Trends In Dynamics Research Articles

Dual-track spatio-temporal learning for urban flow prediction with adaptive normalization

Robust urban flow prediction is crucial for transportation planning and management in urban areas. Although recent advances in modeling spatio-temporal correlations have shown potential, most models fail to adequately consider the complex spatio-temporal semantic information present in real-world scenarios. We summarize the following three primary limitations in existing models: a) The majority of existing models project overall time periods into the same latent space, neglecting the diverse temporal semantics between different time intervals. b) Existing models tend to capture spatial dependencies from a locale perspective such as surroundings but do not pay attention to the global influence factors. c) Beyond the spatio-temporal properties, the dynamics and instability of the data sequences introduce perturbations to the prediction results, potentially leading to model degradation. To address these issues, we propose a dual-track spatial-temporal learning module named DualST for accurate urban flow inference. To more effectively differentiate semantic information in the time dimension, we assign the overall time scales into closeness and periodicity. The dual-track module, which includes temporal causality inference and temporal contextual inference, simultaneously exploits the dynamic evolutionary trends and periodic traffic patterns, respectively. The proposed DualST captures global spatial features in a self-supervised manner which not only enriches the spatial semantics but also avoids introducing additional prior knowledge. To eliminate the instability caused by dynamics, we first adopt spatio-temporal adaptive normalization to learn appropriate data sequence normalization. We evaluate the proposed DualST on two typical urban flow datasets. The experiment results show that our model not only exhibits a consistent superiority over various state-of-the-art baselines but also has remarkable generalization capability.

Increasing Burden of Osteoarthritis in China: Trends and Projections from the Global Burden of Disease Study 2019.

BACKGROUND This study aimed to evaluate the epidemiology of osteoarthritis in China in a comprehensive and reliable way, to project its future epidemiological patterns, and to mitigate its health hazards. MATERIAL AND METHODS Data were extracted and analyzed from the Global Burden of Diseases Study 2019. Trends in osteoarthritis epidemiology were explored using joinpoint regression analysis. Additionally, we analyzed dynamic trends using the sociodemographic index (SDI) of China. To assess and predict the epidemiology of osteoarthritis from 2020 to 2039, we used both the Bayesian age-period-cohort model and Nordpred model. RESULTS The number of prevalent cases, incident cases, and years lived with disability (YLDs) for osteoarthritis in China increased from 51.8, 4.6, and 1.8 million, respectively, in 1990, to 132.8, 10.7, and 4.7 million, respectively, in 2019, and the average annual percentage changes were 3.286, 2.938, and 3.324, respectively. The prevalence and YLDs peaked in the population aged over 90 years old, while the incidence peaked in the population aged around 50 years old. A significant positive correlation was found between osteoarthritis burden and SDI. Osteoarthritis burden is expected to continue to increase. In the population studied here, it was higher in women than in men, but this may invert by 2039. CONCLUSIONS The prevalence, incidence, and YLDs of osteoarthritis had significantly increased and may continue to increase during the next 2 decades. Prevention and treatment strategies should target women, middle-aged individuals, and the elderly.

Y AND Z GENERATIONS PREFERENCES FOR WORD-OF-MOUTH MARKETING

This article discusses the differences in generational preferences for word-of-mouth marketing. Differences between Generations Y and Z regarding different forms and sources of marketing are evaluated. The research objective was to discuss and analyze the results of the social-media campaign achieved by the non-governmental organization “Safari” through the developed strategy in a specific reporting period in order to find out whether the differences exist in the preferences of generation Y and Z for WOM marketing. To meet the research objective, the complete process of Word-of-Mouth (WOM) marketing planning and implementation was identified, each component of the communication activities cycle has been studied and the role of influencers in obtaining the desired responses from Gen Z toward the application “Safe YOU” has been evaluated. Applied method is the observation and content-analyses. The findings reveal that Generation Y exhibits a notable inclination toward seeking information via recommendations and evaluations predominantly from various sources, including Facebook. Among the various tools used, including Facebook, photo and video content are the most effective. This reliance on input from strangers signifies an evolving trend in trust dynamics, emphasizing the significance of online credibility and collective feedback in their decision-making process. In contrast, Generation Z demonstrates a marked preference for influence marketing, relying heavily on information sourced directly from influencers. Mirroring older generational behavior, Generation Z exhibits a parallel dependence on social networks as a primary information conduit. These findings underscore the importance of tailored marketing strategies that acknowledge and adapt to the unique preferences of each generation. Keywords: Influence Marketing, Generation Y, Generation Z, Consumer preferences, Marketing Strategies

Trends of the COVID-19 dynamics in 2022 and 2023 vs. the population age, testing and vaccination levels.

