Deep learning-based models have achieved impressive results across various practical fields. However, these models are susceptible to attacks. Recent research has demonstrated that adversarial samples can significantly decrease the accuracy of deep learning models. This susceptibility poses considerable challenges for their use in security applications. Various methods have been developed to enhance model robustness by training with more effective and generalized adversarial examples. However, these approaches tend to compromise model accuracy. Currently proposed detection methods mainly focus on speech adversarial samples generated by specified white-box attack models. In this study, leveraging manifold learning technology, a method is proposed to detect whether a speech input is an adversarial sample before feeding it into the recognition model. The method is designed to detect speech adversarial samples generated by black-box attack models and achieves a detection success rate of 84.73%. It identifies the low-dimensional manifold of training samples and measures the distance of a sample under investigation to this manifold to determine its adversarial nature. This technique enables the preprocessing detection of adversarial audio samples before their introduction into the deep learning model, thereby preventing adversarial attacks without affecting model robustness. Full article

The retinoblastoma (RB) transcriptional corepressor 1 (RB1) is a critical tumor suppressor gene, governing diverse cellular processes implicated in cancer biology. Dysregulation or deletion in RB1 contributes to the development and progression of various cancers, making it a prime target for therapeutic intervention. RB1′s canonical function in cell cycle control and DNA repair mechanisms underscores its significance in restraining aberrant cell growth and maintaining genomic stability. Understanding the complex interplay between RB1 and cellular pathways is beneficial to fully elucidate its tumor-suppressive role across different cancer types and for therapeutic development. As a result, investigating vulnerabilities arising from RB1 deletion-associated mechanisms offers promising avenues for targeted therapy. Recently, several findings highlighted multiple methods as a promising strategy for combating tumor growth driven by RB1 loss, offering potential clinical benefits in various cancer types. This review summarizes the multifaceted role of RB1 in cancer biology and its implications for targeted therapy. Full article

Coronavirus disease 2019 (COVID-19) has affected medical practice. More than 7,000,000 patients died worldwide after being infected with COVID-19; however, no specific laboratory markers have yet been established to predict death related to this disease. In contrast, electrocardiographic changes due to COVID-19 include QT prolongation and ST-T changes; however, there have not been studies on the ambulatory electrocardiographic markers of COVID-19. We encountered three patients diagnosed as having COVID-19 who did not have a prior history of significant structural heart diseases. All patients had abnormalities in ambulatory echocardiogram parameters detected by high-resolution 24 h electrocardiogram monitoring: positive late potentials (LPs) and T-wave alternans (TWA), abnormal heart rate variability (HRV), and heart rate turbulence (HRT). Case 1 involved a 78-year-old woman with a history of chronic kidney disease, Case 2 involved a 76-year-old man with hypertension and diabetes, and Case 3 involved a 67-year-old man with renal cancer, lung cancer, and diabetes. None of them had a prior history of significant structural heart disease. Although no significant consistent increases in clinical markers were observed, all three patients died, mainly because of respiratory failure with mild heart failure. The LP, TWA, HRV, and HRT were positive in all three cases with no significant structural cardiac disease at the initial phase of admission. The further accumulation of data regarding ambulatory electrocardiographic markers in patients with COVID-19 is needed. Depending on the accumulation of data, the LP, TWA, HRV, and HRT could be identified as potential risk factors for COVID-19 pneumonia in the early phase of admission. Full article

Per- and polyfluoroalkyl substances (PFASs) are carbon–fluorine compounds with widespread industrial and domestic use, posing potential toxicological risks to humans and ecosystems. Several analytical methods have been developed to assess the occurrence of PFASs in the environment, but a standardized method, applicable to all matrices, is still lacking. This paper reviews the extraction and chromatographic detection methods for PFAS assessment in environmental samples, considering parameters such as the LOD, LOQ, and recoveries. Solid phase extraction (SPE) is commonly used, showing high recovery rates for water, soil, and sediment samples using HBL and WAX polymeric sorbents (85–100% and 93–111.5%, respectively). LC-MS has demonstrated low LODs and LOQs in seawater (0.01–0.08 ng L⁻¹; 0.03–0.24 ng L⁻¹), marine sediment (0.002–0.018 ng g⁻¹; 0.004–0.054 ng g⁻¹), and dust (0.08–0.68 pg g⁻¹; 0.26–2.25 pg g⁻¹), indicating its sensitivity when detecting trace PFAS levels. Evaluating PFASs is crucial for the development of future removal strategies and risk assessments. Potential solutions including the use of PFAS substitutes and innovative adsorption techniques for their adsorption could present promise in reducing their environmental presence. Full article

