bluuebunny/crossref_metadata_2025 huggingface dataset:
Three Myths of Kingship in Early Greece and the Ancient Near East
Authors: Metcalf Christopher
Published: December 2024

On the basis of recently discovered sources and original research, this book identifies and analyses three story-patterns associated with human kingship in early Greek and ancient Near Eastern myth. The first of these, the 'Myth of the Servant', was used to explain how an individual of non-royal lineage rose to power from obscure origins. The second myth, on the 'Goddess and the Herdsman', made the fundamental claim that the ruler engaged in a sexual relationship with a powerful female deity. Third, although kings are often central to the ancient literary evidence, the texts themselves were usually authored by others, such as poets, priests, prophets or scholars; like kings, these characters similarly tended to base their authority on their ability to articulate and enact the divine will. The stage was thus set for narratives of conflict between kings and other intermediaries of the gods.
Feminist Political Economy
Authors: Cantillon Sara , Mackett Odile , Stevano Sara
Published: December 2024

Feminist political economy is essential to understanding the power relations and hierarchies that shape and sustain contemporary capitalism. Motivated by the rejection of gender-blind approaches in economics feminist political economy provides compelling insights into the relations between the economic, the social and the political in the reproduction of inequality. Sara Cantillon, Odile Mackett and Sara Stevano have written a much-needed introduction to key topics in feminist political economy, including the global division of labour, social reproduction, child and elder care, the household and intra-household inequalities, labour market inequalities, welfare regimes, the feminization of poverty and economic indicators. The authors take a global perspective throughout and engage in debates that are relevant for the Global North and/or the Global South. The book offers readers a deeper and more nuanced understanding of the role of power relations and inequality in the economy and is suitable for a variety of courses in political economy, feminism, gender studies, economics, social policy and development studies.
How to Save the City
Authors: Chatterton Paul
Published: December 2024

A call to arms, How to Save the City invites the reader to engage with the challenges of living and working in cities at a time when several conflating emergencies have become more pressing and connected. While the climate crisis is the most urgent, we also face deep social crises in housing, gender and race inequalities, the breakdown of our natural world, our energy consumption, and the deep ripples resulting from the COVID-19 pandemic. These emergencies are playing out in acute ways in urban areas. Locked in to high-energy, high-resource use, cities are responsible for about three-quarters of global greenhouse gas emissions, have ecological and carbon footprints far bigger than their city limits, and are the beating heart of our pro-growth, unequal, consumer-saturated way of life. The city has to change, but how and by whom? Paul Chatterton engages, inspires and empowers the reader to take action to make cities more sustainable, liveable and safer places. He guides the reader through a sequence of challenges, strategies, players, moves and practical tactics of how to save their city.
Sustainable Development, Education and Learning
Authors: Thoresen Victoria W.
Published: December 2024

The UN's Sustainable Development Goal (SDG) number four (4) focuses on inclusive, quality education, galvanizing efforts for substantial educational reform around the globe. Progress is being made but are the initiatives being upscaled and mainstreamed rapidly enough? Has caring become an essential aspect of learning? Have cooperative learning and creativity been given enough attention? Are teachers receiving sufficient support? These are some of the questions raised by Victoria Thoresen as she considers the goals and challenges iterated in the SDG.

Thoresen argues that unless implementation of the new definitions of inclusive, quality education are prioritized everywhere, sustainable development will be severely hampered and, conceivably, misdirected. She examines the recent evolution of education in light of political and commercial ambitions, technological advancements, and knowledge creation and sharing. Key concerns relating to education for and learning about sustainable development are identified and major obstacles to achieving inclusive, quality education for all are discussed.
Lost in Ideology
Authors: Blakely Jason
Published: December 2024

Modern political life is a confusing and disorientating terrain of competing ideologies. Jason Blakely offers readers a lively, fresh and insightful guide through the labyrinth of conflicting and competing ideas in order to better understand why ideology in the modern era can be so divisive.

 Lost in Ideology sets out from the conviction that the current disorientation engulfing the world's liberal democracies is in no small part ideological in origin. People feel confused because there are multiple ideological maps, so to speak, each marked by dramatically different points of interest, rivers, summits, roads, and total topographies. Ideology in the modern era has the paradoxical effect of orienting millions even as it disorients millions. This leads us to the present-day predicament in which individuals of every imaginable political stripe confidently declare: 'I have a theory - but you? You have an ideology!'
Taiwan
Authors: Sullivan Jonathan , Nachman Lev
Published: December 2024

As a top twenty global economy and tech powerhouse, a liberal democracy on the frontline of autocratic pressure and a pivotal component in the free and open Indo-Pacific, the future security of Taiwan has enormous ramifications for today's global order.

