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Introduction: This study investigates the impact of smart refrigerators on the logistics and management of biological samples, emphasizing the critical phases of transport and storage to enhance the pre-analytical quality of blood samples. Efficient sample management is crucial for ensuring diagnostic accuracy. Objective: The primary objective is to evaluate the efficiency of smart refrigerators equipped with cloud technology in optimizing the transport and storage of biological samples. The secondary objective is to assess healthcare personnel's perceptions and satisfaction with these technologies. Method: A longitudinal prospective analysis was conducted to assess both the quantitative incidence of pre-analytical errors and the qualitative perceptions of healthcare personnel regarding these technologies. Samples were collected from six primary care centers within the Elche General Health Department, with one center using smart refrigerators and five using conventional methods. The refrigerators featured GPS, real-time temperature sensors, alert systems for cold chain interruptions, and RFID technology. Training on refrigerator use, systematic data collection on pre-analytical errors, and surveys and semi-structured interviews with healthcare personnel were conducted. Descriptive methods and hypothesis testing, including Z-statistics and logistic regression models, were used for statistical analysis. Results: The analysis revealed a significant decrease in the incidence of coagulated and hemolyzed samples at the center using smart refrigerators. Specifically, the rate of coagulated samples was reduced by 69.39%, while hemolyzed samples decreased by 78.12%. This improvement contrasts with trends observed in centers using conventional practices. A significant 94.62% of the staff reported a positive experience with the smart refrigerators, highlighting high satisfaction and the importance of stricter control in handling and transporting samples to prevent errors. Conclusions: The use of smart refrigerators in the transport and storage of biological samples effectively improves the pre-analytical quality of blood samples, reduces pre-analytical errors, and enhances staff satisfaction. These findings underscore the importance of incorporating advanced technologies in the management of biological samples in primary care settings.

Student engagement is associated with various aspects of students' school experiences, including student achievement, high school completion, and post-secondary success. As measurement of student engagement has grown in countries around the world, few studies have been conducted in South America. This study examined a translated version of the Student Engagement Instrument, widely used in the U.S. and other countries, in a study of 2337 adolescents in Chile. Consistent with prior research, confirmatory factor analyses revealed a six-factor solution as the best fit for the data. However, fewer items were retained than on the studies of the SEI with students in the U.S. The Future Goals and Aspirations and Extrinsic motivation subscales were associated, in expected directions, with achievement 1 year later.

Through the theoretical framework of pedagogy and education as an instrument of social and personal development, this study addresses two key issues for the construction of a mature-older person's identity, namely, generativity and life satisfaction. The main aim here is to explore the generative interest and life satisfaction of a group of mature-older university students and verify whether the years linked to the program and the rate of participation in other types of social agencies and institutions have a positive impact on both constructs. The sample comprised 347 subjects, who were administered the Loyola Generativity Scale -- LGS and the Satisfaction with Life Scale -- SWLS. The results show that level of education and rate of participation have a positive influence on generative interest, while health, marital status and time linked to the higher education program have a positive effect on life satisfaction.

Objectives: The main objective was to investigate the incidence of transfusion-associated graft-versus-host disease (TA-GVHD) in patients who underwent haploidentical hematopoietic cell transplants (HCT) and received non-irradiated leukoreduced blood components. The secondary objective was to describe our leukodepletion results in blood products obtained by the filters employed at our center. Study Design and Methods: Clinical records from 2018 to 2023 were retrospectively analyzed, along with a prospective evaluation of residual leukocytes in blood components from June to November 2023 in order to confirm effectivity of our leukodepletion method. Results: 150 patients were included, no cases of TA-GVHD were reported after using non-irradiated blood products. The incidence of grade 3–4 acute and moderate-severe chronic GVHD was 12.7% (n = 19) and 2.7% (n = 4), respectively. The cumulative incidence of death was 39.3% (n = 52) with a 3.7-year overall survival (CI 95%, 3.3- 4.1 years). Leukodepletion analysis showed a reduction of 99.93% in platelet concentrates and 99.98% in packed red blood cells. Discussion: TA-GVHD in HCT remains a concern traditionally mitigated using blood product irradiation. Recent evidence obtained in favor of leukoreduction techniques question this need, especially in resource-limited settings. Conclusion: These findings support leukoreduction as a primary TA-GVHD preventive measure,along with the advantage in cost reduction. [ABSTRACT FROM AUTHOR]

