Classical Experiments Research Articles

Role Hierarchy as a Status Construction Machine: A Replication

Status construction theory offers a framework for investigating inequality-justifying consequences of microlevel encounters. While organizational role hierarchies (e.g., manager-employee or customer-server) dominate our daily encounters with categorically different others, there is no systematic empirical evaluation of the status construction effect of role hierarchies. I replicated the classic status construction experiment both in the lab and online to answer these questions. Results show that (1) the categorical membership consistently associated with a high-status role was stereotypically perceived as more respectable and leader-like but not more competent compared with the group linked to a low-status role and (2) only behavioral experience of the role hierarchy was sufficient to produce consensual status beliefs. Future implications and limitations are discussed.

UiO-66(Zr)-2OH-Supported Pd0 NP Catalysts Accelerated a Fenton-Like Reaction: Iron Cycling and Hydrogen Peroxide Generation Achieved Simultaneously.

Both the sluggish kinetics of Fe(II) regeneration and usage restriction of H2O2 have severely hindered the scientific progress of the Fenton reaction toward practical applications. Herein, a reduction strategy of activated hydrogen, which was used to simultaneously generate H2O2 and accelerate the regeneration of ferrous in a Fenton-like reaction based on the reduction of activated hydrogen derived from H2, was proposed. Two types of composite catalysts, namely, Pd/UiO-66(Zr)-2OH and Pd@UiO-66(Zr)-2OH, were successfully prepared by loading nano-Pd particles onto the outer and inner pores of UiO-66(Zr)-2OH in different loading modes, respectively. They were used to enhance the reduction of activated hydrogen. The characterization results based on the analysis of scanning electron microscopy, transmission electron microscopy, Fourier transform infrared spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy revealed that the materials were successfully prepared. By using a trace amount of ferrous iron and without adding H2O2, trimethoprim (C0 = 20 mg·L-1), as a target pollutant, could be nearly 100% degraded within 180 min in the reaction system composed of these two materials. The cycle of iron and the self-generation of H2O2 were verified by the detection of ferrous H2O2 in the system. Density functional theory calculation results further confirmed that the pore-filled Pd0 NPs, as the main catalytic site for Pd@UiO-66(Zr)-2OH, could produce H2O2 under the combined action of hydrogen and oxygen. The Pd@UiO-66(Zr)-2OH system had excellent stability after multiple applications (at least 6 cycles), all of which resulted in 100% removal of trimethoprim. The degradation efficiency of the Pd/UiO-66(Zr)-2OH system for TMP gradually decreased from 97 to 80% after six cycles. The results of electron paramagnetic resonance combined with classical radical burst experiments revealed the degradation pathways in the reaction system with hydroxyl radicals and singlet oxygen as the main reactive oxygen particles.

Intraspecific predator interference promotes biodiversity in ecosystems.

Explaining biodiversity is a fundamental issue in ecology. A long-standing puzzle lies in the paradox of the plankton: many species of plankton feeding on a limited variety of resources coexist, apparently flouting the competitive exclusion principle (CEP), which holds that the number of predator (consumer) species cannot exceed that of the resources at a steady state. Here, we present a mechanistic model and demonstrate that intraspecific interference among the consumers enables a plethora of consumer species to coexist at constant population densities with only one or a handful of resource species. This facilitated biodiversity is resistant to stochasticity, either with the stochastic simulation algorithm or individual-based modeling. Our model naturally explains the classical experiments that invalidate the CEP, quantitatively illustrates the universal S-shaped pattern of the rank-abundance curves across a wide range of ecological communities, and can be broadly used to resolve the mystery of biodiversity in many natural ecosystems.

Intraspecific predator interference promotes biodiversity in ecosystems

Explaining biodiversity is a fundamental issue in ecology. A long-standing puzzle lies in the paradox of the plankton: many species of plankton feeding on a limited variety of resources coexist, apparently flouting the competitive exclusion principle (CEP), which holds that the number of predator (consumer) species cannot exceed that of the resources at a steady state. Here, we present a mechanistic model and demonstrate that intraspecific interference among the consumers enables a plethora of consumer species to coexist at constant population densities with only one or a handful of resource species. This facilitated biodiversity is resistant to stochasticity, either with the stochastic simulation algorithm or individual-based modeling. Our model naturally explains the classical experiments that invalidate the CEP, quantitatively illustrates the universal S-shaped pattern of the rank-abundance curves across a wide range of ecological communities, and can be broadly used to resolve the mystery of biodiversity in many natural ecosystems.

