Processing Demands Research Articles

Environmentally sustainable inventory control for perishable products: A bi-objective reorder-level policy

In order to improve sustainability and transparency in the decision making for inventory control, this paper presents a reorder-level model that considers product perishability. Conversely to most inventory control policies, the classical economic perspective is paired with an environmental one for a stochastic bi-objective optimization approach to reduce inventory logistics emissions and costs. In order to contrast stockouts, lost-sale costing and a service level constraint are integrated for a more comprehensive approach. Results show how the two objectives may be in contrast, and how Pareto-efficient solutions can help to analyze and select the proper trade-offs during decision making. Experiments indicate, for a case-study application, how the most relevant aspects affecting system performance are product shelf life and the possible need of temperature control during storage. Moreover, considering multiple sustainability perspectives in inventory management can help businesses consolidate and future-proof their operations, as well as meet environmental standards and customer demand for greener products and processes.

Effect of Some Technological Factors of Extraction on Total Lentinan Content in Sapa Shiitake Mushroom Extract

In Vietnam, the source of shiitake mushroom is very abundant and grown in many provinces/cities, the total yield reaches hundreds of thousands of tons/per year, mainly serving the demand of domestic food processing, and did not develop into medicinal mushrooms yet. Among them, Sapa shiitake mushroom is being widely cultivated in Sapa-Vietnam, and is a raw material with great potential for lentinan exploitation. Until now, researches on extracting and obtaining lentinan in Vietnam are still limited. Those are reasons to carry out this research. The effects of solvent in combination with assistance of ultrasound wave in lentinan extracting capability in Sapa shiitake mushroom were studied. Before carrying out extracting of lentinan; The dried fruit bodies of Sapa shiitake mushroom was crushed in to 1mm. Five extracting parameters include concentration of Na0H solvent (%), proportion of Na0H solvent and raw material (v:w), extracting temperature, ultrasound time and ultrasound intensity were carried out. An extraction without the use of ultrasound for 180 min was control sample. Total lentinan content was obtained during the extracting process. The results indicated that shiitake mushrooms were extracted by using 0.35% Na0H solvent, the rate of Na0H solvent and mushrooms was 12:1 (v:w), intensity of ultrasound was 58 W/cm2, frequency was 20 kHz, extracting temperature was 65 °C, time of extraction was 6 min gave total lentinan content 1.63 times higher than the control.

Strategies to Prepare Chitin and Chitosan-Based Bioactive Structures Aided by Deep Eutectic Solvents: A Review

Chitin and chitosan, abundant biopolymers derived from the shells of crustaceans and the cell walls of fungi, have garnered considerable attention in pharmaceutical circles due to their biocompatibility, biodegradability, and versatile properties. Deep eutectic solvents (DESs), emerging green solvents composed of eutectic mixtures of hydrogen bond acceptors and donors, offer promising avenues for enhancing the solubility and functionality of chitin and chitosan in pharmaceutical formulations. This review delves into the potential of utilizing DESs as solvents for chitin and chitosan, highlighting their efficiency in dissolving these polymers, which facilitates the production of novel drug delivery systems, wound dressings, tissue engineering scaffolds, and antimicrobial agents. The distinctive physicochemical properties of DESs, including low toxicity, low volatility, and adaptable solvation power, enable the customization of chitin and chitosan-based materials to meet specific pharmaceutical requirements. Moreover, the environmentally friendly nature of DESs aligns with the growing demand for sustainable and eco-friendly processes in pharmaceutical manufacturing. This revision underscores recent advances illustrating the promising role of DESs in evolving the pharmaceutical applications of chitin and chitosan, laying the groundwork for the development of innovative drug delivery systems and biomedical materials with enhanced efficacy and safety profiles.

Iron-catalysed nitrene transfer reaction to form C[sbnd]N bonds

Direct CN bond forming reaction by utilizing the non-precious transition metals is an attractive field of research in organic synthesis. Unlike the conventional use of precious metals like rhodium, palladium, ruthenium, and iridium that are commonly used in these reactions, the use of non-precious metals, particularly those are non-toxic and high abundant, holds distinct attention owing to the increasing demand of sustainable chemical processes. Among them, iron catalysis offers notable advantages for sustainable chemical synthesis. Iron-catalysed nitrene transfer reactions have emerged as robust and eco-friendly methods for constructing various valuable CN bonds. In this review, we provide a comprehensive overview of the advancements in iron catalysis for the nitrene transfer reactions aimed at synthesizing diverse CN bonds.

