Machine learning-based identification of segment joint failure in underground tunnels.

Shield tunnels that reside deep within soft soil are subject to longitudinal differential settlement and structural deformation during long-term operation. Longitudinal deformation can be classified into two modes: bending and dislocation deformation. The failure of bolts and engineering treatment techniques differ between these two modes. Therefore, it is imperative to accurately identify the tunnel's longitudinal deformation mode to determine the validity of the segment joint and implement appropriate engineering treatment. Traditional methods for detecting dislocation or opening suffer from high labour costs. To address this issue, this study presents an innovative identification method using a back-propagation neural network (BPNN) to detect segment joint failure in underground tunnels. First, this study collects the tunnel settlement curves of various subways located in the East China soft soil area, and it calculates tunnel settlement-dislocation and settlement-opening datasets using the equivalent axial stiffness model. A corresponding BPNN regression model is subsequently established, and the new settlement curve is the input to this regression model to predict the dislocation and opening, thereby determining the validity of the segment joint. The efficiency of this method is demonstrated through its successful application to the Hangzhou Metro Tunnel. This article is part of the theme issue 'Artificial intelligence in failure analysis of transportation infrastructure and materials'.

Recent advances in sustainable nature-based functional materials for biomedical sensor technologies.

The lightweight, low-density, and low-cost natural polymers like cellulose, chitosan, and silk have good chemical and biodegradable properties due to their individually unique structural and functional elements. However, the mechanical properties of these polymers differ from each other. In this scenario, chitosan lacks good mechanical properties than cellulose and silk. The synthesis of nano natural polymer and reinforcement with suitable chemical compounds as the development of nanocomposite gives them promising multidisciplinary applications. Many kinds of research are already published with innovative bio-derived polymeric functional materials (Bd-PFM) applications. Most research interest is carried out on health concerns. Lots of attention has been paid to biomedical applications of Bd-PFM as biosensors. This review aims to provide a glimpse of the nanostructures Bd-PFM biosensors.

Mental Health Experts as Objects of Epistemic Injustice-The Case of Autism Spectrum Condition.

This theoretical paper addresses the issue of epistemic injustice with particular reference to autism. Injustice is epistemic when harm is performed without adequate reason and is caused by or related to access to knowledge production and processing, e.g., concerning racial or ethnic minorities or patients. The paper argues that both mental health service users and providers can be subject to epistemic injustice. Cognitive diagnostic errors often appear when complex decisions are made in a limited timeframe. In those situations, the socially dominant ways of thinking about mental disorders and half-automated and operationalized diagnostic paradigms imprint on experts' decision-making processes. Recently, analyses have focused on how power operates in the service user-provider relationship. It was observed that cognitive injustice inflicts on patients through the lack of consideration of their first-person perspectives, denial of epistemic authority, and even epistemic subject status, among others. This paper shifts focus toward health professionals as rarely considered objects of epistemic injustice. Epistemic injustice affects mental health providers by harming their access to and use of knowledge in their professional activities, thus affecting the reliability of their diagnostic assessments.

Hypertension Diagnosis with Backpropagation Neural Networks for Sustainability in Public Health.

This paper presents the development of a multilayer feed-forward neural network for the diagnosis of hypertension, based on a population-based study. For the development of this architecture, several physiological factors have been considered, which are vital to determining the risk of being hypertensive; a diagnostic system can offer a solution which is not easy to determine by conventional means. The results obtained demonstrate the sustainability of health conditions affecting humanity today as a consequence of the social environment in which we live, e.g., economics, stress, smoking, alcoholism, drug addiction, obesity, diabetes, physical inactivity, etc., which leads to hypertension. The results of the neural network-based diagnostic system show an effectiveness of 90%, thus generating a high expectation in diagnosing the risk of hypertension from the analyzed physiological data.

Research on Infant Health Diagnosis and Intelligence Development Based on Machine Learning and Health Information Statistics.

