SHAPE Probing to Screen Computationally Designed RNA.

RNA design is a major challenge for the future development of synthetic biology and RNA-based therapy. The development of efficient and accurate RNA design pipelines is based on trial and error strategies. The fast progression of such algorithms requires assaying the properties of many RNA sequences in a short time frame. High throughput RNA structure chemical probing technologies such as SHAPE-MaP allow for assaying RNA structure and interaction rapidly and at a very large scale. However, the promiscuity of the designed sequences that may differ only by one nucleotide requires special care. In addition, it necessitates the analysis and evaluation of many experimental results that may reveal to be very tedious. Here we propose an experimental and analytical workflow that eases the screening of thousands of designed RNA sequences at once. In particular, we have developed shapemap tools a customized software suite available at https://github.com/sargueil-citcom/shapemap-tools .

Combining slow-release fertilizer and plastic film mulching reduced the carbon footprint and enhanced maize yield on the Loess Plateau.

Agricultural practices significantly contribute to greenhouse gas (GHG) emissions, necessitating cleaner production technologies to reduce environmental pressure and achieve sustainable maize production. Plastic film mulching is commonly used in the Loess Plateau region. Incorporating slow-release fertilizers as a replacement for urea within this practice can reduce nitrogen losses and enhance crop productivity. Combining these techniques represents a novel agricultural approach in semi-arid areas. However, the impact of this integration on soil carbon storage (SOCS), carbon footprint (CF), and economic benefits has received limited research attention. Therefore, we conducted an eight-year study (2015-2022) in the semi-arid northwestern region to quantify the effects of four treatments [urea supplied without plastic film mulching (CK-U), slow-release fertilizer supplied without plastic film mulching (CK-S), urea supplied with plastic film mulching (PM-U), and slow-release fertilizer supplied with plastic film mulching (PM-S)] on soil fertility, economic and environmental benefits. The results revealed that nitrogen fertilizer was the primary contributor to total GHG emissions (≥71.97%). Compared to other treatments, PM-S increased average grain yield by 12.01%-37.89%, water use efficiency by 9.19%-23.33%, nitrogen accumulation by 27.07%-66.19%, and net return by 6.21%-29.57%. Furthermore, PM-S decreased CF by 12.87%-44.31% and CF per net return by 14.25%-41.16%. After eight years, PM-S increased SOCS (0-40 cm) by 2.46%, while PM-U decreased it by 7.09%. These findings highlight the positive effects of PM-S on surface soil fertility, economic gains, and environmental benefits in spring maize production on the Loess Plateau, underscoring its potential for widespread adoption and application.

Carbon emissions in China's steel industry from a life cycle perspective: Carbon footprint insights.

China is the most important steel producer in the world, and its steel industry is one of the most carbon-intensive industries in China. Consequently, research on carbon emissions from the steel industry is crucial for China to achieve carbon neutrality and meet its sustainable global development goals. We constructed a carbon dioxide (CO2) emission model for China's iron and steel industry from a life cycle perspective, conducted an empirical analysis based on data from 2019, and calculated the CO2 emissions of the industry throughout its life cycle. Key emission reduction factors were identified using sensitivity analysis. The results demonstrated that the CO2 emission intensity of the steel industry was 2.33 ton CO2/ton, and the production and manufacturing stages were the main sources of CO2 emissions, accounting for 89.84% of the total steel life-cycle emissions. Notably, fossil fuel combustion had the highest sensitivity to steel CO2 emissions, with a sensitivity coefficient of 0.68, reducing the amount of fossil fuel combustion by 20% and carbon emissions by 13.60%. The sensitivities of power structure optimization and scrap consumption were similar, while that of the transportation structure adjustment was the lowest, with a sensitivity coefficient of less than 0.1. Given the current strategic goals of peak carbon and carbon neutrality, it is in the best interest of the Chinese government to actively promote energy-saving and low-carbon technologies, increase the ratio of scrap steel to steelmaking, and build a new power system.

[Recommendations for Reducing the Environmental Impact of Inhalers in Portugal: Consensus Document]. / Recomendações para a Redução do Impacto Ambiental dos Inaladores em Portugal: Documento de Consenso.