Multidrug tolerance conferred by loss-of-function mutations in anti-sigma factor RshA of Mycobacterium abscessus.

Low-level drug resistance in noncanonical pathways can constitute steppingstones toward acquisition of high-level on-target resistance mutations in the clinic. To capture these intermediate steps in Mycobacterium abscessus (Mab), we performed classic mutant selection experiments with moxifloxacin at twofold its minimum inhibitory concentration (MIC) on solid medium. We found that low-level resistance emerged reproducibly as loss-of-function mutations in RshA (MAB_3542c), an anti-sigma factor that negatively regulates activity of SigH, which orchestrates a response to oxidative stress in mycobacteria. Since oxidative stress is generated in response to many antibiotics, we went on to show that deletion of rshA confers low to moderate resistance-by measure of MIC-to a dozen agents recommended or evaluated for the treatment of Mab pulmonary infections. Interestingly, this moderate resistance was associated with a wide range of drug tolerance, up to 1,000-fold increased survival of a ΔrshA Mab mutant upon exposure to several β-lactams and DNA gyrase inhibitors. Consistent with the putative involvement of the SigH regulon, we showed that addition of the transcription inhibitor rifabutin (RBT) abrogated the high-tolerance phenotype of ΔrshA to representatives of the β-lactam and DNA gyrase inhibitor classes. In a survey of 10,000 whole Mab genome sequences, we identified several loss-of-function mutations in rshA as well as non-synonymous polymorphisms in two cysteine residues critical for interactions with SigH. Thus, the multidrug multiform resistance phenotype we have uncovered may not only constitute a step toward canonical resistance acquisition during treatment but also contribute directly to treatment failure.

Pair‐Coordinated Calling: Eurasian Magpies Respond Differently to Simulated Intruder Pairs That Overlap or Alternate Their Calls

ABSTRACTAnimal vocalisations are widely used to signal strength or motivation of a caller in competitive interactions, such as in territorial defence. Substantial understanding of signalling functions in territorial conflicts is based on singing by male songbirds. Yet, in many species, both pair members call during territorial conflicts, as well as in predator‐induced situations, leading to complex signalling interactions in which calls overlap or alternate. This raises the question as to whether or not variation in how individuals in pairs time their calls is perceived as meaningful by receivers. Here, we tested with playback experiments whether Eurasian magpies (Pica pica), a species producing alarm calls (so‐called chatter calls) in territorial defence, respond stronger to simulated pair‐intruders who overlap their calls with each other than to those who alternate them. Magpies emitted a significantly longer first chatter calls in response to playback with overlapping calls but chattered significantly sooner and approached the loudspeakers significantly more closely in response to playbacks of alternating (and therefore longer) call sequences. These findings exemplify that the timing of calls by pair members matters, but in more complex ways than we predicted. The overlapping playback appeared to trigger a longer yet later initial chatter response and a weaker approach response, suggesting that the different ways in which magpies respond reflect different levels of arousal or defence strategies. The results may also reflect uncertainty by receivers due to a potential mismatch between signalled and perceived information: While overlapping calls may signal high arousal by both callers, a longer alternating sequence could be perceived as a more aroused longer signal. These findings expand on classical experiments on call function, suggesting that pairs can vary the message by coordinating their alarm calls in different ways, similar to how duetting pairs time their song contributions in advertisement signalling.

Ecological functional near-infrared spectroscopy in mobile children: using short separation channels to correct for systemic contamination during naturalistic neuroimaging.

The advances and miniaturization in functional near-infrared spectroscopy (fNIRS) instrumentation offer the potential to move the classical laboratory-based cognitive neuroscience investigations into more naturalistic settings. Wearable and mobile fNIRS devices also provide a novel child-friendly means to image functional brain activity in freely moving toddlers and preschoolers. Measuring brain activity in more ecologically valid settings with fNIRS presents additional challenges, such as the increased impact of physiological interferences. One of the most popular methods for minimizing such interferences is to regress out short separation channels from the long separation channels [i.e., superficial signal regression (SSR)]. Although this has been extensively investigated in adults, little is known about the impact of systemic changes on the fNIRS signals recorded in children in either classical or novel naturalistic experiments. We aim to investigate if extracerebral physiological changes occur in toddlers and preschoolers and whether SSR can help minimize these interferences. We collected fNIRS data from 3- to 7-year-olds during a conventional computerized static task and in a dynamic naturalistic task in an immersive virtual reality (VR) cave automatic virtual environment. Our results show that superficial signal contamination data are present in young children as in adults. Importantly, we find that SSR helps in improving the localization of functional brain activity, both in the computerized task and, to a larger extent, in the dynamic VR task. Following these results, we formulate suggestions to advance the field of developmental neuroimaging with fNIRS, particularly in ecological settings.

