bluuebunny/crossref_metadata_2025 huggingface dataset:
Use of Smart Glasses for Boosting Warehouse Efficiency: Implications for Change Management
Authors: Epe Markus , Azmat Muhammad , Islam Dewan Md Zahurul , Khalid Rameez
Published: October 2024

Background: Warehousing operations, crucial to logistics and supply chain management, often seek innovative technologies to boost efficiency and reduce costs. For instance, AR devices have shown the potential to significantly reduce operational costs by up to 20% in similar industries. Therefore, this paper delves into the pivotal role of smart glasses in revolutionising warehouse effectiveness and efficiency, recognising their transformative potential. However, challenges such as employee resistance and health concerns highlight the need for a balanced trade-off between operational effectiveness and human acceptance. Methods: This study uses scenario and regression analyses to examine data from a German logistics service provider (LSP). Additionally, structured interviews with employees from various LSPs provide valuable insights into human acceptance. Results: The findings reveal that smart glasses convert dead time into value-added time, significantly enhancing the efficiency of order picking processes. Despite the economic benefits, including higher profits and competitive advantages, the lack of employee acceptance due to health concerns still needs to be addressed. Conclusions: After weighing the financial advantages against health impairments, the study recommends implementing smart glass technology in picking processes, given the current state of technical development. This study’s practical implications include guiding LSPs in technology adoption strategies, while theoretically, it adds to the body of knowledge on the human-technology interface in logistics.
An Inverted-Sandwich Dichromium(I) Complex Stabilized by Guanidinate Ligands
Authors: Noor Awal , Qayyum Sadaf , Dickert Andre , El Oirdi Mohamed
Published: October 2024

Reduction of the four-coordinate “ate” species [(RC(NAr)2Cr(µ-Cl)2Li(THF)2] (1) (R = diisopropylamine; Ar = 2,6-diisopropylphenyl) with potassium graphite (KC8) in toluene leads to the formation of a toluene-bridged inverted-sandwich dichromium(I) complex, (µ-η6:η6-C7H8)[Cr{RC(NAr)2}]2 (2). X-ray analysis confirms the dinuclear nature of (2). The compound [C69H104Cr2N6], crystallized in the monoclinic space group, P21/c, has the following cell parameters: a  =  15.108(3) b  =  29.155(6) c  =  17.486(4) Å, β  =  101.19(3)°, V  =  7555(3) A3, and Z  =  4.
The Effect of Calcium Sulfate on the Hydration and Properties of Red Mud-Based Calcium Ferroaluminate Cement Clinker
Authors: Shi Nan , Ma Ya , Zhang Xiang , Li Jun , Lu Xiaolei , Zhang Lina , Cheng Xin
Published: October 2024

The hydration of high-alkali red mud-based ferroaluminate cement (RCFA) clinker with calcium sulfate needs to be regulated. This study explored the effects of the calcium sulfate type and dosage on the hydration and properties of high-alkali RCFA clinker. The research results show that when 4% gypsum was added, the 3 d compressive strength of cement was 39.1 MPa, and the 28 d compressive strength was 63.2 MPa. The 28 d strength increased by 61.6% compared with the 3 d strength. The properties of cement paste can be adversely affected by excessive anhydrite content. The exothermic hydration of clinker was accelerated by calcium sulfate at the beginning, but the rate declined as the process progressed. Sufficient sulfur supply can enhance the hydration of ye’elimite, thereby increasing the AFt content in the hydration product. The mass loss of the hydration product is mainly caused by the dehydration of ettringite, monosulfoaluminate, and AH3. In addition, the Na element in the RCFA hydration product is mainly present in monosulfoaluminate and unhydrated cement particles.
A Review on Research Progress of Corrosion Resistance of Alkali-Activated Slag Cement Concrete
Authors: Liang Qiushuang , Huang Xinlu , Zhang Lanfang , Yang Haiyan
Published: October 2024

China is the largest producer and user of Ordinary Silicate Cement (OPC), and rapid infrastructure development requires more sustainable building materials for concrete structures. Portland cement emits large amounts of CO2 in production. Given proposals for “carbon peaking and carbon neutralization”, it is extremely important to study alternative low-carbon cementitious materials to reduce emissions. Alkali-activated slag (AAS) cement, a new green cementitious material, has high application potential. The chemical corrosion resistance of AAS concrete is important for ensuring durability and prolonging service life. This paper reviews the hydration mechanism of AAS concrete and discusses the composition of hydration products on this basis, examines the corrosion mechanism of AAS concrete in acid, sulfate, and seawater environments, and reviews the impact of its performance due to the corrosion of AAS concrete in different solutions. Further in-depth understanding of its impact on the performance of concrete can provide an important theoretical basis for its use in different environments and provides an important theoretical basis for the application of AAS concrete, so that we can have a certain understanding of the durability of AAS concrete.
Adhesion-Related Phenomena of Stellite 6 HVOF Sprayed Coating Deposited on Laser-Textured Substrates
Authors: Dlouhá Žaneta , Duliškovič Josef , Netrvalová Marie Frank , Naďová Jana , Vostřák Marek , Kraft Sebastian , Löschner Udo , Martan Jiří , Houdková Šárka
Published: October 2024

