Reduction System Research Articles

Treatment of Fractures of the Humeral Surgical Neck: MIROS Versus Intramedullary Nailing—A Retrospective Study

This retrospective study compares the clinical outcomes of the Minimally Invasive Reduction and Osteosynthesis System (MIROS) and intramedullary nailing (IMN) in treating isolated surgical neck fractures of the humerus. A total of 42 patients were included, with 18 treated using MIROS and 24 with IMN. The primary outcomes assessed were the complication rates, functional recovery (DASH score), pain levels (VAS), and radiological healing. The MIROS group exhibited a higher complication rate (22.2% vs. 8.8%), with K-wire migration and superficial infections being the most frequent. Patients treated with MIROS reported lower postoperative pain (VAS 45 ± 25.7) compared to the IMN group (VAS 58.1 ± 12.5). Both groups demonstrated radiological healing within three months, but one MIROS patient required reoperation due to hardware failure. No significant differences were observed in the DASH scores between the groups. Our findings suggest that IMN is a preferable treatment option for younger patients with good bone quality, while MIROS may still be beneficial for elderly patients with significant comorbidities, albeit with a higher risk of complications. Future prospective studies are recommended to confirm these findings.

Multibody elastodynamic modeling of parallel manipulators based on the Lagrangian equations without Lagrangian multipliers

Due to the complexity of the multi constraint and multi closed-loop of parallel mechanisms (PMs), their dynamic equations require additional Lagrangian multipliers and constraint equations, which is unfavorable for solving the dynamic equations. In this paper, a multibody elastodynamic modeling of PMs based on the Lagrangian equations is proposed to fix this issue. First, we decompose the closed-loop PMs into open-loop ones by cutting open at the joints, and we propose the subassembly element that considers the flexible links and joints to avoid the singularity of the traditional constraint equations. Second, we extract the nonsingular independent coordinates for these nodes that are constrained by joints and rigid element through multi-point constraint theory and singularity analysis, and then summarized to establish the global independent generalized displacement coordinates (IGDCs). Third, we formulate the Lagrangian equations through the global IGDCs by closing the open-loop of the mechanism. The Guyuan, improved reduction system, subspace iteration method, and precision integration method are respectively presented to analyze the natural frequencies and dynamic response of the mechanism. The proposed method is computationally efficient because the computation concerning the Lagrangian multipliers are not required. Finally, the 3PRRR PM is presented to implement the proposed method.

Advanced systems for enhanced CO2 electroreduction.

Carbon dioxide (CO2) electroreduction has extraordinary significance in curbing CO2 emissions while simultaneously producing value-added chemicals with economic and environmental benefits. In recent years, breakthroughs in designing catalysts, optimizing intrinsic activity, developing reactors, and elucidating reaction mechanisms have continuously driven the advancement of CO2 electroreduction. However, the industrialization of CO2 electroreduction remains a challenging task, with high energy consumption, high costs, limited reaction products, and restricted application scenarios being the issues that urgently need to be addressed. To accelerate the progress of CO2 electroreduction towards practical application, this review shifts the research focus from catalysts to aspects such as reactions and systems, aiming to improve reaction efficiency, reduce technical costs, expand the range of products, and enhance selectivity, offering readers a new perspective. In particular, innovative and specific design strategies such as CO2 reduction coupled with alternative oxidation, co-reduction reaction of CO2 and C/N/O/S-containing species, cascade systems, and integrated CO2 capture and reduction systems are discussed in detail. Additionally, personal views on the opportunities and future challenges of the aforementioned innovative strategies are provided, offering new insights for the future research and development of CO2 electroreduction.

Structural insulation panel system (SIP) as an alternative for cooling energy saving, decarbonization, and energy cost reduction in hot and dry climates. A simulation-based approach

ABSTRACT During the last decades, the growing urban prospects represent a challenging condition to develop climate change adaptation solutions before the urban overheating effects and its challenges to the environment, human health, and building energy consumption, which is critical in hot arid climates with record-breaking heatwaves where society is turning to air conditioning instead of energy-efficient building envelopes. The primary aim of this study was to examine the influence of the Structural Insulation Panel (SIP) system heat transfer in energy-related aspects and contrast it with those of conventional construction systems. Therefore, a comparative study was carried out in low-income dwellings to measure the thermal transmittance of the building envelope and assess the thermal energy simulation allocated in Köppen-Geiger´s hot desert climate, characterized by typical maximum temperatures of 45°C in the summer season. The investigation ascertained the levels of energy consumption, the capacity of the air conditioning system, the associated energy costs, and the potential decrease in carbon footprint. The study shows SIP as a viable construction system alternative, the evidence shows a 20% heat gain reduction, the Heating, Ventilation, and Air Conditioning (HVAC) system capacity was reduced by 38%, and energy cost by 27%. The system also contributes to the decarbonization and carbon footprint by 20%. Likewise, to reduce the heat flow, a crucial element is evident, since transmittance in thermal bridges significantly affects the heat transfer in these low thermal conductivity systems with structural reinforcement elements.

