The effect of amphiphilic block copolymer polyethylene glycol (PEG)-polypropylene glycol (PPG)-PEG concentration in the polyphenylsulfone (PPSU) casting solution and coagulation bath temperature (CBT) on the structure, separation, and antifouling performance of PPSU ultrafiltration membranes was studied for the first time. According to the phase diagram obtained, PPSU/PEG-PPG-PEG/N-methyl-2-pyrrolidone (NMP) systems are characterized by a narrow miscibility gap. It was found that 20 wt. % PPSU solutions in NMP with the addition of 5–15 wt. % of PEG-PPG-PEG block copolymer feature upper critical solution temperature, gel point, and lower critical solution temperature. Membrane composition and structure were studied by Fourier-transform infrared spectroscopy, scanning electron and atomic force microscopies, and water contact angle measurements. The addition of PEG-PPG-PPG to the PPSU casting solution was found to increase the hydrophilicity of the membrane surface (water contact angle decreased from 78° for the reference PPSU membrane down to 50° for 20 wt. %PPSU/15 wt. % PEG-PPG-PEG membrane). It was revealed that the pure water flux increased with the rise of CBT from 18–20 L·m⁻²·h⁻¹ for the reference PPSU membrane up to 38–140 L·m⁻²·h⁻¹ for 20 wt. % PPSU/10–15 wt. % PEG-PPG-PEG membranes. However, the opposite trend was observed for 20 wt. % PPSU/5–7 wt. % PEG-PPG-PEG membranes: pure water flux decreased with an increase in CBT. This is due to the differences in the mechanism of phase separation (non-solvent-induced phase separation (NIPS) or a combination of NIPS and temperature-induced phase separation (TIPS)). It was shown that 20 wt. % PPSU/10 wt. % PEG-PPG-PEG membranes were characterized by significantly higher antifouling performance (FRR—81–89%, DR_r—26–32%, DR_ir—10–20%, DT—33–45%) during the ultrafiltration of bovine serum albumin solutions compared to the reference PPSU membrane prepared at different CBTs (FRR—29–38%, DR_r—6–14%, DR_ir—74–89%, DT—88–94%). Full article

The authors present changes in the content and teaching methods of religious education (RE) in the third decade of the 21st century, as proposed by the current curricular reform of compulsory education in Slovakia. First, they analyse the reform documents in terms of social competence development as one of the RE content requirements. Second, they seek a teaching methodology that applies a balanced approach to the use of information and communication technologies (ICT) while protecting RE pupils and their building of healthy human relationships from the potential threat of digital addiction. The authors based their teaching ideas on the findings from their research. To explore the relationship between addictive Internet behaviour and social intelligence, they used a questionnaire including the Internet Addiction Test and the TSIS Scale. The Mann–Whitney U test was used for statistical analysis. Data on 386 adolescent respondents revealed a statistically significant difference between males and females in social awareness, with males performing significantly better. A weak positive relationship (ρ = 0.240) was identified between social awareness and addictive Internet behaviour. In the discussion, the authors suggest teaching methods for developing social competence via RE without resisting the opportunities provided by ICT, while also avoiding an increase in the risk of online social media addiction. They suggest that even denominational RE should prioritize cultivating healthy relationships not only with God but also relationships with other people, the outside world, and oneself. Full article

Snakebite accidents, neglected tropical diseases per the WHO, pose a significant public health threat due to their severity and frequency. Envenomation by Bothrops genus snakes leads to severe manifestations due to proteolytic enzymes. While the antibothropic serum produced by the Butantan Institute saves lives, its efficacy is limited as it fails to neutralize certain serine proteases. Hence, developing new-generation antivenoms, like monoclonal antibodies, is crucial. This study aimed to explore the inhibitory potential of synthetic peptides homologous to the CDR3 regions of a monoclonal antibody targeting a snake venom thrombin-like enzyme (SVTLE) from B. atrox venom. Five synthetic peptides were studied, all stable against hydrolysis by venoms and serine proteases. Impressively, four peptides demonstrated uncompetitive SVTLE inhibition, with Ki values ranging from 10⁻⁶ to 10⁻⁷ M. These findings underscore the potential of short peptides homologous to CDR3 regions in blocking snake venom toxins, suggesting their promise as the basis for new-generation antivenoms. Thus, this study offers potential advancements in combatting snakebites, addressing a critical public health challenge in tropical and subtropical regions. Full article

