Reduction System Research Articles

S-Fe/Co@GC reduction-oxidation sequential reaction system for the high-efficiency mineralization of tetrabromobisphenol A in water

The lipophilic, bioaccumulative, persistent nature of Tetrabromobisphenol A (TBBPA) contributes to its widespread detection in various environmental media, posing significant negative implications for the living environment and human health. In this study, a reduction system and a reduction-oxidation sequential reaction system were developed using a magnetic core-shell bimetallic amendment (S-Fe/Co@GC) to investigate the degradation and mineralization properties of TBBPA. Additionally, the degradation mechanism and degradation pathway of TBBPA in various systems were analyzed. In the sole S-Fe/Co@GC reduction system, sulfurized nano-zero-valent iron (S-Fe) and Co0 exhibited remarkable reductive capabilities towards TBBPA. The reaction of S-Fe/Co@GC gradually facilitated the debromination of TBBPA, ultimately leading to its conversion into bisphenol A. The reaction process demonstrated the synergistic effect among S-Fe, Co0, and graphite carbon, leading to a remarkable enhancement in the reduction performance of the material. Consequently, TBBPA removal efficiency reached 97.5% within a time frame of 10 h. In the reduction-oxidation sequential reaction system, the debromination of TBBPA during the reduction stage enhanced the subsequent oxidation stage's total organic carbon (TOC) removal rate. During the oxidation stage (0.03 mmol of PMS added at 30 min), TBBPA underwent attack by SO4·-, ·OH, O2·-, and 1O2, leading to cleavage and opening of its structure. This process resulted in the conversion of TBBPA into short-chain fatty acids, ultimately mineralizing it into CO2 and H2O. Thus, this degradation pathway mitigated potential environmental risk associated with intermediates. The final TOC removal rate significantly increased to 72.7% when the dose of composite material was set at 1.0 g/L, surpassing that achieved by the conventional advanced oxidation system. Hence, the S-Fe/Co@GC reduction-oxidation sequential reaction system provides a new strategy for treating high-concentration TBBPA-contaminated 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>

Machine Learning-Based Precise Monitoring of Aluminium-Magnesium Alloy Dust

： Al-Mg alloys are widely used in industrial production, which can lead to occupational health issues and explosion hazards. The study focuses on applying a machine learning-enhanced Kalman filtering algorithm to detect the concentration of Al-Mg alloy dust, significantly reducing dust hazards and constructing an efficient and safe dust reduction and removal system. A machine learning-based Kalman filter algorithm is proposed for fast and accurate detection of high Al-Mg dust concentrations (200-1200 g/m³). The results show that the KFGRU approach outperforms the traditional line filter method, achieving answer times between 2.6 s and 6 s—an improvement of 62.5% over the traditional method. As far as the forecast accuracy is concerned, the KFGRU method yields a minimal curve deviation value, reaching as low as 0.097, which represents a significant improvement compared to the 0.151 of the Kalman filter algorithm, the 0.217 of the sliding average method, and the 0.177 of the median filter methods.

Sturgeon-MKIV: Constraint-Based Level and Playthrough Generation with Graph Label Rewrite Rules

Procedurally generated game levels should be completable. The representation used for levels and game mechanics impacts the types of games for which different techniques can be applied. Previous work used a constraint solving approach to simultaneously generate levels with example playthroughs, showing they can be completed using the game's mechanics. However, that work used 2D grid-based rewrite rules. In this work, we extend previous approaches by representing levels as more general graphs, and game mechanics as rewrites on node and edge labels of subgraphs. Using this approach, graph-based levels with playthroughs are generated. We describe the approach and demonstrate its application in some games with graph-based levels.