The focus of this research is to examine the feasibility of using laser texturing as a method for surface preparation prior to thermal spraying. The experimental part includes the thermal spraying of a Stellite 6 coating by High Velocity Oxygen Fuel (HVOF) technology on laser-textured substrates. The thermal spraying of this coating was deposited both on conventional substrate material (low carbon steel) and on substrates that had been previously heat treated (nitrided steel). The properties of the coatings were analysed using scanning electron microscopy (SEM), optical microscopy (OM) and Raman spectroscopy. Adhesion was assessed through a tensile adhesion test. The results showed the usability of laser texturing in the case of carbon steel, which was comparable or even better than traditional grit blasting. For nitrided steel, the problem remains with the hardness and brittleness of the nitrided layer, which allows for the propagation of brittle cracks near the interface and thus reduces the adhesion strength.
Damage Evolution Mechanism of Railway Wagon Bogie Adapter 1035 Steel and Damage Parameter Calibration Based on Gursone–Tvergaarde–Needleman Model
Authors: Yin Jiachuan , Huang Xiaomin , Ma Guangzhi , Song Changzhe , Tang Xuefeng , Ji Hongchao
Published: October 2024

As a critical component of a train, the railway wagon bogie adapter has higher quality requirements. During the forging process, external loads can induce voids, cracks, and other defects in the forging, thereby reducing its service life. Hence, studying the damage behavior of the forging material, specifically AISI 1035 steel, becomes crucial. This study involved obtaining stress–strain curves for AISI 1035 steel through uniaxial tensile tests at temperatures of 900 °C, 1000 °C, and 1100 °C, with strain rates of 0.1 s−1, 1 s−1, and 10 s−1. Subsequently, SEM was used to observe samples at various deformation stages. The damage parameters, q1,  q2 and q3 in the GTN model “a computational model used to analyze and simulate material damage which can effectively capture the damage behavior of materials under different loading conditions” were then calibrated using the Ramberg–Osgood model and stress–strain curve fitting. Image Pro Plus software v11.1 quantified the sample porosity as f0, fn, fc and fF. A finite element model was established to simulate the tensile behavior of the AISI 1035 steel samples. By comparing the damage parameters of f0, fn, fc and fF obtained by the finite element method and experimental method, the validity of the damage parameters obtained by the finite element inverse method could be verified.
Debonding Detection of Thin-Walled Adhesive Structure by Electromagnetic Acoustic Resonance Technology
Authors: Liu Ne , Shen Shiqiang , Zhu Ying , Gao Ying , Pan Yongdong
Published: October 2024

The detection of debonding defects in thin-walled adhesive structures, such as clad-iron/rubber layers on the leading edges of helicopter blades, presents significant challenges. This paper proposes the application of electromagnetic acoustic resonance technology (EMAR) to identify these defects in thin-walled adhesive structures. Through theoretical and simulation studies, the frequency spectrum of ultrasonic vibrations in thin-walled adhesive structures with various defects was analyzed. These studies verified the feasibility of applying EMAR to identify debonding defects. The identification of debonding defects was further examined, revealing that cling-type debonding defects could be effectively detected using EMAR by exciting shear waves with the minimum defect diameter at 5 mm. Additionally, the method allows for the quantitative analysis of these defects in the test sample. Due to the limited size of the energy exchange region in the transducer, the quantitative error becomes significant when identifying debonding defects smaller than this region. The EMAR identified debonding defects in clad-iron structures of rotor blades with a maximum error of approximately 15%, confirming its effectiveness for inspecting thin-walled adhesive structures.
The Development and Experimental Validation of a Real-Time Coupled Gear Wear Prediction Model Considering Initial Surface Topography, Dynamics, and Thermal Deformation
Authors: Zhang Jingqi , Zhou Jianxing , Cui Quanwei , Dong Ning , Jiang Hong , Fang Zhong
Published: October 2024

Errors affect the actual meshing process of gears, alter the actual wear pattern of the tooth profile, and may even impact the overall service life of machinery. While existing research predominantly focuses on individual errors or a narrow set of factors, this study explores the combined effects of multiple errors on tooth profile wear. A comprehensive gear wear prediction model was developed, integrating the slice method, lumped mass method, Hertz contact model, and Archard’s wear theory. This model accounts for initial tooth surface topography, thermal deformation, dynamic effects, and wear, establishing strong correlations between gear wear prediction and key factors such as tooth surface morphology, temperature, and vibration. Experimental validation demonstrated the model’s high accuracy, with relatively small deviations from the observed wear. Initial profile errors (IPEs) at different positions along the tooth width result in varying relative sliding distances, leading to differences in wear depth despite a consistent overall trend. Notably, large IPEs at the dedendum and addendum can influence wear progression, either accelerating or decelerating the wear process over time.
Integrating Evolutionary Game-Theoretical Methods and Deep Reinforcement Learning for Adaptive Strategy Optimization in User-Side Electricity Markets: A Comprehensive Review
Authors: Cheng Lefeng , Wei Xin , Li Manling , Tan Can , Yin Meng , Shen Teng , Zou Tao
Published: October 2024

