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Holism evolution states that although energy, matter, life, consciousness and the human personality are independent and different substances/levels of evolution, they are holistically and intimately related. This paper presents the findings from teaching chemistry to high school science students and post-graduate university science-education students using poetry constructed from physical science ideas embedded in holism evolution. The research findings are based on observations of student behaviour and their written feedback from being taught chemistry using poems on the periodic table and acids and bases. Both poems demonstrate the holism intimacy between various substances/levels of evolution, with the periodic table poem also presenting groups of chemical elements as representing the characteristics of infant, teenager, adult and old age of matter, presenting a holistic relationship between matter and life. The findings indicate that using holism evolution infused content led to a personally meaningful engagement with chemistry even among students with limited previous interest in the subject. Many post-graduate students expressed new levels of engagement with chemistry as well as new insights to enliven their teaching practice. [ABSTRACT FROM AUTHOR]

The quality of seawater is very important for the state of Qatar as it is a peninsula. This paper is focused on the analysis of several physicochemical parameters, such as pH, Conductivity, Total Dissolved Solids (TDS), Turbidity, Alkalinity (M), Total Hardness, Silica, Sulphate, Iron, Nitrate, Phosphate, and Temperature from different sampling sites along major coastal areas on the East Coast of Qatar--namely the Doha Corniche, Al Khor, and Mesaieed. The results revealed that Qatari coastal waters contained typical values of each physicochemical parameter analyzed and were clean and unaffected by the risks of polluted waters or large-scale algal blooming. Across all nine samples, the pH values of the different water samples ranged from 7.7-7.9. Across all nine samples, the conductivity ranged from 57,590 to 64,960 µS/cm. Across all nine samples, the TDS readings ranged from 41110 - 43380 ppm. Across all nine samples, the turbidity ranged from 1 to 2.65 NTU. Across all nine samples, the alkalinity ranged from 110 to 127 ppm as CaCO3. Across all nine samples, the hardness ranged from 6640 to 6515 ppm as CaCO3. Across all nine samples, the Silica levels ranged from 0.15 to 0.23 ppm as Si. Across all nine samples, the sulfate levels ranged from 2140 to 2145 ppm as SO4. Across all nine samples, the iron levels ranged from 0.03 to 0.1 ppm as Fe+3. Across all nine samples, the nitrate levels ranged from 3.2 to 6.6 ppm as NO3. Across all nine samples, the phosphate levels all read 0 ppm as PO4 (below the detection limit). Across all nine samples, the temperature levels ranged from 24 to 28.8°C. [ABSTRACT FROM AUTHOR]

Computer-based learning environments (CBLEs) are powerful tools to support student learning. Increasingly of interest is the data that is recorded as learners interact with a CBLE. This process data yields opportunities for researchers to examine learners' engagement with a CBLE and explore whether specific interactions are associated with learner variables, with direct implications for improving learning outcomes and CBLE design. As CBLEs increase in number and complexity, researchers continue to seek more effective strategies to analyze process data. While a variety of strategies are in use, from visualizations to predictive modeling, none yet offer the capabilities to both uncover hidden, meaningful interactions and descriptively analyze those interactions rapidly across the complete data set. This paper details a method that addresses current challenges, and then applies the method to existing data from a prior study which investigated the effects of adding a visual scaffold to a chemistry-based CBLE. Using a biochemical coding approach through a cultural-historical activity theory (CHAT) framework, the method successfully identified 257 unique, meaningful patterns of interaction that were strategically grouped into nine categories of mediated actions. Though no differences in mediated actions were observed between learners in the experimental (visual scaffolds) and control conditions, three mediated actions were significantly and positively associated with higher learning outcomes in the visual scaffold condition. The results not only provide insight into why the addition of visual scaffolds led to higher learning outcomes among participants but have broader implications for filling a gap in the field of process data analytics for CBLEs in science education. [ABSTRACT FROM AUTHOR]

The increasing levels of CO2 in the atmosphere due to anthropogenic activities pose a significant threat to the global climate. Conversion of CO2 to value-added chemicals such as methanol offers a promising approach for mitigating climate change while simultaneously generating useful products. This review paper provides a comprehensive overview of the synthesis and evaluation of nanocatalysts for CO2 hydrogenation to methanol. I will highlight the ongoing research and new advances being made in this field, including various catalyst materials, their preparation methods, and performance evaluations. I will also discuss the challenges and future perspectives in developing efficient and stable nanocatalysts for CO2 hydrogenation to methanol. [ABSTRACT FROM AUTHOR]

This Ambix special issue explores premodern alchemical ideas and practices in their entanglements with medicine. It employs diverse methods, from traditional close reading to the new distant-reading framework of computational humanities, to investigate alchemical thought over a timespan of several centuries. In medieval times, everyday practices could offer heuristic models of material transformation – such as the fermentation of bread as a model for metallic transmutation (Schmechel). Paracelsus relied on “fire” to link his natural philosophy with his medical alchemy; new computational methods show how his ideas evolved over time (Hedesan). Early modern medical pluralism favoured the thriving of chemical medicine in Italy; diplomatic efforts introduced chemical remedies into acknowledged pharmacopoeias (Clericuzio). An English physician offers William Cavendish both practical distillation recipes and the hope of learning more about the principles of chemistry (Begley). In eighteenth-century France, Diderot draws on chemical ideas to blur the conceptual boundary between living and non-living matter (Wolfe). The papers largely adhere to integrated history and philosophy of science (iHPS) and to a pragmatist “operational ideal of knowledge” (Chang). They showcase the interdisciplinarity of premodern scientific thought and examine how medicine and alchemy, but also theory and (everyday) practice informed each other fruitfully across the ages. [ABSTRACT FROM AUTHOR]

