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Purpose. As a scientific field, bioinformatics has drawn remarkable attention from various fields, such as information technology, mathematics, and modern biological sciences, in recent years. The topic models originating from the field of natural language processing have become the focus of attention with the rapid accumulation of biological datasets. Thus, this research is aimed at modeling the topic content of the bioinformatics literature presented by Iranian researchers in the Scopus Citation Database. Methodology. This research was a descriptive-exploratory study, and the studied population included 3899 papers indexed in the Scopus database, which had been indexed in this database until March 9, 2022. The topic modeling was then performed on the abstracts and titles of the papers. A combination of LDA and TF-IDF was utilized for topic modeling. Findings. The data analysis with topic modeling resulted in identifying seven main topics "Molecular Modeling," "Gene Expression," "Biomarker," "Coronavirus," "Immunoinformatics," "Cancer Bioinformatics," and "Systems Biology." Moreover, "Systems Biology" and "Coronavirus" had the largest and smallest clusters, respectively. Conclusion. The present investigation demonstrated an acceptable performance for the LDA algorithm in classifying the topics included in this field. The extracted topic clusters indicated excellent consistency and topic connection with each other. [ABSTRACT FROM AUTHOR]

Background. In addition to the usual difficulty of managing human capital in any organization, healthcare institutions have other problems to solve arising from the circumstances and the very nature of the work they perform, such as the ethical pressure on staff, emotional exhaustion, the distribution of work shifts, or the general shortage for nurses. In many cases, this situation has an impact on the quality of care. Objective. The main objective of this research is to compile, in a single document, human resource practices that help health centre managers improve results in terms of performance and quality of care, as well as avoid the intention of abandoning the job, specifically related to the work of nurses. Methods. To this end, a systematic literature review has been performed based on 229 papers published in the Web of Science database, from which the practical implications for nurses proposed by these authors have been extracted. Results. The main results suggest that developing affective commitment helps to improve organizational performance and enhance patient safety culture. Furthermore, improving communication and meaningfulness of work, recognition by superiors, or job flexibility would improve the quality of outcomes, for the work of nurses. Conclusions and Implications for Nursing. Stimulating normative commitment, reducing excessive control, and paying attention to job burnout and job stress help combat the intention of voluntary turnover or leaving the job, especially in the case of nurses. [ABSTRACT FROM AUTHOR]

Mobile Healthcare Social Media (MHSM) is an innovative combination of mobile devices and mobile communication technology. How can users shift from spontaneous to conscious cognitive mode, break their usage inertia, and actively adapt to the social structure of mobile health social media to improve information-sharing performance? This study uses adaptive structuring theory as the theoretical foundation to deeply analyze adaptive information-sharing behavior and its specific forms in the mHealth social media environment; it uses cognitive shift theory and social exchange theory as the theoretical framework to comprehensively explore the antecedent motivations of users engaging in adaptive information-sharing behavior and its posterior effects. Theoretically, it promotes the innovation and development of information-sharing behavior research and the further deepening of the application of adaptive structuring theory at the information behavior level. It is also conducive to bridging the digital divide and maximizing the value of health information resources. This paper takes 1000 survey data as the experimental data source for studying the influence of mobile social media sharing behavior on the subjective well-being and mental health regulation of Internet users and concludes that in practice, it is beneficial to optimize the design of information-sharing-related functions in mobile health social media, improve the effect of user information sharing in mobile health social media environment, and enhance the efficiency of information sharing so that mobile social media sharing behavior can better contribute to the subjective well-being and mental health regulation of Internet users. This paper has an obvious psychological adjustment effect on groups who use too much social media and can help them analyze why they are affected by some social media, thereby producing psychological effects. [ABSTRACT FROM AUTHOR]

Building a new development pattern based on the "double-cycle" is a major strategic plan of China. Under the background of the new development pattern of the "double-cycle" and the context of environmental constraints, this paper tries to explore the impact of marine economic development on marine cultural industry and marine innovation development, the extent of the impact of marine cultural industry on marine economic growth, and the internal relationship between them under the new development pattern of double circulation. In this paper, Fujian Province is taken as the research object to construct an indicator system of the marine culture development to reflect the living standard, employment level, and spiritual and cultural levels of people in the marine area, and the external influence of the marine economy and marine culture industry is taken as the indicator variable to measure the integrated development. The internal changes are regarded as the index to assess the integration level of the two, and the evaluation theoretical model of the dynamic evolution level of the marine economy and marine cultural industry is constructed. The vector autoregression model and impulse response function are used to study the interactive correlation between the growth of the marine economy and the development of the cultural industry. The results show the following: In the long run, there is a cointegration relationship between the marine culture industry and the gross ocean product (GOP), which is a long-term balanced and stable relationship. The development level of the marine economy and the development of marine culture industry are mutually influencing and promoting. [ABSTRACT FROM AUTHOR]

Preferential access to scarce resources can bring competitive advantages and better performance to enterprises. However, the existing literature has a relatively single research path on the influencing factors of enterprise resource access, which has lack of sufficient research from the perspective of multidimensional environment. In particular, as an important factor affecting enterprises' access to external resources, few studies have given empirical results on the impact of political factors such as government structure on enterprise resource access. Preferential access to scarce resources can bring competitive advantages and better performance to enterprises. However, the existing literature has a relatively single research path on the influencing factors of enterprise resource access, which lacks sufficient research from the perspective of multidimensional environment. In particular, as an important factor affecting enterprises' access to external resources, few studies have given empirical results on the impact of political factors such as government structure on enterprise resource access. Through the discussion of multidimensional environmental factors, this paper can provide theoretical reference for the reform of government institutions and the establishment of good political relations between enterprises and the government. Focusing on the multidimensional environment of government structure, political relations, and enterprise resource acquisition, this paper takes 129 enterprises in Central China as samples and uses the structural equation model to empirically verify the relationship between the formalization of government structure, liaison mechanism, decentralization, and enterprise resource acquisition, especially the easing effect of political relations. The results show that the formalization of government structure is promoting enterprises to obtain policy resources and financial resources; the liaison mechanism helps enterprises to obtain financial resources and market resources; decentralization has a significant positive impact on enterprises' access to policy resources and market resources; and political connection magnifies the positive effect of government structure on enterprise resource acquisition, but there are differences in different dimensions. [ABSTRACT FROM AUTHOR]

