Different Levels Of Importance Research Articles

НЕЧЕТКИЙ МЕТОД ПОВЫШЕНИЯ КОНТРАСТНОСТИ КАРТОГРАФИЧЕСКИХ ИЗОБРАЖЕНИЙ НИЗКОГО КАЧЕСТВА

In this study, we have developed a new image enhancement method that uses fuzzy logic. This method allows us to split pixel values into different levels of importance, which helps to compensate for the loss of local brightness in dark and bright areas of an image. The goal is to increase the overall brightness of the image while preserving details. The process involves three stages. Firstly, the satellite image is transformed into a membership space using the c-means clustering algorithm. This creates a model that can be used to convert each pixel value into a level of importance. Secondly, a corresponding model is created for each level of importance based on the membership data. Finally, the image is transformed back into a standard brightness space by combining the grayscale values for each level. Our results show that this method improves the visual quality and accuracy of measurements when compared to traditional methods.

Effects of listeners’ dialectal variation on comprehensibility and accentedness judgements of second language speech

Abstract This study investigated the impact of listeners’ dialectal variations within the same L1 on perceptions of L2 speech comprehensibility and accentedness. Thirty untrained British and American English-L1 raters assessed recorded L2 speech samples from 29 Finnish learners of English and provided scalar judgments for their comprehensibility and accentedness. Four linguistically trained graduate students evaluated the samples for segmental accuracy, speech rate, word stress and intonation. Results of linear mixed models indicated no significant effect of raters’ L1 variety on global comprehensibility and accentedness ratings. While American and British raters relied on same pronunciation features in their comprehensibility judgments, they placed different levels of importance on pronunciation features when making accentedness judgments. Particularly, both groups primarily exhibited sensitivity towards segmental errors in their assessments of accentedness, whereas American raters demonstrated an additional sensitivity to intonation. The findings underscore the complexity of accent perception based on the L1 variety of listeners.

Realities or mythologies: England's village pubs and counterurbanisation

The countryside is again becoming a ‘popular’ destination for many as they seek to find residence away from the urban. Within this narrative of counterurbanisation village services, and interactions within them are often seen as being attractive and integral to the ‘dream’ of rural living. Yet the realties are often very different, as can be seen through the village pub. Whilst the village pub for many represents a space which goes beyond the consumption of alcohol and offers economic, social, and cultural importance, it can also be a space of difference and inequality. However, there remains a gap in our knowledge regarding the different narratives ascribed to the village pub from those who have moved or want to move to the rural. And how these narratives are often interwoven with the ‘rural idyll’ leading to inaccurate representations and unrealistic expectations of the village pub. The importance of this paper resides addressing some of the above gaps by looking at the village pub, its meaning and importance to individuals and communities in the context of counterurbanisation. By looking at the village pub through, an English rural county, and a cultural lens this paper highlights that the village pub is seen and experienced as adding value of different kinds – economic, social, and cultural, and that different groups attach different levels of importance to these kinds of value. Through drawing on Bourdieu's concept of capitals to explore these values it is shown that the different kinds of value attached to village pubs can work in the Bourdieusian interpretation as capital and be self-expanding and inter-convertible but can also work to undermine one another. Thus, impacting on how village pubs are seen and experienced within the context of counterurbanisation.

Identifying future district heating potentials in Germany: a study using empirical insights and distribution cost analysis

District heating will play an important role in the transition towards climate-neutral heating. Various studies on modelling the energy system show that district heating and the related expansion of the networks can have different levels of importance. A main reason is that the costs for distribution grid expansion are not well or not at all considered and empirical evidence for a threshold for cost-effective distribution costs is missing in such studies. In this paper, we aim to improve empirical evidence allowing to improve the representation of future district heating expansion in energy systems models. For that, the current status of district heating is analysed in high spatial resolution for Germany. The results show that with the currently accepted average costs, a large range of the possible future market share of district heating for buildings between 17 - 52% is possible by 2050, with the parameters of the connection rate and the renovation rate of the building stock. We conclude that the district heating share could be increased by the factor of 2 to 5 in the future, proving the importance of climate-neutral district heating in the transition.

