Greater Complexity Research Articles

Orphan Disease, Drugs, and Dentistry: A Cumulative Review

Orphan diseases also known as rare diseases (RDs) are typically hereditary in nature. According to World Health Organization, RDs have a prevalence of 1 in 1000 individuals. Few RDs such as Turner syndrome, Synovitis-acne-pustulosis-hyperostosis-osteitis (SAPHO), Williams syndrome, neurofibromatosis type I, Gorlin–Goltz, Schimke immuno, and cherubism exhibit oral signs. The disease’s great complexity and relatively low occurrence necessitates a diagnostotherapeutic strategy based on the Integration of Several Specializations. Rare illnesses require a worldwide agreement about the planning of future interventions. Dentists are often the first medical professionals to recognize RDs because oral symptoms often appear several years before the corresponding systemic symptoms. The objective of this article is to showcase information about RDs and several activities undertaken over the past decade to address this worldwide issue.

Impaired Exercise Capacity and Mortality Risk in Adults With Congenital Heart Disease

BackgroundAn association between impaired exercise capacity and risk of mortality has been reported among adults with congenital heart disease (CHD). Over the years, treatment methods have improved and may influence outcome. Hence, we report data from a national cohort reflecting a contemporary population. ObjectivesThe purpose of this study was to investigate the association between exercise capacity (workload) and mortality in a large registry-based cohort. MethodsData on exercise capacity using cycle ergometer were retrieved from the national registry of CHD. The association between predicted exercise capacity (%ECpred) and mortality was analyzed using Cox regression. ResultsIn total, 3,721 adults (>18 years, 44.6% women) with CHD were included. The median age was 27.0 years (IQR: 20.8-41.0 years) and mean %ECpred was 77% ± 20%. Over a mean follow-up of 9.4 ± 6.0 years, there were 214 (5.8%) deaths. The Multivariable Cox regression model showed that moderately and severely impaired exercise capacity (50-<70 %ECpred: HR: 2.1, 95% CI: 1.4-3.2, P < 0.001, and <50 %ECpred: HR: 3.5, 95% CI: 2.1-6.0, P < 0.001) and CHD complexity were associated with higher mortality (moderate complexity: HR: 1.9 95% CI: 1.2-3.0, P = 0.003, great complexity: HR: 2.3 95% CI: 1.3-4.2, P = 0.008) when adjusted for New York Heart Association class, physical activity, cardiovascular medication, sex, impaired systemic ventricular function, and age. ConclusionsImpaired exercise capacity and CHD complexity are independently associated with all-cause mortality in patients with CHD. Exercise capacity is an easily accessible variable that may be a useful tool for risk assessment in adult patients with CHD, but this needs confirmation in prospective studies.

3D PET/CT Tumor Co-Segmentation Based on Background Subtraction Hybrid Active Contour Model

Accurate tumor segmentation in medical images plays an important role in clinical diagnosis and disease analysis. However, medical images usually have great complexity, such as low contrast of computed tomography (CT) or low spatial resolution of positron emission tomography (PET). In the actual radiotherapy plan, multimodal imaging technology, such as PET/CT, is often used. PET images provide basic metabolic information and CT images provide anatomical details. In this paper, we propose a 3D PET/CT tumor co-segmentation framework based on active contour model. First, a new edge stop function (ESF) based on PET image and CT image is defined, which combines the grayscale standard deviation information of the image and is more effective for blurry medical image edges. Second, we propose a background subtraction model to solve the problem of uneven grayscale level in medical images. Apart from that, the calculation format adopts the level set algorithm based on the additive operator splitting (AOS) format. The solution is unconditionally stable and eliminates the dependence on time step size. Experimental results on a dataset of 50 pairs of PET/CT images of non-small cell lung cancer patients show that the proposed method has a good performance for tumor segmentation.