Jonathan Sullivan and Lev Nachman consider Taiwan's complex and multi-layered history and the many dimensions it holds in international politics. They show that an appreciation of its critical role in geopolitics is more than just the crude dichotomies of 'democracy vs authoritarianism' or 'independence vs unification'. Its history and future are intimately tied to wider questions of decolonialism, national identity, economic interdependence, multiculturalism and modern values - all set against an ever-present security threat.
Platelet characteristics in extremely preterm infants after fatty acid supplementation: a randomized controlled trial
Authors: Lundgren Pia , Pivodic Aldina , Nilsson Anders K. , Hellgren Gunnel , Danielsson Hanna , Wackernagel Dirk , Pupp Ingrid Hansen , Ley David , Sävman Karin , Uhlén Mattias , Smith Lois E. H. , Hellström Ann
Published: December 2024

Background

Two risk factors for severe retinopathy of prematurity (ROP) in extremely preterm infants are thrombocytopenia and low levels of arachidonic acid (AA) and docosahexaenoic acid (DHA). To date, these risk factors have not been linked.

Method

Infants born < 28 weeks gestational age (GA) from 2016 to 2019 were randomized to postnatal enteral AA/DHA supplementation or standard care (controls). Levels of AA and DHA, platelet counts ( < 100 × 109/L defined as thrombocytopenia) and platelet-related proteins in the infants’ first four weeks of life were evaluated for their association with severe ROP.

Results

The mean birthweight of 178 included infants was 806 ± 200 grams, and the mean GA was 25.6 ± 1.4 weeks. During the first four postnatal weeks, 20.2% of AA/DHA-supplemented infants had thrombocytopenia versus 27.7% of controls (p = 0.29). In infants with thrombocytopenia, fewer AA/DHA-supplemented infants developed severe ROP than non-supplemented controls, 29.4% (5/17) versus 65.4% (17/26) (p = 0.031). Thrombocytopenia and serum levels of AA and DHA correlated with several platelet-related proteins involved in angiogenesis and ROP, such as platelet-derived growth factor subunits A and B and vascular endothelial growth factor.

Conclusions

AA and DHA supplementation is associated with less severe ROP in thrombocytopenic infants, possibly by modulating platelet activation and function.

Impact

Postnatal enteral supplementation with arachidonic acid (AA) and docosahexaenoic acid (DHA) to extremely preterm infants reduces the risk of severe retinopathy of prematurity (ROP) in infants with thrombocytopenia. The impact of AA and DHA might be, at least in part, mediated through altered platelet activation.

We found that AA and DHA may reduce the risk of severe ROP, possibly by modulating platelet-related proteins involved in angiogenesis.

Our findings strongly support that supplementing AA and DHA to extremely preterm infants is crucial and can significantly impact their health.
Predicting Auditory Skill Outcomes After Pediatric Cochlear Implantation Using Preoperative Brain Imaging
Authors: Yuan Di , Chang Wai Tsz , Ng Iris H.-Y. , Tong Michael C. F. , Chu Winnie C. W. , Young Nancy M. , Wong Patrick C. M.
Published: December 2024

Purpose:

Our study used preoperative neuroanatomical features to predict auditory development in Chinese-learning children with cochlear implants (CIs).

Method:

T1-weighted whole-brain magnetic resonance imaging (MRI) scans were obtained from 17 Chinese-learning pediatric CI candidates (12 females and five males, age at MRI = 23.0 ± 15.0 months). Voxel-based morphometry was applied to examine the children's whole-brain structure. Machine learning was employed using neuroanatomical features to predict children's auditory skills up to 24 months after CI. The whole-brain neural model and auditory/visual cortex neural model were compared with a nonneural model using gender, age at CI activation, and preoperative residual hearing as predictors. Model performance was quantified using the mean square error (
MSE
) between predicted values and observations.

Results:

The model with preoperative neuroanatomical features showed a significantly smaller
MSE
than the nonneural model in predicting auditory skills in children with CIs. Specifically, the auditory-related area played an important role in predicting post-CI outcomes.

Conclusions:

The preoperative neuroanatomical features outperformed the nonneural features in predicting auditory skills in children with CIs. These results indicate that neural structure holds the potential to serve as an objective and effective feature for predicting post-CI outcomes.

Supplemental Material:

https://doi.org/10.23641/asha.28012046
“High-temperature” oscillations of magnetoresistance as a method
for the investigation of electronic spectra
Authors: Bogod Yu. A. , Krasovitsky Vit. B. , Lemeshevskaya E. T.
Published: December 2024

The possibility of investigation of the parameters describing electronic spectra by means of “hightemperature” oscillations of the magnetoresistance are discussed using bismuth and bismuth-antimony alloys as an example. For the first time information has been obtained concerning the temperature dependence of the carrier concentration in Bi and the alloy Bi0.98Sb0.02 in the temperature ranges 20–70 °K and 20–45 °K, respectively; in addition, information has been obtained on the dependence of the carrier concentration in Bi on magnetic field at 18, 36, and 61 °K in the quantum limit (H→|| C1 and 15 ≲ H ≲ kOe).
Electric field in superconducting alloys with nonmagnetic impurities of transition metals
Authors: Kon L. Z. , Tabakar’ V. P.
Published: December 2024