Intelligent health diagnosis for young children aims at maintaining and promoting the healthy development of young children, aiming to make young children have a healthy state and provide a better future for their physical and mental health development. The biological basis of intelligence is the structure and function of human brain and the key to improve the intelligence level of infants is to improve the quality of brain development, especially the early development of brain. Based on machine learning and health information statistics, this paper studies the development of infant health diagnosis and intelligence, physical and mental health. Pre-process the sample data, and use the filtering method based on machine learning and health information statistics for feature screening. Compared with traditional statistical methods, machine learning and health information statistical methods can better obtain the hidden information in the big data of children's physical and mental health development, and have better learning ability and generalization ability. The machine learning theory is used to analyze and mine the infant's health diagnosis and intelligence development, establish a health state model, and intuitively show people the health status of their infant's physical and mental health development by means of data. Moreover, the accumulation of these big data is very important in the field of medical and health research driven by big data.

Alineadores en ortodoncia / Aligners in orthodontics

Objetivo: Describir los alineadores en ortodoncia y su utilidad en la salub bucal del paciente. Método: descriptiva documental desde un diseño bibliográfico, siendo escrutada una población de 15 artículos científicos tomados de bases de datos publicadas entre 2016 al 2021. Conclusión: Los alineadores dentales sirven para corregir casos simples, nivelar arcos, mantener la longitud de la raíz y cerrar espacios. Estos alineadores se pueden alterar con cambios térmicos físicos sobre todo si es sometido a alimentos calientes. Da la posibilidad de mostrar al paciente cómo será el resultado final, esto se logra mediante las simulaciones digitales que permite este método. Es un tratamiento que requiere de experiencia por parte del profesional.

Objective: To describe aligners in orthodontics and their usefulness in the oral health of the patient. Method: Descriptive documentary from a bibliographic design, being scrutinized a population of 15 scientific articles taken from databases published between 2016 to 2021. Conclusion: Dental aligners are used to correct simple cases, level arches, maintain root length and close spaces. These aligners can be altered by physical thermal changes especially if subjected to hot food. It gives the possibility to show the patient how the final result will be, this is achieved through digital simulations that this method allows. It is a treatment that requires experience on the part of the professional.

Hacia el buen gobierno por la salud: incorporación de la diversidad de percepciones en salud urbana / Towards good governance for health: incorporating the diversity of perceptions around urban health

Objetivo: Analizar las similitudes y diferencias discursivas en torno a la conceptualización de la salud y los activos y necesidades en salud percibidas en los barrios y la ciudad de Bilbao, en un proceso participativo. Método: Se realizaron talleres participativos con profesionales, vecinos/as y ciudadanía asociada. Se analizaron las diferencias de percepciones en torno a los tres bloques de contenido con base en el modelo de salud referido, así como los tipos -de carácter más individual o estructural- de necesidades y activos de salud identificados. Resultados: La conceptualización de la salud desde una mirada biopsicosocial fue más clara entre las/los profesionales, si bien ambos perfiles apuntaron a la importancia de sus determinantes sociales. La formulación de necesidades y activos en salud por parte de las/los vecinas/os se realizó desde el impacto en su vida cotidiana y desde una posición de usuarias/os con respecto a una Administración proveedora de servicios. Entre la ciudadanía asociada y las/los profesionales, se aludió en mayor medida a determinantes intermedios y estructurales, así como a cuestiones relacionadas con el ámbito de actuación de la Administración. Conclusiones: La inclusión de la multiplicidad y la diversidad de percepciones en la planificación son aspectos clave para el buen gobierno local por la salud. Para afrontar sus contradicciones es necesario un compromiso de los gobiernos por la incorporación efectiva de la participación ciudadana. (AU)

Objective: To analyse the similarities and differences in the discourse surrounding the conceptualisation of health and the perceived health assets and needs in the neighborhoods and city of Bilbao in a participatory process. Method: Participatory workshops were held with professionals, neighbors and associated citizens. The differences in perceptions of the three content blocks were analysed on the basis of the health model referred, as well as the typologies -of a more individual or structural nature- of identified health needs and assets. Results: The conceptualisation of health from a biopsychosocial perspective was clearer among professionals, although both profiles pointed to the importance of its social determinants. The formulation of needs and assets in health by the neighbors was made from the impact on their daily life and from a position of users with respect to a service provider administration. Among the associated citizens and professionals, intermediate and structural determinants were more frequently mentioned, as well as issues related to the administration's scope of action. Conclusions: The inclusion of the multiplicity and diversity of perceptions in planning is key to good local government for health. To address their contradictions, a commitment by governments to effectively incorporate citizen participation is needed. (AU)

[Towards good governance for health: incorporating the diversity of perceptions around urban health]. / Hacia el buen gobierno por la salud: incorporación de la diversidad de percepciones en salud urbana.