Influence Technique Training Data sensor (Triton Wear) To improve biomechanical variables for some stages Performance and achievement 50m freestyle youth

Swimming is one of the sports with great muscular effort and complex motor performance that requires coordination and harmony between the movements of the parts of the body contributing to performance that defies the limits of humans. The development of physical abilities and the improvement of technical performance can only be separated from the support of scientific theories and technology, in order to improve training methods and feedback system based on the fusion of information and data using modern sensors and information collection system. On the performance and mechanical conditions of the swimmer to help develop performance and achievement, the researchers used for this purpose a device (Triton Wear data sensor) to collect information and feedback on performance, to prepare special exercises and correct thereal-time performance of 50 m swimmers. The research was conducted on a sample of swimmers amounting to (6) young swimmers whose technical and mechanical data was extracted after wearing the sensor under the head cover of each swimmer, and the performance data was analyzed on this system, and the experiment lasted for six weeks, during which special exercises and feedback were given. Instantaneous based on the sensor data of each member of the sample, and after conducting post-tests, it was shown that the exercises and feedback based on the sensor technology, had a direct impact on the improvement of the average performance of the sample in the 50-meter freestyle race and the improvement of all biomechanical values (such as average speed, frequency and length, acceleration and instantaneous strength) This improvement indicated that data collection and nutrition Using the sensor's multi-information fusion can be applied more precisely and differently in the training of different swimming races, and can find many motor problems in sports swimmers to describe training solutions for them, both for specific parts of the body and the body as a whole. Techniques for accurately identifying this valuable information can therefore be used for quantitative biomechanical analysis. And to reach the training process.

A distributed and energy-efficient KNN for EEG classification with dynamic money-saving policy in heterogeneous clusters

Due to energy consumption’s increasing importance in recent years, energy-time efficiency is a highly relevant objective to address in High-Performance Computing (HPC) systems, where cost significantly impacts the tasks executed. Among these tasks, classification problems are considered due to their great computational complexity, which is sometimes aggravated when processing high-dimensional datasets. In addition, implementing efficient applications for high-performance systems is not an easy task since hardware must be considered to maximize performance, especially on heterogeneous platforms with multi-core CPUs. Thus, this article proposes an efficient distributed K-Nearest Neighbors (KNN) for Electroencephalogram (EEG) classification that uses minimum Redundancy Maximum Relevance (mRMR) as a feature selection technique to reduce the dimensionality of the dataset. The approach implements an energy policy that can stop or resume the execution of the program based on the cost per Megawatt. Since the procedure is based on the master-worker scheme, the performance of three different workload distributions is also analyzed to identify which one is more suitable according to the experimental conditions. The proposed approach outperforms the classification results obtained by previous works that use the same dataset. It achieves a speedup of 74.53 when running on a multi-node heterogeneous cluster, consuming only 13.38% of the energy consumed by the sequential version. Moreover, the results show that financial costs can be reduced when energy policy is activated and the importance of developing efficient methods, proving that energy-aware computing is necessary for sustainable computing.

Complexity of carbon dioxide flux in urban areas: A comparison with natural surfaces

The characteristics of turbulent CO2 transport and its dissimilarity with heat and water vapor are investigated over both natural and urban areas. A novel index TS is proposed to effectively quantify the transport similarity between two scalars. By comparison, it is found that the transport of CO2 shows great complexity in urban areas. It is ideal in natural areas that heat, water vapor, and CO2 are efficiently transported by thermal plumes (i.e., the dominant coherent structures under unstable conditions), and that the transport similarity among them becomes increasingly evident with the increase of atmospheric instability. However, in urban areas, the transport of CO2 shows significant dissimilarity from that of heat and water vapor, and it is hard to detect the role of thermal plumes. Furthermore, it is observed that the sector-average CO2 flux in urban areas changes largely with the wind blowing from different urban functional areas. Specially, for a given direction, there might be contrasting characteristics in CO2 transport under different unstable conditions. These features can be explained by the flux footprint. Since the CO2 sources and sinks are distributed heterogeneously in urban areas, the variation of footprint areas with wind direction or atmospheric instability, causes the alternation between source-dominated (i.e., upward) and sink-dominated (i.e., downward) CO2 transport. Therefore, the role of coherent structures in CO2 transport is substantially confused by spatially-confined sources/sinks in urban areas, leading to significant transport dissimilarity between CO2 and heat or water vapor and thus the great complexity in CO2 transport. The findings in this study are helpful to promote the understanding of the global carbon cycle in depth.