Proposal of an innovative MCDA evaluation methodology: knowledge discovery through rank reversal, standard deviation, and relationship with stock return

Financial performance analysis is of vital importance those involved in a business (e.g., shareholders, creditors, partners, and company managers). An accurate and appropriate performance measurement is critical for decision-makers to achieve efficient results. Integrated performance measurement, by its nature, consists of multiple criteria with different levels of importance. Multiple Criteria Decision Analysis (MCDA) methods have become increasingly popular for solving complex problems, especially over the last two decades. There are different evaluation methodologies in the literature for selecting the most appropriate one among over 200 MCDA methods. This study comprehensively analyzed 41 companies traded on the Borsa Istanbul Corporate Governance Index for 10 quarters using SWARA, CRITIC, and SD integrated with eight different MCDA method algorithms to determine the position of Turkey's most transparent companies in terms of financial performance. In this study, we propose "stock returns" as a benchmark in comparing and evaluating MCDA methods. Moreover, we calculate the "rank reversal performance of MCDA methods". Finally, we performed a "standard deviation" analysis to identify the objective and characteristic trends for each method. Interestingly, all these innovative comparison procedures suggest that PROMETHEE II (preference ranking organization method for enrichment of evaluations II) and FUCA (Faire Un Choix Adéquat) are the most suitable MCDA methods. In other words, these methods produce a higher correlation with share price; they have fewer rank reversal problems, the distribution of scores they produce is wider, and the amount of information is higher. Thus, it can be said that these advantages make them preferable. The results show that this innovative methodological procedure based on 'knowledge discovery' is verifiable, robust and efficient when choosing the MCDA method.

Expounding the Environment of Small and Medium Enterprises (SMEs): A Qualitative Study Conducted in Pakistan

The aim of this study is to expound the environment of SMEs by way of identifying, ranking and classifying factors that affect growth of SMEs. The overall design of the study comprises of review of literature, data collection from primary sources and application of modeling techniques. This is a qualitative study that comprises of literature review along with experts’ opinion for exploring environmental factors affecting growth of SMEs. The experts are selected on the basis of non-probability based purposive sampling and data is collected by face to face interview through a questionnaire. The factors are ranked in different levels of importance using Interpretive Structural Model (ISM) which later on are classified in independent, dependent, autonomous and linkage using MICMAC. The results of literature review and experts’ opinion show that there are fifteen important factors that are critical. The results of ISM show that the least critical factors occupying Level I includes ‘age of enterprise’, ‘experience of owner’ and ‘education of owner’, whereas, ‘trade internationalization’ is the most critical factor occupying Level IX. Remaining eleven factors are with effects that range on the continuum of moderate to severe moderate occupying middle position of the model. The results of MICMAC reveal that trade internationalization is categorized as the important independent factor along with seven other factors. Six factors are categorized as dependent factors. Only one factor is classified as autonomous, and as such no factor is categorized in linkage. This is a seminal research study that contributes to the literature by providing new firsthand information on the phenomenon under study by using novel mathematical modeling techniques. This study is helpful to all stakeholders including Government, industry, researchers and academicians in prioritizing the critical factors for revolutionary growth of SME sector.

Integrating fish nursery ground conservation with sustainable resource use: The case of Trichiurus japonicus in the East China Sea

Abstract Sustainable fisheries management seeks to balance fisheries' conservation with fishers' economic well‐being. Marine protected areas are increasingly used as a component of management frameworks to improve the resilience of, or maintain, marine resources. However, any spatial management measures need to consider the seasonal distribution of key species at key life stages, such as the recruitment stage. Trichiurus japonicus (hairtail) is the highest yielding single fish species in China, but it is showing signs of miniaturization and early maturity, which are indicators of overfishing. Thus, it is a suitable model species for studies aiming to find a solution to the challenge of balancing fishing activities with resource protection. The potentially important seasonal nursery grounds of T. japonicus in the East China Sea were identified using a model combining data for the variability in abundance and the probability of occurrence of T. japonicus recruits. Based on fishery‐independent survey data, a Bayesian hierarchical species distribution model revealed that the locations and sizes of core nursery grounds of T. japonicus varied seasonally and that the main drivers were depth, sea bottom temperature and sea bottom salinity. The possible seasonal interactions between fishing effort and nursery grounds at different levels of importance were evaluated by analysing the spatial overlap between fishery hot spots and T. japonicus core nursery grounds. The results showed that the proportion of overlap was highest in spring and lowest in summer. These findings highlight the urgent need to develop fleet‐adapted management measures for different levels of overlap and suggest that the eastern and southern areas of the East China Sea hairtail national aquatic germplasm resources conservation zone (TCZ) should be included in conservation planning.

Winter is coming: How laypeople think about different kinds of needs.