With the rapid development of smart grids, the strategic behavior evolution in user-side electricity market transactions has become increasingly complex. To explore the dynamic evolution mechanisms in this area, this paper systematically reviews the application of evolutionary game theory in user-side electricity markets, focusing on its unique advantages in modeling multi-agent interactions and dynamic strategy optimization. While evolutionary game theory excels in explaining the formation of long-term stable strategies, it faces limitations when dealing with real-time dynamic changes and high-dimensional state spaces. Thus, this paper further investigates the integration of deep reinforcement learning, particularly the deep Q-learning network (DQN), with evolutionary game theory, aiming to enhance its adaptability in electricity market applications. The introduction of the DQN enables market participants to perform adaptive strategy optimization in rapidly changing environments, thereby more effectively responding to supply–demand fluctuations in electricity markets. Through simulations based on a multi-agent model, this study reveals the dynamic characteristics of strategy evolution under different market conditions, highlighting the changing interaction patterns among participants in complex market environments. In summary, this comprehensive review not only demonstrates the broad applicability of evolutionary game theory in user-side electricity markets but also extends its potential in real-time decision making through the integration of modern algorithms, providing new theoretical foundations and practical insights for future market optimization and policy formulation.
Fast Global and Local Semi-Supervised Learning via Matrix Factorization
Authors: Du Yuanhua , Luo Wenjun , Wu Zezhong , Zhou Nan
Published: October 2024

Matrix factorization has demonstrated outstanding performance in machine learning. Recently, graph-based matrix factorization has gained widespread attention. However, graph-based methods are only suitable for handling small amounts of data. This paper proposes a fast semi-supervised learning method using only matrix factorization, which considers both global and local information. By introducing bipartite graphs into symmetric matrix factorization, the technique can handle large datasets effectively. It is worth noting that by utilizing tag information, the proposed symmetric matrix factorization becomes convex and unconstrained, i.e., the non-convex problem minx(1−x2)2 is transformed into a convex problem. This allows it to be optimized quickly using state-of-the-art unconstrained optimization algorithms. The computational complexity of the proposed method is O(nmd), which is much lower than that of the original symmetric matrix factorization, which is O(n2d), and even lower than that of other anchor-based methods, which is O(nmd+m2n+m3), where n represents the number of samples, d represents the number of features, and m≪n represents the number of anchors. The experimental results on multiple public datasets indicate that the proposed method achieves higher performance in less time.
On Productiveness and Complexity in Computable Analysis Through Rice-Style Theorems for Real Functions
Authors: Xie Jingnan , Hunt Harry B. , Stearns Richard E.
Published: October 2024

This paper investigates the complexity of real functions through proof techniques inspired by formal language theory. Productiveness, which is a stronger form of non-recursive enumerability, is employed to analyze the complexity of various problems related to real functions. Our work provides a deep reexamination of Hilbert’s tenth problem and the equivalence to the identically 0 function problem, extending the undecidability results of these problems into the realm of productiveness. Additionally, we study the complexity of the equivalence to the identically 0 function problem over different domains. We then construct highly efficient many-one reductions to establish Rice-style theorems for the study of real functions. Specifically, we show that many predicates, including those related to continuity, differentiability, uniform continuity, right and left differentiability, semi-differentiability, and continuous differentiability, are as hard as the equivalence to the identically 0 function problem. Due to their high efficiency, these reductions preserve nearly any level of complexity, allowing us to address both complexity and productiveness results simultaneously. By demonstrating these results, which highlight a more nuanced and potentially more intriguing aspect of real function theory, we provide new insights into how various properties of real functions can be analyzed.
Dynamic Evolution Game Strategy of Government, Power Grid, and Users in Electricity Market Demand-Side Management
Authors: Shen Xin , Tang Jianlin , Zhang Yijing , Qian Bin , Li Jiahao , Zhou Mi , Zhao Yitao , Yin Yujun
Published: October 2024

In the process of promoting demand-side management, the core stakeholder groups are government departments, power grid companies, and electricity users. Due to the different positions and conflicting interests of the three parties in the game, intense and complex battles will occur. This paper investigates a tripartite evolutionary game involving government, power grid companies, and electricity users in the context of demand-side management (DSM) and analyzes the dynamic interactions between government departments, power grid companies, and electricity users within the framework of DSM using evolutionary game theory. Using evolutionary game theory, we explore how incentives and strategic interactions among these three stakeholders evolve over time, affecting the stability of DSM policies. The model addresses the asymmetry in the decision-making process and examines the dynamic equilibrium outcomes under various scenarios. The results provide insights into the optimal design of incentive mechanisms to enhance DSM adoption. The findings offer practical recommendations to improve DSM policies, fostering balanced interests between government, grid companies, and users. This research contributes to a deeper understanding of strategic interactions in DSM, revealing how adaptive behaviors can enhance energy efficiency. It also underscores the importance of carefully designed incentive mechanisms in achieving long-term stability and cooperation among key stakeholders.
A Commentary on US Sovereign Debt Persistence and Nonlinear Fiscal Adjustment
Authors: Andric Vladimir , Bodroza Dusko , Djukic Mihajlo
Published: October 2024