Based on the knowledge organization method, this paper explores the construction method of the traditional Chinese medicine (TCM) clinical knowledge coding model by taking TCM clinical electronic medical record data as the research object. Firstly, extracting technology is used to obtain the required data in the electronic medical record. Then, by constructing the clinical knowledge coding model, the tacit knowledge is made explicit, establishing the clinical knowledge base and exploring the connotation of TCM clinical knowledge. It provides necessary data resources for deepening the expression level of TCM clinical knowledge, constructing accurate TCM clinical diagnosis, intervention, and evaluation models, and promoting the inheritance, innovation, and development of TCM. In this paper, we extracted the data of 318 cases of distention and established the TCM clinical database from the basic information of patients, clinical diagnosis information, clinical diagnosis and treatment information, and clinical evaluation information. Based on the knowledge coding model and the connotation of knowledge attributes, the established TCM clinical knowledge base was to explore the law of TCM clinical precision diagnosis and treatment. [ABSTRACT FROM AUTHOR]

This paper aims to establish strategies of coping with COVID-19 pandemic adopted by the clients of social assistance from the perspective of social workers. The qualitative research among Polish social workers and family assistants was conducted from September to November 2021. Based on 30 in-depth interviews with social work professionals, groups of social assistance clients' behaviours were identified and classified into the theoretical models of reactions to social change by Merton and Giddens. The following types of behaviour have been selected and categorized into four groups of reactions when dealing with social workers in a pandemic situation: coolheaded calculation, defiance, confusion, and adaptation. At the same time, reactions to the situation of social change were categorized into one of the strategies of active or passive behaviour: innovation, contestation, retreat, and acceptance. In addition, we discussed the impact of clients' coping strategies on social workers and established three attitudes of the surveyed social workers: adapting to the pandemic situation and customer behaviour, assuming the role of an emotional buffer and informant, and expecting support from superiors and coworkers. Knowing the behaviour of social assistance clients in a challenging situation makes it possible to adopt tailor-made measures. [ABSTRACT FROM AUTHOR]

Rehabilitation nursing teaching is one of the key points of nursing teaching. The quality of rehabilitation nursing teaching directly affects the comprehensive ability of clinical interns. Therefore, teachers must further deepen the reform of clinical nursing teaching, improve the teaching system, and explore effective clinical nursing teaching methods. This paper introduces the application of the network teaching mode based on sandwich in rehabilitation nursing teaching, which provides guidance and help for the clinical nursing teaching mode. Through sandwich teaching activities for third year students of the nursing department, taking mastering theoretical knowledge, changing critical thinking ability, and changing learning initiative as indicators, this paper analyzes the sandwich teaching mode and discusses the cultivation of nursing students' ability. The experimental results showed that after the intervention, there was a statistically significant difference in the learning initiative of students in the experimental group (t = − 29.713 , p ≤ 0.001). After the intervention, there was a significant difference in the learning initiative of the control group (t = − 3.368 , p ≤ 0.001). [ABSTRACT FROM AUTHOR]

In order to solve the problem of resource ecological compensation, this paper proposed a model of resource ecological compensation mechanism based on a rural leisure sports environment. The model is carried out in many places in China. The survey data involves 31 provinces, 10 years, and 43 indicators, with a total of 43 × 10 × 31 = 13,330 data. The preliminary basis of mechanism construction is summarized from four aspects. Finally, make full use of modern information technology to improve the network platform of the compensation mechanism, promote the efficient allocation and comprehensive utilization of ecotourism resources, and lay a solid foundation for establishing a reasonable and perfect resource ecological compensation mechanism and ensuring the long-term and stable operation of the mechanism. Through the experiment, it is found that the timely and effective publication of information can eliminate the inner estrangement between the two sides, so as to make the behavior of both sides more rational. A special information feedback department is established to deal with the opinions put forward by all compensation parties in tourism development, extract effective information, summarize and publish reasonable guidance information, and guide the compensation of both sides to an ideal balance through the feedback of this information. The effectiveness of the experiment is verified. [ABSTRACT FROM AUTHOR]

The main semantic symbol systems for people to express their emotions include natural language and music. The analysis and establishment of semantic association between language and music is helpful to provide more accurate retrieval and recommendation services for text and music. Existing researches mainly focus on the surface symbolic features and association of natural language and music, which limits the performance and interpretability of applications based on semantic association of natural language and music. Emotion is the main meaning of music expression, and the semantic range of text expression includes emotion. In this paper, the semantic features of music are extracted from audio features, and the semantic matching model of audio emotion analysis is constructed to analyze ethnic music audio emotion through feature extraction ability of deep structure. The model is based on the framework of emotional semantic matching technology and realizes the emotional semantic matching of music fragments and words through semantic emotional recognition algorithm. Multiple experiments show that when W = 0.65 , the recognition rate of multichannel fusion model is 88.42%, and the model can reasonably realize audio emotion analysis. When the spatial dimension of music data changes, the classification accuracy reaches the highest when the spatial dimension is 25. Analysing the semantic association of audio promotes the application of folk music in occupational therapy. [ABSTRACT FROM AUTHOR]

This paper adopts the method of psychological data analysis to conduct in-depth research and analysis on the correlation between teachers' classroom teaching behaviors and students' knowledge acceptance. Firstly, this paper proposes a health factor prediction model, which is specifically divided into clustering and then classification model and a clustering and classification synthesis model. The classroom learning process is coded, sampled, and quantified to obtain data on students' learning behaviors, and a visualization system based on classroom students' learning behaviors is designed and developed to record and analyze students' behaviors in the classroom learning process and grasp students' classroom learning. These two models use algorithms to fine-grained divide the dataset from the perspective of subject users and mental health factors, respectively, and then use decision tree algorithms to classify and predict the mental health factor information by the subject user base information. Second, based on the collected datasets, we designed comparison experiments to validate the clustering-then-classification model and the integrated clustering-classification model and selected the optimal model for comparison. Teachers should increase effective praise and encouragement behaviors; teachers should increase meaningful teacher-student interaction behaviors; teachers should be proficient in teaching media technology to reduce unnecessary time wastage. Strategies to enhance teachers' TPACK include enriching teachers' knowledge base of CK, TK, and PK; developing teachers' integration thinking; and enriching teachers' types of activities for integrating technology. [ABSTRACT FROM AUTHOR]