Needs play a key role in many fields of social sciences and humanities, ranging from normative theories of distributive justice to conceptions of the welfare state. Over time, different conceptions of what counts as a need (i. e., what is considered a normatively relevant need) have been proposed. Many of them include (in one way or the other) needs for survival, decency, belonging, and autonomy. Little work has been done on how these kinds of needs are evaluated in terms of their significance for distributive justice. To begin closing this gap, we investigate the role of the four aforementioned kinds of needs for impartial observers. We do so in two empirical studies. The first study asks participants to evaluate the importance of each of the four kinds of needs separately. We find that different levels of importance are attributed to the kinds of needs, which places them in a hierarchy. The second study asks participants to make distributive decisions. Results further support the hierarchy found in the first study and, additionally, reveal that participants tend to make coherent allocation decisions.

Improving QoS in mobile multimedia streaming with SCTP-PQ

The Stream Control Transmission Protocol (SCTP) is often the preferred transport layer protocol in streaming applications. This protocol combines the best aspects of Transmission Control Protocol (TCP) and User Datagram Protocol (UDP), but also offers additional features. SCTP supports multihoming and multi-streaming applications and has a congestion mechanism like TCP. Media streaming consists of different types of frames with different levels of importance. For example, I-frames carry more information than B-frames in Moving Picture Experts Group (MPEG). Usually, MPEG frames are processed using the First-In-First-Out (FIFO) algorithm. In this paper, a four-level priority queue integrated protocol named SCTP Priority Queue (SCTP-PQ) has been developed to reduce jitter and delay in real-time multimedia streaming for mobile devices. As part of the development, priority and retransmitted packets are determined on the sending side and these packets are processed faster by using the priority queue on the receiving side. In this way, the average queue delay of priority packets on the receiving side is reduced by 90 % and the throughput values are increased by an average of 10 times. The developed protocol has been extensively tested and compared with SCTP. The results show that the SCTP-PQ outperforms the standard SCTP in terms of jitter and delay.

The importance of warehouses in logistics outsourcing: benchmarking the perspectives of 3PL providers and shippers

PurposeAn ever-increasing number of companies outsource logistics activities to third-party logistics (3PL) providers to beat the competition. From the buyer's (shippers') perspective, selecting the right 3PL provider is crucial, and from the 3PL provider's perspective, it is imperative to be attractive and to retain clients. To this aim, a potential lever can be physical assets, such as warehouses, which the literature has traditionally neglected. The objective is to benchmark the importance of warehouses for 3PL providers to attract/retain clients and for shippers to select the right 3PL provider.Design/methodology/approachThe authors performed an empirical investigation through interviews on dyads (3PL providers/shippers) and utilized the Best-Worst Method (BWM) to rank the criteria used in the 3PL buying process and allow the warehouse's role to emerge.FindingsResults show that the 3PL buying process consists of four phases and three evaluation steps. The selection criteria are classified into three groups: order qualifiers, order winners and retention factors. The warehouse has different levels of importance throughout the process. It appears that it can indirectly enhance the attractiveness and retention capability of 3PL providers through other selection criteria.Originality/valueBy combining the resource-based view and the customer value theory, this research extends the theory on logistics outsourcing by studying the phases of the 3PL buying process and scrutinizing the criteria used in different evaluation steps. The research adds a double perspective of analysis (3PL providers and shippers), which is missing in the literature, and focuses on the importance of warehouses.

Authenticity and Performance: An Analysis of the Influence of Strong and Weak Relationships on Users' Self-Presentation in Social Media

The rise of online social media has led to a shift in peoples social interactions from offline to online platforms. Online social interaction has become an integral part of societal interactions. Platforms like WeChat Moments and Tik Tok offer distinctive social channels, providing a platform with a more diverse audience. As a result, individuals can present their performances to audiences with different levels of relationship strength. This paper aims to explore the differences in self-presentation motivations and strategies when facing audiences with different levels of relationship strength on WeChat Moments and Tik Tok. This paper analyzes the impact of relationship strength on self-presentation, exploring the influence of strong and weak relationships on college students self-presentation in social media. Based on the survey and interview results, the paper compares the differences and connections in self-presentation of college students on WeChat Moments and Tik Tok. The findings indicate that the images users present on social media are closely related to their relationship with the audience. Users adjust their self-presentation strategies based on the composition ratio of strong and weak relationships in the social platform. Furthermore, users perform different degrees of impression management, presenting different levels of authenticity. Users also assign different levels of importance to different audiences and adopt different image correction strategies based on the level of importance. Moreover, in response to the findings of the study, the paper highlights the problems that exist in social media interaction and makes targeted recommendations for the development of online social interaction.

