Exploring the path of digital governance of urban industrial pollution: empirical evidence from 280 cities in China.

Urban industrial pollution plays a dominant role in environmental pollution in China. Exploring the digital governance path of urban industrial pollution can provide strong support for improving environmental quality. This article empirically investigates the role and path of digitalization in the governance of urban industrial pollution from three dimensions: economic scale, structural scale, and technological scale. The results show that there is an inverted "U"-shaped relationship between digitalization and urban industrial pollution, with initial promotion followed by suppression. Among them, economic scale, industrial transformation and upgrading, and green innovation are the paths for digital governance of urban industrial pollution. In addition, there is a chain path of "green innovation-industrial transformation and upgrading" between the two. Through spatial Durbin model and regional heterogeneity analysis, it is found that digitalization has a spatial spillover effect on urban industrial pollution control, and eastern regions, regions with high economic development level and industrialized cities benefit more from digital urban industrial pollution control. The research conclusions of this article provide references for the Chinese government to formulate relevant policies, deepen the integration of digitalization and urban industrial pollution, and promote digital governance of urban industrial pollution.

[The contribution of the adapted physical activity and health teacher in psychiatry]. / Apports de l'enseignant en activité physique adaptée et santé en psychiatrie.

A teacher of adapted physical activity and health (EAPAS) is a paramedical professional. A professional degree in sciences and techniques of physical and sports activities, with a specialization in adapted physical activity and health, is a prerequisite for this profession. These studies can be supplemented by a professional master's degree. EAPAS practitioners can work in the medico-social, somatic, psychiatric, geriatric and functional rehabilitation sectors. In mental health, they work as part of multi-disciplinary teams, with institutional support. They act on medical prescription to achieve psychological, physical, motivational and social benefits.

Network Structure of Interpersonal Sensitivity in Patients With Mood Disorders: A Network Analysis.

OBJECTIVE: Interpersonal sensitivity, characterized by a heightened awareness of others' behavior and emotions, is linked to mood disorders. However, current literature lacks a comprehensive analysis of how some items of the Interpersonal Sensitivity Measure (IPSM) interrelate and contribute to the overall construct. This study constructed a network for interpersonal sensitivity symptomatology to identify core IPSM items in patients with mood disorders. METHODS: The IPSM, a 36-item self-report scale, was utilized to evaluate interpersonal sensitivity symptoms in 837 participants (major depressive disorder [MDD], n=265; bipolar I disorder [BD I], n=126; and bipolar II disorder [BD II], n=446). We performed exploratory graph analysis, employing regularized partial correlation models to estimate the network structure. Centrality analysis identified core IPSM symptoms for each mood disorder group. Network comparison tests assessed structural differences between the MDD and BD subgroups. RESULTS: Network analysis detected five communities. Item 10 ("I worry about being criticized for things that I have said or done") showed the highest value in strength. Multiple items on "Interpersonal Worry/Dependency" and "Low Self-Esteem" showed high strength centrality. Network structure invariance and global strength invariance test results indicated no significant differences between the MDD and BD subgroups. CONCLUSION: Our findings emphasize the importance of addressing "Interpersonal Worry/Dependency" and "Low Self-Esteem" in the IPSM network among mood disorder patients based on core items of the network. Additionally, targeted treatments and comprehensive strategies in this aspect could be crucial for managing mood disorders.

An intuitionistic fuzzy graph's variation coefficient measure with application to selecting a reliable alliance partner.

Group decision-making (GDM) is crucial in various components of graph theory, management science, and operations research. In particular, in an intuitionistic fuzzy group decision-making problem, the experts communicate their preferences using intuitionistic fuzzy preference relations (IFPRs). This approach is a way that decision-makers rank or select the most desirable alternatives by gathering criteria-based information to estimate the best alternatives using a wider range of knowledge and experience. This article proposes a new statistical measure in a fuzzy environment when the data is ambiguous or unreliable to solve a decision-making problem. This study uses the variation coefficient measure combined with intuitionistic fuzzy graphs (IFG) and Laplacian energy (LE) to solve a GDM problem that utilizes intuitionistic fuzzy preference relations (IFPRs) to select a reliable alliance partner. Initially, the Laplacian energy determines the weight of individual standards, and the obtained weight average further estimates the overall criterion weight vector. We establish the authority criteria weights using the variation coefficient measure and then ultimately rank the alternatives for each criterion using the same measure. We examine four distinct companies Alpha, Beta, Delta, and Zeta to conduct a realistic GDM to choose which alliance partner would be ideal. We successfully implemented the suggested technique, determining that Alpha satisfies company standards and is ranked first among other companies. Moreover, this technique is useful for all kinds of Intuitionistic fuzzy group decision-making problems to select optimal ones.

