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Herein, a control method based on the optimal energy efficiency of a hydraulic quadruped robot was proposed, which not only realizes the optimal energy efficiency of flying trot gait but also ensures the stability of high-speed movement. Concretely, the energy consumption per unit distance was adopted as the energy efficiency evaluation index based on the constant pressure oil supply characteristics of the hydraulic system, and the global optimization algorithm was adopted to solve the optimal parameters. Afterward, the gait parameters that affect the energy efficiency of quadruped were analyzed and the mapping relationship between each parameter and energy efficiency was captured, so as to select the optimum combination of energy efficiency parameters, which is significant to improve endurance capability. Furthermore, to ensure the stability of the high-speed flying trot gait motion of the hydraulic quadruped robot, the active compliance control strategy was employed. Lastly, the proposed method was successfully verified by simulations and experiments. The experimental results reveal that the flying trot gait of the hydraulic quadruped robot can be stably controlled at a speed of 2.2 m/s.

This paper introduces a self-sensing anthropomorphic robot hand driven by Twisted String Actuators (TSAs). The use of TSAs provides several advantages such as muscle-like structures, high transmission ratios, large output forces, high efficiency, compactness, inherent compliance, and the ability to transmit power over distances. However, conventional sensors used in TSA-actuated robotic hands increase stiffness, mass, volume, and complexity, making feedback control challenging. To address this issue, a novel self-sensing approach is proposed using strain-sensing string based on Conductive Polymer Composite (CPC). By measuring the resistance changes in the strain-sensing string, the bending angle of the robot hand's fingers can be estimated, enabling closed-loop control without external sensors. The developed self-sensing anthropomorphic robot hand comprises a 3D-printed structure with five fingers, a palm, five self-sensing TSAs, and a 3D-printed forearm. Experimental studies validate the self-sensing properties of the TSA and the anthropomorphic robot hand. Additionally, a real-time Virtual Reality (VR) monitoring system is implemented for visualizing and monitoring the robot hand's movements using its self-sensing capabilities. This research contributes valuable insights and advancements to the field of intelligent prosthetics and robotic end grippers.

In this paper, we present the development of our latest flapping-wing micro air vehicle (FW-MAV), named Explobird, which features two wings with a wingspan of 195 mm and weighs a mere 25.2 g, enabling it to accomplish vertical take-off and hover flight. We devised a novel gear-based mechanism for the flapping system to achieve high lift capability and reliability and conducted extensive testing and analysis on the wings to optimise power matching and lift performance. The Explobird can deliver a peak lift-to-weight ratio of 1.472 and an endurance time of 259 s during hover flight powered by a single-cell LiPo battery. Considering the inherent instability of the prototype, we discuss the derivatives of its longitudinal system, underscoring the importance of feedback control, position of the centre of gravity, and increased damping. To demonstrate the effect of damping enhancement on stability, we also designed a passive stable FW-MAV. Currently, the vehicle is actively stabilised in roll by adjusting the wing root bars and in pitch through high-authority tail control, whereas yaw is passively stabilised. Through a series of flight tests, we successfully demonstrate that our prototype can perform vertical take-off and hover flight under wireless conditions. These promising results position the Explobird as a robust vehicle with high lift capability, paving the way towards the use of FW-MAVs for carrying load equipment in multiple tasks.

In-pipe robots have been widely used in pipes–with smooth inner walls. However, current in-pipe robots face challenges in terms of moving past obstacles and climbing in marine-vessel pipeline systems, which are affected by marine biofouling and electrochemical corrosion. This paper takes inspiration from the dual-hook structure of Trypoxylus dichotomus’s feet and gecko?like dry adhesives, proposing an in-pipe robot that is capable of climbing on rough and smooth pipe inwalls. The combination of the bioinspired hook and dry adhesives allows the robot to stably attach to rough or smooth pipe inwalls, while the wheel-leg hybrid mechanism provides better conditions for obstacle traversal. The paper explores the attachment and obstacle-surmounting mechanisms of the robot. Moreover, motion strategies for the robot are devised based on different pipe structural features. The experiments showed that this robot can adapt to both smooth and rough pipe environments simultaneously, and its motion performance is superior to conventional driving mechanisms. The robot’s active turning actuators also enable it to navigate through horizontally or vertically oriented 90° bends.