OBJECTIVE: To analyse the similarities and differences in the discourse surrounding the conceptualisation of health and the perceived health assets and needs in the neighborhoods and city of Bilbao in a participatory process. METHOD: Participatory workshops were held with professionals, neighbors and associated citizens. The differences in perceptions of the three content blocks were analysed on the basis of the health model referred, as well as the typologies -of a more individual or structural nature- of identified health needs and assets. RESULTS: The conceptualisation of health from a biopsychosocial perspective was clearer among professionals, although both profiles pointed to the importance of its social determinants. The formulation of needs and assets in health by the neighbors was made from the impact on their daily life and from a position of users with respect to a service provider administration. Among the associated citizens and professionals, intermediate and structural determinants were more frequently mentioned, as well as issues related to the administration's scope of action. CONCLUSIONS: The inclusion of the multiplicity and diversity of perceptions in planning is key to good local government for health. To address their contradictions, a commitment by governments to effectively incorporate citizen participation is needed.

Diagnóstico em saúde mental: aceitação e desprezo da pluralidade / Mental health diagnosis: acceptance and contempt of plurality

Resumo Neste ensaio, discutem-se constructos ligados às concepções de saúde e doença e, em particular, a aspectos que influenciaram e influenciam a noção de adoecimento mental. Partindo de uma revisão narrativa de literatura, visitam-se diferentes tempos e ideias que, em consonância, apontam que processos produtivos, época, território, conjunturas políticas e simbólicas, assim como modelos sanitários, sugestionam a forma de se diagnosticar e intervir sobre doenças. A atitude diagnóstica diante daquilo que se considera ou não patológico revela características fundadoras das sociedades e das forças que as operam e, ao alcançar o campo da subjetividade, potencializa-se como força capaz de elevar ou anular a pluralidade contida na existência humana.

Abstract This essay discusses constructs linked to the conceptions of health and illness and, in particular, ideas that influenced and still influence the notion of mental illness. Starting from a narrative literature review, different times and ideas are visited, which, in consonance, point out that productive processes, time, territory, political and symbolic situations, as well as health models, suggest the way to diagnose and intervene in diseases. The diagnostic attitude towards what is considered pathological or not reveals fundamental characteristics of societies and the forces that operate them and, by reaching the field of subjectivity, it is potentialized as a force capable of elevating or canceling the diversity contained in human existence.

Características sociodemográficas, económicas y de salud de los beneficiarios de los Servicios Educacionales Complementarios Básicos / Sociodemographic, economic and health-related characteristics of the beneficiaries of Basic Complementary Educational Services

Introducción: La nueva Ley Universitaria 30220 permite mejorar las condiciones básicas de calidad universitaria en Perú, y es pertinente conocer las condiciones del estudiante y su procedencia para la mejora continua de su progreso académico. Objetivo: Determinar las características sociodemográficas, económicas y de salud de beneficiarios de los servicios educacionales complementarios básicos de la Universidad Nacional de Frontera, Sullana Perú. Métodos: Se trata de un estudio descriptivo. Se revisaron los cuestionarios socioeconómicos, familiares y de salud de los beneficiarios. La población fue censal y ascendió a 1285 estudiantes. Resultados: Del total de estudiantes, 64 por ciento fueron mujeres y 35 por ciento hombres; asimismo, se determinó un elevado porcentaje de estudiantes con servicio de agua por horas, y se observó que algunos trabajaban en ocupaciones de ventas, en trabajo independiente y como mototaxistas. También se determinó que la mayoría de los estudiantes percibían un sueldo mensual entre 250-500 soles. En cuanto a la vacunación, se determinó que los estudiantes se colocaron la vacuna antitetánica, la vacuna contra el sarampión, la vacuna contra la hepatitis B, y la vacuna contra el virus del papiloma humano. Además, se halló un bajo porcentaje de estudiantes con asma, con algún tipo de alergia, y con padecimiento de alguna discapacidad, depresión y abuso sexual. Conclusiones: El servicio complementario de salud que brinda la universidad es pertinente para reducir riesgos de deserción por motivos de salud durante el pregrado. Aunque se necesita articular esfuerzos con los Gobiernos locales para establecer programas de salud(AU)