Cu array fabrication: An environmentally sustainable approach through bicontinuous microemulsion differential electrodeposition for advanced power device packaging

BackgroundThe demand for high-power density packaging and integration processes for third-generation semiconductors, like silicon carbide (SiC), necessitates advancements beyond conventional Si-based packaging technologies. Cu-Cu direct bonding emerges as a promising alternative in semiconductor packaging. However, achieving Cu-to-Cu direct bonding with low-temperature, low-pressure, and short-time poses significant challenges. Transient Liquid Phase Bonding (TLP) offers a low-temperature joining solution, but prolonged reflow time hinders its wide applications. MethodsThis study introduces a novel strategy utilizing bicontinuous microemulsion (BME) electrodeposition to fabricate micron-sized Cu arrays, addressing these challenges in achieving Cu bonding. The core of Cu array manufacturing lies in the differential electrodeposition rate of Cu ions in the aqueous and organic phases. This principle is rooted in the excellent conductivity of the aqueous solution compared to the non-conductivity of the organic solution. Significant findingsWe elucidate the growth mechanism and validate a theory for achieving void-free optimal growth of Cu arrays within BME and compared the cross-sectional morphology and fracture modes of TLP solder joints with micron and nano Cu arrays. Furthermore, the ability to recycle the BME soft template aligns with green chemistry principles, offering a sustainable die-attach approach for third-generation semiconductor device packaging.

A high-data-rate hybrid index communication system based on quadrature chaos shift keying

To address the rapidly increasing challenges posed by the demands for large-scale data transmission and processing, this paper proposes a high-data-rate hybrid index modulation communication system based on quadrature chaos shift keying (HR-HIM-QCSK). The system employs a hybrid modulation involving carrier index and slot index. In this approach, three mutually orthogonal reference signals are constructed using Walsh codes. These reference signals are then utilized to create three distinct QCSK signals, distinguishing between the activation modes of carriers and time slots. This design allows all slots to carry QCSK signals, significantly enhancing the data rate of the HR-HIM-QCSK system. Theoretical analysis and simulations conducted under additive white Gaussian noise and multipath Rayleigh fading channels demonstrate that the HR-HIM-QCSK system outperforms other competing systems in terms of bit error rate (BER) performance. Further analysis covers aspects such as data rate, spectral efficiency, complexity and covertness, highlighting the superior performance of the HR-HIM-QCSK system in high-data-rate communication. This study provides valuable insights for the design of efficient chaotic communication systems.

Decreasing Intracellular Entropy by Increasing Mitochondrial Efficiency and Reducing ROS Formation-The Effect on the Ageing Process and Age-Related Damage.

A hypothesis is presented to explain how the ageing process might be influenced by optimizing mitochondrial efficiency to reduce intracellular entropy. Research-based quantifications of entropy are scarce. Non-equilibrium metabolic reactions and compartmentalization were found to contribute most to lowering entropy in the cells. Like the cells, mitochondria are thermodynamically open systems exchanging matter and energy with their surroundings-the rest of the cell. Based on the calculations from cancer cells, glycolysis was reported to produce less entropy than mitochondrial oxidative phosphorylation. However, these estimations depended on the CO2 concentration so that at slightly increased CO2, it was oxidative phosphorylation that produced less entropy. Also, the thermodynamic efficiency of mitochondrial respiratory complexes varies depending on the respiratory state and oxidant/antioxidant balance. Therefore, in spite of long-standing theoretical and practical efforts, more measurements, also in isolated mitochondria, with intact and suboptimal respiration, are needed to resolve the issue. Entropy increases in ageing while mitochondrial efficiency of energy conversion, quality control, and turnover mechanisms deteriorate. Optimally functioning mitochondria are necessary to meet energy demands for cellular defence and repair processes to attenuate ageing. The intuitive approach of simply supplying more metabolic fuels (more nutrients) often has the opposite effect, namely a decrease in energy production in the case of nutrient overload. Excessive nutrient intake and obesity accelerate ageing, while calorie restriction without malnutrition can prolong life. Balanced nutrient intake adapted to needs/activity-based high ATP requirement increases mitochondrial respiratory efficiency and leads to multiple alterations in gene expression and metabolic adaptations. Therefore, rather than overfeeding, it is necessary to fine-tune energy production by optimizing mitochondrial function and reducing oxidative stress; the evidence is discussed in this paper.

