuses on exploring the evolution of Palliative Care in Portugal. Ten years after the approval of its Basic Law, the aim was to investigate the quality of the path followed and the guidelines that could promote its development. Thus, this study sought to identify a) the goals of the current members of parliament concerning Palliative Care, b) the major priorities that should guide the development of Palliative Care in the coming decade, c) the facilitating or hindering factors to accelerating the process, and d) to propose consensually agreed measures for an integral development of Palliative Care within the health system. Methods Qualitative data analysis was performed from the reading of literature and interviews conducted via Zoom with several intentionally chosen participants, leading to the creation of a Focus Group. The NVivo® 10 was used for data processing and categorisation. Results Three key themes emerged concerning the current status of palliative care: the policymakers, the technicians, and the society. This first line of structuring is explained by a second set of categories, namely, a) knowledge about palliative care; b) Palliative care organisation from the policymakers’ perspective. In the technicians' domain: a) knowledge about palliative care, b) clinical training, and c) medical specialty. Finally, in society: a) knowledge about palliative care. Significance of the Results Advancing general education, increasing qualitative training for the different health professionals, reformulating laws supporting them, promoting flexibility of the implementation methodologies, and establishing medical specialty, are crucial to achieving the proposed goal.

Access to maternal healthcare services is a challenge in most low and middle-income countries. South Africa is one of the countries striving to improve the accessibility of maternal healthcare services. Although South Africa has put some interventions to improve the accessibility of maternal healthcare services, vulnerable women including women with disabilities are still facing numerous challenges when trying to access maternal healthcare services. The aim of the study was to explore the experiences of women with disabilities in the province of KwaZulu-Natal in South Africa in accessing public maternal healthcare services. Twelve women with disabilities (four with physical impairments, four with hearing impairments and four with visual impairments) were interviewed for this study. Data were transcribed verbatim and analysed utilising the Framework of Assessing Access to Maternal Healthcare Services by Peters et al. 2008. The study found that narrow passages and information in inaccessible formats were a challenge for women with visual impairments. The women with hearing impairments had challenges in communication as most facilities did not have sign language interpreters, negative attitudes of health care workers and being ignored when they asked for help. The women with physical impairments encountered inaccessible buildings, narrow passages, small consultation rooms and equipment which is not adjustable such as beds and scales.

Audit&amp;Feedback (A&amp;F) consists of multidimensional quality improvement activities, but its optimal design is still debated. Our study aims to outline how interventions of the Italian EASY-NET research program were designed, to explore whether desirable characteristics of an "ideal" A&amp;F were adopted. A&amp;F design included description of the working group, targeted clinical behaviors, selected indicators, sources, feedback procedures, corrective actions expected. Information was classified into four topics: nature of the desired action, type of data available, feedback display and delivery. Out of 9 projects, 3/9 aimed at changing a focused clinical behavior, 6/9 were generic; all projects identified clinicians as recipients, 8 explicitly considered managers. It was planned to develop an average of 27 indicators from administrative databases, as needed supplemented by ad hoc data collection. Five projects included outcome measures. Comparators derived from scientific literature or from territorial real-life data. Feedback was scheduled every 12, 6 or 3 months, or upon request, delivered as aggregate data (graphs and tables) via web platforms, e-mail, workshops, and individual meetings. In conclusion, at an early stage the projects were mostly “wide focused”, but improvements in A&amp;F design and delivery have been introduced, and projects, still ongoing, will offer interesting insights on A&amp;F effectiveness.

The study follows the interaction between the individual and the social context regarding the development of adolescents protected in residential houses from the child protection system in Iasi County, Romania. Starting from the evidence that in situations of providing relatively identical material and social resources, the results obtained by these children vary greatly, we examine how the meaning (understood mainly as purpose and mattering) can constitute a developmental resource. Considering theoretical models and previous research, the study aims to describe, through a qualitative approach, how these young people see themselves and the external environment (family and residential care), how they project their future (their purpose and objectives), and how these constructions and perceptions can influence their quality of life and social integration. We conducted three focus groups with 35 adolescents and young people (the ages 13-21) protected in and for different periods in residential houses (period 1-20 years). The results highlighted that a specific meaning is reconfigured as compensatory when affected by a trauma or adverse external event and thus can be a resource for resilience. On the other hand, the research highlighted that only the existence of goals alone is insufficient to generate action, and the unrealistic meanings given to own persons, experiences, and resources can be dangerous.

Disinfection byproducts (DBPs) are formed whenever disinfectant ingredients are in contact with organic matter. Due to widespread increase in production and use of disinfectants and antiseptics, the presence of their components in coastal environments is increasing. However, very limited scientific literature is available in regard to the occurrence of DBPs and related compounds in the coastal zone and particularly in seawater. In this context, the aim of this preliminary compilation is to outline the main up-to-date findings and raise awareness on their increasing occurrence in coastal environments. Sampling and analysis of marine samples in the USA, Spain, China, Taiwan, Malaysia, Korea, Kuwait and Hong-Kong revealed the presence of several categories of DBPs and related compounds in coastal environments, with the highest levels being detected in urban areas, probably related to the nearby wastewater treatment plants. The investigations considered in this preliminary compilation, report the detection of DBPs and related compounds as well as the formation of toxic brominated and iodinated DBPs in high levels due to chlorination of wastewater, especially after use of seawater for flushing in toilets. New DBP groups have also been detected, namely halogenated phenolic DBPs and halopyrroles.

Fragile X Syndrome (FXS) is a pervasive developmental disorder and the most common monogenic cause of autism spectrum disorder (ASD). Female heterozygous (HET) carriers play a major role in the transmission of the pathology and present several FXS- and ASD-like behavioral alterations. Despite their clear genetic origins, FXS symptoms are known to be modulated by environmental factors, e.g., the exposure to chronic stress, especially during critical life periods, such as pregnancy. Pregnancy, together with pups’ care, constitutes maternal experience, i.e., another powerful environmental factor affecting several neurobehavioral functions in females. Here we investigated the impact of maternal experience on the long-term effects of stress in Fmr1-HET female mice. Our findings demonstrated that the behavioral abnormalities of HET females, i.e., hyperactivity and memory deficits, were unaffected by stress or maternal experience. In contrast, stress, independently of maternal experience, induced the appearance of cognitive deficits in WT mice. Maternal experience increased anxiety levels in all mice and enhanced their corticosterone levels, concomitantly promoting the effects of stress on social communication and adrenal glands. Our results advance our understanding of the environmental modulation of the behavioral alterations observed in FXS mice and highlight the long-term impact of maternal experience and its interactions with chronic stress.

