Effective degradation technologies have been extensively investigated and used to remove azo dyes from wastewater for decades. However, no review dealing with both electrooxidation and chemical reduction of azo dyes from an economic and, therefore, application-relevant perspective has been found in the current literature. A novelty of this review article consists not only in the brief summarization and comparison of both methods but mainly in the evaluation of their economic side. Based on the literature survey of the last 15 years, the costs of treatment approaches published in individual research articles have been summarized, and the missing data have been calculated. A broad spectrum of advanced electrode materials and catalysts have been developed and tested for the treatment, specifically aiming to enhance the degradation performance. An outline of the global prices of electrode materials, reducing agents, and basic chemicals is involved. All additional costs are described in depth in this review. The advantages and disadvantages of respective methods are discussed. It was revealed that effective and cheap treatment approaches can be found even in advanced degradation methods. Based on the collected data, electrooxidation methods offer, on average, 30 times cheaper treatment of aqueous solutions. Concerning chemical reduction, only ZVI provided high removal of azo dyes at prices <100 $ per kg of azo dye. The factors affecting total prices should also be considered. Therefore, the basic diagram of the decision-making process is proposed. In the conclusion, challenges, future perspectives, and critical findings are described.

Wastewater textile dye treatment is a challenge that requires the development of eco-friendly technology to avoid the alarming problems associated with water scarcity and health-environment. This study investigated the potential of phengite clay as naturally low-cost abundant clay from Tamgroute, Morocco (TMG) that was activated with a 0.1 M NaOH base (TMGB) after calcination at 850 °C for 3 h (TMGC) before its application in the Congo red (CR) anionic dye from the aqueous solution. The effect of various key operational parameters: adsorbent dose, contact time, dye concentration, pH, temperature, and the effect of salts, was studied by a series of adsorption experiments in a batch system, which affected the adsorption performance of TMG, TMGC, and TMGB for CR dye removal. In addition, the properties of adsorption kinetics, isotherms, and thermodynamics were also studied. Experimental results showed that optimal adsorption occurred at an acidic pH. At a CR concentration of 100 mg L-1, equilibrium elimination rates were 68%, 38%, and 92% for TMG, TMGC, and TMGB, respectively. The adsorption process is rapid, follows pseudo-second-order kinetics, and is best described by a Temkin and Langmuir isotherm. The thermodynamic parameters indicated that the adsorption of CR onto TMGB is endothermic and spontaneous. The experimental values of CR adsorption on TMGB are consistent with the predictions of the response surface methodology. These led to a maximum removal rate of 99.97% under the following conditions: pH = 2, TMGB dose of 7 g L-1, and CR concentration of 50 mg L-1. The adsorbent TMGB\'s relatively low preparation cost of around $2.629 g-1 and its ability to regenerate in more than 6 thermal calcination cycles with a CR removal rate of around 56.98%, stimulate its use for textile effluent treatment on a pilot industrial scale.

OBJECTIVE: Heart failure (HF) is a complex clinical syndrome with high mortality and hospitalization rates. Non-invasive remote patient monitoring (RPM) interventions have the potential to prevent disease worsening. However, the long-term cost-effectiveness of RPM remains unclear. This study aimed to assess the cost-effectiveness of RPM in the Netherlands (NL), the United Kingdom (UK), and Germany (DE) highlighting the differences between cost-effectiveness from a societal and healthcare perspective.
METHODS: We developed a Markov model with a lifetime horizon to assess the cost-effectiveness of RPM compared with usual care. We included HF-related hospitalization and non-hospitalization costs, intervention costs, other medical costs, informal care costs, and costs of non-medical consumption. A probabilistic sensitivity analysis and scenario analyses were performed.
RESULTS: RPM led to reductions in HF-related hospitalization costs, but total lifetime costs were higher in all three countries compared to usual care. The estimated incremental cost-effectiveness ratios (ICERs), from a societal perspective, were €27,921, €32,263, and €35,258 in NL, UK, and DE respectively. The lower ICER in the Netherlands was mainly explained by lower costs of non-medical consumption and HF-related costs outside of the hospital. ICERs, from a healthcare perspective, were €12,977, €11,432, and €11,546 in NL, the UK, and DE, respectively. The ICER was most sensitive to the effectiveness of RPM and utility values.
CONCLUSIONS: This study demonstrates that RPM for HF can be cost-effective from both healthcare and societal perspective. Including costs of living longer, such as informal care and non-medical consumption during life years gained, increased the ICER.