Kinetic equations are derived for superconductors with nonmagnetic impurities of transition metals. The properties of an impurity are described by the Anderson Hamiltonian. From the kinetic equations obtained the excitation distribution function is determined and, on the basis of the latter, the electric field in a superconductor in contact with a normal metal to which an electric field has been applied is calculated.
Charge fluctuations in a system of spin density waves
Authors: Akhiezer I. A. , Barannik E. A.
Published: December 2024

We have studied charge fluctuations in a system of spin density waves. We show that in the long wavelength regime, along with modified Langmuir vibrations there exists a branch of the zero-sound type. At wave vectors close to the wave vector of the spin density wave, there are two activation branches of charge fluctuations with activation energies of the order of the gap width in the spectrum of the single-particle spin density wave excitations.
Possible surface mechanism of dislocation formation during growth of a helium single crystal
Authors: Kosevich Yu. A. , Svatko S. V.
Published: December 2024

A hypothesis is proposed as to the existence of a certain surface mechanism of dislocation nucleation during the growth of a helium single crystal.
Investigating impacts of erosion on wind turbine blades
Authors: Thompson Avery
Published: December 2024

Detailed model provides insights into how blade aerodynamics affect particle collisions.
Toward optimal disease surveillance with graph-based active learning
Authors: Tsui Joseph L.-H. , Zhang Mengyan , Sambaturu Prathyush , Busch-Moreno Simon , Suchard Marc A. , Pybus Oliver G. , Flaxman Seth , Semenova Elizaveta , Kraemer Moritz U. G.
Published: December 2024

Tracking the spread of emerging pathogens is critical to the design of timely and effective public health responses. Policymakers face the challenge of allocating finite resources for testing and surveillance across locations, with the goal of maximizing the information obtained about the underlying trends in prevalence and incidence. We model this decision-making process as an iterative node classification problem on an undirected and unweighted graph, in which nodes represent locations and edges represent movement of infectious agents among them. To begin, a single node is randomly selected for testing and determined to be either infected or uninfected. Test feedback is then used to update estimates of the probability of unobserved nodes being infected and to inform the selection of nodes for testing at the next iterations, until certain test budget is exhausted. Using this framework, we evaluate and compare the performance of previously developed active learning policies for node selection, including Node Entropy and Bayesian Active Learning by Disagreement. We explore the performance of these policies under different outbreak scenarios using simulated outbreaks on both synthetic and empirical networks. Further, we propose a policy that considers the distance-weighted average entropy of infection predictions among neighbors of each candidate node. Our proposed policy outperforms existing ones in most outbreak scenarios given small test budgets, highlighting the need to consider an exploration–exploitation trade-off in policy design. Our findings could inform the design of cost-effective surveillance strategies for emerging and endemic pathogens and reduce uncertainties associated with early risk assessments in resource-constrained situations.
Deictic shifts and re-contextualization in translation
Authors: Diyanati Masoumeh , Amouzadeh Mohammad
Published: December 2024

This study investigates the challenges of translating English demonstratives into Persian, with a focus on deictic
shifts and their discourse-pragmatic implications. It aims to outline the recontextualization that deictic terms undergo during
translation and the role of discourse-pragmatic factors in this process. Utilizing a parallel database of literary and academic
texts in English and Persian, all instances of English demonstratives and their Persian counterparts have been identified and
compared based on type, form, and quantity. An analysis of 1,849 instances of demonstrative discrepancies reveals two primary
types of deictic shifts: (1) genuine shifts, which involve a change in the deictic center due to the translator’s
(inter)subjectivity, leading to the re-contextualization of discourse, and (2) non-genuine shifts, where there is no change in the
origo. The findings indicate a tendency for genuine shifts to alternate between distal-to-proximal and
proximal-to-distal, with a marked preference for distal-to-proximal shifts, attributed to the unmarked nature of proximal deixis
in Persian. Furthermore, translators frequently replace pure deictics with impure forms or add deictic terms for clarity,
reflecting broader translation strategies aimed at ensuring the definiteness and explicitness of referents.
Demonstrative pronouns in Kina Rutul
Authors: Mukhin Timofey , Nasledskova Polina
Published: December 2024

This paper presents the results of an experimental study of exophoric uses of demonstrative pronouns in the Kina variety of Rutul (Lezgic, East Caucasian). We collected the questionnaire designed by Wilkins (1999) from seven female native speakers of different ages to determine the spatial meanings of demonstrative pronouns and to identify secondary parameters affecting the use of pronouns, such as visibility of the object and boundaries of the living space. The demonstrative system of Kina Rutul proved to be polycentric (person-oriented). In addition, we found a difference in use of the distal demonstrative. Some speakers use it considering the distance to both participants, while others use it only as a speaker (and not addressee) oriented term. We suppose that this difference might correlate with the speakers’ age and be evidence in favour of a potential change in the system of demonstrative pronouns in the modern language.
Lability in Balkan Slavic
Authors: Makartsev Maxim , Wahlström Max , Escher Anastasia
Published: December 2024