Photocatalytic water splitting for large-scale solar-to-chemical energy conversion and storage

Sunlight-driven water splitting allows renewable hydrogen to be produced from abundant and environmentally benign water. Large-scale societal implementation of this green fuel production technology within energy generation systems is essential for the establishment of sustainable future societies. Among various technologies, photocatalytic water splitting using particulate semiconductors has attracted increasing attention as a method to produce large amounts of green fuels at low cost. The key to making this technology practical is the development of photocatalysts capable of splitting water with high solar-to-fuel energy conversion efficiency. Furthermore, advances that enable the deployment of water-splitting photocatalysts over large areas are necessary, as is the ability to recover hydrogen safely and efficiently from the produced oxyhydrogen gas. This lead article describes the key discoveries and recent research trends in photosynthesis using particulate semiconductors and photocatalyst sheets for overall water splitting, via one-step excitation and two-step excitation (Z-scheme reactions), as well as for direct conversion of carbon dioxide into renewable fuels using water as an electron donor. We describe the latest advances in solar water-splitting and carbon dioxide reduction systems and pathways to improve their future performance, together with challenges and solutions in their practical application and scalability, including the fixation of particulate photocatalysts, hydrogen recovery, safety design of reactor systems, and approaches to separately generate hydrogen and oxygen from water.

Fusion algorithms on identifying vacant parking spots using vision-based approach

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p>In densely populated cities, parking space scarcity results in issues like traffic congestion and difficulty finding parking spots. Recent advancements in computer vision have introduced methods to address parking lot management challenges. The availability of public image datasets and rapid growth in deep learning technology has led to vision-based parking management studies, offering advantages over sensor-based systems in comprehensive area coverage, cost reduction, and additional functionalities. This study presents an innovative fusion algorithm that integrates object detection with occupancy state algorithms to accurately identify vacant parking spaces. The employment of the YOLOv7 framework for vehicle instance segmentation, combined with three occupancy algorithms Euclidean distance (ED), intersection over reference (IoR), and intersection over union (IoU) are compared to determine the occupancy state of observed areas. The proposed method is evaluated using the CNRPark-EXT dataset, and its performance is compared with state-of-the-art methods. As a result, the proposed approach demonstrates robustness under varying conditions. It outperforms existing methods in terms of system evaluation performance, achieving accuracies of 98.88%, 97.99%, and 90.04% for ED, IoR, and IoU, respectively. This fusion detection method enhances adaptability and addresses occlusions, emphasizing YOLOv7’s advantages and accurate shape approximation for slot annotation. This study contributes valuable insights for effective parking management systems and has potential usage in the real-world implementation of intelligent transportation systems.</p></div></div></div>

A human digital twin approach for fatigue-aware task planning in human-robot collaborative assembly

Human-robot collaboration (HRC) has emerged as a pivotal paradigm in manufacturing, integrating the strengths of both human and robot capabilities. Neglecting human physical fatigue may adversely affect worker health and, in extreme cases, may lead to musculoskeletal disorders. However, human fatigue has rarely been considered for decision-making in HRC manufacturing systems. Integrating adaptive decision-making to optimise human fatigue in HRC manufacturing systems is crucial. Nonetheless, real-time perception and estimation of human fatigue and decision-making informed by human fatigue face considerable challenges. To address these challenges, this paper introduces a human digital twin method, a bidirectional communication system for physical fatigue assessment and reduction in human-robot collaborative assembly tasks. The methodology encompasses an IK-BiLSTM-AM-based surrogate model, which consists of inverse kinematics analysis (IK), bidirectional long short-term memory (BiLSTM), and attention mechanism (AM), for real-time muscle force estimation integrated with a muscle force-fatigue model for muscle fatigue assessment. An And-Or graph and optimisation model-based HRC task planner is also developed to alleviate physical fatigue via task allocation. The efficacy of this approach has been validated through proof-of-concept assembly experiments involving multiple subjects. The results show that the IK-BiLSTM-AM model achieves a minimum of 8% greater accuracy in muscle force estimation than the baseline methods. The 12-subject assessment results indicate that the task planner effectively reduces the physical fatigue of workers while performing collaborative assembly tasks.