Elevating Restorative Dentistry: Use of the Art of Stamp Techniques in Mandibular Posterior Regions.

In modern dentistry, restorations that are more aesthetically pleasing have now replaced the amalgam restorations. The "stamp technique" is one of the more recently developed techniques for combining aesthetics and functionality. When caries are visible on radiographs or clinical examinations of teeth with complete marginal ridges and an ideal tooth structure, this method can be used. This novel stamp technique involves creating an index beforehand, which is essentially a miniature impression or negative copy of the occlusal topography. The advantage of the stamp technique is that it replicates the actual occlusion and its anatomy, reducing the need for additional corrections. The amount of time required for the restoration's polishing and finishing is also decreased. In comparison to manual methods, for the posterior teeth, the occlusal stamp is approachable as it is a biomimetic direct composite restoration that helps to restore hidden caries with the impaired occlusal surface. It produces better outcomes as it takes less post-restoration filling adjustments.

Research on entity relation extraction for Chinese medical text.

Currently, the primary challenges in entity relation extraction are the existence of overlapping relations and cascading errors. In addressing these issues, both CasRel and TPLinker have demonstrated their competitiveness. This study aims to explore the application of these two models in the context of entity relation extraction from Chinese medical text. We evaluate the performance of these models using the publicly available dataset CMeIE and further enhance their capabilities through the incorporation of pre-trained models that are tailored to the specific characteristics of the text. The experimental findings demonstrate that the TPLinker model exhibits a heightened and consistent boosting effect compared to CasRel, while also attaining superior performance through the utilization of advanced pre-trained models. Notably, the MacBERT + TPLinker combination emerges as the optimal choice, surpassing the benchmark model by 12.45% and outperforming the leading model ERNIE-Health 3.0 in the CBLUE challenge by 2.31%.

Emotion Regulation, Relationship and Therapeutic Change in Analytical Psychology and Contemporary Psychodynamic Approaches.

All contemporary psychotherapies agree that (failing) emotion regulation is central to psychological disorders and that psychotherapy is about improving emotion regulation. In his research on the "emotion-laden" complex Jung put an emphasis on the role of failing emotion regulation in contributing to psychological disorders as well as to change in the process of psychotherapy, but he left this field of research and took a very different direction in favour of his archetype concept. Psychodynamic approaches generally argue that changes in emotion regulation are accomplished through corrective emotional experiences in the therapeutic relationship. Insights from affective neurosciences and attachment research have had a major influence on how the therapeutic relationship is constructed in contemporary psychodynamic approaches. There is a lack of similar developments in analytical psychology, which leads to substantial differences between the models of Jungian psychotherapy in contrast to other contemporary psychodynamic approaches. The implications of these differences for the practice of psychotherapy and especially the role of the therapeutic relationship are pointed out.

Toutes les psychothérapies actuelles s'accordent sur le fait que la régulation (défaillante) de l'émotion est au centre des désordres psychologiques et que la psychothérapie vise à améliorer la régulation de l'émotion. Dans sa recherche sur le « complexe à haute charge émotionnelle ¼, Jung a mis l'accent sur le rôle de la régulation défaillante de l'émotion comme participant aux désordres psychologiques ainsi qu'au changement dans le processus de psychothérapie. Mais il a abandonné ce champ de recherche et pris une direction très différente, y préférant son concept de l'archétype. Les approches psychodynamiques plaident généralement en faveur de l'idée que les changements dans la régulation de l'émotion sont atteints par les expériences émotionnelles corrective dans la relation thérapeutique. Des apports venant des neurosciences affectives et des recherches sur l'attachement ont eu une influence majeure sur comment la relation thérapeutique est construite dans les approches psychodynamiques actuelles. De tels développements font défaut dans la psychologie analytique, ce qui conduit à des différences considérables entre les modèles de psychothérapie jungienne en contraste avec les autres approches psychodynamiques actuelles. L'article souligne les conséquences de ces différences dans la pratique de la psychothérapie, tout particulièrement en ce qui concerne le rôle de la relation thérapeutique.

