Complex Process Research Articles

Upconversion nanoparticles-modified aptasensors for highly sensitive mycotoxin detection for food quality and safety.

Mycotoxins, highly toxic and carcinogenic secondary metabolites produced by certain fungi, pose significant health risks as they contaminate food and feed products globally. Current mycotoxin detection methods have limitations in real-time detection capabilities. Aptasensors, incorporating aptamers as specific recognition elements, are crucial for mycotoxin detection due to their remarkable sensitivity and selectivity in identifying target mycotoxins. The sensitivity of aptasensors can be improved by using upconversion nanoparticles (UCNPs). UCNPs consist of lanthanide ions in ceramic host, and their ladder-like energy levels at f-orbitals have unique photophysical properties, including converting low-energy photons to high-energy emissions by a series of complex processes and offering sharp, low-noise, and sensitive near-infrared to visible detection strategy to enhance the efficacy of aptasensors for novel mycotoxin detection. This article aims to review recent reports on the scope of the potential of UCNPs in mycotoxin detection, focusing on their integration with aptasensors to give readers clear insight. We briefly describe the upconversion photoluminescence (UCPL) mechanism and relevant energy transfer processes influencing UCNP design and optimization. Furthermore, recent studies and advancements in UCNP-based aptasensors will be reviewed. We then discuss the potential impact of UCNP-modified aptasensors on food safety and present an outlook on future directions and challenges in this field. This review article comprehensively explains the current state-of-the-art UCNP-based aptasensors for mycotoxin detection. It provides insights into potential applications by addressing technical and practical challenges for practical implementation.

Machine learning bias correction and downscaling of urban heatwave temperature predictions from kilometre to hectometre scale

AbstractThe urban heat island (UHI) effect exacerbates near‐surface air temperature (T) extremes in cities, with negative impacts for human health, building energy consumption and infrastructure. Using conventional weather models, it is both difficult and computationally expensive to simulate the complex processes controlling neighbourhood‐scale variation of T. We use machine learning (ML) to bias correct and downscale T predictions made by the Met Office operational regional forecast model (UKV) to 100 m horizontal grid length over London, UK. A set of ML models (random forest, XGBoost, multiplayer perceptron) are trained using citizen weather station observations and UKV variables from eight heatwaves, along with high‐resolution land cover data. The ML models improve the T mean absolute error (MAE) by up to 0.12°C (11%) relative to the UKV. They also improve the UHI diurnal and spatial representation, reducing the UHI profile MAE from 0.64°C (UKV) to 0.15°C. A multiple linear regression performs almost as well as the ML models in terms of T MAE, but cannot match the UHI bias correction performance of the ML models, only reducing the UHI profile MAE to 0.49°C. UKV latent heat flux is found to be the most important predictor of T bias. It is demonstrated that including more heatwaves and observation sites in training would reduce overfitting and improve ML model performance.

Formation of chronic morphine withdrawal memories requires C1QL3-mediated regulation of PSD95 in the mouse basolateral amygdala

Chronic morphine withdrawal memory formation is a complex process influenced by various molecular mechanisms. In this study, we aimed to investigate the contributions of the basolateral amygdala (BLA) and complement component 1, q subcomponent-like 3 (C1QL3), a secreted and presynaptically targeted protein, to the formation of chronic morphine (repeat dosing of morphine) withdrawal memory using conditioned place aversion (CPA) and chemogenetic methods. We conducted experiments involving the inhibition of the BLA during naloxone-induced withdrawal to assess its impact on CPA scores, providing insights into the significance of the BLA in the chronic morphine memory formation process. We also examined changes in C1ql3/C1QL3 expression within the BLA following conditioning. Immunofluorescence analysis was employed to reveal the co-localization of C1QL3 and the G-protein coupled receptor, brain-specific angiogenesis inhibitor 3 (BAI3) in the BLA, supporting their involvement in synaptic development. Moreover, we downregulated C1QL3 expression in the BLA to investigate its role in chronic morphine withdrawal memory formation. Our findings revealed that BLA inhibition during naloxone-induced withdrawal led to a significant reduction in CPA scores, confirming the critical role of the BLA in this memory process. Additionally, an upregulation of C1ql3 expression within the BLA post-conditioning suggested its participation in withdrawal memory formation. Co-localization of C1QL3 and BAI3 in the BLA further supported their involvement in synaptic development. Furthermore, downregulation of C1QL3 in BLA effectively hindered chronic morphine withdrawal memory formation, emphasizing its pivotal role in this process. Notably, we identified postsynaptic density protein 95 (PSD95) as a potential downstream effector of C1QL3 during chronic morphine withdrawal memory formation. Blocking PSD95 led to a significant reduction in CPA scores, and it appeared that C1QL3 modulated the ubiquitination degradation of PSD95, resulting in decreased PSD95 protein levels. This study underscores the importance of the BLA, C1QL3 and PSD95 in chronic morphine withdrawal memory formation. It provides valuable insights into the underlying molecular mechanisms, emphasizing their significance in this intricate process.

