Browse Articles

Efficient cutting stock optimization strategies for the steel industry

This study addresses a cutting stock problem in steel cutting industry by developing a mathematical model in which machine specifications and cutting conditions are constraints. The solution process involves three key steps: (i) Problem representation, where feasible cutting solutions are modeled based on pre-cut steel bars and customer orders, (ii) Problem space reduction, which reduces the problem space by eliminating suboptimal solutions and following manufacturer loss limits, and (iii) Optimal solution search, whereas the optimal solution is identified using a new Adaptive Pathfinding Optimization Algorithm. This algorithm combines a newly proposed Wandering Ant Colony Optimization with a brute force method, and uses specific conditions to determine which of these two approaches to be used to obtain the solution. The proposed algorithm can also be applied to other cutting stock problems, such as paper roll cutting, metal rod cutting, and wood plank cutting. The algorithm was applied to real customer orders in a steel manufacturer and showed significant benefits by reducing the number of planners from four to merely one person and decreasing the cutting planning time from six hours to under one hour. Additionally, the algorithm yields an average cost saving of USD 3.95 per ton, or 52.18% of the baseline.

Applying the active learning strategy to the construction of full-dimensional neural network potential energy surfaces: Critical tests in H2O–He spectroscopic calculation

An uncertainty-driven active learning strategy was employed to achieve efficient point sampling for full-dimension potential energy surface constructions. Model uncertainty is defined as the weighted square energy difference between two neural network models, and the local maximums of uncertainty would be added to the training set by two criteria. A two-step sampling procedure was introduced to reduce the computational costs of expansive double-precision neural network training. A reference potential energy surface (PES) of the 6-D H2O–He system was constructed first by the MLRNet model with a weighted Root-Mean-Square-Error (RMSE) of 0.028 cm−1. The full-dimension long-range function was fitted by a pruned basis expansion method. The current sampling method is reliable for the long-range switched fundamental invariant neural network (LS-FI-NN) to construct spectroscopically accurate PES, where the single precision model achieves a test set RMSE of 0.3253 cm−1 with 472 fitting points and the double precision model is 0.0710 cm−1 with only 613 points. In comparison, the MLRNet requires 652 points to reach a similar accuracy. However, the MLRNet, with fewer parameters, shows lower training errors across all sampling cycles and lower test errors in the first few cycles, indicating its potential with an appropriate sampling procedure. The spectroscopic calculations were performed to validate the accuracy of PESs. The energy levels of the double precision LS-FI-NN showed great agreement with the reference PES’s results, with only 0.0161 and 0.0044 cm−1 average errors for vibrational levels and the band origin shifts.

Investigating the influence of language teachers’ constructivist self-efficacy on their practice of constructivism in Ghanaian language and culture instruction

The education system in Ghana is undergoing a transition from a behaviorist instructional philosophy to a constructivist one, aiming to produce learners who can actively contribute to nation-building. Nonetheless, given the heavy demands on teachers regarding this abrupt shift into constructivist teaching, there is a need to examine teachers’ sense of efficacy in relation to the enactment of the core principles of this novel instructional philosophy—i.e., social, cognitive, and critical constructivism— laid down in the newly introduced standards-based curriculum. An explanatory sequential mixed method was used to obtain data from basic school teachers in the Sunyani-West Municipal of Bono Region, Ghana. Using adapted teacher self-efficacy and constructivist learning environment scales, quantitative data were gathered from 104 teachers. Qualitative data were also gathered from 15 conveniently sampled language teachers to augment the quantitative findings. Using partial least squares structural equation modelling, a significant positive association was discovered between teachers’ efficacy and the practice of social and cognitive constructivism. Nonetheless, teachers’ efficacy did not statistically predict their practice of critical constructivism. The qualitative results showed that sociocultural concerns probably accounted for the insignificant association between efficacy and critical constructivism. It was therefore concluded that sociocultural norms designed for bringing up a child in Ghana tend to inhibit the enactment of critical constructivism. The study recommends that the National Council for Curriculum and Assessment, in partnership with the Ghana Tertiary Education Commission, should update teacher professional development programs in universities and colleges of education to incorporate constructivist principles, particularly critical pedagogy, aiming to produce competent teachers capable of fostering learners’ autonomy, critical thinking, and problem-solving skills as outlined in the Standards-Based Curriculum (SBC).