Prediction of power consumption and its signals in sustainable turning of PH13-8Mo steel with different machine learning models

Due to extensive distribution and huge demand of energy efficient processes, the energy-saving of machining processes draws more and more attention, and a significant variety of methods have evolved to prognosis or optimise the energy consumption in machining operations. Similarly, the estimation of power consumption-cutting conditions relationships is of great importance for optimizing processing costs and for cleaner machining. Compared to traditional methods, machine learning (ML) approach is one of the effective analysis options to model machinability indicators such as cutting force, tool wear, power consumption and surface quality. In this study, PH13-8Mo stainless steel was machined with coated carbide inserts using primarily Dry, MQL, nano-Graphene + MQL, nano-hBN + MQL, Cryo, Cryo + MQL cutting environments. Power consumption and its signals during milling were measured and different machine learning models were applied to estimate the Pc. To develop the Pc model based on the ML algorithm, 70% of the power consumption data is reserved for training and 30% for testing. In all cutting environments, power consumption increased by an average of 3.14% as feed speed increased. The reduction in Pc compared to the dry cutting was calculated as an average of 2.2%, 3.17%, 2.57%, 4.88% and 5.45% for MQL, nano-Graphen + MQL, nano-hBN + MQL, Cryo, Cryo + MQL, respectively. It is seen that the developed prediction model can reflect the power consumption-parameter relationships at high accuracy.

Towards Energy Efficient Cloud: A Green and Intelligent Migration of Traditional Energy Sources

Geographically distributed cloud data centers (DCs) consume enormous amounts of energy to meet the ever-increasing processing and storage demands of users. The brown energy generated using fossil fuels is expensive and significantly contributes to global warming. Considering the environmental impact caused by the high carbon emissions and relatively high energy cost of brown energy, we propose the integration of renewable energy sources (RES), especially solar and wind energy, with brown energy to power cloud data centers. In our earlier study, we addressed the intermittency of renewable energy sources, where we replaced the random initialization of artificial neural network (ANN) edge weights with the harmony search algorithm (HSA)-optimized assignment of weights. This study incorporated reliably forecast solar and wind energy into the input parameters of our proposed green energy manager (GEM), for cost minimization, carbon emission minimization, and better energy management of cloud DCs, to make our current study more reliable and trustworthy. Four power sources, on-site solar energy and wind energy, off-site solar energy and wind energy, energy stored in energy storage devices, and brown energy, were considered in this study and simulations were carried out for three different cases. The simulation results showed that case 1 (all brown) was 58% more expensive and caused 71% higher carbon emissions than case 2.1 (cost minimization). Case 1 (all brown) was 39% more expensive and had 80% higher carbon emissions than case 2.2 (carbon emission minimization). The simulation results justify the necessity and importance of the GEM, and finally the results proved that our proposed GEM is less expensive and more environmentally friendly.

INTEGRATION OF IOT WITH CLOUD, FOG, AND EDGE COMPUTING: A REVIEW

Purpose of review. The paper provides an in-depth exploration of the integration of Internet of Things (IoT) technologies with cloud, fog, and edge computing paradigms, examining the transformative impact on computational architectures. Approach to review. Beginning with an overview of IoT's evolution and its surge in global adoption, the paper emphasizes the increasing importance of integrating cloud, fog, and edge computing to meet the escalating demands for real-time data processing, low-latency communication, and scalable infrastructure in the IoT ecosystem. The survey meticulously dissects each computing paradigm, highlighting the unique characteristics, advantages, and challenges associated with IoT, cloud computing, edge computing, and fog computing. The discussion delves into the individual strengths and limitations of these technologies, addressing issues such as latency, bandwidth consumption, security, and data privacy. Further, the paper explores the synergies between IoT and cloud computing, recognizing cloud computing as a backend solution for processing vast data streams generated by IoT devices. Review results. Challenges related to unreliable data handling and privacy concerns are acknowledged, emphasizing the need for robust security measures and regulatory frameworks. The integration of edge computing with IoT is investigated, showcasing the symbiotic relationship where edge nodes leverage the residual computing capabilities of IoT devices to provide additional services. The challenges associated with the heterogeneity of edge computing systems are highlighted, and the paper presents research on computational offloading as a strategy to minimize latency in mobile edge computing. Fog computing's intermediary role in enhancing bandwidth, reducing latency, and providing scalability for IoT applications is thoroughly examined. Challenges related to security, authentication, and distributed denial of service in fog computing are acknowledged. The paper also explores innovative algorithms addressing resource management challenges in fog-IoT environments. Conclusions. The survey concludes with insights into the collaborative integration of cloud, fog, and edge computing to form a cohesive computational architecture for IoT. The future perspectives section anticipates the role of 6G technology in unlocking the full potential of IoT, emphasizing applications such as telemedicine, smart cities, and enhanced distance learning. Cybersecurity concerns, energy consumption, and standardization challenges are identified as key areas for future research.