Revisiting Kabardian Phonology: A Syllabic Analysis

This paper provides an autosegmental analysis of phonological alternations in Kabardian, an Abhkaz-Adyghean language. It illustrates how several phonological re-write rules, postulated in Colarusso’s (1992) phonological analysis of Kabardian which, in some cases, lacks adequate explanation, may be uniformly reinterpreted as instances of mapping between the segmental tier and the skeletal tier in an autosegmental approach. In doing so, this paper illustrates a case where the skeletal make-up of a language may be dominant over underlying segments and be crucial in determining the output forms of a language, a process which may be translated into high-ranking constraints under a constraint-based framework. This paper, therefore, provides a more economical and explanatorily adequate analysis of Kabardian phonological alternations.

Chiral SPINOL‐Derived Borophosphate‐Catalyzed Asymmetric 1,4‐Reduction of Exocyclic α,β‐Unsaturated Ketones

AbstractAn asymmetric 1,4‐reduction of exocyclic α,β‐unsaturated ketones, yielding diverse optically active α‐substituted tetralones, has been achieved using a chiral SPINOL‐derived borophosphate catalyst. The enantioselectivity‐determining step of the reaction involves the protonation of a highly active boron enolates intermediate. This catalytic reduction system, comprising chiral SPINOL‐derived borophosphate and pinacolborane, has potential for broader application in other asymmetric reduction reactions.

Finding k Shortest Paths in Cayley Graphs of Finite Groups

We present a new method for finding k shortest paths between any two vertices in the Cayley graph Cay(G,S)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {Cay}(G, S)$$\\end{document} of a finite group G with its generating set S closed under inverses. By using a reduced convergent rewriting system R for G, we first find the lexicographically minimal shortest path between two vertices in Cay(G,S)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {Cay}(G, S)$$\\end{document}. Then, by symmetrizing the length-preserving rules of R, we provide a polynomial time algorithm (in the size of certain rewrite rules, the lexicographically minimal shortest path, and k) for finding k shortest paths between two vertices in Cay(G,S)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {Cay}(G, S)$$\\end{document}. Our implementation of finding k shortest paths between two vertices in Cay(G,S)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {Cay}(G, S)$$\\end{document} is also discussed.

A solving new method for the urea-selective catalytic reduction (SCR) system in a diesel engine using coupled hyperbolic-parabolic partial differential equations (PDEs)

To control the diesel engine urea SCR system with high accuracy, firstly, the partial differential equations of the SCR system are simplified through variable substitution and the method of characteristic lines to eliminate the partial derivative terms of the hyperbolic partial differential equations in the flow direction. The backward difference method is used to solve the problem, and the adaptive time step is adjusted to improve computational efficiency. Secondly, the Levenberg-Marquardt algorithm is applied to identify the model parameters per second based on the 1800-s test bench data. By combining the experimental data with the parameter identification results, this paper calculated the downstream NOx concentration with 99.5 % accuracy. Finally, the 1800s transient test data was applied to a commonly used single-state SCR control model, and cell numbers 1–4 of the cases were numerically simulated. It was found that the reduced-order model had a computation time of 1 s but was less accurate. When the test data was applied to the model presented in this study, the calculation time was 27s, and the model's calculation results show that the average error of the downstream NOx concentration is 16.95 ppm, which is 14.3 ppm lower than that of the two-cell one-state model.

Human Adaption to Climate Change: Marine Disaster Risk Reduction in the Era of Intelligence

With the intensification of global warming and sea level rise, extreme weather and climate events occur frequently, increasing the probability and destructive power of marine disasters. The purpose of this paper is to propose the specific application of artificial intelligence (AI) in marine disaster risk reduction. First, this paper uses computer vision to assess the vulnerability of the target and then uses CNN-LSTM to forecast tropical cyclones. Second, this paper proposes a social media communication mechanism based on deep learning and a psychological crisis intervention mechanism based on AIGC. In addition, the rescue response system based on an intelligent unmanned platform is also the focus of this research. Third, this paper also attempts to discuss disaster loss assessment and reconstruction based on machine learning and smart city concepts. After proposing specific application measures, this paper proposes three policy recommendations. The first one is improving legislation to break the technological trap of AI. The second one is promoting scientific and technological innovation to break through key technologies of AI. The third one is strengthening coordination and cooperation to build a disaster reduction system that integrates man and machine. The purpose of this paper is to reduce the risk of marine disasters by applying AI. Furthermore, we hope to provide scientific references for sustainability and human adaptation to climate change.

