bluuebunny/crossref_metadata_2025 huggingface dataset:
Farmers’ intention towards drone adoption in granary areas of KADA, IADA Kemasin Semerak, Kelantan and IADA KETARA, Terengganu, Malaysia
Authors: Man N , Ramli N N , Che’Ya N N
Published: December 2024

Rice is Malaysia’s staple food and, therefore, critical to the nation’s food security. To ensure sufficient production, the country relies on designated granary areas as government-recognised regions dedicated to paddy cultivation, with major and minor granary areas spread across the country. However, the paddy production in Kelantan and Terengganu falls short due to factors such as ageing farmers, farm size, labour, etc. Drone technology offers a promising solution, particularly for automating fertiliser application, pesticide spraying, and seed broadcasting. The technology aligns with the principles of sustainable agriculture, as it supports both environmental stewardship and economic sustainability in food production while enhancing productivity and food security. Although farmers acknowledge the advantages of drones, the widespread adoption of this technology remains elusive. Therefore, this study aims to investigate the intentions of paddy farmers to adopt drones in granary areas of KADA, IADA Kemasin Semerak, and KETARA. Data was collected from 384 respondents through surveys and analysed using descriptive analysis. The results revealed high levels of knowledge (K) of respondents, subjective norms (SN), perceived behaviour control (PBC), attitudes (ATT), and intention (INT) towards drone adoption among the respondents. In conclusion, the study suggests a high level of perceived intention for drone adoption among paddy farmers. Based on these findings, it is recommended that paddy farming development authorities organise programmes to promote and encourage drone use. This will help farmers overcome challenges in paddy farming that drone technology can address.
Multi-criteria overlay analysis to determine road management priorities based on regional economic condition indicators
Authors: Kresnanto Nindyo Cahyo , Putri Wika Harisa , Hapsari Murti Ayu
Published: December 2024

Road construction has a positive impact on the growth of economic businesses and people’s income; although it is not felt quantitatively by the community, from a macro perspective, it increases Gross Regional Domestic Product (GRDP) significantly. So, ideally, the entire road network in an area must be managed well and evenly. However, the regional government’s budget will only be able to fund some maintenance or improvements to existing roads. Conditions like this require prioritization of road management based on regional conditions. This research aims to prioritize road management with a case study in Purwodadi Regency, Central Java Province, Indonesia. Prioritization uses a spatial analysis approach with several spatial indicator variables of economic conditions: the accessibility index, the ratio of road length to regional area, the independent village index, and the disadvantaged village index. The method used to analyze is multi-criteria overlay analysis (MCOA). MCOA allocates/prioritizes spatial objects (road networks) to suit certain purposes based on various attributes the selected spatial objects must have. The research results can show the road management priorities at the research location based on attribute/spatial variable influences (thematic map). Road networks in areas with a low economic index are a top management priority.
Urban geometry approaches to investigate urban heating in the Cilacap urbanized area.
Authors: Widyasamratri Hasti , Kusumawanto Arif , Musyafiq Afrizal Abdi , Puspitasari Ardiana Yuli
Published: December 2024

Residentials, commercials, and industries are urbanization indicators in many areas. Focusing on urban geometry (H/W ratio), this research was conducted. Cilacap urbanized area was chosen as the focus of the study since it became a newly developed city in southern central Java island. Not only is Cilacap the main city that connects big cities between West Java province and Yogyakarta Special Region province, but it also has national industrial objects that create a high intensity of urban development that might influence urban heating. This study investigates the urban heating in Cilacap City using urban geometry approaches in the Geographic Information System (GIS) by calculating average building height, street width, and surface towards sustainable urban planning. As expected, this study supports the urban planner in managing the urban building configuration to reduce the heat effect. There were ten street corridors to investigate. The result shows that corridor 1, corridor 2, and corridor 3 have higher UHI intensity and H/W ratio than others, corresponding to the actual street orientation.
An automated method for progress monitoring of under-ground pipe installation sites using image color analysis of iPhone LiDAR camera data
Authors: Mizutan Tsukasa , Iwai Shunsuke
Published: December 2024

This research presents an innovative method for automated progress monitoring at underground pipe installation sites. The method leverages the LiDAR camera of an iPhone to capture detailed point cloud data of construction sites. Through sophisticated image color analysis, the method accurately distinguishes between piped and non-piped areas within excavations. Key aspects of the proposed workflow include the segmentation of excavation areas, differentiation of main and side excavations, and application of an earth color mask to isolate pipes in RGB space. The study focuses on enhancing the precision of measurements like excavation width, depth, and pipe burial depth, addressing challenges in traditional construction site monitoring. The developed algorithm significantly reduces the manual labor traditionally required for dimensional measurements and construction volume evaluation, offering an efficient, cost-effective solution. Empirical tests demonstrate the method’s capability in drastically improving measurement accuracy, labor costs, and processing time in construction site monitoring. This approach represents a significant stride in the digital transformation of the construction industry, leveraging readily available smartphone technology to streamline complex monitoring tasks.
Utilizing Machine Learning to Determine User Interface Elements in Agricultural Mobile Location-Based Services
Authors: Osman Mohamad Jahidi , Idris Nurul Hawani , Mohd Salleh Mohd Radhie , Majid Zulkepli , Ismail Zamri , Othman Nurain
Published: December 2024

