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The purpose of this study was to define and outline areas prone to disease causing elements by analyzing the spatial distribution and concentration of toxic and essential elements in a section of the Voltaian sedimentary basin.

A total of 2,668 soil samples were analysed by the inductively coupled plasma mass spectrometry technique and were re-appraised by comparing with baseline values of elements accepted globally to be in soils. The concentrations of arsenic (As), chromium (Cr), iron (Fe) and magnesium (Mg) were evaluated. Factor analysis, hierarchical cluster analysis and principal component analysis multivariate techniques were used to identify the source patterns of the elements in the soils. The Getis-Ord Gi method was used to generate the optimised maps for these selected elements. These maps spatially defined and outlined high value clusters which imply potential pollution or areas with high background values (hotspots), whereas the low value clusters imply areas with low background values (cold-spots).

The multivariate analysis supports a dominant geogenic source of these heavy elements with obvious influences from variably metamorphosed mafic–ultramafic rocks known to have contributed to the deposition of sediments in the basin. The hotspots for As were located around Nalerigu and to the east of Nawchugu. A Cr hotspot was located to the east of Nawchugu with Cr cold-spots located within Nalerigu and Yunyuo. Fe hotspots were observed to the south of Nalerigu and the east of Nawchugu with Fe cold-spots around Yunyuo, Bongo-Da and Nagbo. The spatial maps demonstrated the presence of toxic and deficient areas of all the selected elements used in the investigation. Therefore, it suggested the likely health implications depending on the exposed elements, their pathways and recommended the usefulness of using the results displayed in the spatial maps to guide in devising appropriate remediation techniques.

This paper fulfils an identified need to study the distribution of elements and the possible effects it may have on the health and livelihoods of those residing in these areas.

China has established 14 marine economic development demonstration zones in 2018, which has become an important step in exploring the high-quality development of the marine economy. The paper statistically analyzes the documents related to the field of marine economy and special economic zones (SEZs) and strives to find out the hot spots, intersections and related development contexts of the two in the research direction, so as to provide some ideas for later research.

By taking the bibliographic information data of “Marine Economy” and “Special Economic Zone” in the Web of Science database as a sample, the paper applies the Citespace bibliometric tool to analyze the evolution of disciplinary distribution, research country, author collaboration and research hotspot trends in the two fields.

It can be found from the paper results that the current research on marine economy and SEZs involves the intersection of many disciplines. China and the United States are the leaders in this field. However, there is more extensive cooperation between authors from different countries, but the cooperation depth needs to be strengthened. At the same time, compared with the terrestrial economy, the trend of its research hotspots is lagging to a certain extent. Moreover, there is still no systematic and professional research paradigm on marine economy.

At present, there are a few research studies on marine economic development demonstration areas or marine SEZs, and related bibliographical references are incomplete, which leads to insufficient samples, and bibliometric methods cannot fully reveal the general research rules and development trends in this field.

The research on the marine economic development demonstration area is still in its infancy. The paper jointly analyzes the literature in the two fields of marine economy and SEZs, aims to find the intersection and related research hotspots of the two, and provides references for the future research of marine development demonstration areas, which is of certain practical significance.

This study aims to investigate the intricate relationships between a community energy system, water resources and biodiversity conservation, with a specific focus on augmenting community energy resilience in Bondo. The primary objective is to gain an in-depth understanding of how community members perceive and experience the challenges related to balancing the often-conflicting demands of energy, water and biodiversity conservation within this context.

The research uses a qualitative approach to unravel the multifaceted dynamics of community energy systems, water resources and biodiversity conservation in Bondo. Data were collected through focus groups and direct observations, enabling a nuanced exploration of community perspectives and lived experiences. The subsequent analysis of this qualitative data follows established thematic analysis procedures.

The study's findings shed light on the formidable barriers that impede rural communities in Malawi from accessing electricity effectively. Even in communities fortunate enough to have electricity connections, the lack of knowledge regarding productive electricity use results in community energy systems operating at significantly reduced load factors. Furthermore, the intricate challenge of managing a biodiversity hotspot persists, exacerbated by the densely populated peripheral communities' continued reliance on forest, land and water resources. These activities, in turn, contribute to ecosystem degradation.

In a context where government-led management of forest reserves and game reserves has not yielded the expected results due to a multitude of factors, there arises a compelling need for innovative approaches. One such innovation involves fostering partnerships between the government and experienced trusts as lead organisations, providing a fresh perspective on addressing the complex interplay between community energy systems, water resources and biodiversity conservation. This novel approach opens doors to explore alternative pathways for achieving the delicate balance between human energy needs and the preservation of vital ecosystems.