Frontal polymerization in thin layers: Hydrodynamic effects and asymptotic dynamics

Buoyancy-driven convection currents arise from temperature gradients in thermal frontal polymerization (FP) when the spatially localized polymerization reaction travels perpendicularly to the gravity field. We propose a theoretical study of the system dynamics under adiabatic conditions. The polymer and the reactant mixture are considered to be in the same liquid phase, but the viscosity can increase with the degree of polymerization. We find that the reaction zone propagates as a hot spot-like pattern with a broken symmetry in both the vertical and horizontal directions. Furthermore, the system can reach an asymptotic dynamics characterized by a front with a steady shape that propagates at constant speed with a steady vortex surrounding it. As the strength of the vortex is increased, either by decreasing the reactants’ viscosity or by increasing the layer’s thickness, we observe a transition between (i) a passive regime predicted by pure reaction–diffusion and hydrodynamic models and (ii) an active chemo-hydrodynamic regime where such models separately break down. In the active regime (ii), the front speed decreases as convection intensifies. By means of a scaling analysis, we explain how hydrodynamic currents might lower the velocity of a polymerization wave. As the viscosity of the polymer is enlarged, the flow is shifted ahead of the reaction zone and becomes more symmetrical with respect to the middle of the system, as recently observed in solid–liquid FP experiments [Y. Gao et al., Phys. Rev. Lett. 130, 028101 (2023) and Y. Gao et al., Int. J. Heat Mass Transf. 240, 126622 (2025)].

Agro-physiological and transcriptome profiling reveal key genes associated with potato tuberization under different nitrogen regimes in aeroponics

Nitrogen (N) is a crucial nutrient for the growth and development of potatoes. However, excessive use of nitrogen fertilizers can have detrimental effects on human health, aquatic ecosystems, and the environment. Therefore, understanding the genes involved in nitrogen metabolism is essential for developing future strategies to improve nitrogen use efficiency (NUE) in plants. This study aimed to identify genes associated with high tuber yield in two contrasting potato varieties Kufri Jyoti (N inefficient) and Kufri Pukhraj (N efficient) grown under low and high nitrogen regimes using an aeroponics system. Both varieties were grown in aeroponics with two nitrogen doses (low N: 0.5 mM N; high N: 5 mM N) using a completely randomized design (CRD) with three replications over two years. The phenotypic results confirmed that Kufri Pukhraj was more nitrogen use efficient compared to Kufri Jyoti, particularly under low nitrogen conditions. Additionally, transcriptome analysis produced high-quality data ( ≥ Q20), ranging from 4.35 to 5.46 Gb per sample. Statistically significant genes (p ≤  0.05) were identified based on the reference potato genome. Differentially expressed genes (DEGs) were categorized as either up-regulated or down-regulated in leaf and tuber tissues. Transcriptome profiling of both tuber and leaf tissues revealed genes associated with traits contributing to high tuber yield under both high and low nitrogen conditions. The DEGs were further characterized through gene ontology (GO) annotation and KEGG pathway analysis. Selected genes were validated through real-time quantitative polymerase chain reaction (RT-qPCR) analysis. In summary, several genes were identified as being involved in high tuber yield component traits in potatoes under different nitrogen conditions. These included glutaredoxin, transcription factors (BTB/POZ, AP2/ERF, and MYB), nitrate transporter, aquaporin TIP1;3, glutamine synthetase, aminotransferase, GDSL esterase/lipase, sucrose synthase, UDP-glycosyltransferases, osmotin, xyloglucan endotransglucosylase/hydrolase, and laccases. Additionally, we identified overexpressed genes including cysteine protease inhibitor 1, miraculin, sterol desaturase, and pectinesterase in Kufri Pukhraj under low N stress. Our study highlights these genes’ roles in enhancing tuber yield in potatoes cultivated under both high and low nitrogen in aeroponics.

