In modern process industries, data-driven models are important tools for real-time monitoring when key performance indicators are difficult to measure directly. While accurate predictions are essential, reliable uncertainty quantification (UQ) is equally critical for safety, reliability, and decision-making, but remains a major challenge in current data-driven approaches. In this work, we introduce a diffusion-based posterior sampling framework that inherently produces well-calibrated predictive uncertainty via faithful posterior sampling, eliminating the need for post-hoc calibration. In extensive evaluations on synthetic distributions, the Raman-based phenylacetic acid soft sensor benchmark, and a real ammonia synthesis case study, our method achieves practical improvements over existing UQ techniques in both uncertainty calibration and predictive accuracy. These results highlight diffusion samplers as a principled and scalable paradigm for advancing uncertainty-aware modeling in industrial applications.
Wenli Gou, Sameer Alshehri, Niloofar Pirestani
et al.
Abstract This research endeavors to elucidate the process of developing and characterizing a novel plant-derived biogenic-based bi-functionalized MCM-41 (Mobil Composition of Matter No. 41), abbreviated as Bif-MCM-41, prepared through an environmentally friendly one-pot method. The Bif-MCM-41 material was functionalized with two different silane coupling agents with different functional groups to enhance its adsorption properties. XRD and TEM confirmed the mesoporous structure constructed from well-ordered hexagonal arrays of parallel microchannels, while FESEM revealed uniform Bacillus-like (rod-shaped) morphology. The material exhibited a high surface area (988 m2 g−1), a pore volume of 0.72 cm3 g- 1 and a bimodal pore distribution (1.3 nm and 2.5 nm) based on 2D-NLDFT method, confirming a well-developed micro-mesoporous structure. Adsorption studies for tetracycline were conducted under varying conditions, and both linear and nonlinear isotherm and kinetic models were applied to assess adsorption behavior. The maximum Langmuir adsorption capacity reached 765.4 mg g−1 at 293 K. Nonlinear fitting provided a more accurate representation of adsorption behavior, and kinetic studies indicated a pseudo-first-order mechanism, suggesting surface reaction dominance. Thermodynamic analysis confirmed the process as spontaneous and exothermic, driven by π–π stacking and hydrogen bonding. The combination of biogenic synthesis, dual functionalization, and outstanding adsorption performance represents a unique contribution to the development of sustainable adsorbents. This study offers both mechanistic insight and practical relevance, bridging green chemistry with high-efficiency pollutant removal.
Abstract To overcome the short retention time in small-scale wastewater treatment plants, it is necessary to develop processes with fast reaction rates. The microwave-Fenton-like reaction (MW-Fenton-like reaction), which combines external energy and catalysts, provides a solution with rapid reaction rate and high degradation efficiency. In this reaction, catalysts significantly influence decomposition efficiency. Developing magnetic catalysts can simplify the separation process. In this study, the superiority of copper-based metal oxides for the MW-Fenton-like reaction was confirmed through comparative experiments of various metal oxides. Based on these findings, highly active CuFe2O4/Cu particles were developed. The synthesized particles, with rough-surfaced solid-sphere morphology, exhibited ferromagnetic properties and were completely separated using a laboratory-scale magnet. CuFe2O4/Cu also showed high degradation over a wide pH range and achieved the highest degradation rate at pH 7. Furthermore, comparison of 4-nitrophenol (4-NP) degradation using MW and conventional heating demonstrated MW was superior in reaction rate, efficiency, and reusability.
The current surge in supply chain finance has significantly alleviated the "capital challenges" faced by domestic related enterprises, enabling enterprises upstream and subsequent stages of the industrial chain to achieve effective circulation of financing services in the supply chain based on the credit of core enterprises. By gathering essential information from the heart of the supply chain, supply chain financing enables efficient resource distribution and aids all stakeholders in making well-informed choices. However, supply chain finance in China still faces numerous obstacles, such as information asymmetry and inefficient credit transmission chains, hindering its long-term development. This paper designs an operational framework for supply chain finance incorporating blockchain technology, clearly defines the participating entities, and analyzes their business relationships. Based upon evolutionary game theory, a supply chain finance financing game model incorporating blockchain technology is constructed. A comparative analysis of the model's equilibrium points and their stability is conducted. The choices of evolutionary equilibrium strategies adopted by small and medium-sized enterprises, key players, and financing entities within this framework are explored, and the influence of blockchain technology on the prerequisites for completing supply chain finance transactions is investigated.