In developing and exploring extreme and harsh underwater environments, underwater robots can effectively replace humans to complete tasks. To meet the requirements of underwater flexible motion and comprehensive subsea operation, a novel octopus-inspired robot with eight soft limbs was designed and developed. This robot possesses the capabilities of underwater bipedal walking, multi-arm swimming, and grasping objects. To closely interact with the underwater seabed environment and minimize disturbance, the robot employs a cable-driven flexible arm for its walking in underwater floor through a bipedal walking mode. The multi-arm swimming offers a means of three-dimensional spatial movement, allowing the robot to swiftly explore and navigate over large areas, thereby enhancing its flexibility. Furthermore, the robot’s walking arm enables it to grasp and transport objects underwater, thereby enhancing its practicality in underwater environments. A simplified motion models and gait generation strategies were proposed for two modes of robot locomotion: swimming and walking, inspired by the movement characteristics of octopus-inspired multi-arm swimming and bipedal walking. Through experimental verification, the robot’s average speed of underwater bipedal walking reaches 7.26 cm/s, while the horizontal movement speed for multi-arm swimming is 8.6 cm/s.

The lightweight design of hydraulic quadruped robots, especially the lightweight design of the leg joint Hydraulic Drive Unit (HDU), can improve the robot's response speed, motion speed, endurance, and load capacity. However, the lightweight design of HDU is a huge challenge due to the need for structural strength. This paper is inspired by the geometric shape of fish bones and biomimetic reinforcing ribs on the surface of the HDU shell are designed to increase its strength and reduce its weight. First, a HDU shell with biomimetic fish bone reinforcing ribs structure is proposed. Then, the MATLAB toolbox and ANSYS finite element analysis module are used to optimize the parameters of the biomimetic reinforcing ribs structure and the overall layout of the shell. Finally, the HDU shell is manufactured using additive manufacturing technology, and a performance testing platform is built to conduct dynamic and static performance tests on the designed HDU. The experimental results show that the HDU with biomimetic fish bone reinforcing ribs has excellent dynamic performance and better static performance than the prototype model, and the weight of the shell is reduced by 20% compared to the prototype model. This work has broad application prospects in the lightweight and high-strength design of closed-pressure vessel components.

Perching allows small Unmanned Aerial Vehicles (UAVs) to maintain their altitude while significantly extending their flight duration and reducing noise. However, current research on flying habitats is poorly adapted to unstructured environments, and lacks autonomous capabilities, requiring ideal experimental environments and remote control by personnel. To solve these problems, in this paper, we propose a bat-like UAV perching mechanism by investigating the bat upside-down perching method, which realizes double self-locking in the perching state using the ratchet and four-link dead point mechanisms. Based on this perching mechanism, this study proposes a control strategy for UAVs to track targets and accomplish flight perching autonomously by combining a binocular camera, single-point LiDAR, and pressure sensors. Autonomous perching experiments were conducted for crossbar-type objects outdoors. The experimental results show that a multirotor UAV equipped with the perching mechanism and sensors can reliably achieve autonomous flight perching and re-flying off the target outdoors. The power consumption is reduced to 2.9% of the hovering state when perched on the target object.

The earthworm has been attracted much attention in the research and development of biomimetic robots due to their unique locomotion mechanism, compact structure, and small motion space. This paper presents a new design and prototype of a worm-inspired metameric robot with a movement pattern similar to that of earthworms. The robot consists of multiple telescopic modules connected in series through joint modules. The telescopic module mimics the contraction and elongation motion modes of the earthworm segments. A kinematic and dynamic analysis is conducted on the telescopic module, and an input torque calculation method is provided to ensure sufficient friction between the robot and the pipe wall. The gait modes of the prototype robot for straight and turning locomotion are introduced, and these modes are extended to robots constructed by different numbers of telescopic modules. In addition, a method is proposed to increase the friction between the robot and the pipe wall in the aforementioned gait modes without changing the robot structure, thereby improving the robot’s motion ability in pipelines. The theoretical model of gait modes has also been validated through gait experiments. The findings of this paper would provide a useful basis for the design, modeling, and control of future worm inspired robots.