This article focuses on the history of the customs laboratories in the United States between the 1870s and the 1930s, focusing especially on the decades up to World War I. It pays attention to the various dimensions of these laboratories, in particular the context of their creation. The first customs laboratory was established in New York in 1878, and over the subsequent years, similar laboratories were set up across the country. The evolution of this network was influenced by factors such as the increasing specialization of these spaces, their geographic distribution, and changes in their organization and scope. The article also explores the types of imported merchandise analyzed in these labs; the roles of their staff, especially customs chemists, both within and outside these laboratories; their impact on the circulation of goods and in generating revenue from taxation; and the main challenges faced by customs chemists in adapting and standardizing their work. After discussing the necessity of customs laboratories in the United States, the article examines their progressive specialization, with a detailed study of the customs laboratory in New York. This laboratory was the largest and most significant due to its location and longevity. Finally, the paper considers the relationship between customs labs and the law, and how these spaces adapted to new challenges during the first third of the twentieth century. [ABSTRACT FROM AUTHOR]

This paper explores how the culture within a Danish university study programme affects students' aspirations of becoming a high school chemistry teacher. We draw on ethnographic fieldwork and qualitative interviews to describe and analyse the culture of the programme. In the analysis we foreground the case of two students to understand their identity negotiations and changes in their teacher aspirations over time. By combining a 'domains-of-power framework' with the concept of 'science identity', we show how everyday practices formed a culture of power that positioned research in the centre and teaching as a less attractive career path. By unfolding the subtle mechanisms that together form a culture of power, which works both to include and exclude, we show the ways in which the two student's aspirations for becoming high school chemistry teachers somewhat diminished over time. The study concludes that negotiating a science identity at a research-intensive university programme, makes it almost impossible to develop and keep an aspiration for becoming a high school teacher. To address the current and future shortage of science teachers across Europe, our findings underline the need for a more inclusive culture at the university to support science students' diverse aspirations. [ABSTRACT FROM AUTHOR]

Friction and wear collectively account for nearly a quarter of the world’s energy consumption, resulting in over eight Gigatons of CO2 emissions annually. With increasing mobility and industrial activity, the adverse effects of friction and wear on energy, the environment, the global economy, and sustainability will undoubtedly intensify. Unless we reverse this unsustainable trend, our planet could face a major ecological and environmental catastrophe. Fortunately, significant strides have been made in reducing friction to almost undetectable levels, with friction coefficients below 0.001. These remarkable achievements have resulted from numerous collaborative efforts and global initiatives focused on developing novel materials, surfaces, and interfaces that exhibit minimal or near zero friction, even at macro or engineering scales. This paper provides a comprehensive overview of the factors that contribute to and hinder superlubric sliding conditions, examining the impact of both intrinsic and extrinsic factors that are integral parts of the test conditions and environments. Drawing from recent analytical, experimental, and computational findings, underlying mechanisms most responsible for superlubricity are also discussed. The paper discusses recent mechanistic studies on highly ordered 2D materials, such as graphene, MoS2, h-BN, MXene, etc., and thin solid coatings such as diamond-like carbon or DLCs, as well as liquids, and discusses their potential for the development of large-scale mechanical systems. These exciting advancements pave the way for designing and producing next-generation engineering systems that can minimize friction in practical applications, thus conserving energy, enhancing durability, and protecting the environment for a sustainable future.

Nitrogen oxides (NOx = NO + NO2) are air pollutants which are co-emitted with CO2 during high-temperature combustion processes. Monitoring NOx emissions is crucial for assessing air quality and for providing proxy estimates of CO2 emissions. Satellite observations, such as those from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5P satellite, provide global coverage at high temporal resolution. However, satellites measure only NO2, necessitating a conversion to NOx. Previous studies have applied a constant NO2-to-NOx conversion factor. In this paper, we develop a more realistic model for NO2-to-NOx conversion and apply it to TROPOMI data of 2020 and 2021. To achieve this, we analysed plume-resolving simulations from the MicroHH large-eddy simulation model with chemistry for the Bełchatów (PL), Jänschwalde (DE), Matimba (ZA) and Medupi (ZA) power plants, as well as a metallurgical plant in Lipetsk (RU). We used the cross-sectional flux method to calculate NO, NO2 and NOx line densities from simulated NO and NO2 columns and derived NO2-to-NOx conversion factors as a function of the time since emission. Since the method of converting NO2 to NOx presented in this paper assumes steady-state conditions and that the conversion factors can be modelled by a negative exponential function, we validated the conversion factors using the same MicroHH data. Finally, we applied the derived conversion factors to TROPOMI NO2 observations of the same sources. The validation of the NO2-to-NOx conversion factors shows that they can account for the NOx chemistry in plumes, in particular for the conversion between NO and NO2 near the source and for the chemical loss of NOx further downstream. When applying these time-since-emission-dependent conversion factors, biases in NOx emissions estimated from TROPOMI NO2 images are greatly reduced from between −50 % and −42 % to between only −9.5 % and −0.5 % in comparison with reported emissions. Single-overpass estimates can be quantified with an uncertainty of 20 %–27 %, while annual NOx emission estimates have uncertainties in the range of 4 %–21 % but are highly dependent on the number of successful retrievals. Although more simulations covering a wider range of meteorological and trace gas background conditions will be needed to generalise the approach, this study marks an important step towards a consistent, uniform, high-resolution and near-real-time estimation of NOx emissions – especially with regard to upcoming NO2-monitoring satellites such as Sentinel-4, Sentinel-5 and CO2M.

Different types of models are used to study the stress-strain behavior of asphalt concrete mixture during compaction. For modeling it is necessary to know the values of model parameters in the whole range of changes in the characteristics of the compacted material. The aim of the paper is to develop a methodology for determining model parameters based on the results of laboratory creep-recovery testing of asphalt-concrete mixture. In the paper, a model reflecting elastic, visco-elastic and visco-fluid properties of the compacted material is adopted. A differential equation representing the law of behavior of the asphalt-concrete mixture layer under load is obtained. The stages of creep-recovery testing are analytically described, namely: rapid loading with a constant load and deformation under this load; load removal and recovery. Initial conditions for the mentioned stages are determined. Taking into account the initial conditions, analytical expressions of the laws of deformation of the model under the action of a constant load and in the process of recovery are obtained. The methodology of laboratory experiments on creep-recovery is described, according to the results of which the required values of the model parameters with minimum absolute error are obtained. The developed methodology allows to determine the parameters of the model describing the stress-strain behavior of asphalt-concrete mixture of different density and temperature. Consequently, it is possible to simulate the behavior of the asphalt concrete mixture layer at the preliminary, main and final stages of compaction in order to determine the effective operating modes of compaction equipment.