The evolution of mobile location-based technology revolutionizes user experiences, providing personalized services and seamless navigation. This transformation influences how individuals interact with information and surroundings, enhancing daily life’s connectivity and convenience. However, creating interactive mobile location-based user interfaces (UI) for diverse users, especially in lower-middle-income countries, poses a significant challenge. Overcoming barriers to technology adoption within this diverse user group necessitates strategic planning to prevent exacerbating the digital divide. It is imperative to comprehend farmers’ preferences and requirements, especially in the context of user interface design. This study aims to determine preferred UI elements using machine learning based on respondents’ demographic characteristics. This investigation examines the user interface preferences of chili farmers in reporting pest and disease incidents through the implementation of a machine learning algorithm. Data was acquired through surveys and field experiments involving specified user interface elements for reporting chili crop issues in Batu Pahat and Johor Bahru. The findings of this study were analyzed using the Random Forest (RF) and Support Vector Machine (SVM) algorithms, and it shows that the image icon and radio button were the respondents’ preferences in stating the name of the disease. Based on the overall accuracy and kappa values, Random Forest is the more effective model for making predictions in this study. The findings support the transition of Malaysian farmers towards becoming intelligent farmers when designing the UI based on the demographic characteristics of farmers, aligning with the objectives of the Shared Prosperity Vision 2030 and endorsing the National Agrofood Policy 2021-2030 (NAP2.0). Additionally, this initiative aligns with the Food and Agriculture Organization of the United Nations (FAO) efforts to digitize farmers, including smallholders.
Semantic segmentation of high resolution imagery using U-Net for classification of sugarcane age in parts of Lumajang Jember Regency
Authors: Jatmiko R H , Rosyadi R I , Yusdipriantono M , Dewi A L F , Dariansyah T A , Afwani M Z , Lestari F N , Raharja M A E
Published: December 2024

Sugar cane mapping at a lower cost and time is an important need for farmers and the sugar industry. Semantic image segmentation with U-Net offers a potential solution to overcome this problem. This research uses high resolution Google Satellite imagery to examine the area around the Jatiroto Sugar Factory in Jember Regency, East Java Province. The aim of this research is to carry out semantic segmentation on high resolution images using U-Net to determine the age classification of sugarcane. The results showed that U-Net was able to achieve sugarcane age classification accuracy of 83.6%. Disturbances in the form of differences in recording and contrast of image mosaic results result in the learning curve experiencing overfitting. Image segmentation reveals the presence of new objects beyond the training data, necessitating future development related to the findings of visual interpretation, field data, and segmentation data. In conclusion, U-Net shows promising potential for sugarcane age classification in Google Satellite imagery. Further research is needed to improve accuracy and overcome the various obstacles encountered.
Visualization of urban growth modelling land use change using cellular automata
Authors: Bhattacharya Apratim , Paul Prabir K. , Khatua Aniruddha , Aithal Bharath H.
Published: December 2024

The phenomenon of urbanization, which is driven by a significant growth in population, leads to the expansion of cities at the cost of reducing Land Cover areas. The necessity of monitoring and predicting urban growth trends lies in the establishment and maintenance of sustainability. The objective of this work is to utilize the Spatial Lag Model to analyze the urban growth pattern of the Asansol-Durgapur region. The aim is to investigate the interconnections between the factors contributing to urban growth. Additionally, The Cellular Automata-based SLEUTH model will be employed to forecast the likelihood of future growth in the region. The accurate modeling and prediction of urban areas necessitate the consideration of multiple variables and the utilization of big datasets, hence posing a significant challenge to researchers. The research reveals that the existence of multimodal infrastructure, such as well-connected roads, highways, and railroads, that offer convenient accessibility, along with neighbourhood development and, the presence of vacant lands in the vicinity, has a crucial role in driving population migration toward urban regions, hence contributing to urban expansion. These results aid in developing policy measures and sustainable actions to mitigate urbanization’s anthropogenic effects. Integrating machine learning with the models and continuous data updates are recommended for better urban growth predictions.
Reviewing the versioning in 3D city model to track building history and progress
Authors: Idris Nabila Husna , Azri Suhaibah , Ujang Uznir
Published: December 2024