The purpose of this paper is to show how the self-exciting threshold autoregressive (SETAR) model might be a suitable econometric framework for characterizing the dynamics of the US public debt/GDP ratio after the Bretton Woods collapse. Our preferred SETAR specifications are capable of capturing the main stylized facts of the US public debt/GDP ratio between 1974 and 2024. In addition, the estimated SETAR models are consistent with theoretical frameworks that look to explain the behavior of the US public debt/GDP ratio before and after the Global Financial Crisis (GFC). Finally, under the assumption of public debt/GDP ratio stationarity, for which we find only limited and inconclusive evidence, this paper provides some arguments for why previous studies, which use the exponential smooth threshold autoregressive (ESTAR) models, logistic smooth threshold autoregressive (LSTAR) models or SETAR-type models for the first differences of the US public debt/GDP ratio, are potentially misspecified on both econometric and economic grounds.
Comprehensive Numerical Analysis of Time-Fractional Reaction–Diffusion Models with Applications to Chemical and Biological Phenomena
Authors: Owolabi Kolade M. , Jain Sonal , Pindza Edson , Mare Eben
Published: October 2024

This paper aims to present a robust computational technique utilizing finite difference schemes for accurately solving time fractional reaction–diffusion models, which are prevalent in chemical and biological phenomena. The time-fractional derivative is treated in the Caputo sense, addressing both linear and nonlinear scenarios. The proposed schemes were rigorously evaluated for stability and convergence. Additionally, the effectiveness of the developed schemes was validated through various linear and nonlinear models, including the Allen–Cahn equation, the KPP–Fisher equation, and the Complex Ginzburg–Landau oscillatory problem. These models were tested in one-, two-, and three-dimensional spaces to investigate the diverse patterns and dynamics that emerge. Comprehensive numerical results were provided, showcasing different cases of the fractional order parameter, highlighting the schemes’ versatility and reliability in capturing complex behaviors in fractional reaction–diffusion dynamics.
Predicting Factor of Safety of Slope Using an Improved Support Vector Machine Regression Model
Authors: Lei Daxing , Zhang Yaoping , Lu Zhigang , Lin Hang , Jiang Zheyuan
Published: October 2024

To reduce the disasters caused by slope instability, this paper proposes a new machine learning (ML) model for slope stability prediction. This improved SVR model uses support vector machine regression (SVR) as the basic prediction tool and the grid search method with 5-fold cross-validation to optimize the hyperparameters to improve the prediction performance. Six features, namely, unit weight, cohesion, friction angle, slope angle, slope height, and pore pressure ratio, were taken as the input of the model, and the factor of safety was taken as the model output. Four statistical indicators, namely, the coefficient of determination (R2), mean absolute percentage error (MAPE), mean absolute error (MAE), and root mean squared error (RMSE), were introduced to assess the generalization performance of the model. Finally, the feature importance score of the features was clarified by calculating the importance of the six features and visualizing them. The results show that the model can well describe the nonlinear relationship between features and the factor of safety. The R2, MAPE, MAE, and RMSE of the testing dataset were 0.901, 7.41%, 0.082, and 0.133, respectively. Compared with other ML models, the improved SVR model had a better effect. The most sensitive feature was unit weight.
Harmonic Mitigation in Multi-Pulse Rectification: A Comparative Study of 12-, 18-, and 24-Pulse Systems
Authors: Albalawi Hani , Wadood Abdul , Khan Shahbaz , Alatwi Aadel Mohammed
Published: October 2024

In the evolution of the modern “More Electric Aircrafts” (MEAs) concept, higher-pulse rectification systems using differential fork autotransformers play a pivotal role. These systems align with the MEAs concept, which aims to replace traditional hydraulic and pneumatic systems with electric alternatives. The reason is that MEAs prioritize weight reduction to enhance fuel efficiency and reduce emissions. Higher-pulse rectifiers achieve this by minimizing losses and optimizing power conversion. Additionally, they mitigate harmonics, ensuring a clean power supply to critical avionic components. These systems also regulate voltage effectively, contributing to overall system stability. Furthermore, their compliance with IEEE-519 standards ensures their safe and efficient operation. Keeping in view the above applications, a comparative study of 12-, 18-, and 24-pulse rectification systems was carried out using different autotransformer topologies. The simulation and hardware results are presented for validation. The voltage and current waveforms were meticulously analyzed for each topology, emphasizing the pivotal role played by the differential fork autotransformer design. By quantifying the total harmonic distortion (THD) levels using MATLAB simulations, intriguing insights were revealed. Notably, the 24-pulse system emerged as the clear winner in harmonic mitigation, showcasing its superior waveform quality and reduced harmonic content. However, the 18-pulse configuration also exhibited a commendable performance, surpassing the 12-pulse counterpart.
Elimination Algorithms for Skew Polynomials with Applications in Cybersecurity
Authors: Rasheed Raqeeb , Sadiq Ali Safaa , Kaiwartya Omprakash
Published: October 2024