The ever deepening population aging has brought opportunities and challenges to the continued expansion of tourism consumption in China. In this article, the impact of population aging on household tourism consumption was studied from both theoretical and empirical aspects. First, the micro mechanisms of the impact of population aging on household tourism consumption were analyzed, which include economic condition mechanism, intergenerational care mechanism, health status mechanism and Internet use mechanism. Subsequently, the impact of population aging on household tourism consumption and its impact mechanisms were tested, and the heterogeneity analysis was conducted, by using the data of China Family Panel Studies (CFPS) from 2014, 2016 and 2018. The main conclusions of the article are as follows: (1) Population aging has a significant negative impact on household tourism consumption, and a series of robustness test results such as endogenous treatment support this finding. (2) The results of the impact mechanism test show that population aging has a negative mediating effect on household tourism consumption by reducing household economic conditions. The moderating effect of intergenerational care on the effect of population aging on household tourism consumption is insignificant. Health status of the elderly and Internet use have a significant positive moderating effect on the impact of population aging on household tourism consumption. (3) The results of the heterogeneity analysis show that the negative impact of population aging on household tourism consumption in urban areas is greater than that in rural areas, and the negative impact of population aging on household tourism consumption of families with the old-old elderly is greater than that of falimies with the young-old elderly. The conclusions of this article provide important references for activating tourism consumption in China in the context of population aging.

Although, central venous pressure (CVP) is among the most frequent estimated hemodynamic parameters in the critically ill setting, extremely little is known on how intensive care unit (ICU) nurses use this index in their decision-making process. The purpose of the study was to develop a new questionnaire for accessing how ICU nurses use CVP measurements to address patients’ he-modynamics investigating its validity and reliability. A cross-sectional study was conducted among 120 ICU nurses from four ICUs of Greece. Based on a comprehensive literature review and the evaluation of a five-experts panel a new questionnaire, named “CVP-Score”, was created having 8 items. The construct validity and the reliability of the questionnaire were examined. The half of the study participants’ (51.7%) was working at a specialized ICU, and they had a mean [±Standard Deviation (SD)] ICU experience of 13(±7.1) years. The estimated construct validity of the new-developed tool was acceptable, while the internal consistency reliability as measured by Cronbach alpha was excellent (0.901). CVP Score had acceptable test-retest reliability (r=0.996, p<0.001) and split-half reliability (0.855). CVP Score is a valid and reliable instrument for measuring how critical care nurses use CVP measurements in their decision-making process.

Most head and neck cancers are diagnosed in advanced stages, when the curative interventions are no longer possible. The assessment and the multidisciplinary therapeutic approach of the locally advanced cases are difficult since the onset of the disease becomes a significant challenge for the whole attending team (including both the patient and his family) because they have to deal with to an extensive symptomatology (abundant secretions, refractory pain, mutilations predominantly in the cephalic area), with the cure of stomas (tracheostomy, gastrostomy) and with various post-therapeutic sequelae. The present paper reflects the impact of late diagnosis, the complexity of the multimodal specific oncological treatment (chemotherapy, radiotherapy, immunotherapy, pal-liative and terminal treatment), the adaptation of medical care to the psycho-emotional structure, having as an example the case of 54-year old patient (with his consent) diagnosed with pharyn-golaryngeal neoplasm who presented himself to “St. Luca” Chronic Disease Hospital, the Oncol-ogy-Palliative Care Department, in September 2021. In patients with locally advanced head and neck cancers, besides the specifically oncological therapeutic decisions, the empathic-emotional connection between the medical team with the patient and his family plays a key role in the ther-apeutic conduct.

Interprofessional collaboration between general practitioners (GPs) and community pharmacists (CPs) is central to implement antimicrobial stewardship (AMS) programs in primary care. This study aimed to design a GP-pharmacist antimicrobial stewardship (GPPAS) model in Australian primary care. A seven-component exploratory study was conducted since 2017 to 2021 to inform a GPPAS model. We generated both secondary and primary evidence through a systematic review, a scoping review, a rapid review, nationwide surveys of Australian GPs and CPs including qualitative components and a pilot study of a GPPAS model. All study evidence was synthesised, reviewed, merged and triangulated to design a prototype GPPAS model using a Systems Engineering Initiative for Patient Safety theoretical framework. Secondary evidence informed effective GPPAS interventions, and primary evidence captured interprofessional issues, challenges and future needs to implement GPPAS interventions by GPs and CPs. A GPPAS model framework involving GP-pharmacist team-based five GPPAS sub-models were successfully designed to foster AMS education, antimicrobial audits, diagnostic stewardship, delayed prescribing, and routine review of antimicrobial prescription by improved GP-CP collaboration. A GPPAS model could be used as a guide to collaboratively optimise antimicrobial use by GPs and CPs. Implementation studies on GPPAS model and sub-models are required to integrate GPPAS model into GP-pharmacist interprofessional care models in Australia.

(1) Background: Ventilator-associated pneumonia (VAP) causes high mortality among patients with respiratory disease and imposes major burdens on healthcare infrastructure. Models that use electronic health record data to predict the onset of VAP may spur earlier treatment and improve patient outcomes. We developed and studied the performance of interpretable machine learning (ML) models that predict the onset of VAP from electronic health records (EHRs); (2) Methods: We trained Logistic Regression (LR), full feature Explainable Boosting Machine (fEBM), and eXtreme Gradient Boosting (XGBoost) ML models on data from the MIMIC- III (v1.3) database. Model performance was measured by area under the receiver operating characteristic curves (AUCs). We trained a minimal-feature EBM model (mEBM) with features derived from white blood cell (WBC) counts, duration of ventilation, and Glasgow Coma Scale (GCS). Finally, model robustness was evaluated on randomly sparsified EHR datasets; (3) Results: The fEBM model outperformed the XGBoost and LR models at 24 hours post-intubation. The mEBM model maintained an AUC of 0.893. The fEBM model performance remained robust on sparsified datasets; (4) Conclusions: Our novel interpretable ML algorithm reliably predicts the onset of VAP in intubated patients. Integration of this EBM-based model into clinical practice may enable clinicians to better anticipate and prevent VAP.

Background: The COVID-19 pandemic has changed the way dentistry has been practiced world over , this study sought to assess the impact of the COVID-19 pandemic on the patterns of attendance for dental treatment in a large hospital in Kuwait compare them to data from the year prior to the pandemic Methods: A total of 176,690 appointment records of 34,250 patients presenting to the AlJahra specialist hospital, Kuwait for dental treatment from April 2019 to March 2021 were analyzed. Types of procedures and the departments to which they presented were analyzed and the patterns of attendance before and during the pandemic were compared; Results: While there was a significant reduction in the number of orthodontic, endodontic and periodontal procedures there was no impact on oral surgery, restorative procedures or pediatric dentistry; Conclusions: There has been a return in the numbers of patients availing dental treatment, however, there has been a definite shift in the use of certain dental procedures .

Clinicians are key in reclaiming the medical arts ceded to clinically irrelevant technology and thereby aligning patient with fast-changing biological realities. Narrowing the chasm between virtual and real perceptions of health hazards requires: 1) becoming acutely aware of the habitat loss aggravating the pervasive dissemination of chemicals via conventional food, air, and consumer products and the proliferation of non-ionizing radiation; and 2) making strategic use of slow, system 2 thinking so as to respond wisely to the rampant epidemics of chronic low-dose toxicity disregarded or misdiagnosed for half a century. To respond adaptively, take a moment during each patient encounter to add chronic ambient poisoning to the differential diagnosis and investigate subtle symptoms and signs of irritation in vulnerable organ systems. Enacting adaptive response across our profession could ease the suffering of millions, help avert the sixth extinction, and contribute to continuation of evolved life as we know it.