Managing information regarding building history and progress poses significant challenges, particularly in contexts such as construction, renovation, or demolition within urban environments. This study reviews the importance and application of versioning as a solution to address these challenges. Versioning offers a systematic approach to documenting changes over time, facilitating the tracking of building evolution. In the context of 3D city models, versioning provides advantages such as enhanced visualization and analysis capabilities, enabling stakeholders to better understand the development trajectory of urban landscapes. Versioning serves multiple crucial functions within the realm of 3D city models. Firstly, it enables the depiction of temporal information, aligning with the model’s time dimension and delineating key events such as generation, modification, or destruction. Additionally, versioning acts as a vital backup and recovery mechanism, affording users the ability to revert to primary iterations should issues arise. Moreover, it plays a pivotal role in ensuring rigorous quality control, necessitating thorough examination and approval of each model iteration before progression. This study aims to delve into the significance and practicality of versioning within the context of 3D city models, employing CityGML and CityJSON formats for comparative analysis. By scrutinizing the benefits and limitations of versioning across these data models, the research sheds light on its nuanced implications. Furthermore, it surveys prior research endeavors utilizing versioning and temporal data in 3D city model applications, offering insights into existing methodologies and their efficacy. Ultimately, the investigation reveals the complexities associated with implementing versioning, particularly within the CityGML framework, attributed to its intricate schema.
Building footprint extraction from aerial imagery through semantic segmentation techniques
Authors: Teo Tee-Ann , Chen Pei-Cheng
Published: December 2024

The extraction of building footprints from aerial images is crucial for creating detailed topographic maps. Leveraging advancements in artificial intelligence, particularly deep learning, presents a promising avenue for enhancing the automation of this extraction process. This study aims to establish a methodology that employs deep learning semantic segmentation technology to detect and reconstruct building footprints from digital aerial images. The methodology encompasses several key steps: generating true-ortho images from multi-view aerial images, constructing dataset for building regions, employing deep learning semantic segmentation, and regularizing the detected building footprints. The test area is located in Hsinchu, Taiwan. The experiment utilizes 25cm aerial true-ortho images for building region detection through the TransUNet semantic segmentation method. An additional data covering approximately 7km2 was utilized as an independent check region. The precision and recall metrics for building detection achieved 90% and 91%, respectively. Post-boundary regularization, the extraction of building footprints from the identified building regions was successfully executed. This proposed scheme shows the efficacy of automatically extracting building footprints by integrating aerial orthoimagery with deep learning technology, significantly benefiting the creation of precise topographic maps.
Estimation of elephant home range in Endau-Rompin (Peta) National Park using geospatial approach
Authors: Mohd Salleh Nurul Anisah , Hassan Noordyana , Tarmidi Mohamad Zakri
Published: December 2024

The tropical rainforest coverage is decreasing has caused wildlife habitat lost. Instead of that, the wildlife especially elephants have lack source of food. Due to that, the elephants tend to go to the areas near the forest and human settlements. This problem has contributed to the occurrences of human-elephant conflict. To overcome this problem, the estimation of elephant home range is crucial as one of the approaches in establishment of wildlife corridor. To estimate the elephant home range in Endau-Rompin National Park (Peta), the habitat suitability model was utilized. The factors that characterise the elephant home range has been identified based on weighted overlay analysis based on the literature review. The parameters involve are Digital Elevation Model (DEM) data, Normal Difference Vegetation Index (NDVI), proximity to river, Land Surface Temperature (LST), Slope and land use and land cover (LULC). Buffer analysis is used to identify surrounding geographic features. Results shows that LULC was the highest weight (30 %) as influence on elephant habitat suitability. While proximity to river, slope and NDVI were weighted with 20%. The habitat suitability has shown the elephant home range of year 2018 to 2020 was increasing. As a conclusion, the weighted overlay can identify the factors that gives effects to elephant home range. However, lack of detailed information for each environmental variables on how the factors would affects.
Potential applications of remote sensing and Earth observation approaches to monitor mangrove ecosystem services: A review
Authors: Roslani Muhammad Akmal , Ismail Mohd Hasmadi , Kamarudin Norizah
Published: December 2024

Remote sensing technologies offer significant potential for monitoring mangrove ecosystems, which serve as invaluable hubs of biodiversity and providers of crucial ecosystem services (ESs). In the face of mounting threats from human activities and climate change, effective monitoring becomes paramount to safeguarding their health and the services they offer. Remote sensing and Earth observation techniques present exceptional opportunities for monitoring mangrove ecosystems and their ESs. Despite the successful use of remote sensing and Earth observation-based technologies in mapping and monitoring mangrove ecosystems, few studies have been undertaken to utilize them for assessing mangrove ESs. This paper explores the vast potential of remote sensing and Earth observation in monitoring mangrove ecosystems and assessing their ESs. Through a comprehensive review and discussion of relevant scientific literature, researchers also have employed various sensors to study carbon stocks, species diversity, biomass, and related topics. These findings provide a set of values data essential for protecting, preserving, and conserving these ecosystems and their resources, thereby facilitating better management, planning, and policymaking. By leveraging these technologies, policymakers, scientists, and conservationists can make informed decisions to conserve mangrove ecosystems and ensure their long-term viability.
Community-based mobile crack monitoring for landslide inventory
Authors: Jekop Advero Reyes , Idris Nurul Hawani , Ishak Mohamad Hafis Izran
Published: December 2024