An Ambient Measurement Technique for Vehicle Emission Quantification and Concentration Source Apportionment.

We develop a new technique called plume regression where fast response instruments located at the roadside are used to measure exhaust plumes of passing vehicles. The approach is used to generate highly disaggregated vehicle emissions information by vehicle type, which compares well with traditional vehicle emission remote sensing. Additionally, the technique provides valuable new information on ambient concentration source apportionment by vehicle type. The technique is flexible enough to consider a wide range of air pollutants and be deployed at roadside ambient monitoring locations. The new approach is used to quantify emissions and concentration source apportionment for ammonia (NH3) and nitrogen oxides (NOx). We find that emissions of NH3 are generally very well controlled from diesel vehicles including those with selective catalytic reduction systems that use NH3 to reduce emissions of NOx. By contrast, gasoline passenger cars are shown to be the dominant contributor to NH3 emissions, which increase with vehicle mileage. Average fuel-specific NH3 emission factors for gasoline vehicles range from 0.3 to 1.2 g kg-1, while diesel vehicle emission factors remain below 0.06 g kg-1, with the exception of Euro VI buses with the latest regulatory provisions (0.5 g kg-1).

Techno-economic analysis of hybrid renewable energy systems for cost reduction and reliability improvement using dwarf mongoose optimization algorithm

The global energy crisis, particularly in isolated and remote regions, has increased interest in renewable energy sources (RESs) to meet growing energy demands. Integrating RESs with energy storage systems offers a promising solution to mitigate fluctuations and intermittency, but concerns about cost and reliability remain. This study explores the optimal design of various microgrid configurations, combining photovoltaic (PV), wind turbine (WT), battery energy storage system (BESS), and diesel generator (DG) systems for Najran city, Saudi Arabia, via real-world meteorological and load demand data. The Dwarf Mongoose Optimization Algorithm (DMOA), alongside the salp swarm algorithm (SSA) and whale optimization algorithm (WOA), was applied to minimize the levelized cost of energy (LCOE) while improving system reliability. The results demonstrate that the PV/BESS configuration, although cost-effective with an LCOE of 0.038 USD/kWh, fail to meet reliability constraints with a loss of power supply probability (LPSP) of 0.679. In contrast, the PV, WT, BESS, and DG configurations achieved an LPSP of 1.9 × 10^--8% with an LCOE of 0.199 USD/kWh, offering a robust and reliable solution for the region's energy needs. This paper presents a novel application of the DMOA for optimizing hybrid renewable energy systems, demonstrating its effectiveness in achieving a balance between cost and reliability. This strategy provides a viable approach for sustainable energy planning in similar regions facing energy challenges.

Masked Divalent Reactivity of Heterobimetallic Lanthanide Isocarbonyl Complexes

A new rare‐earth reduction system is described in which trivalent yttrium and dysprosium react as though present in their unstable divalent oxidation state. This masked divalent reactivity is achieved using the isocarbonyl‐bridged dimers [(Cpttt2M)(μ‐Fp)]2 (M = Y, 1Y; M = Dy, 1Dy; Cpttt = 1,2,4‐C5tBu3H2; Fp = CpFe(CO)2), where the reducing electrons originate from the bridging [Fp]– ligands. The reactivity of 1Y and 1Dy is showcased by reducing the N‐heterocycles 2,2'‐bipyridyl (bipy), phenazine (phnz) and hexaazatrinaphthylene (HAN) to give corresponding mono‐, di‐ and tri‐metallic rare‐earth complexes, respectively, with the heterocyclic ligands present in their singly, doubly and triply reduced forms, respectively. The dynamic magnetic properties of the dysprosium compounds are described. Compound 1Dy is a single‐molecule magnet (SMM) with an appreciable energy barrier of 449(17) cm–1, whereas [(Cpttt2Dy)2(m‐phnz)] (3Dy) is not an SMM because of a strong, competing equatorial crystal field. Surprisingly, [(Cpttt2Dy)3(HAN)] (4Dy) is also not an SMM, the origins of which are traced to the impact of the tert‐butyl substituents on the dysprosium centre and its interaction with the radical [HAN]3– ligand.