The population, governments, and researchers show much less interest in the COVID-19 pandemic. However, many questions still need to be answered: why the much less vaccinated African continent has accumulated 15 times less deaths per capita than Europe? or why in 2023 the global value of the case fatality risk is almost twice higher than in 2022 and the UK figure is four times higher than the global one? The averaged daily numbers of cases DCC and death DDC per million, case fatality risks DDC/DCC were calculated for 34 countries and regions with the use of John Hopkins University (JHU) datasets. Possible linear and non-linear correlations with the averaged daily numbers of tests per thousand DTC, median age of population A, and percentages of vaccinations VC and boosters BC were investigated. Strong correlations between age and DCC and DDC values were revealed. One-year increment in the median age yielded 39.8 increase in DCC values and 0.0799 DDC increase in 2022 (in 2023 these figures are 5.8 and 0.0263, respectively). With decreasing of testing level DTC, the case fatality risk can increase drastically. DCC and DDC values increase with increasing the percentages of fully vaccinated people and boosters, which definitely increase for greater A. After removing the influence of age, no correlations between vaccinations and DCC and DDC values were revealed. The presented analysis demonstrates that age is a pivot factor of visible (registered) part of the COVID-19 pandemic dynamics. Much younger Africa has registered less numbers of cases and death per capita due to many unregistered asymptomatic patients. Of great concern is the fact that COVID-19 mortality in 2023 in the UK is still at least 4 times higher than the global value caused by seasonal flu.

Research on the spatial patterns and evolution trends of the coupling coordination between digital finance and sustainable economic development in the Yellow River Basin, China.

In the current global context, digital finance (DF) and sustainable economic development (SED) are important topics. The synergies between DF and SED have already been proven. However, the measurement and quantitative analysis of the coupling coordination degree (CCD) of DF and SED have not received sufficient attention to date. Based on data from 55 cities in the Yellow River Basin (YRB) from 2011 to 2021, this study constructs an evaluation index system of DF and SED and measures their level, respectively. The proposed CCD model is then used to measure the CCD between the two systems. In addition, kernel density estimation, Markov chain, σ-convergence, β-convergence, and the quadratic assignment procedure (QAP) method are used to study the spatial pattern, distribution dynamic evolution trend, convergence, and influencing factors of the regional differences in the CCD. The results show that: (1) From 2011 to 2021, the CCD level showed a stable upward trend and regional heterogeneity, and the time stage characteristics were more obvious. (2) The center position and change interval of the overall distribution curve of the kernel density estimation gradually shifted to the right. The Markov transfer probability matrix shows that the CCD is more stable among different levels, indicating a phenomenon of "club convergence". (3) A convergence analysis shows that there are significant σ-convergence, absolute β-convergence, and conditional β-convergence. (4) The QAP regression shows that factors such as the regional differences in GDP per capita have a significant impact on the regional differences in the CCD. This study offers a comprehensive structure that can be used to examine the synergistic effects between DF and SED; the research findings can also provide perspectives for other areas.

Spatial-temporal pattern and spatial convergence of carbon emission intensity of rural energy consumption in China.