Reinforcement learning (RL) provides much potential for locomotion of legged robot. Due to the gap between simulation and the real world, achieving sim-to-real for legged robots is challenging. However, the support polygon of legged robots can help to overcome some of these challenges. Quadruped robot has a considerable support polygon, followed by bipedal robot with actuated feet, and point-footed bipedal robot has the smallest support polygon. Therefore, despite the existing sim-to-real gap, most of the recent RL approaches are deployed to the real quadruped robots that are inherently more stable, while the RL-based locomotion of bipedal robot is challenged by zero-shot sim-to-real task. Especially for the point-footed one that gets better dynamic performance, the inevitable tumble brings extra barriers to sim-to-real task. Actually, the crux of this type of problem is the difference of mechanics properties between the physical robot and the simulated one, making it difficult to play the learned skills well on the physical bipedal robot. In this paper, we introduce the embedded mechanics properties (EMP) based on the optimization with Gaussian processes to RL training, making it possible to perform sim-to-real transfer on the BRS1-P robot used in this work, hence the trained policy can be deployed on the BRS1-P without any struggle. We validate the performance of the learning-based BRS1-P on the condition of disturbances and terrains not ever learned, demonstrating the bipedal locomotion and resistant performance.

Soft grippers have great potential applications in daily life, since they can compliantly grasp soft and delicate objects. However, the highly elastic fingers of most soft grippers are prone to separate from each other while grasping objects due to their low stiffness, thus reducing the grasping stability and load-bearing capacity. To tackle this problem, inspired from the venus flytrap plant, this work proposes a mutual-hook mechanism to restrain the separation and improve the grasping performance of soft fingers. The novel soft gripper design consists of three modules, a soft finger-cot, two Soft Hook Actuators(SHAs) and two sliding mechanisms. Here, the soft finger-cot covers on the soft finger, increasing the contact area with the target object, two SHAs are fixed to the left and right sides of the finger-cot, and the sliding mechanisms are designed to make SHAs stretch flexibly. Experiments demonstrate that the proposed design can restrain the separation of soft fingers substantially, and the soft fingers with the finger-cots can grasp objects three times heavier than the soft fingers without the proposed design. The proposed design can provide invaluable insights for soft fingers to restrain the separation while grasping, thus improving the grasping stability and the load-bearing capacity.

In rehabilitation training, it is crucial to consider the compatibility between exoskeletons and human legs in motion. However, most exoskeletons today adopt an anthropomorphic serial structure, which results in rotational centers that are not precisely aligned with the center of the hip joint. To address this issue, we introduce a novel exoskeleton called the Parallel Hip Exoskeleton (PH-Exo) in this paper. PH-Exo is meticulously designed based on the anisotropic law of output torque. Considering the friction of the drive components, a dynamic model of the human–machine complex is established. Simulation analysis demonstrates that PH-Exo not only exhibits outstanding torque performance but also achieves high controllability in both flexion/extension and adduction/abduction directions. Additionally, a robust controller is designed to address model uncertainty, friction, and external interference. Wearing experiments indicate that under the control of the robust controller, each motor achieves excellent tracking performance.

We previously developed a powered hip prosthetic mechanism with kinematic functions of hip flexion–extension and abduction–adduction, and its theoretical and simulation-based kinematics were verified. Because internal–external hip rotation has a positive effect on the movements of human lower limbs according to medical research, we developed a novel hip prosthetic mechanism based on a previous hip prosthesis that possesses motion characteristics similar to those of a human bionic hip, and the motion characteristics of multiple Degrees-of-Freedom (DoFs) were analyzed after kinematic modeling. Then, a walking model of the human?machine model was established, and the walking stability of an amputee, which reflects the rehabilitation effect, was explored while the hip prosthetic mechanism considered the internal–external rotation of the hip. Finally, a prototype and its verification platform were built, and kinematic validation of the hip prosthetic mechanism was carried out. The results showed that the designed Parallel Mechanism (PM) possesses human-like motion characteristics similar to those of a human bionic hip and can be used as a hip prosthesis. Moreover, the existing motion characteristic of internal–external hip rotation can enhance the walking stability of an amputee via this hip prosthetic mechanism.