The separation of Li⁺ and [Bmim]⁺(1-Butyl-3-methylimidazolium) using a cation exchange membrane in an electric field is studied in this work. The effects of the type of cation exchange membrane, current density, total cation concentration, temperature, and anion types on the separation efficiency are investigated. The results indicate that it is feasible to achieve the efficient separation of Li⁺ and [Bmim]⁺ using the selectivity of cation exchange membranes under an electric field. The CIMS membrane (a type of cation exchange membrane produced by ASTOM Corporation) shows obvious selectivity of Li⁺ from [Bmim]⁺. When the current density is 5 mA/cm² and the feed concentrations of Li⁺ and [Bmim]⁺ are 0.3 mol/L and 0.2 mol/L, respectively, the selective transport coefficient of CIMS can reach 5.9 in the first 120 min of the process. The separation efficiency can be effectively improved by reducing the current density and increasing the total cation concentration. Decreasing the feed temperature can slightly improve the separation efficiency. Changing the type of anion in the feed from chloride to acetate has no detectable effect on the separation. Full article

Olive leaf contains plenty of phenolic compounds, among which oleuropein (OP) is the main component and belongs to the group of secoiridoids. Additionally, phenolic compounds such as oleocanthal (OL) and oleacein (OC), which share a structural similarity with OP and two aldehyde groups, are also present in olive leaves. These compounds have been studied for several health benefits, such as anti-cancer and antioxidant effects. However, their impact on the skin remains unknown. Therefore, this study aims to compare the effects of these three compounds on melanogenesis using B16F10 cells and human epidermal cells. Thousands of gene expressions were measured by global gene expression profiling with B16F10 cells. We found that glutaraldehyde compounds derived from olive leaves have a potential effect on the activation of the melanogenesis pathway and inducing differentiation in B16F10 cells. Accordingly, the pro-melanogenesis effect was investigated by means of melanin quantification, mRNA, and protein expression using human epidermal melanocytes (HEM). This study suggests that secoiridoid and its derivates have an impact on skin protection by promoting melanin production in both human and mouse cell lines. Full article

Exploring phytochemicals from ethnomedicinal plants for pharmacological applications is a promising research area. By studying ethnomedicine, researchers can identify plants used for centuries to treat ailments and investigate their phytochemicals. Consequently, phytochemicals can be isolated, characterized, and tested for pharmacological activities, leading to new drug development. This research also helps preserve traditional knowledge and biodiversity. Lithospermum officinale L., found in Eurasia, Argentina (South), Colombia, and the United States, is valued for its medicinal properties, including anti-inflammatory, antioxidant, and antimicrobial effects. The current review emphasizes L. officinale L. as a significant reservoir of bioactive phytochemicals, with alkaloids, quinones, glucosides, phenolics, flavonoids, and lipids identified as the principal metabolites. It also unveils the unexplored potential of this plant for future research endeavors. Continued research on L. officinale L. can unlock its full potential, providing insights into its medicinal uses and contributing to biodiversity preservation. Full article

Background: The impaction of the maxillary canine is a common occurrence, and orthodontists must be prepared to manage it. The purpose of this article is to present a study of the efficacy of a double-wire orthodontic appliance compared to a control group in the alignment of impacted maxillary canines in the dental arch. Methods: To diagnose an impacted maxillary canine, a panoramic radiograph was taken and a detailed analysis was performed by the same orthodontist. This article presents the results of 28 impacted maxillary canines with inclusion criteria of A2 (tooth angulation to the midline 16°–45°), V1 (vertical height of the tooth crown above the cementoenamel junction but less than half the length of the root of the maxillary lateral incisor), and O3 (medial position of the canine crown of more than half but less than the entire root width of the lateral incisor) positions in 21 patients (7 males and 14 females) with a mean age of 14.02 years (SD = 1.61) who were treated by the same orthodontist for impacted maxillary canines using a fixed double-wire orthodontic appliance. The analyzed data were compared with the control group (treated with a fixed orthodontic appliance and active ligature), which was matched for pretreatment age and the A2, V1, and O3 positions of the impacted maxillary canine. Results: With both methods, the impacted maxillary canines were aligned and guided into a correct position in the dental arch, but the mean active orthodontic traction of 31 ± 4.2 weeks in the SG was statistically significantly shorter (p < 0.05) in comparison to 37 ± 6.3 weeks in the CG, and the number of visits was statistically significantly (p < 0.05) fewer in the SG (5 ± 2) than in the CG (11 ± 5). Conclusions: The findings of this study are important to the field of orthodontics and show that the alignment of impacted maxillary canines with A2, V1, and O3 positions can be achieved with both methods, but with the double-wire appliance, the treatment time was shorter and the number of visits was statistically significantly fewer. The results of this study suggest that this approach may be more efficient and cost-effective compared to conventional methods. Full article