Masked Divalent Reactivity of Heterobimetallic Lanthanide Isocarbonyl Complexes.

A new rare-earth reduction system is described in which trivalent yttrium and dysprosium react as though present in their unstable divalent oxidation state. This masked divalent reactivity is achieved using the isocarbonyl-bridged dimers [(Cpttt2M)(μ-Fp)]2 (M = Y, 1Y; M = Dy, 1Dy; Cpttt = 1,2,4-C5tBu3H2; Fp = CpFe(CO)2), where the reducing electrons originate from the bridging [Fp]- ligands. The reactivity of 1Y and 1Dy is showcased by reducing the N-heterocycles 2,2'-bipyridyl (bipy), phenazine (phnz) and hexaazatrinaphthylene (HAN) to give corresponding mono-, di- and tri-metallic rare-earth complexes, respectively, with the heterocyclic ligands present in their singly, doubly and triply reduced forms, respectively. The dynamic magnetic properties of the dysprosium compounds are described. Compound 1Dy is a single-molecule magnet (SMM) with an appreciable energy barrier of 449(17) cm-1, whereas [(Cpttt2Dy)2(m-phnz)] (3Dy) is not an SMM because of a strong, competing equatorial crystal field. Surprisingly, [(Cpttt2Dy)3(HAN)] (4Dy) is also not an SMM, the origins of which are traced to the impact of the tert-butyl substituents on the dysprosium centre and its interaction with the radical [HAN]3- ligand.

Preparation and NH3 adsorption behavior of porous magnesium oxychloride cement-based SrCl2

In addressing challenges in Selective Catalytic Reduction (SCR) systems in vehicles, the development of novel SrCl2 composite materials with high ammonia adsorption and structural stability is crucial. In this context, we employed the porous magnesium oxychloride cement (PMOC) as a carrier material, successfully fabricating a mesoporous PMOC-SrCl2 material via solution impregnation technology. Simultaneously, we employed various characterization techniques such as XRD, full-pore analysis, TG, SEM, TEM, and EDS to examine the material. We conducted static adsorption assessments on numerous candidate materials at 0.1Mpa and 293.15 K. The synthesized C3 series material (Mass ratio of SrCl2 to PMOC = 10:3), solution impregnated for 1 h, exhibited exceptional ammonia adsorption capacity (up to 38.01 mmol·g−1). Through model fitting of experimental data, we discovered that the adsorption process of this material closely aligns with the pseudo-second-order kinetic model and the Langmuir model. Over an adsorption time span of 180 min, the adsorption rate of the composite material increased by 129 % compared to pure SrCl2. In the cycle performance testing phase, we observed that the material exhibited no significant degradation in performance after undergoing 10 cycles of adsorption/desorption. This structurally stable, cost-effective, and readily accessible high-efficiency ammonia adsorption material undoubtedly possesses immense potential to solve the application challenges of ammonia adsorption materials within automotive selective catalytic reduction systems.

Longer-term compliance benefits of oncology-specific smart pump drug error reduction systems.

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.