Machining processes hold a pivotal place in the sphere of modern manufacturing. Thus, constant advancements to enhance their efficiency and sustainability are warranted. This review paper discusses the recent advancements in machining with Minimum Quantity Lubrication and a combination of Nano-Fluids with Minimum quantity lubrication (Nano-Fluid MQL). Recent developments are assessed with particular emphasis on critical parameters such as cutting temperatures, tool wear, and surface quality. In addition, the environmental and economic aspects of using MQL in combination with nano-fluids are discussed. This combinatory approach is evaluated as a sustainable solution in machining. This paper also presents the literature survey of nano-fluids and the application of nano-fluids in MQL.

Abstract Accurate atom mapping, which establishes correspondences between atoms in reactants and products, is a crucial step in analyzing chemical reactions. In this paper, we present a novel end-to-end approach that formulates the atom mapping problem as a deep graph matching task. Our proposed model, AMNet (Atom Matching Network), utilizes molecular graph representations and employs various atom and bond features using graph neural networks to capture the intricate structural characteristics of molecules, ensuring precise atom correspondence predictions. Notably, AMNet incorporates the consideration of molecule symmetry, enhancing accuracy while simultaneously reducing computational complexity. The integration of the Weisfeiler-Lehman isomorphism test for symmetry identification refines the model’s predictions. Furthermore, our model maps the entire atom set in a chemical reaction, offering a comprehensive approach beyond focusing solely on the main molecules in reactions. We evaluated AMNet’s performance on a subset of USPTO reaction datasets, addressing various tasks, including assessing the impact of molecular symmetry identification, understanding the influence of feature selection on AMNet performance, and comparing its performance with the state-of-the-art method. The result reveals an average accuracy of 97.3% on mapped atoms, with 99.7% of reactions correctly mapped when the correct mapped atom is within the top 10 predicted atoms. Scientific contribution The paper introduces a novel end-to-end deep graph matching model for atom mapping, utilizing molecular graph representations to capture structural characteristics effectively. It enhances accuracy by integrating symmetry detection through the Weisfeiler-Lehman test, reducing the number of possible mappings and improving efficiency. Unlike previous methods, it maps the entire reaction, not just main components, providing a comprehensive view. Additionally, by integrating efficient graph matching techniques, it reduces computational complexity, making atom mapping more feasible.

Abstract Motivation Drug combination therapies have shown promise in clinical cancer treatments. However, it is hard to experimentally identify all drug combinations for synergistic interaction even with high-throughput screening due to the vast space of potential combinations. Although a number of computational methods for drug synergy prediction have proven successful in narrowing down this space, fusing drug pairs and cell line features effectively still lacks study, hindering current algorithms from understanding the complex interaction between drugs and cell lines. Results In this paper, we proposed a Permutable feature fusion network for Drug-Drug Synergy prediction, named PermuteDDS. PermuteDDS takes multiple representations of drugs and cell lines as input and employs a permutable fusion mechanism to combine drug and cell line features. In experiments, PermuteDDS exhibits state-of-the-art performance on two benchmark data sets. Additionally, the results on independent test set grouped by different tissues reveal that PermuteDDS has good generalization performance. We believed that PermuteDDS is an effective and valuable tool for identifying synergistic drug combinations. It is publicly available at https://github.com/littlewei-lazy/PermuteDDS . Scientific contribution First, this paper proposes a permutable feature fusion network for predicting drug synergy termed PermuteDDS, which extract diverse information from multiple drug representations and cell line representations. Second, the permutable fusion mechanism combine the drug and cell line features by integrating information of different channels, enabling the utilization of complex relationships between drugs and cell lines. Third, comparative and ablation experiments provide evidence of the efficacy of PermuteDDS in predicting drug-drug synergy.

Background: Haptic feedback has been shown to be an effective facilitator of the learning of scientific concepts in a series of studies. However, little is known about the underlying salient learning mechanisms, which are activated when learning from haptic feedback. Objectives: We investigate the learning mechanism in a higher chemistry education setting, in which the students learned about the abstract concept of potential energy in a quantum chemical context. Methods: In this work, we present a mixed‐methods problem‐solving prior to instruction (PS‐I) study with chemistry bachelor students. In an interactive quantum chemistry learning environment, the students explored the energetic profiles of nucleophilic substitution reactions and the corresponding activation barriers experienced as repulsion and attraction. We measured cognitive and affective mechanisms which have been shown to be activated in PS‐I designs, such as knowledge gap awareness, state curiosity, and positive affect as well as the learning outcome quantitatively and the learning trajectories qualitatively. Results and Conclusions: Planned contrasts revealed a small hindering effect of the haptic feedback on the learning outcome. Thematic analysis of the qualitative data lets us attribute this effect to the lack of scaffolding of the haptic feedback and the spontaneous atomic movements in the simulation, which may be interpreted as a visual representation of force in itself. This work highlights the importance of accurate mappings of the haptic feedback unto the target domain and further delivers insight into the prior conceptions of chemistry undergraduate students. Lay Description: What is already known about this topic: Haptic feedback can facilitate learning by grounding abstract concepts in sensory experiences.While previous studies have reported positive affective results, the cognitive results are ambiguous.Moreover, it was frequently reported that the learning of potential energy in a (quantum) chemical context is particularly difficult due to (i) the lack of grounding opportunities and (ii) the diverse previous conceptions. What this paper adds: A learning environment to interact with molecular systems in real‐time is proposed.The concept of activation energy is grounded in sensory experience of pushing and being pulled.The mixed‐methods design allows to explore cognitive and affective variables as well as the specific prior conceptions activated by the environment. Implications for practice and/or policy: We found a small negative effect of the haptic feedback on the learning outcome, potentially due to insufficient introduction of it to the students.The spontaneous movement of the atoms was identified as a more suitable external representation of the force.Future studies should investigate, if explicit introduction of the embodied metaphor can reverse this effect. [ABSTRACT FROM AUTHOR]