Thunderstorms endanger life and infrastructure. The accurate and precise prediction of thunderstorms is therefore helpful to enable protection measures and to reduce the risks. This manuscript presents the latest developments to improve thunderstorm forecasting in the first few hours. This includes the description and discussion of a new Julia-based method (JuliaTSnow) for the temporal extrapolation of thunderstorms and the blending of this method with the numerical weather prediction model (NWP) ICON. The combination of ICON and JuliaTSnow attempts to overcome the limitations associated with the pure extrapolation of observations with atmospheric motion vectors (AMVs) and thus increase the prediction horizon. For the blending, the operational ICON-D2 is used, but also the experimental ICON-RUC, which is implemented with a faster data assimilation update cycle. The blended products are evaluated against lightning data. The critical success index (CSI) for the blended RUC product is higher for all forecast time steps. This is mainly due to the higher resolution of the AMVs (prediction hours 0–2) and the rapid update cycle of ICON-RUC (prediction hours 2–6). The results demonstrate the potential of the rapid update cycle to improve the short-term forecasts of thunderstorms. Moreover, the transition between AMV-driven nowcasting to NWP is much smoother in the blended RUC product, which points to the advantages of fast data assimilation for seamless predictions. The CSI is well above the critical value of 0.5 for the 0–2 h forecasts. Values below 0.5 mean that the number of hits (correct informations) is lower than the number of failures, which results from the missed cells plus false alarms. The product is then no longer useful in forecasting thunderstorms with a spatial accuracy of 0.3 degrees. Unfortunately, with RUC, the CSI also drops below 0.5 when the last forecast is more than 3 h away from the last data assimilation, indicating the lack of model physics to accurately predict thunderstorms. This lack is simply a result of chaos theory. Within this context, the role of NWP in comparison with artificial intelligence (AI) is discussed, and it is concluded that AI could replace physical short-term forecasts in the near future. Full article

Horizontal wells within the roof are an effective method to develop gas in broken and soft coal seams, and layer-penetrating fracturing is a key engineering method for the stimulating of horizontal wells within the roof of a coal seam. To understand the propagation law of fracture in the composite roof of coal seams, this study conducted research using numerical simulation and physical similarity simulation methods. Furthermore, engineering experiments were carried out at the Panxie coal mine in the Huainan Mining Area and the Luling coal mine in Huaibei Mining Area, to further validate this technology. The numerical simulation results indicated that fracture within the coal seam roof can propagate from the roof to the target coal seam, effectively fracturing the coal seam. Due to the coal seam’s plasticity being greater than that of the roof mudstone, the coal seam forms a broader fracture than the roof. With the increase in pseudo roof mudstone thickness and being under constant fracturing displacement, the energy consumed by the pseudo roof mudstone during fracturing causes a decrease in pore pressure when fracture extends to the coal seam, resulting in a reduction in fracture width. Therefore, the pseudo roof mudstone is an adverse factor for the expansion of hydraulic fracturing. Physical similarity simulation results demonstrated that when horizontal boreholes were arranged within the siltstone of the coal seam roof, were under reasonable vertical distance and high flow rate fracturing via fluid injection conditions, and if the coal seam had a thin pseudo roof mudstone, the fracture could propagate through the direct roof-pseudo roof interface and the pseudo roof-coal seam interface, extending to the lower coal seam. The fracture form was curved and had irregular vertical fractures, indicating that hydraulic fracturing can achieve production enhancement and the transformation of soft and hard coal seams. However, when the coal seam had a thick pseudo roof mudstone, the mudstone posed strong resistance to hydraulic fracturing, making it difficult for the fracture to propagate to the lower coal seam. Therefore, the pseudo roof mudstone plays a detrimental role in hydraulic fracturing and the production enhancement of coal seams. The engineering verification conducted at Panxie coal mine and Luling coal mine showed that by utilizing a construction drainage rate of 7.5 cubic meters per minute at Panxie coal mine, the maximum fracture length reached 218.3 m, with a maximum fracture height of 36.8 m. The maximum daily gas production of a single well reached 1450 cubic meters per day, with a total gas extraction volume of 43.62 × 10⁴ cubic meters across 671 days. At Luling coal mine, utilizing a construction drainage rate of 10 cubic meters per minute, the maximum fracture length reached 169.1 m, with a maximum fracture height of 20.5 m. The maximum daily gas production of a single well reached 10,775 cubic meters per day, with a total gas extraction volume of 590 × 10⁴ cubic meters for 1090 days. This indicated that the fracture within the roof of coal seams can penetrate the composite roof of coal seams and extend to the interior of the coal seams, achieving the purpose of transforming fractured and low-permeability coal seams and providing an effective mode of gas extraction. Full article

