Scope 3 emissions are major contributor for emissions of many industries. Since these emissions are indirect/complex in nature, data availability is a major challenge in estimating them. Current methods mostly rely on high level economic transactions with less inclusion of product details and have shortcomings in handling lack of data. In this research, we firstly discussed the benefits/shortcomings of existing methodologies for estimating scope 3 emissions and proposed a Machine Learning (ML) based framework to overcome those shortcomings. In our approach we map the Central Product Classification (CPC) system with International Standard Industry Classification (ISIC) and North American Industry Classification System (NAICS) together to gain higher granularity in scope 3 emission estimation. For ML models implementation, we used the supply chain emission factors based on NAICS codes as targeted variable. Our best performing model, Gradient Boosting Decision Trees, achieved an R² score of 0.9108 and MSE of 0.034 while giving balanced importance to CPC and ISIC codes. Results suggest our ML framework, combined with integrated classifications, can enhance the granularity and predictive accuracy for scope 3 emission factors derived from monetary input-output databases.

This paper proposed an Unmanned Surface Vehicle (USV) for water quality monitoring purposes. The USV offered high maneuverability and accurate monitoring result with IOT implementation. The paper discussed the design and development of a USV, identifying the functionality of USV sensory system, and evaluating performance of USV based on stability, velocity, and acceleration. The USV is designed based on hemisphere shape and is equipped with two brushed DC motor propellers for maneuvering purposes. The buoyancy of USV is set at 89.1% positive buoyancy for stability purposes. Dabble Gamepad controller is implemented for USV to move remotely. Temperature, pH and turbidity sensors are embedded into the USV system for monitoring purposes. Internet of Things (IoT) system is coupled with the vehicle for data monitoring via internet as it offers versatility and efficiency. The developed USV shows outstanding results in terms of maneuverability and sensors functionality. The embedded sensors reading shows stable and accurate. This developed USV will have impact in maintaining the sustainability, and wellbeing of ecosystems and health of water resources.

A natural convection greenhouse solar dryer for Kapenta fish was designed and evaluated for its effectiveness in drying performance, thermal efficiency, specific energy consumption, and economic viability in terms of net present value and payback period. The system featured a 1.0 m × 0.9 m drying tray and a 1.5 m² greenhouse floor area, with 40% of the surface exposed for additional solar heating. Constructed from LDPE film, timber, HDPE components, rocks, mosquito netting, and a zipper, the dryer was optimized for efficient airflow, heat retention, and user convenience. Natural convection facilitated continuous airflow, as heated air exited through a top outlet while cooler ambient air entered from the bottom. Internal temperatures ranged from 49 °C to 60 °C, sustained by heat-retaining rocks that extended drying beyond peak sunlight hours. During testing, a 3 kg batch of fish with an initial moisture content of 76.7% was dried to 2.1% (wet basis) within 4.5 hours, compared to 14.3% moisture under open sun drying. The system achieved a thermal efficiency of 22.3% and a specific energy consumption of 2.81 kWh/kg, with an average airflow rate of 0.021 kg/s. Even under moderate solar radiation (773.9 W/m²) and ambient temperatures (19.1 °C), the dryer performed effectively, allowing up to two drying cycles per day. With a payback period of only 1.2 years and nearly nine years of debt-free operation, the system offers a sustainable, low-cost, and practical solution for Kapenta fish preservation in solar-rich regions with limited low-temperature infrastructure.

Machine vision plays an important role in the development of agriculture to improve productivity. In the current research, this project plans to develop an automated navigation system that can carry an autonomous vehicle that will travel between rows in the orchard. The system focuses on identifying the straight lines of the tree rows by identifying the center line for robot navigation in garden rows using the Hough Transform and image processing techniques such as morphing, thresholding and edge detection with the Canny operator. The system is intended for outdoor use only as it is designed for garden navigation. MATLAB is the main software used in this project to simulate a visual approach that provides an image processing workspace with different features. The algorithm was then evaluated using several image parks with different characteristics, and the result showed that the proposed method can successfully detect center lines as autonomous vehicle guidance to travel between rows with different tree heights and sizes.

Piliostigma reticulatum (D.C.) Hochst is a plant belonging to the legume family. The population widely uses it as medicine, food, feed, and many others. This study aimed to enlighten the status of P. reticulatum in the Maradi region through an ethno-nutritional survey. Three localities in the region were concerned by the study, namely the city of Maradi, the rural commune of Sarkin Hausa (Mayahi department), and the Aguie department. A population of 920 people were interviewed, mostly constituted of Hausa ethnic group (89.5%). The respondents were classified according to gender with 36.2% female and 63.8% male. However, 55.5% of them were aged between 20 and 40 years old. The main activity of respondents was mainly agriculture (30%) followed by pupils/students (24.6%). This study shows that P. reticulatum 97.4% of the population in the study area surveys stated to recognize the plant. Furthermore, it was noted that 99% of the surveys that recognized the plant were ≥ 40 years old. On the other hand, this wild plant is better known in rural areas (100% in the rural commune of Sarkin Hausa) than in urban areas (93.53% in the city of Maradi). In addition, the tree is better used in rural areas (99% in Sarkin Hausa) than in urban areas (73.23% in Maradi). It was found that P. reticulatum is an available tree throughout the study zone (92.7%). Indeed, 89.5% of respondents know that the tree is used either in human food or in animal feed and that these pods and seeds are the most used parts accordingly 27.9% and 15.3% respectively. Indeed, highly appreciated by this population, up to its usage in traditional medicine; thus, the study revealed that 35.3% of respondents disclosed that all organs of the plant are useful.