Pure lanthanum hexaboride (LaB₆) ceramics were prepared using powders of different grain sizes. The ceramics could reach a relative density of 98.2% at high temperatures and pressures, but had a low flexural strength (136.9 MPa). LaB₆ ceramics were synthesized using ZrO₂-Al₂O₃-TiO₂ (ZAT) as sintering additives. The ceramics demonstrate high density and excellent mechanical properties. The hot pressure sintering (HPS) method was utilized in the synthesis of the ceramics. Investigations were conducted on the effects of ZAT content, as well as the effects of the sintering temperature and pressure on the sintering behavior, microstructure, and mechanical and electrical properties of LaB₆ ceramics. LaB₆ ceramics fabricated with a ZAT addition of 6 wt.%, at a sintering temperature of 1700 °C, and under a pressure of 50 MPa, exhibited superior sintering and electrical properties, including a relative density of 97%, a conductivity of 7.2 MS/m, a flexural strength of 281.5 MPa, and a Vickers hardness of 21.2 GPa. The LaB₆ ceramics synthesized in this research exhibit promising potential as electron-emitting cathodes for field emission applications. Full article

This review article addresses the antioxidant properties of different natural products, including ascorbic acid, gallic acid, oxalic acid, L-glutathione (GSH), bacteriorhodopsin, green tea polyphenols, glucose, hydroxycinnamic acid, ethanoic acid, betanin, and L-glutathione, in the reduction of graphene oxide (rGO). rGO can cause damage to cells, including oxidative stress and inflammation, limiting its application in different sectors that use graphene, such as technologies used in medicine and dentistry. The natural substances reviewed have properties that help reduce this damage, neutralizing free radicals and maintaining cellular integrity. This survey demonstrates that the combination of these antioxidant compounds can be an effective strategy to minimize the harmful effects of rGO and promote cellular health. Full article

This paper proposes a nonlinear teaching approach, based on learning theories in cognitive psychology, with a special focus on large-cohort economics modules. The fundamental rationale is to match the features of teaching with the nature of learning. This approach was implemented in an undergraduate economics module, which received qualitative feedback and quantitative evaluation. Formal econometric models with both binary and continuous treatment effects were developed and estimated to quantify the effects of the proposed approach. Evidence shows that the nonlinear teaching approach significantly improves the effectiveness and efficiency of the learning-teaching process but does not promote student attendance. Full article

To enhance the precision and efficiency of the tractor-failure-rate and equipment-quality inspection, the present study introduces a wireless rapid detection method for assessing tractor quality. For this study, which was based on the symmetrical structural characteristics of tractors, we designed a magnetic suction accelerometer. The test system was composed of a wireless router, a magnetic suction accelerometer sensor, a data-acquisition terminal, and other components. This test system aimed to test the equipment quality of the tractor at idle speed before leaving the factory. The experiment found that the vibration characteristics of the tractor had a symmetrical pattern on the left and right sides of the front and rear axle at idle. When the idle speed of the tractor was 800 r/min and 1000 r/min, the predominant vibration direction of both sides of the front axle of the tractor was the Y direction, while the predominant vibration direction of the rear axle was the Z direction. The experimental results showed that the proposed wireless rapid detection method of tractor quality and the designed acceleration sensor had good testing accuracy. The present study could provide a novel rapid detection method for the failure detection of power machinery in the agricultural field and for inspection before leaving the factory. The implementation of the method could improve the detection efficiency, and reduce the detection cost and the incidence of failure during actual use. Full article

In the digital age, maintaining election integrity is critical, especially in Africa, where the security of electronic elections is often questioned. This study presents a blockchain-based vote counting and validation (BBVV) system developed using a mixed methods approach that combines stakeholder questionnaires to capture system specification and randomized historical election data analysis, following the Design Science Research strategy. Using the theory of the Byzantine General Problem, the BBVV protocol is proposed, which provides an accurate local count of votes at polling stations before national aggregation. The system was tested with randomized historical election data on the Algorand blockchain TestNet and confirmed that a local consensus on the vote count could be reached before it is added to the national tally on the blockchain. Our results show that in the cases where consensus was reached, this was the instance in only about 5% of the voting scenarios, with only 10% of the total vote being considered valid due to the strict consensus requirements. In addition, significant discrepancies were found between officials, with no consensus reached in 95% of cases which was due to the rogue values generated by a randomized dataset. The performance of the BBVV system was evaluated using transaction metrics, saturation, throughput, traffic, and latency to assess its efficiency, scalability, and reliability. The results suggest that blockchain technology can significantly improve the integrity of elections by ensuring a transparent, secure, and accurate vote-counting process. Future work will focus on improving the adaptability and scalability of the BBVV system for different electoral situations. Full article