The escalating issue of solid waste with a significant focus on plastic waste has prompted the exploration of alternative sustainable approaches for waste management. This paper discusses the pressing environmental challenges associated with solid waste, particularly plastics. It highlights the importance of implementing a systematic approach that aligns with the most effective environmental practices. With approximately 5.6 million tonnes of plastic waste produced annually in India alone, and only 12.3 % being recycled, there is a critical need for a sustainable plastic-waste management strategy. Traditional methods like landfilling, incineration, and recycling have some limitations, emphasizing the need for a sustainable approach. In this context, plastic biodegradation by microorganisms isolated from landfills presents a promising solution, efficiently breaking down plastics into carbon dioxide, water, and biomass in an eco-friendly manner. In recent years, substantial research efforts have been dedicated to identify microorganisms and enzymes with the ability to degrade plastics. This review thus, explores the limitations of conventional plastic waste management and delves into microbiological-based approaches, with the focus on recent advances and findings in this arena. The crucial prerequisite for sustainable and eco-friendly alternatives to combat plastic pollution is underscored. Therefore, this paper also explores the current challenges associated with the biodegradation of plastics and accentuates future prospects for the ongoing advancement of plastic biodegradation technologies.

Advanced industrialization requires an enormous amount of water, dyes, and chemicals, and it continuously releases toxic effluents into the environment and water bodies. In textile, paper, leather, and other industries, dyes are the compounds being used to provide color to the substances. Among all of the dyes utilized in the dyeing sector, azo dyes contribute about 60 % of all dyestuffs used globally. Synthetic dyes harm the aesthetic qualities of water resources by elevating COD (Chemical oxygen demand) and BOD (Biological oxygen demand), toxic substances, turbidity, hindering photosynthesis, stifling plant development, contaminating the food chain, inducing recalcitrance, and accumulation, and effectively stimulating toxicity, carcinogenicity, as well as mutagenicity. To minimize negative impacts on the surroundings, people, and natural water bodies, wastewater comprising dye pollutants must be removed effectively through eco-friendly technology. As a result, treatment of these textile effluents is required before they are eliminated into the surroundings. Physical, chemical, physio-chemical, and biological methods are among those used for treating textile wastewater. Biological methods, such as treatment with bacteria, bacterial enzymes, fungi, and plants, were used due to their environment-friendly and cost-effective method. The classification of dyes and their degradation mechanism by bacteria are addressed in this paper.

The principle of Fourier Transform Infrared (FTIR) spectroscopy is based on atoms vibration and rotation, and it has become a universal and widely used spectral methodology to detect the internal molecular structures in all kinds of fields. Numerous review articles related to the applications of FTIR spectroscopy have been published in recent years. In addition, more and more scientists are aware the significance role of sample preparation to improve our life quality in life science. However, the application of FTIR spectroscopy in sample preparation hasn't been summarized. Thus, in the current paper, the application of FTIR spectroscopy in sample preparation was reviewed with the focuses on characterization of separation materials including both solid sorbents and liquid extractants, and the extraction mechanisms involved in the separation towards different targets including inorganic molecules such as rare earth elements, organic molecules such as phenolics, pharmaceuticals and illicit-drugs, and biomacromolecules of DNA and proteins. We believe that the current paper will be interested for the researchers in food science, forensic medicine, clinical medicine, environmental analysis and analytical chemistry.

The 9th International Tribology Conference, Fukuoka 2023 was held on 25–30 September 2023 at Fukuoka International Congress Center in Fukuoka City, Japan. The number of participants was 975 from 30 countries and regions, and the number of papers presented was 676. We thank all the people who joined and contributed to ITC. Papers submitted to this special issue went through peer-review process. Twenty papers were already published in Part 1, and 19 papers were accepted for publication in this Part 2. On behalf of the Organizing Committee, we would like to thank all the authors for their contributions, and also thank the editors, reviewers and the editorial office of Tribology Online for their efforts. Taking this opportunity, we would like to include in the next page the manuscript of the congratulatory speech delivered by Professor Masato Tanaka in Banquet on Thursday, 28 September, 2023

Biotoxins are ranges of toxic substances produced by animals, plants, and microorganisms, which could contaminate foods during their production, processing, transportation, or storage, thus leading to foodborne illness, even food terrorism. Therefore, proposing simple, rapid, and effective detection methods for ensuring food free from biotoxin contamination shows a highly realistic demand. Aptamers are single-stranded oligonucleotides obtained from the systematic evolution of ligands by performing exponential enrichment (SELEX). They can specifically bind to wide ranges of targets with high affinity; thus, they have become important recognizing units in safety monitoring in food control and anti-terrorism. In this paper, we reviewed the technical points and difficulties of typical aptamer screening processes for biotoxins. For promoting the understanding of food control in the food supply chain, the latest progresses in rapid optical detection of biotoxins based on aptamers were summarized. In the end, we outlined some challenges and prospects in this field. We hope this paper could stimulate widespread interest in developing advanced sensing systems for ensuring food safety.

This paper presents the results of studies on the transformation of geraniol (GA) in the presence of the natural mineral bentonite. The paper determines the influence of temperature, catalyst content, and reaction time on the course of the process. In order to determine the most favorable process conditions, the catalytic tests were carried out without solvent and under atmospheric pressure. Three functions were chosen to determine the most favorable process conditions: GA conversion and the selectivities of the main products: linalool – LO and beta-pinene – BP. In addition, the paper optimize GA transformation process based on response surface methodology (RSM). The impact of the most relevant process indicators was presented. For all factors of the method, their effects on all primary parameters were determined in the form of second-degree polynomials, and such process conditions were determined to achieve their maximum.