Optimizing of selective catalytic reduction urea injection and NOx conversion analysis of diesel engine based on higher-order physical model and sequential quadratic programming algorithm

In order to maximize the NOx conversion rate and minimize NH3 slip in the diesel selective catalytic reduction (SCR) system, first, the high-order SCR model was simplified and solved using the trapezoidal method and second-order backward difference formula, while the chemical reaction parameters were optimized using the Gauss-Newton method. The results of the engine bench test show that the mean absolute errors of NH3 and NOx concentrations under steady-state operating conditions were 2.67 ppm and 1.72 ppm, respectively, and 5.46 ppm and 42.50 ppm under severe operating conditions. Second, urea injection rate is optimized based on a high-order model combined with the sequential quadratic programming (SQP) algorithm. The change in NOx conversion rate at different temperatures and air speeds is analyzed, and the results show that the NOx conversion is best at 650 K and 29,000 h⁻1. Third, the experiment validation show that the optimal NH3/NOx ratio is 0.69 at 554 K and 54,200 h⁻1; 0.8; and 1.37 at 746 K and 116,700 h⁻1. Finally, this paper simulates and analyzes the SCR emission characteristics at different temperatures and air speeds when the upstream NOx concentration is 1,000 ppm.

A lotus-inspired triphase continuous CO2 photo-thermal reduction system with wide applicability and tunable interface environment

A lotus-inspired triphase continuous CO2 photo-thermal reduction system with wide applicability and tunable interface environment

Unveiling a novel mechanism: Reduction of graphene oxide by Lysinibacillus sp. through secretion of l-ascorbic acid

The graphene oxide (GO) reduction by microorganisms has garnered considerable interest, yet the specific mechanisms underlying the bacteria secretion of reducing substances for GO reduction remain unclear. This study aims to learn that bacterial extracellular components can reduce graphene oxide through direct (contacting GO) and indirect (not contacting GO) reduction experiments. The subsequent investigation focused on identifying the specific substances secreted by bacteria capable of GO reduction. The results of non-targeted metabolomics revealed differential expression of cacid (L-AA) demonstrates a significant up-regulation. The further experiment involved the supplementation of L-AA in the reduction system of Lysinibacillus sp. with GO, demonstrating enhanced reduction efficacy, with the ID/IG ratio of reduced graphene oxide (rGO) increasing to 1.073 after 4 d of reduction with 0.5 g L−1 L-AA. Therefore, the mediation of GO reduction by L-AA secreted by Lysinibacillus sp. is proposed as a viable mechanism, offering novel insights into microbial GO reduction.

Reducing Carbon Footprint in Cooking: A Study on Energy Efficiency and Environmental Impact

The study investigates the potential reduction in carbon emissions during cooking by using air-based insulators and automated flame reduction systems. The primary focus is on minimizing heat losses to the environment and boiling inefficiencies. The study includes simulations data to quantify energy savings and equivalent carbon footprint reduction, both at the household and community levels. The findings support the development of a prototype device aimed at improving cooking efficiency. Design requirements, potential risks, failure modes, and practical implications are discussed. The paper provides a comprehensive analysis, supported by simulations, explanatory drawings, and graphs.

On the optimality of the square-root wiener time-frequency mask for noise reduction in cochlear implants

This work presents a theoretical foundation and experimental results to support the quasi-optimality of the square-root Wiener (SRW) filter for noise reduction with speech envelope preservation. The optimal time–frequency mask (TFM) for noise reduction with real-world speech envelope preservation is developed. It is demonstrated that the SRW approximates the optimal TFM for perfect envelope estimates. Attenuation functions, envelope preservation errors, and intelligibility results obtained from two objective metrics were compared for different types of noise, contamination levels, and envelope approximations. No statistically significant differences were found between the SRW and the optimal TFM results. Therefore, the SRW filter may be considered a quasi-optimal TFM for noise reduction with speech envelope preservation. This finding justifies and corroborates empirical observations recently reported in the literature about the superior intelligibility results of the SRW compared to other TFMs, such as the Wiener filter and the binary mask. These contributions are of special interest to designers of high-performance noise reduction systems in cochlear implant applications.