The article assesses claims made in the previous studies regarding the increase in the number of identical
transitive and intransitive verbs with patient-like arguments, that is, patientively labile (P-labile) verbs, in Macedonian in
comparison with the other South Slavic languages. Based on an extensive sample of 130 varieties from different parts of the South
Slavic dialectal continuum, this study confirms the observations regarding increased lability in Western and some Southeastern
Macedonian dialects. Additionally, outside the labile hotbed, lability remains low with relatively homogenous patterning.
Fuzzy-based voltage balancing technique for better operation of Multilevel Inverter in Harmonics Mitigation
Authors: Yong Swee Xiang , Hoon Yap , Mun Hou Kit , Low Foo Wah
Published: December 2024

The deployment of renewable energy sources, particularly in grid-connected inverters, necessitates efficient power electronics converters to ensure seamless integration in distributed generation (DG) systems. However, challenges such as power quality issues, specifically harmonics induced by non-linear loads, persist in these systems, necessitating innovative solutions. This paper proposes the implementation of a Multilevel Inverter-based Active Power Filter (MI-APF) to enhance harmonic filtering capabilities and address power quality issues. Despite its potential, MI-APF faces voltage imbalance challenges within the inverter due to differential charge and discharge rates among capacitors. To counteract this, a robust voltage balancing technique leveraging Fuzzy Logic Control (FLC) is introduced. The objective of this research is to develop a single-phase shunt active power filter (SAPF) utilizing a five-level cascaded H-bridge (CHB) inverter and design a new FLC-based voltage balancing algorithm for CHB inverters. The proposed technique, utilizing FLC, is rigorously evaluated, demonstrating its effectiveness in mitigating voltage imbalances, and enhancing power system reliability. There is a significant reduction in the Total Harmonic Distortion (THD) of the output voltage compared to conventional methods, indicating improved power quality. Additionally, the system’s response time is notably faster, with minimal overshoot, showcasing FLC’s ability to adapt swiftly and accurately to dynamic conditions, thereby enhancing overall system performance.
Reinforcement Learning assisted LQR Tuning of a Load Bearing Robotic Arm
Authors: Murali Rishen , King Phang Swee
Published: December 2024

In this paper, a Linear Quadratic Regulator feedback controller that is tuned by a Reinforcement Learning agent is implemented into the control of a DOBOT Magician Robot Arm to carry and place a load, to which the performance will be compared to the same action undergone by the default movement control of the DOBOT Magician. A 3D URDF model of the DOBOT Magician is imported into Simulink in MATLAB to derive a state-space model. The state-space model is then shaped in Python together with an LQR controller. The Q and R values, which correspond to the state deviation and control effort of the LQR controller, are iteratively tuned by a Reinforcement Learning agent created through TensorFlow in Python, being trained to maximise the efficiency of a particular movement that is performed under a set time frame. Once the Q and R values have been set, the movement efficiency is then benchmarked against the efficiency of the default DOBOT movement.
Design of a Gross Pollutant Trap (GPT) for Drainage Systems in Malaysia
Authors: Sze Leong Pui , Kum Tien Douglas Tong
Published: December 2024

Gross Pollutant Trap (GPT) is a mechanical device that is installed prior to the river outfall to capture gross pollutants such as debris and coarse sediments from stormwater. Gross pollutants are defined as solid debris with the dimension of 5 mm or above. By eliminating gross pollutants from entering rivers, the water treatment process can be carried out more effectively leading to improved water quality. However, despite its benefits, GPT use in Malaysia is limited due to challenges in its maintenance and high installation costs. The purpose of this study is to design and evaluate a GPT for use under Malaysian weather conditions, able to capture general wastes and suitable to be placed according to infrastructure conditions. The efficiency of waste removal, stormwater flow, and ease of maintenance were considered. Evaluations were carried out using a scaled model. The trapping efficiency of solid debris and also of coarse sediments were conducted on the model. In the solid debris experiment, scaled down debris was used for testing based on the scale ratio of the full prototype to the scale model. It was found that the GPT had an average debris trapping efficiency of 86.6%. In addition, the GPT showed an efficiency of 74.5% for trapping coarse sediments. These results indicated that the purpose designed GPT can be used to trap gross pollutants efficiently from stormwater with a similar performance expected for a full-scale prototype. Its efficiency was considered high based on previous studies. This study was able to demonstrate that a purpose designed GPT to suit local conditions could safeguard the environment through preventing gross pollutants from entering rivers which reduces pollution and potential for flash floods.
Hibiscus sabdariffa as Coagulant to Treat Laundry Wastewater
Authors: Ng W J , Ismail N , Yoon L W
Published: December 2024