Experimental and numerical study on focused wave generation using different energy modes

This paper reports an experimental and numerical study on the generation of freak waves related to the spatiotemporal focusing mechanism, where multiple water waves converge at a specific point in space and time to produce a large transient wave. A new energy distribution mode of constant-difference wave number (CDK) within the wave group is proposed and applied to both a physical and a numerical flume to generate focused waves, with primary attention given to the water surface elevation, underlying kinematics, and internal spectrum structure during the focused wave generation process. The classical experiment by Baldock et al. [“A laboratory study of nonlinear surface waves on water,” Philos. Trans. R. Soc., Ser. A 354, 649–676 (1996)], which used a constant-difference wave period within the wave group, is chosen for comparison. Spectral analysis shows that the CDK energy distribution mode can easily stimulate multiwave resonance in the focused wave group, where significant energy transfer from the main frequencies to higher harmonics is observed. Compared with the data from Baldock et al. [“A laboratory study of nonlinear surface waves on water,” Philos. Trans. R. Soc., Ser. A 354, 649–676 (1996)], the CDK wave group produces larger focused wave crests with higher propagation speeds and larger velocity gradients near the water surface due to strong multiwave resonance. The effects of the input spectrum, incident amplitude and initial water depth under different energy modes on focused-wave generation are analyzed. All the results indicate that the CDK energy distribution mode can produce larger focused waves compared to other energy distribution modes, which offers a novel approach for generating freak waves in the laboratory.

A bi-component model to assess the rheology of soft cellular aggregates probed using the micropipette aspiration technique

The micro-pipette aspiration technique is a classical experiment used to characterize the physical properties of inert fluids and biological soft materials such as cellular aggregates. The physical parameters of the fluid, as viscosity and interfacial tension, are obtained by studying how the fluid enters the pipette when the suction pressure is increased and how it relaxes when the suction pressure is put to zero. A mathematical model representative of the experiment is needed to extrapolate the physical parameters of the fluid-like matter; however, for biological materials as cells or cell aggregates mathematical models are always based on strong starting hypotheses that impact the significance of the identified parameters. In this article, starting from the bi-constituent nature of the cell aggregate, we derive a general mathematical model based of a Cahn–Hilliard–Navier–Stokes set of equations. The model is applied to describe quantitatively the aspiration-retraction dynamics of a cell-aggregate into and out of a pipette. We demonstrate the predictive capability of the model and highlight the impact of the assumptions made on the identified parameters by studying two cases: one with a non-wetting condition between the cells and the wall of the pipette (classical assumption in the literature) and the second one, which is more realistic, with a partial wetting condition (contact angle θs = 150°). Furthermore, our results provide a purely physical explanation to the asymmetry between the aspiration and retraction responses which is alternative to the proposed hypothesis of an mechano-responsive alteration of the surface tension of the cell aggregate. Statement of significanceOur study introduces a general mathematical model, based on the Cahn-Hilliard-Navier-Stokes equations, tailored to model micro-pipette aspiration of cell aggregates. The model accounts for the multi-component structure of the cell aggregate and its intrinsic viscoelastic rheology. By challenging prevailing assumptions, particularly regarding perfect non-wetting conditions and the mechano-responsive alteration of cell surface tension, we demonstrate the reliability of the mathematical model and elucidate the mechanisms at play, offering a purely physical explanation for observed asymmetries between the aspiration and retraction stages of the experiment.

What Do News Disseminators and Audiences in the Digital Age Need Most? — Skills? Knowledge? Or Accuracy-Motivated Sceptical Knowing

In the digital age, journalism encounters both challenges and opportunities. Drawing on a wide range of classic discussions and investigative experiments, this article introduces the concept of “accuracy-motivated sceptical knowing.” This concept, driven by the verification of factual accuracy, represents a professional form of sceptical knowing and is crucial for becoming a responsible media professional and an informed citizen. This article discusses the necessity of transitioning from “general scepticism” to accuracy-motivated sceptical knowing. From the perspectives of both the disseminator and the audience, this article proposes methods for accuracy-motivated sceptical knowing: the disseminator should persist and innovate, while the audience should focus on the source, evidence, openness, and education, and both disseminators and audiences should embrace the “Hurtt Six Points” — questioning, suspension, search, empathy, self-esteem, and autonomy. Finally, this article clarifies the difference between accuracy-motivated sceptical knowing and related concepts, as well as the boundaries of its application.