The growth of photosynthetic organisms requires specific ranges of temperature and photosynthetically active radiation. Monitoring and maintaining these conditions is technically difficult, especially in outdoor cultures. In such cases, a typical meteorological sequence can be a useful tool for estimating the growth of photosynthetic organisms. This study proposes a new methodology based on long-term meteorological sequences to simulate the growth of photosynthetic organisms. This case study addresses microalgae growth simulation (Chlorella vulgaris) in Riosequillo in the north of the Madrid region (Spain) for the four seasons of the year. Then, these estimates are compared with the observed results of an experimental culture of microalgae in domestic wastewater. The results also show strong agreement with the probability distribution function of the daily biomass concentration, giving the best results for typical summer and spring meteorological sequences. The methodology seems to confirm the representativeness of typical meteorological sequences, allows for the identification of the most likely production scenarios for project feasibility analyses, and may be applied to decision-making processes. [ABSTRACT FROM AUTHOR]

The conventional detection of Forward Brillouin Scattering (FBS) in optical fibers requires of interferometric techniques using lengths of tens of meters. In this paper, we demonstrate an alternative approach that provides efficient and high-resolution detection of FBS signals, while using just a 20 cm length section of bare fiber. It consists of a pump and probe scheme using a fiber ring resonator as the interrogation system of the mechanical vibration, which modulates the resonances. The result is an amplitude modulated optical trace which allows the detection of resonances R0,m and TR2,m.

The symptoms of multiple sclerosis (MS) are determined by the location of demyelinating lesions in the white matter of the brain and spinal cord. Currently, magnetic resonance imaging (MRI) is the most common tool used for diagnosing MS, understanding the course of the disease, and analyzing the effects of treatments. However, undesirable components may appear during the generation of MRI scans, such as noise or intensity variations. Mathematical morphology (MM) is a powerful image analysis technique that helps to filter the image and extract relevant structures. Granulometry is an image measurement tool for measuring MM that determines the size distribution of objects in an image without explicitly segmenting each object. While several methods have been proposed for the automatic segmentation of MS lesions in MRI scans, in some cases, only simple data preprocessing, such as image resizing to standardize the input dimensions, has been performed before the algorithm training. Therefore, this paper proposes an MRI preprocessing algorithm capable of performing elementary morphological transformations in brain images of MS patients and healthy individuals in order to delete undesirable components and extract the relevant structures such as MS lesions. Also, the algorithm computes the granulometry in MRI scans to describe the size qualities of lesions. Using this algorithm, we trained two artificial neural networks (ANNs) to predict MS diagnoses. By computing the differences in granulometry measurements between an image with MS lesions and a reference image (without lesions), we determined the size characterization of the lesions. Then, the ANNs were evaluated with the validation set, and the performance results (test accuracy = 0.9753; cross-entropy loss = 0.0247) show that the proposed algorithm can support specialists in making decisions to diagnose MS and estimating the disease progress based on granulometry values. [ABSTRACT FROM AUTHOR]