The precise movement speed regulation is a key factor to improve the control effect and efficiency of the cyborg rats. However, the current stimulation techniques cannot realize the graded control of the speed. In this study, we achieved the multi-level speed regulation of cyborg rats in the large open field and treadmill by specifically targeting the Cuneiform Nucleus (CnF) of the Mesencephalic Locomotor Region (MLR). Detailed, we measured the influence of each stimulation parameter on the speed control process which included the real-time speed, accelerated speed, response time, and acceleration period. We concluded that the pulse period and the pulse width were the main determinants influencing the accelerated speed of cyborg rats. Whereas the amplitude of stimulation was found to affect the response time exhibited by the cyborg rats. Our study provides valuable insights into the regulation of rat locomotion speed and highlights the potential for utilizing this approach in various experimental settings.

Amplifying the intrinsic wettability of substrate material by changing the solid/liquid contact area is considered to be the main mechanism for controlling the wettability of rough or structured surfaces. Through theoretical analysis and experimental exploration, we have found that in addition to this wettability structure amplification effect, the surface structure also simultaneously controls surface wettability by regulating the wetting state via changing the threshold Young angles of the Cassie–Baxter and Wenzel wetting regions. This wetting state regulation effect provides us with an alternative strategy to overcome the inherent limitation in surface chemistry by tailoring surface structure. The wetting state regulation effect created by multi-scale hierarchical structures is quite significant and plays is a crucial role in promoting the superhydrophobicity, superhydrophilicity and the transition between these two extreme wetting properties, as well as stabilizing the Cassie–Baxter superhydrophobic state on the fabricated lotus-like hierarchically structured Cu surface and the natural lotus leaf.

Superhydrophobic coatings with high non-wetting properties are widely applied in anti-icing applications. However, the
micro-nanostructures on the surfaces of superhydrophobic coatings are fragile under external forces, resulting in reduced
durability. Therefore, mechanical strength and durability play a crucial role in the utilization of superhydrophobic materials.
In this study, we employed a two-step spraying method to fabricate superhydrophobic FEVE-based coatings with
exceptional mechanical durability, utilizing fluorinated TiO2 nanoparticles and fluorinated Al2O3 microwhiskers as the
fillers. The composite coating exhibited commendable non-wetting properties, displaying a contact angle of 164.84° and
a sliding angle of 4.3°. On this basis, the stability of coatings was significantly improved due to the interlocking effect
of Al2O3 whiskers. After 500 tape peeling cycles, 500 sandpaper abrasion tests, and 50 kg falling sand impact tests, the
coatings retained superhydrophobicity, exhibiting excellent durability and application capability. Notably, the ice adhesion
strength on the coatings was measured at only 65.4 kPa, while the icing delay time reached 271.8 s at -15 °C. In addition,
throughout 500 freezing/melting cycles, statistical analysis revealed that the superhydrophobic coatings exhibited a
freezing initiation temperature as low as -17.25 °C.

Surface-tension-confined microfluidic devices are platforms for manipulating 2D droplets based on patterned surfaces with
special wettability. They have great potential for various applications, but are still in the early stages of development and
face some challenges that need to be addressed. This study, inspired by the Wenzel and slippery transition of rose petal,
develops a Patterned Oil-triggered Wenzel-slippery Surface (POWS) to examine the microfluidic devices. A laser-chemical
composite method is established to fabricate POWSs, which take rose-petal-like microstructures as wettability pattern and
a superamphiphobic surface as the background. The prepared POWSs switched between high adhesion superhydrophobic
state and the slippery liquid-infused surface state through adding or removing the lubricant oil. In the high adhesion
superhydrophobic state, the droplets can be sticked on the surface. In the slippery liquid-infused state, the droplet can slide
along the wettability pattern as the designed route. A POWS-based droplet reactor is further constructed, on which, the
droplets can be remotely controlled to move, mix and react, as required. Such a POWS, which manipulates droplets with
surface tension controlled by the switchable wettability patterns, would be a promising candidate to construct multiple
surface-tension-confined microfluidic devices. In addition, the fabrication technique and design principle proposed here
may aid the development of various field related to the bio-inspired surfaces, such as water collection, desalination and
high throughput analysis, etc.