New-Style Logic Operation and Neuromorphic Computing Enabled by Optoelectronic Artificial Synapses in an MXene/Y:HfO2 Ferroelectric Memristor.

Today's computing systems, to meet the enormous demands of information processing, have driven the development of brain-inspired neuromorphic systems. However, there are relatively few optoelectronic devices in most brain-inspired neuromorphic systems that can simultaneously regulate the conductivity through both optical and electrical signals. In this work, the Au/MXene/Y:HfO2/FTO ferroelectric memristor as an optoelectronic artificial synaptic device exhibited both digital and analog resistance switching (RS) behaviors under different voltages with a good switching ratio (>103). Under optoelectronic conditions, optimal weight update parameters and an enhanced algorithm achieved 97.1% recognition accuracy in convolutional neural networks. A new logic gate circuit specifically designed for optoelectronic inputs was established. Furthermore, the device integrates the impact of relative humidity to develop an innovative three-person voting mechanism with a veto power. These results provide a feasible approach for integrating optoelectronic artificial synapses with logic-based computing devices.

Synergistic Solvation as the Enhancement of Local Mixing.

Mixing two solvents can sometimes make a much better solvent than expected from their weighted mean. This phenomenon, called synergistic solvation, has commonly been explained via the Hildebrand and Hansen solubility parameters, yet their inability in other solubilization phenomena, most notably hydrotropy, necessitates an alternative route to elucidating solubilization. While, recently, the universal theory of solubilization was founded on the statistical thermodynamic fluctuation theory (as a generalization of the Kirkwood-Buff theory), its demand for experimental data processing has been a hindrance for its wider application. This can be overcome by the solubility isotherm theory, which is founded on the fluctuation theory yet reduces experimental data processing significantly to the level of isotherm analysis in sorption. The isotherm analysis identifies the driving force of synergistic solvation as the enhancement of solvent mixing around the solute, opposite in behavior to hydrotropy (characterized by the enhancement of demixing or self-association around the solute). Thus, the fluctuation theory, including its solubility isotherms, provides a universal language for solubilization across the historic subcategorization of solubilizers, for which different (and often contradictory) mechanistic models have been proposed.

Рефлексия о технике в социальной мифологии В.Ф. Одоевского: финал романтического механицизма

The article is devoted to the origins of reflection on technology in Russian philosophy and literature from the 19th and 20th centuries. Our focus is on the technical developments and the phenomenon of technology as it appears in the works of the Russian philosopher Vladimir Odoevsky. The appeal to Odoevsky’s ideas is of particular relevance in today’s context of the formation of technological societies and perspectives. It is with the achievements of mechanics and technology that Odoevsky correlates his hopes for the good development of man and society, he connects the enlightenment and education of young people. At the same time, Odoevsky sees the danger lurking in mechanism and rational knowledge. This danger will be the loss of integrity, decay and devastation that will befall the world that has survived the crisis of culture. Turning to the work of the thinker, we trace the trends in reflection on technology from a philosophical position, as well as in unity with the poetic and musical. The theoretical basis of the study is the opposition of Odoevsky’s technical and poetic as vectors of social development. As a result of the analysis, the author of the article comes to an ambivalent assessment of the role of technology by Odoevsky, contrasting the romanticization of technology with the negative prospects of the “industrial”, “egoistic” century, which are further developed in the domestic and foreign philosophy of technology and anti-utopia of the 20th and 21th centuries. In his futuristic projects, Odoevsky discovers the potential of scientific foresight, embodied in the achievements of modern science and technology. The transition in the assessment of technology from idealism to scientific realism and positivism, reasoning of a social orientation (“Russian Nights”, 1844), the key opposition in Odoevsky’s concept of the romanticization of technology to the negative prospects of technical expansion is further developed in the domestic and foreign philosophy of technology of the 20th and 21th centuries. The modern appeal to reflection on technology in Russian philosophy and literature is due to the expansive introduction of technology into the life of society, the rejection of ethical neutrality and the trend towards autonomy, as well as the demand for the modern educational process, university training programs for both humanitarian and technical orientation.