Identifying the frontiers of a specific research field is one of the most basic tasks in bibliometrics and research published in leading conferences is crucial to the data mining research community, whereas few research studies have focused on it. The purpose of this study is to detect the intellectual structure of data mining based on conference papers.

This study takes the authoritative conference papers of the ranking 9 in the data mining field provided by Google Scholar Metrics as a sample. According to paper amount, this paper first detects the annual situation of the published documents and the distribution of the published conferences. Furthermore, from the research perspective of keywords, CiteSpace was used to dig into the conference papers to identify the frontiers of data mining, which focus on keywords term frequency, keywords betweenness centrality, keywords clustering and burst keywords.

Research showed that the research heat of data mining had experienced a linear upward trend during 2007 and 2016. The frontier identification based on the conference papers showed that there were five research hotspots in data mining, including clustering, classification, recommendation, social network analysis and community detection. The research contents embodied in the conference papers were also very rich.

This study detected the research frontier from leading data mining conference papers. Based on the keyword co-occurrence network, from four dimensions of keyword term frequency, betweeness centrality, clustering analysis and burst analysis, this paper identified and analyzed the research frontiers of data mining discipline from 2007 to 2016.

The performance of Wireless Sensor Networks (WSNs) applications is bounded by the limited resources of battery-enabled Sensor Nodes (SNs), which include energy and computational power; the combination of which existing research seldom focuses on. Although bio-inspired algorithms provide a way to control energy usage by finding optimal routing paths, those which converge slower require even more computational power, which altogether degrades the overall lifetime of SNs.

Hence, two novel routing protocols are proposed using the Red-Deer Algorithm (RDA) in a WSN scenario, namely Horizontal PEG-RDA Equal Clustering and Horizontal PEG-RDA Unequal Clustering, to address the limited computational power of SNs. Clustering, data aggregation and multi-hop transmission are also integrated to improve energy usage. Unequal clustering is applied in the second protocol to mitigate the hotspot problem in Horizontal PEG-RDA Equal Clustering.

Comparisons with the well-founded Ant Colony Optimisation (ACO) algorithm reveal that RDA converges faster by 85 and 80% on average when the network size and node density are varied, respectively. Furthermore, 33% fewer packets are lost using the unequal clustering approach which also makes the network resilient to node failures. Improvements in terms of residual energy and overall network lifetime are also observed.

Proposal of a bio-inspired algorithm, namely the RDA to find optimal routing paths in WSN and to enhance convergence rate and execution time against the well-established ACO algorithm. Creation of a novel chain cluster-based routing protocol using RDA, named Horizontal PEG-RDA Equal Clustering. Design of an unequal clustering equivalent of the proposed Horizontal PEG-RDA Equal Clustering protocol to tackle the hotspot problem, which enhances residual energy and overall network lifetime, as well as minimises packet loss.

This paper aims to review the literature on carbon trading from the perspective of evolution, finds out the evolution path of these literatures and gives out the future research hotspots in this field.

Uses visualization tools (CiteSpace and HistCite) to systematically categorize the literature on carbon-trading schemes in the Web of Science core collection from 1998 to 2018, comprehensively analyzes carbon-trading schemes from four dimensions, namely, discipline evolution, keyword evolution, citation cluster evolution and citation path evolution.

Research on carbon-trading schemes has a specific development and evolution path along four dimensions, namely, in the discipline dimension, the largest change lies in the mathematics pointed to by at least four different disciplines; the keyword evolution dimension shows a gradual deepening emphasis on coordinated development; citation clusters identify three major clusters – carbon prices, China’s carbon trading, carbon market and supply chain; and citation paths identify three major evolutionary paths, the most important of which shows that “What affects carbon price?” has changed to “What is the impact of carbon prices?”

Reveals the evolution path of carbon trading research studies and proposes four possible development directions for carbon-trading scheme research, which is helpful for future carbon trading-related research and serves as a reference for the promotion of and improvements in carbon-trading schemes.

This study aims to provide a systematic and complete knowledge map for use by researchers working in the field of research data. Additionally, the aim is to help them quickly understand the authors' collaboration characteristics, institutional collaboration characteristics, trending research topics, evolutionary trends and research frontiers of scholars from the perspective of library informatics.

The authors adopt the bibliometric method, and with the help of bibliometric analysis software CiteSpace and VOSviewer, quantitatively analyze the retrieved literature data. The analysis results are presented in the form of tables and visualization maps in this paper.