Spine biomechanical testing methods in the past few decades have not evolved beyond employing either cadaveric studies
or finite element modeling techniques. However, both these approaches may have inherent cost and time limitations.
Cadaveric studies are the present gold standard for spinal implant design and regulatory approval, but they introduce significant
variability in measurements across patients, often requiring large sample sizes. Finite element modeling demands
considerable expertise and can be computationally expensive when complex geometry and material nonlinearity are introduced.
Validated analogue spine models could complement these traditional methods as a low-cost and high-fidelity alternative.
A fully 3D printable L-S1 analogue spine model with ligaments is developed and validated in this research. Rotational
stiffness of the model under pure bending loading in flexion-extension, Lateral Bending (LB) and Axial Rotation
(AR) is evaluated and compared against historical ex vivo and in silico models. Additionally, the effect of interspinous,
intertransverse ligaments and the Thoracolumbar Fascia (TLF) on spinal stiffness is evaluated by systematic construction
of the model. In flexion, model Range of Motion (ROM) was 12.92 ± 0.11° (ex vivo: 16.58°, in silico: 12.96°) at 7.5Nm.
In LB, average ROM was 13.67 ± 0.12° at 7.5 Nm (ex vivo: 15.21 ± 1.89°, in silico: 15.49 ± 0.23°). Similarly, in AR,
average ROM was 17.69 ± 2.12° at 7.5Nm (ex vivo: 14.12 ± 0.31°, in silico: 15.91 ± 0.28°). The addition of interspinous
and intertransverse ligaments increased both flexion and LB stiffnesses by approximately 5%. Addition of TLF showed
increase in flexion and AR stiffnesses by 29% and 24%, respectively. This novel model can reproduce physiological ROMs
with high repeatability and could be a useful open-source tool in spine biomechanics.

The disparity between the postoperative outcomes of rhinoplasty and the expected results frequently necessitates secondary
or multiple surgeries as a compensatory measure, greatly diminishing patient satisfaction. However, there is renewed optimism
for addressing these challenges through the innovative realm of Four-Dimensional (4D) printing. This groundbreaking
technology enables three-dimensional objects with shape-memory properties to undergo predictable transformations under
specific external stimuli. Consequently, implants crafted using 4D printing offer significant potential for dynamic adjustments.
Inspired by worms in our research, we harnessed 4D printing to fabricate a Shape-Memory Polyurethane (SMPU) for use
as a nasal augmentation prosthesis. The choice of SMPU was guided by its Glass Transition Temperature (
Tg), which falls
within the acceptable temperature range for the human body. This attribute allowed for temperature-responsive intraoperative
self-deformation and postoperative remodeling. Our chosen animal model for experimentation was rabbits. Taking into
account the anatomical structure of the rabbit nose, we designed and produced nasal augmentation prostheses with superior
biocompatibility. These prostheses were then surgically implanted in a minimally invasive manner into the rabbit noses.
Remarkably, they exhibited successful temperature-controlled in-surgery self-deformation according to the predetermined
shape and non-invasive remodeling within a mere 9 days post-surgery. Subsequent histological evaluations confirmed the
practical viability of these prostheses in a living organism. Our research findings posit that worm-inspired 4D-printed SMPU
nasal prostheses hold significant promise for achieving dynamic aesthetic adjustments.

The creation of 3D nanofibers offering desirable functions for bone regeneration is developed due to the latest improvisations
to the electrospinning technique. Synthetic polymers are among the best choices for medical usage due to their lower
costs, high tensile properties, and ease of spinnability compared to natural polymers. In this communication, we report a
series of interventions to polymers modified with Mg-based fillers for ideal tissue engineering applications. The literature
survey indicated that these filler materials (e.g., nano-sized particles) enhanced biocompatibility, antibacterial activity,
tensile strength, and anti-corrosive properties. This review discusses electrospinning parameters, properties, and applications
of the poly(ε-caprolactone), poly(lactic acid), poly(3-hydroxybutyric acid-co-3-hydroxy valeric acid), polyurethane,
and poly(vinyl pyrrolidone) nanofibers when modified with Mg-based fillers. This report encourages researchers to use
synthetic polymers with Mg as fillers and validate them for tissue engineering applications.