Laundry wastewater is a major contributor to the global annual wastewater output, highlighting the importance of reusing larger volumes of the wastewater as a valuable water resource. Among the conventional wastewater, coagulation process displays promising results in treating laundry wastewater. However, studies show that the conventional chemical coagulant such as alum has been associated with health concerns. To address these drawbacks, a more environmentally friendly alternative such as natural coagulant is being explored such as Hibiscus sabdariffa due to it seed contain high protein content. This present study aims to characterize Hibiscus sabdariffa seeds and determine the optimal conditions for effectively treating laundry wastewater using Hibiscus sabdariffa as a natural coagulant. Additionally, the study compared the effectiveness of natural and chemical coagulants in this application. The studies parameter ranges include pH (2 –11) and dosages (50 – 500 mg/L). Water quality parameters such as Chemical Oxygen Demand (COD), Total Suspended Solid (TSS) and turbidity will be used to evaluate the coagulation performance. The jar test experiment was carried out and found out that natural coagulant performed best at a pH of 2 and a dosage of 100 mg/L, resulting in COD, turbidity, and TSS removal efficiencies of 32.59%, 77.98%, and 86.51% respectively, with final treated ef luent levels of 212 mg/L for COD, 11.25 NTU for turbidity, and 17 mg/L for TSS, meeting the requirements of Standard B discharge except for the COD and pH. In comparison, the alum chemical coagulant demonstrated better performance, achieving 57.96% COD removal, 95.24% turbidity removal, and over 95% TSS removal. This study successfully showed that the Hibiscus sabdariffa is capable of treating laundry wastewater, showcasing comparable performance to the chemical coagulant in removing turbidity and TSS.
To Simulate the Air Flow and Temperature Distribution for a Data Centre
Authors: Jilian Bong Russell Evangelino , Sivasankaran Praveena Nair , Muniandy Nagentrau , Jayatilleke Benedict , Kanesavathanan
Published: December 2024

The building of data centres has risen sharply around the world because of the quick technological advances in fields including the internet, mobile internet, cloud computing, and big data applications. But the problems that this expansion has brought about in terms of the environment and energy are becoming more and more of a worry. The term “data centre” gained popularity in the 1990s as IT operations expanded, and affordable networking equipment became widely available. The study aims to optimize air distribution, improve energy efficiency, and address challenges in achieving optimal airflow for HVAC systems in data centres, especially small ones. The project is conducted numerically using ANSYS Fluent CFD solver. The results from the experimental simulations are compared to industrial simulation data from the Perunding Shanu Sdn. Bhd., both qualitatively and quantitatively. From the experimental simulation and industrial simulation data, the temperature and airflow performances are very comparable. There was a good agreement between the experimental simulation and industrial simulation results. Three different iterations were tested in this paper, 500, 1000, and lastly using the longest test duration at 2000 iterations. However, the case with the longest test duration at 2000 iterations caused instability in the simulation. With 500 and 1000 iterations producing an average temperature range of 20°C (293 K) to 23°C (296 K), which is in line with projected values, the experiment effectively achieved its goals. But when the iterations were increased to 2000, instability developed, and room temperatures rose to about 32°C (305 K). By the time the simulation was run, there was a reversed flow occurring. Despite being higher than usual, this temperature is still within a range that is suitable for human activities. Interestingly, even though the heat source temperature was only 100°C, the simulation showed a high temperature of 199°C (472 K) after 2000 iterations. This value depicts the worst-case situation in a data centre setting, when substantial heat is created; average server operation temperatures are anticipated to be lower. Results from the experimental simulation showed that having the current Precision Air Conditioner unit specification (30 kW, at 5000 CFM and 18°C) is overcooling the room. Hence, the PAC unit specification could be reduced to a more suitable and environmentally friendly one.
Building Energy Modelling for Energy-Efficient Retrofitting as Catalyst for Low Carbon Building
Authors: Loong Ling Jer , Muniandy Nagentrau , Leng Choo Hui
Published: December 2024

Greenhouse gases is a major contributor to escalating global climate change. Even with the rapid progress of technology, outdated systems and methods continue to exist. This research focuses on employing Building Energy Modelling (BEM), particularly the BEopt software, to enhance energy efficiency via building retrofitting, thereby addressing the pressing problem of greenhouse gas emissions and ultimately achieving low carbon building in Malaysia. The research aims to optimize residential building energy consumption by identifying effective retrofitting strategies and cost-efficient scenarios. In the initial stage, research was conducted on BEM to understand its capabilities in retrofitting residential buildings for energy efficiency. Extensive research on residential buildings in Malaysia helped identify essential parameters for inclusion. Moving on, this research is based on a real existing terrace house in Malaysia. Therefore, collecting accurate data from the house owner was crucial as it may directly affect the simulated results later. After entering the data, the BEopt software generates a baseline electricity output result, which are then compared to the actual electricity bill from the homeowner, showing a difference of just 4.33%. Moving on, 8 different parameters were selected for optimization as they were more feasible in Malaysia compared to others. After the simulations, all eight cases’ results indicated reduction in annual kWh consumption.
Assessment of the suitability and durability of a recycled polymer product as a building component
Authors: Markovičová L , Zatkalíková V , Chobot P
Published: December 2024