It is evident that skew polynomials offer promising directions for developing cryptographic schemes. This paper focuses on exploring skew polynomials and studying their properties with the aim of exploring their potential applications in fields such as cryptography and combinatorics. We begin by deriving the concept of resultants for bivariate skew polynomials. Then, we employ the derived resultant to incrementally eliminate indeterminates in skew polynomial systems, utilising both direct and modular approaches. Finally, we discuss some applications of the derived resultant, including cryptographic schemes (such as Diffie–Hellman) and combinatorial identities (such as Pascal’s identity). We start by considering a bivariate skew polynomial system with two indeterminates; our intention is to isolate and eliminate one of the indeterminates to reduce the system to a simpler form (that is, relying only on one indeterminate in this case). The methodology is composed of two main techniques; in the first technique, we apply our definition of a (bivariate) resultant via a Sylvester-style matrix directly from the polynomials’ coefficients, while the second is based on modular methods where we compute the resultant by using evaluation and interpolation approaches. The idea of this second technique is that instead of computing the resultant directly from the coefficients, we propose to evaluate the polynomials at a set of valid points to compute its corresponding set of partial resultants first; then, we can deduce the original resultant by combining all these partial resultants using an interpolation technique by utilising a theorem we have established.
Robust Classification via Finite Mixtures of Matrix Variate Skew-t Distributions
Authors: Mahdavi Abbas , Balakrishnan Narayanaswamy , Jamalizadeh Ahad
Published: October 2024

Analysis of matrix variate data is becoming increasingly common in the literature, particularly in the field of clustering and classification. It is well known that real data, including real matrix variate data, often exhibit high levels of asymmetry. To address this issue, one common approach is to introduce a tail or skewness parameter to a symmetric distribution. In this regard, we introduce here a new distribution called the matrix variate skew-t distribution (MVST), which provides flexibility, in terms of heavy tail and skewness. We then conduct a thorough investigation of various characterizations and probabilistic properties of the MVST distribution. We also explore extensions of this distribution to a finite mixture model. To estimate the parameters of the MVST distribution, we develop an EM-type algorithm that computes maximum likelihood (ML) estimates of the model parameters. To validate the effectiveness and usefulness of the developed models and associated methods, we performed empirical experiments, using simulated data as well as three real data examples, including an application in skin cancer detection. Our results demonstrate the efficacy of the developed approach in handling asymmetric matrix variate data.
S&SEM: A Secure and Speed-Up Election Mechanism for PoS-Based Blockchain Network
Authors: Naz Sana , Siddiqui Mohsin Javaid , Lee Scott Uk-Jin
Published: October 2024

To be a stakeholder/validator/token holder is not so difficult in the Proof of Stake (POS)-based blockchain networks; that is why the number of validators is large in these networks. These validators play an essential part in the block creation process in the PoS-based blockchain network. Due to the large validators, the block creation time and communication message broadcasting overhead get increased in the network. Many consensus algorithms use different techniques to reduce the number of validators, such as Delegated Proof of Stake (DPoS) consensus algorithms, which select the set of delegators via stake transactions for the block creation process. In this paper, we propose S&SEM, a secure and speed-up election process to select the ‘z’ number of validators/delegators. The presented election process is based on a traditional voting style with multiple numbers of rounds. The presented election mechanism reduces the possibility of malicious activity in the voting process by introducing a special vote message and a round that checks duplicate votes. We did horizontal scaling in the network to speed up the election process. We designed an improved incentive mechanism for the fairness of the election process. The designed reward and penalty procedure controls the nodes’ behaviors in the network. We simulate the S&SEM, and the result shows that the presented election process is faster and more secure to select delegators than the existing process used by DPOS.
Computational Fluid Dynamics Modelling of Hydrogen Production via Water Splitting in Oxygen Membrane Reactors
Authors: Bittner Kai , Margaritis Nikolaos , Schulze-Küppers Falk , Wolters Jörg , Natour Ghaleb
Published: October 2024

The utilization of oxygen transport membranes enables the production of high-purity hydrogen by the thermal decomposition of water below 1000 °C. This process is based on a chemical potential gradient across the membrane, which is usually achieved by introducing a reducing gas. Computational fluid dynamics (CFD) can be used to model reactors based on this concept. In this study, a modelling approach for water splitting is presented in which oxygen transport through the membrane acts as the rate-determining process for the overall reaction. This transport step is implemented in the CFD simulation. Both gas compartments are modelled in the simulations. Hydrogen and methane are used as reducing gases. The model is validated using experimental data from the literature and compared with a simplified perfect mixing modelling approach. Although the main focus of this work is to propose an approach to implement the water splitting in CFD simulations, a simulation study was conducted to exemplify how CFD modelling can be utilized in design optimization. Simplified 2-dimensional and rotational symmetric reactor geometries were compared. This study shows that a parallel overflow of the membrane in an elongated reactor is advantageous, as this reduces the back diffusion of the reaction products, which increases the mean driving force for oxygen transport through the membrane.
Just Sustainabilities: Building Bridges and Breaking Barriers to Empower Employees for Inclusive Workplaces—Evidence from Ghana
Authors: Nkansah-Dwamena Ernest
Published: October 2024