3D-printed Porous Titanium Alloy Implants (pTi), owing to their biologically inertness and relatively smooth surface
morphology, adversely affect the biological functions of surrounding cells. To address the challenges, constructing a bioinspired
interface that mimics the hierarchical structure of bone tissue can enhance the cellular functions of cells. In this
context, Hollow Mesoporous Silica Nanoparticles (HMSNs), renowned for their unique physicochemical properties and
superior biocompatibility, offer a promising direction for this research. In this research, the initially synthesized HMSNs
were used to construct a “hollow-mesoporous-macroporous” hierarchical bioinspired coating on the pTi surface through
the Layer-by-Layer technique. Simultaneously, diverse morphologies of coatings were established by adjusting the deposition
strategy of PDDA/HMSNs on the pTi surface (pTi-HMSN-2, pTi-HMSN-4, pTi-HMSN-6). A range of techniques
were employed to investigate the physicochemical properties and regulation of cellular biological functions of the diverse
HMSN coating strategies. Notably, the pTi-HMSN-4 and pTi-HMSN-6 groups exhibited the uniform coatings, leading
to a substantial enhancement in surface roughness and hydrophilicity. Meantime, the coating constructed strategy of pTi-
HMSN-4 possessed commendable stability. Based on the aforementioned findings, both pTi-HMSN-4 and pTi-HMSN-6
facilitated the adhesion, spreading, and pseudopodia extension of BMSCs, which led to a notable upsurge in the expression
levels of vinculin protein in BMSCs. Comprehensive analysis indicates that the coating, when PDDA/HMSNs are
deposited four times, possesses favorable overall performance. The research will provide a solid theoretical basis for the
translation of HMSN bioinspired coatings for orthopedic implants.

Excellent fluid sealing performance is crucial to ensuring the safety of important equipment, especially in aerospace field,
such as space capsule and fuel chamber. The frequently opening and closing of the sealing devices is particularly important.
Driven by this background, clams (Mactra chinensis) which can open and close their double shells with superior sealing
performance, are studied in this work. Here, we show that the clam’s sealing ability is the result of its unique multilevel
intermeshing microstructures, including hinge teeth and micro-blocks. These microstructures, which resemble gear teeth,
engage with each other when the shell closes, forming a tight structure that prevents the infiltration of water from the outside.
Furthermore, the presence of micron blocks prevents the penetration of finer liquids. The simulation results of the bionic
end seal components show that the multilevel microstructure has a superior sealing effect. This research is expected to be
applied to undersea vehicles that require frequent door opening and closing.

It is generally considered that heat treatments have a negative impact on the mechanical properties of nacre due to thermal
decomposition of the organic matrix. However, the present work investigated the microindentation behavior on fresh
and heat-treated nacres from two orthogonal directions, and the results demonstrate that both hardness value and damage
tolerance can remain almost unchanged on the cross-section with the organic matrix degeneration, despite a significant
deterioration on the platelet surface. Theoretical analyses suggest that the anisotropic response of indentation behavior to
heat treatment in nacre is primarily caused by its structural orientation. Specifically, compared with a single layer of irregular
interplatelet interfaces in cross-sectional specimens, the multiple layers of parallel interlamellar interfaces in in-plane
specimens exhibit a much greater ability to impede indenter-triggered destruction, and heat treatments would reduce the
in-plane hardness but nearly have no effect on the cross-sectional hardness. Moreover, the deeper embedding of platelets
in cross-sectional specimens enhances their resistance to interface cracking caused by organic matrix degradation at high
temperatures, leading to a reduced sensitivity to damage. Therefore, the indentation behavior of nacre shows different
tendencies in response to variations in the organic matrix state along normal and parallel directions.

The Whale Optimization Algorithm (WOA) is a swarm intelligence metaheuristic inspired by the bubble-net hunting tactic
of humpback whales. In spite of its popularity due to simplicity, ease of implementation, and a limited number of parameters,
WOA’s search strategy can adversely affect the convergence and equilibrium between exploration and exploitation
in complex problems. To address this limitation, we propose a new algorithm called Multi-trial Vector-based Whale Optimization
Algorithm (MTV-WOA) that incorporates a Balancing Strategy-based Trial-vector Producer (BS_TVP), a Local
Strategy-based Trial-vector Producer (LS_TVP), and a Global Strategy-based Trial-vector Producer (GS_TVP) to address
real-world optimization problems of varied degrees of difficulty. MTV-WOA has the potential to enhance exploitation and
exploration, reduce the probability of being stranded in local optima, and preserve the equilibrium between exploration and
exploitation. For the purpose of evaluating the proposed algorithm's performance, it is compared to eight metaheuristic
algorithms utilizing CEC 2018 test functions. Moreover, MTV-WOA is compared with well-stablished, recent, and WOA
variant algorithms. The experimental results demonstrate that MTV-WOA surpasses comparative algorithms in terms of the
accuracy of the solutions and convergence rate. Additionally, we conducted the Friedman test to assess the gained results
statistically and observed that MTV-WOA significantly outperforms comparative algorithms. Finally, we solved five engineering
design problems to demonstrate the practicality of MTV-WOA. The results indicate that the proposed MTV-WOA
can efficiently address the complexities of engineering challenges and provide superior solutions that are superior to those
of other algorithms.