Thin metal layers such as silver (Ag) are being utilized for various optical and plasmonic applications as well as for electrical purposes, e.g., as transparent electrodes in display devices or solar cells. This paper focuses on optical MEMS applications such as the Fabry–Pérot interferometer (FPI). Within such filters, reflector materials such as distributed Bragg reflectors (DBRs) or subwavelength gratings (SWGs) have been widely used so far, whereas metallic thin films (MTFs) were limited in application due to their comparatively higher absorption. In this paper, thin sputtered Ag layers with thicknesses of 20, 40 and 60 nm on glass substrates have been investigated, and it is shown that the absorption is very low in the visible spectral range (VIS) and increases only in near-infrared (NIR) with increasing wavelength. Thus, we consider Ag-thin layers to be an interesting reflector material at least for the VIS range, which can be easily fabricated and integrated. However, Ag is not inert and stable when exposed to the atmosphere. Hence, it needs a passivation material. For this purpose, AlN has been chosen in this contribution, which can be deposited by sputtering as well. In this contribution, we have chosen thin AlN layers for this purpose, which can also be deposited by sputtering. Thus, various AlN/Ag/AlN-reflector stacks were created and patterned by lift-off technology preferably. The fabricated reflectors were characterized with respect to adhesion, stress, cohesion, homogeneity, and most importantly, their optical properties. It was found that the thickness of the AlN can be used to adjust the reflectance–transmittance ratio in the VIS range, and influences the adsorption in the NIR range as well. Based on the measured values of the reflectors with 40 nm Ag, an exemplary transmission filter characteristics has been predicted for a wavelength range from 400 to 800 nm. Both the maximum transmittance and the full width at half maximum (FWHM) can be tuned by variation of the AlN thickness from 20 to 60 nm.

The risks climate change poses to cultural heritage have garnered increased attention in recent decades, prompting reactions from organizations such as UNESCO and ICOMOS. While there is a consensus among heritage actors that the climate crisis requires a departure from “business as usual”, there is no unanimity regarding which aspects of heritage protection should remain unchanged and which necessitate transformation, nor what level of action and transformation is required. Such disagreements may not always be immediately apparent, as different approaches are often mentioned within the same policy paper or call for action. They offer different interpretations of the climate crisis impacts, different framings of what is at stake, and different political visions regarding the necessary steps, thus creating tensions. This paper utilizes maximum variation sampling to identify and analyse groups of approaches through which climate change has been addressed within the cultural heritage field, ranging from technical protection to decolonisation. It highlights the significance of grasping their political and eco-social underpinnings, crucial for fostering transdisciplinary dialogues that draw upon the expertise of natural and social sciences, engineering and humanities to alleviate tensions, jointly shape future actions and develop sustainable solutions that respect and protect heritage while fostering regenerative socio-ecological relations.

In this paper we describe the development of a self-test on content knowledge as one element of a digital learning environment. The self-test on prior knowledge consists of tasks in the categories Periodic Table of Elements, chemical bonding, chemical formulas, and chemical reactions (reaction equations and reaction mechanisms). For the study, tasks from all topics have been used in a paper-pencil multiple-choice and multiple response test on the task at hand and an accompanying questionnaire with closed and open items. The results of the study show that the students rated the tasks as suitable. Comments for improving the tasks regarding the wording or the design were implemented. Because of students’ lack of understanding regarding some of the technical terms, a glossary and games will be added to the digital learning environment. Many students overestimated their knowledge and their competences, therefore the self-test in the learning environment will include feedback to ensure that the students can improve their content knowledge and its application.

The IUPAC International Chemical Identifier (InChI) is a structure-based chemical identifier that encodes various aspects of a chemical structure into a hierarchically layered line notation. Because InChI is non-proprietary, open-source, and freely available to everyone, it is adopted in popular chemical information resources and software programs. This paper describes the InChI Open Education Resource (OER) (https://www.inchi-trust.org/oer/), designed to provide educators and other interested parties with resources, training material, and information related to InChI. Currently, the OER contains over 100 materials collected from various sources and provides users with search, filtering, and sorting functionalities to locate specific records. New relevant materials can be suggested by anyone, allowing the scientific community to share and find InChI-related resources. This paper will show how to use the InChI OER tag taxonomy to filter content and demonstrate two resources within the InChI OER; the ChemNames2LCSS Google Sheet and the InChILayersExplorer, an Excel spreadsheet that breaks an InChI into its layers. While the InChI OER is of value to a broader chemistry community, this paper seeks to reach out to chemical educators and provide them with an understanding of InChI and its role in the practice of science.

Hyperbranched polyester polyols have emerged as a promising candidate for polyurethane coatings due to their unique structure and properties. In this context, this paper aims to synthesize a new hyperbranched polyester polyol and evaluate its potential as a polyol for polyurethane coating applications. In this study, the synthesis of hyperbranched polyester polyol involves the reaction between a multifunctional alcohol and a multifunctional carboxylic acid or anhydride. It is further modified by incorporating 2-hydroxyethyl methacrylate and styrene. The properties of the polyester polyol were characterized using various analytical techniques, including FTIR, NMR, SEM and TGA. This paper also provides a discussion on the potential applications of the synthesized hyperbranched polyester polyol in several industries such as automotive, aerospace and construction.

Those who work with wood should have a basic knowledge of wood anatomy and chemistry so they can understand how different anatomical and chemical features influence wood properties and, in turn, how these properties contribute to different treatments and final wood utilization. However, little attempt has been made to map global research trends in wood anatomy and chemistry. This paper presents a bibliometric review of research trends in wood anatomy and chemistry to determine research trends and gaps in these research areas. A total of 183 publications on wood anatomy and chemistry from 1974 to 2023 were reviewed. The analysis was done with the VOSviewer software (version 1.6.13). The analysis focused on the bibliographic coupling of countries, co-authorship of authors, citation of documents, and co-occurrence of keywords, which were presented as network visualization maps. The findings revealed that the wood anatomy and chemistry publication trends, although not completely gradient, have been upwards since 2000. Countries including Germany, the United States, Switzerland, the United Kingdom, Brazil, the Netherlands, China, Italy, Mexico, Spain, the Czech Republic, Canada, Australia, Chile, Finland, France, Sweden, and Japan had a great impact on this research area. It also became evident that African countries lag in this area of research. Only one data source - Scopus - was used. It has a wide coverage of publications from diverse areas and provides researchers with information on the most important academic literature in any specific scientific domain. Therefore, the representation of publications presented in this study is limited to only the Scopus data source. [ABSTRACT FROM AUTHOR]