Background. The practice of traditional Chinese medicine (TCM) began several thousand years ago, and the knowledge of practitioners is recorded in paper and electronic versions of case notes, manuscripts, and books in multiple languages. Developing a method of information extraction (IE) from these sources to generate a cohesive data set would be a great contribution to the medical field. The goal of this study was to perform a systematic review of the status of IE from TCM sources over the last 10 years. Methods. We conducted a search of four literature databases for articles published from 2010 to 2021 that focused on the use of natural language processing (NLP) methods to extract information from unstructured TCM text data. Two reviewers and one adjudicator contributed to article search, article selection, data extraction, and synthesis processes. Results. We retrieved 1234 records, 49 of which met our inclusion criteria. We used the articles to (i) assess the key tasks of IE in the TCM domain, (ii) summarize the challenges to extracting information from TCM text data, and (iii) identify effective frameworks, models, and key findings of TCM IE through classification. Conclusions. Our analysis showed that IE from TCM text data has improved over the past decade. However, the extraction of TCM text still faces some challenges involving the lack of gold standard corpora, nonstandardized expressions, and multiple types of relations. In the future, IE work should be promoted by extracting more existing entities and relations, constructing gold standard data sets, and exploring IE methods based on a small amount of labeled data. Furthermore, fine-grained and interpretable IE technologies are necessary for further exploration. [ABSTRACT FROM AUTHOR]

Moxibustion is a thermal therapy in traditional Chinese medicine that relies on the heat from burning moxa to be transferred beneath the skin surface. Although moxibustion has long been in widespread practice, the mechanism of heat transfer modality and temperature distribution during this treatment is not yet well understood. The current paper presents the first examination by magnetic resonance imaging (MRI) of the three-dimensional temperature elevation during moxibustion treatment. A mathematical model for the prediction of temperature elevation during moxibustion therapy has been constructed and compared with the experimental data. Good agreement between the measured temperature and the results of numerical calculations has been found. Tissue up to 3 cm deep can be heated during the treatment. It was revealed that both heat conduction and radiation heat transfer play important roles during the treatment. The results presented in the current paper can be used for understanding the mechanisms of Chinese medicine and developing useful guidelines for Chinese medicine doctors. [ABSTRACT FROM AUTHOR]

This paper addresses the mixture symptom mention problem which appears in the structuring of Traditional Chinese Medicine (TCM). We accomplished this by disassembling mixture symptom mentions with entity relation extraction. Over 2,200 clinical notes were annotated to construct the training set. Then, an end-to-end joint learning model was established to extract the entity relations. A joint model leveraging a multihead mechanism was proposed to deal with the problem of relation overlapping. A pretrained transformer encoder was adopted to capture context information. Compared with the entity extraction pipeline, the constructed joint learning model was superior in recall, precision, and F1 measures, at 0.822, 0.825, and 0.818, respectively, 14% higher than the baseline model. The joint learning model could automatically extract features without any extra natural language processing tools. This is efficient in the disassembling of mixture symptom mentions. Furthermore, this superior performance at identifying overlapping relations could benefit the reassembling of separated symptom entities downstream. [ABSTRACT FROM AUTHOR]

This paper reviews the hypothesis of harmonic cancellation according to which an interfering sound is suppressed or canceled on the basis of its harmonicity (or periodicity in the time domain) for the purpose of Auditory Scene Analysis. It defines the concept, discusses theoretical arguments in its favor, and reviews experimental results that support it, or not. If correct, the hypothesis may draw on time-domain processing of temporally accurate neural representations within the brainstem, as required also by the classic equalization-cancellation model of binaural unmasking. The hypothesis predicts that a target sound corrupted by interference will be easier to hear if the interference is harmonic than inharmonic, all else being equal. This prediction is borne out in a number of behavioral studies, but not all. The paper reviews those results, with the aim to understand the inconsistencies and come up with a reliable conclusion for, or against, the hypothesis of harmonic cancellation within the auditory system. [ABSTRACT FROM AUTHOR]

The sustainable development of smart community is the key to China's grassroots governance and also the general trend of China's urban modernization. In the supervision of the smart community, the optimization of the behavior of the regulatory subject cannot be separated. Previous studies have focused more on how subjects participate in supervision and less on the behavior of stakeholders in the game. This paper analyzes the game behavior of regulatory participants in the process of sustainable development of smart community and studies the optimization strategy of regulatory behavior according to the game behavior logic among participants. The results show the following. (i) Government behavior plays a leading role in supervision. (ii) When the government invests resources in the screening of third-party evaluation agencies and service purchase and mainly adopts policy punishment methods for stakeholders with rent-seeking behavior, the probability of regulatory participation stakeholders' positive behavior is the greatest. (iii) The improvements should be made from the aspects of information network construction, the refinement of reward and punishment measures, and the improvement of evaluation party access rules. This not only helps to enhance the good supervision situation of the supervision enthusiasm of the participants but also can realize the self-discipline operation of the smart community and enhance the responsibility consciousness of the evaluation institutions. [ABSTRACT FROM AUTHOR]

Smart grids, which possess flexibility, cleanliness, safety, economy, and friendliness, have drawn a lot of attention from all over the world in an era of rapid social and economic development, power technology change, and energy and environmental constraints. However, there are still issues with the design, installation, and operation of smart substations, such as insufficient LAN integration, difficulty quantifying network performance, and inability to keep track of communication. The basic meaning and key technologies of substation communication standards are used as the research object in this paper, and the basic attributes of substation data flow, such as source, type, and function, are qualitatively analyzed. The mathematical model that is most closely fitted is 2.8% more effective. The research object is the topology of the process bus. Through the comparison of various solutions, including star topology, ring topology, bus topology, and mesh topology, the advantages and disadvantages of each topology networking scheme are revealed along with the particular functional requirements of the substation process layer. Further discussion is given to the crucial topology-related technologies of network congestion and flow control. [ABSTRACT FROM AUTHOR]

This paper uses the theory of mental health education to conduct an in-depth study and analysis of teachers' educational management, and based on this, it designs a survey method on teachers' status and analyzes its strategic methods based on the results of the survey. Using literature analysis, questionnaires, survey interviews, and statistical analysis, the analysis of mental health of primary and secondary school teachers in the city was made. The results of the survey and analysis of the questionnaire results were used to construct a compatible mental health evaluation model. It was found that the overall level of elementary school teachers' mental health is poor at present, and different levels of mental health were presented with school sections and ages. A total of 286 questionnaires were distributed, 278 valid questionnaires were returned, and statistical analysis was conducted using EXCEL tables based on the collected data. The data analysis results show that the mental health level of teachers in middle school is significantly lower than that of teachers in primary school, and the mental health level of teachers in primary and secondary schools decreases with the increase of age. Therefore, to prevent the small and the gradual, start from the source; do a good job in the publicity of mental health education in peacetime; popularize the knowledge of mental health, so that teachers have a correct understanding of mental health education; improve the professional level of teachers; set up professional teachers in professional positions; establish sound job system and evaluation system, etc. Promote the balanced development of school psychological counseling rooms, strengthen the construction of professional teachers in mental health education, improve various systems of mental health education, comprehensively popularize teachers' mental health education and training, and mobilize teachers' enthusiasm for scientific research on mental health education. Improve the understanding of mental health education in colleges and universities, and regard mental health education as the foundation of all education. [ABSTRACT FROM AUTHOR]