This paper proposes a novel empirical strategy to measure cultural justifications of domestic violence within households, with direct implications for demographic behavior and gender inequality. Leveraging survey data on individual attitudes and high-frequency time-use diaries from Italian couples with children, I construct a composite index that integrates stated beliefs with observed household practices. Using structural equation modeling, I disentangle latent tolerance of domestic violence from reported attitudes and validate the index against both individual and partner characteristics, as well as time allocation patterns. Results reveal systematic heterogeneity by gender, education, and normative environments. Conservative gender and parenthood norms are strong predictors of tolerance, while higher male education reduces it. Tolerance of violence is also positively associated with reported leisure time with partners and children, suggesting that co-presence does not necessarily reflect egalitarian interaction but may coexist with unequal bargaining structures. Beyond advancing measurement, the findings highlight how cultural tolerance of domestic violence is embedded in household arrangements that influence fertility, labor supply, and the intergenerational transmission of norms. The proposed framework offers a scalable tool for economists and policymakers to monitor hidden inequalities and design interventions targeting family stability, gender equity, and child well-being.
Supply chain operations generate vast amounts of operational data; however, critical knowledge such as system usage practices, troubleshooting workflows, and resolution techniques often remains buried within unstructured communications like support tickets, emails, and chat logs. While RAG systems aim to leverage such communications as a knowledge base, their effectiveness is limited by raw data challenges: support tickets are typically noisy, inconsistent, and incomplete, making direct retrieval suboptimal. Unlike existing RAG approaches that focus on runtime optimization, we introduce a novel offline-first methodology that transforms these communications into a structured knowledge base. Our key innovation is a LLMs-based multi-agent system orchestrating three specialized agents: Category Discovery for taxonomy creation, Categorization for ticket grouping, and Knowledge Synthesis for article generation. Applying our methodology to real-world support tickets with resolution notes and comments, our system creates a compact knowledge base - reducing total volume to just 3.4% of original ticket data while improving quality. Experiments demonstrate that our prebuilt knowledge base in RAG systems significantly outperforms traditional RAG implementations (48.74% vs. 38.60% helpful answers) and achieves a 77.4% reduction in unhelpful responses. By automating institutional knowledge capture that typically remains siloed in experts' heads, our solution translates to substantial operational efficiency: reducing support workload, accelerating resolution times, and creating self-improving systems that automatically resolve approximately 50% of future supply chain tickets. Our approach addresses a key gap in knowledge management by transforming transient communications into structured, reusable knowledge through intelligent offline processing rather than latency-inducing runtime architectures.
Recent crises have increased concerns about supply security in sectors that are considered strategically important. The goal of sufficient domestic production capacities has motivated various forms of subsidies, tariffs and other instruments. This paper revisits Warren Buffett's (2003) proposal of tradeable import certificates (TIC) in this context. TIC differ from classical import quotas mainly by linking the import volume to export performance. The certificate price functions like a mix of flexible tariffs and export subsidies whose levels depend on net imports in the strategic sector. We analyse benefits and drawbacks in a simple two-country model. In competitive markets, TIC constitute a transparent and efficient instrument that effectively reduces incentives for other countries to deviate from agreements via hidden subsidies or non-tariff trade barriers. However, TIC can have adverse effects if there are domestic producers with market power in the certificate market.
This study constructs a quantifiable modelling framework to simulate non-kinetic strategic deterrence pathways in rare earth supply disruption scenarios, based on structured responses from expert interviews led by Dr. Daniel O'Connor, CEO of the Rare Earth Exchange (REE). Focusing on disruption impacts on national security systems, the study proposes four core modelling components: Security Critical Zones (SCZ), Strategic Signal Injection Function (SSIF), System-Capability Migration Function (SCIF), and Policy-Capability Transfer Function (PCTF). The framework integrates parametric ODEs, segmented function modelling, path-overlapping covariance matrices, and LSTM networks to simulate nonlinear suppression trajectories triggered by regime signals. Data is derived from expert interviews and scenario analyses centered on U.S.-China dynamics in ISR, electronic warfare, and rare earth control. Results show institutional signals have strong tempo and path-coupling effects, capable of causing rapid degradation of strategic capabilities. The model is adaptable across national resource frameworks and extendable to AI sandbox engines for situational simulation and counterfactual reasoning. This research introduces the first unified system for modelling, visualizing, and forecasting non-kinetic deterrence, offering methodological support to policymakers and analysts navigating institutionalized strategic competition.
Md. Moshiur Rahman Tushar, Zaki Alam Pushan, Nirupam Aich
et al.