This consensus document addresses the reduction of the environmental impact of inhalers in Portugal. It was prepared by the Portuguese Council for Health and the Environment and the societies representing the specialties that account for these drugs' largest volume of prescriptions, namely the Portuguese Society of Pulmonology, the Portuguese Society of Allergology and Clinical Immunology, the Portuguese Society of Pediatrics, the Portuguese Society of Internal Medicine, the Portuguese Association of General and Family Medicine and also a patient association, the Respira Association. The document acknowledges the significant impact of pressurized metered-dose inhalers on greenhouse gas emissions and highlights the need to transition to more sustainable alternatives. The carbon footprint of pressurized metered-dose inhalers and dry powder inhalers in Portugal was calculated, and the level of awareness among prescribing physicians on this topic was also estimated. Finally, recommendations were developed to accelerate the reduction of the ecological footprint of inhalers.

Este documento de consenso aborda a redução do impacto ambiental dos inaladores em Portugal. Foi elaborado pelo Conselho Português para a Saúde e Ambiente e pelas sociedades que representam as especialidades com maior volume de prescrição destes medicamentos, nomeadamente a Sociedade Portuguesa de Pneumologia, a Sociedade Portuguesa de Alergologia e Imunologia Clínica, a Sociedade Portuguesa de Pediatria, a Sociedade Portuguesa de Medicina Interna e a Associação Portuguesa de Medicina Geral e Familiar em conjunto com uma associação de doentes, a Associação Respira. Reconhece-se o impacto significativo dos inaladores pressurizados doseáveis nas emissões de gases com efeito de estufa e a necessidade de transição para alternativas mais sustentáveis. Calculou-se a pegada de carbono dos inaladores pressurizados doseáveis e dos inaladores de pó seco em Portugal e estimou-se o nível de literacia dos médicos prescritores relativamente a este tema. Finalmente, foram elaboradas recomendações com o objetivo de acelerar a redução da pegada ecológica dos inaladores.

Does artificial intelligence affect the ecological footprint? -Evidence from 30 provinces in China.

Artificial intelligence (AI) technology serves as a powerful tool to optimize energy efficiency and lessen ecological footprints. Using data from 30 provinces in China over the period from 2018 to 2022, this study investigates how regional AI development affects the per capita ecological footprint and explores the underlying mechanisms. The results show that: (1) Regional AI development can significantly decrease the ecological footprint, and this conclusion remains robust after a series of robustness checks. (2) Mediation effect analysis indicates that AI technology mainly decreases the ecological footprint by improving energy utilization efficiency. (3) The panel threshold model results show that AI's influence on the ecological footprint has a single energy efficiency threshold. Only when regional energy efficiency exceeds a certain threshold can AI fully exert its suppressive effect on the ecological footprint. (4) Regional heterogeneity analysis shows that the reduction effect of AI on the ecological footprint is more pronounced in the central and eastern regions of China. This paper helps clarify the specific impact of AI technology development on the ecological footprint and provides scientific evidence for regional technology development, energy efficiency improvement, and ecological environment policy formulation.

Combining large language models with enterprise knowledge graphs: a perspective on enhanced natural language understanding.

Knowledge Graphs (KGs) have revolutionized knowledge representation, enabling a graph-structured framework where entities and their interrelations are systematically organized. Since their inception, KGs have significantly enhanced various knowledge-aware applications, including recommendation systems and question-answering systems. Sensigrafo, an enterprise KG developed by Expert.AI, exemplifies this advancement by focusing on Natural Language Understanding through a machine-oriented lexicon representation. Despite the progress, maintaining and enriching KGs remains a challenge, often requiring manual efforts. Recent developments in Large Language Models (LLMs) offer promising solutions for KG enrichment (KGE) by leveraging their ability to understand natural language. In this article, we discuss the state-of-the-art LLM-based techniques for KGE and show the challenges associated with automating and deploying these processes in an industrial setup. We then propose our perspective on overcoming problems associated with data quality and scarcity, economic viability, privacy issues, language evolution, and the need to automate the KGE process while maintaining high accuracy.

Environmental Sustainability Initiatives in the Operating Room: A Scoping Review.