Landslides are a common natural disaster that can cause significant damage and loss of life. In Malaysia, the current methods for monitoring and mapping landslides are mainly based on satellite imagery and field surveys. There is a lack of targeted platforms to engage communities in landslide monitoring within their neighbourhoods, with the existing platforms not specifically focusing on involving communities in landslide monitoring. Therefore, this study aims to propose a community-based crack monitoring mobile app for landslide inventory. The objectives included 1) identifying suitable data and information for a community to report landslide activities within the neighbourhood and 2) developing a mobile application for monitoring structural cracks for landslide inventory. The methodology involved five phases: planning, analysis, design, system development, and system evaluation. The findings highlighted the lack of targeted platforms for community engagement in landslide monitoring, proposing a friendly mobile application for the community to report landslides in their area. The application includes several key modules, such as user registration and authentication, data submission and retrieval, and mapping and visualisation. This study offers significant benefits by enhancing public awareness and participation, timely reporting of potential landslide risks, and practical mitigation efforts, ultimately minimising the impact of landslides and saving lives.
Assessment of sustainable geothermal potential in Patigi region, North-Central Nigeria
Authors: Salaudeen S. A. , Adagunodo T. A. , Sunmonu L. A. , Suleman K. O. , Ayanbisi O. W. , Oladapo O. F.
Published: December 2024

This study examines the geothermal potential in the Patigi region of Nigeria to address local and national power challenges. The study area and its environs are currently experiencing a power outage for the past three years. As energy is one of the most vital factors that facilitate development in a region or country at large.Aeromagnetic data were utilised to determine the geothermal potential, which could be added to the energy mix to boost the energy supply in the region. The geothermal parameters that were established from the study are the Curie point depth, geothermal gradient, and heat flow. The residual map was segmented into nine overlapping spectral blocks, and the logarithm of spectral energies was plotted against wave number. From these plots, the centroid depth (Z0) and the depth to the top boundary (Zt) were derived to calculate the Curie point depth (CPD), geothermal gradient (GG), and heat flow (HF). The results indicated that the Curie point depth values ranged from 34.09 km to 55.19 km, with an average of 41.87 km. The geothermal gradient values varied from 10.51 to 17.01 °C/km, averaging 14.13 °C/km. The heat flow values spanned from 26.27 to 42.53 mW/m², with an average of 35.32 mW/m². The deepest Curie point depth was observed in the central and northeastern parts of the study area, while shallower depths were found in other parts. Geothermal and heat flow contour maps highlighted hotspots in the southeastern and eastern regions, including Kusoji, Rogun, Ekopapo-Yagi, Etsufu, Sankwafuji, Momba, Koro, and Rodun. These hotspots are deemed suitable for geothermal energy exploitation, potentially addressing the power challenges in the study area and throughout Nigeria.Developing geothermal energy resources in Nigeria can significantly help achieve sustainable development goals 7, 9, 11, and 13. It could also enhance a reduction of unemployment and poverty in Nigeria.
Greener Technology of Producing Polyhydroxyalkanoate using Anthracene as Carbon Source
Authors: Akinwumi A.R. , Nwinyi O.C. , Ayeni A.O. , Mohan S.V.
Published: December 2024

The study investigated the potential of Bacillus cereus AAR-1 (OQ999178) to simultaneously degrade anthracene, a toxic environmental pollutant, and produce polyhydroxyalkanoate (PHA), an eco-friendly and sustainable biopolymer. Using a Taguchi L16 (4*3) array for optimization, it was found that a 10% seed inoculum, grown for 8 days in a minimal salt medium containing 400 ppm of anthracene and 2 g/L of NH4Cl as carbon and nitrogen sources, respectively, maximized anthracene degradation and PHA accumulation by B. cereus AAR-1. The bacterial biomass had a colony count of 1 x 106 cfu/ml and produced 286 mg/L of biopolymer, as extracted using a hypochlorite-chloroform solvent method. Fourier-transform infrared spectroscopy (FTIR) analysis confirmed the biopolymer as PHA. This study identifies a key hydrocarbon-degrading bacterium at a municipal dumpsite, which plays a significant role in environmental biotechnology by supporting cleaner and greener technologies. This contribution aligns with the goals of SDG 12 and 14.
Environmental Impact of Pre-occupational radon level measurements in medical imaging facilities of a tertiary hospital in south-west Nigeria
Authors: Aremu A. A. , Oni O. M. , Oladipo A. E. , Oladapo O. O. , Obafemi Y. D. , Oniha M. I. , Babarimisa I. O. , James U. E.
Published: December 2024