(1) Background: Early interventions may effectively reduce the risk of mental disorders in individuals with ultra-high risk. Specifying the health needs of individuals with ultra-high risk is crucial before the implementation of successful early intervention. This study aimed to explore the differences in lifestyles, mental risks, and physical indices among individuals with ultra-high risk, patients with schizophrenia, and healthy subjects. (2) Methods: A cross-section design applying seven questionnaires with physical examinations for 144 participants aged 13–45 years old was conducted in this study. The questionnaires included one about personal data, four on mental risks, and two for lifestyles. (3) Results: The individuals with ultra-high risk scored similarly in many dimensions as the patients with schizophrenia, but they displayed lower positive symptoms, lower negative symptoms, lower prodromal symptoms, higher interpersonal deficits, lower nutrition intake, and higher levels of exercise than the patients with schizophrenia. Female individuals with ultra-high risk had lower self-esteem, higher positive symptoms, lower nutrition intake, and higher exercise levels than male ones. (4) Conclusions: The study pinpointed specific health needs with interpersonal deficits, nutrition intake, and physical activity for the individuals with ultra-high risk. Future interventions targeted on improving social function, dietary pattern, and exercise will be beneficial. Full article

The electrocatalytic nitrogen reduction reaction (NRR) for synthesizing ammonia holds promise as an alternative to the traditional high-energy-consuming Haber–Bosch method. Rational and accurate catalyst design is needed to overcome the challenge of activating N₂ and to suppress the competitive hydrogen evolution reaction (HER). Single-atom catalysts have garnered widespread attention due to their 100% atom utilization efficiency and unique catalytic performance. In this context, we constructed theoretical models of metal single-atom catalysts supported on titanate nanosheets (M-TiNS). Initially, density functional theory (DFT) was employed to screen 12 single-atom catalysts for NRR- and HER-related barriers, leading to the identification of the theoretically optimal NRR catalyst, Ru-TiNS. Subsequently, experimental synthesis of the Ru-TiNS single-atom catalyst was successfully achieved, exhibiting excellent performance in catalyzing NRR, with the highest NH₃ yield rate reaching 15.19 μmol mg_cat⁻¹ h⁻¹ and a Faradaic efficiency (FE) of 15.3%. The combination of experimental results and theoretical calculations demonstrated the efficient catalytic ability of Ru sites, validating the effectiveness of the constructed theoretical screening process and providing a theoretical foundation for the design of efficient NRR catalysts. Full article

Pradofloxacin—a dual-targeting fluoroquinolone—is the most recent approved for use in food animals. Minimum inhibitory and mutant prevention concentration values were determined for pradofloxacin, ceftiofur, enrofloxacin, florfenicol, marbofloxacin, tildipirosin, tilmicosin, and tulathromycin. For M. haemolytica strains, MIC_50/90/100 values were ≤0.016/≤0.016/≤0.016 and MPC_50/90/100 values were 0.031/0.063/0.063; for P. multocida strains, the MIC_50/90/100 values ≤0.016/≤0.016/0.031 and MPC_50/90/100 ≤ 0.016/0.031/0.063 for pradofloxacin. The pradofloxacin C_max/MIC₉₀ and C_max/MPC₉₀ values for M. haemolytica and P. multocida strains, respectively, were 212.5 and 53.9 and 212.5 and 109.7. Similarly, AUC₂₄/MIC₉₀ and AUC₂₄/MPC₉₀ for M. haemolytica were 825 and 209.5, and for P. multocida, they were 825 and 425.8. Pradofloxacin would exceed the mutant selection window for >12–16 h. Pradofloxacin appears to have a low likelihood for resistance selection against key bovine respiratory disease bacterial pathogens based on low MIC and MPC values. Full article