Local GHR roles in regulation of mitochondrial function through mitochondrial biogenesis during myoblast differentiation

BackgroundMyoblast differentiation requires metabolic reprogramming driven by increased mitochondrial biogenesis and oxidative phosphorylation. The canonical GH-GHR-IGFs axis in liver exhibits a great complexity in response to somatic growth. However, the underlying mechanism of whether local GHR acts as a control valve to regulate mitochondrial function through mitochondrial biogenesis during myoblast differentiation remains unknown.MethodsWe manipulated the GHR expression in chicken primary myoblast to investigate its roles in mitochondrial biogenesis and function during myoblast differentiation.ResultsWe reported that GHR is induced during myoblast differentiation. Local GHR promoted mitochondrial biogenesis during myoblast differentiation, as determined by the fluorescence intensity of Mito-Tracker Green staining and MitoTimer reporter system, the expression of mitochondrial biogenesis markers (PGC1α, NRF1, TFAM) and mtDNA encoded gene (ND1, CYTB, COX1, ATP6), as well as mtDNA content. Consistently, local GHR enhanced mitochondrial function during myoblast differentiation, as determined by the oxygen consumption rate, mitochondrial membrane potential, ATP level and ROS production. We next revealed that the regulation of mitochondrial biogenesis and function by GHR depends on IGF1. In terms of the underlying mechanism, we demonstrated that IGF1 regulates mitochondrial biogenesis via PI3K/AKT/CREB pathway. Additionally, GHR knockdown repressed myoblast differentiation.ConclusionsIn conclusion, our data corroborate that local GHR acts as a control valve to enhance mitochondrial function by promoting mitochondrial biogenesis via IGF1-PI3K/AKT/CREB pathway during myoblast differentiation.2uqMpL47bHNL2ReoTRE-H3Video

Robert Boyle, the Bible, and Natural Philosophy

The great chemist Robert Boyle was also a serious student of the Bible and Christian theology, both of which profoundly influenced his natural philosophy. Christian beliefs and moral attitudes motivated him to extend human dominion over the creation by advancing scientific knowledge and giving medicines from his laboratory to the poor. His outspoken advocacy of empiricism, over and against those who believed that unaided reason was sufficient to probe the depths of nature, was rooted in the conviction that the free, wise, and powerful Creator knows the creation far better than we creatures ever will. He vigorously promoted what he called “the mechanical philosophy”, partly because he found it far more theologically attractive than the pagan Greek conception taught in the universities, which conceived of “Nature” as a semi-divine being with a mind and powers of its own. It also underscored the great complexity of the world machine, requiring an intelligent Creator to have assembled it—thereby (he hoped) moving people not only to acknowledge God but to live piously and humbly.

Morphology and Morphometry of Aortic Valve in Humans and Porcines – A Comparative Study

Background: The aortic valve is a semilunar valve with three leaflets that are in the left ventricle’s outflow tract and only permits unidirectional blood flow away from the ventricle. The valve leaflet can tolerate extremely high mechanical and hemodynamic forces resulting from the great complexity and complicated cellular and molecular functions. Aims: The aim of the study is to provide an add-on to the understanding of the morphological and morphometrical aspects of human and porcine aortic heart valves on comparative grounds so that they can be used as a guide in the construction of three-dimensional (3D)-printed mechanical valve. Materials and Methods: Twenty swine and twenty human hearts were compared and examined in this investigation. The porcine and human hearts weighing in between 300 g and 450 g were considered, and any variation from the normal and any mechanical damage rendered during procurement were all excluded from the study. Results: The length of the attached margin of the right coronary cusp, left coronary cusp, and noncoronary cusp of human and porcine were 45.15 mm, 36.47 mm, and 41.53 mm and 36.55 mm, 43.14 mm, and 36.10 mm, respectively. The length of the free margin and the height of the cusps from nadir to the sinotubular junction and the effective height of the cusp from nadir to the free margin of the cusps of human and porcine have been compared. Conclusion: The human and swine aortic valves share morphological and morphometrical characteristics, which can be used to create 3D valves and tissue engineering procedures with greater biocompatibility and biofunctionality.

Computational Investigation of Interactions between Carbon Nitride Dots and Doxorubicin.