An Evidence-Based Comprehensive Review of Laughter Therapy in Depression Management

Abstract: Depression is a widespread mental health challenge, necessitating diverse therapeutic approaches. Emerging research suggests that laughter may offer a valuable adjunctive intervention for individuals grappling with depressive symptoms. This review systematically investigates the multifaceted relationship between laughter and depression, elucidating the underlying mechanisms and potential therapeutic benefits. A comprehensive literature search was conducted across multiple electronic databases, including PubMed, PsycINFO, Scopus, and Google Scholar. Keywords used in the search included “laughter therapy,” “humor,” “depression,” “mental health,” and “psychological well-being.” The search was limited to articles published in English and included both peer-reviewed journal articles and relevant gray literature. Relevant data were extracted from each study, including the study design, sample size, participant characteristics, type of laughter intervention, duration and frequency of the intervention, outcome measures, and key findings. The extracted data were organized into tables to facilitate comparison across studies. By synthesizing findings from clinical studies, neuroscience research, and anecdotal evidence, this review examines the physiological, psychological, and social dimensions of laughter's impact on depression. Special attention is given to neurochemical pathways, stress modulation, cognitive restructuring, and social dynamics. The physiological effects of laughter on depression encompass neurochemical regulation (endorphins, serotonin, dopamine), stress reduction, and immune system modulation. Psychologically, laughter contributes to cognitive reframing, enhanced coping mechanisms, and mood regulation. Socially, it strengthens social bonds, mitigates social isolation, and fosters a positive social environment. In conclusion, this review synthesizes current knowledge on the healing potential of laughter in mitigating depression, providing a holistic understanding of its multifaceted impact. The findings underscore the importance of integrating laughter-based interventions into mental health care practices and highlight avenues for future research and clinical applications in the realm of depression treatment.

Effects of Roller Milling Parameters on Wheat-Flour Damaged Starch: A Comprehensive Passage Analysis and Response-Surface Methodology Optimization.

Damaged starch typically arises from mechanical damage caused by the action of the roller mills during the wheat flour milling process. The content of resulting damaged starch in the flour significantly influences its characteristics, emphasizing the importance of understanding and controlling the formation of damaged starch for the production of specialized flours. A detailed passage analysis from three different commercial mills revealed that starch damage control is primarily achievable at front passages of the sizing and reduction system, which generate the majority of the flour release in the mill. Also, it revealed that damaged starch content increases progressively from the initial to the final passages during milling in the break, sizing and reduction system. To investigate the effects of milling parameters on damaged starch, flour yield, and energy consumption, a three-level and three-variable Box-Behnken experimental design with response surface methodology was applied. As independent variables roll gap (0.05-0.35 mm), feed rate (0.15-0.35 kg/cm min), and fast roll speed (400-800 rpm) were employed. The obtained models were utilized to optimize milling conditions for producing flours with special characteristics.

Emulsification and interfacial characteristics of different surfactants enhances heavy oil recovery: experimental evaluation and molecular dynamics simulation study

The high viscosity and poor fluidity of heavy oil challenge its extraction, leading to the widespread use of surfactant emulsification to reduce viscosity and enhance recovery. This study evaluated three surfactants—sodium dodecyl sulfate (SDS), sodium oleate (SO), and APG0810—for their suitability and effectiveness in the X reservoir. The solution properties of these surfactants were analyzed and their micro-mechanisms investigated using MD calculations. The effects of surfactant concentration and additives on emulsification and viscosity reduction were elucidated. Ultimately, a system for emulsification and viscosity reduction was selected for physical simulation research. The experimental findings show that SO reduces interfacial tension from 52.4 mN/m to 0.0027 mN/m, transforming lipophilic surfaces into hydrophilic. MD analyses reveal SO’s optimal interfacial properties, with the lowest interfacial energy of −6423.4 kcal/mol, maximum interfacial thickness of 2.56 nm, and minimal diffusion coefficient of 0.4087 Å2/ps at the oil-water interface. These findings align with experimental results, confirming SO’s superior interfacial properties. Combining 0.3% SO with 0.5% n-pentanol results in a 98% viscosity reduction. The emulsion shows excellent stability, with no water separation in the first 30 min and only 8.3% after 2 h. Physical simulation results show that in high(low) permeability core displacement experiments, system flooding and subsequent water flooding can increase recovery rates by 15.39%(36.91%), indicating the system’s potential for enhancing oil recovery in Reservoir X. The findings suggest that the implementation of this system not only boosts the crude oil recovery rate but also carries economic significance in the industry.