Background: The Sequential Organ Failure Assessment (SOFA) is a scoring system used for the evaluation of disease severity and prognosis of critically ill patients. The impedance ratio (Imp-R) is a novel mortality predictor. Aims: This study aimed to evaluate the combination of SOFA + Imp-R in the prediction of mortality in critically ill patients admitted to the emergency department (ED). Methods: A retrospective cohort study was performed in adult patients with acute illness admitted to the ED of a tertiary-care referral center. Baseline SOFA score and bioelectrical impedance analysis to obtain the Imp-R were performed within the first 24 hours after admission to the ED. A Cox regression analysis was performed to evaluate mortality risk of initial SOFA score plus Imp-R. Harrell's C-statistic and decision curve analyses (DCA) were performed. Results: Out of 325 patients, 240 were included for analysis. Overall mortality was 31.3%. Only 21.3% of non-surviving patients died after hospital discharge, and 78.4% died during hospital stay. Of the latter, 40.6% died in the ED. SOFA and Imp-R values were higher in non-survivors and were significantly associated with mortality in all models. The combination of SOFA + Imp-R significantly predicted 30-day mortality, in-hospital mortality, and ED mortality with area under the curve (AUC) of 0.80 (95% CI: 74-0.86), 0.79 (95% CI: 0.74-0.86) and 0.75 (95% CI: 0.66-0.84) respectively. The DCA showed that combining SOFA + Imp-R improved the prediction of mortality through the lower risk thresholds. Conclusion: The addition of Imp-R to baseline SOFA score at admission to the ED improves mortality prediction in severely acutely ill patients admitted to the ED.

The aim was to evaluate levels of compassion fatigue in nursing professionals working in complex care units of a Brazilian university hospital. A cross-sectional, descriptive, and correlational study was carried out with nursing workers from complex care units of a University Hospital. Data were collected in the second half of 2019, in the pre-pandemic period of COVID-19, using the Brazilian version of the Professional Quality of Life Scale (ProQoL-BR). A total of 146 individuals partici-pated, including 41 (28.1%) nurses, 92 (63.0%) nursing technicians and 13 (8.9%) nursing assis-tants. It was observed that 26.1% presented high level of compassion satisfaction. For 17.5% there was level of burnout and 49.7%, medium level of burnout; and 22.0% with high and 46.1% with medium level of secondary traumatic stress. Twenty-eight (19.2%) professionals had compassion fatigue, of which 16 (57.1%) were nursing technicians. There is a high percentage of professionals with medium and high rates of burnout and secondary traumatic stress, a fact that is reinforced by the presence of compassion fatigue in almost one fifth of the studied individuals. These results highlights how much the health of these workers can be affected by living with traumatic patient experiences.

Decision-making using evidence-based practice (EBP) is generally universally accepted by nurses. Such acceptance may affect the personnel’s behaviour towards patients, which is also demonstrated by taking into consideration the patient’s preferences, including the patient’s spiritual needs, in the care plan. The provision of such care requires the development of an attitude of approval and an adequate level of communicative competence, which will enable the actual implementation of the EBP. The purpose of our study was to assess the perception of spirituality and the nurse’s role in providing spiritual care, as well as the perception of the significance of communication skills in the approval of EBP in professional practice. A multi-centre cross-section study was conducted on a population of 1176 participants (459 undergraduate (Bachelor programme, BP) and 717 postgraduate students (Master programme, MP)) from 10 medical universities in Poland. Three tools were used in the study to evaluate the participants’ approach: Evidence-Based Practice Competence Questionnaire (EBP-COQ), The Spirituality and Spiritual Care Rating Scale (SSCRS), and Communication Skills Attitude Scale (CSAS). Structural equation modelling was used for the analysis. An analysis of structural equations revealed the presence of positive relationships of the attitude to spiritual care and the role of communicative competences with the approach to EBP regardless of the cohort. A significant difference was found related to the influence of age on the attitude toward learning communicative competences. The approval in this respect was observed to decrease with age in the MP group. Increasing approval of EBP requires strengthening the approach to activity-centred spiritual care, with the simultaneous development of a positive attitude towards learning communicative competences. The model reveals the need to integrate a humanistic approach with EBP, which can be achieved by planning different interventions in different groups of recipients: nurses, academic teachers and students.

Aim: The aim of this study was to estimate the number of nurses who independently care for pa-tients with severe respiratory failure receiving mechanical ventilation (MV) or veno-venous ex-tracorporeal membrane oxygenation (VV-ECMO). Additionally, the study analyzed the actual role of nurses in the treatment of patients with MV and VV-ECMO. Methods: We conducted a cross-sectional study using postal surveys. The study included 725 Japanese intensive care units (ICUs). Descriptive statistics were conducted. Results: Among the 725 ICUs, we obtained 302 re-sponses (41.7%) and analyzed 282 responses. The median number of nurses per bed was 3.25. The median proportion of nurses who independently cared for patients with MV was 60% [IQR: 42.3-77.3]. The median proportion of nurses who independently cared for patients with VV-ECMO was 46.9 (35.7-63.3%) in the ICU experiencing VV-ECMO use. Concerning task-sharing, 33.8% of ICUs and nurses did not facilitate weaning from MV. Nurses always ti-trated sedatives in 44.5% of ICUs. Conclusion: Nurse staffing might be inadequate in all ICUs, es-pecially for severe respiratory failure. The proportion of competent nurses for caring for severe respiratory failure in ICUs should be considered when determining the work force of nurses.

Background Although aminoglycosides are often used as treatment for Gram-Negative infections, optimal dosing regimens remains unclear, especially in ICU patients. This is due to a large between- and within-subject variability in the aminoglycosides’ pharmacokinetics in this population. Objective The review provides comprehensive data on the pharmacokinetics of aminoglycosides in patients hospitalized in ICU by summarizing all published PopPK models in ICU patients for amikacin, gentamicin, and tobramycin. The objective was to determine the presence of a consensus on the structural model used, significant covariates included, and therapeutic targets considered during dosing regimen simulations. Methods A literature search was conducted from the Medline/PubMed database, using the terms: ‘amikacin’, ’gentamicin’, ’tobramycin’, ‘pharmacokinetic(s)’, nonlinear mixed effect’, population’, ‘intensive care’ and ‘critically ill’. Results Nineteen articles were retained where amikacin, gentamicin and tobramycin pharmacokinetics were described in six, eleven and five models, respectively. Two-compartment model best described amikacin and tobramycin pharmacokinetics, whereas one-compartment model majorly described gentamicin pharmacokinetics. The most recurrent significant covariates were renal clearance and bodyweight. Across all aminoglycosides, mean interindividual variability in clearance and volume of distribution were 41.6% and 22.0%, respectively. A common consensus for an optimal dosing regimen for each aminoglycoside was not reached. Conclusion This review showed models developed for amikacin, from 2015 until now and for gentamicin and tobramycin from the past decades. Despite growing challenges of external evaluation, the latter should be more considered during model development. Further research including new covariates, additional simulated dosing regimens and external validation should be considered to better understand aminoglycosides pharmacokinetics in ICU patients.