The study of carbon dots is one of the frontiers of materials science due to their great structural and chemical complexity. These issues have slowed down the production of solid models that are able to describe the chemical and physical features of carbon dots. Recently, several studies have started to resolve this challenge by producing the first structural-based interpretation of several kinds of carbon dots, such as graphene and polymeric ones. Furthermore, carbon nitride dot models established their structures as being formed by heptazine and oxidized graphene layers. These advancements allowed us to study their interaction with key bioactive molecules, producing the first computational studies on this matter. In this work, we modelled the structures of carbon nitride dots and their interaction with an anticancer molecule (Doxorubicin) using semi-empirical methods, evaluating both geometrical and energetic parameters.

Phenotypes and outcomes in non-anticoagulated patients with atrial fibrillation: An unsupervised cluster analysis

BackgroundPatients with atrial fibrillation are characterized by great clinical heterogeneity and complexity. The usual classifications may not adequately characterize this population. Data-driven cluster analysis reveals different possible patient classifications. AimsTo identify different clusters of patients with atrial fibrillation who share similar clinical phenotypes, and to evaluate the association between identified clusters and clinical outcomes, using cluster analysis. MethodsAn agglomerative hierarchical cluster analysis was performed in non-anticoagulated patients from the Loire Valley Atrial Fibrillation cohort. Associations between clusters and a composite outcome comprising stroke/systemic embolism/death and all-cause death, stroke and major bleeding were evaluated using Cox regression analyses. ResultsThe study included 3434 non-anticoagulated patients with atrial fibrillation (mean age 70.3±17 years; 42.8% female). Three clusters were identified: cluster 1 was composed of younger patients, with a low prevalence of co-morbidities; cluster 2 included old patients with permanent atrial fibrillation, cardiac pathologies and a high burden of cardiovascular co-morbidities; cluster 3 identified old female patients with a high burden of cardiovascular co-morbidities. Compared with cluster 1, clusters 2 and 3 were independently associated with an increased risk of the composite outcome (hazard ratio 2.85, 95% confidence interval 1.32–6.16 and hazard ratio 1.52, 95% confidence interval 1.09–2.11, respectively) and all-cause death (hazard ratio 3.54, 95% confidence interval 1.49–8.43 and hazard ratio 1.88, 95% confidence interval 1.26–2.79, respectively). Cluster 3 was independently associated with an increased risk of major bleeding (hazard ratio 1.72, 95% confidence interval 1.06–2.78). ConclusionCluster analysis identified three statistically driven groups of patients with atrial fibrillation, with distinct phenotype characteristics and associated with different risks for major clinical adverse events.

Binding Affinity and Mechanisms of Potential Antidepressants Targeting Human NMDA Receptors.

Depression, a mental disorder that plagues the world, is a burden on many families. There is a great need for new, fast-acting antidepressants to be developed. N-methyl-D-aspartic acid (NMDA) is an ionotropic glutamate receptor that plays an important role in learning and memory processes and its TMD region is considered as a potential target to treat depression. However, due to the unclear binding sites and pathways, the mechanism of drug binding lacks basic explanation, which brings great complexity to the development of new drugs. In this study, we investigated the binding affinity and mechanisms of an FDA-approved antidepressant (S-ketamine) and seven potential antidepressants (R-ketamine, memantine, lanicemine, dextromethorphan, Ro 25-6981, ifenprodil, and traxoprodil) targeting the NMDA receptor by ligand-protein docking and molecular dynamics simulations. The results indicated that Ro 25-6981 has the strongest binding affinity to the TMD region of the NMDA receptor among the eight selected drugs, suggesting its potential effective inhibitory effect. We also calculated the critical binding-site residues at the active site and found that residues Leu124 and Met63 contributed the most to the binding energy by decomposing the free energy contributions on a per-residue basis. We further compared S-ketamine and its chiral molecule, R-ketamine, and found that R-ketamine had a stronger binding capacity to the NMDA receptor. This study provides a computational reference for the treatment of depression targeting NMDA receptors, and the proposed results will provide potential strategies for further antidepressant development and is a useful resource for the future discovery of fast-acting antidepressant candidates.

Measuring Experience of Inpatient Child and Adolescent Mental Health Services (CAMHS).