Abstract Per- and polyfluoroalkyl substances (PFAS) are emerging water contaminants with significant environmental and health impacts, posing challenges in water treatment due to their high stability and persistence. With increasing regulations, a critical need remains in understanding the sustainability of PFAS treatment technologies. Our review examines the environmental, economic, and social impacts of current PFAS treatment technologies across different water types and contexts. Additionally, we propose a framework for future sustainability studies to enable more holistic technology evaluations under specific conditions.
Abstract: Water quality study presents status of water for domestic, irrigation, industrial and other uses. Indiscriminate and wasteful water consumption, improper waste disposal practices, and underground contamination have led to deterioration and pollution of water quality. This study was aimed at determining water quality status using parameters in borehole water. Samples from two different towns; Ngwo and Enene, Enugu East. Sampling locations 1(6o 28’24.7”N 7o 34’49.2”E) and 2(6o 27’36”N 7 o 36’46”E) are situated within Nike East Local Government (precisely Emene) while sample 3(6o 25’52.8”N 7o 25’10.6”E), 4(6o 25’55.3”N 7o 24’22.8”E) and 5(6o 25’50.4”N 7o 26’08.5”E) are within Enugu Ngwo (9thMile Corner). The parameters analyzed include; Electrical conductivity, Turbidity, pH, TDS, TSS, SS, Calcium, Magnesium, and Total Hardness, using laboratory standard methods of analysis. The data provided by this investigation shows that the water samples from Enugu Ngwo only is more acidic outside the recommended level. Other qualities of all the parameters are all measurable for both locations. Based on these findings, recommendations were presented for the purpose of improving water quality and sustainable assess in Enugu Metropolis and beyond.
As global demand for green hydrogen rises, potential hydrogen exporters move into the spotlight. However, the large-scale installation of on-grid hydrogen electrolysis for export can have profound impacts on domestic energy prices and energy-related emissions. Our investigation explores the interplay of hydrogen exports, domestic energy transition and temporal hydrogen regulation, employing a sector-coupled energy model in Morocco. We find substantial co-benets of domestic climate change mitigation and hydrogen exports, whereby exports can reduce domestic electricity prices while mitigation reduces hydrogen export prices. However, increasing hydrogen exports quickly in a system that is still dominated by fossil fuels can substantially raise domestic electricity prices, if green hydrogen production is not regulated. Surprisingly, temporal matching of hydrogen production lowers domestic electricity cost by up to 31% while the effect on exporters is minimal. This policy instrument can steer the welfare (re-)distribution between hydrogen exporting firms, hydrogen importers, and domestic electricity consumers and hereby increases acceptance among actors.
We investigate the impact of judges' gender on the outcome of domestic violence cases. Using data from São Paulo, Brazil, between 2011 and 2019, we find that a domestic violence case assigned to a female judge is 28% (9.7 p.p.) more likely to result in a conviction than a case assigned to a male judge with similar career characteristics. To show that this decision gap rises due to different gender perspectives about domestic violence and not because female judges are stricter than their male counterparts in all rulings, we compare it against the gender conviction-rate gap in similar types of crime. We find that this gap for domestic violence cases is larger than the same gap for other physical assault cases (8.5 p.p.). Furthermore, we find evidence that at least two channels explain this gender conviction-rate gap for domestic violence cases: gender-based differences in evidence interpretation and gender-based sentencing criteria. We also find that female judges write longer sentences, schedule more hearings, and write more judicial documents than their male peers when analyzing domestic violence cases. Lastly, we find that the gender conviction-rate gap has no significant impact on the probability of appeals, ruling reversals, or recidivism.
The Metaverse is a concept that proposes to immerse users into real-time rendered 3D content virtual worlds delivered through Extended Reality (XR) devices like Augmented and Mixed Reality (AR/MR) smart glasses and Virtual Reality (VR) headsets. When the Metaverse concept is applied to industrial environments, it is called Industrial Metaverse, a hybrid world where industrial operators work by using some of the latest technologies. Currently, such technologies are related to the ones fostered by Industry 4.0, which is evolving towards Industry 5.0, a paradigm that enhances Industry 4.0 by creating a sustainable and resilient world of industrial human-centric applications. The Industrial Metaverse can benefit from Industry 5.0, since it implies making use of dynamic and up-to-date content, as well as fast human-to-machine interactions. To enable such enhancements, this article proposes the concept of Meta-Operator: an Industry 5.0 worker that interacts with Industrial Metaverse applications and with his/her surroundings through advanced XR devices. This article provides a description of the technologies that support Meta-Operators: the main components of the Industrial Metaverse, the latest XR technologies and the use of Opportunistic Edge Computing communications (to interact with surrounding IoT/IioT devices). Moreover, this paper analyzes how to create the next generation of Industrial Metaverse applications based on Industry 5.0, including the integration of AR/MR devices with IoT/IIoT solutions, the development of advanced communications or the creation of shared experiences. Finally, this article provides a list of potential Industry 5.0 applications for the Industrial Metaverse and analyzes the main challenges and research lines. Thus, this article provides useful guidelines for the researchers that will create the next generation of applications for the Industrial Metaverse.