Radiation facilities are placed in an enclosed environment to prevent scattered radiation from getting out of the room, by so doing the rooms foil gas exchange from the outdoor environment, thereby increasing the radon concentration in the indoor air. This study aimed at estimating the occupational radon exposure level in medical facility room in order to estimate the radiological risk in such environment. RAD7 electronic device was used to measure the indoor radon concentration in the five proposed rooms in the newly built Radiology department of a University Teaching Hospital while a digital thermometer was used to measure the ambient temperature. The radon concentrations ranged between 12.09 Bq/m3 and 58.52 Bq/m3. The ultrasound room has the least average value of 12.09 Bqm−3 and the Fluoroscopy room has the maximum average value of 58.52 Bqm−3. The radon level translated into the effective dose, working level and excess life-time cancer risk for any worker staying for a period of nine hours per day, over a year. Fluoroscopy facility was estimated to present the highest annual absorbed dose and annual effective dose with 0.73 mSvy−1 and 0.8858 mSv y−1, respectively. The mean radon concentration for the five rooms was 41.96Bq/m3. The calculated annual effective dose rate and the mean annual absorbed dose rate to the lung within the radiation facilities rooms were 0.529 mSvy−1 and 0.6350 mSv y−1, respectively. The indoor radon concentrations measured and the effective dose value of 200 Bq/m3 and 1 mSvy−1 respectively is below the reference limit set by International Commission Radiation Protection (ICRP) Agency. This implies that the radiation facility rooms are in conformity with international best practices and this is in agreement with SDG 3 (Good Health and well –being)
Effective Sustainable Vector Control of Anopheles gambiae in Ota
Authors: Adedoyin E. D. , Cleanclay W. D. , Iheagwam F. N.
Published: December 2024

This study investigates the resistance status of Anopheles gambiae in Ota to malathion, fenitrothion, alphacypermethrin, and deltamethrin, and its implications for sustainable vector control and public health. Female larvae and pupae were collected from breeding sites in Atan and Nestle areas using the standard dipping method and reared to adulthood (2-5 days old, non-blood-fed). These adult mosquitoes were then assessed for responsiveness to malathion (5%), fenitrothion (1%), deltamethrin (0.05%), and alphacypermethrin (0.05%) following World Health Organization standard protocols. Genotypic analysis of knockdown resistance (kdr) alleles in the resistant mosquito population was conducted using polymerase chain reaction. The mortality rate of the mosquitoes to malathion and fenitrothion (100%) exposure was higher than alphacypermethrin (11.8%) and deltamethrin (12.5%). Contrary, the 50% and 95% knockdown time thresholds of alphacypermethrin (1.47 ×108 and 2.57×108 min) and deltamethrin (190.12 and 319.53 min) were higher than malathion (52.86 and 84.02 min) and fenitrothion (53.35 and 90.71 min). The kdr allele frequency was 100% for alphacypermethrin resistance and 23.5% for deltamethrin. This study shows the high efficacy of malathion and fenitrothion for mosquito control and potential resistance to alphacypermethrin and deltamethrin in Ota. Robust mosquito surveillance and resistance profiling on a large scale is required in Ota for effective sustainable vector management and malaria eradication promoting good health and wellbeing.
Sustainable Role of Terminalia catappa Extract for Maintaining Antioxidant Activities in Wistar Rats
Authors: Iheagwam F.N , Adedoyin E.D
Published: December 2024

Oxidative stress is linked to various diseases, including cancer and cardiovascular disorders, due to the imbalance between reactive oxygen species and the body’s antioxidant defenses. The use of natural antioxidants presents a sustainable approach to mitigating oxidative damage, aligning with Sustainable Development Goals 3 and 12. This study evaluates the impact of repeated oral administration of Terminalia catappa aqueous extract (AETC) on antioxidant activities in Wistar rats over 28 days. The enzymatic activities and non-enzymatic concentration of endogenous antioxidants were investigated in the plasma and tissues at the end of the experiment. Results indicated increased renal superoxide dismutase, hepatic peroxidase, erythrocyte and renal glutathione-S-transferase activities. Hepatic reduced glutathione concentration was increased while plasma and renal malondialdehyde concentrations were reduced. These results emphasise AETC’s tissue-specific antioxidant effects and its potential as a protective agent against oxidative damage, consolidating the ethnobotanical use of Terminalia catappa leaves as a tonic for health-improving benefits promoting good health in addition to advocating for ecofriendly and sustainable health solutions. Further elucidatation of AETC antioxidant mechanisms and optimisation of its therapeutic applications is required.
Environmental Impact Assessment for Sustainable Development in Malaria-Endemic Regions: Addressing the Threat of Drug-Resistant Plasmodium falciparum in Africa
Authors: Nwinyi O. C. , Balogun D. O. , Isibor P. O. , Oyesile O. O. , Oyegbade S. A. , Mameh E. O. , Aririguzoh V. O.
Published: December 2024

Malaria is a significant cause of death for children under the age of five years and pregnant mothers. In Africa, Plasmodium falciparum is the primary cause of malaria. According to the World Health Organization, sub-Saharan Africa accounts for over 84% of malaria cases worldwide. This impact leads to an economic burden and high mortality rates of maternal and infant mortality. The pathogenic virulence of Plasmodium falciparum is attributed to specific molecular markers that confer resistance to antimalarial medications. The observed genetic variability in markers, such as the chloroquine resistance transporter genes and dihydrofolate reductase pathway, result from events related to mutations or changes that transpire at one identifiable genetic loci. This resistance significantly reduced therapeutic efficacy in most African countries. This review examined the growth and spread of resistance mechanisms and evaluated potential antimalarial drugs using novel medication combinations. A key focus of this review is the potential to identify and validate new molecular markers in blood samples from infected patients using DNA methylation profiling, microarrays, and DNA and RNA sequencing. The significance of this is that it reveals the trends of the parasite spread and the consideration of combining molecular marker testing with clinical treatments. This knowledge would assist researchers in looking for accurate and real-time markers to evaluate artemisinin combination therapy resistance. The emergence and spread of drug-resistant Plasmodium falciparum pose a challenge to global health. Therefore, sustainable development strategies to address this issue will focus on informed decision-making, baseline assessment of previous information on drug resistance, and future forecasts on the impact of molecular markers in most African countries.
Environmental assessment of radionuclides within hydrocarbon producing communities in Ondo State, Nigeria
Authors: Bayode O. P. , Alabi O. O. , Isola G. A. , Morakinyo R. O. , Araka I. O. , Ogunwale E. I.
Published: December 2024