Are nanocubes more efficient than nanospheres to enhance the nuclear magnetic relaxation of water protons? A Monte Carlo simulation study

Iron oxide superparamagnetic nanoparticles have been extensively studied as T2 contrast agents in magnetic resonance imaging. The theory of nuclear magnetic relaxation induced by superparamagnetic nanoparticles has been validated by numerous experimental studies in the case of spherical particles. Recently, several studies focused on the synthesis of cubic nanoparticles. Some of them reported significantly higher relaxivities compared to their spherical counterpart and attributed this increase to their specific shapes. This work investigates the impact of cube-shaped nanoparticles on nuclear magnetic relaxation through Monte Carlo methods. Transverse relaxation at high static magnetic field is simulated by modeling the proton diffusion in the magnetic field generated by a cubic or a spherical nanoparticle. The results indicate that, in the case of magnetite nanoparticles, there is no significant difference between both shapes for sizes above 30 nm when particles are compared at equal volumes and magnetization. Below this size, a −40%–15% variation of the relaxation rates is predicted for the cubic case compared to the spherical case. These results are explained using general relaxation models that incorporate the distribution of the magnetic field generated by the nanoparticles. The simulation predictions are compared to some experimental results from the literature, revealing that, in some cases, the magnetic field specific to the nanoparticle shape alone cannot explain the observed increase in the relaxation rate of cubic nanoparticles.

Association between Body Roundness Index and Depression Among Middle-aged and Older Adults in Chinese Communities: An Empirical Analysis Based on CHARLS Data

Background The relationship between depression and obesity has been confirmed by multiple studies. Compared to conventional measurement indicators such as body mass index or waist circumference, the body roundness index (BRI) demonstrates higher accuracy in assessing body fat content, especially visceral adiposity. Nevertheless, despite the advantages of BRI in measuring fat, the specific link between BRI and depression remains unclear. This study aims to clarify the potential correlation using data from the China Health and Retirement Longitudinal Study (CHARLS). Methods This study used CHARLS data from 2015 and 2020. We screened and included 7,258 middle-aged and older adults without depressive symptoms at baseline. We explored the connection between BRI and depression risk through logistic regression analyses, restricted cubic spline analyses, subgroup analyses, and interaction tests Results After adjusting for covariates, a positive correlation was observed between BRI and depression risk. Specifically, a one-unit increase in BRI led to a 14% increase in depression risk (OR =  1.14, 95% CI: 1.09-1.20, P <  0.001). Conclusion BRI is linked to a higher risk of depression in middle-aged and older adults in China and can be used as a simple indicator to predict depression.

Disentangling signal contributions in two-dimensional electronic spectroscopy in the pump–probe geometry

Since its introduction almost three decades ago, two-dimensional electronic spectroscopy (2DES) has evolved into a mature and powerful technique to reveal the inner workings of quantum systems with high temporal and spectral resolution. In general, this technique can isolate different contributions to the nonlinear response and provides access to different dynamical quantum pathways of the system evolution. Such isolation of pathways can be achieved in different experimental geometries. In its original, fully noncollinear implementation, directional phase matching allows for such signal isolation, while in the modern commonly employed pump–probe geometry, experimentally challenging phase-cycling schemes are employed. Here, we show how rephasing, non-rephasing, and zero- and double-quantum 2DES signals can be isolated in the pump–probe geometry without a need for phase-cycling. For this, we utilize established causality restrictions of the nonlinear response, allowing us to separate the different contributions in the spectral domain. We demonstrate this using data recorded for a molecular J-aggregate, acting as an effective three-level system. This approach bridges the gap between the capabilities of shaper-based and fully noncollinear 2DES and experimentally simpler implementations, such as those based on birefringent common-path interferometers.

Correction: Substance use and disordered eating risk among college students with obsessive-compulsive conditions

On the spectral shape of the structural relaxation in supercooled liquids

Structural relaxation in supercooled liquids is non-exponential. In susceptibility representation, χ″(ν), the spectral shape of the structural relaxation is observed as an asymmetrically broadened peak with a ν1 low- and ν−β high-frequency behavior. In this perspective article, we discuss common notions, recent results, and open questions regarding the spectral shape of the structural relaxation. In particular, we focus on the observation that a high-frequency behavior of ν−1/2 appears to be a generic feature in a broad range of supercooled liquids. Moreover, we review extensive evidence that contributions from orientational cross-correlations can lead to deviations from the generic spectral shape in certain substances, in particular in dielectric loss spectra. In addition, intramolecular dynamics can contribute significantly to the spectral shape in substances containing more complex and flexible molecules. Finally, we discuss the open questions regarding potential physical origins of the generic ν−1/2 behavior and the evolution of the spectral shape toward higher temperatures.