As the competition between enterprises intensifies, employees have witnessed a decline of psychological health year by year and severe anxiety and depression. To ensure the normal work of employees, it is important to implement psychological occupational therapy intervention (POTI). The previous studies on corporate occupational values focus on the behavioral variables and attitude variables related to occupations. The research paradigm does not suit a specific group of employees. Therefore, this paper explores the individual differences in POTI guided by the realization of occupational values. For a specific group of employees, the correlations of the psychological problems with job attitude, job involvement, and psychological health level were reasoned logically, a theoretical model was established, and the full-model map was plotted to illustrate the influence of the realization of occupational values over POTI. Then, the evaluation data on the psychological intervention effect of 2,800 employees were explored based on multikernel learning, and an individual difference prediction model was constructed through multikernel learning. Finally, the predicted results of different groups of employees were compared, revealing the effectiveness of our algorithm. [ABSTRACT FROM AUTHOR]

This paper constructs an evaluation model of occupational competency in rehabilitation therapy and applies it to the improvement of college students' innovative and entrepreneurial competencies. Based on clarifying the connotation of college students' entrepreneurial competency, this study carries out research on the evaluation system of college students' entrepreneurial competency. First, the method of qualitative research is used to conduct in-depth interviews with college students and entrepreneurial mentors to understand the views of these groups on college students' entrepreneurial competency, and the coding of the interview contents is carried out by applying the rooting theory, and finally, a theoretical model of the composition of college students' entrepreneurial competency is derived. The front-line position of talent cultivation is the construction of faculty, because the faculty with high-quality vocational ability is an indispensable prerequisite for the development of universities, and the teaching level of the faculty is the key factor for the effectiveness of teaching to appear. Based on the perspective of role theory, we analyze the problems and reasons for the lack of competency in the role-playing process; integrate the three stages of understanding the role, playing the role, and adjusting the role with the competency model; and propose strategies to improve the competency of youth social workers in the process of playing the role, to help workers accurately understand the role, correctly play the role, and reasonably adjust the role. The curriculum is designed to cultivate the competency of college student nursing positions, which is conducive to improving the professional quality of college student nursing service providers and regulating college student nursing practice so that they can actively respond to problems. This will strengthen the entire teaching faculty and enhance the professional competence of full-time teachers. [ABSTRACT FROM AUTHOR]

Virtual reality technology has attracted researchers' attention because it can provide users with a virtual interactive learning environment. Based on the theory of virtual reality technology, this paper proposes the system model design and architecture of virtual interactive music-assisted interactive teaching and realizes key technologies such as modeling, music-assisted interactive teaching scene interaction, and database access. In the simulation process, based on the VRML/X3D bottom interactive system template, after comprehensive application research, comparative analysis of various modeling methods, the system verified the use of digital cameras combined with the modeling technology based on music elements to collaboratively establish VRML virtual model connections. For inline node function, we combined it with Outline3D to realize VRML integration and then use VizX3D, X3D-Edit to build X3D model and realize the conversion from VRML to X3D, which solves the system completeness problem of music-assisted interactive teaching. The experimental results show that, according to the statistical analysis of the data after the experiment, when the position changes in the virtual 3D music-assisted interactive teaching scene, it will be displayed in the plane layer, and the real-time coordinates of the virtual music-assisted interactive teaching scene displayed in HTML have case. By analyzing the scenes and dynamic effects in the works, the effects of the virtual world can be better displayed through the performance of details. The better accuracy and delay error reached 89.7% and 3.11%, respectively, which effectively improved the effect and feasibility of applying virtual reality technology to music-assisted interactive teaching. [ABSTRACT FROM AUTHOR]

Objective. Aging and AD are associated in some way, then it is reasonable to ask whether or not it is possible to age without AD inexorably appearing at any moment, depending on the period of life. Therefore, the goal of this review is to verify, in light of some aging theories, the prevalence of AD. Methods. For the purpose of this manuscript, the indexers Alzheimer, aging, Alzheimer, and aging were considered; theories of aging were researched. The research was conducted using PubMed, Medline, Scopus, Elsevier, and Google Scholar. Results. The most common subjects in the papers analyzed for this manuscript were aging and Alzheimer's disease. The association between Alzheimer and theories of aging seems inconclusive. Conclusions. Accordingly, the general idea is that AD is associated with aging in such a way that almost all people will present this disease; however, it is plausible to consider that the increase in life expectancy will generate a high prevalence of AD. In a general sense, it seems that the theories of aging explain the origin of AD under superlative and catastrophic considerations and use more biomolecular data than social or behavioral data as the bases of analysis, which may be the problem. [ABSTRACT FROM AUTHOR]

The discrete Gel'fand–Yaglom theorem was studied several years ago. In the present paper, we generalize the discrete Gel'fand–Yaglom method to obtain the determinants of mass matrices which appear in current works in particle physics, such as dimensional deconstruction and clockwork theory. Using the results, we show the expressions for vacuum energies in such various models. [ABSTRACT FROM AUTHOR]

An improved principle is proposed in this paper to achieve a more efficient amplitude suppression of an oscillating pendulum by a controllable moving mass. By establishing the governing equation of the pendulum with a moving mass, several suppression rules are presented to stipulate the motion parameters of the moving mass. The damping ratio is introduced to quantify the suppression effects generated by the mass intermittent motion. With the verification of the accuracy of the present model, some simulation has been taken to get the maximum damping ratio and solve the problem of the nonsynchronous motion. The simulation results show that the new principle is a more powerful control method for the oscillation problem of a pendulum. It is suggested that the new method should carry out the relevant active control experiment in the future research. [ABSTRACT FROM AUTHOR]