This study aimed to evaluate the presence of radionuclides in water and fish within oil and gas-producing areas of Ondo State, Nigeria. A carefully calibrated Nal (TI) detector was used to analyze 25 water and 25 fish samples from various sites within these communities. Radionuclide concentrations in the water ranged from 93.20 ± 0.41 to 1957.12 ± 5.86,Bq/l while in fish, it ranged from 37.30 ± 0.16 to 783.01 ± 2.34.Bq/kg The study also calculated the absorbed gamma radiation dose rate and excess lifetime cancer risk based on the detected radionuclides. While the radiological hazards exceeded recommended safety levels in water samples, fish samples remained within global permissible limits. The findings highlight potential health risks from radiological exposure in these regions, especially concerning water usage, which contradicts the goals of SDG 6 on ensuring safe access to water. The contamination due to oil spills continues to threaten both aquatic life and human health.
Stochastic Dynamical Modeling for Time-series Zero-Degree Isotherm Heights Prediction over Tropical Climate
Authors: Lawal Y. B. , Owolawi P. A. , Tu C. , Van Wyk E. , Ojo J. S.
Published: December 2024

The accurate prediction of zero-degree isotherm height plays a significant role in weather forecasting and climate modelling, which have applications in agriculture, aviation, telecommunications, and disaster management. Climate action as one of the Sustainable Development Goals (SDGs) can only be achieved continuous study and understanding of our complex atmosphere. The dynamics of the atmosphere is a hot issue in research due to the random process or random probability distribution of the parameters associated with the environment, in which rain height is a key factor. Advanced Deep Learning (ADL) has achieved reasonable results in many fields and the associated applications, especially in the accurate prediction of time-series events. In this study, we adopted stochastic dynamical models to forecast Zero-Degree Isotherm Height (ZDIH) in Akure, a tropical region located in the Southwestern Nigeria. Existing methods, including traditional statistical approaches and ITU-R recommendations, have shown limited accuracy and generalizability due to their inability to capture intricate patterns in atmospheric data. One of the goals of this research is to identify gaps in the existing methods, such as their reliance on shallow learning techniques and their inadequacy in processing large volumes of data with high variability. This research proposes a new approach by applying the Seasonal AutoRegressive Moving Average (SARIMA) and two ADL models, namely; the Long Short-Term Memory (LSTM), and the hybrid LSTM, referred to as Long Short-Term Memory - Convolutional Neural Network (LSTM-CNN) model. Six years (2005-2010) of archived data from the National Aeronautics Space Administration (NASA) are used for the prediction. The result shows seasonality and a fairly stable trend over the yearly analysis. The ZDIH is generally low throughout the rainy season with a mean value of 4.75 km while mean of 4.94 km was observed during the dry season. Validation and comparison of the models revealed that SARIMA (2, 1, 1)(1, 1, 1, 12) model has a better performance over the other two models with RMSE and r2 of 46.3 and 0.89, respectively. The LSTM provides a fair performance, while the hybrid LSTM-CNN model performed poorly. The outcome of the research suspects the seasonality feature (i.e parameter “s”) of SARIMA could be responsible for its higher prediction accuracy over the ADL models. The results obtained demonstrate that the model significantly improves forecasting accuracy and it is hereby recommended for prediction of ZDIH the tropical region.
Emotional Alignment for Human-Robot Cooperation in Musical Tasks
Authors: Wang Huijiang , Iida Fumiya
Published: December 2024

Current artificial intelligence (AI) studies have witnessed the widespread use of large language models (LLMs), significantly impacting human-machine interaction (HMI) by endowing machines with emotional subtleties. Despite the efficacy of LLMs, it remains a challenge for the learning-based agents to develop reliable computational emotion models, particularly for real-world human-robot teaming, due to the lack of embodiment. This paper investigates emotional alignment within physical human-robot interaction (pHRI) scenarios. We propose a theoretical framework that enables the robot to cooperate with a human pianist in accomplishing piano-playing tasks. By considering the human users’ emotional states, the robot regulates keystroke dynamics and fingering arrangements, crucial factors affecting the resultant musical quality. Utilizing multimodal sensors and sensor fusion, the robot can capture, interpret and infer the emotional states of the human user. Consequently, the robot’s decision-making process for action selection mirrors human-like artistic patterns.
Sustaining Evolution for Shallow Embodied Intelligence
Authors: Langdon W. B. , Hulme Daniel
Published: December 2024