Electric vehicle braking energy recovery control method integrating fuzzy control and improved firefly algorithm

Braking energy recovery is crucial for improving the energy efficiency and extending the range of electric vehicles. If a large amount of braking energy is wasted, it will lead to problems such as reduced range and increased battery burden for electric vehicles. Therefore, an electric vehicle braking energy recovery control model that integrates fuzzy control algorithm with genetic firefly algorithm is proposed. Experimental analysis showed that the decrease in the state of charge of the model was 12.44%, and the braking energy recovery rate reached 52.1% in practical applications. Based on the above data, the proposed method can effectively control the amount of energy recovery. In addition, when the system chip value was 10%, the total amount of recovered energy at the battery end was the highest. Conversely, the total amount of recovered energy at the battery end was relatively small. In summary, the designed electric vehicle braking energy recovery control model can effectively control the amount of braking energy recovery of electric vehicles, ensuring the maximum recovery while also considering the durability and driving stability of the vehicle battery. The method can effectively extend mileage range in the electric vehicle industry, promoting the development and technological innovation of the new energy industry.

Triplet pair dynamics of singlet fission in orthorhombic polycrystalline powder of rubrene as revealed by magnetoluminescence

Singlet fission, which may increase the energy conversion efficiency of solar cells, proceeds via multiple spin levels of a triplet pair. To clarify the spin-related elementary processes of the triplet pair, we measured the magnetoluminescence effect of the fluorescence of rubrene, in the form of orthorhombic polycrystalline powder, in the range of ±300 mT at room temperature. Model simulations using the density matrix method were performed to elucidate how the features of the magnetoluminescence effect depend on the triplet pair dynamics. Simulations of the observed field dependence of the magnetoluminescence effect revealed an anisotropy of 1:100 for the two-dimensional hopping of triplet excitons forming a triplet pair in the ab plane, for which the exchange interaction depends on the separation distance between the two triplet excitons. The effective lifetime of the spin-correlated triplet pair responsible for the magnetoluminescence effect is estimated to be 2.2 ns.

DMCM: Dwo-branch multilevel feature fusion with cross-attention mechanism for infrared and visible image fusion

In response to the limitations of current infrared and visible light image fusion algorithms—namely insufficient feature extraction, loss of detailed texture information, underutilization of differential and shared information, and the high number of model parameters—this paper proposes a novel multi-scale infrared and visible image fusion method with two-branch feature interaction. The proposed method introduces a lightweight multi-scale group convolution, based on GS convolution, which enhances multi-scale information interaction while reducing network parameters by incorporating group convolution and stacking multiple small convolutional kernels. Furthermore, the multi-level attention module is improved by integrating edge-enhanced branches and depthwise separable convolutions to preserve detailed texture information. Additionally, a lightweight cross-attention fusion module is introduced, optimizing the use of differential and shared features while minimizing computational complexity. Lastly, the efficiency of local attention is enhanced by adding a multi-dimensional fusion branch, which bolsters the interaction of information across multiple dimensions and facilitates comprehensive spatial information extraction from multimodal images. The proposed algorithm, along with seven others, was tested extensively on public datasets such as TNO and Roadscene. The experimental results demonstrate that the proposed method outperforms other algorithms in both subjective and objective evaluation results. Additionally, it demonstrates good performance in terms of operational efficiency. Moreover, target detection performance experiments conducted on the M3FD dataset confirm the superior performance of the proposed algorithm.