Legal pathways for China’s blue carbon conservation: a perspective of synergizing ocean and climate rule of law

Blue carbon serves as a significant natural carbon sink and presents substantial opportunities for greenhouse gas mitigation actions. This study first elucidates the importance of blue carbon conservation and its basis in international law, and then analyzes the progress and shortcomings of China’s efforts in blue carbon protection in the areas of legislation, enforcement, and judicial practices related to ocean governance and climate change mitigation. Finally, from the perspective of coordinating ocean and climate governance, this paper proposes legal pathways to improve blue carbon conservation. In terms of legislation, it advocates for the explicit inclusion of the legal concept of “blue carbon” in the legal frameworks governing ocean and climate governance, and for the clarification of the legal status of “blue carbon credits”. In terms of regulatory enforcement, it recommends developing a detailed implementation plan to integrate blue carbon into the China Certified Emission Reduction (CCER) system, designating a regulatory body for blue carbon trading, and establishing a multi-stakeholder governance mechanism involving government, market, and society. In the judicial realm, the paper suggests issuing judicial interpretations to clarify the scope, prerequisites, and implementation of “purchasing blue carbon credit” to prevent such purchases from becoming a “free pass” that could damage marine ecosystems

Assessing the Effects of Unit-Based Pricing on Household Waste Reduction During COVID-19 in Japan

Focusing on the COVID-19 period in Japan, this study identifies the effectiveness of a municipal unit-based pricing (UBP) system on household waste reduction through a panel data analysis targeting 770 cities for 2013–2022. It focuses on simple unit pricing (SUP) and two-tiered pricing (TTP) systems as the UBP components. As previous studies have not considered the COVID-19 period when assessing UBP, this study significantly contributes to the literature by providing new evidence. The main findings are as follows: First, SUP effectively reduced household waste even during the COVID-19 period; however, its effectiveness was slightly neutralized owing to the pandemic environment. Second, TTP also restrained household waste efficiently; however, its effect was smaller than that of SUP, and its reduction effect accelerated during the COVID-19 period (in 2020) because people became cautious about excessive waste volumes beyond the TTP criteria. The study implicates the need to expand the municipal adoption of the UBP system for household waste reduction.

In-Sensor Noise Reduction and Reservoir Computing System Using ZnO Optoelectronic Memristors for Artificial Vision Applications

In-Sensor Noise Reduction and Reservoir Computing System Using ZnO Optoelectronic Memristors for Artificial Vision Applications

Analysis of the stereoselective fate and toxicity of penflufen in the water-sediment system for risk reduction

Chiral succinate dehydrogenase inhibitor (SDHI) fungicides are widely used in agricultural production, but there is insufficient research on their environmental risk in water–sediment ecosystems. Here, the stereoselective fate and toxic effects of the chiral SDHI fungicide, penflufen, in the water–sediment system were investigated. The results showed that S-penflufen is more persistent in water, sediment, and zebrafish. Additionally, the sorption coefficient (Koc) in sediment and uptake rate constant (Ku) in zebrafish of S-penflufen were higher than those of R-penflufen. The acute toxicity of S-penflufen to zebrafish, Daphnia magna and Chironomus kiiensis were 32-, 6.1-, and 8.9-fold higher than those of R-penflufen. The AlphaFold2 and molecular docking results showed that S-penflufen had stronger binding capability with SDH in the three water–sediment organisms than R-penflufen. Therefore, S-penflufen induced stronger sub-chronic toxic effects on zebrafish than R-penflufen, even at 0.05 mg/L. The results of multi-omics analysis showed that S-penflufen affected the tricarboxylic acid cycle in zebrafish and induced antioxidant, detoxification, and immune system responses, ultimately affecting zebrafish metabolic processes and cellular function. The overall results indicate that S-penflufen has a higher risk in water–sediment systems. Moreover, combining multi-omics and AlphaFold2 techniques facilitates the elucidation of the molecular mechanism of the stereoselective toxic effects of chiral pesticides.

Novel Single Perovskite Material for Visible-Light Photocatalytic CO2 Reduction via Joint Experimental and DFT Study.

Developing advanced and economically viable technologies for the capture and utilization of carbon dioxide (CO2) is crucial for sustainable energy production from fossil fuels. Converting CO2 into valuable chemicals and fuels is a promising approach to mitigate atmospheric CO2 levels. Among various methods, photocatalytic reduction stands out for its potential to reduce emissions and produce useful products. Here, novel perovskite ZnMoFeO3 (ZMFO) nanosheets are presented as promising semiconductor photocatalysts for CO2 reduction. Experimental results show that ZMFO has a narrow bandgap, exceptional visible light response, large specific surface area, high crystallinity, and various surface-active sites, leading to an impressive photocatalytic CO2 reduction activity of 24.87 µmolg-1h-1 and strong stability. Theoretical calculations reveal that CO2 conversion into CO and CH4 on the ZMFO surface follows formaldehyde and carbine pathways. This study provides significant insights into designing innovative perovskite oxide-based photocatalysts for economical and efficient CO2 reduction systems.