Introduction: The new University Law 30220 allows improving the basic conditions of university quality in Peru, insofar it is pertinent to know students' conditions and origins in view of the continuous improvement of their academic progress. Objective: To determine the sociodemographic, economic and health-related characteristics of beneficiaries of basic complementary educational services of the National University of Frontera in Sullana, Peru. Methods: This is a descriptive study. The socioeconomic, family and health questionnaires of the beneficiaries were reviewed. The population was of census type and amounted to 1,285 students. Results: Of the total of students, 64 percent were women and 35 percent were men. Likewise, a high percentage of students with hourly water service was determined, as well as some were observed to work in sales occupations, self-employment and as motorcycle taxi drivers. Most of the students were observed to receive a monthly salary between 250-500 soles. Regarding vaccination, the students were observed to receive vaccines against tetanus, measles, hepatitis B and human papillomavirus vaccines. In addition, a low percentage of students with asthma, with some type of allergy or suffering from some disability, depression and sexual abuse was found. Conclusions: The complementary health service offered by the university is pertinent to reduce the risk of dropping out due to health-related reasons during undergraduate studies. Although it is necessary to coordinate efforts with local governments for establish health programs(AU)

End-to-End AI-Based Point-of-Care Diagnosis System for Classifying Respiratory Illnesses and Early Detection of COVID-19: A Theoretical Framework.

Respiratory symptoms can be caused by different underlying conditions, and are often caused by viral infections, such as Influenza-like illnesses or other emerging viruses like the Coronavirus. These respiratory viruses, often, have common symptoms: coughing, high temperature, congested nose, and difficulty breathing. However, early diagnosis of the type of the virus, can be crucial, especially in cases, such as the COVID-19 pandemic. Among the factors that contributed to the spread of the COVID-19 pandemic were the late diagnosis or misinterpretation of COVID-19 symptoms as regular flu-like symptoms. Research has shown that one of the possible differentiators of the underlying causes of different respiratory diseases could be the cough sound, which comes in different types and forms. A reliable lab-free tool for early and accurate diagnosis, which can differentiate between different respiratory diseases is therefore very much needed, particularly during the current pandemic. This concept paper discusses a medical hypothesis of an end-to-end portable system that can record data from patients with symptoms, including coughs (voluntary or involuntary) and translate them into health data for diagnosis, and with the aid of machine learning, classify them into different respiratory illnesses, including COVID-19. With the ongoing efforts to stop the spread of the COVID-19 disease everywhere today, and against similar diseases in the future, our proposed low cost and user-friendly theoretical solution could play an important part in the early diagnosis.

Mechanoluminescence Rebrightening the Prospects of Stress Sensing: A Review.

The emergence of new applications, such as in artificial intelligence, the internet of things, and biotechnology, has driven the evolution of stress sensing technology. For these emerging applications, stretchability, remoteness, stress distribution, a multimodal nature, and biocompatibility are important performance characteristics of stress sensors. Mechanoluminescence (ML)-based stress sensing has attracted widespread attention because of its characteristics of remoteness and having a distributed response to mechanical stimuli as well as its great potential for stretchability, biocompatibility, and self-powering. In the past few decades, great progress has been made in the discovery of ML materials, analysis of mechanisms, design of devices, and exploration of applications. One can find that with this progress, the focus of ML research has shifted from the phenomenon in the earliest stage to materials and recently toward devices. At the present stage, while showing great prospects for advanced stress sensing applications, ML-based sensing still faces major challenges in material optimization, device design, and system integration.

A novel comprehensive model of set pair analysis with extenics for river health evaluation and prediction of semi-arid basin - A case study of Wei River Basin, China.