There has been an important drive towards embedding feedback and experience data to improve health services in the UK. The current paper examines the gap in evidence and the lack of adequate measures of inpatient CAMHS experience. It presents the context of inpatient CAMHS and what factors influence care experience, before exploring the current practices for measuring experience and the implications for young people and families. The paper explores the dialectic that-given the nature of the work balancing risk and restrictions in inpatient CAMHS-it is essential that patient voice is at the centre of quality measures, and achieving this comes with a great complexity. The health needs of adolescents are unique, as are the interventions of psychiatric inpatient care, but current measures in routine use are often not developmentally adapted and lack validity. This paper looks to interdisciplinary theory and practice to consider what the application of a valid and meaningful measure of inpatient CAMHS experience might incorporate. It makes the case that the development of a measure of relational and moral experience of inpatient CAMHS would have significant implications for the quality of care and safety of adolescents during a period of acute crisis.

Dropout among students in higher education: a case study

It is known as a university dropout when a student, for various reasons, abandons his academic training and moves away from the educational system. This problem is very present worldwide, directly affecting the education of many young people and requiring specialists and professionals to find a solution. In this work, the factors that influence university dropout were analyzed according to the perception of students of the faculty of education of the Universidad Nacional Mayor de San Marcos (UNMSM) during the year 2019, for which a questionnaire of 30 items was applied. Given the results obtained, it is possible to affirm that the most influential factors are personal, academic, economic, and institutional. In addition, it was concluded that university dropout is a problem of great complexity that encompasses a wide range of factors that influence a student's academic life in different ways.

Incidence and risk factors for complex regional pain syndrome in radius fractures: meta-analysis.

This meta-analysis aimed to evaluate the incidence and risk factors for complex regional pain syndrome (CRPS) in radius fractures. The meta-analysis was performed using the PubMed, Embase, Scopus, and Cochrane Collaboration Library databases. Studies focusing on patients with conservative or surgically treated radius fractures leading to CRPS were included. A control group consisting of patients with radius fractures and no CRPS (-) was included. The outcome measures were incidence and risk factors. Comparative studies were also included. Data were combined using Review Manager 5.4. Out of 610 studies, nine studies were included. The incidence of CRPS after radius fractures ranged from 0.19 to 13.63% (95% CI: 11.12-16.15%). Open fractures, high-energy mechanisms in radial head fractures, and associations with ulnar fractures were risk factors for CRPS [(RR: 0.98; 95% CI: 0.97-1.00), (RR: 0.18; 95% CI: 0.07-0.47), and (RR: 1.25; 95% CI: 1.17-1.35), respectively]. Other risk factors were female sex and high body mass index [(RR: 1.20; 95% CI: 1.05-1.37) and (MD: 1.17; 95% CI: 0.45-1.88)]. Psychiatric factors also increased the incidence of CRPS (RR: 2.04; 95% CI: 1.83-2.28). On the other hand, the type of surgery (external fixation or open reduction and internal fixation) and manipulations; associated comorbidities (diabetes and hypertension) together with tobacco and alcohol abuse; marital status, educational level, employment status, and socioeconomic status were not risk factors (p > 0.05). The incidence of CRPS in radius fractures was 13.63%. Fractures with greater complexity or greater associated tissue damage, female sex, high BMI, and psychiatric disorders were risk factors for the development of CRPS. Meta-analysis of cohort and case series studies; II.

Examining the differential risk from high-level artificial intelligence and the question of control

Artificial Intelligence (AI) is one of the most transformative technologies of the 21st century. The extent and scope of future AI capabilities remain a key uncertainty, with widespread disagreement on timelines and potential impacts. As nations and technology companies race toward greater complexity and autonomy in AI systems, there are concerns over the extent of integration and oversight of opaque AI decision processes. This is especially true in the subfield of machine learning (ML), where systems learn to optimize objectives without human assistance. Objectives can be imperfectly specified or executed in an unexpected or potentially harmful way. This becomes more concerning as systems increase in power and autonomy, where an abrupt capability jump could result in unexpected shifts in power dynamics or even catastrophic failures. This study presents a hierarchical complex systems framework to model AI risk and provide a template for alternative futures analysis. Survey data were collected from domain experts in the public and private sectors to classify AI impact and likelihood. The results show increased uncertainty over the powerful AI agent scenario, confidence in multiagent environments, and increased concern over AI alignment failures and influence-seeking behavior.