Although endometriosis is a benign disease, it is associated with cancer-related gene mutations, such as KRAS or PIK3CA. Endometriosis is associated with elevated levels of inflammatory factors that cause severe pain. In a previous study, we demonstrated that KRAS or PIK3CA mutations are associated with the activation of cell proliferation, migration, and invasion in a patient-derived immortalized endometriotic cell line, HMOsisEC10. In this study, we investigated the effects of these mutations on progesterone resistance. Since the HMOsisEC10 had suppressed progesterone receptor (PR) expression, we transduced PR-B to HMOsisEc10 cell lines including KRAS mutant and PIK3CA mutant cell lines. We conducted a migration assay, invasion assay, and MTT assay using dienogest and medroxyprogestrone acetate. All cell lines showed progesterone sensitivity with or without mutations. Regarding inflammatory factors, real-time quantitative RT-PCR revealed that the KRAS mutation cell line exhibited no suppression of Cox-2 and mPGES-1 on progesterone treatment, whereas IL-6, MCP-1, VEGF, and CYP19A1 were significantly suppressed by progesterone in both mutated cell lines. Our results suggest that KRAS mutation and PIK3CA mutation in endometriotic cells may not be associated with progesterone resistance in terms of aggressiveness. However, KRAS mutations may be associated with progesterone resistance in the context of pain. Full article

The uncertainty of surrounding rock parameters varies due to changes in the boundary conditions of the tunnel model, and no suitable method to ensure that the updated parameters of the finite element model (FEM) are applicable throughout the constructional environment. To address this issue, a probabilistic baseline model method was introduced to invert the rock parameters and obtain values suitable for the complete constructional environment. First, the probabilistic statistical theory was applied to statistically analyze the measurement data from tunnels under different constructional environments, which provides insight into the variation in rock parameters. Then, an objective optimization function based on a genetic algorithm (GA) was constructed to optimize the accuracy by minimizing the error between the measurement data and the simulation data. Next, a Kriging model was built that utilized Young’s modulus and cohesion as updated parameters. This approach contributes to overcoming the inefficiency of multi-objective optimization computations. By using the Kriging model, optimal values for the rock parameters were obtained. Finally, the effectiveness and applicability of the proposed method were validated by comparing the measured data with the updated model data under different constructional environments. Full article

This paper introduces a pioneering method for real-time image processing in electronic component assembly, revolutionizing quality control in manufacturing. By promptly capturing images from pick-and-place machines during the interval between component pick-up and mounting, defects are identified and promptly addressed in line. This proactive approach ensures that defective components are rejected before mounting, effectively preventing issues from ever occurring, thus significantly enhancing efficiency and reliability. Leveraging rapid network protocols such as gRPC and orchestration via Kubernetes, in conjunction with C++ programming and TensorFlow, this approach achieves an impressive average turnaround time of less than 5 milli-seconds. Rigorously tested on 20 operational production machines, it not only ensures adherence to IPC-A-610 and IPC-STD-J-001 standards but also optimizes production efficiency and reliability. Full article