Based on the panel data of 30 provinces (municipalities and autonomous regions) in China from 2005 to 2019, this paper uses Gini coefficient decomposition and kernel density estimation to investigate the regional differences and dynamic evolution trend of rural energy carbon emission intensity in China. Then, the convergence model is used to analyze the convergence characteristics and influencing factors of carbon emission intensity. The study found the following: (1) During the observation period, the carbon emissions of coal energy and oil energy were much higher than those of gas energy. The carbon emissions of rural energy consumption experienced three stages of development, and the carbon emission intensity showed a downward trend as a whole. The spatial distribution pattern of total carbon emissions present an "adder" distribution, and the spatial agglomeration phenomenon gradually strengthens with the passage of time. (2) The Gini coefficient of China's rural energy consumption carbon emission intensity shows a trend of "Inverted N-shaped." The Gini coefficient of carbon emission intensity in the eastern and northeastern regions shows an increasing trend, while the Gini coefficient of carbon emission intensity in the western and central regions shows a downward trend. The super variable density is the main source of carbon emission intensity difference. The peak value of the main peak of the nuclear density curve of the carbon emission intensity increased significantly, the bimodal form evolved into a single peak form, and the density center moved to the left. (3) The carbon emission intensity of rural energy consumption in the whole, central, and western regions of China has the characteristic of σ convergence, while the carbon emission intensity in the eastern and northeastern regions does not have the characteristic of σ convergence. There is a significant spatial positive correlation in the carbon emission intensity, there is also a significant β convergence characteristic, the speed of conditional β convergence is significantly higher than that of absolute β convergence, and the spatial interaction will further improve the convergence speed. Industrial structure, industrial agglomeration, and energy efficiency will increase the convergence speed. In terms of sub-regions, the conditional convergence rate of carbon emission intensity in the four regions shows a decreasing trend in the northeast, central, eastern, and western regions.

Geography of population migration of the Southern Federal District

The article, based on state statistics, conducted a study of the transformation of geography and trends in the development of migration of the population of the Southern Federal District. Using an interdisciplinary integrated approach, an analysis of migration flows, their directions, scale and intensity was carried out, the geography of migrations of the most migratoryly attractive subject of the district - Krasnodar Territory - was determined, and mapping of migration indicators was carried out using modern information technologies for studying space and visualization.It is shown that, despite the decrease in migration turnover due to the coronavirus pandemic, the long- term trend of positive migration dynamics in the Southern Federal District has remained, and in terms of the intensity of net migration in 2021, the macroregion took first place among all Russian districts.There have been no major changes in the geography of incoming and outgoing migration flows. Intra- Russian migration is characterized by a migration outflow of the population to the Central and Northwestern federal districts, and migrants from all other districts, but most of all from Siberia and the Far East, come to the southern macroregion. The main flows of international migrants come from citizens of the CIS countries, primarily from Ukraine, Armenia, Kazakhstan, Tajikistan, Uzbekistan, and Azerbaijan.A comparative analysis of the migration movement of the subjects of the Southern Federal District showed that in the macroregion Krasnodar Territory ranks first in terms of the volume and effectiveness of migration, and in terms of the intensity of migration movement, it exceeds the Russian average. To date, the steady trend of positive dynamics in the migration balance that has developed in Kuban since the middle of the last century has been preserved. However, there has been a significant decline in net migration. The main modern vector of intra-Russian migration flows is movement to Kuban from the northern regions of Russia, Siberia and the Far East. Most international migrants arrived in the Krasnodar region from CIS countries. During the study period, the main suppliers of cross-border migrants were Ukraine, Armenia and Kazakhstan.