Bacground, the increasing number of elderly is a new challenge for health care systems around the world. The phenomenon of the complex health problems experienced by the elderly encourages families to bring the elderly to a nursing home. The purpose of this study was to describe the condition of the elderly living in nursing homes and their care needs. Methodology, this research design is a literature review, article search using 5 databases, namely Scopus, ProQuest, Pubmed, CINAHL and Scient Direct. Articles reviewed from 2019 to 2021. Protocol and evaluation of literature review using the PRISMA checklist, and the assessment guide using the Joanna Briggs Institute Guideline. Results, the health conditions of the elderly who live in the orphanage are mostly aged 60 years and over, physically experiencing disturbances in their daily activities and dependence. Psychologically experiencing anxiety, depression, loneliness and even mental disorders and socially need family support. The care needs of the elderly in nursing homes include services by competent and culturally sensitive staff and nurses, safe and comfortable nursing home environmental services, privacy needs and social interactions, spiritual needs services, social guidance services, and skills guidance services. Conclusion, based on the literature review, it can be seen that nursing services should be provided in a humanistic and holistic manner, the elderly are clients who have both bio-psycho-socio-cultural and spiritual needs. So that nursing services are aimed at meeting the needs of the elderly in a comprehensive manner.

Direct and indirect anthropogenic factors play a massive role in driving wildlife species towards extinction. Longitudinal retrospective studies identify key ‘factors’ responsible for the decline in numbers of wildlife, however, lack the reasoning behind the events leading to mortality. The overarching aim of this study was to categorize these ‘factors’ into different stressor categories faced by reptiles to understand its impact on an individual, and to compare how each stressor category influences the survival of an individual. The results from this study indicated that almost half of the number of reptiles being hospitalized were due to exposure to preliminary stressors such as lawn mowing incidents and pet attack. Primary and secondary admissions were fairly equal in number, however the mortality rate for secondary admissions was drastically high (~80%). The discussion integrates species’ ecology and stress physiology which can prove to have multi-faceted benefits across the fields of ecology and animal welfare. Ecologists can use the results from this study to comprehend species’ activity patterns to better plan reptilian conservation programs, whereas, for wildlife clinicians and rehabilitators, assignment of stressor categories could be a beneficial tool for bolstering the welfare monitoring program for small native reptiles in clinical settings.

Objectives: A wealth of literature has established risk factors for social isolation among older people, however much of this research has focused on community-dwelling populations. Relatively little is known about how risk of social isolation is experienced among those living in long-term care (LTC) homes. We conducted a scoping review to identify possible risk factors for social isolation among older adults living in LTC homes. Methods: A systematic search of five online databases retrieved 1535 unique articles. Eight studies met the inclusion criteria. Results: Thematic analyses revealed that possible risk factors exist at three levels: individual (e.g., communication barriers), systems (e.g., location of LTC facility), and structural factors (e.g., discrimination). Discussion: Our review identified several risk factors for social isolation that have been previously documented in literature, in addition to several risks that may be unique to those living in LTC homes. Results highlight several scholarly and practical implications.

Loneliness is a frequent negative feeling among older people. A programme aimed at alleviating loneliness among older people by promoting social capital, i.e. social support and participation, was conducted in primary health care centres in Spain. We aimed to explore participants’ experiences of loneliness and social participation before the programme, perceived programme effects and contextual influences. A descriptive-interpretative qualitative design was used. 41 persons were included comprising older people, health and social care professionals, and volunteers. Data were collected through three focus groups, 36 semi-structured interviews and participant-observation of the intervention. A thematic content analysis was applied. Older persons with diverse profiles of loneliness and participation decreased their loneliness, increased their knowledge and participation in local community assets, and developed companionship, a sense of belonging, peer support and friendship. Their mental wellbeing increased and participants could deal better with health or family problems. An empowerment process was observed. However, loneliness persisted among some widowed participants and health and social vulnerabilities hampered some impacts. Conflicts and exclusion were occasional unintended effects. The promotion of social capital in ageing to alleviate loneliness involves complex processes interrelated with health and socio-economic factors. Future programmes should be adapted to local contexts and participants’ characteristics.

Although it may seem paradoxical, primary care and mental health professionals develop prejudices and discriminatory attitudes towards people with mental health problems in a very similar way to the rest of the population. The main objective of this project was to design, implement and evaluate two awareness interventions respectively tailored to reduce stigma and discrimination beliefs and attitudes towards persons with a mental health diagnosis among primary care (PC) and mental health (MH) professionals. These interventions were developed by Obertament, the Catalan alliance against stigma and discrimination in mental health. The TLC3 (Targeted, Local, Credible, Continuous Contact) methodology was adapted to the Catalan PC and MH professional contexts. Activists with lived experience of mental health diagnosis carried out awareness-raising interventions in PC and MH health centres. The efficacy of these interventions was evaluated using two prospective double-blind cluster-wait-list-randomized-controlled trial experimental designs. Stigmatizing beliefs and behaviours were measured with the Opening Minds Stigma Scale for Health Care Providers in primary care centres and with the Beliefs and Attitudes towards Mental Health Service users’ rights in mental health centres. Positive reductions in both PC and MH professionals’ stigmatising beliefs and attitudes were found in the 1-month follow-up, although a ‘rebound effect’ at the 3-month follow up was also detected. This emphasizes the importance of the continuity of the presence of anti-stigma activities and messages. Attrition rates where high, which can hamper the reliability of the results. Further follow-up studies should enquiry effects of long-term interventions aimed at reducing stigmatising beliefs and attitudes among primary care and mental health professionals.

The cluster randomized trial ARena (Sustainable reduction of antibiotic-induced antimicrobial resistance, 2017-2020) promoted the appropriate use of antibiotics for acute non-complicated infections in primary care networks (PCNs) in Germany. A process evaluation aimed to provide insights into determinants of practice and explored factors associated with antibiotic prescribing patterns. In a nested mixed-methods approach, a three-waves survey used study-specific questionnaires for participating physicians and medical assistants to assess potential impacts and uptake of the complex intervention program. Stakeholders received a one-time online questionnaire to reflect on network-related aspects. Semi-structured, open-ended interviews with a purposive sample of physicians, medical assistants and stakeholders explored aspects regarding the acceptance of the program components for daily practice and the perceived sustainability of intervention component effects. The intervention components were perceived to be smoothly integrable into practice routines. The highest uptake was reported for the educational components: feedback reports, background information, e-learning modules, and disease specific quality circles. Participation in PCNs was seen as motivational factor for guideline-oriented patient care and the adoption of new routines Future approaches to fostering appropriate use of antibiotics by targeting health literacy competencies and clinician’s therapy decisions should combine evidence-based information sources, audit and feedback reports and QCs.