Todas las psicoterapias contemporáneas coinciden en que la regulación (fallida) de las emociones es central a los trastornos psicológicos y que la psicoterapia consiste en mejorar la regulación de las emociones. En su investigación sobre el complejo "de tonalidad afectiva", Jung hizo hincapié en el rol de una fallida regulación emocional en el desarrollo de los trastornos psicológicos, así como al cambio en el proceso de psicoterapia, pero abandonó este campo de investigación y tomó una dirección muy diferente en favor de su concepto de arquetipo. En general, los enfoques Psicodinámicos sostienen que los cambios en la regulación de las emociones se logran a través de experiencias emocionales correctivas en la relación terapéutica. Los conocimientos de las neurociencias afectivas y la investigación sobre el apego han tenido una gran influencia en cómo comprender la conformación de la relación terapéutica en los abordajes psicodinámicos contemporáneos. Faltan desarrollos similares en la psicología analítica, lo que conduce a diferencias sustanciales entre los modelos de la psicoterapia Junguiana en contraste con otros enfoques psicodinámicos contemporáneos. Se señalan las implicaciones de estas diferencias para la práctica de la psicoterapia y se destaca especialmente el rol de la relación terapéutica.

A novel constraint-based structure learning algorithm using marginal causal prior knowledge.

Causal discovery with prior knowledge is important for improving performance. We consider the incorporation of marginal causal relations, which correspond to the presence or absence of directed paths in a causal model. We propose the Marginal Prior Causal Knowledge PC (MPPC) algorithm to incorporate marginal causal relations into a constraint-based structure learning algorithm. We provide the theorems of conditional independence properties by combining observational data and marginal causal relations. We compare the MPPC algorithm with other structure learning methods in both simulation studies and real-world networks. The results indicate that, compare with other constraint-based structure learning methods, MPPC algorithm can incorporate marginal causal relations and is more effective and more efficient.

Hybrid-resolution facial and dental scanning: a cost-effective approach to utilizing 3D facial data in anterior dental implant restoration.

As digital technology becomes more prevalent in the practice of dental medicine, methods to fully replace 2-dimensional photography and analog devices such as the facebow are still in their infancy. As more practices adopt 3-dimensional (3D) intraoral scanners, effective digital communication of the relationships between the teeth and the face becomes essential. With the high cost of intraoral scanners, the additional expense of a face scanner is not a feasible investment for many practices. This article explores a technique for meshing (lower resolution) facial data obtained from a smartphone-based scanner with high-resolution intraoral scan data. In this approach, the data from a free 3D scanning application on a smartphone and a traditional intraoral scanner are meshed so that high-resolution data are available for intraoral features and lower resolution data are used to capture the gross contours of the face. In this way, a hybrid-resolution composite scan that incorporates all of the data needed to simulate the face and accurately reproduce the teeth is generated without the cost of additional scanning equipment. This article defines a new term, the facial registration scan, for use alongside the familiar digital bite registration obtained with an intraoral scanner. To illustrate the clinical use of the hybrid-resolution scan concept, this article presents a case in which this method was used for the restoration of maxillary anterior implants.

A cost-sensitive decision model for efficient pooled testing in mass surveillance of infectious diseases like COVID-19.

The COVID-19 pandemic has imposed significant challenges on global health, emphasizing the persistent threat of large-scale infectious diseases in the future. This study addresses the need to enhance pooled testing efficiency for large populations. The common approach in pooled testing involves consolidating multiple test samples into a single tube to efficiently detect positivity at a lower cost. However, what is the optimal number of samples to be grouped together in order to minimize costs? i.e. allocating ten individuals per group may not be the most cost-effective strategy. In response, this paper introduces the hierarchical quotient space, an extension of fuzzy equivalence relations, as a method to optimize group allocations. In this study, we propose a cost-sensitive multi-granularity intelligent decision model to further minimize testing costs. This model considers both testing and collection costs, aiming to achieve the lowest total cost through optimal grouping at a single layer. Building upon this foundation, two multi-granularity models are proposed, exploring hierarchical group optimization. The experimental simulations were conducted using MATLAB R2022a on a desktop with Intel i5-10500 CPU and 8G RAM, considering scenarios with a fixed number of individuals and fixed positive probability. The main findings from our simulations demonstrate that the proposed models significantly enhance the efficiency and reduce the overall costs associated with pooled testing. For example, testing costs were reduced by nearly half when the optimal grouping strategy was applied, compared to the traditional method of grouping ten individuals. Additionally, the multi-granularity approach further optimized the hierarchical groupings, leading to substantial cost savings and improved testing efficiency.