In 1867, controversy erupted when Jean-Anne-Henri Depaul, a Paris accoucheur , tested Justus von Liebig's new "food for infants" on four newborns, all of whom died within days. This paper examines the origins of Liebig's food, the debates in the French Academy of Medicine after Depaul's experiment, and how the events were discussed in the medical and popular presses. I argue that the controversy was shaped by a number of interconnected concerns, including the product's impracticality, disagreements within the field of chemistry, the riskiness of Depaul's experimentation, Liebig's problematic celebrity, the potential hubris of trying to emulate a natural product, and national tensions between France and Germany. Infant feeding was an emotionally charged and highly politicized site where multiple interests, anxieties, and ways of knowing collided. Although commercial infant foods, many of which made reference to Liebig in their advertising, would ultimately find popularity in the last decades of the nineteenth century, close attention to the first years of Liebig's product demonstrates that its credibility as a "scientific" mode of infant feeding was far from assured. Rather, Liebig's milk illustrates the early challenges of constructing and enforcing knowledge and trust at the intersection between food, science, and infant life, in both professional and popular arenas. [ABSTRACT FROM AUTHOR]

As scholarly communication becomes more multimodal in nature, research articles embrace semiotic resources in appended genres such as the graphical abstract (GA). As an established genre in Chemistry research articles, GAs visually remediate chemical processes or research niche. However, this genre still remains in a peripheral area of English for Specific Purposes (ESP) courses as ESP practitioners mainly focus on textual modes. With limited opportunities to compose GAs, students foster genre remediation skills that are limited to textual genres only, ignoring the potential of reading-to-design skills. Upon student composition and critical reflections on GAs, as well as qualitative and quantitative data collection from a survey and interview involving professors, young researchers (YRs) and students, this paper examines rhetorical functions as well as image and text relations, while throwing some light on skills and challenges involved when GA composition is intentionally embedded in an ESP course, and discusses ensuing pedagogical implications. • Switching from reading-to-write to reading-to-design skills. • Embedding critical visual literacy tasks and student remediation of RAs. • Visual remediation awareness through student agency and reflection. [ABSTRACT FROM AUTHOR]

Herein, short review paper investigated the rapidly progress in fluorescent biosensors field and their significant influences on analytical chemistry applications. An electrical signal can be produced from a biological reaction using an integrated receptor-transducer device called a biosensor. Because there are so many uses for biosensors in the medical field, including medication delivery, environmental monitoring, water and food quality monitoring, and illness detection, biosensor design and development have become a top priority for scientists and researchers in the last ten years. In the beginning, we started to explain the basic principles of fluorescence. Then, we moved to discuss about the current advancements, creative sensor designs, and the fusion of materials science and nanotechnology. The paper highlighted the sensitivity of fluorescent biosensors by addressing a wide range of applications, including biological research, environmental monitoring, and medical diagnostics. This review paper censoriously assessed the present difficulties, such as interference and constrained dynamic range, and provided explanations into ongoing research. Advanced material and nanotechnology integration is emerging as a force that improves biosensor performance and broadens their uses. This study also discussed the future possible breakthroughs in biosensor technology and its broad use in a variety of scientific and societal fields.

The comprehension of molecular structure is pivotal in chemistry education. Over the past decade, Mahidol University International College has employed various teaching tools for the introductory chemistry laboratory class. This paper outlines our evolutionary shift from traditional tools, such as plastic and plasticine models, to the integration of computer software, and ultimately to augmented reality (AR) and virtual reality (VR) tools—specifically, MoleculARweb and MolecularWebXR developed by École Polytechnique Fédérale de Lausanne researchers. In this paper, we detail the implementation of these tools in our classes and present the outcomes of student surveys. Our instructional focus encompasses VSEPR, Atomic Orbitals, Molecular Orbitals, Skeletal Formula, and Enantiomers. This paper not only serves as a model for educators in general chemistry at secondary school or university levels to incorporate technology into their classrooms but also showcases a collaborative endeavor between Swiss and Thai researchers.

Abstract Trillion of cigarette butts are annually littered without being recycled. This work aims at valorizing the whole cigarette butts and their components (paper, filter and tobacco) into Fe‐Nx‐C electrocatalysts for oxygen reduction reaction (ORR) in acid and alkaline media. The pristine wastes were pyrolyzed at 450 °C, activated with KOH at 700 °C, blended with iron phthalocyanine (FePc) precursor, and heat‐treated at 600 °C to produce a robust Fe‐Nx‐C material with ORR active units. The effect of the cigarette components on the final electrocatalytic activity was evaluated by thoroughly investigating the surface chemistry with XPS. The electrocatalysts displayed similar results among the different components in both media due to comparable surface chemistry, especially concerning the nitrogen functional groups. The highest performance was obtained in alkaline where the electrocatalysts from whole cigarettes and paper (CIGF_450 and CIGPF_450) showed an E1/2 of 0.89 V vs RHE, slightly larger than that of Pt/C with 40 wt % of Pt, which encouraged to replace Pt‐based electrocatalysts in alkaline fuel cells.

Ancient glass products have suffered from the baptism of time and experienced changes in the burial environment and weathering, resulting in a change in the proportions of their chemical composition and interfering with their accurate identification by later generations. In this paper, the chemical composition of ancient glass products is predicted and identified. First, the multivariate statistical ANOVA test is applied to explore the relationship between whether the cultural relics samples are weathered or not and the glass type, decoration, and color to derive a law of chemical composition of the cultural relics and to analyze the correlation and difference among the four factors. Second, compared with the relevant data of the existing glass products, the missing values are processed by using the method of filling in the plurality. The weathering condition of the sampling points of the samples whose surfaces are not weathered is judged by the “distance discrimination method.” Combined with the characteristics of the lead-barium glass and the high-potassium glass, the law of the chemical composition content on the surface of the samples, weathered or not, is explored. The modeling of the gray prediction method was applied again to predict the chemical composition content before weathering. Finally, the generalized Shapley function of fuzzy measurement was used to analyze the correlation between indicators and the chemical compositions and their differences. The scheme proposed in this paper can solve the difficult problem of category judgment in archeology, which is of great significance in promoting the smooth progress of archaeological work.