In this retrospective report we present five cases of critically ill pregnant or newly delivered women positive for Covid-19 admitted to our obstetrical departments at Karolinska University Hospital. They compose 6% of eighty-three pregnant women that tested positive for SARS-CoV-2 during the period March 25 to May 4, 2020. Three patients were at the time of admission in gestational week between 21+4 to 22+5 and treated during their antenatal period, meanwhile the other two were admitted within 1 week postpartum. All of them were in a need of intensive care, one was treated with high flow oxygen therapy, the other four with invasive mechanical ventilation (three with endotracheal intubation and one with extra corporeal membrane oxygenation). Age above thirty, overweight and gestational diabetes are notable factors in the cases presented. At the time of admission, they all presented with symptoms as fever, cough and dyspnea. Chest imaging with computer tomography scan was performed in each case and demonstrated multifocal pneumonic infiltrates in all of them but no pulmonary embolism was confirmed in any. Neither did the echocardiogram indicates any cardiomyopathy. Four of the patients have been discharged from the hospital, with an average of 20 hospital days. One antenatal pregnant woman needed prolonged ECMO therapy, in gestational week 27+3 she went into cardiac arrest, resulting in an urgent c-section on maternal indication. At the time of writing she is still hospitalized. In coherence with other published reports our cases indicate that critically ill pregnant women infected by SARS-Cov-2 may develop severe respiratory distress syndrome requiring prolonged intensive care. The material is limited for conclusions to be taken, more detailed information on symptoms, treatment, and outcomes for pregnant and postpartum women managed in intensive care is therefore needed.

Background: The COVID-19 among humans is spreading heavily and is largely impacting the mental health of the general population, students, and health care workers worldwide. Hence, this review aims to summarize the literatures addressing the impact of the COVID-19 pandemic on the mental health of the general population, students, and health care workers. Methods: Published articles concerning mental health of the general population, students, and health care workers related to the COVID-19 outbreak have been considered and reviewed. Results and Discussion: Mental health symptoms of stress, anxiety, and depression are common psychological reactions to the COVID-19 pandemic in the general population, students, and health care workers. This collectively influences daily behavior, economy, prevention strategies and decision making from policy makers and health organizations, weakening the strategies of COVID-19 control leading to more morbidity and mental health needs at the global level. Conclusion: There is a need for more evidence-based research from other affected countries, particularly in vulnerable populations such as children and adolescents, people of lower socioeconomic status, and those residing in rural areas, so that valid strategies can be developed and COVID-19 and outbreaks of similar types in the near future can be prevented.

The challenge regarding COVID-19 is to prevent complications and fatal evolution. Azithromycin (AZM) and hydroxychloroquine (HCQ) have proven their antiviral effect in vitro. We aimed to assess the efficacy and safety of AZM alone or combined to HCQ, prescribed, at an early stage, in patients with Covid-19, in a primary care setting. Eighty-eight patients received either no or a symptomatic treatment (NST) (n=34) or AZM alone (n=34) or AZM+HCQ (n=20). The efficacy end point was the time to clinical recovery and the safety end point was the occurrence of cardiovascular events. The mean (SD) times to achieve clinical recovery were respectively 25.8 days (11.1), 12.9 days (13.4) and 9.2 days (9.3), showing a statistically significant difference between NST and AZM alone (p<0.0001) or AZM+HCQ (p<0.0001). To improve the evidence level, a case-control analysis was performed on a sample of 57 patients (19/group) matched for age, sex and BMI. The statistical difference between NST and AZM was confirmed (p=0.0149) as well as the difference with AZM+HCQ (p=0.0002). No cardiac toxicity was recorded in any patient. No statistical difference was shown between AZM and AZM+HCQ groups, although the dual therapy tended to be more effective in patients over 50 years, based on an analysis using the cox model. In conclusion, AZM and AZM+HCQ favourably impacted the course of the disease. We need trials, ideally prospective/double blind, to show if a statistical difference can be evidenced with a broader group, and clarify the indications of each treatment depending on initial clinical presentation.

Dental services are significantly impacted by the COVID-19 pandemic. Almost all dental procedures carry a high infection risk for providers and patients due to spread of aerosols. As a consequence, national public health agencies, and dental professional associations have issued guidelines for enhanced infection control, personal protection equipment and limiting care to urgent or emergency services. However, there is no dental service concept for disaster preparedness or response that might be applied. Similarly, pathways to care provision in a post-pandemic future are missing. We propose Safe Aerosol-free, Emergent Dentistry (SAFE Dentistry) as one approach to dental services during and emerging from pandemics. The concept’s starting point is the identification of the most common patient needs. The next step is to replace common treatments relating to the most common needs with alternative interventions with less infection risk because they do not generate aerosols. SAFE Dentistry is innovative, safe, and responds to the requirements of a pandemic and post-pandemic emergence where the risk of disease transmission remains high. SAFE Dentistry thereby ensures continuity of dental services while protecting providers and patients from infectious pathogens. Moreover, SAFE Dentistry allows dental service providers to remain operational and generate income even under pandemic conditions. Implementation and policy options for SAFE Dentistry include universal availability without co-payments by patients and a uniform bundled payment scheme for providers to simplify budgeting, reimbursement and to provide easier administration during a pandemic. Adaptations and adjustments of the concept are possible and encouraged, as long as the principle of avoiding aerosol-generation is maintained.

Nonpharmacological therapeutic interventions in elderly may lead to the reduction of cognitive and depressive symptoms. The aim of the study was to evaluate changes in cognitive functions and mood er or not. in older adults participating in therapy, conducted in the community day-care center (CD-CC). 46 elderly adults (21 M, 25 W) (SG) were examined. The control group (CG) included 45 adults (12 M, 33 W), who participated in the activities of the University of the Third Age (U3A). The following measuring tools were used: Mini-Mental State Examination (MMSE), Clock-Drawing Test (CDT), Verbal Fluency Test (VFT), Digit Span Test (DST), Stroop Color and Word Test (SCWT), Beck's Depression Inventory (BDI), and Hospital Anxiety and Depression Scale (HADS). The intervention consisted of CD-CC 6-month complex therapy. In the SG, compared to the CG, the scores on the: MMSE, CDT, VFT, DST, and SCWT were significantly lower (p<0,05), and BDI was significantly higher (p<0,05). After intervention, the SG and the CG, did not show substantial differences in their scores on the: MMSE, CDT, and BDI. In the SG, a significant improvement (p<0,05) was reported on the: VFT, BDI, and HADS scores. The CD-CC complex therapy can be helpful for the cognitive and emotional elderly functioning.