The whole trusteeship of green agricultural production plays an important role in promoting the protection of black land, and it is particularly crucial to clarify the behavioral characteristics and game relationships of agents involved in the whole trusteeship. This study uses the dynamic evolutionary game method to construct a tripartite evolutionary game model of governments, service organizations and farmers participating in the whole trusteeship of green agricultural production, aiming to come up with effective strategies to promote the widespread application of green agricultural production trusteeship and achieve agricultural green development. The results are as follows: (1) At present, the agricultural production model in Northeast China is dominated by traditional agricultural production and supplemented by green agricultural production. (2) Incentive and punitive measures will encourage agents to adopt positive strategies. (3) In areas with a poor awareness of green agricultural production trusteeship, the government’s incentive and punishment measures for farmers and service organizations are imbalanced. (4) The relatively high cost of trusteeship leads to a lack of market competitiveness, which has a negative impact on service organizations promoting green agricultural production trusteeship. This study provides an effective reference for improving the overall implementation effect of black land protection in Northeast China. Full article

This paper proposes a novel soft sensor modeling approach, MIC-TCA-INGO-LSSVM, to address the decline in performance of soft sensor models during the fermentation process of Pichia pastoris, caused by changes in working conditions. Initially, the transfer component analysis (TCA) method is utilized to minimize the differences in data distribution across various working conditions. Subsequently, a least squares support vector machine (LSSVM) model is constructed using the dataset adapted by TCA, and strategies for improving the northern goshawk optimization (INGO) algorithm are proposed to optimize the parameters of the LSSVM model. Finally, to further enhance the model’s generalization ability and prediction accuracy, considering the transfer of knowledge from multiple-source working conditions, a sub-model weighted ensemble scheme is proposed based on the maximum information coefficient (MIC) algorithm. The proposed soft sensor model is employed to predict cell and product concentrations during the fermentation process of Pichia pastoris. Simulation results indicate that the RMSE of the INGO-LSSVM model in predicting cell and product concentrations is reduced by 47.3% and 42.1%, respectively, compared to the NGO-LSSVM model. Additionally, TCA significantly enhances the model’s adaptability when working conditions change. Moreover, the soft sensor model based on TCA and the MIC-weighted ensemble method achieves a reduction of 41.6% and 31.3% in the RMSE for predicting cell and product concentrations, respectively, compared to the single-source condition transfer model TCA-INGO-LSSVM. These results demonstrate the high reliability and predictive performance of the proposed soft sensor method under varying working conditions. Full article

A non-structural SARS-CoV-2 protein, PLpro, is involved in post-translational modifications in cells, allowing the evasion of antiviral immune response mechanisms. In this study, potential PLpro inhibitory drugs were designed using QSAR, molecular docking, and molecular dynamics. A combined QSAR equation with physicochemical and Free-Wilson descriptors was formulated. The r², q², and r²_test values were 0.833, 0.770, and 0.721, respectively. From the equation, it was found that the presence of an aromatic ring and a basic nitrogen atom is crucial for obtaining good antiviral activity. Then, a series of structures for the binding sites of C111, Y268, and H73 of PLpro were created. The best compounds were found to exhibit pIC₅₀ values of 9.124 and docking scoring values of −14 kcal/mol. The stability of the compounds in the cavities was confirmed by molecular dynamics studies. A high number of stable contacts and good interactions over time were exhibited by the aryl-thiophenes Pred14 and Pred15, making them potential antiviral candidates. Full article

This study aims to evaluate several defined specimen parameters that would allow to determine the surgical accuracy of breast-conserving surgeries (BCS) in a representative population of patients. These specimen parameters could be used to compare surgical accuracy when using novel technologies for intra-operative BCS guidance in the future. Different specimen parameters were determined among 100 BCS patients, including the ratio of specimen volume to tumor volume (resection ratio) with different optimal margin widths (0 mm, 1 mm, 2 mm, and 10 mm). Furthermore, the tumor eccentricity [maximum tumor-margin distance − minimum tumor-margin distance] and the relative tumor eccentricity [tumor eccentricity ÷ pathological tumor diameter] were determined. Different patient subgroups were compared using Wilcoxon rank sum tests. When using a surgical margin width of 0 mm, 1 mm, 2 mm, and 10 mm, on average, 19.16 (IQR 44.36), 9.94 (IQR 18.09), 6.06 (IQR 9.69) and 1.35 (IQR 1.78) times the ideal resection volume was excised, respectively. The median tumor eccentricity among the entire patient population was 11.29 mm (SD = 3.99) and the median relative tumor eccentricity was 0.66 (SD = 2.22). Resection ratios based on different optimal margin widths (0 mm, 1 mm, 2 mm, and 10 mm) and the (relative) tumor eccentricity could be valuable outcome measures to evaluate the surgical accuracy of novel technologies for intra-operative BCS guidance. Full article