РОЖДАЕМОСТЬ НА ДАЛЬНЕМ ВОСТОКЕ РОССИИ: ТЕНДЕНЦИИ, ПРИЧИНЫ, ПУТИ РЕШЕНИЯ

Significance. Given the current trends in demographic development, the existing disproportion between the population and the vast territory of the Far Eastern Federal District may significantly increase in the future, which will intensify certain concerns about a possible violation of the geopolitical balance out here. Fertility indicators have revealed the main demographic risk zones of the regions of the eastern territories. The purpose of the study is to analyze dynamics in birth rates in the Russian Far East, gender composition and age structure of the population to identify risk zones when taking effective measures to improve the situation. Material and methods. The analysis used World Health Organization data, databases and collections of Rosstat and the Ministry of Health of the Russian Federation by federal district and region of Russia, information on the implementation of the National Demography Project. Results. Determining trends in dynamics in birth rates in the Russian Far East shows that in urban areas of the Far Eastern regions, the type of demographic behavior inherent in the newcomer population and focused on having one child prevails, while in rural areas the traditions of the indigenous population are preserved. Until 2015, relatively high birth rates were recorded in “national” regions with the predominance of populations belonging to the indigenous people of the North and the Far East, in whose culture large families are accepted. The mother’s average age is increasing, there was a shift in the age of first-time mothers (20-24 years) to an older age group (25-29 years and 30-34 years). A decline in fertility in the near future will be due to a significant reduction in the number of women of reproductive age, especially in its active phase (20–39 years). A new model of marital and, as a result, reproductive behavior of young families is being formed. From the point of view of marital behavior, it implies an increase in the age at first marriage, refusal of marriage, popularity of informal marriage, etc. From the point of view of reproductive behavior, it involves postponing births in marriage until material standards are achieved, as well as in the interests of increasing one’s social status. Conclusion. One of the promising areas for improving the demographic situation is the adoption of effective social measures and programs to increase birth rates in young families. Only a rising dynamics in birth rates can give a real and sustainable impetus to stabilizing fertility for the national security of the eastern territories.

Dynamic assessment of community resilience in China: empirical surveys from three provinces.

Strengthening the construction of community resilience and reducing disaster impacts are on the agenda of the Chinese government. The COVID-19 pandemic could alter the existing community resilience. This study aims to explore the dynamic change trends of community resilience in China and analyze the primary influencing factors of community resilience in the context of COVID-19, as well as construct Community Resilience Governance System Framework in China. A community advancing resilience toolkit (CART) was used to conduct surveys in Guangdong, Sichuan, and Heilongjiang provinces in China in 2015 and 2022, with community resilience data and information on disaster risk awareness and disaster risk reduction behaviors of residents collected. The qualitative (in-depth interview) data from staffs of government agencies and communities (n = 15) were pooled to explore Community Resilience Governance System Framework in China. Descriptive statistics analysis and t-tests were used to investigate the dynamic development of community resilience in China. Hierarchical regression analysis was performed to explore the main influencing factors of residential community resilience with such socio-demographic characteristics as gender and age being controlled. The results indicate that community resilience in China has improved significantly, presenting differences with statistical significance (p < 0.05). In 2015, connection and caring achieved the highest score, while disaster management achieved the highest score in 2022, with resources and transformative potential ranking the lowest in their scores in both years. Generally, residents presented a high awareness of disaster risks. However, only a small proportion of residents that were surveyed had participated in any "community-organized epidemic prevention and control voluntary services" (34.9%). Analysis shows that core influencing factors of community resilience include: High sensitivity towards major epidemic-related information, particular attention to various kinds of epidemic prevention and control warning messages, participation in epidemic prevention and control voluntary services, and formulation of epidemic response plans. In this study, we have constructed Community Resilience Governance System Framework in China, which included community resilience risk awareness, community resilience governance bodies, community resilience mechanisms and systems. During the pandemic, community resilience in China underwent significant changes. However, community capital was, is, and will be a weak link to community resilience. It is suggested that multi-stages assessments of dynamic change trends of community resilience should be further performed to analyze acting points and core influencing factors of community resilience establishment at different stages.

Развитие инструментов экономического механизма в АПК России

The article is devoted to the issues of improving the tools of economic regulation in the agro-industrial complex of Russia in the context of modern challenges and threats. The authors emphasize that state support for the agro-industrial complex includes a whole system of existing mechanisms and tools. Despite the fact that the agri-food sector is one of the most dynamically developing sectors of the economy, in recent years there has been the decrease in the profitability of agricultural producers, the increase in price imbalances between various sectors of the AIC, the decrease in investment activity, insufficient efficiency of agricultural insurance and the low stimulating role of taxation. The article notes that at present the role of the state in the formation of the organizational and economic mechanism for the development of agriculture is significantly increasing. In this regard, the authors have proposed the set of tools for an economic mechanism aimed at forming sustainable and dynamic trends in the development of the country’s agri-food sector in order to ensure its extended reproduction.