Among humans, simply looking at infants can activate affiliative and nurturant behaviors. However, it remains unknown whether mere exposure to infants also activates other aspects of the caregiving motivational system, such as generalized defensiveness in the absence of immediate threats. Here, we demonstrate that simply viewing faces of infants (especially from the ingroup) may heighten vigilance against social threats and support for institutions that purportedly maintain security. Across two studies, participants viewed and rated one among several image types (between-subjects design): infants, adult males, adult females, and puppies in Study 1, and infants of varying racial/ethnic groups (including one's ingroup) and puppies in Study 2. Following exposure to one of these image types, participants completed measures of intergroup bias from a range of outgroups that differed in perceived threat, belief in a dangerous world, right-wing authoritarianism and social-political conservatism (relative to liberalism). In Study 1 (United States), stronger affiliative reactions to images of infants (but not adults or puppies) predicted stronger perceptions of a dangerous world, endorsement of right-wing authoritarianism, and support for social-political conservatism (relative to liberalism). Study 2 (Italy) revealed that exposure to images of ingroup infants (compared to outgroup infants) increased intergroup bias against outgroups that are characterized as threatening (immigrants and Arabs) and increased conservatism. These findings suggest a predisposed preparedness for social vigilance in the mere suggested presence of infants e.g., viewing images, even in the absence of salient external threats.

This retrospective study evaluates the effect of a telemedicine program developed in the central Catalan region in lowering the environmental footprint by reducing the emission of atmospheric pollutants thanks to a reduction in the number of hospital visits involving journeys by road. Between January 2018 and June 2019 a total of 12,322 referrals were made to telemedicine services in the primary care centers, avoiding a total of 9,034 face-to-face visits. In total, the distance saved was 192,682 km, with a total travel time savings of 3,779 hours and a total fuel reduction of 11,754 liters with an associated cost of €15,664. This represents an average reduction of 3,248.3 g of carbon dioxide, 4.05 g of carbon monoxide, 4.86 g of nitric oxide and 3.2 g of sulphur dioxide. This study confirms that telemedicine reduces the environmental impact of atmospheric pollutants emitted by vehicles, reducing the number of journeys made for face-to-face visits and can contribute to environmental sustainability.

Background: Level of perceived competence as a basic psychological need could trigger achievement of diabetes self-management goals. Due to lack of a specific data collection tool to measure level of self-competence among Persian speaking patients with diabetes this study was conducted for cross-cultural adaptation and psychometric assessment of the Persian version of Perceived Competence Scale for Diabetes (PCSD-P). Methods: Standard translation/back-translation procedure was carried out to prepare a preliminary draft of the PCSD-P. Content and face validity of the early draft were checked by an expert panel including 15 scholars in the field of health education and promotion as well as nursing education with experience of working and research on diabetes. The final drafted questionnaire was completed by 177 randomly selected patients with type 2 diabetes. Based on the collected data structural validity of the contrived version was appraised using exploratory and confirmatory factor analysis (EFA, CFA). Cronbach's alpha and Intraclass Correlation coefficients (ICC) were used to check the scale’s reliability and internal consistency. ; (3) Results: The estimated measures of Content Validity Index (CVI= 0.95) and Content Validity Ratio (CVR= 0.8) were in the range of acceptable recommended limits. The EFA analysis results demonstrated a single factor solution according to the items’ loadings for the component. The model fit indices i.e. RMSEA= 0.000, CFI=1, TLI=1, GFI= 0.998, NFI= 0.999 RFI= 0.995 confirmed consistency of the hypothesized one-factor solution. Values of the internal consistency and reliability coefficients were also in the vicinity of acceptable range (α= 0.892, ICC=0. 886, P= 0.001). Conclusions: The study findings revealed good internal validity and applicability of the PCSD-P to measure degree of self-competence among Persian speaking type 2 diabetes patients to manage the chronic disease. Due to unrepresentativeness of the study sample future cross-cultural test of PCSD-P on diverse and broader Persian speaking populations is recommended.

Pharmacists and pharmacies are highly visible and accessible to the public and have long been regarded as a source for immunization services in the United States. As international travel continues to increase and grow in popularity in this country, there is a pressing need for expanded access to preventative health services including routine and travel vaccinations and medications for prophylaxis or self-treatment of conditions that may be acquired overseas. In the United States, the scope of pharmacy practice continues to expand and incorporate these preventable health services to varying degrees on a state-by-state level. As a result, pharmacists can help to increase access to and awareness of the need for these services to insure that patients remain healthy while traveling abroad and that they do not acquire a travel-related disease while on their trip. For those pharmacists interested in starting a travel health service, considerations should be undertaken that ensures that they have the necessary training, education, and skill set in order to provide this specialty level of care and that their practice setting is optimally designed to facilitate this service. Outcomes from studies that have evaluated pharmacy-based travel health services are positive, which further supports the role of the pharmacist in this setting. Therefore, the purpose of this paper is to highlight United States pharmacy laws and regulations, pharmacist training, travel clinic considerations, and patient care outcomes from pharmacy-based travel health services.

Malaysia became the centre of international attention when it democratically removed a semi-authoritarian government of 62 years during its 14th general election this year. This electoral success has provided geriatric medicine in Malaysia with the unexpected ageing icon in the oldest prime minister in the world. Political change has led to a wave of optimism for the expansion of geriatric services in Malaysia, which has met with numerous challenges in the last two decades. The number of geriatrics specialists and services had already begun expanding under the previous government. However, existing geriatricians will need to reassess the landscape of delivery and access of care in our rapidly growing ageing population and develop new strategies to truly expand their services. In addition to unrelenting efforts in the recruitment and training of future geriatricians, the steady expansion of the geriatric workforce should take into account the inclusion of geriatric medicine in the undergraduate training curricula of all healthcare professionals. Expansion of geriatric services will also be a cost-effective strategy to reduce the growing national healthcare budget incurred by the growing needs of an ageing population.

The research is carried out to assess factor affecting the health condition of the elderly people in the slum areas in Sylhet City. This research was quantitative type. In Quantitative approach, primary data were collected and used from the randomly selected elderly people in the Sylhet City slum areas. The secondary data were collected from many articles, documents, newspaper, magazine etc. By analyzing the survey data, it is illustrated that the slum dwellers are deprived from the basic needs. Meanwhile, elderly people can‟t fulfill their medical treatment due to their financial condition because of their work incompatibility. This study identifies the factor affecting health condition such as financial condition, lack of knowledge about proper medical facilities, communication gap between the authority and patient, unemployment, and so on. These factors also affect their health situation. Many diseases like asthma, heart disease are occurred. This study also mentions about the livelihood of slum people are so poor in condition. Due to financial condition, aged people can‟t take their proper treatment and their family member can‟t afford it. This study also understands that the people from slum areas are getting concerned about their medical care. They are easily going to the hospital and take their service because of low pricing. On the other hand, people are meanwhile stopped their treatment of financial situation. This study finds the health situation of elderly people at slum areas in metropolitan city and their consciousness.