The global healthcare industry has a substantial environmental footprint and therefore has a responsibility to decrease its impact. Changes to increase sustainability will only occur if healthcare providers (HCPs) and decision-makers understand and incorporate environmentally conscious practices in the operating room (OR). This scoping review aimed to assess hospital initiatives undertaken to support environmental sustainability in the OR, with a focus on HCP and hospital decision-maker beliefs and perceptions related to sustainability. A scoping review was conducted using Embase and PubMed. Searches were performed to identify relevant studies published between January 2011 and November 2022. A total of 163 publications were included: 10 systematic literature reviews and 153 original research articles. Most studies reported department-wide sustainability measures (waste reduction, staff education, etc), which were evaluated by the reduction in generated waste and energy, emission of greenhouse gasses, and costs. Despite up to 97% of HCPs noting willingness to improve sustainability within practices, up to 80.9% of HCPs stated that they lacked the necessary training and information. In conclusion, this research highlights a recent increase in interest about sustainability initiatives in the OR and that HCPs and surgical staff are not only willing to participate but also have suggestions on how to minimize the environmental impact of the OR.

Tracking Carbon and Ammonia Emission Flows of China's Nitrogen Fertilizer System: Implications for Domestic and International Trade.

China is the world's largest producer, consumer, and exporter of synthetic nitrogen (N) fertilizer. To assess the impact of domestic demand and international exports, we quantified the life-cycle CO2eq and ammonia (NH3) emissions by tracking carbon (C) and nitrogen (N) flows from coal/gas mining through ammonia production to N fertilizer production, application, and export. In 2020, China's N fertilizer system emitted 496.04 Tg of CO2eq and 3.74 Tg of NH3, with ammonia production and N fertilizer application processes contributing 36 and 85% of the life-cycle CO2eq and NH3 emissions, respectively. As the largest importers of N fertilizer, India, Myanmar, South Korea, Malaysia, and the Philippines collectively shifted 112.41 Tg of CO2eq. For every ton of N fertilizer produced and used in China, 16 t of CO2eq and 0.18 t of NH3 were emitted, compared to 9.7 t of CO2eq and 0.13 t of NH3 in Europe. By adopting currently available technologies, improving N fertilizer utilization efficiency and employing nitrification inhibitors could synergistically reduce CO2eq emissions by 20% and NH3 emissions by 75%, while energy transformation efforts would primarily reduce CO2eq emissions by 59%. The production of ammonia using green electricity or green hydrogen could significantly enhance the decarbonization of China's N fertilizer system.

Assessing the carbon footprint of soybean transportation in Brazil: a network equilibrium model approach.

Brazil has historically invested few resources in its transport infrastructure, leaving gaps and reducing its efficiency. The country presents a high dependence on road transport, which results in increased operational costs and higher greenhouse gas (GHG) emissions. Consequently, the performance of cargo transportation in Brazil has been deteriorating, accompanied by a rise in the consumption of fossil fuels and noteworthy levels of GHG emissions. This article assesses the carbon intensity of soybean transport operations within Brazil. Utilizing a network equilibrium model, this study estimated the soybean transportation flows that minimize the total cost of transporting this product across the origins and destinations within the grain handling system. The modeling also calculated the GHG emissions in transportation. The results show that the transportation of soybeans produced 2.74 million tonnes of CO2 equivalent annually, with road transport accounting for 81.7% of these emissions. The state of Mato Grosso, responsible for 44.08 kg CO2 equivalent per tonne of soybeans transported, contributed almost 49% of the total emissions due to the extensive distances involved. In contrast, states like Paraná and Rio Grande do Sul, located closer to southern ports, exhibited the lowest emissions, with rates of 11.55 kg CO2 eq/t and 12.52 kg CO2 eq/t, respectively. The analysis highlights the significant potential for reducing GHG emissions by increasing the use of rail and barge transport, particularly in high-emission regions such as Mato Grosso.

The urban-rural dietary water footprint and its inequality in China's urban agglomerations.