Three-dimensional MoS2@GF cathode design based on substrate and boundary effects: Enhancement of bilayer capacitance and exposure of edge active sites for efficient mercury removal from wastewater

Mercury ions are present in water bodies through various processes and human activities, causing pollution to the environment and potential health risks to humans. In order to achieve the purification of mercury-containing wastewater and recycle of mercury resources, we designed a novel electrochemical reduction system to treat mercury-containing wastewater. MoS2@GF electrode was prepared by one-step solvothermal method. In the electrocatalytic reduction system MoS2@GF was the cathode and IrO2/Ti was the anode, and the reduction mechanism and optimal reaction conditions were investigated. The topological defects of GF can enable the uniformly distributed MoS2 to expose a large number of S-vacancies, which can quickly utilize water molecules to produce H* with strong reductivity, and the anode produces ·O2−. These free radicals can efficiently and indirectly reduce Hg2+ to Hg0. Under the conditions of voltage 2 V, electrode spacing 20 mm and stirring rate 200 r/min, the cathode achieves 96.3 % Hg2+ removal efficiency for 50 mg/L HgSO4–10 % H2SO4 solution in 0.5 h. The above research provides a novel method that can recover and utilize mercury resources efficiently and a thought for the application of electrochemical method to the treatment of heavy metal wastewater.

Catanionic Surfactant Systems for Emulsifying and Viscosity Reduction of Shale Oil

Shale oil resources are abundant in the second member of the Kongdian Formation, Cangdong Sag, Bohai Bay Basin, China. However, the shale oil here has high viscosity and poor fluidity, resulting in low recovery and huge difficulty in development, gathering, and transporting. This study assembled a catanionic surfactant (PSG) through electrostatic interactions between cetyltrimethylammonium bromide (CTAB) and α-olefin sulfonate (AOS) in an aqueous phase, which can be used as an effective emulsifying and viscosity-reducing agents for shale oils of Dagang oilfield. The interfacial activity and emulsification performance of PSG can be optimized by changing the molar ratio of CTAB to AOS. Notably, the PSG assembled at the molar ratio of 6:4 shows the best performance, with ultra-high surface activity and excellent salt resistance. At an oil/water ratio of 1:1 and 50 °C, an aqueous solution of 0.2% PSG can emulsify five types of shale oil, making it form shale oil-in-water (O/W) emulsion with a viscosity of less than 35 mPa·s, thereby reducing the viscosity of shale oil and improving its flowability. Importantly, shale oil and water can be separated by simple sedimentation without adding demulsifiers. This study has important guiding significance for the efficient development and transportation of shale oil.

Experimental study of SCR DeNOX efficiency at low exhaust gas temperatures

The DeNOX efficiency of the Selective Catalyst Reduction (SCR) system relates closely to the urea injection, and the starting injection time of urea injection depends on the exhaust gas temperature. For the diesel vehicle driving on real roads, the exhaust gas temperatures change significantly. At high temperatures, the SCR system actively injects urea; whereas at low temperatures, no urea injection happens and the catalyst reaction relies solely on the stored ammonia in the catalytic container. Thus, it is important to investigate the SCR DeNOX efficiency under condition of different temperature ranging from low to high temperature. In this paper, a heavy-duty diesel vehicle was tested under stationary idling condition with first rapid acceleration, then high-speed holding running and finally deceleration, and the NOX emission performance at various exhaust temperatures was acquired under two distinct operating conditions: active injection of ammonia at higher temperatures and no ammonia injection at lower temperatures. Furthermore, a deep learning model was built for predicting NOX downstream of the SCR by utilizing exhaust flow rate, average exhaust temperature, and NOX emission concentration upstream of the SCR as input parameters, and this model was verified with a model fit of 0.98. The results show that the SCR DeNOX efficiency achieves 99 % with active urea injection during high-temperature stages, and 30–40 % during low-temperature stages, relying on ammonia storage. During the ammonia storage stage, the SCR DeNOX efficiency exhibits high sensitivity to temperature, with a rate of decreases of 1.3 %/°C per unit temperature. In the active ammonia injection stage, the SCR DeNOX efficiency decreases at a rate of 0.5 %/°C per unit temperature. Various reaction stages exhibit a significant relationship between SCR DeNOX efficiency and exhaust temperature.