The objective of this study was the evaluation of the locomotion activity of heifers and Holstein dairy cows during estrus. We have analyzed the locomotion activity using the Heatime RuminAct device on 180 cows (32 heifers and 148 dairy cows) and we evaluated a total of 633 estrus cycles during the reference period of 3 days before estrus, 3 days after estrus, and on the day ofestrus occurrence. The datawere analyzed using the DataFlowTM II program. The locomotion of cows was expressed in the units of locomotion activity in 24 h (u.24 h⁻¹). During the reference period of 3 days before estrus, the cows showed locomotion activity of 558 u.24 h⁻¹, with an increase in locomotion activity on the day of estrus of 836 u.24 h⁻¹, and, during the reference period of 3 days after estrus, the level of locomotion activity decreased to 537 836 u.24 h⁻¹, which is a similar level of locomotion activity to the reference period before estrus. Through the statistical analysis, we evaluated the impact of parity, lactation stage, milk yield, and individuality on changes in locomotion activity during estrus and throughout the reference period, and we found a significant effect of parity (F = 13.41, p < 0.001) on changes in the locomotion activity of dairy cows during estrus. Based on these results, this research offers fresh perspectives on assessing specific factors affecting the locomotion activity of dairy cows during estrus through the practical application of electronic systems for estrus detection on dairy farms. Full article

Artificial intelligence (AI) refers to computer algorithms that replicate the cognitive function of humans. Machine learning is widely applicable using structured and unstructured data, while deep learning is derived from the neural networks of the human brain that process and interpret information. During the last decades, AI has been introduced in several aspects of healthcare. In this review, we aim to present the current application of AI in the neonatal intensive care unit. AI-based models have been applied to neurocritical care, including automated seizure detection algorithms and electroencephalogram-based hypoxic-ischemic encephalopathy severity grading systems. Moreover, AI models evaluating magnetic resonance imaging contributed to the progress of the evaluation of the neonatal developing brain and the understanding of how prenatal events affect both structural and functional network topologies. Furthermore, AI algorithms have been applied to predict the development of bronchopulmonary dysplasia and assess the extubation readiness of preterm neonates. Automated models have been also used for the detection of retinopathy of prematurity and the need for treatment. Among others, AI algorithms have been utilized for the detection of sepsis, the need for patent ductus arteriosus treatment, the evaluation of jaundice, and the detection of gastrointestinal morbidities. Finally, AI prediction models have been constructed for the evaluation of the neurodevelopmental outcome and the overall mortality of neonates. Although the application of AI in neonatology is encouraging, further research in AI models is warranted in the future including retraining clinical trials, validating the outcomes, and addressing serious ethics issues. Full article

The membrane biofilm reactor (MBfR) is a novel wastewater treatment technology, garnering attention due to its high gas utilization rate and effective pollutant removal capability. This paper outlines the working mechanism, advantages, and disadvantages of MBfR, and the denitrification pathways, assessing the efficacy of MBfR in removing oxidized pollutants (sulfate (SO₄⁻), perchlorate (ClO₄⁻)), heavy metal ions (chromates (Cr(VI)), selenates (Se(VI))), and organic pollutants (tetracycline (TC), p-chloronitrobenzene (p-CNB)), and delves into the role of related microorganisms. Specifically, through the addition of nitrates (NO₃⁻), this paper analyzes its impact on the removal efficiency of other pollutants and explores the changes in microbial communities. The results of the study show that NO³⁻ inhibits the removal of other pollutants (oxidizing pollutants, heavy metal ions and organic pollutants), etc., in the simultaneous removal of multiple pollutants by MBfR. Full article