Stop Fooling Yourself! (Diagnosing and Treating Confirmation Bias).

Confirmation bias (CB) is a cognitive bias that allows us to fool ourselves by selectively filtering data and distorting analyses to support favored beliefs or hypotheses. In this article, I will briefly review some classic experiments from cognitive psychology that illustrate what a powerful, pernicious, and insidious force CB is. I will then discuss how to recognize CB in our own thinking and behavior and describe specific elements of good experimental design that can mitigate its effects. These elements-such as randomization and blinding-are conceptually straightforward but often difficult in practice and therefore not as widely implemented as they should be.

Emission in the Biological Window from AIE-Based Carbazole-Substituted Furan-Based Compounds for Organic Light-Emitting Diodes and Random Lasers.

The emission quenching observed in devices utilizing luminescent materials such as solid thin films is a prevalent issue. Consequently, searching for new organic luminescent compounds exhibiting aggregation-induced emission (AIE) behavior and characterized by relatively simple and cost-effective synthesis is of crucial interest among applications from optoelectronics and organic lasing branches. Herein, we report the optical properties of three furan-based carbazole-substituted compounds, namely, tBuCBzSO2Ph, tBuCBzSPh, and tBuCbzTCF, exhibiting the aforementioned AIE phenomenon. The optical properties of dyes were determined in classical spectroscopic experiments supported by quantum-chemical calculations. The thermal investigations and electrochemical properties of dyes were performed to verify their usefulness in the construction of organic light-emitting diodes (OLEDs). In pursuit of this objective, OLEDs with a different design were fabricated, and their performance was subject to evaluation. In more detail, the different design strategies relying on the utilization of neat-dye films, as well as the preparation of dye-doped poly(9-vinylcarbazole):2-(4-tert-butylphenyl)-5-(4-biphenylyl)-1,3,4-oxadiazole (PVK:PBD) matrices were examined. The analysis that was conducted indicated the superior potential of tBuCBzSPh for optoelectronic applications. Notably, the positive impact of the AIE effect on the emission of the OLEDs and the ability to establish the lasing phenomenon in asymmetric, poly(methyl methacrylate) (PMMA)-doped polymeric slab waveguides were verified. The study showed that the combination of the strong intramolecular charge transfer (ICT) effect with dye aggregation enables the tuning of the emission of the OLED toward the first biological window, making examined dyes promising candidates for biomedical purposes. The same optical region can be attained for laser emission at relatively low pumping conditions, reaching as low as 7.3 kW of optical power for the tBuCBzSO2Ph compound.

Leapfrogging Sycamore: Harnessing 1432 GPUs for 7× faster quantum random circuit sampling

Abstract Random quantum circuit sampling serves as a benchmark to demonstrate quantum computational advantage. Recent progress in classical algorithms, especially those based on tensor network methods, has significantly reduced the classical simulation time and challenged the claim of the first-generation quantum advantage experiments. However, in terms of generating uncorrelated samples, time-to-solution, and energy consumption, previous classical simulation experiments still underperform the Sycamore processor. Here we report an energy-efficient classical simulation algorithm, using 1432 GPUs to simulate quantum random circuit sampling which generates uncorrelated samples with higher linear cross entropy score and is 7 times faster than the Sycamore 53 qubits experiment. We propose a post-processing algorithm to reduce the overall complexity, and integrate state-of-the-art high-performance general-purpose GPU to achieve two orders of lower energy consumption compared to previous works. Our work provides the first unambiguous experimental evidence to refute Sycamore’s claim of quantum advantage, and redefines the boundary of quantum computational advantage using random circuit sampling.