This study examines the critical role of inclusive, people-centered strategies in driving organizational sustainability, focusing on two key institutions in the Ashanti Region of Ghana: Presbyterian University College (PUC) and Presbyterian Agogo Women’s College of Education (APWCE). Employing a qualitative research design, including 100 interviews, five focus groups, and participant observations, this study investigates employee perspectives on Diversity, Equity, and Inclusion (DEI) practices in the workplace. The findings identify key empowerment strategies—flexible job roles, participatory decision-making, leadership development, and open communication—that enhance employee engagement and commitment to sustainability efforts. The findings also demonstrate employees’ vital role in advancing sustainability through involvement in green initiatives, community engagement, and integrating sustainability into core organizational practices. This contribution intellectually bridges the gap between DEI policies and their practical application, offering a nuanced understanding of how cultural and social dimensions influence sustainability in underexplored contexts like Ghana. It emphasizes aligning organizational values with employee well-being to enhance job satisfaction and retention, presenting actionable strategies for fostering innovation, resilience, and long-term success. The increasing global focus on sustainability and the growing need for inclusive practices in organizational settings underscores the timeliness of this manuscript. It offers a holistic, forward-thinking approach that is especially relevant for organizations navigating post-pandemic workplace dynamics and seeking to align sustainability with equity and inclusivity.
Effect of Surface Roughness on Corrosion Resistance of Mooring Chains for Offshore Floating Photovoltaics
Authors: Wang Feng , Wang Yong , Wang Wei , Lin Bin , Qu Minggui
Published: October 2024

Mooring chains are key components of offshore floating photovoltaic systems. Although their service safety is often affected by the harsh service environment, the influence of surface roughness on their corrosion resistance is not clear. This study investigated the corrosion behavior of mooring chain steel using cyclic salt-spray corrosion and electrochemical tests. Scanning electron microscopy, energy-dispersive spectrometry, optical profilometry, and other analytical techniques were used to study the composition and morphology of the corrosion products. The corrosion behavior was studied by electrochemical polarization curves, alternating current impedance spectroscopy, and X-ray photoelectron spectroscopy. The results show that the salt-spray corrosion resistance of mooring chain steel significantly improved with the reduction in specimen surface roughness, and the number and depth of corrosion pits were reduced. Mass loss after 24 h of salt-spray corrosion was exponentially related to initial roughness (Ra). Improved surface roughness significantly increased the pitting potential of the specimens, widened the passivation range, and enhanced the repassivation capability, thus significantly improving the pitting resistance. The pitting potential is linearly related to the initial roughness of the specimen. The oxide contents of Fe, Mo, and Si in the passivation film tended to increase with a smoother surface, which contributes to its densification. This effectively blocks chloride ion attack, thus improving the corrosion resistance of the mooring chain steel.
Effects of Mixtures of Emerging Pollutants and Drugs on Modulation of Biomarkers Related to Toxicity, Oxidative Stress, and Cancer
Authors: Manuguerra Simona , Carli Fabrizia , Scoditti Egeria , Santulli Andrea , Gastaldelli Amalia , Messina Concetta Maria
Published: October 2024

Background/Objectives: Over time, the scientific community has developed a growing interest in the effects of mixtures of different compounds, for which there is currently no established evidence or knowledge, in relation to certain categories of xenobiotics. It is well known that exposure to pollutants causes oxidative stress, resulting in the overproduction of reactive oxygen species (ROS), which can affect signaling pathways that regulate the cell cycle, apoptosis, energy balance, and cellular metabolism. The aim of this study was to investigate the effects of sub-lethal concentrations of mixtures of emerging pollutants and pharmaceuticals on the modulation of biomarkers related to toxicity, oxidative stress, and cancer. Methods: In this study, the hepatoma cell line HepG2 was exposed to increasing concentrations of polybrominated diphenyl ether 47 (BDE-47), cadmium chloride (CdCl2), and carbamazepine (CBZ), both individually and in mixtures, for 72 h to assess cytotoxicity using the MTT assay. The subsequent step, following the identification of the sub-lethal concentration, was to investigate the effects of exposure at the gene expression level, through the evaluation of molecular markers related to cell cycle and apoptosis (p53), oxidative stress (NRF2), conjugation and detoxification of xenobiotics (CYP2C9 and GST), DNA damage (RAD51 and γH2AFX), and SUMOylation processes (SUMO1 and UBC9) in order to identify any potential alterations in pathways that are normally activated at the cellular level. Results: The results showed that contaminants tend to affect the enzymatic detoxification and antioxidant system, influencing DNA repair defense mechanisms involved in resistance to oxidative stress. The combined effect of the compounds at sub-lethal doses results in a greater activation of these pathways compared to exposure to each compound alone, thereby exacerbating their cytotoxicity. Conclusions: The biomarkers analyzed could contribute to the definition of early warning markers useful for environmental monitoring, while simultaneously providing insight into the toxicity and hazard levels of these substances in the environment and associated health risks.
Optical Forces on Chiral Particles: Science and Applications
Authors: Yi Weicheng , Huang Haiyang , Lai Chengxing , He Tao , Wang Zhanshan , Dai Xinhua , Shi Yuzhi , Cheng Xinbin
Published: October 2024