The well-being equation: How inner fulfilment drives the impact of older persons on the Ghanaian society.

Understanding and managing the complex processes of ageing is a critical function of gerontological nursing, especially when it comes to older people's well-being and their contributions to society. Globally, older persons contribute in many ways to families and communities. However, the relationship between older person's overall well-being and their propensity to contribute to society remains an important gap in research. The study examined the association between well-being and the impact of older persons on Ghanaian society. A secondary analysis of longitudinal survey data of the 2014/15 Study on Global Ageing and Adult Health (SAGE Wave 2) conducted by the World Health Organization was used. The multilevel logistic regression technique was used to examine four dimensions of well-being and their associations with high social contribution among older persons. The output was reported as odds ratios (OR). The results show that older persons who had high physical and psychological well-being were more likely to contribute to society (OR = 1.25, 95% CI = 0.93, 1.68), (OR = 1.75, 95% CI = 1.32, 2.33). However, those with high levels of emotional and spiritual well-being were less likely to make social contributions (OR = 0.66, 95% CI = 0.49, 0.88), (OR = 0.88, 95% CI = 0.66, 1.18). This study shows a positive association between well-being and older persons' societal impact. Good mental and physical health encourage societal involvement among older persons, while high emotional and spiritual well-being may lead to less societal contribution. These findings are important for nursing policies promoting social contribution and well-being among older persons 60 years and over in Ghana.

G-quadruplex forming motifs in the promoter region of the B-MYB proto-oncogene

To combat cancer, a comprehensive understanding of the molecular mechanisms and behaviors involved in carcinogenesis is crucial, as tumorigenesis is a complex process influenced by various genetic events and disease hallmarks. The B-MYB gene encodes a transcription factor involved in cell cycle regulation, survival, and differentiation in normal cells. B-MYB can be transformed into an oncogene through mutations, and abnormal expression of B-MYB has been identified in various cancers, including lung cancer, and is associated with poor prognosis. Targeting this oncogene is a promising approach for anti-cancer drug design. B-MYB has been deemed undruggable in previous reports, necessitating the search for novel therapeutic options. In this study, we found that the B-MYB gene promoter contains several G/C rich motifs compatible with G-quadruplex (G4) formation. We investigated and validated the existence of G4 structures in the promoter region of B-MYB, first in vitro using a combination of bioinformatics, biophysical, and biochemical methods, then in cell with the recently developed G4access method.

Evaluating the role of city representation in modelling the urban precipitation effect of Kuala Lumpur

Urbanization of Earth's land surface is one of the most impactful human interactions on the global ecosystem. Urban land cover substantially alters the transfer of heat, moisture, momentum, and aerosols between the surface and the atmosphere. These surface modifications are the first link in a complex process sequence that causes changes in clouds and precipitation, the so-called urban precipitation effect. Most studies on this topic to date have assumed a homogeneous representation of the city landscape, disregarding the potential effect of its heterogeneity on precipitation. We investigated the impact of Kuala Lumpur's urban precipitation effect through a set of sensitivity studies performed with the Weather Research and Forecasting model, in which different representations of the urban landscape were considered. We showed that including Kuala Lumpur city in the simulations causes a localised increase in accumulated rainfall, rainy day frequency and total extreme rainfall within the boundaries of the urban area. This effect is more pronounced when the city is represented as a homogeneous, high-density landscape compared to the more realistic heterogeneous case, where spatially varying urban canopy parameters are included in the model. Therefore, accurately representing urban areas in climate models is necessary to better estimate the urban precipitation effect.