WITHDRAWN: Sustainable practices in entertainment computing

The increasing progression of the entertainment computing industry, covering primarily gaming, streaming, and virtual reality, results in detrimental consequences to the environment in terms of excessive energy demands for information processing and an increased amount of e-waste created by users. Sustainable entertainment computing is thus calling for improved strategies in management of such concerns with green solutions. This research work is aimed at identifying the approaches and tools which can be used to support the idea of sustainable computing in entertainment technology. The critical objective is to propose the use of energy efficient hardware and software and utilization of power in data centres from renewable energy resources. Lifecycle analysis, from production to disposal, is employed to assess and mitigate the environmental impact of both hardware and software. Furthermore, there are green certification and eco-labels on products and services to guarantee that, they are environmentally amenable. The findings suggest that several sustainable initiatives, namely development of energy-efficient hardware, optimized software and energy from renewable sources for data centres can be useful to minimize the entertainment computing sector’s impact on the environment. This paper provides a framework for entertainment technology companies towards more sustainable in their computing practices and therefore, adding to the growing list of organizations that are trying to push the entertainment industry towards a more sustainable future.

Musical Advantage in Lexical Tone Perception Hinges on Musical Instrument

Different musical instruments have different pitch processing demands. However, correlational studies have seldom considered the role of musical instruments in music-to-language transfer. Addressing this research gap could contribute to a nuanced understanding of music-to-language transfer. To this end, we investigated whether pitched musicians had a unique musical advantage in lexical tone perception relative to unpitched musicians and nonmusicians. Specifically, we compared Cantonese pitched musicians, unpitched musicians, and nonmusicians on Thai tone discrimination and sequence recall. In the Thai tone discrimination task, the pitched musicians outperformed the unpitched musicians and the nonmusicians. Moreover, the unpitched musicians and the nonmusicians performed similarly. In the Thai tone sequence recall task, both pitched and unpitched musicians recalled level tone sequences more accurately than the nonmusicians, but the pitched musicians showed the largest musical advantage. However, the three groups recalled contour tone sequences with similar accuracy. Collectively, the pitched musicians had a unique musical advantage in lexical tone discrimination and the largest musical advantage in level tone sequence recall. From a theoretical perspective, this study offers correlational evidence for the Precision element of the OPERA hypothesis. The choice of musical instrumental may matter for music-to-language transfer in lexical tone discrimination and level tone sequence recall.

Benchmarking of industrial wastewater treatment processes using a complex probabilistic hesitant fuzzy soft Schweizer–Sklar prioritized-based framework

The objective of this research work is to effectively handle the intricate and uncertain nature of decision-making in the context of industrial wastewater treatment. The prioritization of wastewater treatment is of utmost importance in order to save the environment, promote human health, ensure adherence to legal regulations, conserve resources, and foster overall sustainability. The demand for efficient and sustainable wastewater treatment processes is increasing globally, but selecting appropriate treatment technologies for industrial effluents is challenging due to its complex nature. Our study aims to provide a systematic framework for evaluating and selecting treatments based on efficacy, affordability, and environmental impact. Aggregation operators are one of the fundamental ideas in the framework of information fusion for addressing real-life problems. Numerous scholars have made significant contributions to the development of aggregation operators specifically designed for multi-parameter decision-making (MPDM) whenever circumstances are characterized by uncertainty. Regrettably, the current operators can only be employed within strict limits and constraints. Therefore, this research formulates novel prioritized aggregation operators that alleviate the restrictive constraints associated with the current operators. After this, we present a new methodology that combines the Schweizer–Sklar prioritized aggregation operators with a complex probabilistic hesitant fuzzy soft framework. For this purpose, we develop the averaging aggregation operators and geometric aggregation operators. Following that, we proceed to examine the theorems and properties associated with them by providing rigorous proofs. Then, we develop a novel decision-making technique with a numerical example based on the wastewater treatment process. Through this novel technique, the best process is the activated sludge process. We perform the validity tests to evaluate the feasibility and effectiveness of MPDM techniques.

Biosynthesis and Biotechnological Synthesis of Hydroxytyrosol.