Exploring the characteristics of vegetation dynamics and quantitatively analyzing the potential drivers and the strength of their interactions are of great significance to regional ecological environmental protection and sustainable development. Therefore, based on the 2000–2022 MODIS NDVI dataset, supplemented by climatic, topographic, surface cover, and anthropogenic data for the same period, the Sen+Mann–Kendall trend analysis, coefficient of variation, and Hurst exponent were employed to examine the spatial and temporal characteristics and trends of NDVI in Hubei Province, and a partial correlation analysis and geographical detector were used to explore the strength of the influence of driving factors on the spatial differentiation of NDVI in vegetation and the underlying mechanisms of interaction. The results showed that (1) the mean NDVI value of vegetation in Hubei Province was 0.762 over 23 years, with an overall increasing trend and fluctuating upward at a rate of 0.01/10a (p < 0.005); geospatially, there is a pattern of “low east and high west”; the spatial change in NDVI shows a trend of “large-scale improvement in the surrounding hills and mountains and small-scale degradation in the middle plains”; it also presents the spatial fluctuation characteristics of “uniform distribution in general, an obvious difference between urban and rural areas, and a high fluctuation of rivers and reservoirs”, (2) the future trend of NDVI in 70.76% of the region in Hubei Province is likely to maintain the same trend as that of the 2000–2022 period, with 70.78% of the future development being benign and dominated by sustained improvement, and (3) a combination of partial correlation analysis and geographical detector analysis of the drivers of vegetation NDVI change shows that land cover type and soil type are the main drivers; the interactions affecting the distribution and change characteristics of NDVI vegetation all showed two-factor enhancement or nonlinear enhancement relationships. This study contributes to a better understanding of the change mechanisms in vegetation NDVI in Hubei Province, providing support for differentiated ecological protection and project implementation. Full article

Although current policies discourage the use of corporal punishment (CP), its use is still widespread in the US. The objective of this study was to assess the proportion of parents who used CP during the pandemic and identify related risk and protective factors. We analyzed results of a nationwide cross-sectional internet panel survey of 9000 US caregivers who responded in three waves from November 2020 to July 2021. One in six respondents reported having spanked their child in the past week. Spanking was associated with intimate partner violence and the use of multiple discipline strategies and not significantly associated with region or racial self-identification. Parents who spanked sought out more kinds of support, suggesting an opportunity to reduce spanking through more effective parenting resources. Additionally, these results suggest that parents who report using CP may be at risk for concurrent domestic violence. Full article

Community care encompasses inherent risks for both clients and healthcare providers. Maintaining a safe environment for the delivery of care services ensures that any risk of unintentional or intentional personal harm is minimised. The aim of this scoping review is to (a) provide an overview of existing knowledge by summarising the current literature and (b) identify gaps pertaining to understanding and managing environmental risk in community care settings. Guided by the Population/Concept/Context approach and PRISMA guidelines, this paper used two questions to answer how a score-based tool for assessing client suitability in community care is developed and how an environmental screening tool assists with reducing risk to community care workers. Literature searches of CINAHL, PubMed (Medline), Web of Science and PsychINFO databases were conducted between September 2023 and November 2023. We included full text articles published from 2018 to 2023. The following four broad areas were identified as key components in the structure of an environmental screening tool: environmental factors, health factors, socioeconomic factors and cultural factors. The results of this review provide valuable information which can be utilised by care organisations to develop and/or refine tools to ensure the safety and wellbeing of workers within the community care sector. Full article

The application of synthetic biology tools to modulate gene expression to increase yield has been thoroughly demonstrated as an effective and convenient approach in industrial production. In this study, we employed a high-throughput screening strategy to identify a 5′ UTR sequence from the genome of B. subtilis 168. This sequence resulted in a 5.8-fold increase in the expression level of EGFP. By utilizing the 5′ UTR sequence to overexpress individual genes within the rib operon, it was determined that the genes ribD and ribAB serve as rate-limiting enzymes in the riboflavin synthesis pathway. Constructing a 5′ UTR library to regulate EGFP expression resulted in a variation range in gene expression levels exceeding 100-fold. Employing the same 5′ UTR library to regulate the expression of EGFP and mCherry within the operon led to a change in the expression ratio of these two genes by over 10,000-fold. So, employing a 5′ UTR library to modulate the expression of the rib operon gene and construct a synthetic rib operon resulted in a 2.09-fold increase in riboflavin production. These results indicate that the 5′ UTR sequence identified and characterized in this study can serve as a versatile synthetic biology toolkit for achieving complex metabolic network reconstruction. This toolkit can facilitate the fine-tuning of gene expression to produce target products. Full article