An interdisciplinary integrated specialized one-stop outpatient clinic for idiopathic intracranial hypertension - a comprehensive assessment of patient satisfaction.

BACKGROUND: Management of idiopathic intracranial hypertension (IIH) is complex requiring contributions from multiple specialized disciplines. In practice, this creates considerable organizational and communicational challenges. To meet those challenges, we established an interdisciplinary integrated outpatient clinic for IIH with a central coordination and a one-stop concept. Here, we aimed to evaluate effects of this one-stop concept on subjective patient satisfaction and economic outcome in patients with IIH. METHODS: In a retrospective cohort study, we compared the one-stop era with integrated care (IC, 1-JUL-2021 to 31-DEC-2022) to a reference group receiving standard care (SC, 1-JUL-2018 to 31-DEC-2019) regarding subjective patient satisfaction (assessed by the Vienna Patient Inventory). Multivariable binary linear regression models were used to adjust for confounders. RESULTS: Baseline characteristics of the IC group (n = 85) and SC group (n = 81) were comparable (female: 90.6% vs. 90.1%; mean age: 33.6 vs. 32.8 years, educational level: ≥9 years of education 60.0% vs. 59.3%; located in Vienna 75.3% vs. 76.5%). Compared to SC, management within IC concept was associated with statistically significantly higher subjective patient satisfaction (beta = 0.93; p < 0.001) with the strongest effects observed in satisfaction with treatment accessibility and availability (beta = 2.05; p < 0.001). Subgroup analyses of patients with migration background and language barrier consistently indicated stronger effects of IC in these groups. CONCLUSIONS: Interdisciplinary integrated management of IIH statistically significantly and clinically meaningfully improves patient satisfaction - particularly in socioeconomically underprivileged patient groups. Providing structured central coordination to facilitate and improve access to interdisciplinary management provides means to further improve outcome.

Reconstruct incomplete relation for incomplete modality brain tumor segmentation.

Different brain tumor magnetic resonance imaging (MRI) modalities provide diverse tumor-specific information. Previous works have enhanced brain tumor segmentation performance by integrating multiple MRI modalities. However, multi-modal MRI data are often unavailable in clinical practice. An incomplete modality leads to missing tumor-specific information, which degrades the performance of existing models. Various strategies have been proposed to transfer knowledge from a full modality network (teacher) to an incomplete modality one (student) to address this issue. However, they neglect the fact that brain tumor segmentation is a structural prediction problem that requires voxel semantic relations. In this paper, we propose a Reconstruct Incomplete Relation Network (RIRN) that transfers voxel semantic relational knowledge from the teacher to the student. Specifically, we propose two types of voxel relations to incorporate structural knowledge: Class-relative relations (CRR) and Class-agnostic relations (CAR). The CRR groups voxels into different tumor regions and constructs a relation between them. The CAR builds a global relation between all voxel features, complementing the local inter-region relation. Moreover, we use adversarial learning to align the holistic structural prediction between the teacher and the student. Extensive experimentation on both the BraTS 2018 and BraTS 2020 datasets establishes that our method outperforms all state-of-the-art approaches.

Navigating obstetric bad news: Insights from tertiary care medical teams.