Visceral leishmaniasis (VL), one of the deadliest parasitic diseases in the world, causes more than 50,000 human deaths each year and afflicts millions of people throughout South America, East Africa, South Asia, and Mediterranean Region. In 2015 the World Health Organization classified VL as a neglected tropical disease (NTD), prompting concentrated study of the VL epidemic using mathematical and simulation models. This paper reviews literature related to prevalence and prevention control strategies. More than thirty current research works were reviewed and classified based on VL epidemic study methods, including modeling approaches, control strategies, and simulation techniques since 2013. A summarization of these technical methods, major findings, and contributions from existing works revealed that VL epidemic research efforts must improve in the areas of validating and verifying VL mathematical models with real-world epidemic data. In addition, more dynamic disease control strategies must be explored and advanced simulation techniques must be used to predict VL pandemics. [ABSTRACT FROM AUTHOR]

This paper describes a convenient and straightforward method developed to extract keratin particles (KPs) from human hair. It also involves their characterization by several methods and encapsulation of the anticancer drug Paclitaxel (Taxol) within them, aiming for targeted delivery to cancerous sites and slow release at their vicinity. The KPs obtained were in micrometer in size. They are capable of encapsulating Taxol within them with a high encapsulation efficiency of 56% and a drug loading capacity of 2.360 g of Taxol per g keratin. As revealed by the SEM elemental analysis, KPs do not contain any toxic metal ion, and hence, they pose no toxicity to human cells. The pH-dependent release kinetics of the drug from KPs indicates that the drug is released faster when the pH of the solution is increased in the 5.0 to 7.0 pH range. The release kinetics obtained is impressive, and once targeted to the cancerous sites, using cancer directing agents, such as folic acid; a glutamate urea ligand known as DUPA; aminopeptidase N, also known as CD13; and FAP-α-targeting agents, the slow release of the drug is expected to destroy only the cancerous cells. The Noyes-Whitney dissolution model was used to analyze the release behavior of Taxol from KPs, which shows excellent fitting with experimental data. The pH dependence of drug release from keratin is also explained using the 3-D structures and keratin stability at different pH values. [ABSTRACT FROM AUTHOR]

The spiculation sign is one of the main signs to distinguish benign and malignant pulmonary nodules. In order to effectively extract the image feature of a pulmonary nodule for the spiculation sign distinguishment, a new spiculation sign recognition model is proposed based on the doctors' diagnosis process of pulmonary nodules. A maximum density projection model is established to fuse the local three-dimensional information into the two-dimensional image. The complete boundary of a pulmonary nodule is extracted by the improved Snake model, which can take full advantage of the parallel calculation of the Spike Neural P Systems to build a new neural network structure. In this paper, our experiments show that the proposed algorithm can accurately extract the boundary of a pulmonary nodule and effectively improve the recognition rate of the spiculation sign. [ABSTRACT FROM AUTHOR]

Angiogenesis is a crucial area in scientific research because it involves many important physiological and pathological processes. Indeed, angiogenesis is critical for normal physiological processes, including wound healing and embryonic development, as well as being a component of many disorders, such as rheumatoid arthritis, obesity, and diabetic retinopathies. Investigations of angiogenic mechanisms require assays that can activate the critical steps of angiogenesis as well as provide a tool for assessing the efficacy of therapeutic agents. Thus, angiogenesis assays are key tools for studying the mechanisms of angiogenesis and identifying the potential therapeutic strategies to modulate neovascularization. However, the regulation of angiogenesis is highly complex and not fully understood. Difficulties in assessing the regulators of angiogenic response have necessitated the development of an alternative approach. In this paper, we review the standard models for the study of tumor angiogenesis on the macroscopic scale that include in vitro, in vivo, and computational models. We also highlight the differences in several modeling approaches and describe key advances in understanding the computational models that contributed to the knowledge base of the field. [ABSTRACT FROM AUTHOR]

Background and Aim: Gastric cancer (GC) is the common leading cause of cancer-related death worldwide. Immune-related genes (IRGs) may potentially predict lymph node metastasis (LNM). We aimed to develop a preoperative model to predict LNM based on these IRGs. Methods: In this paper, we compared and evaluated three machine learning models to predict LNM based on publicly available gene expression data from TCGA-STAD. The Pearson correlation coefficient (PCC) method was utilized to feature selection according to its relationships with LN status. The performance of the model was assessed using the area under the curve (AUC) and F1 score. Results: The Naive Bayesian model showed better performance and was constructed based on 26 selected gene features, with AUCs of 0.741 in the training set and 0.688 in the test set. The F1 score in the training set and test set was 0.652 and 0.597, respectively. Furthermore, Naive Bayesian model based on 26 IRGs is the first diagnostic tool for the identification of LNM in advanced GC. Conclusion: These results indicate that our new methods have the value of auxiliary diagnosis with promising clinical potential. [ABSTRACT FROM AUTHOR]

User authentication has been widely used by biometric applications that work on unique bodily features, such as fingerprints, retina scan, and palm vessels recognition. This paper proposes a novel concept of biometric authentication by exploiting a user's medical history. Although medical history may not be absolutely unique to every individual person, the chances of having two persons who share an exactly identical trail of medical and prognosis history are slim. Therefore, in addition to common biometric identification methods, medical history can be used as ingredients for generating Q&A challenges upon user authentication. This concept is motivated by a recent advancement on smart-card technology that future identity cards are able to carry patents' medical history like a mobile database. Privacy, however, may be a concern when medical history is used for authentication. Therefore in this paper, a new method is proposed for abstracting the medical data by using attribute value taxonomies, into a hierarchical data tree (h-Data). Questions can be abstracted to various level of resolution (hence sensitivity of private data) for use in the authentication process. The method is described and a case study is given in this paper. [ABSTRACT FROM AUTHOR]

The l 1 -norm regularization has attracted attention for image reconstruction in computed tomography. The l 0 -norm of the gradients of an image provides a measure of the sparsity of gradients of the image. In this paper, we present a new combined l 1 -norm and l 0 -norm regularization model for image reconstruction from limited projection data in computed tomography. We also propose an algorithm in the algebraic framework to solve the optimization effectively using the nonmonotone alternating direction algorithm with hard thresholding method. Numerical experiments indicate that this new algorithm makes much improvement by involving l 0 -norm regularization. [ABSTRACT FROM AUTHOR]

In this paper, we have used an agent-based stochastic tumor growth model and presented a mathematical and theoretical perspective to cancer therapy. This perspective can be used to theoretical study of precision medicine and combination therapy in individuals. We have conducted a series of in silico combination therapy experiments. Based on cancer drugs and new findings of cancer biology, we hypothesize relationships between model parameters which in some cases represent individual genome characteristics and cancer drugs, i.e., in our approach, therapy players are delegated by biologically reasonable parameters. In silico experiments showed that combined therapies are more effective when players affect tumor via different mechanisms and have different physical dimensions. This research presents for the first time an algorithm as a theoretical viewpoint for the prediction of effectiveness and classification of therapy sets. [ABSTRACT FROM AUTHOR]