The study on water resources is very important for a country like Mali Republic. This is because the climate of the Sahel is projected by many climate scenarios that contribute to a premature dry season. So, the Klela basin being one of the affected areas by the phenomenon is selected for this study. Hence, it is interesting to evaluate this vital resource for a better planning in order to facilitate the decision making from the concerned authorities. For this research, the hydrological model, GR4J, is used to evaluate the dynamics of the surface water flow. The main objective of this study is to assess and predict (using scenarios RCP4.5 and RCP8.5) the correlation between rainfall and runoff in the Klela basin. In tandem with on this objective, the water flow and climate data were used as input data into the GR4J model. The model was calibrated and evaluated using the time series data 2000-2007 and 2008-2013, respectively. The performance of the model was evaluated mainly based on the Nash-Sutcliffe efficiency. The overall outputs display that the surface water flow is declining over time and this is more significant in the worst scenario RCP8.5.

The purpose of this work is to investigate and evaluate the level of contamination of naturally occurring radionuclides in environmental soil samples collected at a place from West Kirby using gamma-ray spectroscopy. The Broad Energy Germanium (BEGe2825) detector has the ability to detect gamma-rays in the range of 3 keV-3MeV. This detector offers a very good resolution, low noise performance and almost ideal Gaussian shape in our analysis. Under our depth of interest of 0 – 48 cm, a total of six spectra were measured. From known values of gamma-ray energies, a calibrated curve was plotted. From the analysis, the mean activity concentration of naturally radionuclides of uranium-238, thorium-232 and potassium-40 obtained are 6.7 ± 0.1 Bq/kg, 5.6 ± 0.1Bq/kg and 398.2± 8.2 Bq/kg were found in the range of (5.37 ± 0.30- 8.86 ±0.40) Bq/kg, (4.37 ± 0.31- 8.72 ±0.35) Bq/kg and (384 ± 19 and 416 ± 21) Bq/kg respectively. Man-made radionuclides of americium-241 and cesium-137 mean activity concentrations are 4.3± 0.1 Bq/kg and 14.5 ± 0.3 Bq/kg were found in the range of (BDL: 5.95±0.32) Bq/kg and (6.66 ± 0.35- 29.2 ±1.5) Bq/kg respectively.

Reviewer Acknowledgements, Vol. 16, No. 3, August 2022

Discussions about the extent of integration of adolescent refugees as well as integrating displaced people ‘correctly’ in the respective education system of the target country have long been held about. Since crisis caused by, for example, war or the Covid-19 pandemic increase the numbers of refugees all over the world, a high number of displaced people suffer from experienced traumas and might therefore be impaired in participating in curricular education. For this study, the observation of three adolescent refugees who attend different sports classes, thus being encompassed by variable social settings, has been at the center of attention for one semester. To ensure data variety, principals, PE teachers, refugee students, ‘regular’ students have been interviewed, respectively.
 The analysis revealed that huge differences in terms of adaptation as well as impairment could be observed among the participating adolescent refugees. While one of the refugee students easily adapted among the observed manifestations (non-)verbal communication, social form, behavioral strategies and potentials of physical education, the other adolescent refugee displayed severe impairment in all of the manifestations mentioned above; hence, experienced traumata experienced before, during or after flight require newly arriving students being psychologically examined and monitored. 
  

Social CRM is a new technology that integrates social networking activities within traditional CRM itself. Social media might be the most effective strategy in the context of CRM technology concerning the availability of efforts and time by owners. Therefore, it’s important for financial institutions to take advantage of it upon this opportunity by considering social CRM as part of development and enhancing relationship with their customers. Nevertheless, little empirical studies have focused on adoption of social CRM in banking sector. This research paper aims to investigate the factors that impact banks’ intention to adopt social CRM, based on combining the Technology-Organization-Environment (TOE) with Technology Acceptance Model (TAM) as the theoretical framework. TOE variables such as top management support and relative advantages found to have a direct impact on the two TAM mediating variables (perceived usefulness and perceived ease of use), and an indirect impact on social CRM adoption. Further, results suggested that consumer pressure and competitive pressure have a direct impact on social CRM adoption. The researcher tested the hypothesis using structural equation modeling (SEM). The findings from a survey of 220 employees in banks in Palestine showed that all eight hypotheses were supported as both consumer pressure and competitive pressure in the environmental context have a significant direct impact on social CRM adoption intention, followed by top management support in organizational and technological contexts; relative advantages have the most significant impact on perceived ease of use and perceived usefulness which in turn, have a direct and significant impact on social CRM adoption intention. The contribution of the study, limitations, future studies and conclusion are presented.