OBJECTIVES: To analyze the self-reported perception of obstetric medical teams regarding the practice of delivering bad news in public and private hospitals. METHODS: Cross-sectional study considering physicians delivering obstetric care at the Municipal Hospital Vila Santa Catarina, Municipal Hospital Dr. Moysés Deutsch, and Albert Einstein Israelite Hospital, in São Paulo, Brazil. The applied questionnaire reflected the steps of the SPIKES protocol for delivering difficult news, with the questions adapted to obstetric and fetal medicine practice context. RESULTS: Specialists self-reported higher levels of knowledge, better emotional management, and superior strategy planning and summarization skills than residents. Participants with more than five years of experience reported higher knowledge levels, better emotional management, and superior strategy development skills. When comparing professionals from private and public hospitals, no significant differences emerged in self-reported communication aspects. CONCLUSIONS: Experience duration significantly influences professionals' impressions in their ability to provide information, manage emotions, and plan post-diagnosis. Specialists and those with more years of experience self-report enhanced readiness in executing communication steps effectively. PRACTICE IMPLICATIONS: Our findings underscore the importance of tailored training and experience in navigating sensitive medical conversations in the field of Obstetrics.

Wave propagation in tailored metastructures consisting of elastic beams and rigid bodies.

This paper presents a study of wave propagation through an infinite periodic structure that consists of elastic Timoshenko beams interconnected with rigid bodies. This is a generalized approach in which the beams are not coaxial and the centre of mass of each rigid body is placed away from the intersection of their neutral axes. An analytical approach is used by applying the transfer matrix method (TMM), along with the Floquet-Bloch theorem for elastic wave propagation. Subsequent parametric analysis is performed with visualization of resulting band diagrams of a representative structure. These results are verified through comparison with solutions obtained using the finite-element method (FEM). In this manner, a comprehensive dynamical analysis of tailored metastructures is provided.This article is part of the theme issue 'Current developments in elastic and acoustic metamaterials science (Part 2)'.

Low Ventricular Stiffness Is Associated With Suboptimal Outcomes in Patients With a Single Right Ventricle After the Fontan Operation: A Novel Phenotype.

BACKGROUND: Despite a rigorous screening process, including cardiac catheterization, a subset of patients with a single right ventricle (SRV) demonstrates suboptimal short-term outcomes after the Fontan operation. The goal of this study was to perform a comprehensive assessment of diastolic function in pre-Fontan patients with an SRV using invasive reference-standard measures and determine their associations with post-Fontan outcomes. METHODS AND RESULTS: Children aged 2 to 6 years with SRV physiology undergoing pre-Fontan heart catheterization were recruited prospectively. Patients were divided into those who had an optimal or suboptimal outcome. A suboptimal outcome was defined as length of stay ≥14 days or heart transplant/cardiac death in first year after Fontan. Patients underwent pressure-volume loop analysis using reference-standard methods. The measure of ventricular stiffness, ß, was obtained via preload reduction. Cardiac magnetic resonance imaging for extracellular volume and serum draws for matrix metalloproteinase activity were performed. Of 19 patients with an SRV, 9 (47%) had a suboptimal outcome. Mean age was 4.2±0.7 years. Patients with suboptimal outcomes had lower ventricular stiffness (0.021 [0.009-0.049] versus 0.090 [0.031-0.118] mL-1; P=0.02), lower extracellular volume (25% [28%-32%] versus 31% [28%-33%]; P=0.02), and lower matrix metalloproteinase-2 (90 [79-104] versus 108 [79-128] ng/mL; P=0.01) compared with patients with optimal outcomes. The only invasive measure that had an association with suboptimal outcome was ß (P=0.038). CONCLUSIONS: Patients with an SRV with suboptimal outcome after the Fontan operation had lower ventricular stiffness and evidence of maladaptive extracellular matrix metabolism compared with patients with optimal outcome. This appears to be a novel phenotype that may have important clinical implications and requires further study.

Selection of appropriate location based on signed distance based ranking approach with interval type-2 trapezoidal fuzzy preference relations.

In real life situation, it is often difficult to judge the relative importance of different parameters being considered for evaluating some alternatives. In the context of fuzzy sets, it is a situation where it is difficult to define precise membership grades for attribute values. Here we require more generalized type of fuzzy sets which have a greater representational power than ordinary fuzzy sets. For this purpose we use "interval type-2 trapezoidal fuzzy preference relations (IT2TrFPRs)" in this article as a generalization of fuzzy preference relations and consider the environment discussed above, where there is no information on priority weights. A collective decision matrix will be constructed on the basis of hybrid averages using weighted averaging and signed distance based OWA operation. Then a least deviation model will be employed in order to determine the priority weight vectors. Finally, the alternatives will be ranked on the basis of weighted normalized signed distance of each alternative from the ideal solution. Moreover, a real life example of location selection is illustrated to elaborate the effectiveness of the proposed scheme.