Lenski’s experiments with E. Coli show Biology can sustain continual evolutionary improvement. However long term evolutionary experiments (LTEE) with evolutionary computing find that information theory’s failed disruption propagation (FDP) in deeply nested genetic programming (GP) hierarchies can greatly slow adaptation. We propose that researchers aiming at embodied artificial intelligence should control software robustness by using porous high surface area geometrical architectures, perhaps composed of many shallow mangrove like tree structures intimately linked to their data rich fitness environment.
Inherent Behavioral Stochasticity in Soft Robots: Analysis and Control Strategies
Authors: Nazeer Muhammad Sunny , Zaidi Syeda Shadab Zehra , Cianchetti Matteo , Falotico Egidio
Published: December 2024

The unique composition of soft robots, predominantly constructed from elastomers and polymers, amplifies the likelihood of unpredictability in their performance, setting the stage for significant behavioral stochasticity as compared to their rigid counterparts. In this paper, we present a control-centric perspective on the intrinsic behavioral stochasticity observed in soft robots, exploring the underlying reasons and presenting control methodologies tailored to address the associated challenges. In addition to these challenges, we also provide insights on the potential benefits that the intrinsic behavior of the soft structure can have when they come in contact with unstructural environments. Finally, we discuss the generic control schemes traditionally used with these robots and highlighted potential strategies to alleviate the performance gaps introduced by the inherent unpredictability.
Experience-based Learning and Adaptive Behavior for Improved Situation-Awareness of a Social Robot
Authors: Sirithunge Chapa , Jayasekara A. G. Buddhika P. , Chandima D. P.
Published: December 2024

When robots work in close contact with their human counterparts, they have to perceive their surroundings adequately. Hence have adequate situation-awareness. In such cases, an encounter will include the robot itself, the surrounding and the humans. Existing frameworks to interpret such situations, considered a limited number of observable human cues and inputs from the surrounding so far. Therefore only a few aspects of a situation were effectively perceived by these mechanisms. In our work, we trained a Deep Q-Network (DQN) which takes a number of attributes in a situation as input before a robot makes decisions regarding an interaction in a domestic environment. Large number of situations were simulated and trained, so that adaptive responses were generated through the model for different individuals a robot will encounter. Hence an experience-based, adaptive cognitive framework for robots has been developed for initiating an interaction with their humans. This creates situation-awareness in a robot and enables user-centered perception, demolishing the requirement of the human to adopt a restricted behavior to accommodate the robot’s limited perceptive skills. Human acceptance towards the system has been evaluated through a set of experiments conducted over a period of time. Critical observations during the experiments have been highlighted.
Market Sensemaking for Consumers’ Collective Political Agency
Authors: Dalmoro Marlon , Peñaloza Lisa
Published: December 2024

Employing the theoretical lens of Weick's work on sensemaking, this paper explains how consumers collectively decipher and address their political interests. Based on historiographic data among Gaúchos in Southern Brazil, the findings detail how improvised enactments of consumer culture trigger interpretive capacities that decipher the effects of the enactments on the group, and how articulation of hot conflict and cool inference interpretations politicize such enactments. Ultimately, such socially engaged articulation informs committed interpretation, compromise, and consensus, that in turn motivate and justify subsequent enactments advancing group interests. Discussion elaborates the importance of sensemaking capacities and articulation, and the significance of committed interpretation in enabling and blocking collective compromise and consensus. This research contributes to knowledge of: 1) meso-level processes of collectively reasoned action among members of a consumer culture, 2) group structure enhancing consumers’ collective market sensemaking, and 3) particular market sensemaking challenges for consumption politics in a postcolonial context. The paper closes with suggestions for further research in other forms of consumer culture in postcolonial conditions.
Risks and Opportunities of Citizens’ Governance Spaces: Insights for Democratic Theory and Practice
Authors: Dzur Albert W. , Hendriks Carolyn M.
Published: December 2024

Chapter 6 draws out opportunities, risks, and lessons of citizens’ governance spaces. Opportunities include fostering practical political agency, as citizens instigate and lead policy work; enacting inclusion, voice, and outreach; allowing citizens to rethink and reframe issues, experiment, and work nimbly across sectors. Risks include reproducing inequalities, co-opting civil society, behaving unaccountably, and shifting the production of essential public goods to under-resourced or unrepresentative citizens. Critics of neoliberalism worry that citizen spaces merely meliorate gaps in the market or state rather than contest bigger structural causes; citizen governance solutions can mask the severity of some public problems and weaken calls for government action. The chapter reflects on theoretical insights from citizen spaces, arguing that their problem-solving governance work aligns with pragmatic, Dewey-inspired democratic theory and prompts the reconstruction of core concepts such as “democratic experimentalism.” The chapter draws out key lessons for citizens and for public, private and civil society actors who might partner with them.
Shakespeare and Science
Authors: Rutter Tom
Published: December 2024