Gate-based quantum neurons in hybrid neural networks

Abstract Quantum computing is conceived as a promising and powerful next-generation platform for information processing and it has been shown that it could bring significant accelerations to certain tasks, compared to its classical counterparts. With recent advances in noisy intermediate-scale quantum (NISQ) devices, we can process classical data from real-world problems using hybrid quantum systems. In this work, we investigate the critical problem of designing a gate-based hybrid quantum neuron under NISQ constraints to enable the construction of scalable hybrid quantum deep neural networks (HQDNNs). We explore and characterize diverse quantum circuits for hybrid quantum neurons and discuss related critical components of HQDNNs. We also utilize a new schema to infer multiple predictions from a single hybrid neuron. We further compose a highly customizable platform for simulating HQDNNs via Qiskit and test them on diverse classification problems including the iris and the wheat seed datasets. The results show that even HQDNNs with the simplest neurons could lead to superior performance on these tasks. Finally, we show that the HQDNNs are robust to certain levels of noise, making them preferred on NISQ devices. Our work provides a comprehensive investigation of building scalable near-term gate-based HQDNNs and paves the way for future studies of quantum deep learning via both simulations on classical computers and experiments on accessible NISQ devices.

Do we really need ligands in Ir-catalyzed C-H borylation?

Direct borylation of C-H bonds is a privileged strategy to access versatile building blocks and valuable derivatives of complex molecules (late-stage functionalization, metabolite synthesis). This perspective aims to provide an overview and classification of the catalytic systems developed in this fast-growing area of research. Unexpected selectivity differences between two established directed-borylation systems have been discovered using high-throughput experimentation highlighting the importance of classical control experiments in catalysis research.

Decisional components of motor responses are not related to online response control: Evidence from lexical decision and speed-accuracy tradeoff manipulations.

Evidence suggests that decision processes can propagate to motor-response execution. However, the functional characterization of motor decisional components is not yet fully understood. By combining a classic lexical decision experiment with manipulations of speed-accuracy tradeoff (SAT), the present experiment assessed the hypothesis that decisional effects on chronometric measures of motor-response execution are related to online response control. The electromyographic (EMG) signal associated with manual button-press responses was used to dissociate the premotor component (from stimulus onset until the onset of the EMG activity) from the motor component (from EMG onset until the button-press), thus enabling the assessment of decision-related effects in terms of motor-response duration within single-trial reaction times. Other than replicating all the previously reported SAT effects, the experiment revealed hindered control processes when the instructions emphasized speed over accuracy, as indicated by measures of response control such as partial errors, fast errors, and correction likelihood. Nonetheless, the lexicality effect on motor responses, consisting of slower motor times for pseudowords compared to words, was impervious to any SAT modulation. The results suggest that SAT-induced variations in decision and response control policies may not be the prominent determinant of decision-related effects on motor times, highlighting the multiple "cognitive" components that affect peripheral response execution.

Astrocyte tau deposition in progressive supranuclear palsy is associated with dysregulation of MAPT transcription

Progressive supranuclear palsy (PSP) is a neurodegenerative disease characterized by 4R tau deposition in neurons as well as in astrocytes and oligodendrocytes. While astrocytic tau deposits are rarely observed in normal aging (so-called aging-related tau astrogliopathy, ARTAG) and Alzheimer’s disease (AD), astrocytic tau in the form of tufted astrocytes is a pathognomonic hallmark of PSP. Classical biochemical experiments emphasized tau synthesis in neurons in the central nervous system, suggesting that astrocytic tau inclusions might be derived from uptake of extracellular neuronal-derived tau. However, recent single-nucleus RNAseq experiments highlight the fact that MAPT, the gene encoding tau, is also expressed by astrocytes, albeit in lower amounts. We, therefore, revisited the question of whether astrocyte-driven expression of tau might contribute to astrocytic tau aggregates in PSP by performing fluorescent in situ hybridization/immunohistochemical co-localization in human postmortem brain specimens from individuals with PSP and AD with ARTAG as well as normal controls. We find that, in PSP but not in AD, tau-immunoreactive astrocytes have higher levels of MAPT mRNA compared to astrocytes that do not have tau aggregates. These results suggest that astrocytic responses in PSP are unique to this tauopathy and support the possibility that fundamental changes in PSP astrocyte-endogenous mRNA biology contribute to increased synthesis of tau protein and underlies the formation of the astrocytic tau deposits characteristic of PSP.