The aim of this work is to assess the influence of natural environmental conditions (temperature, time, humidity, microorganisms, UV radiation) on the modification of the properties of polypropylene composites. The study evaluates the suitability and durability of recycled polymer products by investigating changes in tensile strength, hardness and fire performance under natural ageing conditions. Recycled polymers offer environmental benefits, but their longterm properties require careful assessment for practical applications. Samples were exposed to natural weathering for a specified period and mechanical properties were measured periodically. Tensile strength was evaluated to determine structural integrity, hardness to assess surface durability and fire properties to ensure compliance with safety regulations. The results showed an initial slight increase in tensile strength and hardness. With increasing length of exposure, the composite started to degrade gradually which was reflected by a decrease in the monitored parameters. The fire resistance proved to be insufficient as the composite exhibited poor fire safety in both horizontal and vertical directions, but this can be improved by the addition of fire retardants. The study concluded that although recycled polymers show promising durability, specific formulations may require improvements to maintain mechanical properties over time.
Study on the surface roughness of the spun parts produced by the textured and non-textured forming tool
Authors: Šugárová J , Šugár P , Frnčík M
Published: December 2024

The paper brings the results of an experimental study of the multi-pass cold metal spinning process employing a laser-textured tool of 90MnCrV8 (1.2842) steel. The tool with a nose radius surface modified by pulse laser machined hexagonally arranged texture made up of dimple-like depressions with a diameter of 100 μm, depth of 20 μm, and density of 6 % was applied for testing the surface finish of DC01 low carbon steel sheet of the thickness 1 mm by applying various spinning tool pass profiles, mandrel speeds, and tool feeds. On the cylindrical-shaped spun samples, the surface roughness of the spun cup wall was evaluated. The measurements in 0°, 45°, and 90° directions related to the blank material rolling direction were realised, and these responses were compared with those which have been observed on the parts produced by the conventional, non-textured tool. The analysis showed that applying a laser-textured roller reduces the arithmetic mean height of the spun part roughness profile Ra by about 30 % compared to this achieved using the non-textured roller. The Ra reduction of about 15.2 % compared to the initial roughness of the blank material was documented. In contrast, the influence of the planar anisotropy of the material on the surface roughness was not proven.
Effect of nanosecond laser modification on roughness, morphological and wettability state of Ti Grade 2 surfaces
Authors: Antala R , Šugár P , Šugárová J , Moško M
Published: December 2024

In this study, the impact of laser structuring parameters on the surface roughness and wettability of flat Ti Grade 2 surfaces was examined. Six experimental surfaces were prepared applying different levels of laser pulse energy maintaining the constant value of the scanning speed and five surfaces were prepared using various values of scanning speed while keeping the pulse energy constant. The surface morphology was documented employing high-resolution digital microscopy followed by the surface roughness parameters measurement using the contact profilometer. Finally, the surface wettability was measured using the sessile drop technique. The contact angle values in the range of 68.64° to 95.92° were detected, showing the tendency of increasing with the increase of the scanning speed. It corresponds with the trend of surface roughness parameters Rsk and Rkμ to be higher when the scanning speed is increased. The growth of the laser pulse energy revealed the contact angles from 47.29° to 112.39°, with an opposite tendency of the contact angle decreasing with the rise of the laser pulse energy. It is consistent with the trend of a slight decrease in the surface profile kurtosis Rkμ when the pulse energy grows.
Impact of nickel addition on the phase composition and properties of Sn-Ag-Cu solder alloys
Authors: Machajdíková T , Čička R , Černičková I , Ďuriška L , Drienovský M
Published: December 2024

Lead-free solders have been adopted widely due to the environmental and health concerns associated with lead. However, these alloys face several challenges that impact their performance and reliability in electronic applications, e.g. high melting temperature, decrease in mechanical properties, and formation of brittle intermetallic compounds [1]. The addition of nickel has the potential to improve the properties of lead-free solder alloys [2-4]. This study focuses on the addition of Ni into the solder alloy with varying nickel content (0.1 - 4 mass% Ni) using computational thermodynamics and experimental techniques. For the computational part, the phase equilibria of the system were predicted to analyse the effect of nickel on the solder properties. The experimental part employed various techniques (scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray diffraction, and differential scanning calorimetry). From the experimental results, it was found that the primary phases identifed were Ag
3
Sn, β — Sn, and Cu
6
Sn
5. At a nickel content of 1 wt.% or higher, the NisSn2
phase also appeared. As the nickel content increased, the alloy’s melting temperature rose sharply, and changes in the solubility of other elements, as well as the stabilization of the Ni
3
Sn
4 and Cu
6
Sn
5 phases, were observed. The analysis revealed that Ni content significantly influences the phase composition of the alloy.
Methods for determining reliability of complex systems
Authors: Labašová E , Labaš V
Published: December 2024

The paper deals with the determination of the final reliability function of a complex system on the model example. Three methods were used to determine the reliability function: the method of minimum paths, the method of critical sections and the decomposition method. The MATLAB program was used for calculations. The article presents the basic principles of individual methods and the functional relationships used to determine the reliability function of the systems. Virtual block diagrams of the respective system are also shown for all three methods. In terms of calculation efficiency, the decomposition method seems to be the most suitable. It is not necessary to apply the idempotence transformation because neither of elements of the system is repeated in virtual models more than once. In the methods of minimal paths and critical sections, it is necessary to apply the idempotence transformation, because some elements of the system can be found more than once in virtual models.
Heterogeneous nucleation in an aluminum droplet at low supercooling
Authors: Kožíšek Z , Král R , Zemenová P
Published: December 2024