This book shows how Shakespeare’s plays and poems made detailed use of the knowledge and theories about the cosmos, the natural world, and human biology that were available to him. These range from astronomical and anatomical ideas derived from medieval scholars, Islamic philosophers, and ancient Greek and Roman authorities, through to the challenges issued to those models by more recent figures such as Copernicus and Vesalius. Shakespeare’s treatment of these materials was informed by the poetic and dramatic media in which he worked: in particular, the inherently dialogic nature of drama enabled an approach that could be provisional, exploratory, and tolerant of uncertainty and contradiction. Shakespeare made the early modern playhouse a venue for the production of scientific understanding through performance, illusion, and the creative use of space. As well as surveying current scholarship that contextualizes Shakespeare’s work in relation to histories of meteorology, matter theory, humoral physiology, racialization, mathematics, and more, Shakespeare and Science offers detailed and original readings of texts including the Histories, Hamlet, Antony and Cleopatra, Othello, King Lear, The Tempest, the Sonnets, and Lucrece. It also makes extensive reference to primary works by figures such as Robert Recorde, William Fulke, Juan Huarte, and Thomas Elyot. Its four chapters focus on astronomy and meteorology, matter, the body, and mathematics, and its overall approach is informed by recent critical and historical work that interrogates ‘science’ as a concept and that questions both the boundary between literature and science and the idea of a seventeenth-century ‘scientific revolution’.
Professional Boundaries and Dual Relationships in Rural Social Work
Authors: Barsky Allan
Published: December 2024

This chapter delves into the complex ethical issues that may arise in the context of rural social work practice. Specifically, it focuses on the challenges of maintaining appropriate professional boundaries and managing dual relationships when working in small, tight-knit communities, where dual relationships and multiple connections are commonplace, and authenticity and informality are highly valued. The chapter also explores the strengths and positive opportunities of practicing in this context. In other words, it considers not only how to minimize the potential harms of managing professional boundaries and dual relationships but also approaches that maximizes potential good. It reviews the relevant ethical principles and standards, focusing on those related to the core social work values of access to services, human relationships, integrity, and respect for the dignity and worth of all people. The chapter also considers whether and how rural social work practice is different from urban practice, including how factors such as culture, access to resources, social expectations, norms, and traditions may affect decisions about the most effective and most ethical ways to interact with individual clients, families, groups, organizations, and communities.
The Long Walk: Autumn 1568
Authors: Snow Dean
Published: December 2024

David Ingram, Richard Browne, and Richard Twide began their long walk in October 1568. They knew of the French outpost known as Fort Caroline in northeast Florida from Hawkins’s stop there in 1565. They made that their goal, hoping to find a ship returning to Europe there. The evidence allows reconstruction of their route, segmented into 12 highly likely waypoints of their 246-day journey by foot and canoe, 87 days fewer than they needed to travel 3,651 miles in 11 months at 15 miles per day. Their autumn 1568 hike took them from waypoint 1 to beyond waypoint 4. The trail system of eastern North America had been developed and used by the indigenous nations of the continent for millennia. In Texas they followed trails previously used by the Spanish explorer known by his title as Cabeza de Vaca, and like him they learned to use sign language to communicate with speakers of the many languages they encountered. Ingram made his usual observations of plants, birds, and other animals along the way.
The Long Walk: Winter 1568–1569
Authors: Snow Dean
Published: December 2024

The winter segment of the long walk took Ingram, Browne, and Twide through three highly probable waypoints along the northern Gulf Coast. At or very near the town de Soto had earlier named Iniahica they found out that Fort Caroline had been destroyed by the Spanish. This forced the three men to set a new goal. They only other spot they knew to be regularly visited by northern European ships was Cape Breton, northern Nova Scotia. This was a dauntingly distant goal but seemingly the only one possible. They headed northeastward, beginning along trails previously traversed by de Soto and his army in 1540. They followed these as far north as Cofitachequi, where de Soto had turned inland through the Appalachian Mountains in search of gold. Ingram continued northeast, past Occaneechi town and on to Chesapeake Bay. Here they entered the coastal domain of Eastern Algonquian speakers, whose people and towns would be documented by John White and Thomas Harriot in the 1580s. By this time the three men were adept itinerant traders, making their way from town to town like the many indigenous trading teams they encountered.
The Long Walk: Summer 1569
Authors: Snow Dean
Published: December 2024

After passing through the farming villages of southern New England, Ingram and his companions entered the coastal region along the Gulf of Maine. Here farming was not productive, and the Eastern Algonquian villagers were mostly hunter-gatherers. The indigenous man known as Tisquantum, “Squanto” to the English, later described in considerable detail the same countryside that Ingram saw a few decades earlier. Their residents are often referred to today as Eastern Abenaki. Here Ingram saw a more northerly adaptation, people who wore warm clothing and relocated seasonally. Ingram and his partners came to the end of the indigenous trail system when they reached the Penobscot River. Further progress toward their goal at Cape Breton would require travel by swift birchbark canoes on interior rivers and their tributaries.