The accelerated development of urbanization in semi-arid areas is easy to cause varying degrees of disturbance to its fragile aquatic ecosystem. To find a general method for assessing the health status in semi-arid basins in China, and to provide theoretical basis for river health management and sustainable development, this study is that health evaluation index system is established in the Wei River Basin, covering a huge semi-arid area, and analyzed the biological structure of plankton obtained by field sampling and identified in laboratory, chemical conditions including dissolved oxygen, water temperature, ammonia nitrogen, pH, chlorophyll and other water physical and chemical factors determined by field instruments and sediment heavy metals analyzed in laboratory, physical habitat scored on site and social factors including water resource utilization rate and water consumption per 10,000 yuan of GDP collected in local water resource bulletin. Based on the idea of game theory, an improved coupling model of set pair analysis with extenics is established to assess and predict health. The results show that Wei River System and Jing River System are healthy, Beiluo River System is sub-healthy, and the whole Wei River Basin is also healthy; most of the cross-sections have a tendency to change to a bad level. Compared with simple weighting, set pair analysis and variable fuzzy set methods based on the corresponding sampling data and the weight in this paper, the coupling model can explain the transition and its trend between levels, reflect the certainty and uncertainty, and get more accurate results. It is suggested that daily monitoring and management should be strengthened in most sections to improve their health. And improve the development level of ecological function and social service function, give priority to the development of downstream water resources economy.

The adaptation and feasibility of dialectical behaviour therapy for adults with intellectual developmental disabilities and transdiagnoses: A pilot community-based randomized controlled trial.

INTRODUCTION: Preliminary evidence suggests dialectical behaviour therapy (DBT) may be beneficial for persons with intellectual disabilities. This pilot randomized controlled trial aimed to determine the feasibility of adapted DBT for adults with intellectual disabilities and co-morbid psychiatric disorders in the community. METHODS: An adapted DBT programme (aDBT-ID) was delivered to adults with mild-to-moderate intellectual disability (n = 20) and their caregivers (n = 20). A single-blind, mixed-methods design was employed with treatment (n = 10) and control (n = 10). In addition to feasibility, pre-post-measures of emotional regulation, anger and mental health were taken from clients and caregivers. RESULTS: Results suggest it was feasible and beneficial to deliver adapted DBT in the community. Qualitative findings found both participants and caregivers were satisfied with the treatment delivery. No differences between conditions were found. CONCLUSION: This pilot study highlights the feasibility of adapted DBT for individuals with intellectual disabilities and the practicalities of delivering community-based inclusive research.

Sensors for Structural Health Monitoring of Agricultural Structures.

The health diagnosis of agricultural structures is critical to detecting damages such as cracks in concrete, corrosion, spalling, and delamination. Agricultural structures are susceptible to environmental degradation due to frequent exposure to water, organic effluent, farm chemicals, structural loading, and unloading. Various sensors have been employed for accurate and real-time monitoring of agricultural building structures, including electrochemical, ultrasonic, fiber-optic, piezoelectric, wireless, fiber Bragg grating sensors, and self-sensing concrete. The cost-benefits of each type of sensor and utility in a farm environment are explored in the review. Current literature suggests that the functionality of sensors has improved with progress in technology. Notable improvements made with the progress in technology include better accuracy of the measurements, reduction of signal-to-noise ratio, and transmission speed, and the deployment of machine learning, deep learning, and artificial intelligence in smart IoT-based agriculture. Key challenges include inconsistent installation of sensors in farm structures, technical constraints, and lack of support infrastructure, awareness, and preference for traditional inspection methods.

The Impact of Sickle Cell Anemia and Mental Health Diagnoses on Healthcare Use and Preventive Care among Children Enrolled in Medicaid, 2005-2012.

OBJECTIVE: To examine mental health diagnoses, healthcare use, and receipt of age-appropriate preventive care, including antibiotic prophylaxis, hydroxyurea therapy, and transcranial Doppler screenings, among children with sickle cell anemia (SCA). STUDY DESIGN: Children aged 1-17 years with SCA from 6 states having 3 or more Medicaid claims with a SCA diagnosis within a year (2005-2012) were included. Children with mental health diagnoses were identified with 1 or more mental health encounters. Poisson and logistic regression models with general estimating equations assessed the relationship between mental health diagnoses, healthcare use, and receipt of age-appropriate preventive care. RESULTS: In total, 7963 children with SCA were identified (22 424 person-years); 1593 person-years (7.1%) included 1 or more mental health diagnoses. Children with a mental health diagnosis were more likely to have inpatient admissions (incidence rate ratio [IRR] 1.46, 95% CI 1.36-1.56) and outpatient (IRR 1.27, 95% CI 1.21-1.34), emergency department (IRR 1.39, 95% CI 1.30-1.48), and well-child visits (IRR 1.19, 95% CI 1.11-1.29). Those with a mental health diagnosis were more likely to receive hydroxyurea therapy (odds ration [OR] 1.17, 95% CI 1.03-1.33) and less likely to receive transcranial Doppler screenings (OR 0.79, 95% CI 0.68-0.93). CONCLUSIONS: Children with SCA do not receive adequate age-appropriate preventive care. Further research is necessary to identify key points of coordination between mental health and SCA services throughout the life course. This approach may help to increase receipt of age-appropriate preventive care and decrease reliance on acute care.