The crystallization of the aluminum (Al) sample was detected by the differential scanning calorimetry (DSC) at the undercooling ΔTC
∼ 18.3°C. At the undercooling ΔT = 6.8°C < ΔTC
, the crystallization event was detected after a time delay of several minutes. The nucleation kinetics on an inner droplet surface is analyzed by numerically solving of the nucleation equations to determine the number of nuclei formed in the Al droplet sample of the mass m
0 = 9.91 mg at ΔT = 6.8 °C. The depletion of the Al melt due to the formation of crystal nuclei is taken into account. The nucleation rate for different cluster sizes tends to a quasi-stationary limit which is lower than predicted by the classical nucleation model. Homogeneous nuclei in the droplet volume are formed earlier than heterogeneous ones, but at longer times (several minutes) the heterogeneous nucleation prevails.
Biochars from Cardboard as an Alternative adsorbent for the Removal of Pesticides from the Water Environment
Authors: Ščasná M , Kucmanová A , Sirotiak M
Published: December 2024

Hydrothermal carbonisation (HTC) is a promising method for converting biomass into carbonaceous materials with high adsorption capacity. This study examines the effect of various HTC conditions on the production of hydrochars from egg cardboard waste and their efficiency in removing metribuzin from aqueous environments. The results showed that temperature and HTC time significantly influenced biochar yield, organic carbon content, and sorption efficiency. The highest yield, 68.18 %, was achieved at 200 °C, whereas at 240 °C, the yield dropped to 23.08 %. Conversely, higher temperatures (220-240 °C) enhanced the retention of organic carbon, contributing to improved sorption properties. Morphological analysis via SEM confirmed that higher temperatures and longer reaction times promote the formation of a porous structure, which is crucial for adsorption applications. At 240 °C, the biochar exhibited substantial fragmentation and increased surface heterogeneity, indicating a high degree of carbonisation. Biochar produced at this temperature achieved the highest metribuzin removal efficiency, exceeding 60 % after 5 hours of contact, underscoring the importance of optimising production conditions to maximise sorption capacity for organic pollutants. These results contribute to a better understanding of the relationship between hydrochar production conditions, organic carbon content, and adsorption properties, which is important for future applications in water treatment and environmental engineering.
Surface modification of parts manufactured by fused deposition modeling
Authors: Pätoprstý B , Morovič L , Buranský I , Dubnička M , Vozár M
Published: December 2024

The production of parts by additive manufacturing is a quickly progressing area. The issue with additively manufactured parts is surface treatment with conventional methods. One of the possibilities is the treatment of the surface by drag finishing, when it is possible to modify even the complicated shapes of the parts. The article deals with the modification of additively produced parts by drag finishing. The goal was to find out to what extend is it possible to modify the integrity of the surface of parts produced by additive manufacturing. Simple cylindrical parts were produced by Fused Deposition Modelling technology. The parts were made of ABS plastic with different layer thickness. Surface roughness changes over time were monitored. As a drag finishing machine, a device developed at Faculty of Material Science and Technology was used. Two drag finishing media were used for part processing - Al2O3 and SiC + walnut shells. It was determined that the roughness of the surface of additively manufactured parts can be significantly improved.
Oil palm land cover classification using WorldView satellite and machine learning algorithms from QGIS ENMAP-box plugin
Authors: Ang Y , Shafri H Z M , Marzuki F A A , Shaharum N S N , Lee Y P , Bakar S A , Abidin H , Lim H S , Abdullah R , Al-Habshi M M
Published: December 2024

Mapping oil palm within a plantation is a crucial task for efficient oil palm management. Using satellite data and machine learning techniques to accurately map land cover classes help in identifying and differentiating between oil palm and other types of land cover. Pertaining to this research, WorldView satellite imagery was employed to assess the land cover classification using machine learning algorithms from the QGIS EnMAP-Box plugin. Machine learning classifiers used for the analysis of land cover classification are random forest (RF), XGBoost, and LGBM. In order to assess how well each classifier performed, accuracy assessments were conducted, namely kappa accuracy, overall accuracy, in addition to user accuracy, as well as producer accuracy. The classification map generated by the best-performing classifier was then utilized. The result shows RF achieved the highest accuracy of 83.1% overall as well as kappa accuracy of 79.5%, compared to XGBoost and LGBM classifiers. RF also shows acceptable user accuracy and producer accuracy in most classes, such as mature oil palm and water. The best classification map obtained from RF serves as an inventory for effective plantation management, facilitating tasks such as oil palm tree identification, replanting programs, and other operations. This comprehensive approach plays a crucial role in monitoring and overseeing the development of oil palm for sustainable production.
Investigating the relationship between particulate matter (PM2.5) concentration and aerosol optical depth (AOD) over Thailand during the dry period
Authors: Kaewmesri Pramet , Uamkasem Budsaba , Koedkurang Kanjana , Chalermpong Patiwet , Sriwilas Phukrit , Tupbamroong Jinnawat , Petchprayoon Pakorn
Published: December 2024