The research results from this study show that collaboration between scholars and institutions is weak. It also identified the current hotspots in the field of research data, these being: data literacy education, research data sharing, data integration management and joint library cataloguing and data research support services, among others. The important dimensions to consider for future research are the library's participation in a trans-organizational and trans-stage integration of research data, functional improvement of a research data sharing platform, practice of data literacy education methods and models, and improvement of research data service quality.

Previous literature reviews on research data are qualitative studies, while few are quantitative studies. Therefore, this paper uses quantitative research methods, such as bibliometrics, data mining and knowledge map, to reveal the research progress and trend systematically and intuitively on the research data topic based on published literature, and to provide a reference for the further study of this topic in the future.

The purpose of this paper is to present a comprehensive analysis of the carbon footprint of the Delft University of Technology (TU Delft), including direct and indirect emissions from utilities, logistics and purchases, as well as a discussion about the commonly used method. Emissions are presented in three scopes (scope 1 reports direct process emissions, scope 2 reports emissions from purchased energy and scope 3 reports indirect emissions from the value chain) to identify carbon emission hotspots within the university’s operations.

The carbon footprint was calculated using physical and monetary activity data, applying a process and economic input-output analysis.

TU Delft’s total carbon footprint in 2018 is calculated at 106 ktCO₂eq. About 80% are indirect (scope 3) emissions, which is in line with other studies. Emissions from Real estate and construction, Natural gas, Equipment, ICT and Facility services accounted for about 64% of the total footprint, whereas Electricity, Water and waste-related carbon emissions were negligible. These findings highlight the need to reduce universities’ supply chain emissions.

A better understanding of carbon footprint hotspots can facilitate strategies to reduce emissions and finally achieve carbon neutrality. In contrast to other work, it is argued that using economic input-output models to calculate universities’ carbon footprints is a questionable practice, as they can provide only an initial estimation. Therefore, the development of better-suited methods is called for.

Quantitative and spatial-explicit flood risk information is of great importance for strengthening climate change adaptation and flood resilience. Shanghai is a coastal megacity at large estuary delta with rising flood risks. This study aims to quantify the overall economic-societal risks of storm flooding and their spatial patterns in Shanghai.

Based on multiple storm flood scenarios at different return periods, as well as fine-scale data sets including gridded GDP, gridded population and vector land-use, a probabilistic risk model incorporating geographic information system is used to assess the economic-societal risks of flooding and their spatial distributions.

Our results show that, from 1/200 to 1/5,000-year floods, the exposed assets will increase from USD 85.4bn to USD 657.6bn, and the direct economic losses will increase from USD 3.06bn to USD 52bn. The expected annual damage (EAD) of assets is around USD 84.36m. Hotpots of EAD are mainly distributed in the city center, the depressions along the upper Huangpu River in the southwest, the north coast of Hangzhou Bay, and the confluence of the Huangpu River and Yangtze River in the northeast. From 1/200 to 1/5,000-year floods, the exposed population will rise from 280 thousand to 2,420 thousand, and the estimated casualties will rise from 299 to 1,045. The expected annual casualties (EAC) are around 2.28. Hotspots of casualties are generally consistent with those of EAD.

In contrast to previous studies that focus on a single flood scenario or a particular type of flood exposure/risk in Shanghai, the findings contribute to an understanding of overall flood risks and their spatial patterns, which have significant implications for cost-benefit analysis of flood resilience strategies.

This paper aims to provide an overview of South African perspectives on preventing, monitoring and combating hate victimisation, towards informing international understandings.

Using a general review approach, this paper provides a historical examination of measures proposed by the South African Government and civil society since 1994, to prevent, monitor and combat hate crime, hate speech and intentional unfair discrimination.

Regardless of a constitutional commitment to social inclusion, diversity and minority rights, significant progress remains lacking after almost three decades of related advocacy, lobbying and limited government intervention. Findings of the South African Hate Crimes Working Group (HCWG) longitudinal Monitoring Project emphasise the need for decisive legal responses to hate victimisation.

A Bill, recognising hate crime and hate speech as distinct criminal offences, has been in development for almost 15 years and will soon serve before Parliament. Enactment of this legislation will be ground-breaking in Africa.

This paper contributes to the field of hate studies by providing an overview of the journey towards current conceptual understandings of hate in (South) Africa. It sets the stage for evaluating the potential of the redesigned HCWG monitoring tool, which holds promise for early identification and intervention in hate hotspots and targeted sectors. This instrument can establish trends not only in South Africa but also across the African continent.