ВАЛОВИЙ ВНУТРІШНІЙ ПРОДУКТ ЯК ІНДИКАТОР РІВНЯ ЕКОНОМІЧНОГО РОЗВИТКУ КРАЇНИ (НА ПРИКЛАДІ ЧЕСЬКОЇ РЕСПУБЛІКИ)

The article addresses the current issue of researching and analyzing Gross Domestic Product (GDP) as an indicator of national economic competitiveness on a global scale and its impact on the macroeconomic stability of the Czech Republic. The authors emphasize the importance of GDP analysis for effective economic management, planning, forecasting, and ensuring macroeconomic stability. The study is based on a review of previous research and publications by both Ukrainian and foreign scholars. As a result, the concept of Gross Domestic Product (GDP) is thoroughly analyzed, with three main aspects of the concept elucidated: "gross," "domestic," and "product." Furthermore, the article provides crucial explanations to enhance comprehension of the GDP concept. Moreover, the article extensively analyzes the dynamics of nominal and real Gross Domestic Product (GDP) of the Czech Republic from 2016 to 2022. Special attention is given to the impact of the COVID-19 pandemic on the Czech economy and its adverse effects in 2020. The causes of GDP decline are highlighted, along with data on economic recovery at the end of 2020 and an assessment of GDP dynamics in 2021 and 2022. The significance of evaluating GDP growth rates and their potential implications for the Czech economy are underscored, as well as the importance of GDP per capita as an indicator of Czech economic competitiveness and the country's position in the GDP per capita ranking. Additionally, the article examines the impact of declining household consumption on Czech GDP due to inflation and low investments. The methodology of correlation-regression analysis is employed to identify trends in GDP dynamics, along with projected GDP values for 2024 and 2025. It is noted that the main drivers of Czech economic growth should be the export activities of companies and the recovery of household demand. However, further research is needed to explore the analysis of GDP dynamics as an indicator of macroeconomic stability, its impact on forming global competitiveness rankings, and positioning the Czech Republic in the global economic community.

Управлінська діяльність через призму психології: актуальні напрямки розвитку

The article is devoted to the study of key aspects of the psychology of managerial activity in the modern business environment. It offers an in-depth analysis of the latest trends in understanding leadership, group dynamics, decision-making, motivation, stress management, and communication, based on recent advances in psychological science. The article discusses the latest approaches to leadership, in particular the role of emotional intelligence as a critical factor in effective leadership. Contemporary research confirms that leaders with a high level of emotional intelligence are better at managing a team, as they are able to recognize and adequately respond to the emotions of their subordinates, which helps to increase motivation and reduce conflicts in the team. A fairly important aspect is group dynamics, which include the interaction between team members, as well as the impact of cognitive differences on teamwork performance. Research shows that diversity of opinions and approaches within a team can improve performance, but conflicts can also arise. An important task for managers is to ensure effective communication and create an environment that promotes constructive interaction. Decision-making is another key aspect of management that requires taking into account cognitive biases. Psychological research demonstrates that biases can significantly affect decision-making, often leading to irrational choices. It is important for managers to be aware of these biases and be able to minimize them by using analytical tools and techniques to help them make more far-reaching decisions. Another important aspect is the intrinsic motivation of employees. Modern theories of motivation emphasize the importance of intrinsic stimuli, such as self-fulfillment and professional development, in improving performance. Managers should focus not only on external rewards, but also on creating conditions that promote the development of intrinsic motivation in employees. Stress management is also an important part of management activities. The article explores the latest stress management techniques, such as relaxation techniques, time management, and creating a supportive work environment. Reducing employees’ stress levels has a positive impact on their productivity and overall job satisfaction. Finally, considerable attention is paid to non-verbal communication, which in plays a critical role in management processes. Nonverbal cues can both support and undermine verbal messages, making them an important aspect of effective communication in organizations. The article proposes an integrated approach to the study of psychological aspects of managerial activity, which allows to improve the efficiency of management strategies and increase the overall productivity of organizations.