A digital workflow for full-mouth rehabilitation using CAD-CAM tooth reduction template.

A digital workflow is presented for multiple transfers of targeted jaw relation and restorative spaces from interim to definitive restorations in patients with severe tooth wear. Following analysis of the targeted restorative space, segmented arch stereolithographic templates were digitally created and fabricated for precise control of reduction depth. Then, the jaw relation was transferred from the initially determined stabilization splint to the temporary fixed restoration and definitive restoration by using a digital articulator. This digital approach yielded a stabilized jaw relationship and restorative spaces transferring effect throughout successive stages of occlusal reconstruction resulting in satisfactory prosthetic outcomes.

A dendrite is a dendrite is a dendrite? Dendritic signal integration beyond the "antenna" model.

Neurons in central nervous systems receive multiple synaptic inputs and transform them into a largely standardized output to their target cells-the action potential. A simplified model posits that synaptic signals are integrated by linear summation and passive propagation towards the axon initial segment, where the threshold for spike generation is either crossed or not. However, multiple lines of research during past decades have shown that signal integration in individual neurons is much more complex, with important functional consequences at the cellular, network, and behavioral-cognitive level. The interplay between concomitant excitatory and inhibitory postsynaptic potentials depends strongly on the relative timing and localization of the respective synapses. In addition, dendrites contain multiple voltage-dependent conductances, which allow scaling of postsynaptic potentials, non-linear input processing, and compartmentalization of signals. Together, these features enable a rich variety of single-neuron computations, including non-linear operations and synaptic plasticity. Hence, we have to revise over-simplified messages from textbooks and use simplified computational models like integrate-and-fire neurons with some caution. This concept article summarizes the most important mechanisms of dendritic integration and highlights some recent developments in the field.

Integrating graph convolutional networks to enhance prompt learning for biomedical relation extraction.

BACKGROUND AND OBJECTIVE: Biomedical relation extraction aims to reveal the relation between entities in medical texts. Currently, the relation extraction models that have attracted much attention are mainly to fine-tune the pre-trained language models (PLMs) or add template prompt learning, which also limits the ability of the model to deal with grammatical dependencies. Graph convolutional networks (GCNs) can play an important role in processing syntactic dependencies in biomedical texts. METHODS: In this work, we propose a biomedical relation extraction model that fuses GCNs enhanced prompt learning to handle limitations in syntactic dependencies and achieve good performance. Specifically, we propose a model that combines prompt learning with GCNs for relation extraction, by integrating the syntactic dependency information analyzed by GCNs into the prompt learning model, by predicting the correspondence with [MASK] tokens labels for relation extraction. RESULTS: Our model achieved F1 scores of 85.57%, 80.15%, 95.10%, and 84.11% in the biomedical relation extraction datasets GAD, ChemProt, PGR, and DDI, respectively, all of which outperform some existing baseline models. CONCLUSIONS: In this paper, we propose enhancing prompt learning through GCNs, integrating syntactic information into biomedical relation extraction tasks. Experimental results show that our proposed method achieves excellent performance in the biomedical relation extraction task.

A Deterministic Method to Construct a Common Supercell Between Two Similar Crystalline Surfaces.

Here, a deterministic algorithm is proposed, that is capable of constructing a common supercell between two similar crystalline surfaces without scanning all possible cases. Using the complex plane, the 2D lattice is defined as the 2D complex vector. Then, the relationship between two surfaces becomes the eigenvector-eigenvalue relation where an operator corresponds to a transformation matrix. It is shown that this transformation matrix can be directly determined from the lattice parameters and rotation angle of the two given crystalline surfaces with O(log Nmax) time complexity, where Nmax is the maximum index of repetition matrix elements. This process is much faster than the conventional brute force approach ( O ( N max 4 ) $O(N_{\mathrm{max}}^4)$ ). By implementing the method in Python code, experimental 2D heterostructures and their moiré patterns and additionally find new moiré patterns that have not yet been reported are successfully generated. According to the density functional theory (DFT) calculations, some of the new moiré patterns are expected to be as stable as experimentally-observed moiré patterns. Taken together, it is believed that the method can be widely applied as a useful tool for designing new heterostructures with interesting properties.