BACKGROUND: Germany has the highest per capita health care spending among EU member states, but its hospitals face pressure to generate profits independently due to the government\'s withdrawal of investment cost coverage. The diagnosis related groups (DRG) payment system was implemented to address the cost issue, challenging hospital physicians to provide services within predefined prices and an economic target corridor to reduce costs. This study examines the extent of cost awareness among medical personnel in German hospitals and its influencing factors.
METHODS: We developed an online survey in which participants across all specialties in hospitals estimated the prices in euros of four common interventions and answered questions about their human capital and perceived stress on the workplace. As a measure of cost awareness, we used the probability of estimating the prices correctly within a reasonable margin. We employed logit logistic regression estimators to identify influencing factors in a sample of 86 participants.
RESULTS: The results revealed that most of the respondents were unaware of the costs of common interventions. General human capital, acquired through prior education, and job-specific human capital had no influence on cost awareness, whereas domain-specific human capital, that is, gaining economic knowledge based on self-interest, had a positive nonlinear effect on cost awareness. Furthermore, an increased stress level negatively influenced cost awareness.
CONCLUSIONS: This paper is the first of its kind for the German health care sector that contributes responses to the question whether health care professionals in German hospitals have cost awareness and if not, what reasons lie behind this lack of knowledge. Our findings show that the cost awareness desired by the introduction of the DRG system has yet to be achieved by medical personnel.

While numerous studies have addressed the photocatalytic degradation of 2,6-dichlorophenol (2,6-DCP) in wastewater, an existing research gap pertains to operational factors\' optimization by non-linear prediction models to ensure a cost-effective and sustainable process. Herein, we focus on optimizing the photocatalytic degradation of 2,6-DCP using artificial intelligence modeling, aiming at minimizing initial capital outlay and ongoing operational expenses. Hence, Fe/Zn@biochar, a novel material, was synthesized, characterized, and applied to harness the dual capabilities of 2,6-DCP adsorption and degradation. Fe/Zn@biochar exhibited an adsorption energy of -21.858 kJ/mol, effectively capturing the 2,6-DCP molecules. This catalyst accumulated photo-excited electrons, which, upon interaction with adsorbed oxygen and/or dissolved oxygen generated •O2-. The •OH radicals could also be produced from h+ in the Fe/Zn@biochar valence band, cleaving the C-Cl bonds to Cl- ions, dechlorinated byproducts, and phenols. An artificial neural network (ANN) model, with a 4-10-1 topology, \"trainlm\" training function, and feed-forward back-propagation algorithm, was developed to predict the 2,6-DCP removal efficiency. The ANN prediction accuracy was expressed as R2 = 0.967 and mean squared error = 5.56e-22. The ANN-based optimized condition depicted that over 90% of 2,6-DCP could be eliminated under C0 = 130 mg/L, pH = 2.74, and catalyst dosage = 168 mg/L within ∼4 h. This optimum condition corresponded to a total cost of $7.70/m3, which was cheaper than the price estimated from the unoptimized photocatalytic system by 16%. Hence, the proposed ANN could be employed to enhance the 2,6-DCP photocatalytic degradation process with reduced operational expenses, providing practical and cost-effective solutions for petrochemical wastewater treatment.

Mobile cloud computing (MCC) provides resources to users to handle smart mobile applications. In MCC, task scheduling is the solution for mobile users\' context-aware computation resource-rich applications. Most existing approaches have achieved a moderate service reliability rate due to a lack of instance-centric resource estimations and task offloading, a statistical NP-hard problem. The current intelligent scheduling process cannot address NP-hard problems due to traditional task offloading approaches. To address this problem, the authors design an efficient context-aware service offloading approach based on instance-centric measurements. The revised machine learning model/algorithm employs task adaptation to make decisions regarding task offloading. The proposed MCVS scheduling algorithm predicts the usage rates of individual microservices for a practical task scheduling scheme, considering mobile device time, cost, network, location, and central processing unit (CPU) power to train data. One notable feature of the microservice software architecture is its capacity to facilitate the scalability, flexibility, and independent deployment of individual components. A series of simulation results show the efficiency of the proposed technique based on offloading, CPU usage, and execution time metrics. The experimental results efficiently show the learning rate in training and testing in comparison with existing approaches, showing efficient training and task offloading phases. The proposed system has lower costs and uses less energy to offload microservices in MCC. Graphical results are presented to define the effectiveness of the proposed model. For a service arrival rate of 80%, the proposed model achieves an average 4.5% service offloading rate and 0.18% CPU usage rate compared with state-of-the-art approaches. The proposed method demonstrates efficiency in terms of cost and energy savings for microservice offloading in mobile cloud computing (MCC).