Geography and form of settlement of Russians of the near abroad (Baltic states, Belarus, Moldova): main trends of the first quarter of the 21st century

The article identifies the main trends of the territorial dynamics of the Russian population of the Baltic states, Belarus, Moldova and Transnistria during 2000s-2010s. It was found that, correlating with the general decline, the geography of Russian population also decreased. However, in all the studied countries the fragmentation of the settlement system occurred at the expense of settlements of lower taxonomic ranks (farms, small villages). In larger settlements, Russian groups persisted even in Moldova and Lithuania, which demonstrated the highest rates of demographic decline of Russian communities in the post-Soviet period. The largest concentrations of the Russian population in all the considered countries remained in the capitals. Moreover, they were also the epicenters of assimilation, the main factor of Russian depopulation in the 2000s and the first half of the 2010s. The level of urbanization of Russian communities remained very high in all the countries (80-90%), but at the beginning of the 21st century it decreased. This process was related not so much to the increased rootedness of Russian villagers, but rather to the migration of the Russian population from peripheral regions to the rural outskirts of metropolitan agglomerations. Being a form of deurbanization, it represented a variant of the geodemographic metropolization of Russian communities (the increasing concentration in capital regions). Only in Moldova the increased demographic stability of rural Russians was determined by a small group of old believer villages amidst a high level of derussification of the rest of the settlement network. Only the Russian community of Transnistria demonstrated an increased territorial and quantitative stability in the 2000s and 2010s. It clearly illustrated the significant role of geocivilizational orientation of post-Soviet states in the demographic dynamics of the local Russian population.

ЦИКЛИЧНОСТЬ ЭКОНОМИЧЕСКОЙ ДИНАМИКИ

Cyclical dynamics is a universal form of movement of nature, society and the economy. The specificity of economic dynamics is that it has a more probabilistic character than, for example, natural cycles. It is important to take this fact into account in the process of forecasting economic development. In the modern economy, forecasting plays an essential role, which is due to the practical significance of forecasts. The cyclical type of oscillation is characterized by repeated periods of decline and rise. The uneven development of the economy, reflected in the distribution of dynamic series of statistical data characterizing the results of economic activity for various types of fluctuations in economic dynamics, is a basic condition for the development of management technologies on a state and economic scale. However, in the practice of public administration of national economic complexes and the national economy as a whole, the economic unevenness of economic development is often ignored. The cyclical nature of economic dynamics and the onset of the crisis are determined by the trends in the development of production and the economy as a whole, the state of socio-economic relations, the content and nature of public life. The imbalance of the economic interests of the state and private capital, economic and political elites and citizens can lead to crises in the economy. The peculiarity of cyclicity in the agricultural sector of the Russian economy, the nature and duration of the crisis determine the need for the use of non-standard methods of crisis management, which is facilitated by a comprehensive study of existing problems, the causes of downward trends in economic dynamics and the effectiveness of priority areas of industry development. The latest financial and economic crisis of the world economy, which affected Russia and the most vulnerable sphere of its economy - the agricultural sector, showed that the process of achieving sustainable agricultural development is long and requires effective use of state support measures and various elements of anti–crisis management, the development of tools for diagnosing and forecasting crisis phenomena, the formation of programs for the soft passage of agriculture downward trajectory of the economic cycle. The article discusses the theoretical foundations of the cyclical nature of economic dynamics.

Global trends and hotspots in the field of mitochondrial dynamics and hepatocellular carcinoma: A bibliometric analysis from 2007 to 2023

BackgroundMitochondria are dynamic organelles, and mitochondrial dynamics are important for the maintenance of mitochondrial inheritance and function. Recently, an increasing number of studies have shown that mitochondrial dynamics play an important role in the occurrence and development of hepatocellular carcinoma (HCC). However, bibliometric analyses of mitochondrial dynamics in HCC are scarce. Therefore, we conducted a bibliometric analysis to explore the current global research status and trends in mitochondrial dynamics and HCC. MethodsGlobal publications on mitochondrial dynamics and HCC published between 2007 and May 2023 were retrieved from the Web of Science Core Collection (WoSCC) database. Bibliometric analysis was performed using Bibliometrix, VOSviewer, and CiteSpace to analyze the numbers, citations, countries, institutions, authors, journals, references, and keywords. ResultsA total of 518 publications were retrieved fromthe WoSCC database. China and The Fourth Military Medical University were the most productive countries and institutions. Zorzano, A published the most literature whereas Chen, HC was the author with the highest number of co-citations. Plos One was the most popular journal, whereas the Journal of Biological Chemistry had the highest number of co-citations. The most frequently used keyword was “mitochondria”. Further analysis of the references and keywords showed that the molecular mechanisms linking them to drug therapy targets should be the focus of future studies. ConclusionsResearch on mitochondrial dynamics in HCC has received much attention, and many studies have been published. However, research on mitochondrial dynamics and HCC has been limited by insufficient regional development imbalances and global cooperation. Nevertheless, future research on mitochondrial dynamics and HCC is promising, especially regarding the molecular mechanisms of mitochondrial fission and fusion and how to link the currently known molecular mechanisms with drug therapy targets for HCC.