Food system is the main consumer of water resources, and the differences in urban and rural diets pose new challenges to the water sustainability and increase the uncertainty of food security in China. In this study, we quantified the dietary water footprint (DWF) of urban and rural residents at the city scale in four major urban agglomerations in China from 2015 to 2021, identified the key economic and educational factors of urban and rural DWF, and measured the inequality of urban and rural DWF driven by the main influencing factors. We found that there was a 27.17 % increase in urban DWF and a 23.18 % increase in rural DWF between 2015 and 2021. Cereals had the largest water footprint among the 12 food types, accounting for 20.27 % and 31.57 % of urban and rural DWF, respectively. Meanwhile, milk and dairy products contributed the most to the difference between urban and rural DWF, up to 57.89 m3 each year. The main economic factor of DWF was consumption expenditure. The number of primary school students and the number of primary schools are the most important educational factors of urban and rural DWF, respectively. The results show there is an inequality between DWF and major educational factors, with a decreasing trend in DWF inequality over time. This study revealed for the first time the difference between urban and rural DWF at the city scale, and clarified the impact of regional educational inequality on DWF. A greater focus should be placed on the primary education-related factors that influence DWF inequality, in order to better target sustainable DWF strategies for urban and rural residents.

Impact of the circular economy on ecological footprint: evidence from Germany.

The circular economy practices contribute to sustainable development by maximising efficiency, utilising renewable resources, extending product lifespans, and implementing waste reduction strategies. This study investigates the individual impacts of four sources of the circular economy on the ecological footprint in Germany, a country that is among the pioneers in establishing a comprehensive roadmap for the circular economy. The four sources examined are renewable energy consumption (REC), recycling, reuse, and repair of materials. Using time series data from 1990 to 2021, the study employed the dynamic autoregressive distributed lag (ARDL) simulation technique and also applied kernel-based linear regression (KRLS) to test the robustness of the results. The findings revealed that reuse practices significantly reduce the ecological footprint in both the short and long run. REC and repair also substantially decrease the ecological footprint, as shown by the simulation analysis. Conversely, while recycling is generally considered crucial for minimising environmental impact, in this study, it was found to contribute to environmental degradation. This paradox may be attributed to the nascent state of the recycling industry and data limitations. The results from KRLS confirm the findings of the dynamic ARDL. It is recommended that policymakers develop measures that are appropriate, efficient, and targeted to enhance the role of each source of the circular economy in reducing the ecological footprint in Germany. The major limitation of the study is its reliance on the indirect measures of circular economy attributed to the non-availability of data on direct measures.

Low-carbon diets across diverse dietary patterns: Addressing population heterogeneity under constrained optimization.

Mathematical optimization is a useful tool for modeling diets that fulfill requirements for health and environmental sustainability, however, population-based optimization approaches fail to account for underlying dietary diversity in populations. This study proposes a methodological approach to consider diverse dietary intake patterns in mathematical optimization of nutritionally adequate low-carbon diets and investigates the differences between different population groups, along with trade-offs between greenhouse gas emission (GHGE) reduction and the inconvenience of dietary changes required to achieve optimized diets. A k-means clustering analysis was applied to individual dietary intake data from Denmark, which resulted in four clusters with different dietary patterns. This was followed by quadratic programming, wherein the total dietary changes required from the observed diet within each cluster were used as a proxy for consumer inconvenience (i.e., "inconvenience index") and were minimized while fulfilling nutrient constraints and incrementally tightened GHGE constraints. Across clusters, a steep increase of the inconvenience index was observed at GHGE levels below approximately 3 kg CO2e/10 MJ, corresponding to GHGE reductions of 24-36 % in different clusters. In all clusters, the optimized diets with nutritional and GHGE constraints showed common traits of increased content of cereals and starches, eggs, and fish and decreased amounts of beef and lamb, cheese, animal-based fats, and alcoholic beverages, but differences across clusters were also observed, maintaining characteristics of the clusters' baselines. When additional health-based targets for food amounts were applied as constraints, the optimized diets converged towards the same type of diet. The total inconvenience of dietary changes required to fulfill constraints differed between clusters, indicating that specific sub-populations may be more effective targets for dietary transition. The method has potential for future integration of more sustainability aspects and different consumer preferences.

MCF classifier: Estimating, standardizing, and stratifying medicine carbon footprints, at scale.