This paper proposes some results concerning the interaction of living matter of different organization levels (prokaryotes and eukaryotes) with the flux of thermal neutrons. The phenomenon of the virtual neutron trap was tested during the passage of thermalized neutrons from the Pu-Be couple through a flat layer of E. coli suspension. We have studied the metabolic characteristics of A. salina cysts before and after artificial neutron flux exposure. It has been demonstrated that the concentrations of some metals in samples of alive and dead cysts irradiated with an artificial flow of thermal neutrons are not equal. The content of Mn in alive A. salina samples has increased more than ten-fold after their interaction with neutron flux, while the amount of As decreased by a factor of two after exposure. Levels of other elements (Al, Cr, Ni, Cu, Cd, and Pb) did not show any significant difference. Trace element composition of cysts was assessed using the method of atomic absorption spectroscopy with electrothermal atomization and the Zeeman background correction. [ABSTRACT FROM AUTHOR]

The main aim of the paper was to simulate the drug release by a multifractal theoretical model, as a valuable method to assess the drug release mechanism. To do this, drug delivery films were prepared by mixing poly(vinyl alcohol boric acid) (PVAB) and diclofenac (DCF) sodium salt drug in different mass ratios from 90/10 to 70/30, in order to obtain drug delivery systems with different releasing rates. The different drug content of the three systems was confirmed by energy-dispersive spectroscopy (EDAX) analysis, and the encapsulation particularities were investigated by scanning electron microscopy (SEM), atomic force microscopy (AFM), and polarized optical microscopy (POM) techniques. The ability of the PVAB matrix to anchor the DCF was assessed by Fourier transform infrared (FTIR) spectroscopy. The in vitro release of the diclofenac sodium salt from the formulations was investigated in biomimetic conditions (pH = 7.4 and 37°C) by UV-Vis spectroscopy, measuring the absorbance of the drug at 275 nm and fitting the results on a previously drawn calibration curve. An estimation of the drug release kinetics was performed by fitting three traditional mathematical models on experimental release data. Further, the drug delivery was simulated by the fractal theory of motion, in which the release dynamics of the polymer-drug complex system is described through various Riccati-type "regimes." To explain such dynamics involved multifractal self-modulation in the form of period doubling, quasiperiodicity, intermittency, etc., as well as multifractal self-modulation of network type. Standard release dynamics were explained by multifractal behaviors of temporary kink type. The good correlation between the traditional mathematical models and the new proposed theoretical model demonstrated the validity of the multifractal model for the investigation of the drug release. [ABSTRACT FROM AUTHOR]

Background. Uterine contraction (UC) is the tightening and shortening of the uterine muscles which can indicate the progress of pregnancy towards delivery. Electrohysterogram (EHG), which reflects uterine electrical activities, has recently been studied for UC monitoring. In this paper, we aimed to evaluate different EHG segments for recognizing UCs using the convolutional neural network (CNN). Materials and Methods. In the open-access Icelandic 16-electrode EHG database (122 recordings from 45 pregnant women), 7136 UC and 7136 non-UC EHG segments with the duration of 60 s were manually extracted from 107 recordings of 40 pregnant women to develop a CNN model. A fivefold cross-validation was applied to evaluate the CNN based on sensitivity (SE), specificity (SP), and accuracy (ACC). Then, 1056 UC and 1056 non-UC EHG segments were extracted from the other 15 recordings of 5 pregnant women. Furthermore, the developed CNN model was applied to identify UCs using different EHG segments with the durations of 10 s, 20 s, and 30 s. Results. The CNN achieved the average SE, SP, and ACC of 0.82, 0.93, and 0.88 for a 60 s EHG segment. The EHG segments of 10 s, 20 s, and 30 s around the TOCO peak achieved higher SE and ACC than the other segments with the same duration. The values of SE from 20 s EHG segments around the TOCO peak were higher than those from 10 s to 30 s EHG segments on the same side of the TOCO peak. Conclusion. The proposed method could be used to determine the efficient EHG segments for recognizing UC with the CNN. [ABSTRACT FROM AUTHOR]

As an inevitable product of the development of the construction industry, safety production has attracted more and more attention. In particular, it affects sustainable development. It is important to study the unsafe behavior of individuals. This study integrated the hybrid method of necessary condition analysis (NCA) and structural equation model (SEM). Based on the institutional environment perspective of social cognition theory, an empirical analysis was conducted through field observation and 186 questionnaire data to explore the influence of the institutional environment, safety attitude, and unsafe behavior. The results showed that improved safety attitudes of workers are a key requisite to curb unsafe behavior, and it was confirmed that safety attitude plays a complete mediating role between institutional environment and unsafe behavior. Through the analysis of the necessary conditions and mediating effects of safety attitude, the study deepened the theoretical understanding of the interaction between institutional environment, safety attitude, and unsafe behavior. Also, it provided relevant management suggestions for the construction industry in safety management. [ABSTRACT FROM AUTHOR]

The art of music, which is a necessary component of daily life and an ideology older than language, reflects the emotions of human reality. Many new elements have been introduced into music as a result of the quick development of technology, gradually altering how people create, perform, and enjoy music. It is incredible to see how actively AI has been used in music applications and music education over the past few years and how significantly it has advanced. AI technology can efficiently pull in the course, stratify complex large-scale music or sections, simplify teaching, improve student understanding of music, solve challenging student problems in class, and simplify the tasks of teachers. The traditional music education model has been modified, and the music education model's audacious innovation has been made possible by reducing the distance between the teacher and the student. A classification algorithm based on spectrogram and NNS is proposed in light of the advantages in image processing. The abstract features on the spectrogram are automatically extracted using the NNS, which completes the end-to-end learning and avoids the tediousness and inaccuracy of manual feature extraction. This study, which uses experimental analysis to support its findings, demonstrates that different music teaching genres can be accurately classified at a rate of over 90%, which has a positive impact on recognition. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to review some of the psychological and neural mechanisms behind mindfulness practice in order to explore the unique factors that account for its positive impact on emotional regulation and health. After reviewing the mechanisms of mindfulness and its effects on clinical populations we will consider how the practice of mindfulness contributes to the regulation of emotions. We argue that mindfulness has achieved effective outcomes in the treatment of anxiety, depression, and other psychopathologies through the contribution of mindfulness to emotional regulation. We consider the unique factors that mindfulness meditation brings to the process of emotion regulation that may account for its effectiveness. We review experimental evidence that points towards the unique effects of mindfulness specifically operating over and above the regulatory effects of cognitive reappraisal mechanisms. A neuroanatomical circuit that leads to mindful emotion regulation is also suggested. This paper thereby aims to contribute to proposed models of mindfulness for research and theory building by proposing a specific model for the unique psychological and neural processes involved in mindful detachment that account for the effects of mindfulness over and above the effects accounted for by other well-established emotional regulation processes such as cognitive reappraisal. [ABSTRACT FROM AUTHOR]