Chiral particles have attracted considerable attention due to their distinctive interactions with light, which enable a variety of cutting-edge applications. This review presents a comprehensive analysis of the optical forces acting on chiral particles, categorizing them into gradient force, radiation pressure, optical lateral force, pulling force, and optical force on coupled chiral particles. We thoroughly overview the fundamental physical mechanisms underlying these forces, supported by theoretical models and experimental evidence. Additionally, we discuss the practical implications of these optical forces, highlighting their potential applications in optical manipulation, particle sorting, chiral sensing, and detection. This review aims to offer a thorough understanding of the intricate interplay between chiral particles and optical forces, laying the groundwork for future advancements in nanotechnology and photonics.
My Early Years of Yeast Mitochondrial Genetics
Authors: Macreadie Ian G.
Published: October 2024

There have been massive technological advances in molecular biology and genetics over the past five decades. I have personally experienced these advances and here I reflect on those origins, from my perspective, studying yeast mitochondrial genetics leading up to deciphering the functions of the mitochondrial genome. The yeast contributions commenced in the middle of the last century with pure genetics, correlating mutants with phenotypes, in order to discover genes, just like the early explorations to discover new lands. The quest was to explore the mitochondrial genome and find its genes and their products. It was most fortunate that DNA sequencing technologies became available in the late 1970s, and laboratories were restructured enormously to keep pace with the emerging technologies. There were considerable costs in equipping laboratories, purchasing ultracentrifuges and restriction endonucleases, and undertaking DNA sequencing; additionally, workers required special safety gear.
Pathogenicity of Citrobacter freundii Causing Mass Mortalities of Macrobrachium rosenbergii and Its Induced Host Immune Response
Authors: Chen Anting , Qian Qieqi , Cai Xiaoyu , Yin Jia , Liu Yan , Dong Qi , Gao Xiaojian , Jiang Qun , Zhang Xiaojun
Published: October 2024

Citrobacter freundii is an opportunistic pathogen of freshwater aquatic animals, which severely restricts the sustainable development of the aquaculture industry. In this study, a dominant strain, named FSNM-1, was isolated from the hepatopancreas of diseased Macrobrachium rosenbergii. This strain was identified as C. freundii based on a comprehensive analysis of its morphological, physiological, and biochemical features and molecular identification. Challenge experiments were conducted to assess the pathogenicity of C. freundii to M. rosenbergii. The results showed that the FSNM-1 strain had high virulence to M. rosenbergii with a median lethal dose (LD50) of 1.1 × 106 CFU/mL. Histopathological analysis revealed that C. freundii infection caused different degrees of inflammation in the hepatopancreas, gills, and intestines of M. rosenbergii. The detection of virulence-related genes revealed that the FSNM-1 strain carried colonization factor antigen (cfa1, cfa2), ureases (ureG, ureF, ureD, ureE), and outer membrane protein (ompX), and virulence factor detection showed that the FSNM-1 strain had lecithinase, amylase, lipase, gelatinase, and hemolysin activities but did not produce protease and DNase activities. To investigate the immune response of M. rosenbergii to C. freundii, the expression levels of ALF3, MyD88, SOD, proPO, TRAF6, and TNF immune-related genes were monitored at different points of time in the hepatopancreas, gills, intestines, and hemocytes of M. rosenbergii after infection. The results demonstrated a significant upregulation in the expression levels of the ALF3, MyD88, SOD, proPO, TRAF6, and TNF genes in M. rosenbergii at the early stage of C. freundii infection. This study highlights C. freundii as a major pathogen causing mass mortality in M. rosenbergii and provides valuable insights into its virulence mechanisms and the host’s immune response.
Microfacies and Evolution of the Carbonate Factory During the Middle Permian in Northwest Sichuan Basin, China
Authors: Zhou Siyu , Zhong Dakang , Sun Haitao , Huang Xiaojie , Wang Chenguang , Liu Xuanwei
Published: October 2024

Located in the eastern Paleo-Tethys Ocean and near the equator, carbonate sedimentation widely developed in the Sichuan Basin in the Permian Guadalupian period. Although the growth and decline of carbonate particles are closely related to the surrounding sedimentary environment, the relationships between the grain composition and distribution of the northwest Sichuan Basin and the sedimentary environment are not clear. This study explored the particle type, particle content, and sedimentary structure of 300 thin sections from 19 wells and seven field profiles of the Guadalupian period in the northwest Sichuan Basin, identified seven microfacies and four microfacies associations, analyzed the sedimentary environment, and established a sedimentary evolution model. The results show that there was a warm-water Dasycladaceae-dominated and foraminifera-dominated open platform developed in the early Roadian era in the research area. As the climate cooled during the late Roadian era, the warm-water carbonate sedimentary environment was replaced by a cold-water bryozoan-dominated and echinoid-dominated marginal sedimentary environment. As the climate continued to cool and the sea level dropped, the platform margin grain beach sediment underwent further development in the early Wordian era. In the late Wordian era stage, the sedimentary environment was influenced by the Dongwu movement, resulting in sea level changes and acidification caused by hydrothermal activities, which reduced the degree of grain beach development. During the Capitanian era, the climate became warmer due to the eruption of the ELIP. The uplift caused by the Dongwu movement resulted in a relative shallowing of the platform margin region, and hence, the grain beach sediment only developed in the southwest, while the northeast was dominated by deepwater basin sediments. The sudden transition from a warm-water, autotroph-dominated carbonate open platform to a cold-water, heterozoan-dominated carbonate platform margin resulted from a combination of tectonic movements, rapid sea level changes, and sedimentary environment changes during the Guadalupian era.
Control of Seepage Characteristics in Loose Sandstone Heap Leaching with Staged Particle Sieving-Out Method
Authors: Jiang Quan , Jia Mingtao , Yang Yihan , Zhang Chuanfei
Published: October 2024