Impact of the 50 biggest pharma companies: a review of Environmental report aspiring to NetZero

Abstract Background Pharmaceutical companies have a considerable environmental impact in terms of waste disposal, CO2 emissions, plastic usage, and air pollution, water and energy consumption (including those related to transportation and refrigeration of drugs). According to data from 2019, pharmacological firms’ CO2 emissions are 13% greater than those of the car industry. To follow a greener path, pharmaceutical companies should primarily invest in sustainable production and supply, standard criteria, rewards programs, and staff training. This review aims to examine how pharmaceutical businesses incorporate environmental sustainability concerns into their operations, regulations, and communications. Methods We selected the top 50 pharmaceutical companies by revenue using the drugdiscoverytrends.com database. We collected the 2021 ESG report for each company, examining the following aspects: the inclusion of a ‘sustainability’ section or a downloadable sustainability report; the disclosure of the company production and carbon footprint; the existence of concrete measures to limit CO2 emissions, save water and energy, and reduce the effect of transportation. Data were analyzed through descriptive statistics to assess the sustainability of companies. Results Preliminary results indicate that each organization has a different level of importance for the topic of sustainability. Companies focused on CO2 production, few on other areas such as water needs or impact on biodiversity. Logistics correspond to the most impactful carbon footprint. Future forecasts and the path to NetZero emissions will also be emphasized, possibly comparing them with upcoming ESG 2022 reports. Conclusions The first results of our review show that the 50 biggest pharmaceutical companies have a different kind of interest towards environmental-friendly actions. Those with the highest revenues seem to be more careful towards the green issues, but the route to NetZero is still far to be achieved. Key messages • The environmental impact of pharmaceutical companies is greater than other industries. They must balance their business goals with environmental sustainability to reach NetZero as soon as possible. • The future goal of public health will be to monitor the environmental impact of drug production.

The impact of varying key sensory attributes on consumer perception of beer body

Beer body remains a poorly defined term, and although technical brewing experts currently describe it as the fullness of flavour and mouthfeel, little is known regarding the impact of different sensory factors on its perception. Previous studies have linked consumer understanding of beer body with viscosity (e.g. thickness, smoothness), alcohol warmth and flavour intensity. Therefore, modifications to these attributes in a base beer were explored. A commercial 0.05 % lager beer was used as the beer base, with ethanol additions at two levels to yield 2.8 and 4.5 % alcohol by volume (ABV), resulting in three levels in total for ethanol. Viscosity, bitterness and hoppy aroma were each increased to perceivably different levels by the addition of carboxymethyl cellulose (CMC), iso-α-acids, and hop oil extract, respectively, resulting in two levels for each (with addition and without). Beer samples (n = 18) were evaluated by naive UK beer consumers (n = 100) for overall liking, the intensity of perceived body and consumer-derived attributes using the Rate-All-That-Apply (RATA) technique. A 4-way ANOVA revealed significant positive effects of all four variables (p < 0.05) on body intensity ratings and significant impacts of ethanol, bitterness and aroma on overall liking. Correlation of RATA data with overall beer body ratings showed positive correlations with sensory attributes; smooth, overall flavour, overall aftertaste, hoppy flavour and negatively correlated with watery mouthfeel. Furthermore, cluster analysis was conducted on the body intensity ratings revealing three distinct consumer clusters based on the variables. This research suggests that beer consumers are not a homogenous group when it comes to body perception, and they place different levels of importance on different variables and their associated sensory attributes.

MSGCN-ISTL: A multi-scaled self-attention-enhanced graph convolutional network with improved STL decomposition for probabilistic load forecasting

Probabilistic load forecasting has gained widespread attention for its effectiveness in providing scientific power dispatch plans in recent years. Most existing works adopted decomposition strategies to handle the temporal features of load data, but ignored the fact that decomposition components have different levels of importance, resulting in the incomplete extraction of temporal correlation information. Moreover, previous works have primarily concentrated on the geographical correlation among neighboring load zones and overlooked the semantic correlation among load zones, resulting in insufficient extraction of spatial correlation information. In this study, a novel multi-scaled self-attention-enhanced graph convolutional network with improved Seasonal-Trend decomposition based on Loess (STL) decomposition (MSGCN-ISTL) is proposed for probabilistic load forecasting. First, an improved STL decomposition is proposed, which adopts a convolutional neural network with dual convolutional channels to separately handle the different decomposition components, thus improving the extraction of temporal correlation information. Second, a new multi-scaled self-attention-enhanced graph convolutional network is proposed to extract the spatial correlation information from geographical and semantic aspects simultaneously, which enriches the receptive fields and extracts the multi-scaled enhanced spatial features. Experimental results conducted under various conditions demonstrate the superiority and robustness of the proposed model.