TMELand: An end-to-end Pipeline for Quantification and Visualization of Waddington's Epigenetic Landscape based on Gene Regulatory Network.

Waddington's epigenetic landscape is a framework depicting the processes of cell differentiation and reprogramming under the control of a gene regulatory network (GRN). Traditional model-driven methods for landscape quantification focus on the Boolean network or differential equation-based models of GRN, which need sophisticated prior knowledge and hence hamper their practical applications. To resolve this problem, we combine data-driven methods for inferring GRNs from gene expression data with model-driven approach to the landscape mapping. Specifically, we build an end-to-end pipeline to link data-driven and model-driven methods and develop a software tool named TMELand for GRN inference, visualizing Waddington's epigenetic landscape, and calculating state transition paths between attractors to uncover the intrinsic mechanism of cellular transition dynamics. By integrating GRN inference from real transcriptomic data with landscape modeling, TMELand can facilitate studies of computational systems biology, such as predicting cellular states and visualizing the dynamical trends of cell fate determination and transition dynamics from single-cell transcriptomic data. The source code of TMELand, a user manual, and model files of case studies can be downloaded freely from https://github.com/JieZheng-ShanghaiTech/TMELand.

Growth and development and trends in overweight and obesity among 7-12 years old Hmong children in China: an analysis of eight successive national surveys from 1985 to 2019.

To explore the dynamic changes and trends in the body shape of Hmong children aged 7-12 years from 1985 to 2019, and to predict them, to provide a reference for the physical health level of Hmong children. The body shape data of Hmong children aged 7-12 years old from the Chinese National Survey on Students' Constitution and Health (CNSSCH) in 1985, 1991, 1995, 2000, 2005, 2010, 2014, and 2019 were used for longitudinal comparative analysis, and the grey GM(1,1) model was established based on this as a time series. Forecast the future development trend in 2025 and 2030. 1) From 1985 to 2019, all indicators of body shape of Hmong primary school students showed an upward trend, the increase in height (F Boys = 3.91, p > 0.05; F Girls = 3.91, p > 0.05), weight (F Boys = 8.04, p < 0.01; F Girls = 6.36, p < 0.05) and BMI (F Boys = 19.15, p < 0.01; F Girls = 10.24, p < 0.01) increased with age, rate of growth: Weight > BMI > Height, girls grow faster than boys; 2) The prevalence of overweight and obesity increased year by year, from 5.2 and 1.2% in 1991 to 12.4% (χ2 linear trend = 3.89, p < 0.05) and 8.7% (χ2 linear trend = 3.98, p < 0.05) in 2014, respectively, showing a significant growth trend, especially after 2000, overweight and obesity have entered a stage of rapid growth; 3) The forecast results show that the height, weight and BMI will continue to increase in 2025 and 2030, but the growth rate will decrease, the increase of weight and BMI is greater than the height, overweight and obesity are still expected to increase rapidly. The growth and development level of Hmong elementary children continues to increase, and the prevalence of overweight and obesity is increasing year by year, requiring early prevention and intervention to promote the healthy development of physical fitness of Hmong, as well as other ethnic minority students.