Md Rabiul Hasan, Muztoba Ahmed Khan, Thorsten Wuest
Sustainable supply chain management is a key objective of Industry 5.0, leveraging technologies like real-time data analytics, connectivity, and intelligent automation. At the same time, composite materials present benefits such as lightweight structures, crucial for reducing fuel consumption. This study investigates the intersection between sustainable supply chains and composites by analyzing the current status, research gaps, methodologies, and future research opportunities through bibliometric analysis and a systematic review of the state of the art in the composite materials supply chain. A systematic literature review approach is employed to analyze the Scopus and Web of Science (WOS) databases, offering a comprehensive overview of the existing literature. Through bibliometric analysis, the study investigates countries, authors, citations, keywords, subject areas, and article themes within the metadata to provide additional context. An in-depth analysis of thirty selected papers (n=30) sheds light on the key contributions, major challenges, and Key Performance Indicators (KPIs) across various instances of composite material supply chains, resulting in a generalized overview. Furthermore, this research suggests future directions to link the sustainability efforts in composite materials supply chains with current research gaps. The study underscores diverse research themes in the field, highlighting a few influential works and presenting opportunities for advancement in this emerging area. Collectively, these findings offer valuable insights and a robust roadmap for future research in this domain.
Abstract Efficient desalination through a reverse osmosis (RO) membrane requires the prior removal of blockade-causing substances from raw seawater. To achieve ultrahigh-speed processing of a pretreatment process for seawater RO desalination, we combine traditional softening with ballasted flocculation (SBF) for Ca2+ and Mg2+ removal. An alkaline mixture of Ca(OH)2 and Na2CO3 was the most suitable softening agent for Ca2+ and Mg2+ removal with a reduced amount of generated sludge. This softening treatment simultaneously removed the suspended solids and bacteria from actual seawater. The settling velocity of the suspended solids generated via seawater softening was extremely low. Under the optimum conditions for desalinating actual seawater using an anionic polymer flocculant and microsand, the settling velocity exceeded 3.5 cm/s, 833 times higher than that of softening without ballasted flocculation. The amount of sludge after standing for 3 min was 76.5% lower in SBF than in conventional softening. The silt density index of the treated seawater met the water-supply standard of RO membranes (i.e., <3.0). Furthermore, the SBF-generated sludge exhibited considerably improved dewatering property than the sludge obtained via conventional softening. SBF can efficiently and quickly remove the causative substances of RO membrane fouling from seawater, thereby improving the treatability of generated sludge. SBF provides a new pretreatment process for seawater desalination using RO membranes.
Shumaila Kiran, Hasan B. Albargi, Gulnaz Afzal
et al.
Abstract A variety of industries employ synthetic azo dyes. However, the biosphere is being damaged by the unused/leftover azo dyes, which pose a danger to all living things. Therefore, treating them to shield the environment from the potential harm of azo dyes is crucial. Bio-sorption is a cheap and effective mode for eliminating toxic dyes in the environment. The current work focused on synthesizing magnesium oxide (MgO) nanoparticles using an aqueous leaf extract of neem (Azadirachta indica). The XRD and SEM analyses of MgO nanoparticles indicated the crystalline nature of MgO nanoparticles with a cubic structure, and the size was around 90–100 nm. FTIR analysis showed the presence of a stretching frequency peak at 550 cm−1, confirming the Mg–O bond. The surface analysis revealed the cluster form of the synthesized nanoparticles. The UV–visible absorption peak for MgO nanoparticles was found at 294 nm and band gap of 4.52 eV. In order to eliminate the Reactive Red 195 dye, MgO nanoparticles were used. At pH 4, 40 °C, 0.02% dye concentration, and 0.003 g/L catalyst amount, the highest degree of decolorization (91%) was seen. Decreased total organic carbon (TOC) and the chemical oxygen demand (COD) percent were 84.33% and 81.3%, respectively. The proposed mechanism of target dye degradation was also investigated. MgO NPs were found to be effective in their catalytic behavior toward the degradation of Reactive Red 195 dye up to five cycles with almost no change in their catalytic activity.