Security‐based code smell definition, detection, and impact quantification in Android

AbstractAndroid's high market share and extensive functionality make its security a significant concern. Research reveals that many security issues are caused by insecure coding practices. As a poor design indicator, code smell threatens the safety and quality assurance of Android applications (apps). Although previous works revealed specific problems associated with code smells, the field still lacks research reflecting Android features. Moreover, the cost and time limit developers to repairing numerous smells timely. We conducted a study, including Definition, Detection, and Impact Quantification for Android code smell (DefDIQ): (1) define 15 novel code smells in Android from a security programming perspective and provide suggestions on how to eliminate or mitigate them; (2) implement DACS (Detect Android Code Smell) to automatically detect the custom code smells based on ASTs; (3) investigate the correlation between individual smells with DACS detection results, select suitable code smells to construct fault counting models, then quantify their impact on quality, and thereby generating code smell repair priorities. We conducted experiments on 4575 open‐source apps, and the findings are: (i) Lin's CCC between DACS and manual detection results reaches 0.9994, verifying the validity; (ii) the fault counting model constructed by zero‐inflated negative binomial is superior to negative binomial (AIC = 517.32, BIC = 522.12); some smells do indicate fault‐proneness, and we identify such avoidable poor designs; (iii) different code smells have different levels of importance and the repair priorities constructed provide a practical guideline for researchers and inexperienced developers.

Analysis of ICS and SCADA Systems Attacks Using Honeypots

Supervisory control and data acquisition (SCADA) attacks have increased due to the digital transformation of many industrial control systems (ICS). Operational technology (OT) operators should use the defense-in-depth concept to secure their operations from cyber attacks and reduce the surface that can be attacked. Layers of security, such as firewalls, endpoint solutions, honeypots, etc., should be used to secure traditional IT systems. The three main goals of IT cybersecurity are confidentiality, integrity, and availability (CIA), but these three goals have different levels of importance in the operational technology (OT) industry. Availability comes before confidentiality and integrity because of the criticality of business in OT. One of the layers of security in both IT and OT is honeypots. SCADA honeypots are used as a layer of security to mitigate attacks, known attackers’ techniques, and network and system weaknesses that attackers may use, and to mitigate these vulnerabilities. In this paper, we use SCADA honeypots for early detection of potential malicious tampering within a SCADA device network, and to determine threats against ICS/SCADA networks. An analysis of SCADA honeypots gives us the ability to know which protocols are most commonly attacked, and attackers’ behaviors, locations, and goals. We use an ICS/SCADA honeypot called Conpot, which simulates real ICS/SCADA systems with some ICS protocols and ICS/SCADA PLCs.

Applicant qualifications and characteristics in STEM faculty hiring: an analysis of faculty and administrator perspectives

BackgroundThe lack of racial diversity in science, technology, engineering, and mathematics (STEM) disciplines is perhaps one of the most challenging issues in the United States higher education system. The issue is not only concerning diverse students, but also diverse faculty members. One important contributing factor is the faculty hiring process. To make progress toward equity in hiring decisions, it is necessary to better understand how applicants are considered and evaluated. In this paper, we describe and present our study based on a survey of current STEM faculty members and administrators who examined applicant qualifications and characteristics in STEM faculty hiring decisions.ResultsThere are three key findings of the present research. First, we found that faculty members placed different levels of importance on characteristics and qualifications for tenure track hiring and non-tenure track hiring. For example, items related to research were more important when evaluating tenure track applicants, whereas items related to teaching and diversity were more important when evaluating non-tenure track applicants. Second, faculty members’ institutional classification, position, and personal identities (e.g., gender, race/ethnicity) had an impact on their evaluation criteria. For instance, we found men considered some diversity-related items more important than women. Third, faculty members rated the importance of qualifications with diversity, equity, and inclusion (DEI)-related constructs significantly lower than qualifications that did not specify DEI-related constructs, and this trend held for both tenure track and non-tenure track faculty hiring.ConclusionsThis study was an attempt to address the issue of diversity in STEM faculty hiring at institutions of higher education by examining how applicant characteristics are considered and evaluated in faculty hiring practices. Emphasizing research reputation and postdoctoral reputation while neglecting institutional diversity and equitable and inclusive teaching, research, and service stunt progress toward racial diversity because biases—both implicit and explicit, both positive and negative—still exist. Our results were consistent with research on bias in recruitment, revealing that affinity bias, confirmation bias, and halo bias exist in the faculty hiring process. These biases contribute to inequities in hiring, and need to be addressed before we can reach, sustain, and grow desired levels of diversity.

