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Environmentally benign synthesis of CuO impregnated activated carbon nanocomposite for prompt bifunctional water splitting applications
No full textThe global pursuit of sustainable energy solutions has intensified the exploration of efficient and eco-friendly methods for hydrogen production, particularly through the hydrogen evolution reaction (HER) from renewable energy sources. Our research focuses on combining bio-waste-derived activated carbon nanomaterials with green-synthesized copper oxide nanoparticles (CuO@AC) to create efficient electrode materials for enhancing HER and oxygen evolution reaction (OER). The surface features of the composite material indicate a nanoarchitectonics of rubble morphology, and multiple intense peaks provide evidence for the successful fabrication of each expected crystalline phase, reflecting the overall composition and structural integrity of the nanomaterials. Findings also make known that CuO nanoparticles combined with activated carbon exhibit high efficiency for both HER and OER activities. It required an overpotential of 137 mV at 10mAcm-2 current density and a Tafel slope of 94 mV dec-1 to drive the HER, while an overpotential of 194 mV was required to achieve a 10 mA cm-2 current density and a Tafel slope of 67.9 mV dec-1 for the OER catalysis process. This work aims to enhance our understanding of the interactions between activated carbon and metal oxides, highlighting the potential of tailored electrocatalytic materials for sustainable energy conversion and contributing to net-zero emission targets
Ultrasensitive and selective electrochemical sensor for paracetamol based on thiacloprid nanocomposite
No full textThe study introduces a novel electrochemical sensor for paracetamol (PCM) determination based on a nanocomposite composed of zinc layered hydroxide (ZLH) intercalated with sodium dodecyl sulphate and thiacloprid (SDS-THI), integrated with multiwalled carbon nanotubes (MWCNTs). The sensor aims to address limitations of conventional analytical techniques and improve sensitivity, detection limits, and portability. Electrochemical techniques, including electrochemical impedance spectroscopy, square wave voltammetry and cyclic voltammetry, were employed to characterize the sensor performance. The ZLH-SDS-THI/MWCNTs sensor showed superior electrocatalytic activity, with a wide linear range (0.7 to 30 mM) and a low detection limit (LOD = 0.33 mM), outperforming several previously reported sensors. The enhanced performance is attributed to the synergistic properties of the composite materials, which offer improved electron transfer, a high surface area, and effective analyte interaction. Importantly, the sensor demonstrated excellent selectivity, as interference studies revealed that common biological and ionic species such as ascorbic acid, glucose, fructose, lysine, chloride, magnesium, and sulphate ions, even when present at 10-, 20-, and 50-fold excess concentrations relative to PCM, caused less than 10 % signal variation. This confirms the sensor’s robustness and reliability in complex sample matrices. Overall, this work highlights the potential of incorporating unconventional organic dopants, such as thiacloprid, into layered nanostructures to enhance the performance of electrochemical sensors, offering a promising platform for the selective and sensitive determination of pharmaceutical compounds in environmental and clinical applications
Study of the electroreduction process of indium ions from aqueous electrolyte
No full textThe work focuses on the mechanism of the electroreduction of indium ions in an aqueous electrolyte containing hydrochloric acid. The potential region for the electroreduction of indium ions on platinum (-0.3 to -1.5 V), nickel (-0.8 to -1.5 V), and Pt/In (-0.63 to -1.5 V) electrodes was determined by recording potentiodynamic polarization curves. The influence of several factors, including temperature, indium ion concentration, scan rate, and disk electrode rotation speed, on the electroreduction of indium was investigated. It was established that increasing both the temperature and the indium ion concentration in the electrolyte accelerates the reduction process. The process is primarily controlled by the diffusion of indium ions to the cathode surface. Furthermore, polarization curves were obtained using a rotating platinum disk electrode. The dependence of the current density on the electrode rotation speed at different potentials showed that the electroreduction process of indium ions in an aqueous electrolyte is accompanied by diffusion polarization
Prediction of Design Hourly Volumes on Roads with a Dominantly Local Character of Traffic Flows
No full textThe analysis of design hourly volumes is one of the fundamental preconditions for the procedures of designing and evaluating road design solutions. In most cases, on road sections with a predominantly local character of traffic flows, there is an absence of automatic traffic counters, and determining the design hourly volumes is very difficult. In this regard, defining the design hour and developing a model for predicting design hourly volumes based on short-term traffic counts are the primary goals of this paper. Based on data from road sections with an automatic traffic counting system, the design hour is within the range of the 8th to the 16th hour of ordered hourly volumes. After further analysis, the 10th hour was adopted as the proposed value for determining design hourly volumes in local conditions. The prediction model is based on linear regression, i.e. modelling the relationships between the dependent variable, design hourly volume and independent variables, peak traffic volumes during design days. The model was tested for 10th and 30th hours in order to verify the model in local conditions as well as in accordance with the recommendations of the Highway Capacity Manual. The research results indicate that the average percentage deviation of the model-estimated design hourly volumes based on short-term traffic counts compared to the actual realised volumes ranges from 8% to 9%, depending on the analysed design hour
Trust in Artificial Intelligence and Its Acceptance in Croatian Society