Numerical study of magneto convective ag (silver) graphene oxide (GO) hybrid nanofluid in a square enclosure with hot and cold slits and internal heat generation/absorption

Energy transmission is widely used in various engineering industries. In recent times, the utilization of hybrid nanofluids has become one of the most popular choices in various industrial fields to increase thermal performance and enhance power generation, entropy reduction, solar collectors, and solar systems. Motivated by this wide range of applications, the present article explores the mixed convection flow and heat transfer of magnetohydrodynamic \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:Ag$$\\end{document} (Silver) and \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:GO$$\\end{document} (Graphene) nanofluids hybrid nanofluids in a square enclosure with heat generation/absorption by using the MAC method. The vertical walls of the enclosure are assumed to be adiabatic. The horizontal walls are also assumed adiabatic except for the center portion of the top and bottom walls of the cavity. The center portion of the horizontal upper wall is maintained as a cold is \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:{(T}_{c})$$\\end{document}and the lower wall is maintained as hot \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\left({T}_{h}\\right)$$\\end{document}. The dimension equations are transformed into dimensionless form and then discretized and solved with the finite difference Marker and cell (MAC) method. Numerical modelling is implemented, by changing Richardson number \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\left(Ri\\right)$$\\end{document}, The results are located graphically using MATLAB software. The Nusselt number graph was displayed for the Reynolds number (Re), Richardson number\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\:\\left(Ri\\right)$$\\end{document}, and Hartmann number \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\left(Ha\\right)$$\\end{document}. The findings show that enhancing the values of the Richardson number and Reynolds number enhances the Nusselt number values except for the Hartmann number. The findings indicate that the combination of the new model is very good at predicting thermal conductivity and correlates experimental results well. The augmenting strength of magnetic force diminishes fluid flow. Developing the coefficients for the heat source and sink improves energy transmission and heat transfer enhancement. Hybrid nanofluids like \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:Ag-GO$$\\end{document} enhance heat transfer and efficiency. They improve cooling in heat exchangers, radiators, and electronics, boost solar energy systems, aid in cancer treatment and drug delivery, enhance geothermal and wind turbine efficiency, and improve manufacturing processes. Overall, they optimize thermal management in various applications.

An Engineered Imine Reductase for Highly Diastereo‐ and Enantioselective Synthesis of β‐Branched Amines with Contiguous Stereocenters

Abstractβ‐Branched chiral amines with contiguous stereocenters are valuable building blocks for preparing various biologically active molecules. However, their asymmetric synthesis remains challenging. Herein, we report a highly diastereo‐ and enantioselective biocatalytic approach for preparing a broad range of β‐branched chiral amines starting from their corresponding racemic ketones. This involves a dynamic kinetic resolution‐asymmetric reductive amination process catalyzed using only an imine reductase. Four rounds of protein engineering endowed wild‐type PocIRED with higher reactivity, better stereoselectivity, and a broader substrate scope. Using the engineered enzyme, various chiral amine products were synthesized with up to >99.9 % ee, >99 : 1 dr, and >99 % conversion. The practicability of the developed biocatalytic method was confirmed by producing a key intermediate of tofacitinib in 74 % yield, >99.9 % ee, and 98 : 2 dr at a challenging substrate loading of 110 g L−1. Our study provides a highly capable imine reductase and a protocol for developing an efficient biocatalytic dynamic kinetic resolution‐asymmetric reductive amination reaction system.