<p>In Canada, more than 80% of energy in the residential sector is used for space heating and domestic hot water (DHW) production. This study aimed to model and compare the performance of four different systems, using solar energy as a renewable energy source for DHW production. A novel microchannel (MC) solar thermal collector and a microchannel-based hybrid photovoltaic/thermal collector (PVT) were fabricated (utilizing a microchannel heat exchanger in both cases), mathematical models were created, and performance was simulated in TRNSYS software. A water-to-water heat pump (HP) was integrated with these two collector-based solar systems, namely MCPVT-HP and MCST-HP, to improve the total solar fraction. System performance was then compared with that of a conventional solar-thermal-collector-based system and that of a PV-resistance (PV-R) system, using a monocrystalline PV collector. The heat pump was added to the systems to improve the systems’ efficiency and provide the required DHW temperatures when solar irradiance was insufficient. Comparisons were performed based on the temperature of the preheated water storage tank, the PV panel efficiency, overall system efficiency, and the achieved solar fraction. The microchannel PVT-heat pump (MCPVT-HP) system has the highest annual solar fraction among all the compared systems, at 76.7%. It was observed that this system had 10% to 35% higher solar fraction than the conventional single-tank solar-thermal-collector-based system during the wintertime in a cold climate. The performance of the two proposed MC-based systems is less sensitive than the two conventional systems to collector tilt angle in the range of 45 degrees to 90 degrees. If roof space is limited, the MCPVT-HP system is the best choice, as the MCPVT collector can perform effectively when mounted vertically on the facades of high-rise residential and commercial buildings. A comparison among five Canadian cities was also performed, and we found that direct beam radiation has a great effect on overall system solar faction.</p>
Fatima El Asri, Ahmed Errhif, Mohamed-Naoufal Tamsouri
et al.
Abstract Morocco is a very rich country in terms of wetlands, including bays, estuaries, lagoons, lakes, and rivers, among others. However, many of them need to be well managed and better exploited, thus requiring baseline descriptive studies to assess faunal patterns and trends. Oualidia lagoon is not an exception. In fact, the studies conducted to date in the lagoon mainly focused on its oceanographic features and aquaculture capacities. The present paper presents the first study on the whole macrofaunal assemblages of Oualidia lagoon, having as main objectives analyze the composition and structure of the assemblages, as well as their relationships with the main environmental variables explaining their spatial distribution variability in the enclosed ecosystem of the Oualidia coastal lagoon. The benthic macroinvertebrates of Oualidia lagoon were studied in summer 2013 based on 43 stations spread over the whole lagoon by using a Van Veen grab. Two replicate samples were collected for macrobenthos and one additional replicate for sediment analyses at each station. Also, single water salinity and temperature measurements were recorded at each station. Fifty-one species from seven different taxa were recorded, among which mollusks (37%), polychaetes (25%) and crustaceans (25%) dominated in terms of species number. Peringia ulvae, Abra alba, Sphaeroma serratum, Cerastoderma edule and Corophium sp. accounted for 88% of total abundance. The benthos was structured along a downstream–upstream gradient, showing three assemblages, named according to the IndVal index: (1) Diopatra cf. marocensis, (2) Peringia ulvae, and (3) Cerastoderma edule, while the main factors driving their distribution were granulometry and salinity. The Biotic and Environmental analysis showed that the combination of granulometry and salinity was the major factors controlling the spatial distribution of the macrozoobenthos in the Oualidia Lagoon.
Conventional spectrophotometric methods were unable to accurately detect urea concentrations below 100 μg/L. A modified spectrophotometric method was developed to determine the trace urea in the ultrapure water (UPW) production process of the semiconductor manufacturing industry. This method was optimized based on the dosage of chemical agents, length of the optical path, and mode of the water bath. Metal ions were added to promote the stability of the chromogenic system. A calibration graph was observed with ideal linearity in the range of 0.8–100 μg/L. The detection and quantification limits of urea were 0.24 and 0.80 μg/L, respectively. The distribution of urea in raw water for the UPW production process was observed and the urea in tap water was 10–20 μg/L. The urea of municipal reclaimed water was 24–40 μg/L, which was twice that of industrial reclaimed water at 10–18 μg/L. The total removal rate of urea by the UPW production process was 50–70%. Reverse osmosis membranes played a critical role in the removal of urea (over 30%). The urea in the final UPW produced from tap water was approximately 4.1 μg/L, which creates a potential risk of excessive total organic carbon.
HIGHLIGHTS
A spectrophotometric method for the determination of trace urea during ultrapure production process was first established.;
Stability of the absorbance in the color reaction was increased by doping metal ions.;
The urea concentration of municipal reclaimed water was twice that of industrial reclaimed water.;
The urea removal efficiencies in each unit of the ultrapure water production process were explored.;