AIMS: Healthcare accounts for 5% of global greenhouse gas emissions, with medicines making a sizeable contribution. Product-level medicine emission data is limited, hindering mitigation efforts. To address this, we created Medicine Carbon Footprint (MCF) Classifier, to estimate, standardize, stratify and visualize medicine carbon footprints. METHODS: We used molecular weight and chemical structure to estimate the process mass intensity and global warming potential of the active pharmaceutical ingredient in small molecule medicines. This allowed us to estimate medicine carbon footprints per dose, which we categorized into MCF Ratings, accessible via a searchable web application, MCF Formulary. We performed comparison and sensitivity analyses to validate the ratings, and stratification analyses by therapeutic indication to identify priority areas for emission reduction interventions. RESULTS: We generated standardized medicine carbon footprints for 2214 products, with 38% rated LOW, 35% MEDIUM, 25% HIGH and 2% VERY HIGH. These products represented 2.2 billion NHS England prescribed doses in January 2023, with a total footprint of 140 000 tonnes CO2e, equivalent to the monthly emissions of 940 000 cars. Notably, three antibiotics-amoxicillin, flucloxacillin and penicillin V-contributed 15% of emissions. We estimate that implementing the recommended 20% antibiotic prescription reduction could save 4200 tonnes CO2e per month, equivalent to removing 29 000 cars. CONCLUSIONS: Standardized medicine carbon footprints have utility in assessing and addressing the carbon emissions of medicines, and the potential to inform and catalyse changes needed to align better healthcare and net zero commitments.

A preliminary study on the stability of bare footprint linear measurements in four motion states.

In some crime scenes, there may be bare footprints. Analyzing and testing the linear measurements of bare footprints in crime scenes can play an important role in personal analysis and individual identification. However, the linear measurements of bare footprints may be influenced by different motion states, leading to changes in length and width or even significant deviations. Previous studies focused on the linear differences between static and dynamic footprints, and failed to take the speed factor into consideration. This paper studied the stability and change regularities of the linear measurements of bare footprints in four different motion states: standing, normal walking, fast walking and trotting. Dust footprints of the right feet were collected from 80 healthy young adults under these four motion states. Seven linear measurements were obtained for each footprint using the Reel method, totaling 2240 data sets. One-way repeated measures ANOVA was used to assess the measurement variations across the four states. The results showed that there were statistically significant variances in the length measurements (A1-A5) between the standing state and other motion states, whereas no statistically significant variances were observed between the three dynamic states. It was found that the mean values of the five length measurements (A1-A5) increased from static to dynamic state, and then gradually decreased slightly as the walking speed increased. Additionally, no significant differences were found in the two width measurements (MPJ Width and Calc Width) between the four motion states. As a preliminary study, this study can provide a reference for the analysis of bare footprints in different motion states extracted from crime scenes.

The carbon footprint of Bubble-PAPR™: A novel item of personal protective equipment.

Background: Personal protective equipment has important environmental impacts, assessing these impacts is therefore an important element of personal protective equipment design. We applied carbon footprinting methodology to Bubble-PAPR™, a novel, part-reusable and part-recyclable powered air-purifying respirator, designed at our institution. Current guidance states that disposable respirator masks can be worn for 1-h in the United Kingdom, whilst the Bubble-PAPR™ allows prolonged use. Methods: Following a detailed use-case analysis, the carbon footprint of each component was estimated using a bottom-up (attributional) cradle-to-grave process-based analysis. Modelling considered the use of virgin or closed loop recycled polyvinyl chloride for the disposable hood element, and disposal via infectious or recycling waste streams to estimate a per-use carbon footprint. Results: The per-use carbon footprint with manufacture from virgin polyvinyl chloride and disposal via incineration is 0.805 kgCO2e. With nine cycles of closed loop recycling and manufacture of the polyvinyl chloride hood (10 uses), the carbon footprint falls to an average of 0.570 kgCO2e per use. Conclusion: Carbon footprinting may contribute to the value proposition of this novel technology. We estimate that a single Bubble-PAPR™ use has a higher carbon footprint than disposable respirator mask-based PPE. However, this is mitigated in circumstances when multiple disposable mask changes are required (e.g. prolonged use) and use may be justifiable when user comfort, visualisation and communication with patients and colleagues are essential.

Institutional Conversion to Energy-Efficient Ultra-Low Freezers Decreases Carbon Footprint and Reduces Energy Costs.

