Search Results (1,899)

In urban regeneration, co-production has become a significant approach for shaping public space in urban communities. While existing studies focus on the processes and stakeholders involved in co-production of community public space (CPS), few have examined the influence of structural factors. Based on the politics of scale, this study uses thematic analysis within an embedded case study of community centers in Shanghai, China, to analyze the impact of scalar restructuring on community co-production across three dimensions: material scale, organizational scale, and discursive scale. The study finds that local governments actively reshape public space through scalar restructuring, thereby transforming power relations among participants and promoting community co-production. In response to different community conditions and dilemmas, local governments adopt context-specific scalar restructuring strategies. When implementing scalar restructuring strategies such as downscaling, upscaling and scalar recompositing, three corresponding patterns of community co-production often emerge: bonded, procedural, and bridged. This paper contributes by providing a new perspective on the mechanism of community co-production, identifying novel patterns of community co-production and refining the scalar restructuring strategies. It moves beyond spatial limitations and captures the co-production of CPS through a broader lens of power dynamics. Full article

The advancement of efficient energy conversion and storage technologies is fundamentally linked to the development of electrochemical systems, including fuel cells, batteries, and electrolyzers, whose performance depends on key electrocatalytic reactions: hydrogen evolution (HER), oxygen evolution (OER), oxygen reduction (ORR), carbon dioxide reduction (CO₂RR), and nitrogen reduction (NRR). Beyond catalyst design, the electrolyte microenvironment significantly influences these reactions by modulating charge transfer, intermediate stabilization, and mass transport, making electrolyte engineering a powerful tool for enhancing performance. This review provides a comprehensive analysis of how fundamental electrolyte properties, including pH, ionic strength, ion identity, and solvent structure, affect the mechanisms and kinetics of these five reactions. We examine in detail how the electrolyte composition and individual ion contributions impact reaction pathways, catalytic activity, and product selectivity. For HER and OER, we discuss the interplay between acidic and alkaline environments, the effects of specific ions, interfacial electric fields, and catalyst stability. In ORR, we highlight pH-dependent activity, selectivity, and the roles of cations and anions in steering 2e⁻ versus 4e⁻ pathways. The CO₂RR and NRR sections explore how the electrolyte composition, local pH, buffering capacity, and proton sources influence activity and the product distribution. We also address challenges in electrolyte optimization, such as managing competing reactions and maximizing Faradaic efficiency. By comparing the electrolyte’s effects across these reactions, this review identifies general trends and design guidelines for enhancing electrocatalytic performance and outlines key open questions and future research directions relevant to practical energy technologies. Full article

Hydrophilic Interaction Liquid Chromatography (HILIC) has emerged as a powerful and versatile analytical technique for the separation and quantification of polar and ionizable compounds, particularly in the field of pharmaceutical impurity profiling. Over the past two decades, HILIC has gained increasing attention due to its compatibility with mass spectrometry, enhanced retention of hydrophilic impurities, and ability to resolve structurally similar degradation products and process-related impurities that are often inadequately retained by reversed-phase chromatography. This comprehensive review presents a critical overview of HILIC-based methodologies applied to impurity profiling in pharmaceutical analysis from early 2005 to the present. Emphasis is placed on the application of HILIC to both small-molecule drugs and large biomolecules. Additionally, the review categorizes analytical configurations into four main groups based on their operational principles and use cases, offering insights into method selection and performance characteristics. This article serves as a valuable resource for researchers and regulatory scientists seeking to apply HILIC in modern impurity profiling and quality control of pharmaceutical products. Full article

This study presents a novel policy-integrated optimization framework for utility-scale hybrid power plants (HPP), including wind–solar–battery, addressing a critical gap in hybrid renewable energy system design by simultaneously evaluating technical, operational, and economic performance under dynamic policy environments. Unlike conventional approaches that treat these factors separately, this multi-objective optimization model uniquely combines (1) technical reliability assessment through Loss of Load Probability (LOLP) metrics, (2) operational efficiency analysis via curtailment minimization, and (3) economic viability evaluation using net present value (NPV) optimization—all while accounting for policy incentive structures. Applying this framework to comparative U.S. and India case studies reveals how tailored policy combinations can enhance project viability compared to single-incentive scenarios. The results indicate that HPPs are financially unviable without policy support, but targeted incentives like Investment Tax Credits (ITCs) and Production Tax Credits (PTCs) in the U.S. and Accelerated Depreciation (AD), Generation-Based Incentives (GBIs), and Viability Gap Funding (VGF) can improve their viability. The U.S. scenario sees a 197% increase in NPV and a reduction in LCOE to USD 0.055/kWh, while India achieves a 107% turnaround in NPV and an LCOE of USD 0.039/kWh. Sensitivity and breakeven analyses reveal that interest rates and consistent policy support are critical, especially in emerging markets. Specific policy thresholds are identified for feasibility, providing actionable benchmarks. By bridging the gap between technical optimization and policy analysis, this work provides both a methodological advance for HPP design and practical insights for policymakers seeking to accelerate HPP. While this study centers on incentive-driven feasibility, it also outlines key modeling limitations and future improvements, such as market participation, environmental constraints, and advanced system design that will support future HPP planning. Full article