Binary tropical cyclones (BTCs) typically refer to the coexistence of two tropical cyclones (TCs) within a specific distance range, often resulting in disastrous rainstorms in coastal areas of China. However, the differences in rainfall and underlying causes between BTC-influenced typhoons and general typhoons remain unclear. In this article, the TC closer to the rainfall center in the BTC is referred to as the target typhoon (tTC), while the other is termed the accompanying typhoon (cmp_TC). This study compares and analyzes the rainfall differences and potential causes of tTCs and similar typhoons (sim_TC) with a comparable track but which are unaffected by BTCs from 1981 to 2020. The results show that: (1) On average, tTCs and cmp_TCs experience 18.79% heavier maximum daily rainfall compared to general TCs, with a significantly increased likelihood of rainfall ≥250 mm. (2) Given similar tracks, the average rainfall for tTCs (212.62 mm) is 30.2% heavier than that for sim_TCs (163.30 mm). (3) The analysis of potential impact factors on rainfall (translation speed, intensity, direction change) reveals that sim_TCs move at an average of 21.38 km/h, which is about 19.66% faster than the 17.87 km/h of tTCs, potentially accounting for the observed differences in rainfall. (4) Further investigation into the causes of west–east oriented BTC rainfall in the Northern Fujian (N_Fujian) region suggests that water vapor transport and slowing down of the translation speed are the possible mechanisms of BTC influence. Specifically, 80% of tTCs receive water vapor from the direction of their cmp_TC, and the steering flow for tTC is only 59.88% of that for sim_TC. Full article

Recently, heavy rains caused by climate change have resulted in dam failures due to overtopping. This study presents a design method aiming to prevent overtopping failures by applying gabion retaining walls at the dam crest. Simulations, experiments, and measurements were conducted to evaluate the effectiveness of this design. The design framework aims to establish a system in which gabion retaining walls prevent overtopping when water levels exceed the crest of the dam, efficiently draining seepage water into the dam body through vertical filters. Research findings indicate that implementing dam crest core and geomembrane design effectively prevents seepage and saturation of the downstream slope during overtopping events. Notably, the reservoir dam operates in a stable manner, as seepage water passing through the dam body is directed solely to the toe drain. Overall, this design approach suggests its potential as a practical solution by significantly reducing hazards resulting from heavy rainfall. Full article

The set-covering problem aims to find the smallest possible set of subsets that cover all the elements of a larger set. The difficulty of solving the set-covering problem increases as the number of elements and sets grows, making it a complex problem for which traditional integer programming solutions may become inefficient in real-life instances. Given this complexity, various metaheuristics have been successfully applied to solve the set-covering problem and related issues. This study introduces, implements, and analyzes a novel metaheuristic inspired by the well-established Growth Optimizer algorithm. Drawing insights from human behavioral patterns, this approach has shown promise in optimizing complex problems in continuous domains, where experimental results demonstrate the effectiveness and competitiveness of the metaheuristic compared to other strategies. The Growth Optimizer algorithm is modified and adapted to the realm of binary optimization for solving the set-covering problem, resulting in the creation of the Binary Growth Optimizer algorithm. Upon the implementation and analysis of its outcomes, the findings illustrate its capability to achieve competitive and efficient solutions in terms of resolution time and result quality. Full article

This paper presents a historical analysis of a rare dyer’s manuscript, preserved within the Museum of Industry in Ghent, Belgium. The manuscript, originating from a dyer in late 18th-century Antwerp, includes an extensive collection of recipes. The study will enable researchers to better grasp the practices of traditional dyeing techniques and materials in the region during that time. The manuscript focuses primarily on the dyeing of woolen fabrics. Approximately 90 of the 132 recipes utilize red dyes. Recipes for dying orange, brown, black, blue, and green colors are also described. The document mentions the use of madder, brazilwood, redwood, and cochineal. To create a variety of red shades, the dyer describes how fabrics were treated with different mordanting compounds, with alum and tin as the main ingredients, and how the dyeing solutions were prepared. The resulting colors include ‘madder red’, ‘formal red’, ‘crimson’, ‘scarlet’, ‘Turkish red’, ‘fire color’ and ‘flesh color’. In addition to the dyeing recipes, the manuscript contains various accounting documents and correspondences between the dyer, customers, and suppliers. Lastly, over 100 original, colored samples are attached to the described recipes. In this paper, the artifact’s contents will be disclosed, comprising recipes with attached samples and correspondence. Findings resulting from archive research will be included, contextualizing and placing the dyer in their urban and social context. The paper concludes by discussing its potential limitations and provides avenues for possible future research. Full article