With the emergence of unmanned plane, autonomous vehicles, face recognition, and language processing, the artificial intelligence (AI) has remarkably revolutionized our lifestyle. Recent studies indicate that AI has astounding potential to perform much better than human beings in some tasks, especially in the image recognition field. As the amount of image data in imaging center of ophthalmology is increasing dramatically, analyzing and processing these data is in urgent need. AI has been tried to apply to decipher medical data and has made extraordinary progress in intelligent diagnosis. In this paper, we presented the basic workflow for building an AI model and systematically reviewed applications of AI in the diagnosis of eye diseases. Future work should focus on setting up systematic AI platforms to diagnose general eye diseases based on multimodal data in the real world. [ABSTRACT FROM AUTHOR]

The effectiveness of sleep intervention developed by occupational therapists was reviewed, and a conceptual framework for organizing the developing practice of sleep management in occupational therapy was proposed in this paper. Evidence-based articles on sleep management practice in occupational therapy from 2007 to 2017 were retrieved. Four types of effective sleep management intervention were identified from the literature, including the use of assistive devices/equipment, activities, cognitive behavioral therapy for insomnia, and lifestyle intervention, and the use of assistive device was the most popular intervention. Applying the Person-Environment-Occupation Performance (PEOP) framework, we developed a conceptual framework for organizing occupational therapy practice in sleep management. The future development of occupation-based sleep intervention could focus on strategies to (1) minimize the influence of bodily function on sleep, (2) promote environment conducive to sleep, and (3) restructure daytime activity with a focus on occupational balance. [ABSTRACT FROM AUTHOR]

One major limiting factor that prevents the accurate delineation of vessel boundaries has been the presence of blurred boundaries and vessel-like structures. Overcoming this limitation is exactly what we are concerned about in this paper. We describe a very different segmentation method based on a cascade-AdaBoost-SVM classifier. This classifier works with a vessel axis + cross-section model, which constrains the classifier around the vessel. This has the potential to be both physiologically accurate and computationally effective. To further increase the segmentation accuracy, we organize the AdaBoost classifiers and the Support Vector Machine (SVM) classifiers in a cascade way. And we substitute the AdaBoost classifier with the SVM classifier under special circumstances to overcome the overfitting issue of the AdaBoost classifier. The performance of our method is evaluated on synthetic complex-structured datasets, where we obtain high overlap ratios, around 91%. We also validate the proposed method on one challenging case, segmentation of carotid arteries over real clinical datasets. The performance of our method is promising, since our method yields better results than two state-of-the-art methods on both synthetic datasets and real clinical datasets. [ABSTRACT FROM AUTHOR]

This paper aims to promote a national and international occupational health and safety (OHS) intervention for small and medium enterprises (SMEs) within internal and external resources. Based on the characteristics of small SME management, the work environment and occupational health may be positively affected by the dual-effects of employees and government. Evolutionary game theory is utilized to identify relevant interactions among the government, small enterprises, and employees. Furthermore, dynamic simulations of the evolutionary game model are used to explore stability strategies and to identify modes of equilibrium. [ABSTRACT FROM AUTHOR]

Community engagement (CE) has long been endorsed by policy makers and health practitioners. However, uncertainties remain about the workings and outcomes of CE. This study aims to provide in-depth insights into them. In a multiple case study, we investigated three participatory health promotion projects for families in vulnerable situations in the Netherlands. We adopted a realist approach combined with a theory of change (ToC) model. We then analysed the qualitative data for context–mechanism–outcome (CMO) configurations to refine this ToC. Results show that CE can strengthen social networks, empower families, and increase perceived health. However, specific contexts in combination with CE project approaches may or may not trigger positive responses. Participants may feel that they matter when asked to actively contribute to a project, which in turn can enhance their self-confidence. In another context, we found that families were overwhelmed by the responsibilities given to them in the project, leading to feelings of stress and withdrawal from the project. We present a list of CMO configurations and refine the ToC accordingly. Our main conclusion is that flexibility is key when CE is implemented in health promotion. Also, our findings question physical health outcomes as a realistic ambition for CE projects with groups in vulnerable situations. [ABSTRACT FROM AUTHOR]

The urban blue-green space landscape ecology is an important component that supports the urban landscape ecosystem. In this study, a combination model of the grey system theory (GST), analytic hierarchy process (AHP), and technique for order of preference by similarity to ideal solution (TOPSIS) was used to construct criteria layers from the following four aspects: green space vegetation coverage, ecosystem diversity, air and water quality, social participation, and health. The GST method was employed to screen evaluation indicators, the AHP method was used to calculate the weight of each indicator, and finally, TOPSIS was applied for weighted ranking to verify the scientific and rationality of the evaluation system. The results indicated the following: (1) out of 36 indicator factors, 10 were not selected through the GST method; (2) the weight ranking of the criteria layer was as follows, from highest to lowest: D 2 ecosystem diversity 0.4816 > D 1 green space vegetation coverage 0.2608 > D 3 air and water quality 0.1864 > D 4 social participation and health 0.0713; and (3) the relative closeness and ranking of different regions in Jinan city were as follows: Da Ming Hu area > Shan Da Lu area > Gu Cheng area > Shang Bu area. This study can help avoid decision-making errors caused by subjective factors and provide new approaches for the assessment of the ecological health of urban blue-green space landscapes. [ABSTRACT FROM AUTHOR]