Physician and behavioral health provider diagnostic agreement in a general hospital setting.

OBJECTIVE: Behavioral health providers are often employed in inpatient settings. However, it is unclear if there is mental health diagnosis agreement between referring physicians and behavioral health providers. The purpose of this study is to assess for referring physician and behavioral health provider mental health diagnostic agreement in a general hospital setting. METHOD: An analysis of 60 consecutive inpatient referrals to a behavioral health provider in a general hospital setting was conducted. The initial referral diagnosis from referring internal medicine physicians was compared with the diagnosis made by the behavioral health provider. RESULTS: Kappa statistics indicated good diagnostic agreement for substance abuse (.79), anxiety disorders (.82), adjustment disorders (.88), relational conflict (.88), and "other" (.74). There was less agreement for depressive disorders (.55). CONCLUSIONS: Diagnostic agreement was good overall, suggesting that referrals to inpatient behavioral health providers are often appropriate. Results indicated that depression was underdiagnosed by physicians in the study sample. This is problematic given that depression can be successfully treated through the use of medication and psychotherapy.

Mental Health Diagnoses among Children and Adolescents with Chronic Medical Conditions in a Large Urban Cohort.

We analyzed data for 6,458 children with chronic conditions. The most prevalent diagnoses were mood disorders (8.6%), attention deficit hyperactivity disorder (ADHD; 7.4%), conduct disorders (6.1%), and anxiety disorders (4.8%). Adjusted odds of having a mental health diagnosis increased with age for mood disorders and anxiety disorders and decreased with age for ADHD and conduct disorders. When compared with females, males had lower odds of being diagnosed with mood and anxiety disorders and higher odds of being diagnosed with ADHD and conduct disorders. Blacks had lower odds of being diagnosed with anxiety, mood disorders, and ADHD than children in the other racial category. Hispanics had lower odds of being diagnosed with ADHD than children in the other racial category. Racial/ethnic minorities were less likely to have a mental health diagnosis than children in the other race/ethnicity category, which suggests under identification of mental health needs particularly in minority children.

An application of the Pareto method in surveys to diagnose managers' and workers' perception of occupational safety and health on selected Polish construction sites.

The construction industry is an important sector of the economy in Poland. According to the National Labour Inspectorate (PIP) data of 2014, the number of victims of fatal accidents in the construction sector amounted to 80 as compared with 187 injured in all other sectors of economy in Poland. This article presents the results of surveys on the impact of construction worker behaviour on the occupational safety and health outcomes. The surveys took into account the point of view of both construction site management (tactical level) and construction workers (operational level). For the analysis of results, the method of numerical taxonomy and Pareto charts was employed, which allowed the authors to identify the areas of occupational safety and health at both an operational and a tactical level, in which improvement actions needed to be proposed for workers employed in micro, small, medium and large construction enterprises.

Pre-deployment Year Mental Health Diagnoses and Treatment in Deployed Army Women.

We estimated the prevalence of select mental health diagnoses (MHDX) and mental health treatment (MHT), and identified characteristics associated with MHT during the pre-deployment year (365 days before deployment) in active duty Army women (N = 14,633) who returned from Iraq or Afghanistan deployments in FY2010. Pre-deployment year prevalence estimates were: 26.2 % for any select MHDX and 18.1 % for any MHT. Army women who had physical injuries since FY2002 or any behavioral health treatment between FY2002 and the pre-deployment year had increased odds of pre-deployment year MHT. During the pre-deployment year, a substantial percentage of Army women had MHDX and at least one MHT encounter or stay. Future research should determine if pre-deployment MHDX among Army women reflect vulnerability to future MHDX, or if pre-deployment MHT results in protection from chronic symptoms.