The world has changed to a massive degree in the past thousands of years. Most of the time, the amount of carbon dioxide in the atmosphere remains constant. In the late 18th century, according to the sources of CDIAC and NOOA, the level of carbon dioxide began to rise, and then in the 20th century, it went through the roof, reaching levels that had not been seen in nature for millions of years. The increase in carbon in the atmosphere is the major contributing factor to climate change. The key to reversing the damage is restoring the earth’s delicate, balanced carbon cycle. As carbon cycle depicts the way carbon moves around the earth. It consists of sources that emit the carbon component into the atmosphere. The biological side of the carbon cycle is well balanced due to respiration, where carbon dioxide is released into the atmosphere, then plants, bacteria, and algae take carbon dioxide out of the atmosphere during photosynthesis and the process they use to generate chemical energy. On the other hand, oceans are the best sources and sinks; carbon dioxide is endlessly being absorbed into the ocean and released from the oceans almost exactly at the same rate, which is rapidly influencing the carbon cycle. Similarity is a methodology that has many applications in the real world. The current research article is destined to study how statistics of carbon emission metrics are alike and belong to one cluster. In the current study, the research is destined to derive a similarity analysis of several countries’ carbon emission metrics that are alike and often fall in the range of [0, 1]. And deriving the proximity of the carbon emission metrics leading to similarity or dissimilarity. In the current context of data matrices of numerical data, an Euclidian measure of distance between two data elements will yield a degree of similarity. The current research article is destined to study the similarity analysis of carbon emission metrics through fuzzy entropy clustering.

The Three Kingdoms period of ancient China (208-280 AD) refers to the period  between Eastern Han (25–220 AD) and Jin dynasties (266–420), during which China was divided into Shu (221-263 AD), Wei  (220-266 AD) and Wu (222-280 AD) kingdoms, and then united as Jin dynasty. This paper constructs the quarterly series of alliance structures between the Three Kingdoms. By collecting and analyzing a total of two hundred and eighty-nine quarterly observations, the paper shows that the three most frequent alliance structures are ρ0: 1) the finest partition or no-alliance structure with 192 partitions; 2) Three partitions with Shu-Jin alliance and Wu singletion with 57 partions; 3) Wei-Wu alliance and one singletion Shu with 12 partions. It also shows that the observed changes in alliance structures were the consequence of a total of fifteen major battles fought by the three kingdoms. Such results serve as a contribution to the studies of applied game theory, alliance study, and the economic and military histories in ancient China.

The purpose of this research study is to identify the factors of knowledge sharing among library professionals of higher educational institutions of Pakistan. There are very few studies on the knowledge exchange between library professionals in Pakistan’s higher education institutions. In this study model which has all the elements used to examine the knowledge sharing, in the study researcher investigate the impact of technological, organizational and individual on library professionals’ knowledge sharing behavior. The study adopted a descriptive survey design as research design and quantitative as type of research type. Questionnaire was adapted and used to collect data from 240 librarians through Google form survey in the higher educational institutions. The population of study is higher educational institutions of Pakistan. Convenience sampling techniques was used for data collection. The data were analyzed through the measurement model and structural equation model (PLS-SEM). The results of the study technological development, organizational development and individual development are significant for knowledge sharing in higher educational intuitions in Pakistan. This study gave new insights through to policy makers for the future polices to higher authorities.

The nighttime economy has always been an important part of tourism in Thailand. The alcohol industry contends that lifting alcohol restrictions will promote tourism and, consequently, generate additional income. Endogenous Growth Theory, however, emphasizes on investing in human capital, innovation, and knowledge as the most important factors that affect economic growth for a nation. Alcohol consumption incurs opportunity costs, as households lose financial resources and time that could be invested in children’s development. Relaxing control measures to promote alcohol consumption should impede economic development by diminishing the quality of human resources. The paper, therefore, aims to estimate the impact of alcohol consumption on economic growth by using 1990–2019 annual data from Thailand. By adopting Autoregressive Distributed Lag (ARDL) approach, the results reveal that alcohol consumption has significant and negative effects on economic growth in the long run. The statistic tests demonstrate no presence of serial correlation, heteroskedasticity, as well as, endogeneity problems. The finding has been corroborated in international studies, in which alcohol consumption contributes to substantial social and economic costs of the society.

The purpose of this research was to investigate the influence of innovative organizational culture on innovativeness through human resource management and the innovative skills of personnel. The population of this study comprised small and medium enterprises (SMEs) in Thailand from both the manufacturing and service sectors. Purposive sampling was employed to gather information from entrepreneurs, executives, or department managers of SMEs through an online questionnaire distributed via email, obtaining a total of 440 responses. Data were analyzed using descriptive statistics and structural equation models (SEM) for hypothesis testing. The results indicated that SMEs in this context had a moderate level of innovative organizational culture, human resource management, innovative skills, and innovativeness. Moreover, the structural equation model was consistent with the empirical data, revealing that innovative organizational culture has a direct influence on innovativeness. Furthermore, human resource management and the innovative skills of personnel were found to be partial mediators in the relationship between innovative organizational culture and innovativeness. The indirect effect through these two variables was greater than the direct effect. These findings confirmed the relationship between innovative organizational culture, human resource management, innovative skills, and innovativeness among SMEs in Thailand, leading to guidelines for businesses to improve their innovativeness.

The research aims to investigate the prospective implications of Artificial Intelligence (AI) on traditional media, and to elucidate the conceptualization of AI within the discourse of media professionals, governmental and private media stakeholders in Jordan, alongside media scholars and IT experts. Employing the focus group method, a specialized interview tool distinguished by its purpose, design, and procedures, two distinct cohorts were engaged: media practitioners and officials on one hand, and academics and experts on the other. The investigation revealed the absence of a universally agreed upon terminology concerning AI, attributable to its nascent nature and rapid evolution. Notably, AI, leveraging its diverse and highly proficient tools, demonstrates significant potential for transformative impacts across various facets of the media landscape. These encompass the facilitation of exceptional content production, the empowerment of journalists to express their creative capacities, and substantial reductions in time, labor, and procedural overheads in media product development. Concurrently, the integration of AI within media environments is anticipated to pose formidable challenges to existing institutional frameworks. Additionally, the imperative of curriculum development in academic institutions, both public and private, is underscored to acquaint students with AI methodologies.