Reduction System Research Articles

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.

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.

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-second 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 second 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.

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.

Cost-effective non-revenue water reduction: analysis through pilot activities in Kigali City, Rwanda

ABSTRACT Non-revenue water (NRW) is a major problem for water utilities, and its reduction has become an important challenge in ensuring a sustainable water supply. However, a lack of clarity regarding the cost–benefit analysis of investment in pilot activities to reduce NRW may hinder further investment in such projects. Thus, we attempted to identify strategies for effective NRW reduction and establish a method for estimating their cost-effectiveness. To this end, a project to strengthen the NRW management capacity and build a sustainable NRW reduction system was implemented in Kigali City, Rwanda, between 2016 and 2021. The project included four objectives: enhancement of the planning capacity for NRW reduction; acquisition of basic knowledge, skills, and techniques for NRW control; enhancement of staff capacity to execute NRW reduction measures; and establishment of a system to accurately measure NRW ratios. The project helped to formulate a 5-year plan for NRW reduction and 596 employees of Kigali City were trained for the same. The NRW ratios were reduced by 10 and 12% in the two pilot areas of the city. Cost–benefit analysis revealed the effectiveness of the investment in NRW reduction activities over time.

Electronic Effects in Cobalt Phthalocyanine Catalysts Towards Noble-Metal-Free, Photocatalytic CO2-to-CO Reduction

Noble-metal-free CO2 reduction systems based on cobalt phthalocyanine (CoPc) and its derivatives have demonstrated remarkable photocatalytic performances; however, their structure-activity relationship with electronic tuning remains unexplored. Herein, we now provide a systematic study to investigate the electron effects of substituents on the CoPc family in photocatalytic CO2 reduction, where a Cu(I) heteroleptic photosensitizer is utilized. The highest performance can be achieved using cobalt tetracarboxylphthalocyanine in light-driven CO2-to-CO reduction, with a maximum turnover number of 2950 at 450 nm and an outstanding apparent quantum yield of 63.5% at 425 nm, over ten times the activity with the tetra-dimethylamino-substituted CoPc derivative. The favorable electron-withdrawing effects have been further verified by DFT calculations and cyclic voltammetry, which reduces the overpotential required for CO2 reduction and decreases the Gibbs free energy of the catalyst active intermediates, particularly the CO-desorption energetics.

Design of Hydrogen Combustion Engine (Conceptual Brainstorming)

Hydrogen combustion engines present a promising pathway for cleaner transportation, leveraging existing internal combustion engine (ICE) technologies. The design of hydrogen-fueled ICEs requires significant modifications to conventional gasoline or diesel engines due to hydrogen’s distinct combustion properties. This research outlines the key design considerations for hydrogen combustion engines, including fuel storage and injection, combustion chamber modifications, ignition control, and exhaust treatment. The study also discusses recent advancements in engine efficiency, NOx reduction, and dual-fuel systems, along with the challenges of implementing hydrogen-based ICEs in commercial applications. Keywords: hydrogen, combustion, design, ICE, alternative fuels

Sustainable Logistics: Synergizing Passive Design and PV–Battery Systems for Carbon Footprint Reduction

As more companies strive for net-zero emissions, mitigating indirect greenhouse gas emissions embedded in value chains—especially in logistics activities—has become a critical priority. In the European logistics sector, sustainability and energy efficiency are receiving growing attention, given the sector’s intersectional role in both transportation and construction. This transition toward low-carbon logistics design not only reduces carbon emissions but also yields financial benefits, including operational cost savings and new market opportunities. This study examines the impact of passive design strategies and low-carbon technologies in a Swedish logistics center, assessed using the low-carbon design criteria from the BREEAM International standard, version 6. The findings show that passive energy-efficient measures, such as the installation of 47 skylights for natural daylighting, reduced light power density in accordance with AHSHARE 90.1-2019 and the integration of free night flushing, contribute to a 23% reduction in total energy consumption. In addition, the integration of 600 PV panels and 480 batteries with a capacity of 268 ampere-hours and 13.5 kWh storage, operating at 50 volts, delivers a further 56% reduction in carbon emissions. By optimizing the interaction between passive design and active low-carbon technologies, this research presents a comprehensive feasibility analysis that promotes sustainable logistics practices while ensuring a future-proof, low-carbon operational model.

Economic Benefits and Uses of Indigenous Seasonal Weather Forecasts in Zimbabwe

This study presents a seminal contribution regarding the economic value of indigenous seasonal weather forecasts in Zimbabwe. Many farmers (58%) use indigenous seasonal weather forecasts to make maize farming decisions such as selecting suitable varieties. The main indicators used for indigenous seasonal weather forecasts are flowering and fruition of specific trees. Based on travel cost analysis, which incorporates a multi-purpose visit scenario, the study establishes the economic importance of indigenous seasonal weather forecasts with a consumer surplus of US$1,044 per year among the 290 farmers using the forecasts. There is therefore a need to integrate indigenous weather forecasts into national seasonal weather forecasting and disaster risk reduction systems to complement modern seasonal weather forecasts. Co-production of seasonal weather forecasts with farmers is proposed in this regard. This further calls for the need to digitally document, visualize, and disseminate indigenous seasonal weather forecast indicators to a wider audience to increase their use.

Reduction in Optical Feedback Noise of Atomic Force Microscopy by High-Frequency Current Modulation

Introduction: With the advancement of technology, nanotechnology has emerged as a prominent research field. The Atomic Force Microscope (AFM) serves as a vital tool in nanoscience and technology, playing an indispensable role across various domains. Method: However, in the AFM photoelectric sensing system, the optical feedback noise from the beam deflection method can lead to inaccuracies in signal identification and analysis, impacting the accuracy and reliability of AFM measurements. To mitigate this interference, this study proposes a highfrequency current superposition system aimed at reducing optical feedback noise. By superimposing high-frequency currents, the semiconductor laser transitions from a single-mode to a multi-mode operational state, thereby altering its mode of operation and consequently reducing optical feedback noise during sensing. Initially, mathematical modeling and simulation analysis were conducted on the high-frequency current superposition noise reduction system to examine the impact of high-frequency current on the intensity noise of the semiconductor laser. Subsequently, the design of the high-frequency current superposition noise reduction system was outlined, encompassing the development of a constant current drive circuit, a voltage-controlled oscillator circuit, and a biasing circuit. Finally, the high-frequency current superposition noise reduction system underwent testing. Results: During the high-frequency current superposition noise reduction test, the system's Signal-to-Noise Ratio (SNR) increased from 15.57 dB to 17.81 dB, and the system's noise peak-to-peak value decreased from 8 mV to 6 mV. Analysis of the superposition frequency and noise reduction effect determined the optimal superposition frequency of the AFM photoelectric sensor system to be 400 MHz. Characterization experiments of the high-frequency superposition noise reduction system compared the clarity of Escherichia coli images before and after noise reduction. Conclusion: The aforementioned experimental results demonstrated that high-frequency current superposition is an effective noise reduction method capable of mitigating optical noise in the AFM photoelectric sensing system.