Organophosphates, especially their ester, are not only toxic to humans but equally toxic to aquatic and other animal life on Earth when exposed to them. Here, we designed an efficient and easy way to degrade hexamethyl phosphoramide and omethoate organophosphate catalytically in a natural way into non-toxic products. Both hexamethyl phosphoramide and omethoate are possible carcinogens and cause serious health issues in humans and other animals when exposed to them. In this work, a modified sonochemical method was used for the synthesis of ZnO nanoparticles using zinc acetate dihydrate, ethylenediamine dihydrochloride, and polyvinylpyrrolidone. Sodium hydroxide was used as the precipitating agent, and distilled water was used as the solvent. An Elmasonic ultra-sonicator with 240-watt power was used for the preparation of ZnO nanoparticles. The synthesized ZnO nanoparticles with a high surface area (250 m²/g), average particle size of 23 ± 1 nm, and a mesoporous structure with 1.858 nm average pore size were then used for the degradation of organophosphate, i.e., hexamethyl phosphoramide and omethoate pesticide, using 10 µL of concentration to check their catalytic efficiency for the first time. The degradation products were identified using gas chromatography–electron impact mass spectrometry (GC/EIMS). The results showed that omethoate was completely degraded, while hexamethyl phosphoramide showed partial degradation, both producing fewer toxic intermediates. Full article

High-power-density electric machines play a key role in decarbonising transportation technologies. A critical component of the movement towards high-performance machines is the structure and manufacture of the windings, as this is the dominant source of machine loss. Manufacturing time is important to the effectiveness of the production line, with equivalent importance to the electromagnetic and thermal characteristics. Edgewise windings are increasingly considered to have high potential to be quickly and automatically manufactured. However, they are rarely studied considering all the aspects, these being electromagnetic, thermal, and manufacturing characteristics. This paper will experimentally assess the performance of edgewise machines compared to a stranded winding machine, covering all the aforementioned aspects. Two edgewise winding types are considered, parallel slot and parallel tooth. Firstly, a baseline 11 kW stranded winding machine will be introduced, then two edgewise type machines are proposed to be compared to the baseline machine. These comparisons will initially be made based on simulated torque and thermal performance, then the manufacturing time and quality are assessed for each of the coil structures, showing the achievable time reduction by using edgewise coil structures. Motorettes are used to validate thermal performance of the structures, which are used to calibrate simulation models and evaluate the performance of a full machine equivalent model. Under the thermal limit condition, it is shown that the edgewise parallel tooth windings can achieve a torque increase of 27.8% compared to stranded and 24% compared to edgewise parallel slot. Full article

A gas turbine engine is a technological system consisting of a compressor, a combustion chamber, and other modules. All these components are subjected to dynamic and cyclic loads, which lead to fatigue cracks and mechanical damage. The aim of this work is to repair the worn surfaces of a series of DR-59L high-pressure turbine blades by laser powder cladding. A number of technological parameters of laser cladding were tested to obtain a defect-free structure on the witness sample. The metal powder of the cobalt alloy Stellite 21 was used as a filler material. By modeling the process of restoring rotor blades, the operating mode of laser powder cladding was determined. No defects were detected during capillary control of the restored surfaces of the rotor blades. The results of the uniaxial tension test of the restored rotor blades showed increased tensile strength and elongation. With the use of laser powder cladding technology, it was possible to restore the worn surfaces of a series of rotor blades of the DR-59L high-pressure turbine, thereby increasing the life cycle of power plant products. Full article

With the progress of green transformation, government subsidies have become an important incentive for enterprises to invest in green technologies. However, their effectiveness differs markedly under alternative decision-making structures. This study develops a two-tier green supply chain game model comprising manufacturers and e-commerce platform self-operators. Six game structures are examined, covering both scenarios without subsidies and those in which manufacturers receive subsidies. The analysis focuses on product greenness, service levels, retail prices, and the profits of supply chain members. The results show that government subsidies substantially enhance manufacturers’ green investments and motivate platform self-operators to provide higher levels of green services, thereby improving market performance and overall supply chain profitability. Among the different structures, centralized decision-making demonstrates the strongest coordination effect and maximizes the subsidy impact. In contrast, within decentralized structures, subsidies help alleviate double marginalization, but their effectiveness is constrained by the distribution of power. These findings highlight the heterogeneous impacts of subsidies on green supply chain performance, offering theoretical support for targeted government policy design and practical guidance for enterprises to optimize green collaborative strategies. Full article