Acoustic cavitation, an intriguing phenomenon resulting from the interaction of sound waves with a liquid medium, has emerged as a promising avenue in agri-food processing, offering opportunities to enhance established processes improving primary production of ingredients and further food processing. This comprehensive review provides an in-depth analysis of the mechanisms, design considerations, challenges and scale-up strategies associated with acoustic cavitation for agri-food applications. The paper starts by elucidating the fundamental principles of acoustic cavitation and its measurement, delving then into the diverse effects of different parameters associated with, the acoustic wave, mechanical design and operation of the ultrasonic system, along with those related to the food matrix. The technological advancements achieved in the design and set-up of ultrasonic reactors addressing limitations during scale up are also discussed. The design, engineering and mathematical modelling of ultrasonic equipment tailored for agri-food applications are explored, along with strategies to maximize cavitation intensity and efficiency in the application of brining, freezing, drying, emulsification, filtration and extraction. Advanced US equipment, such as multi-transducers (tubular resonator, FLOW:WAVE®) and larger processing surface areas through innovative designing (Barbell horn, CascatrodesTM), are one of the most promising strategies to ensure consistency of US operations at industrial scale. This review paper aims to provide valuable insights into harnessing acoustic cavitation's potential for up-scaling applications in food processing via critical examination of current research and advancements, while identifying future directions and opportunities for further research and innovation.

Soap is a substance now taken for granted, but there is uncertainty, myth and misinformation about its development, and little scholarly attention has been paid to the likely circumstances surrounding its discovery. As part of a MSc in Experimental Archaeology, a project collated the earliest mentions of proto-soaps, reassessed previous experimental conclusions, and developed testable scenarios to explore how soap was first discovered, suggesting that the degreasing of fatty cloths after straining perfumed fats and oils may provide the conditions under which soap was first reliably and repeatedly observed. This paper offers a condensed version of this work. [ABSTRACT FROM AUTHOR]

This article studies the migration and settlement laws of backflow proppants after fracturing tight sandstone. This paper proposes a fitting method based on a multi-task learning network to address the issue of interference from multiple physical parameters during the transport and settlement processes of proppants. This method can effectively handle multi-dimensional interference factors and fit the mapping logic of multiple engineering parameters to transport patterns through the continuous correction of multi-layer networks. We first introduce the characteristics of tight sandstone reservoirs and their important value in mining, as well as the status of current research on the migration and settlement laws of proppants at home and abroad. Based on this, we then deeply analyze the sedimentation rate model of proppants in tight sandstone backflow and the equilibrium height of proppants under multiple factors of interference while considering the distribution characteristics of proppants. In order to more accurately simulate the transport and settlement laws of proppants, this paper introduces a multi-task learning network. This network can comprehensively consider multi-dimensional parameters, learn the inherent laws of data through training, and achieve accurate fitting of the transport and settlement laws of proppants. This study trained and tested the model using actual production data, and the results showed that the proposed model can fit the input–output relationship well, thus effectively supporting the study of proppant transport and settlement laws.

Healthcare is one of the industries that seeks to deliver medical services to patients on time. One of the issues it currently grapples with is real-time patient data exchange between various healthcare organizations. This challenge was solved by both centralized and decentralized cloud computing architecture solutions. In this paper, we review the current state of these two cloud computing architectures in the health sector with regard to the effect on the efficiency of Health Information Exchange (HIE) systems. Our study seeks to determine the relevance of these cloud computing approaches in assisting healthcare facilities in the decision-making process to adopt HIE systems. This paper considers the system performance, patient data privacy, and cost and identifies research directions in each of the architectures. This study shows that there are some benefits in both cloud architectures, but there are also some drawbacks. The prominent characteristic of centralized cloud computing is that all data and information are stored together at one location, known as a single data center. This offers many services, such as integration, effectiveness, simplicity, and rapid information access. However, it entails providing data privacy and confidentiality aspects because it will face the hazard of a single point of failure. On the other hand, decentralized cloud computing is built to safeguard data privacy and security whereby data are distributed to several nodes as a way of forming mini-data centers. This increases the system’s ability to cope with a node failure. Thus, continuity and less latency are achieved. Nevertheless, it poses integration issues because managing data from several sites could be a problem, and the costs of operating several data centers are higher and complex. This paper also pays attention to the differences in aspects like efficiency, capacity, and cost. This paper assists healthcare organizations in determining the most suitable cloud architecture strategy for deploying secure and effective HIE systems.

In this study, we developed a cost-effective and rapid method for fabricating force-sensing resistor (FSR) sensors as an alternative to commercial force sensors. Our aim was to achieve performance characteristics comparable to existing commercial products while significantly reducing costs and fabrication time. We analyzed the material composition of two widely used commercial force sensors: Interlink FSR-402 and Flexiforce A201-1. Based on this analysis, we selected 4B and 9B pencils, which contain high concentrations of graphite, and silicone sealant to replicate these material properties. The fabrication process involved creating piezoresistive sheets by shading A4 copy paper with 4B and 9B pencils to form a uniform layer of graphite. Additionally, we prepared a mixture of 9B pencil lead powder and silicone sealant, ensuring a consistent application on the paper substrate. Measurement results indicated that the force sensor fabricated using a mixture of 9B pencil powder and silicone sealant exhibited electrical and mechanical characteristics closely resembling those of commercial sensors. Load tests revealed that the hand-made sensors provided a proportional voltage output in response to increasing and decreasing loads, similar to commercial FSR sensors. These results suggest that our fabrication method can produce reliable and accurate FSR sensors suitable for various applications, including wearable technology, robotics, and force-sensing interfaces. Overall, this study demonstrates the potential for creating cost-effective and high-performance FSR sensors using readily available materials and simple fabrication techniques.