Rhodesian Readmission and the Decolonization of the National Olympic Committee of Zimbabwe

Abstract In May 1980, the International Olympic Committee (IOC) recognized the National Olympic Committee of Zimbabwe (ZOC) after the latter had spent five years in exile under its former name, the National Olympic Committee of Rhodesia (ROC). Robert Mugabe's Zimbabwean government's desire to have a team compete at the 1980 Moscow Olympics delayed the multiracial restructuring of the ZOC. The government's efforts to reform the ZOC, replacing the old white ROC members, transformed into a two-year-long contentious struggle. After an intervention by the IOC in June 1982, a compromise was reached. The composition of the new ZOC represented the government's greater control over sport in the country. The reformation of the ZOC demonstrates the complex process of transition from Rhodesia to Zimbabwe and the difficulties of decolonization in sport. In examining these events, this article bridges the gap between colonial Rhodesian and postcolonial Zimbabwean sport and presents a case study of decolonization within a sports administration.

Quality Prediction Modeling for Industrial Processes Using Multiscale Attention-Based Convolutional Neural Network.

Soft sensors have been increasingly applied for quality prediction in complex industrial processes, which often have different scales of topology and highly coupled spatiotemporal features. However, the existing soft sensing models usually face difficulties in extracting the multiscale local spatiotemporal features in multicoupled complex process data and harnessing them to their full potential to improve the prediction performance. Therefore, a multiscale attention-based CNN (MSACNN) is proposed in this article to alleviate such problems. In MSACNN, convolutional kernels of different sizes are first designed in parallel in the convolutional layers, which can generate feature maps containing local spatiotemporal features at different scales. Meanwhile, a channel-wise attention mechanism is designed on the feature maps in parallel to get their attention weights, representing the significance of the local spatiotemporal feature at different scales. The superiority of the proposed MSACNN over the other state-of-the-art methods is validated through the performance evaluation in two real industrial processes.

A Morphological Assessment On The Effects Of Embankments On Sediment Transport In Sandy Estuaries

Many large estuaries around the world are engineered to some degree for both flood protection of coastal communities and maintenance of economically vital shipping routes. Engineering challenges arise due to the highly dynamic morphological nature of estuaries, where the complex processes of sediment transport are driven by an interplay between the turbulent flows of rivers and tides. Naturally, the planforms of sandy estuaries have the tendency to converge landwards exponentially, where deviations from this shape provide alternating space and constrictions where tidal sandbars and channels form (Leuven et al., 2018-a; 2018-b). In the case of embankment by bank protection and dikes, such topographically forced channels can develop deep scour holes that endanger bank stability. Our objective is to study effects of channel and planform dynamics on scour depth variation near protected banks. To this end, we conducted scale experiments of estuaries with completely fixed banks in the tilting tidal flume the Metronome (Kleinhans et al., 2017). We study the effects of these fixed banks on the morphological behaviour of the channel pattern through one experiment, two repeat experiments, and a control without fixed banks. By collection of much longer timeseries than available in nature, we use the experiments to shed light on the topographic forcing and channel dynamics of these systems, and on the repeatability of Metronome experiments.

Numerical simulation of surface roughness effects on low-cycle fatigue properties of additively manufactured titanium alloys

Additive manufacturing (AM) is a complex process involving a multiscal physical phenomena (solid–liquid-gas), often resulting in poor surface quality. Although surface treatments such as polishing or chemical treatment can improve surface quality, localized sub-grain stress concentrations induced by surface roughness anomalies are still easily formed, which can lead to the reduction and dispersion of fatigue properties in AM alloys. In this study, a numerical simulation model is proposed to study the association between surface roughness and fatigue properties of AM alloys. Based on the continuum damage mechanics modeling framework, an idealised grain/grain boundary model is generated by employing the Voronoi tessellation meshing technology. The numerical simulations are performed for the model with different surface geometric states. The correlation between surface roughness geometric features and fatigue properties is analyzed and discussed. A parameter “G” which comprehensively considers the influence of the maximum surface height (Rz) and correlation length (Lcor) is proposed to quantify the influence of surface roughness geometric features on the fatigue properties of AM alloys. This finding can be of great significance in improving the surface integrity of components to increase service life.