The growing adoption of the Internet of Things (IoT) demands scalable, energy-efficient communication for autonomous devices. Narrowband IoT (NB-IoT), as a low-power wide-area technology, offers reliable connectivity but remains difficult to integrate in MicroPython systems due to the absence of high-level GSM libraries. This paper introduces a modular, object-oriented MicroPython library that abstracts AT command handling, automates network configuration, and supports protocols such as MQTT and Blynk. The architecture features a layered, hardware-agnostic core and device-specific adapters, enhancing portability and extensibility. The library includes structured exception handling and automated retries to improve system reliability. Empirical validation using a Raspberry Pi Pico and SIM7020E module in a typical IoT scenario demonstrated an up to 81% reduction in implementation time. By providing a reusable and extensible framework, this work improves developer productivity, enhances error resilience, and establishes a solid foundation for rapid NB-IoT application development. Future directions include cross-hardware validation and AI-assisted code and test generation. Full article

Due to the increasing complexity of industrial systems, fault detection hinders the continuity of productivity. Also, many methods in industrial systems whose complexity increases over time have a mechanism based on human intervention. Therefore, the development of intelligent systems in fault detection is critical.. Avoiding false alarms in detecting real faults is one of the goals of these systems. Modern technology has the potential to improve strategies for detecting faults related to machine components. In this study, a hybrid approach was applied on two different datasets for fault detection. First, in this hybrid approach, data is given as input to the artificial neural network. Then, predictions are obtained as a result of training using the ANN mechanism with the feed forward process. In the next step, the error value calculated between the actual values and the estimated values is transmitted to the feedback layers. IWO (Invasive Weed Optimization) optimization algorithm is used to calculate the weight values in this hybrid structure. However the IWO optimization algorithm is designed to be initialized with fractal-based weighting. By this process sequence, it is planned to increase the global search power without getting stuck in local minima. Additionally, fractal-based initialization is an important part of the optimization process as it keeps the overall success and stability within a certain framework. Finally, a testing process is carried out on two separate datasets supplied by the Kaggle platform to prove the model’s success in failure detection. Test results exceed 98%. This success indicates that it is a successful model with high generalization ability. Full article

Multistage pumps serve as the core power source for fluid transportation, and runaway conditions of multistage pumps as turbines (PATs) may lead to severe consequences. This study investigated the pressure pulsation, flow structure, and impeller transient characteristics of an 11-stage petrochemical pump under runaway conditions. Full-flow numerical simulations at varying speeds analyzed head, efficiency, and entropy production via the entropy diagnostic method. The results showed that total entropy production generally increases with rotational speed, while efficiency first rises then declines, peaking at 78.48% at 4000 r/min. Maximum/minimum pressure pulsation peaks consistently occur at identical stages, with dominant peak amplitudes overall increasing with speed. Pressure coefficient amplitudes decrease with frequency growth, with larger pulsation magnitudes observed at monitoring points closer to impeller outlets. Dominant pressure pulsation peaks exhibit upward trends with increasing rotational speed. Both the blade-passing frequency and its harmonics were detected at 5100 r/min, including the impeller inlet/outlet side and the region near the cutwater within the guide vanes. This study identified the critical threshold of 4800 r/min and pinpointed fatigue risk zones, providing a theoretical foundation for designing and manufacturing high-performing multistage PAT systems under runaway conditions. Full article

Background: Undergraduate nursing students (UNSs) often enter clinical training just as they are still mastering the emotional labor of the profession. In Nepal, where teaching hierarchies discourage upward dialogue and hospitals routinely struggle with overcrowding, supply shortages, and outward nurse migration, these learners confront a distinct, under-documented burden of psychological distress. Objective: This study examines how UNSs interpret, negotiate, and cope with the mental health challenges that arise at the intersection of cultural deference, resource scarcity, and migration-fueled uncertainty. Methods: A qualitative design employing reflexive thematic analysis (RTA), guided by the Reflexive Thematic Analysis Reporting Guidelines (RTARG), was used. Fifteen second-, third-, and fourth-year Bachelor of Science in Nursing students at a major urban tertiary institution in Nepal were purposively recruited via on-campus digital flyers and brief in-class announcements that directed students (by QR code) to a secure sign-up form. Participants then completed semi-structured interviews; audio files were transcribed verbatim and iteratively analyzed through an inductive, reflexive coding process to ensure methodological rigor. Results: Four themes portray a continuum from silenced struggle to systemic constraint. First, Shrouded Voices, Quiet Connections captures how students confide only in trusted peers, fearing that formal disclosure could be perceived as weakness or incompetence. Second, Performing Resilience: Masking Authentic Struggles describes the institutional narratives of “strong nurses” that drive students to suppress anxiety, adopting scripted positivity to satisfy assessment expectations. Third, Power, Hierarchy, and the Weight of Tradition reveals that strict authority gradients inhibit questions in classrooms and clinical placements, leaving stress unvoiced and unaddressed. Finally, Overshadowed by Systemic Realities shows how chronic understaffing, equipment shortages, and patient poverty compel students to prioritize patients’ hardships, normalizing self-neglect. Conclusions: Psychological distress among Nepalese UNSs is not an individual failing but a product of structural silence and resource poverty. Educators and policymakers must move beyond resilience-only rhetoric toward concrete reforms that dismantle punitive hierarchies, create confidential support avenues, and embed collaborative pedagogy. Institutional accountability—through regulated workloads, faculty-endorsed wellbeing forums, and systematic mentoring—can shift mental health care from a private struggle to a shared professional responsibility. Multi-site studies across low- and middle-income countries are now essential for testing such system-level interventions and building a globally resilient, compassionate nursing workforce. Full article