This study, grounded in Waxman fusion method, introduces an algorithm for the fusion of visible and infrared images, tailored
to a two-level lighting environment, inspired by the mathematical model of the visual receptive field of rattlesnakes and the
two-mode cells' mechanism. The research presented here is segmented into three components. In the first segment, we design
a preprocessing module to judge the ambient light intensity and divide the lighting environment into two levels: day and night.
The second segment proposes two distinct network structures designed specifically for these daytime and nighttime images.
For the daytime images, where visible light information is predominant, we feed the ON-VIS signal and the IR-enhanced
visual signal into the central excitation and surrounding suppression regions of the ON-center receptive field in the B channel,
respectively. Conversely, for nighttime images where infrared information takes precedence, the ON-IR signal and the
Visual-enhanced IR signal are separately input into the central excitation and surrounding suppression regions of the ONcenter
receptive field in the B channel. The outcome is a pseudo-color fused image. The third segment employs five different
no-reference image quality assessment methods to evaluate the quality of thirteen sets of pseudo-color images produced by
fusing infrared and visible information. These images are then compared with those obtained by six other methods cited in
the relevant reference. The empirical results indicate that this study's outcomes surpass the comparative results in terms of
average gradient and spatial frequency. Only one or two sets of fused images underperformed in terms of standard deviation
and entropy when compared to the control results. Four sets of fused images did not perform as well as the comparison in
the QAB/
F index. In conclusion, the fused images generated through the proposed method show superior performance in
terms of scene detail, visual perception, and image sharpness when compared with their counterparts from other methods.

Medical image segmentation has witnessed rapid advancements with the emergence of encoder–decoder based methods.
In the encoder–decoder structure, the primary goal of the decoding phase is not only to restore feature map resolution, but
also to mitigate the loss of feature information incurred during the encoding phase. However, this approach gives rise to a
challenge: multiple up-sampling operations in the decoder segment result in the loss of feature information. To address this
challenge, we propose a novel network that removes the decoding structure to reduce feature information loss (CBL-Net). In
particular, we introduce a Parallel Pooling Module (PPM) to counteract the feature information loss stemming from conventional
and pooling operations during the encoding stage. Furthermore, we incorporate a Multiplexed Dilation Convolution
(MDC) module to expand the network's receptive field. Also, although we have removed the decoding stage, we still need
to recover the feature map resolution. Therefore, we introduced the Global Feature Recovery (GFR) module. It uses attention
mechanism for the image feature map resolution recovery, which can effectively reduce the loss of feature information.
We conduct extensive experimental evaluations on three publicly available medical image segmentation datasets: DRIVE,
CHASEDB and MoNuSeg datasets. Experimental results show that our proposed network outperforms state-of-the-art
methods in medical image segmentation. In addition, it achieves higher efficiency than the current network of coding and
decoding structures by eliminating the decoding component.

Energy issues have always been one of the most significant concerns for scientists worldwide. With the ongoing over
exploitation and continued outbreaks of wars, traditional energy sources face the threat of depletion. Wind energy is a
readily available and sustainable energy source. Wind farm layout optimization problem, through scientifically arranging
wind turbines, significantly enhances the efficiency of harnessing wind energy. Meta-heuristic algorithms have been widely
employed in wind farm layout optimization. This paper introduces an Adaptive strategy-incorporated Integer Genetic
Algorithm, referred to as AIGA, for optimizing wind farm layout problems. The adaptive strategy dynamically adjusts the
placement of wind turbines, leading to a substantial improvement in energy utilization efficiency within the wind farm. In
this study, AIGA is tested in four different wind conditions, alongside four other classical algorithms, to assess their energy
conversion efficiency within the wind farm. Experimental results demonstrate a notable advantage of AIGA.