Generalized extended Bonferroni means for isomorphic membership grades

The generalized extended Bonferroni mean (GEBM) is a powerful tool for modeling the complex process of aggregating information, whether it is homogeneously or heterogeneously connected, within a composite aggregation structure. It maintains several favorable characteristics and effectively captures the diverse and interconnected nature of expert opinions or criteria, which is commonly observed in various decision-making contexts. This research expands upon the existing GEBM framework by applying it to the specific domains of q-rung orthopair fuzzy sets (q-ROFSs) and extended q-rung orthopair fuzzy sets (Eq-ROFSs). Furthermore, it examines the transformation processes among different variants of GEBMs. To facilitate the development of generalized aggregation functions, the de Morgan triplet for q-ROFSs and Eq-ROFSs are established. By introducing an isomorphism, the transformation relationship between the aggregation functions for q-ROFSs and Eq-ROFSs is analyzed. Based on this foundation, the Bonferroni mean de Morgan triplet-based GEBMs for q-ROFSs and Eq-ROFSs are proposed, and the keeping-order relations for these proposed GEBMs are discussed. Finally, several special cases of the GEBMs for q-ROFSs and Eq-ROFSs are obtained, and several relevant theorems are verified.

Distinct types of selection and genetic architecture shape molecular variation during the domestication of vegetable crops.

Humans select vegetable crops with desirable traits via a complex evolutionary process called domestication, generating a variety of cultivars worldwide. With advances in sequencing technologies, genomic scans for "signatures of selection" are widely used to identify target loci of selection. In the early phases of domestication, humans tended to favor similar sets of phenotypes in diverse crops, resulting in "domestication syndrome" and parallel evolution in multiple species. Subsequently, adaptation to distinct environments or different consumer preferences have diversified crop cultivars. Here, we review molecular and population genetic studies on genes affecting trait evolution during this complex process. We emphasize that, depending on interactions among different types of selection (directional selection within or divergent selection between groups), the genetic architecture of the target trait (Mendelian or polygenic), and the origin of the causal variant (new mutation or standing variation), the resulting molecular patterns of variation can be highly diverse. Situations in which the typical hard selective sweep model could be applied may be limited. Therefore, it is crucial to obtain a thorough understanding of the target species' historical, environmental, and ecological contexts.

Sustaining e-health innovations in a complex hospital environment: learning through evidence.

Implementing and sustaining technological innovations in healthcare is a complex process. Commonly, innovations are abandoned due to unsuccessful attempts to sustain and scale-up post implementation. Limited information is available on what characterizes successful e-health innovations and the enabling factors that can lead to their sustainability in complex hospital environments. We present a successful implementation, sustainability and scale-up of a virtual care program consisting of three e-health applications (telemedicine, telehome monitoring, and interactive voice response) in a major cardiac care hospital in Canada. We describe their evolution and adaptation over time, present the innovative approach for their "business case" and funding that supported their implementation, and identify key factors that enabled their sustainability and success, which may inform future research and serve as a benchmark for other health care organizations. Despite resource constraints, e-health innovations can be deployed and successfully sustained in complex healthcare settings contingent key considerations: simplifying technology to make it intuitive for patients; providing significant value proposition that is research supported to influence policy changes; involving early supporters of adoption from administrative and clinical staff; engaging patients throughout the innovation cycle; and partnering with industry/technology providers.

An approach for assessing the functional vulnerabilities criticality of CPS components

Timely identification of critical security flaws in a cyber-physical system makes identifying risks and potential threats possible. To address this issue, threat models are created to better understand potential vulnerabilities that must be considered to ensure system reliability. Selecting the optimal solution for assessing the functional vulnerabilities criticality of cyber-physical system components is a complex process since all vulnerabilities must be identified, classified, and quantified according to a unified approach as part of the cybersecurity process. An effective tool for cyber-physical systems analysis is the Bayesian attack graph. Each path in the graph represents a sequence of attacks that an attacker can use to achieve a specific goal, such as gaining access to sensitive data or controlling a system. This paper proposes a quantitative method for assessing the vulnerability criticality of cyber-physical system components based on the Promethee II multi-criteria decision-making method. It allows ranking and identification of the system's most vulnerable components. The proposed approach is evaluated using a threat model and three scenarios of cyberattacks on a cyber-physical system. Comparison with TOPSIS, VIKOR, and ELECTRE methods proves the effectiveness of the proposed approach. The proposed approach can help technical specialists make more reasoned decisions when ranking critical vulnerabilities of cyber-physical system components to provide security measures and prevent cyberattacks.