Air pollution, particularly the presence of Particulate Matter (PM2.5), poses significant risks to public health and environmental sustainability. In Thailand, where air quality concerns are prominent, understanding the relationship between PM2.5 concentration and Aerosol Optical Depth (AOD) during the Dry Period is crucial. This research explores the temporal and spatial variations in PM2.5 levels and their correlation with AOD data collected from 2016-2021. Utilizing a simple linear regression model, PM2.5 and AOD data were analysed across five distinct time periods to establish empirical relationships. The analysis revealed varying performance metrics for different time periods and years. R
2 values ranged from 0.43 to 0.79, indicating the extent to which AOD explains PM2.5 variance. Root Mean Square Error (RMSE) values ranged from 7.25 to 22.94, reflecting the average difference between observed and predicted PM2.5 concentrations. The findings underscored the complexity of the relationship between PM2.5 and AOD, with model underestimation during certain periods and overestimation during others. Temporal evaluation during the dry seasons of 2019-2020 and 2020-2021 revealed distinct trends in PM2.5 concentration dynamics. The model consistently underestimated PM2.5 concentrations during November - January, December - February, and November - April periods, while overestimating during February - April. Spatial assessment indicated that while the model captured overall spatial patterns, it tended to underestimate PM2.5 levels at stations with high concentrations Furthermore, the research compared PM2.5 concentrations between the two dry seasons and noted a significant decrease during the 2020-2021 period, possibly attributed to reduced anthropogenic activities during the COVID-19 pandemic. In summary, this research investigates the relationship between PM2.5 and AOD in Thailand during the dry season, employing remote sensing methods, and highlights significant findings through a simple linear regression analysis. The research contributes to informed decision-making by policymakers and environmental agencies, facilitating the development of effective measures to mitigate air pollution and promote public health and environmental sustainability in future.
Evaluating the Suitability of Waste Dumpsites using Geo-spatial Techniques in Kaduna Metropolis, Nigeria
Authors: Aboki Maimunatu , Ponrahono Zakiah , Sydia Nazatul , Zainordin binti , Abu bakar Aisyah binti
Published: December 2024

This study evaluates the suitability of dumpsites in Kaduna Metropolis, Nigeria, Africa with view to map out optimal sites that will be suitable for siting of dumpsites using GIS and Remote Sensing. Diverse array of information including multi-spectral satellite imagery like cloudless Sentinel 2A Geo-referenced data, climate data, and Digital Elevation Models, Software tools QGIS 3.32.1 and ArcGIS 10.8 were employed Analytical Hierarchy Process facilitated the assignment of weights to thematic datasets, assessing consistency ratios Integration of these datasets via the Weighted Linear Combination method yielded suitability sub model map for waste dumpsites. Finally, final suitability map was produced through weighted overlay analysis. The results revealed the periphery of the metropolis offers more favorable conditions for the siting of dumpsites. In contrast, the central core presents significant challenges due to its high tensity urban environment, intense socio-economic activities, and proximity to infrastructure. The highest proportion of land in Kaduna Metropolis is classified as Highly Unsuitable for dumpsite siting, covering 48.15% of the total area surveyed, while the lowest proportion falls into the Highly Suitable category, representing only 0.30% of the surveyed area. It is recommended to prioritize dumpsite development in the less densely populated periphery, engaging stakeholders through transparent decision-making processes. Furthermore, the spatial disparities in dumpsite distribution highlight the need for strategic planning and phased transitioning towards a more balanced distribution of waste management infrastructure.
Object-Oriented Classification Approach (OBIA) in Extracting Burial Plot for Muslim Cemeteries Management
Authors: Khir Sabir Nurul Syahirah , Noor Norzailawati Mohd
Published: December 2024

In contemporary cemetery management planning, the use of the Object-Oriented Classification Approach (OBIA) stands out as an innovative methodology, providing a sophisticated means of exploring and understanding burial grounds by leveraging high-resolution aerial imagery captured from drones. This study delves into the application of OBIA in the extraction of burial plots, aiming to contribute to the systematic management of a Muslim cemetery area and optimize burial space arrangements. Subsequently, these plots are extracted into GIS software, facilitating a comprehensive spatial analysis. OBIA emerges as an efficient method, outperforming traditional approaches, to identify and classify burial plots. The technique successfully maps intricate burial plot patterns and distributions, providing a detailed overview of the cemetery landscape and enabling the calculation of burial density. Beyond its technological contribution, this research offers practical insights for the enhanced management and planning of Muslim cemeteries, ensuring both respectful and efficient use of these sacred spaces. The success of OBIA suggests its potential integration into broader cemetery management practices, paving the way for automation and contributing to sustainable cemetery space utilization.