A nanocomposite membrane incorporating reactive Pd-Fe nanoparticles (NPs) was developed to remediate chlorinated aliphatic hydrocarbons (CAHs) from groundwater. Other than recapturing the produced Fen+ for in-situ regeneration, the functionalized polyanions prevented NPs agglomeration and resulting in a spherical Fe0 core (55 nm, O/Fe = 0.05) and an oxidized shell (4 nm, O/Fe = 1.38). The reactive membranes degraded 92% of target CAHs with a residence time of 1.7 seconds. After long-term treatment and regeneration, reusability was confirmed through recovered reactivity, recurrence of Fe0 in X-ray photoelectron spectroscopy, and >96% remaining of Fe and Pd. The total cost (adjusted present value for 20 years) was estimated to be 13.9% lower than the granular activated carbon system, following an EPA work breakdown structure-based cost model. However, non-target CAHs from groundwater can compete for active sites, leading to decreased surface-area normalized dechlorination rate (ksa) by 28.2-79.9%. A hybrid nanofiltration (NF)/reactive membrane was proposed to selectively intercept larger competitors, leading to 54% increased dechlorination efficiency and 1.3 to 1.9-fold enlarged ksa. Overall, the practical viability of the developed reactive membranes was demonstrated by the stability, reusability, and cost advantages, while the optional NF strategy could alleviate competitive degradation towards complex water chemistry.

The present study investigates the treatment of real coke plant effluent utilising several ultrasound-based hybrid oxidation approaches including Ultrasound (US) alone, US + catalyst, US + H2O2, US + Fenton, US + Ozone, and US + Peroxone, with main objective as maximizing the reduction of chemical oxygen demand (COD). Ultrasonic horn at power of 130 W, frequency as 20 kHz and duty cycle as 70% was applied. Study with varying catalyst (TiO2) dose from 0.5 g/L - 2 g/L revealed 1 g/L as the optimum dose resulting in 65.15% reduction in COD. A 40 ml/L dose of H2O2 was shown to be optimal, giving an 81.96% reduction in COD, based on the study of varied doses of H2O2 from 20 ml/L to 60 ml/L. US + Fenton reagent combination at optimum Fe2+/H2O2 (w/v) ratio of 1:1 resulted in a COD reduction of 85.29% whereas reduction of COD as 81.75% was obtained at the optimum flow rate of ozone as 1 LPM for US + Ozone approach. US + Peroxone demonstrated the best efficiency (90.48%) for COD reduction. To find the toxicity effects, the treated (US + peroxone) and non-treated samples were tested for the growth of bacterial cultures. It was observed that the toxicity of the treated sample increased only marginally after treatment. High-resolution liquid chromatography mass spectrometry (HR-LCMS) analysis was also performed to establish intermediate compounds. Overall, the coupling of ultrasound with oxidation processes produced better results with US + Peroxone established as best treatment approach for coke plant effluent.

Plastic pollution is a generational problem, and stakeholders are turning to chemical recycling as a potential solution. However, decision-makers necessitate quick and reliable capital investment estimations to evaluate innovative technologies, especially in the early project stage, when limited historical data are available. To address this need, we built a database of 160+ chemical recycling plants, querying for nominal capacity, year and place of construction, total capital investment (TCI), number of long-term jobs and opportunity of subsidies. Then, we compared conventional association of the advancement of cost engineering AACE class 5 estimation methods, with literature estimates, and commercial capital expenditure confidence intervals for pyrolysis, gasification, solvolysis, and selective dissolution. We demonstrate the unreliability of classic methods, and we propose ballpark correlations based on the plant capacity, or the energy loss. Chemical recycling plants suffer from poor economy of scale (with current technologies), and capacity is not always the best indicator for TCI estimation. Pyrolysis and gasification are energy-driven technologies, and their TCI correlates very well (R2 =0.91-0.92) with the total energy losses. Solvolysis and selective dissolution, instead, are at an earlier development stage, so cost engineers or researchers will have to accept less certain TCI vs capacity (R2 =0.60).

Recent SARS-CoV-2 pandemic elevated research interest in microorganism-related diseases, and protective health application importance such as vaccination and immune promoter agents emerged. Among the production methods for proteins, recombinant technology is an efficient alternative and frequently preferred method. However, since the production and purification processes vary due to the protein nature, the effect of these differences on the cost remains ambiguous. In this study, brucellosis and its two important vaccine candidate proteins (rOmp25 and rEipB) with different properties were selected as models, and industrial-scale production processes were compared with the SuperPro Designer® for estimating the unit production cost. Simulation study showed raw material cost by roughly 60% was one of the barriers to lower-cost production and 52.5 and 559.8 $/g were estimated for rEipB and rOmp25, respectively.
HighlightsTechno-economic evaluation of recombinant protein produced for vaccine purposesRecombinant proteins rOmp25 and rEipB production process using E.coli BL21Effect of outer membrane and periplasmic space proteins on purification costSimulated cost estimation of rEipB and rOmp25 were 52.5 and 559.8 $/g, respectively.