Platelets are the terminal progeny of megakaryocytes, primarily produced in the bone marrow, and play critical roles in blood homeostasis, clotting, and wound healing. Traditionally, megakaryocytes and platelets are thought to arise from multipotent hematopoietic stem cells (HSCs) via multiple discrete progenitor populations with successive, lineage-restricting differentiation steps. However, this view has recently been challenged by studies suggesting that (1) some HSC clones are biased and/or restricted to the platelet lineage, (2) not all platelet generation follows the “canonical” megakaryocytic differentiation path of hematopoiesis, and (3) platelet output is the default program of steady-state hematopoiesis. Here, we specifically investigate the evidence that in vivo lineage tracing studies provide for the route(s) of platelet generation and investigate the involvement of various intermediate progenitor cell populations. We further identify the challenges that need to be overcome that are required to determine the presence, role, and kinetics of these possible alternate pathways. Full article

Deep neural networks (DNNs) have gained prominence in various applications, but remain vulnerable to adversarial attacks that manipulate data to mislead a DNN. This paper aims to challenge the efficacy and transferability of two contemporary defense mechanisms against adversarial attacks: (a) robust training and (b) adversarial training. The former suggests that training a DNN on a data set consisting solely of robust features should produce a model resistant to adversarial attacks. The latter creates an adversarially trained model that learns to minimise an expected training loss over a distribution of bounded adversarial perturbations. We reveal a significant lack in the transferability of these defense mechanisms and provide insight into the potential dangers posed by $L_{\infty }$-norm attacks previously underestimated by the research community. Such conclusions are based on extensive experiments involving (1) different model architectures, (2) the use of canonical correlation analysis, (3) visual and quantitative analysis of the neural network’s latent representations, (4) an analysis of networks’ decision boundaries and (5) the use of equivalence of $L_2$ and $L_{\infty }$ perturbation norm theories. Full article

Despite fast electrification in India, many communities still suffer from the direct and indirect effects of energy poverty. We investigate whether access to liquified petroleum gas (LPG) and consumption expenditure can be used as measures of energy poverty in India, with a particular focus on gender equality. A district-level, quantitative analysis of household survey data was performed for the energy-poor states of Bihar, Jharkhand, Madhya Pradesh, Odisha, Uttar Pradesh, and West Bengal. Wellbeing and gender equality indices were constructed from contextually relevant indicators, whilst LPG access was considered in terms of physical access, affordability, and awareness. Levels of consumption expenditure were considered based on the updated urban poverty line for India. We found that LPG access and consumption expenditure do not have a significant relationship with wellbeing or gender equality. The result indicates that the traditional economic approach of using consumption expenditure cannot capture the multidimensionality of energy poverty. This has significant implications as it challenges the status quo of energy poverty measurement. The research also adds value to existing arguments that electricity access cannot be used as a sole indicator of energy poverty, by extending the argument to access to a modern cooking fuel. LPG access was, however, strongly associated with the education of women on the health effects of smoke. Consumption expenditure is also strongly associated with female property ownership, which calls for future research on this novel relationship. Full article

Fuzzy multi-attribute decision-making is a hot research topic in which weight information is one of the conditions for forming a complete decision-making model, and it is also an important factor affecting the decision result. In most fuzzy multi-attribute decision-making problems, the weight information is often given in the form of real numbers. However, in real life, the weight information may not be suitable for specific numerical representation, or we cannot accurately determine the weight information. Therefore, it is very important to use fuzzy numbers to represent weight information. In this paper, we study the problem of disturbing fuzzy multi-attribute decision-making in which the attribute weight, decision-maker weight, and attribute information are given in the form of disturbing fuzzy numbers. Firstly, a new disturbing fuzzy integration operator, namely the disturbing fuzzy ring and multiplication aggregation (DFRMA) operator, is proposed, and its characteristics of closure, monotonicity, and boundary are studied. Then, the general steps of the disturbing fuzzy multi-attribute decision method based on the disturbing fuzzy ring and multiplication aggregation (DFRMA) operator are given, which include the single decision step and group decision step. Finally, an example is given to illustrate the practicability and effectiveness of the method. Full article