Dimerization of model polymer chains under nonequilibrium conditions

Dimerization and subsequent aggregation of polymers and biopolymers often occur under nonequilibrium conditions. When the initial state of the polymer is not collapsed, or the final folded native state, the dynamics of dimerization can follow a course sensitive to both the initial conditions and the conformational dynamics. Here, we study the dimerization process by using computer simulations and analytical theory, where the two monomeric polymer chains are in the elongated state and are initially placed at a separation distance, d0. Subsequent dynamics lead to the concurrent processes of collapse, dimerization, and/or escape. We employ Langevin dynamics simulations with a coarse-grained model of the polymer to capture certain aspects of the dimerization process. At separations d0 much shorter than the length of the monomeric polymer, the dimerization could happen fast and irreversibly from the partly extended polymer state itself. At an initial separation larger than a critical distance, dc, the polymer collapse precedes dimerization, and a significant number of single polymers do not dimerize within the time scale of simulations. To quantify these competitions, we introduce several time-dependent order parameters, namely, (i) the time-dependent radius of gyration RG(t) of individual polymers describing the conformational state of the polymer, (ii) a center-to-center of mass distance parameter RMM, and (iii) a time dependent overlap function Q(t) between the two monomeric polymers, mimicking the contact order parameter popular in protein folding. In order to better quantify the findings, we perform a theoretical analysis to capture the stochastic processes of collapse and dimerization by using the dynamical disorder model.

Frequency, predictors and outcomes of intradialytic complications in patients on maintenance haemodialysis in Dar es Salaam: Prospective longitudinal study

Introduction Hemodialysis is a crucial renal replacement therapy option for end stage renal disease (ESRD) patients. Currently, there is a rise of patients who require hemodialysis with concurrent rise in intradialytic complications which can potentiate several outcomes some of which are life threatening. This study assessed the frequency, predictors, and outcomes of intradialytic complications amongst ESRD patients on maintenance hemodialysis. Methodology Prospective longitudinal study using self-designed questionnaires including patient’s demographic data and relevant past medical history, pre-hemodialysis assessment and intra-dialysis monitoring was done for 2 months at Aga Khan Hospital and Muhimbili National Hospital, in Dar es salaam, Tanzania. Results 215 patients were enrolled, of which 138(64.2%) were males with mean age 57(SD 15.37), height 1.64(SD 0.08) and weight 69.27(SD 12.62). Most patients 197(91.6%), were on thrice weekly schedule of which the duration of each session in most patients 206(95.8%) was 4 hours. Diabetes mellitus was the most common etiology of ESRD 126 (58.6%), ArterioVenous fistula (AVF) was the most common vascular access for the procedure 90(41.9%) and mostly, high flux dialyzers were used, FX100 & FX80, (211, 98.2%). There was a statistically significant association between pre-dialysis vital signs, blood flow rate and sex (p value <  0.05) with intradialytic hypertension and hypotension. Interestingly, male sex appeared to elicit a protective effect on intradialytic hypotension (p value < 0.001). Conclusion Hemodialysis is a life-saving procedure with multiple complications of which some have detrimental outcomes. Nonetheless, having a good understanding of the factors associated with the complications, appropriate management and ways of preventing them will remarkably improve the procedure and make it a safer renal replacement modality. Carefully, monitoring pre-dialysis vitals and taking necessary measures when deranged, individualized proper machine settings, sufficient fluid removal and standard blood flow rate may improve the dialysis procedure.

Memory, hysteresis, and kinetic cooperativity in stochastic mnemonic networks

Mnemonic networks are cyclic catalytic networks of monomeric enzymes that exhibit kinetic cooperativity as departures of the mean velocity from the hyperbolic, Michaelis–Menten-like response. In addition, such networks admit a hysteretic response when conformational fluctuations are slow compared to the catalytic rate. Here, we show how these fluctuation-driven effects emerge from the underlying stochasticity in the network. We use the chemical master equation to study the stochastic kinetics of mnemonic networks, which, in their minimal form, include a pair of conformers and triangular reaction pathways. We introduce statistical measures that are conditional on the turnovers to comprehensively analyze molecular fluctuations in the transient and stationary states of these networks. In the transient state, temporal correlations between enzyme turnovers lead to an inequivalence between number and temporal fluctuations, yielding a hysteretic response of the mean velocity to substrates. The transient relaxes to a stationary state with independent and identically distributed turnovers and equality between number and temporal fluctuations. This state is a non-equilibrium stationary state (NESS) when the Kolmogorov loop criterion is not satisfied, leading to the emergence of kinetic cooperativity. The symmetry of the number correlation functions allows us to distinguish between the absence of cooperativity in equilibrium and the accidental vanishing of cooperativity in a NESS. We conclude that memory and hysteresis are transient effects while kinetic cooperativity emerges as the macroscopic manifestation of the microscopic irreversibility of the NESS in a network with cyclic reaction pathways.