Background: Ventilator-associated pneumonia (VAP) is among the most common healthcare-associated infections in Pediatric Intensive Care Units (PICUs). Because of the lack of a gold-standard diagnostic test, early diagnosis of VAP is challenging. We investigated whether bronchial biomarkers interleukin-4 (IL-4), plasminogen activator inhibitor-1 (PAI-1) and soluble receptor for advanced glycation end products (RAGE) could contribute in early VAP diagnosis through their fluctuation in time in critically ill pediatric patients. Methods: Bronchial secretions were collected from PICU patients with VAP on days 1 and 6. PAI-1, RAGE and IL-4 levels were measured by ELISA. Protein concentrations between high and low VAP suspicion patients were compared using unpaired Student’s t or Mann–Whitney U tests. Results: Twenty PICU patients, with median age 7.75yrs (range 0.5-15.3), mechanically ventilated for ≥48hrs with increased oxygenation requirements and VAP clinical/laboratory signs were enrolled. They were divided in VAP high-suspicion (n=12) or low-suspicion (n=8) groups based on Clinical Pulmonary Infection Score (cutoff:6). ΡΑΙ-1 και RAGE levels did not differ between high- or low-VAP suspicion groups the 1st or 6th days (p-value&gt;0.05). IL-4 was not detected in bronchial secretions. Conclusion: Bronchial concentrations of IL-4, PAI-1 and RAGE in critically ill children are not correlated with high- or low-VAP suspicion.

Objectives To develop and validate a prediction model for 28-day in-hospital mortality among adult patients critically ill with COVID-19 in the UK. Design Observational cohort study. Setting 287 adult critical care units in England, Wales and Northern Ireland, of which 260 admitted at least one eligible patient. Participants 10,933 patients with confirmed COVID-19 of whom 10,401 were eligible (excluding 532 patients with a duration of critical care less than 24 hours and 1 patient with unknown 28-day outcome): 8,666 development (March-April 2020) and 1,735 temporal validation (May-August 2020). Main outcome measures 28-day in-hospital mortality from start of critical care. Results Two models were developed using 14 patient level predictors selected from 30 candidate predictors, with and without adjustment for calendar time. In the temporal validation data, the model discrimination was maintained (c index 0.78) but calibration was poor, particularly for the model not adjusted for calendar time (ratio of observed to predicted mortality 0.74 versus 0.88 for the model adjusted for calendar time). Conclusions We developed and validated a prediction model for 28-day in-hospital mortality for patients critically ill with COVID-19. Although absolute predictions were inaccurate due to changing outcomes, the models will support risk-adjustment in analyses and monitoring changes in risk-adjusted outcome over time.

In the following article, we estimate the Renunciation of Healthcare Services-RHS in Italian regions in the context of the Environmental, Social and Governance-ESG model during the period 2004-2022. The data were acquired from the ISTAT-BES dataset. The data were analyzed using the following econometric techniques: Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled Ordinary Least Squares-OLS, Weighted Least Square-WLS,. Results show that RHS tends to growth with the E-Component, is negatively associated to the S-Component, and positively associate with the G-Component within the ESG model. Furthermore, a clusterization with the unsupervised k-Means algorithm is presented and the results are discussed with a confrontation between optimal and suboptimal k values optimized with the Silhouette Coefficient. Finally, a confrontation among eight different machine-learning algorithms is performed to predict the future value of RHS. Outcomes show that the Simple Regression Tree is the best predictive algorithm and that the level of RHS is predicted to growth on average of 4.4% for the Italian regions. Results are critically discussed.

Heel pain in the “funnel-shaped” space between the calcaneus, talus, and talocalcaneonavicular and subtalar joints may be representative of Sinus Tarsi syndrome. The pain is often characterized by a burning, numbness, or tingling sensation that can stem from strains and tears on the ligaments in that area. Injury treatment typically includes balance training, muscle exercises, bracing, foot orthosis, and non-steroidal anti-inflammatory drugs (NSAIDs). This study presents Wharton Jelly (WJ) tissue allografts as an alternative intervention for patients who fail standard-care treatments. WJ targets tissue defects, unlike other therapies, which aim to reduce swelling and symptomatic pain. This study includes five female patients who have previously failed standard-of-care treatment. Each received extracorporeal pulse-activated therapy (EPAT), WJ, laser therapy, and an orthotic. After an average of 80 days, the cohort had an overall 85.29% improvement in pain. The study's limitations include a small cohort size and a non-blinded design. Given the significant improvement in pain, WJ tissue allograft, combined with other techniques, presents an optimal patient care plan for tissue defects associated with Sinus Tarsi syndrome when standard-of-care treatments fail. These results provide evidence for a more extensive, randomized study to define dosage protocols further and confirm safety and efficacy.

In this article, we analyse the ESG determinants of the “Elderly People Treated in Integrated Home Care”-EPIHC in the Italian regions between 2004 and 2022. We used data from the ISTAT-BES database. We used different econometric techniques i.e.: Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled Ordinary Least Squares-OLS and Weighted Least Squares-WLS. The results show that the EPIHC is positively associated with “Nurses, midwives, and Soil sealing by artificial cover" and negatively associated with "Museum heritage density and relevance" and "Trust in law enforcement agencies and firefighters fire". Furthermore, we have applied a k-Means algorithm with the Silhouette Coefficient and we find the presence of two clusters. Finally, we propose a confrontation among eight different machine-learning algorithms and we find that Linear Regression is the best predictive algorithm.

In the following article, it is presented an investigation of the determinants of Beds for High-Care Specialties-BHCS in the Italian regions in the context of Environmental, Social and Governance-ESG approach. Data from ISTAT-BES for 20 countries in the period 2004-2021 are been used. Different econometric techniques have been applied i.e.: Pooled Ordinary Least Squares, Panel Data with Fixed Effects, Panel Data with Random Effects, Dynamic Panel at 1 stage. Furthermore, a cluster analysis performed with a k-Means algorithm optimized with the Silhouette Coefficient indicated the presence of three clusters. Finally, eight different machine-learning algorithms are analysed to predict the future value of BHCS. The results show that the Artificial Neural Network-ANN algorithm is the best algorithm. The future value of BHSC is expected to growth on average of 4.88% for the analysed regions.

The following article presents an analysis of the impact of the Environmental, Social and Governance-ESG determinants on Hospital Emigration to Another Region-HEAR in the Italian regions in the period 2004-2021. The data are analysed using Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled Ordinary Least Squares-OLS, Weighted Least Squares-WLS, and Dynamic Panel at 1 Stage. Results show that HEAR is negatively associated to E, positively to S and negatively associated to the G within the ESG model. The data were subjected to clustering with a k-Means algorithm optimized with the Silhouette coefficient. The optimal clustering with k=2 is compared to the sub-optimal cluster with k=3. The results suggest a negative relationship between the resident population and hospital emigration at regional level. Finally, a prediction is proposed with machine learning algorithms classified based on statistical performance. The results show that the Artificial Neural Network-ANN algorithm is the best predictor. The ANN predictions are critically analyzed in light of health economic policy directions.

In the following article, we analyse the determinants of the number of physicians in the context of ISTAT BES-Benessere Equo Sostenibile data among twenty Italian regions in the period 2004-2022. We apply Panel Data with Random Effects, Panel Data with Fixed Effects, and Pooled OLS-Ordinary Least Squares. We found that the number of Physicians among Italian regions is positively associated, among others, to “Trust in the Police and Firefighters”, “Net Income Inequality”, and negatively associated, among others, to “Research and Development Intensity” and “Soil waterproofing by artificial cover”. Furthermore, we apply the k-Means algorithm optimized with the Silhouette Coefficient and we find the presence of two clusters. Finally, we confront eight different machine-learning algorithms to predict the future value of physicians and we find that the PNN-Probabilistic Neural Network is the best predictive algorithm.