A digital twin is a new trend in the development of the current smart water conservancy industry. The main research content of intelligent water conservancy is clarified. This paper first summarizes and combs the relevant system architecture of smart water conservancy, and puts forward a smart water conservancy framework based on digital twins, highlighting the characteristics of virtual and real interaction, and symbiosis of the water conservancy twin platform. Secondly, the status quo of intelligent water conservancy “sky, air, ground and water” integrated monitoring technology, big data and artificial intelligence, model platform technology, knowledge graph and security technology is analyzed. From the perspective of application, the research progress of each technology in water security, water resources and hydraulic engineering is reviewed. Although the construction of smart water conservancy has made remarkable progress, it still faces many challenges such as data governance, technology integration and innovation, and standardization. In view of these challenges, this paper puts forward a series of countermeasures, and looks forward to the future development direction of intelligent water conservancy.

High-precision and rapid detection of apparent defects in subway tunnel linings is crucial for ensuring the structural integrity of tunnels and the safety of train operations. However, current methods often do not adequately account for the spatial characteristics of these defects and perform poorly in detecting and extracting small-scale defects, which limits the accuracy of detection and geometric parameter extraction. To address these challenges, this paper proposes an efficient algorithm for detecting and extracting apparent defects in subway tunnels. Firstly, YOLOv8 was selected as the foundational architecture due to its comprehensive performance. The coordinate attention module and Bottleneck Transformer 3 were then integrated into the model’s backbone to enhance the focus on defect-prone areas and improve the learning of feature relationships between defects and other infrastructure. Subsequently, a high-resolution detection layer was added to the model’s head to further improve sensitivity to subtle defects. Additionally, a low-quality crack dataset was created using an open access dataset, and transfer learning combined with Real-ESRGAN was employed to enhance the detail and resolution of fine cracks. The results of the field experiments demonstrate that the proposed model significantly improves detection accuracy in high-incidence areas and for small-scale defects, achieving a mean average precision (mAP) of 87% in detecting cracks, leakage, exfoliation, and related infrastructure defects. Furthermore, the crack enhancement techniques substantially improve the representation of fine-crack details, increasing feature extraction accuracy by a factor of four. The findings of this paper could provide crucial technical support for the automated operation and maintenance of metro tunnels.

As large-scale renewable energy sources are increasingly integrated into AC grids via voltage source converters (VSCs), the transient synchronization stability of phase-locked loop (PLL)-based VSCs during fault ride-through is gaining more attention. Most existing studies assume that the positive and negative sequence separation and current control dynamics are much faster than the PLL dynamics, thereby neglecting their impact on the transient synchronization stability of the system. However, when the PLL bandwidth is relatively large, ignoring the positive and negative sequence separation and current control dynamics may result in incorrect stability assessments. To address this issue, this paper first considers the multiple control loop coupling, including positive and negative sequence separation, current control, and PLL, to construct a full-order nonlinear mathematical model of the VSC grid-connected system under asymmetric fault conditions. Based on this, the phase trajectory method is employed to analyze the transient synchronization stability of the system. Additionally, this full-order mathematical model is used to determine the PLL bandwidth boundary beyond which the effects of positive and negative sequence separation and current control dynamics cannot be neglected. Finally, PSCAD/EMTDC simulation results validate the effectiveness of the theoretical analysis presented in this paper.

Drone area coverage primarily involves using unmanned aerial vehicles (UAVs) for extensive monitoring, surveying, communication, and other tasks over specific regions. The significance and value of this technology are multifaceted. Firstly, UAVs can rapidly and efficiently reach remote or inaccessible areas to perform tasks such as terrain mapping, disaster monitoring, or search and rescue, significantly enhancing response speed and execution efficiency. Secondly, drone area coverage in agricultural monitoring, forestry conservation, and urban planning offers high-precision data support, aiding scientists and decision-makers in making more accurate judgments and decisions. Additionally, drones can serve as temporary communication base stations in areas with poor communication, ensuring the transfer of crucial information. Drone area coverage technology is vital in improving work efficiency, reducing costs, and strengthening decision support. This paper aims to solve the optimization problem of multi-UAV area coverage flight path planning to enhance system efficiency and task execution capability. For multi-center optimization problems, a region decomposition method based on the Voronoi graph is designed, transforming the multi-UAV area coverage issue into the single-UAV area coverage problem, greatly simplifying the complexity and computational process. For the single-UAV area coverage problem and its corresponding area, this paper contrives a convolutional neural network with the channel and spatial attention mechanism (CSAM) to enhance feature fusion capability, enabling the model to focus on core features for solving single-UAV path selection and ultimately generating the optimal path. Simulation results demonstrate that the proposed method achieves excellent performance.

This paper aims to present an approach to address the atom rearrangement problem by developing Convolutional Neural Network (CNN) models. These models predict the coordinates for atom movements while ensuring collision-free transitions and filling all vacancies in the target array. The process begins with designing a cost function for the assignment problem that incorporates constraints to prevent collisions and guarantee vacancy filling. We then build and train CNN models using datasets for three different grid sizes: 10×10, 13×13, and 21×21. Our models achieve high accuracy in predicting atom positions, with individual position accuracies of 99.63%, 98.93%, and 97.24%, respectively, for the aforementioned grid sizes. Despite limitations in training larger models due to hardware constraints, our approach demonstrates significant improvements in speed and accuracy. The final section of the paper presents detailed accuracy results and calculation times for each model, highlighting the potential of CNN-based methods in optimizing atom rearrangement processes.

The traditional finite element method (FEM) has limitations in accurately modeling crack propagation. Peridynamics, a nonlocal extension of the classical continuum theory, provides an alternative approach to remedy the limitations of the FEM but with a higher computational cost. In this paper, a peridynamic bond-based fatigue damage model is developed and incorporated into a commercial finite-element software (ABAQUS 2017) via user subroutines. Model-predicted results including the crack path spatial position and the damage accumulation rate were validated against empirical data. The predicted crack growth as a function of loading cycle and crack trajectory showed good agreement with the experimental data over 200,000 loading cycles. Therefore, the integration of the peridynamic bond-based fatigue damage model into existing FEM software provides an economical means to simulate complex fracture behaviors, such as crack growth, in a compact tension specimen examined in this paper.