Massive waste generation linked to overconsumption is considered one of the most significant socio-ecological issues today, becoming a challenge for health and well-being and a barrier to achieving sustainability. Education is key to raising awareness and involving citizens in the adoption of responsible consumption habits, facilitating the recognition of the relationship between our daily activities and the production of waste. The aim of this exploratory study is to analyse the perceptions and commitments of future secondary school teachers (FTs) toward this issue and to explore the educational approaches they propose to address it in the classroom (n = 138). In this work, a mixed-methods approach was used based on quantitative and qualitative data collected through a questionnaire. The results show that FTs have difficulties in recognising the different factors involved in the problem of massive waste generation. However, they incorporate the health and ecological vision, which is close to the holistic vision of the One Health approach. The majority of them take personal responsibility for the problem, although they opt for low-effort options. Regarding the educational proposals they design, only a minority can do it following a commitment-oriented approach. [ABSTRACT FROM AUTHOR]

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This exploratory study analyses the level of the development of the eight key competencies in sustainability of 237 students in the 7th–10th grades, when confronted with a real conflict situation associated with the production and consumption of 'fast fashion'. Their responses were categorised into four levels, representing the degree of development of each competence. The results reflect a low level of competence development, with no significant differences among academic year groups. The competence where the highest level of development was reached was the inter-personal competence, as students recognised that the consumption of fast fashion contributes to the labour exploitation of others. However, this did not prompt students to question the prevailing consumerist values in our society (values-thinking competence), their own practises (implementation competence), or their own contribution to the problem (intra-personal competence). Therefore, it seems necessary to address different socio-environmental issues, critically analyse our daily actions, and thus promote these competencies in sustainability in schools. These will enable students to actively participate in environmental conservation from the perspective of environmental and social justice. [ABSTRACT FROM AUTHOR]

With new high-performance server technology in data centers and bunkers, optimizing search engines to process time and resource consumption efficiently is necessary. The database query system, upheld by the standard SQL language, has maintained the same functional design since the advent of PL/SQL. This situation is caused by recent research focused on computer resource management, encryption, and security rather than improving data mining based on AI tools, machine learning (ML), and artificial neural networks (ANNs). This work presents a projected methodology integrating a multilayer perceptron (MLP) with Kmeans. This methodology is compared with traditional PL/SQL tools and aims to improve the database response time while outlining future advantages for ML and Kmeans in data processing. We propose a new corollary: h k → H = S S E (C) , w h e r e k > 0 a n d ∃ X , executed on application software querying data collections with more than 306 thousand records. This study produced a comparative table between PL/SQL and MLP-Kmeans based on three hypotheses: line query, group query, and total query. The results show that line query increased to 9 ms, group query increased from 88 to 2460 ms, and total query from 13 to 279 ms. Testing one methodology against the other not only shows the incremental fatigue and time consumption that training brings to database query but also that the complexity of the use of a neural network is capable of producing more precision results than the simple use of PL/SQL instructions, and this will be more important in the future for domain-specific problems. [ABSTRACT FROM AUTHOR]

Roux-en-Y gastric bypass (RYGB) is a treatment for severe obesity. However, many patients have insufficient total weight loss (TWL) after RYGB. Although multiple factors have been involved, their influence is incompletely known. The aim of this exploratory study was to evaluate the feasibility and reliability of the use of machine learning (ML) techniques to estimate the success in weight loss after RYGP, based on clinical, anthropometric and biochemical data, in order to identify morbidly obese patients with poor weight responses. We retrospectively analyzed 118 patients, who underwent RYGB at the Hospital Clínico Universitario of Valencia (Spain) between 2013 and 2017. We applied a ML approach using local linear embedding (LLE) as a tool for the evaluation and classification of the main parameters in conjunction with evolutionary algorithms for the optimization and adjustment of the parameter model. The variables associated with one-year postoperative %TWL were obstructive sleep apnea, osteoarthritis, insulin treatment, preoperative weight, insulin resistance index, apolipoprotein A, uric acid, complement component 3, and vitamin B12. The model correctly classified 71.4% of subjects with TWL < 30% although 36.4% with TWL ≥ 30% were incorrectly classified as "unsuccessful procedures". The ML-model processed moderate discriminatory precision in the validation set. Thus, in severe obesity, ML-models can be useful to assist in the selection of patients before bariatric surgery. [ABSTRACT FROM AUTHOR]