Introduction: The storage of biospecimens is a substantial source of greenhouse gas emissions and institutional energy costs. Energy-intensive ultra-low temperature (ULT) freezers used for biospecimen storage are a significant source of carbon emissions. ENERGY STAR-certified ULT freezers have the potential to decrease the carbon footprint. Objective: Quantify the impact of an institutional-scale freezer conversion program on carbon emissions and energy costs. Methods: A ULT freezer energy use prediction model was developed to identify and replace the most inefficient freezers in the research building for this pilot, and eventually institution-wide. Multiple linear regression factors included the number of years of use, storage volume, and ENERGY STAR certification status. Electrical usage and carbon emissions were quantified before and after replacement with ENERGY STAR models. Logistical methods were developed to decrease the risks of exposure of frozen samples to ambient temperature during content transfers. Institution-wide energy costs were derived by converting electrical burden to electrical costs. Carbon footprint assessment from ULT freezer operation was computed using the U.S. EPA Greenhouse Gas Equivalencies Calculator. Results: The pilot project revealed an annual reduction of 310,493 kilowatt hours of electrical usage, equivalent to 134 metric tons of carbon emissions. Annual electrical costs were reduced by $55,889 resulting in an 8-year payback on the initial investment. Using the pilot results, we modeled the benefit of the freezer exchange across the entire institution. The modeling predicted that conversion of the institution's remaining 1119 conventional ULT freezers to ENERGY STAR models would lower annual electrical usage by 7,911,549 kilowatt hours (3423 metric tons of carbon emissions), resulting in savings of over $1.4 million annually. Conclusion: Our methods make a large-scale initiative to replace energy-inefficient ULT freezers logistically possible, reduce carbon footprint, and demonstrate an attractive return on investment while proactively protecting valuable research materials.

Case study of the environmental impacts and benefits of a PBF-LB additively manufactured optimized filtrate nozzle.

In this paper, we present a comprehensive case study of a laser-based powder bed fusion-manufactured optimized filtrate nozzle, focusing on environmental impacts and benefits. The scope of the study covers the raw material production, part manufacturing and use phases. We compare the results for similar components manufactured by conventional, mainly material-removing manufacturing technologies. Primary data, measured from processes, are utilized for life cycle assessment calculations, which are completed with database data when necessary. The results show that by exploiting the design freedom of additive manufacturing, it is possible to achieve positive environmental benefits, namely, a 40% reduction in the carbon footprint during the use phase, although the manufacturing phase per se requires a similar amount or even more resources than the conventional manufacturing route. In addition to environmental benefits, we present here some other potential benefits for using optimized, additively manufactured parts.

Minimizing energy footprint of seawater desalination system via wind power generation in coastal areas.

Wind power has become an essential direction for transforming energy structures in energy-intensive seawater desalination under the dual goals of carbon peaking and carbon neutrality. In this study, the energy footprint of the case project is analyzed by combining the hybrid life cycle analysis and environmentally extended input-output modeling, which is compared with the traditional thermal desalination processes from the whole life cycle perspective. The analysis revealed that the total energy consumption of the seawater desalination driven by wind power generation can be reduced by 79.77% compared with the traditional thermal drive mode under the same water production scale. Although the energy consumption in the construction phase accounts for 24.97% of the total, the energy consumption per unit of water production can be reduced by about 80% after adopting wind power technologies. The payback period is 7.2 years, that is, the energy consumption can be balanced after around 7 years during the operation phase. The results showed that the wind-driven seawater desalination system can significantly decrease the energy consumption of the project, which attempts to provide implications for the upgrading of energy-intensive seawater desalination in coastal areas towards low-carbon transition.

Functional Characterization of Accessible Chromatin in Common Wheat.

Eukaryotic gene transcription is fine-tuned by precise spatiotemporal interactions between cis-regulatory elements (CREs) and trans-acting factors. However, how CREs individually or coordinated with epigenetic marks function in regulating homoeolog bias expression is still largely unknown in wheat. In this study, through comprehensively characterizing open chromatin coupled with DNA methylation in the seedling and spikelet of common wheat, we observed that differential chromatin openness occurred between the seedling and spikelet, which plays important roles in tissue development through regulating the expression of related genes or through the transcription factor (TF)-centered regulatory network. Moreover, we found that CHH methylation may act as a key determinant affecting the differential binding of TFs, thereby resulting in differential expression of target genes. In addition, we found that sequence variations in MNase hypersensitive sites (MHSs) result in the differential expression of key genes responsible for important agronomic traits. Thus, our study provides new insights into the roles of CREs in regulating tissue or homoeolog bias expression, and controlling important agronomic traits in common wheat. It also provides potential CREs for genetic and epigenetic manipulation toward improving desirable traits for wheat molecule breeding.