The Performance Analysis of Facial Expression Recognition System Using Local Regions and Features

Different parts of our face contribute to overall facial expressions, such as anger, happiness and sadness in distinct ways. This paper investigates the degree of importance of different human face parts to the accuracy of Facial Expression Recognition (FER). In the context of machine learning, FER refers to a problem where a computer vision system is trained to automatically detect the facial expression from a presented facial image. This is a difficult image classification problem that is not yet fully solved and has received significant attention in recent years, mainly due to the increased number of possible applications in daily life. To establish the extent to which different human face parts contribute to overall facial expression, various sections have been extracted from a set of facial images and then used as inputs into three different FER systems. In terms of the recognition rates for each facial section, this result confirms that various regions of the face have different levels of importance regarding the accuracy rate achieved by an associated FER system.

Lipoic Acid-Functionalized Hexanuclear Manganese(III) Nanomagnets Suitable for Surface Grafting.

Highly anisotropic single-molecule magnets (SMMs) have attracted much interest in the field of molecular magnetism because of their spin features and potential technological applications. Additionally, a great effort has been devoted to the functionalization of such molecule-based systems which are made with ligands containing functional groups suitable to connect SMMs to junction devices or to perform their grafting on surfaces of different substrates. We have synthesized and characterized two lipoic acid-functionalized and oxime-based Mn(III) compounds, of formula [Mn6(μ3-O)2(H2N-sao)6(lip)2(MeOH)6][Mn6(μ3-O)2(H2N-sao)6(cnph)2(MeOH)6]}·10MeOH (1) and [Mn6(μ3-O)2(H2N-sao)6(lip)2(EtOH)6]·EtOH·2H2O (2) [H2N-saoH2 = salicylamidoxime, lip = lipoate anion, cnph = 2-cyanophenolate anion]. Compound 1 crystallizes in the space group Pī of the triclinic system and 2 crystallizes in the space group C2/c of the monoclinic system. In the crystal, neighboring Mn6 entities are linked using non-coordinating solvent molecules, which are H-bonded to N atoms of -NH2 groups of amidoxime ligand. In addition, Hirshfeld surfaces of 1 and 2 were calculated to study the variety of intermolecular interactions and the different levels of importance that take place in their crystal lattice; this type of computed study is the first time performed on Mn6 complexes. The study of the magnetic properties of 1 and 2 through dc magnetic susceptibility measurements reveals the coexistence of ferromagnetic and antiferromagnetic exchange couplings between the Mn(III) metal ions in both compounds, the latter being the predominant magnetic interaction. A spin S = 4 value of the ground state was obtained using isotropic simulations of the experimental magnetic susceptibility data for both 1 and 2. Ac magnetic susceptibility measurements show features typical of slow relaxation of the magnetization in 1 and 2, which indicate that SMM behavior takes place in both compounds.

Shaping the Knowledge Base of Bioeconomy Sectors Development in Latin American and Caribbean Countries: A Bibliometric Analysis

Academic research on bioeconomy sectors in Latin American and Caribbean countries has developed exponentially over the last few years. Based on the Web of Science (WOS) database and statistical analysis of more than 18.9 thousand documents, the current article offers a bibliometric analysis of these datasets. The main bioeconomy sector identified in the results was biofuel production and all the background terms related to the primary processes of bioenergy. The other segments of the bioeconomy in the Latin America and Caribbean (LAC) region have not yet been studied with the same relevance as biofuels. Since 2008, researchers from Latin American and Caribbean countries have participated significantly in the scientific production of the field studied. However, the most relevant scientific journals belong to European countries or the United States. Journals from Latin American and Caribbean countries have very low representation, although the search topics are directly related to this region. Based on the co-occurrence of keywords, eight clusters with different levels of importance can be distinguished: (1) agriculture; (2) climate change; (3) biodiversity; (4) bioremediation; (5) bioenergy; (6) biofuels; (7) energy efficiency; and (8) bioeconomy. The above results highlight the significant research gap between biofuels and other types of bioeconomy sectors in the region. This is despite the immense biodiversity potential of the LAC countries, which can generate innovative products with bioeconomic added value that can stimulate scientific research in the sustainable bioeconomy.