SEL, a State-based Language for Video Surveillance Modeling, is a formal language designed to represent and identify activities in surveillance systems through scenario semantics and the creation of motion primitives structured in programs. Motion primitives represent the temporal evolution of motion evidence. They are the most basic motion structures detected as motion evidence, including operators such as sequence, parallel, and concurrency, which indicate trajectory evolution, simultaneity, and synchronization. SEL is a very expressive language that characterizes interactions by describing the relationships between motion primitives. These interactions determine the scenario's activity and meaning. An experimental model is constructed to demonstrate the value of SEL, incorporating challenging activities in surveillance systems. This approach assesses the language's suitability for describing complicated tasks. [ABSTRACT FROM AUTHOR]

The problem of finding the best path trajectory in a graph is highly complex due to its combinatorial nature, making it difficult to solve. Standard search algorithms focus on selecting the best path trajectory by introducing constraints to estimate a suitable solution, but this approach may overlook potentially better alternatives. Despite the number of restrictions and variables in path planning, no solution minimizes the computational resources used to reach the goal. To address this issue, a framework is proposed to compute the best trajectory in a graph by introducing the mathematical morphology concept. The framework builds a lattice over the graph space using mathematical morphology operators. The searching algorithm creates a metric space by applying the morphological covering operator to the graph and weighing the cost of traveling across the lattice. Ultimately, the cumulative traveling criterion creates the optimal path trajectory by selecting the minima/maxima cost. A test is introduced to validate the framework's functionality, and a sample application is presented to validate its usefulness. The application uses the structure of the avenues as a graph. It proposes a computable approach to find the most suitable paths from a given start and destination reference. The results confirm that this is a generalized graph search framework based on morphological operators that can be compared to the Dijkstra approach. [ABSTRACT FROM AUTHOR]

BACKGROUND. Hyaluronan (HA), an extracellular matrix glycosaminoglycan, has been implicated in the pathophysiology of COVID-19 infection, pulmonary hypertension, pulmonary fibrosis, and other diseases, but is not targeted by any approved drugs. We asked whether hymecromone (4-methylumbelliferone [4-MU]), an oral drug approved in Europe for biliary spasm treatment that also inhibits HA in vitro and in animal models, could be repurposed as an inhibitor of HA synthesis in humans. METHODS. We conducted an open-label, single-center, dose-response study of hymecromone in healthy adults. Subjects received hymecromone at 1200 (n = 8), 2400 (n = 9), or 3600 (n = 9) mg/d divided into 3 doses daily, administered orally for 4 days. We assessed safety and tolerability of hymecromone and analyzed HA, 4-MU, and 4-methylumbelliferyl glucuronide (4-MUG; the main metabolite of 4-MU) concentrations in sputum and serum. RESULTS. Hymecromone was well tolerated up to doses of 3600 mg/d. Both sputum and serum drug concentrations increased in a dose-dependent manner, indicating that higher doses lead to greater exposures. Across all dose arms combined, we observed a significant decrease in sputum HA from baseline after 4 days of treatment. We also observed a decrease in serum HA. Additionally, higher baseline sputum HA levels were associated with a greater decrease in sputum HA. CONCLUSION. After 4 days of exposure to oral hymecromone, healthy human subjects experienced a significant reduction in sputum HA levels, indicating this oral therapy may have potential in pulmonary diseases where HA is implicated in pathogenesis. TRIAL REGISTRATION. ClinicalTrials.gov NCT02780752. FUNDING. Stanford Medicine Catalyst, Stanford SPARK, Stanford Innovative Medicines Accelerator program, NIH training grants 5T32AI052073-14 and T32HL129970., Introduction Hyaluronan (HA), an extracellular matrix glycosaminoglycan, plays an important role in inflammation (1, 2). Within injured and infected tissues, HA is produced by stromal cells in response to inflammatory [...]