This study addresses the critical need to enhance productivity in industrial automatic systems by optimizing the mass of moving components. The primary challenge is determining the complex, dynamic loads on structural elements, a prerequisite for effective redesign, without access to physical prototypes for experimental measurement. This paper presents a solution through a case study of a load-bearing pylon in a fine blanking plant, which is subject to inertial loads and shocks from pneumatic actuators and shock absorbers. To overcome this challenge, a high-fidelity multibody simulation model is developed to accurately estimate the dynamic loads on the pylon. This data is given as input to the topology optimization (TO) process, following the Design for Additive Manufacturing (DfAM) framework, to redesign the pylon for mass reduction using a Powder Bed Fusion-Laser Beam (PBF-LB). Two materials, EOS Aluminum Al2139 AM and EOS Maraging Steel MS1, are evaluated. The findings demonstrate that the integrated simulation and redesign approach is highly effective. The redesigned pylon’s performance is verified within the same simulation environment, confirming the productivity gains before manufacturing. A cost analysis revealed that the additively manufactured solution is more expensive than traditional methods, and the final choice depends on the overall productivity increase. This research validates a powerful methodology that integrates dynamic multibody analysis with topology optimization for AM. This approach is recommended in the design phase of complex industrial machinery to evaluate and quantify performance improvements and make informed decisions on the cost-effectiveness of introducing AM components without the need for physical prototyping. Full article

Modulating enzymatic activity through physical strategies is increasingly recognized as a powerful approach to optimizing biocatalytic processes in food and biotechnology applications. Cellobiose 2-epimerase (C2E), a key enzyme for synthesizing epilactose, a non-digestible disaccharide with established prebiotic effects, is gaining relevance in functional foods. Emerging strategies, such as the application of moderate electric fields (MEFs), have attracted attention due to their non-thermal, non-invasive nature and their capacity to influence the structural and functional properties of proteins. This review assesses the potential of MEFs to modulate C2E activity and provides an overview of the physicochemical principles governing MEF–protein interactions and summarizes findings from various enzymatic systems, highlighting changes in activity, stability, and substrate affinity under electric field conditions. Particular attention is given to the mechanistic plausibility and processing implications of applying MEFs to C2E-catalyzed reactions. The integration of biochemical, structural, and engineering perspectives suggests that MEF-assisted modulation could overcome current bottlenecks in epilactose production. This approach may enable the sustainable valorization of lactose-rich byproducts and support the development of non-thermal, clean-label technologies for producing functional ingredients. Full article

This paper introduces a novel hybrid shifted Gegenbauer integral–pseudospectral (HSG-IPS) method to solve the time-fractional Benjamin–Bona–Mahony–Burgers (FBBMB) equation with high accuracy. The approach transforms the equation into a form with only a first-order derivative, which is approximated using a stable shifted Gegenbauer differentiation matrix (SGDM), while other terms are computed with precise quadrature rules. By integrating advanced techniques such as the shifted Gegenbauer pseudospectral method (SGPS), fractional derivative and integral approximations, and barycentric integration matrices, the HSG-IPS method achieves spectral accuracy. Numerical results show it reduces average absolute errors (AAEs) by up to 99.99% compared to methods like Crank–Nicolson linearized difference scheme (CNLDS) and finite integration method using Chebyshev polynomial (FIM-CBS), with computational times as low as 0.04–0.05 s. The method’s stability is improved by avoiding ill-conditioned high-order derivative approximations, and its efficiency is boosted by precomputed matrices and Kronecker product structures. Robust across various fractional orders, the HSG-IPS method offers a powerful tool for modeling wave propagation and nonlinear phenomena in fractional calculus applications. Full article