Many forms of biometrics have been proposed and studied for biometrics authentication. Recently researchers are looking into longitudinal pattern matching that based on more than just a singular biometrics; data from user's activities are used to characterise the identity of a user. In this paper we advocate a novel type of authentication by using a user's medical history which can be electronically stored in a biometric security card. This is a sequel paper from our previous work about defining abstract format of medical data to be queried and tested upon authentication. The challenge to overcome is preserving the user's privacy by choosing only the useful features from the medical data for use in authentication. The features should contain less sensitive elements and they are implicitly related to the target illness. Therefore exchanging questions and answers about a few carefully chosen features in an open channel would not easily or directly expose the illness, but yet it can verify by inference whether the user has a record of it stored in his smart card. The design of a privacy preserving model by backward inference is introduced in this paper. Some live medical data are used in experiments for validation and demonstration. [ABSTRACT FROM AUTHOR]

Obesity is classified as a chronic disease. Women and men seem to face different obstacles in their attempts to overcome one of the most challenging tasks in the treatment of this disease, namely, weight reduction maintenance. The Common-Sense-Model (CSM) is mainly used to improve the understanding of self-regulation and health behaviour in chronic diseases but has yet to be explored for obesity. This paper applies the CSM to obesity, focussing on the construct of illness representations, which is the basis of health behaviour according to the CSM. A sample of n = 356 women and n = 77 men with obesity was investigated to assess the extent that illness representations in obesity are shaped by experiences of weight-cycling and the extent that gender influences their quality. Our results show that the representations of timeline and consequences as well as the emotional representation are particularly influenced by weight-cycling, especially in men. On average, women showed more maladaptive illness representations than men. These findings not only contribute to a better applicability of the CSM in obesity, but also emphasize the importance of gender in obesity research and interventions. [ABSTRACT FROM AUTHOR]

Skin cancer is a significant health concern worldwide, and early and accurate diagnosis plays a crucial role in improving patient outcomes. In recent years, deep learning models have shown remarkable success in various computer vision tasks, including image classification. In this research study, we introduce an approach for skin cancer classification using vision transformer, a state-of-the-art deep learning architecture that has demonstrated exceptional performance in diverse image analysis tasks. The study utilizes the HAM10000 dataset; a publicly available dataset comprising 10,015 skin lesion images classified into two categories: benign (6705 images) and malignant (3310 images). This dataset consists of high-resolution images captured using dermatoscopes and carefully annotated by expert dermatologists. Preprocessing techniques, such as normalization and augmentation, are applied to enhance the robustness and generalization of the model. The vision transformer architecture is adapted to the skin cancer classification task. The model leverages the self-attention mechanism to capture intricate spatial dependencies and long-range dependencies within the images, enabling it to effectively learn relevant features for accurate classification. Segment Anything Model (SAM) is employed to segment the cancerous areas from the images; achieving an IOU of 96.01% and Dice coefficient of 98.14% and then various pretrained models are used for classification using vision transformer architecture. Extensive experiments and evaluations are conducted to assess the performance of our approach. The results demonstrate the superiority of the vision transformer model over traditional deep learning architectures in skin cancer classification in general with some exceptions. Upon experimenting on six different models, ViT-Google, ViT-MAE, ViT-ResNet50, ViT-VAN, ViT-BEiT, and ViT-DiT, we found out that the ML approach achieves 96.15% accuracy using Google's ViT patch-32 model with a low false negative ratio on the test dataset, showcasing its potential as an effective tool for aiding dermatologists in the diagnosis of skin cancer. [ABSTRACT FROM AUTHOR]

When older people move into a care home, family members often continue to be involved in caregiving. This can include contributing to discussion and decisions about care and treatment, especially when the resident lacks capacity. However, families may not know what to expect as their relative's condition progresses and may not have a good understanding of their relative's end-of-life care and treatment wishes. Therefore, although often willing, families may feel unprepared for making decisions in advance of or at the time of deterioration and end-of-life. The study aimed to explore the potential role that peer-mentors might have in supporting families to prepare for discussion and decisions about care and treatment and to understand what participants would consider to be important characteristics of an effective peer-mentor and peer-mentoring program. The study was guided by the philosophical assumptions of social constructionism. Data from semistructured interviews with 14 current and 15 bereaved family members and 11 senior members of care were analysed thematically. Findings suggest that peer-mentors could help to empower families to prepare to be involved in discussions and decisions about the types of care their relatives might receive as their health deteriorates and they reach the end-of-life. However, it was seen as important that peer-mentors have lived experience of supporting a relative in a care home, strong interpersonal and communication skills, and the ability to discuss deterioration and end-of-life in a compassionate but factual manner. Although peer-mentoring is often time-limited, introducing mentors to families earlier in the care journey, for example, before admission into a care home, could enable a trusting relationship to develop. This, in turn, could facilitate open discussions about what to expect and different care choices as the person's health changes. [ABSTRACT FROM AUTHOR]

Given the importance of protease’s worldwide market, the determination of optimum conditions and the development of a standard protocol are critical during selection of a reliable method to determine its bioactivity. This paper uses quality control theory to validate a modified version of a method proposed by Charney and Tomarelli in 1947. The results obtained showed that using azocasein substrate bromelain had its optimum at 45°C and pH 9 (Glycine-NaOH 100 mM). We also quantified the limit of detection (LoD) and limit of quantification (LoQ) in the above-mentioned optimum (0.072 and 0.494 mg·mL−1 of azocasein, resp.) and a calibration curve that correlates optical density with the amount of substrate digested. In all analysed samples, we observed a significant decrease in response after storage (around 17%), which suggests its use must be immediately after preparation. Thus, the protocol presented in this paper offers a significant improvement, given that subjective definitions are commonly used in the literature and this simple mathematical approach makes it clear and concise. [ABSTRACT FROM AUTHOR]

This paper is concerned with the mathematical modeling of a severe and common congenital defect called hypoplastic left heart syndrome (HLHS). Surgical approaches are utilized for palliating this heart condition; however, a brain white matter injury called periventricular leukomalacia (PVL) occurs with high prevalence at or around the time of surgery, the exact cause of which is not known presently. Our main goal in this paper is to study the hemodynamic conditions under which HLHS physiology may lead to the occurrence of PVL. A lumped parameter model of the HLHS circulation has been developed integrating diffusion modeling of oxygen and carbon dioxide concentrations in order to study hemodynamic variables such as pressure, flow, and blood gas concentration. Results presented include calculations of blood pressures and flow rates in different parts of the circulation. Simulations also show changes in the ratio of pulmonary to systemic blood flow rates when the sizes of the patent ductus arteriosus and atrial septal defect are varied. These changes lead to unbalanced blood circulations and, when combined with low oxygen and carbon dioxide concentrations in arteries, result in poor oxygen delivery to the brain. We stipulate that PVL occurs as a consequence. [ABSTRACT FROM AUTHOR]