Nonequilibrium Antigen Recognition during Infections and Vaccinations

The initial immune response to an acute primary infection is a coupled process of antigen proliferation, molecular recognition by naive B cells, and their subsequent clonal expansion. This process contains a fundamental problem: the recognition of an exponentially time-dependent antigen signal. Here, we show that an efficient immune response must be stringently constrained to B-cell lineages with high antigen binding affinity. We propose a tuned proofreading mechanism for primary recognition of new antigens, where the molecular recognition machinery is adapted to the complexity of the immune repertoire. We show that this process produces potent, specific, and fast recognition of antigens, maintaining a spectrum of genetically distinct B-cell lineages as input for affinity maturation. Our analysis maps the proliferation-recognition dynamics of a primary infection to a generalized Luria-Delbrück process, akin to the dynamics of the classic fluctuation experiment. This map establishes a link between signal recognition dynamics and evolution. We derive the resulting statistics of the activated immune repertoire: Antigen binding affinity, expected size, and frequency of active B-cell clones are related by power laws, which define the class of generalized Luria-Delbrück processes. Their exponents depend on the antigen and B-cell proliferation rate, the number of proofreading steps, and the lineage density of the naive repertoire. We extend the model to include spatiotemporal processes, including the diffusion-recognition dynamics of a vaccination. Empirical data of activated mouse immune repertoires are found to be consistent with activation involving about three proofreading steps. The model predicts key clinical characteristics of acute infections and vaccinations, including the emergence of elite neutralizers and the effects of immune aging. More broadly, our results establish infections and vaccinations as a new probe into the global architecture and functional principles of immune repertoires. Published by the American Physical Society 2024

Optimizing microseismic monitoring: a fusion of Gaussian–Cauchy and adaptive weight strategies

Abstract In mining mineral resources, it is vital to monitor the stability of the rock body in real time, reasonably regulate the area of ground pressure concentration, and guarantee the safety of personnel and equipment. The microseismic signals generated by monitoring the rupture of the rock body can effectively predict the rock body disaster, but the current microseismic monitoring technology is not ideal. In order to address the issue of microseismic monitoring in deep wells, this research suggests a machine learning-based model for predicting microseismic phenomena. First, this work presents the random spare, double adaptive weight, and Gaussian–Cauchy fusion strategies as additions to the multi-verse optimizer (MVO) and suggests an enhanced MVO algorithm (RDGMVO). Subsequently, the RDGMVO-Fuzzy K-Nearest Neighbours (RDGMVO-FKNN) microseismic prediction model is presented by combining it with the FKNN classifier. The experimental section compares 12 traditional and recently enhanced algorithms with RDGMVO, demonstrating the latter’s excellent benchmark optimization performance and remarkable improvement effect. Next, the FKNN comparison experiment, the classical classifier experiment, and the microseismic dataset feature selection experiment confirm the precision and stability of the RDGMVO-FKNN model for the microseismic prediction problem. According to the results, the RDGMVO-FKNN model has an accuracy above 89%, indicating that it is a reliable and accurate method for classifying and predicting microseismic occurrences. Code has been available at https://github.com/GuaipiXiao/RDGMVO.

Fractional-Order Boosted Hybrid Young's Double-Slit Experimental Optimizer for Truss Topology Engineering Optimization.

Inspired by classical experiments that uncovered the inherent properties of light waves, Young's Double-Slit Experiment (YDSE) optimization algorithm represents a physics-driven meta-heuristic method. Its unique search mechanism and scalability have attracted much attention. However, when facing complex or high-dimensional problems, the YDSE optimizer, although striking a good balance between global and local searches, does not converge as fast as it should and is prone to fall into local optimums, thus limiting its application scope. A fractional-order boosted hybrid YDSE, called FYDSE, is proposed in this article. FYDSE employs a multi-strategy mechanism to jointly address the YDSE problems and enhance its ability to solve complex problems. First, a fractional-order strategy is introduced into the dark edge position update of FYDSE to ensure more efficient use of the search potential of a single neighborhood space while reducing the possibility of trapping in a local best. Second, piecewise chaotic mapping is constructed at the initial stage of the population to obtain better-distributed initial solutions and increase the convergence rate to the optimal position. Moreover, the low exploration space is extended by using a dynamic opposition strategy, which improves the probability of acquisition of a globally optimal solution. Finally, by introducing the vertical operator, FYDSE can better balance global exploration and local exploitation and explore new unknown areas. The numerical results show that FYDSE outperforms YDSE in 11 (91.6%) of cec2022 sets. In addition, FYDSE performs best in 8 (66.6%) among all algorithms. Compared with the 11 methods, FYDSE obtains the optimal best and average weights for the 20-bar, 24-bar, and 72-bar truss problems, which proves its efficient optimization capability for difficult optimization cases.