Hydroxytyrosol (HT), a plant-derived phenolic compound, is recognized for its potent antioxidant capabilities alongside a spectrum of pharmacological benefits, including anti-inflammatory, anti-cancer, anti-bacterial, and anti-viral properties. These attributes have propelled HT into the spotlight as a premier nutraceutical and food additive, heralding a new era in health and wellness applications. Traditional methods for HT production, encompassing physico-chemical techniques and plant extraction, are increasingly being supplanted by biotechnological approaches. These modern methodologies offer several advantages, notably environmental sustainability, safety, and cost-effectiveness, which align with current demands for green and efficient production processes. This review delves into the biosynthetic pathways of HT, highlighting the enzymatic steps involved and the pivotal role of genetic and metabolic engineering in enhancing HT yield. It also surveys the latest progress in the biotechnological synthesis of HT, examining innovative strategies that leverage both genetically modified and non-modified organisms. Furthermore, this review explores the burgeoning potential of HT as a nutraceutical, underscoring its diverse applications and the implications for human health. Through a detailed examination of both the biosynthesis and biotechnological advances in HT production, this review contributes valuable insights to the field, charting a course towards the sustainable and scalable production of this multifaceted compound.

Children's metacognition and cognitive offloading in an immediate memory task.

Cognitive offloading is used to supplement internal processing demands through external actions such as writing down information. While metacognition plays a critical role in adults' cognitive offloading decisions, less is known about the relation between metacognition and cognitive offloading in children. Here, we introduced an immediate memory task to 11- to 12-year-olds under two conditions: no choice to offload and choice to offload. Participants made metacognitive judgements about their memory capacity, and the task performance components such as accuracy and effort. Our results revealed that recall accuracy of the to-be-remembered items increased in the choice condition. Interestingly, while there was a consensus amongst participants that they chose to offload to maximise accuracy and reduce effort, there was no relation between offloading behaviour and metacognitions about accuracy and effort. On the other hand, metacognition for memory capacity was related to offloading behaviour. We discuss the implications for further understanding of the relation between cognitive offloading and metacognition in children.

Spectrum-Dependent Image Convolutional Processing via a Two-Dimensional Polarization-Sensitive Photodetector.

Currently, the improvement in the processing capacity of traditional processors considerably lags behind the demands of real-time image processing caused by the advancement of photodetectors and the widespread deployment of high-definition image sensors. Therefore, achieving real-time image processing at the sensor level has become a prominent research domain in the field of photodetector technology. This goal underscores the need for photodetectors with enhanced multifunctional integration capabilities than can perform real-time computations using optical or electrical signals. In this study, we employ an innovative p-type semiconductor GaTe0.5Se0.5 to construct a polarization-sensitive wide-spectral photodetector. Leveraging the wide-spectral photoresponse, we realize three-band imaging within a wavelength range of 390-810 nm. Furthermore, real-time image convolutional processing is enabled by configuring appropriate convolution kernels based on the polarization-sensitive photocurrents. The innovative design of the polarization-sensitive wide-spectral GaTe0.5Se0.5-based photodetector represents a notable contribution to the domain of real-time image perception and processing.

BDD-persulfate-based anodic oxidation process for progestin degradation: Optimization of conditions, eco-compatibility tests, and cost evaluation

Considering the increasing presence of the hormones levonorgestrel (LNG) and gestodene (GES) in wastewater, the limited effectiveness of conventional treatment methods, and the demand for advanced complementary processes, our study aimed to optimize an anodic oxidation treatment with a focus on low specific energy consumption (SEC) and costs. An electrochemical system coupled to a boron-doped diamond anode (BDD) was continuously used to treat synthetic and real pharmaceutical wastewater from contraceptive production. The central design composite and response surface methodology were the tools employed for optimization. The lowest SEC was obtained as a response to the main process variables: current density, initial pH, and the concentration of the support electrolyte ([Na2S2O8]). The optimal condition ([Na2S2O8]0 = 0.07 mol L−1; [LNG]0,RPW = 1.02±0.05 mg L−1 and [GES]0,RPW = 1.05±0.05 mg L−1; j = 37.5 mA cm−2; pH = 6.75) was established considering an SEC ≤ 3.6 ± 0.8 kWh g−1 and progestins removal ≥70%, which was the experimental condition used to evaluate acute toxicity to Daphnia similis and the effect on estrogenic activity removal using the YES assay. Notably, our study evaluated, for the first time, a comparative investigation that highlights the substantial effect of support electrolytes over the eco-compatibility assessment of the anodic oxidation process investigated. The adaptability of the operation indicates the prospective suitability for the implementation of the process in wastewater treatment facilities in the pharmaceutical industry.