No full textImportant questions concerning citizen trust in artificial intelligence (AI) systems have been raised by their rapid development and widespread application throughout various social and economic activities. Trust in AI has become a crucial element determining the level of its societal acceptance along with a series of interconnected factors. This study aims to investigate the factors influencing trust in AI, the social implications of such trust and distrust, as well as the perception of and readiness to accept AI within Croatian society. Conducted on a sample of 500 respondents in the Republic of Croatia, the research sought to examine the frequency of AI tool usage, the level of trust in AI, and the citizens’ readiness to accept it in everyday and professional contexts. The results indicate an overall moderate level of trust in AI, characterized by a prevailing cautious optimism. Most respondents recognize the benefits of AI in various life situations, while also expressing pronounced caution and selective acceptance of certain forms of its application. Simultaneously, they voice concerns regarding ethical dilemmas. The analysis shows that trust in AI is significantly correlated with the frequency of AI tool usage and the level of digital literacy, suggesting that personal experience and understanding of the technology positively influence the perception of its reliability. Within the Croatian context, a key remaining challenge relates to raising the level of public awareness and building a transparent system for AI application based on ethical standards and social responsibility
Estimation of the Specific Charge in the Tunnel Excavation by Using the Drilling and Blasting Method
No full textThe specific charge (q, kg/m3) is one of the decisive technical parameters to the efficiency of tunnel construction using the drilling and blasting method. To accurately determine and calculate the specific charge (q, kg/m3), thereby improving the efficiency of tunnel construction, currently, there are many methods to determine the specific charge (q, kg/m3), such as: Pokrovsky's method, experimental method, and method of using numerical simulation software. In this paper, the authors used artificial neural network (ANN) and Random forest (RF) techniques to build artificial intelligence models capable of identifying and predicting the specific charge (q, kg/m3) with high accuracy. By using data compiled during the construction of the Deo Ca tunnel, Phu Yen, Vietnam, artificial intelligence models with ANN and RF techniques were built. Based on the prediction results of artificial intelligence models with specific data compiled from the actual construction process of Deo Ca tunnel, the accuracy of the results of the artificial intelligence models was confirmed
Evaluating the Impact of Conservation Tillage on Desert Agro-Pastoral Ecosystems in Inner Mongolia Using Remote Sensing and GIS
No full textAs part of China's northern ecological fragile zone, the desert regions of Inner Mongolia face severe challenges from wind erosion, desertification, and the sustainable development of agro-pastoral systems. Conservation tillage practices - such as reduced tillage, no-tillage, and straw mulching - play a vital role in improving the ecological conditions of these areas. The integration of remote sensing (RS) and geographic information systems (GIS) provides essential technical support for evaluating their ecological impact. However, current research faces limitations including inadequate spatial resolution in traditional methods, poor adaptability of RS change detection algorithms to the complex spectral characteristics of desert environments, and a tendency to assess ecological impact using single-factor analyses. These issues hinder a comprehensive understanding of the overall effects of conservation tillage on agro-pastoral ecosystems. This study leverages GIS and RS technologies to address three core objectives: (1) to analyze the spatial distribution of conservation tillage practices in Inner Mongolia's desert areas and examine their correlation with topography and climate; (2) to apply the Fast Bag-of-Visual-Words (BOVW) algorithm to enhance the accuracy and efficiency of change detection in conservation tillage regions using RS imagery; and (3) to comprehensively assess the impacts of conservation tillage on desert agro-pastoral ecosystems from multiple dimensions, including soil properties, vegetation growth, water resource utilization, and ecosystem services. The study establishes a technical evaluation framework tailored to arid and semi-arid regions, providing a scientific basis for optimizing agricultural production layouts and ecological protection in Inner Mongolia, and offering methodological insights for sustainable development in similar regions
High-Efficiency MPPT Strategies for Floating and Conventional Solar PV: A Simulation- Based Study
No full textSolar photovoltaic (SPV) systems are an environmentally friendly and recyclable source of renewable energy. Direct connection of solar panels to the load results in suboptimal power provision. Therefore, getting the maximum performance from the SPV system is essential to improve efficiency. Various techniques have been proposed to track the maximum power point (MPPT) of the SPV system. Traditional MPPT techniques are usually limited to uniform weather conditions. This paper presents a comprehensive comparative analysis of Maximum Power Point Tracking (MPPT) techniques employed in conventional and floating solar photovoltaic (PV) systems. The study examines various MPPT techniques, including perturb and observe (P&O), particle swarm optimization (PSO), and artificial neural networks (ANN), in both conventional and floating solar photovoltaic systems. The simulations were performed in a MATLAB/Simulink environment. The results of the comparison of MPPT algorithms in this study show that all these algorithms display very high-efficiency rates, generally above 97%, indicating good overall performance of MPPT systems. Still, the ANN and PSO techniques remain at the top. It is also worth noting that FPV systems tend to produce more power than LPV systems, particularly in the summer
Restorative Justice Education Programmes in South African Prisons: The Experience of Phoenix Zululand Facilitators
No full textThe contemporary notion of restorative justice began to emerge during the 1970s and 1980s, a period characterised by a growing recognition of the need to reform criminal justice systems that have traditionally prioritised punishment over the rehabilitation of offenders and the reconciliation between offenders and victims. This study investigates the experiences of facilitators at Phoenix Zululand, who implement restorative justice education programmes within correctional facilities. It evaluates the effectiveness of these programmes and examines the challenges facilitators face in their implementation. Using a qualitative research approach grounded in an interpretivist framework and utilising a phenomenological research design, the study involved 10 participants who were selected through a purposive sampling technique. Data analysis was conducted using the thematic analysis technique. The findings indicate that facilitators possess a generally positive perspective regarding restorative justice education programmes in South Africa’s correctional facilities, noting benefits for both their professional growth and the rehabilitation of offenders. Nonetheless, challenges were identified, including limited access to facilities and gender dynamics affecting female facilitators. These findings emphasise the critical need for effective policy implementation of restorative justice principles within the correctional system