This paper studies the influence of the staged particle sieving-out method on the seepage characteristics in loose sandstone heap leaching. The staged sieving out of ore sample particles was conducted according to particle size, and ground pressure was applied to them. Subsequently, parameters such as the permeability, particle distribution, and pore distribution characteristics of the rock samples were obtained to investigate the influence of the staged particle sieving-out method on the seepage effect of loose sandstone heap leaching. The results indicate that sieving out particles smaller than 0.15 mm can significantly reduce the probability of hole blockage and increase the overall pore size, greatly enhancing permeability. Sieving out particles with sizes between 0.15 mm and 1.2 mm can result in the loss of skeleton particles, reducing the amount of flow channels and thereby decreasing permeability. Sieving out particles larger than 1.2 mm can reduce the overall particle size of rock samples, improve strength and pressure stability, and help maintain permeability. In the surface heap leaching of loose sandstone ore, by sieving out particles smaller than 0.15 mm during deep heap construction and sieving out particles larger than 1.2 mm during mid-level heap construction, and by using vat leaching for sieved-out particles, the seepage effect of the ore heap can be significantly optimized, and complete utilization of resources can be ensured.
Influence of Particle Size on Flotation Separation of Ilmenite and Forsterite
Authors: Zhang Senpeng , Yang Yaohui , Wang Donghui , Yan Weiping , Li Weishi
Published: October 2024

In addition to bubble–particle interaction, particle–particle interaction also has a significant influence on mineral flotation. Fine particles that coat the mineral surface prevent direct contact with collectors and/or air bubbles, thereby lowering flotation recovery. Calculating the particle interaction energy can help in evaluating the interaction behavior of particles. In this study, the floatability of coarse ilmenite (−151 + 74 μm) and different particle sizes (−45 + 25, −25 + 19, −19 μm) of forsterite with NaOL as a collector was investigated. The results showed that forsterite sizes of −45 + 25 and −25 + 19 μm had no effect on the ilmenite floatability, whereas −19 μm forsterite significantly reduced ilmenite floatability. A particle size analysis of artificially mixed minerals and a scanning electron microscopy (SEM) analysis of the flotation products showed that heterogeneous aggregation occurred between ilmenite and −19 μm forsterite particles. The extended DLVO (Derjaguin–Landau–Verwey–Overbeek) theory was applied to calculate the interaction energy between mineral particles using data from zeta potential and contact angle measurements. The results showed that the interaction barriers between ilmenite (−151 + 74 μm) and forsterite (−45 + 25, −25 + 19, and −19 μm) were 11.94 × 103 kT, 8.23 × 103 kT and 4.09 × 103 kT, respectively. Additionally, the interaction barrier between forsterite particles smaller than 19 μm was 0.51 × 103 kT. The strength of the barrier decreased as the size of the forsterite decreased. Therefore, fine forsterite particles and aggregated forsterite can easily overcome the energy barrier, coating the ilmenite particle surface. This explains the effect of different forsterite sizes on the floatability of ilmenite and the underlying mechanism of particle interaction.
Physical and Numerical Modeling of a Flow Control Layer Made with a Sludge and Slag Mixture for Use in Waste Rock Pile Reclamation
Authors: Otalora Vasquez Nelcy Carolina , Maqsoud Abdelkabir , Belem Tikou
Published: October 2024

The reclamation of waste rock piles (WRPs) is complex, requiring adaptation of existing mine site reclamation techniques. An alternative approach has been developed for waste rock piles reclamation which involves installing finer materials on the top of waste rock piles. These finer layers (flow control layers—FCLs) redirect water flowing inside the pile toward its slope and limits water infiltration into reactive waste rocks. In the context of sustainable development, a mixture material made with sludge and slag can be used as an FCL in the reclamation of a waste rock pile. To assess the effectiveness of this material, a physical model was used and instrumented with sensors for monitoring volumetric water content and suction and equipped with the following components: (1) a rain simulator; and (2) drains that allow the recovery of water that infiltrates through the system. The physical model was tested with various cover layer thicknesses, inclinations, and precipitation rates. Investigation results showed that the water infiltration across the system was very low, leading to the conclusion that the sludge and slug mixture performed well as a flow control layer in the reclamation of waste rock piles.