Immobilization of a novel d-allulose 3-epimerase from Bacillus cihuensis within metal-organic frameworks

As a functional low-calorie sugar, d-allulose demonstrates significant potential for applications in the food industry. Ketose 3-epimerases (KE) catalyzing the epimerization of d-fructose into d-allulose, play a critical role in the production of d-allulose. Majority of the reported KE exhibited maximum activity at high temperatures (60–70 °C) and pH (7.5–8.0) with metal ions (Mn2+ or Co2+), resulting in browning reaction and complex processes (adjusting pH of fructose solution, removing heavy metal ions, etc.) in allulose production. In this study, a novel d-allulose 3-epimerase from B. cihuensis (BcDAE) was identified and characterized. The BcDAE showed maximum activity at 40–50 °C and pH 7.0, alongside exhibiting board pH tolerance in weakly acidic environments. As a mesophilic enzyme, BcDAE could provide advantages by mitigating browning reactions of substrate and product, minimizing by-product formation, and reducing energy consumption during production. Robustness in acidic environments of BcDAE might renders the enzyme well-suited for fructose conversion without pH adjustments. Considering the poor thermostability and dependence on Mn2+ of BcDAE, the enzyme was captured in Mn-BTC MOF material using a straightforward co-precipitation method. The MOF-based enzyme was subsequently encapsulated to form micrometer-sized immobilized enzyme PDA@BcDAE@Mn-BTC using polydopamine as the cross-linker. Metal ions are not required in the reaction using the immobilized BcDAE. Significantly, after 10 repeated usage cycles, the immobilized BcDAE maintained a relative enzyme activity exceeding 70%, surpassing the performance of other reported immobilized DAE within MOF. Furthermore, comprehensive characterization of the immobilized BcDAE confirmed the success and feasibility of the immobilization strategy.

The association between the years and modes of sports training and levels of moral competence across eleven sports

Background and Study Aim. Research on moral competency in sports is rare, and findings are inconsistent. These findings point to moral development as a multifaceted and complex process. This process is mediated by various life situations and dilemma choices. Sport can play a crucial role in this area with its often ‘role-taking’ experience and confrontations with personal moral standards. This study aimed to analyze the relationship of competency levels and sport experience across different sports. Material and Methods. A sample of university students in sport-related faculties (N = 947) was assessed with the use of Moral Competence test (MCT). The group was divided into 11 predetermined types of sports, training modes (amateur/professional), and indicated years of training practice. Results. The general moral competency level in the overall researched sample of students was low, but similar to their peer-age reference groups found in relevant literature. The findings indicated some differences in moral competency levels between amateurs and professionals. Amateurs showed a higher competency levels in five types of sports (non-invasion games, martial arts/fighting sports, aquatic boating sports). In contrast, professionals showed a higher competency level in dance sports. The only positive, moderate correlation between years of training and moral competency level was found with professional athletes in aquatic boating sports: the longer they trained, the higher their moral competency level was. Conclusions. These results offer new insight into the impact of sports on moral development and can act as a solid foundation for further in-depth research in this area.

Cerebral blood flow regulation in hypobaric hypoxia: role of haemoconcentration.