Dietary supplements are widely embraced by cancer patients seeking complementary and integrative approaches to their care. Unfortunately, many patients do not discuss supplement use with physicians, often due to perceptions of physician indifference or negativity toward supplements. This communication gap exposes patients to unreliable information sources and, potentially, unnecessary risk. As the healthcare landscape evolves, patients increasingly value physicians who recognize their pivotal role in shaping healthcare decisions. This patient-centered perspective emphasizes the provision of evidence-based information tailored to individual needs, open discussions on potential risks, and shared decision-making. It underscores the importance of respecting patient autonomy, offering alternative options, documenting preferences, and ensuring ongoing support while coordinating with the healthcare team. To address these needs, healthcare providers should transform their perspectives and become expert guides who embrace patients as informed, empowered participants. This approach prioritizes open dialogue that considers both facts and uncertainties regarding dietary supplement use, allowing for mutually informed decision-making. Here, we review the literature and present a practical approach emphasizing open discussions, transparency, and respect for patient autonomy. Following this approach, healthcare providers can empower patients to navigate the complexities of dietary supplement use in the context of cancer care, ultimately safeguarding patient safety and well-being.

In this article, we consider a class of nonsmooth interval-valued multiobjective semi-infinite programming problems with vanishing constraints (in short, NIMSIPVC). We introduce the VC-Abadie constraint qualification (in short, VC-ACQ) for NIMSIPVC and employ it to establish Karush-Kuhn-Tucker (in short, KKT)-type necessary optimality conditions. Related to NIMSIPVC, we formulate interval-valued vector Lagrange type dual and scalarized Lagrange type dual problems. Subsequently, we establish weak, strong, and converse duality results relating NIMSIPVC and corresponding dual problems. In addition, we introduce the notions of saddle points for interval-valued vector Lagrangian and scalarized Lagrangian of NIMSIPVC. Moreover, we establish the saddle point optimality criteria for NIMSIPVC. Various non-trivial examples are provided to demonstrate the validity of established results. To the best of our knowledge, optimality conditions, Lagrange type duality, and saddle point optimality criteria for NIMSIPVC have not been investigated yet via Clarke subdifferentials.

Asphaltene-resin-paraffin deposition (ARPD) is a complicated and prevalent issue in oil and gas industry, impacting the efficiency, integrity of petroleum extraction, production, transportation and processing systems. Considering all witnessed ARPD problems in Azerbaijan oil fields, this paper proposed a chemical method and optimized the type and the concentration of chemical inhibitors. And then the effect of selected chemical reagent on inhibiting the ARPD amount and thus en-hancing oil recovery was detected by reservoir simulation during both waterflooding and CO2 flooding production. Three new chemical compounds (namely, Chemical-A, Chemical-B and Chemical-C) were examined in laboratory conditions and their impact on rheological properties of high-paraffin oilfield samples of Azerbaijan (X, Y and Z) were investigated. Experimental results show that Chemical-C with concentration of 600 g/t has the best efficiency for alleviating the problems. After adding Chemical-C to the crude oil, the freezing point of oil is decreased from 12 °C to (-4) °C, ARPD amount is declined from 0.185 to 0.016 g and oil effective viscosity is reduced from 16.2 mPa·s to 3.1 mPa·s. It is determined that for water and CO2 flooding, higher injection pressure resulted in reduced asphaltene precipitation. Adding selected ARPD inhibitor, the oil recovery for waterflooding can increase from 52% to 62%, while it can rise from 55% to 68% for CO2 flooding.

The task of weakly supervised point cloud semantic segmentation has received widespread attention and also has been widely used in autonomous driving, robotics, and modern industries. Due to the high dimensionality and large volume of point cloud data, many technical difficulties appeal to weakly supervised semantic processing, especially segmentation. However, weakly-supervised schemes usually provide only partial labelling information of the underlying point cloud data and thus need to effectively extract local features, geometric information, and contextual relationships only using these limited labelled data for supervised learning. To improve weakly-supervised semantic segmentation, we propose a novel segmentation network through the boundary-based feature aggregation based on a K-NN algorithm with down-sampling operation, and also introduce the smoothness loss and Siamese loss for effective segmentation. The experiments on public datasets demonstrate that our presented segmentation method exceeds most of the existing fully supervised and weakly-supervised methods in terms of mIoU. Specifically, our network has high segmentation accuracy on the labels of objects with similar geometrical structures, such as ceiling, wall, floor, chair and table, reaching 91.2%, 98.8%, 83.3%, 75.3% and 80.2%, respectively. Extensive experiments also illustrate its robustness, effectiveness, and generalization of the proposed weakly supervised segmentation network.

Femtoscopy is a unique tool to investigate the space-time geometry of the matter created in ultra-relativistic collisions. If the probability density distribution of hadron emission is parametrized, then the dependence of its parameters on particle momentum, collision energy, and collision geometry can be given. In recent years, several measurements came to light that indicated the adequacy of assuming a Lévy-stable shape for the mentioned distribution. In parallel, several new phenomenological developments appeared, aiding the interpretation of the experimental results, or providing tools for the measurements. In this paper we review and discuss some of these advances, phenomenological and experimental.

At present, failure definition and damage characteristic curve (DCC) analysis included in the framework to assess bitumen fatigue cracking performance have an inconsistency in ranking bitumen fatigue behaviour. This study utilized two types of self-healing polymers (STP and IPA1w) to modify the neat asphalt (NA), and research four different types of bitumens: NA, STP-modified bitumen, IPA1w-modified bitumen, and styrene-butadiene-styrene modified bitumen (SBSB), to evaluate the above-mentioned framework. All bitumens were subjected to short-term and long-term aging and tested utilizing the Linear amplitude sweep (LAS) test and simplified viscoelastic-continuum-damage (S-VECD) model. The results showed that the SBSB exhibited the highest numbers of loading cycles (in long-term aging analysis) to reach failure points at 25°C, 28°C, and 31°C which were 2290, 2340, and 2510, respectively. However, this bitumen failed to exhibit the best performance in terms of DCC assessment under the same conditions, confirming the above-mentioned inconsistency. Besides, the current failure criterion could not accurately predict bitumen fatigue behaviour under certain test conditions because two R2 values were below 0.1. As a result, this study proposed a new failure definition and failure criterion to overcome these issues. The proposed failure definition agreed with the DCC analysis to rank bitumen fatigue performance, and the proposed failure criterion showed R2 values higher than 0.9. The new framework presented the modified bitumen containing 0.5% of STP as the asphalt binder with the best fatigue cracking performance, according to the selected test conditions.

In this study, we focus on an abstract form of summation equations, which can be regarded as a particular class of nonlinear difference equations. We investigate sufficient conditions for the existence of discrete almost automorphic solutions by appealing to the fixed point theory and establish a linkage between the existence of discrete almost automorphic solutions and the existence of bounded solutions for the nonlinear difference equations in the spotlight. Consequentially, we propose a discrete counterpart of the Bohr-Neugebauer theorem for the qualitative theory of difference equations.