Family’s perceptions of their members who use nyaope in Tshwane, South Africa

Introduction Over the last two decades, nyaope use has evolved to become a prominent substance use disorder in South Africa, posing a significant public health burden. The majority of users are young people who are solely concerned with their next nyaope joint. This study aimed to explore the perception of family members on the factors associated with the use of and dependency on nyaope. Methods This was a descriptive exploratory qualitative study conducted in Tshwane, South Africa. Data were collected from 32 family members of Nyaope users via three focus group interviews conducted by a retired psychologist nurse in the three townships of Tshwane. Results The findings revealed a complex and interconnected web of elements that shape the journey of individuals from the onset of nyaope use to the point of dependence and eventual departure from their family homes. Rather than following a linear path of events, this pathway is characterised by a dynamic interplay of seven distinct themes, namely concealed nyaope use, family concerns and suspicions regarding nyaope use, confirmation of nyaope use, possible reasons for using nyaope, barriers to obtaining assistance for nyaope users, family distress, and the transition from home to a life on the streets. Conclusion Most users ended up being disconnected from their families. Family members’ opinions noted that the problem is perceived to be a web of elements working together rather than a linear path of events. The findings have implications for substance use services, social services, health and police services as well as schools.

Relativistic energy transfer

Energy transfer processes are ubiquitous in nature and intensely investigated. The investigations concentrate on the transfer of small to intermediate sized energies. Here, we pose the question of whether the transfer of large energies, where relativistic effects play a central role, can be efficient. At large energies, the process leads to ionization of the environment, i.e., it is the interatomic (or intermolecular) Coulombic decay (ICD) process. To that end, we derive asymptotic expressions for the ICD amplitude by employing the Dirac–Breit Hamiltonian and expanding the frequency dependent Coulomb–Breit interaction between the electrons of the donor and those of the acceptor in powers of the inverse distance between their centers of mass. Expressions are separately derived for the two popular Feynman and Coulomb gauges. At long range, the two expressions have a different appearance but are proven to be equivalent. The derived energy transfer rate at long range shows that when the donor is embedded in an environment, the transfer can be highly efficient. A key is that the radiative lifetime of the donor is extremely short (it can be in the attosecond, 10−18 s, regime), and the x-ray emission typically dominates by far Auger decay (also called Auger–Meitner decay), and the ICD can quench this emission. This contrasts with the situation at small to intermediate sized energies, where the radiative lifetime is much smaller and Auger decay (if the channel is open) dominates. In these cases, the major contribution to ICD comes from the neighbors nearby.

Time-resolved nonlinear microspectroscopy with Gaussian beams

Time-resolved nonlinear microspectroscopy bridges high-resolution imaging and ultrafast spectroscopy, enabling the investigation of spatially localized molecular excited state and exciton dynamics on ultrafast timescales. By integrating ultrafast techniques such as pump–probe and coherent multidimensional spectroscopy with microscopy techniques utilizing high numerical aperture objective lenses and structured beams, these approaches provide label-free chemical contrast and reveal transient phenomena critical to understanding complex systems. Recent advancements, including adaptive optics and tailored beam profiles, have further enhanced spatial and temporal control, unlocking new possibilities for studying heterogeneous systems. This work explores time-resolved nonlinear microspectroscopy using Laguerre–Gaussian beams with orbital angular momentum. Analytical expressions for pump–probe microspectroscopy signals are derived to elucidate how beam parameters influence nonlinear responses reflecting spatial diffusion and ultrafast relaxation processes. The results demonstrate the potential of customized ultrafast pulses and spatial light fields to improve both resolution and sensitivity, advancing dynamic studies in materials science, chemistry, and biology.

High-pressure and high-temperature thermoelasticity of tantalum: An <i>ab initio</i> study

We present the thermoelastic properties of the body-centered cubic tantalum calculated within the quasi-harmonic approximation (QHA) and compare them with those given by the quasi-static approximation (QSA) and those measured experimentally. We find that the QHA temperature dependent elastic constants (TDECs) follow the experiment very well from 5 K up to 500 K, and in this range of temperatures are in better agreement with the experiment than the QSA TDECs. At higher temperatures, our QHA results are linear with temperature and fail to follow the measured change in slope of C(T) and C44(T) that become parallel to the QSA results. We also present our QHA pressure dependent elastic constants at 5, 300, 1000, and 1500 K.