The Wax and Wane of CPO Prices in India: A DCC Approach to Understanding Market Sentiment

This study provides a detailed analysis of Crude Palm Oil (CPO) price dynamics, focusing on the relationship between spot and future prices during significant global events, notably the COVID-19 pandemic and the Ukraine-Russia conflict. Utilizing Dynamic Conditional Correlation (DCC) models, the research examines conditional returns and covariance, as well as the correlation trends in the Crude Palm Oil (CPO) market. The study reveals critical insights into market behavior during these tumultuous times. For instance, sharp increases in covariance during key periods suggest strong movement synchronicity between spot and future prices, potentially driven by market-altering events. The onset of COVID-19 and the escalation of the Ukraine-Russia conflict are identified as significant influencers, disrupting global supply chains and impacting global food supplies, which in turn affect both spot and future Crude Palm Oil (CPO) prices. Additionally, the research finds a dynamic correlation trend between the future and spot prices of Crude Palm Oil (CPO). Starting with a strong positive correlation in 2018, the study observes a gradual decrease in this correlation, especially after 2020. This trend indicates diverging market forces or perceptions, particularly in response to the COVID-19 pandemic and the ongoing Ukraine-Russia conflict. Such fluctuations in correlation suggest varying market sentiments and expectations, which have implications for market risk assessment, hedging strategies, and speculative activities

Exploration and efficiency assessment of the management model of higher vocational education with poa concepts

Abstract Current vocational high school management practices suffer from low efficiency, mainly due to inadequate backing from pertinent educational theories. In this study, the POA concept is first used as a guideline for the innovation of the management mode of higher vocational education, and 30 provinces, cities, and autonomous regions in China are taken as the research objects. Then, based on the output and input indicators, we constructed the efficiency assessment system of education management, used the DEA model to make static measurements of education management efficiency in 2020-2022, and further analyzed the dynamic evolution trend of the efficiency of higher vocational education management by using the Malmquist index. According to the results, less than 50% of higher vocational colleges and universities are classified as non-DEA practical situations. For these higher vocational colleges and universities, their input redundancy and output insufficiency are analyzed, in which the two input indicators of total public expenditure and the number of administrative personnel of decision-making unit 1 are insufficient. The input insufficiency rate is 13.43% and 73.01%, respectively. According to the input and output of each higher vocational college or university, the corresponding solution measures are proposed to improve the efficiency of educational management of higher vocational.

Measurement of Dynamic Electric Consumption Trend in a Broiler House in Arkansas

Highlights We quantified the diurnal and seasonal electric load pattern during four consecutive growouts of heavy broilers over an 11-month period on a commercial farm. Consumption was measured separately for ventilation fans, lights, feed motors, well pump motors and radiant tube heater blowers. Ventilation fans were the largest consumer of energy and the largest contributor to peak demand on the farm. Average monthly electric demand ranged from 31% to 77% of the corresponding monthly peak demand, calculated from the largest 15-min period. The electricity cost of raising heavier-weight broiler chickens is higher in the summer ($22 per 1,000 kg live weight) than in the winter ($5 per 1,000 kg live weight). Abstract. Characterizing electric energy use in a commercial broiler house—partitioned by bird age, season, and electric load type—can provide engineers with insight for designing energy conservation practices, as well as help to analyze and design on-site renewable energy production sub-systems. This study monitored electric energy consumption in a commercial broiler house in Arkansas, raising heavy broilers (with a capacity of 17,000 birds) during an 11-month period that included four, 8-week flocks. Average electricity use (RMS voltage and current) was measured at a sampling interval of 5 min for all of the major load types, including ventilation, lighting, feed motors, and well-water pump motor. Results indicated that electric consumption for ventilation fans was the greatest load, accounting for over 88% of the total. The endwall fans (for tunnel ventilation) contributed to the peak electric demand (VA) in nine of the 11 months. Over the 11-month monitoring period, broiler chicken production had an average electric energy consumption (per unit live-weight mass produced) of 43 kWh per metric ton of live weight (in a winter flock) to 184 kWh per metric ton (in a summer flock). The corresponding electric costs were $5 per metric ton and $22 per metric ton in winter and summer flocks, respectively (based upon an electricity unit cost of $0.12/kWh). Keywords: Electricity demand, Energy efficiency, Poultry housing.