Optimization of the fixed-point representation of measurement data for intelligent measurement systems

The development of intelligent measurement systems by implementing AI (artificial intelligence) algorithms on edge sensor nodes is very topical. Due to very limited hardware of sensor nodes, the choice of the optimal digital format for representation of measurement data and parameters of AI algorithms becomes an important issue. The floating-point format is impractical to implement on sensor nodes due to great complexity, while the fixed-point format has significantly less complexity, representing an ideal solution for intelligent sensor nodes. This paper is dealing with performance analysis and optimization of the fixed-point format for measurement data modeled by the Gaussian distribution. The performance analysis is performed in a generalized way, having wide applicability. Furthermore, the paper proposes a rule for optimization of the fixed-point format, providing a high and almost constant level of quality of the fixed-point representation in a very wide variance range of measurement data. Results are confirmed by simulations.

The Exploration of Identity in the Works of Toni Morrison: An Analytical Study

The subject of identification in Toni Morrison's writing is examined in this study. A well-knownwriter of African descent, Morrison has received numerous honors for works, including theNobel Prize for Literature in 1993. Morrison’s books are renowned for the incisive depictions ofAfrican-American life and the nuanced ways in which history, race, and gender interact to createidentity. The aim of this study is to explore how Morrison's characters deal with identity issuesand the difficulties of existing in a society that is frequently unfriendly to people through ananalysis of the novels. The article focuses in particular on the ways that Morrison's charactersnavigate the conflict between individuality and community and how the characters attempt tobalance the needs and wants with those of respective social and cultural environments. The thesisof the study is that Morrison's writings offer a potent witness to the ongoing fight for selfdetermination and the significance of appreciating the complexity of identity. Morrisonemphasizes the ways in which identity is created by a variety of elements in great storytellingand complex characterizations. The Novels also stresses the significance of embracing andenjoying the various experiences and viewpoints that make up the human experience.

Clinical study of magnetic resonance imaging-based texture analysis and fasciculation of the lateral pterygoid muscle in young patients with temporomandibular disorder

We aimed to evaluate the effectiveness of clinical examination combined with texture analysis of magnetic resonance imaging (MRI) and fasciculation patterns of the lateral pterygoid muscle (LPM) in distinguishing among the different anatomic causes of temporomandibular disorder. We divided the patients into four groups: healthy control (HC), disk without displacement (DWoD), disk displacement with reduction (DDWR), and disk displacement without reduction (DDWoR). Demographic information and clinical symptoms of patients in each group were recorded. LPM textures were compared among groups. LPM fasciculation was examined. P<0.05 indicated significant difference. Several clinical symptoms and signs, but not age or sex, differed significantly among groups. Oblique sagittal planar MRI revealed significant differences in the parameters of Angular Second Moment, Contrast, Correlation, Inverse Difference Moment, and Entropy between the healthy controls and the 3 patient groups. MRI of the patients, both without and with disk displacement, demonstrated relative uniformity in gray distribution and correlation of gray values, with greater complexity but an unclear texture and no obvious regularity. The proportion of type B LPM fascicles was significantly higher in the DDWR and DDWoR groups CONCLUSION: Temporomandibular disorder, without and with disk displacement, is associated with clinical symptoms and texture analysis values that differ from healthy muscle. The types of LPM fascicles are related to the position of the articular disk.

Copper Coins, Catchwords, and Contextual Cues: The Climactic Placement of the Widow’s Mites (Mark 12:41–44)

The story of the widow in the temple with her two small copper coins (Mark 12:41-44) is a familiar one, but recent scholarship has yielded a surprisingly divergent array of interpretative options. In particular, in noting the catchword χήρα (vv. 40,42,43) that links this episode to Jesus’s diatribe against the scribes in the preceding pericope (vv. 38-40), recent scholarship has argued, against the traditionally positive interpretation of this narrative, that this context requires a negative or tragic interpretation. The present study argues that catchwords and other contextual clues link the widow narrative not just with the preceding pericope, but with the whole series of five disputations in the temple (vv. 13-40). With the episode functioning in this way as an epilogue to the whole section, the widow may be seen as both a model of discipleship as well as a tragic figure whose poverty illustrates the failure of the religious leadership. Because catchwords are frequently noted but rarely defined, criteria must first be proposed for their identification and verification. These are then applied to the passage in question to demonstrate the lexical and semantic links between it and the preceding passages. Seen in this context, the widow narrative emerges in both greater clarity and greater complexity, illustrating piety and true discipleship on the one hand, and the tragic failure of the temple cult and its leaders on the other.