During acute hypoxic exposure, cerebral blood flow (CBF) increases to compensate for the reduced arterial oxygen content (CaO2). Nevertheless, as exposure extends, both CaO2 and CBF progressively normalize. Haemoconcentration is the primary mechanism underlying the CaO2 restoration and may therefore explain, at least in part, the CBF normalization. Accordingly, we tested the hypothesis that reversing the haemoconcentration associated with extended hypoxic exposure returns CBF towards the values observed in acute hypoxia. Twenty-three healthy lowlanders (12 females) completed two identical 4-day sojourns in a hypobaric chamber, one in normoxia (NX) and one in hypobaric hypoxia (HH, 3500m). CBF was measured by ultrasound after 1, 6, 12, 48 and 96h and compared between sojourns to assess the time course of changes in CBF. In addition, CBF was measured at the end of the HH sojourn after hypervolaemic haemodilution. Compared with NX, CBF was increased in HH after 1h (P=0.001) but similar at all later time points (all P>0.199). Haemoglobin concentration was higher in HH than NX from 12h to 96h (all P<0.001). While haemodilution reduced haemoglobin concentration from 14.8 ± 1.0 to 13.9 ± 1.2g·dl-1 (P<0.001), it did not increase CBF (974 ± 282 to 872 ± 200ml·min-1; P=0.135). We thus conclude that, at least at this moderate altitude, haemoconcentration is not the primary mechanism underlying CBF normalization with acclimatization. These data ostensibly reflect the fact that CBF regulation at high altitude is a complex process that integrates physiological variables beyond CaO2. KEY POINTS: Acute hypoxia causes an increase in cerebral blood flow (CBF). However, as exposure extends, CBF progressively normalizes. We investigated whether hypoxia-induced haemoconcentration contributes to the normalization of CBF during extended hypoxia. Following 4 days of hypobaric hypoxic exposure (corresponding to 3500m altitude), we measured CBF before and after abolishing hypoxia-induced haemoconcentration by hypervolaemic haemodilution. Contrary to our hypothesis, the haemodilution did not increase CBF in hypoxia. Our findings do not support haemoconcentration as a stimulus for the CBF normalization during extended hypoxia.

Restoration manager: Adapting project delivery methods for the restoration of architectural heritage

The restoration of architectural heritage is a complex process and presents intricate and formidable challenges. The project delivery method plays a pivotal role for the success of the restoration process. There exists a diverse array of project delivery methods, each characterized by its distinct set of advantages and disadvantages. In the context of architectural heritage restoration, given its distinct characteristics, these advantages and disadvantages encompass a wide spectrum. Current project delivery methods, while effective for certain contexts, often fall short in addressing the unique requisites of restoration projects. Acknowledging this inadequacy, this article undertakes a research that includes a literature review that not only examines prevailing project delivery methods but also articulates the need for a tailored framework within the restoration field. This article is produced from the doctoral thesis titled "Development of a Sustainable Integrated Management System for the Conservation of Architectural Heritage", which is in the process of preparation. In the light of the results of the survey which is conducted within the scope of the first author's doctoral study in order to examine the project delivery approach preferred among the participants that are working in the field of the conservation of architectural heritage, a project delivery method called "Restoration Manager", which has been precisely prepared to meet the requirements inherent in restoration initiatives, is presented. This comprehensive project delivery method seeks to fill the void by addressing the distinct needs and challenges encountered in restoration projects. The essence of this work is to create an appropriate project delivery system that adapts to the nuances of the restoration works, and through this project delivery framework, the restoration processes and outcomes will successfully be completed.

Students' ‘Looking Back’ in Solving Algebraic Word Problems

Solving mathematics problems is a complex cognitive process that involves a series of steps. These steps typically include understanding the problem, devising a plan, carrying out the plan, and looking back (checking the solution). While each of these steps is crucial, the ‘looking back’ step has not received much attention in mathematics education research. This study investigated Grade 10 mathematics students’ looking back in solving algebraic word problems in Namibia. The study followed a qualitative approach. The sample of the study was 351 Grade 10 students from ten secondary schools in the Ohangwena Region in Namibia. Data was collected using the Algebra Word problem-solving Achievement Test and Interview. The results show that, in general, the students did not look back on their solutions to the algebraic word problem. While some students indicated that looking back necessitates the consolidation of their work, others said looking back on their solutions could be time-wasting and confusing. These findings point to the need for mathematics teachers in Namibia to incorporate and model the looking-back step of mathematical problem-solving in their mathematics teaching.

Estimating Solar Energy within the scope of environmental factors by the Neural Network algorithm

The efficiency of solar energy systems requires a complicated forecasting process due to the variability of sunlight and environmental conditions. Among environmental factors, cloud coverage (% range), temperature (0C), wind speed (Mph), and humidity (%) variables were taken into account in this study. Neural networks (NN), which are machine learning (ML) algorithms with a flexible structure that can define complex relationships and process large amounts of data for solar energy prediction, were used in this study. The NN algorithm showed a high performance, with mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), and R-squared (R2) values calculated as 0.019, 0.139, 0.053, and 0.977, respectively. This study emphasized that solar energy predictions made with the NN algorithm, considering environmental factors, are an essential tool that helps use solar energy systems more efficiently and sustainably.