Dynamic Economic Emission Dispatch (DEED) aims to optimize control over fuel cost and pollution emission, two
conflicting objectives, by scheduling the output power of various units at specific times. Although many methods wellperformed
on the DEED problem, most of them fail to achieve expected results in practice due to a lack of effective trade-off
mechanisms between the convergence and diversity of non-dominated optimal dispatching solutions. To address this issue,
a new multi-objective solver called Multi-Objective Golden Jackal Optimization (MOGJO) algorithm is proposed to cope
with the DEED problem. The proposed algorithm first stores non-dominated optimal solutions found so far into an archive.
Then, it chooses the best dispatching solution from the archive as the leader through a selection mechanism designed based
on elite selection strategy and Euclidean distance index method. This mechanism can guide the algorithm to search for
better dispatching solutions in the direction of reducing fuel costs and pollutant emissions. Moreover, the basic golden jackal
optimization algorithm has the drawback of insufficient search, which hinders its ability to effectively discover more Pareto
solutions. To this end, a non-linear control parameter based on the cosine function is introduced to enhance global exploration
of the dispatching space, thus improving the efficiency of finding the optimal dispatching solutions. The proposed MOGJO is
evaluated on the latest CEC benchmark test functions, and its superiority over the state-of-the-art multi-objective optimizers
is highlighted by performance indicators. Also, empirical results on 5-unit, 10-unit, IEEE 30-bus, and 30-unit systems show
that the MOGJO can provide competitive compromise scheduling solutions compared to published DEED methods. Finally,
in the analysis of the Pareto dominance relationship and the Euclidean distance index, the optimal dispatching solutions
provided by MOGJO are the closest to the ideal solutions for minimizing fuel costs and pollution emissions simultaneously,
compared to the latest published DEED solutions.

Snake Optimizer (SO) is a novel Meta-heuristic Algorithm (MA) inspired by the mating behaviour of snakes, which has
achieved success in global numerical optimization problems and practical engineering applications. However, it also has
certain drawbacks for the exploration stage and the egg hatch process, resulting in slow convergence speed and inferior
solution quality. To address the above issues, a novel multi-strategy improved SO (MISO) with the assistance of population
crowding analysis is proposed in this article. In the algorithm, a novel multi-strategy operator is designed for the exploration
stage, which not only focuses on using the information of better performing individuals to improve the quality of solution,
but also focuses on maintaining population diversity. To boost the efficiency of the egg hatch process, the multi-strategy egg
hatch process is proposed to regenerate individuals according to the results of the population crowding analysis. In addition,
a local search method is employed to further enhance the convergence speed and the local search capability. MISO is first
compared with three sets of algorithms in the CEC2020 benchmark functions, including SO with its two recently discussed
variants, ten advanced MAs, and six powerful CEC competition algorithms. The performance of MISO is then verified on
five practical engineering design problems. The experimental results show that MISO provides a promising performance
for the above optimization cases in terms of convergence speed and solution quality.

Pathfinder algorithm (PFA) is a swarm intelligent optimization algorithm inspired by the collective activity behavior of
swarm animals, imitating the leader in the population to guide followers in finding the best food source. This algorithm has
the characteristics of a simple structure and high performance. However, PFA faces challenges such as insufficient population
diversity and susceptibility to local optima due to its inability to effectively balance the exploration and exploitation
capabilities. This paper proposes an Ameliorated Pathfinder Algorithm called APFA to solve complex engineering optimization
problems. Firstly, a guidance mechanism based on multiple elite individuals is presented to enhance the global search
capability of the algorithm. Secondly, to improve the exploration efficiency of the algorithm, the Logistic chaos mapping
is introduced to help the algorithm find more high-quality potential solutions while avoiding the worst solutions. Thirdly,
a comprehensive following strategy is designed to avoid the algorithm falling into local optima and further improve the
convergence speed. These three strategies achieve an effective balance between exploration and exploitation overall, thus
improving the optimization performance of the algorithm. In performance evaluation, APFA is validated by the CEC2022
benchmark test set and five engineering optimization problems, and compared with the state-of-the-art metaheuristic algorithms.
The numerical experimental results demonstrated the superiority of APFA.