Recovery Capability Research Articles

Dynamic impact assessment of urban floods on the compound spatial network of buildings-roads-emergency service facilities

There are complex interactions among urban spatial elements in rainstorm scenarios. Road interruptions may cause isolation between partially submerged buildings and emergency service facilities, thereby affecting the recovery capability of flooded buildings and the accessibility of emergency service facilities. This study constructed a compound spatial network of urban buildings-roads-emergency service facilities, and analyzed the complex dynamic impacts of time-varying dynamic floods on building risk, road risk, and emergency service accessibility. Firstly, a refined flood risk assessment at the building scale was carried out in combination with flood inundation, building vulnerability, population, vulnerable areas, underground buildings, and life facilities. Secondly, betweenness centrality indicator in complex networks was used to calculate road traffic capacity and collapse threshold, and the accessibility of emergency service facilities is calculated based on road traffic capacity. Finally, the interaction and feedback relationships between the compound spatial network were analyzed. The results show that: (1) Flooded building comprehensive risk analysis reveals that floods have a significant impact on residential and commercial land use, and high-risk flood areas are mainly concentrated in the central region of study area. (2) The road network has a collapse threshold, and the fluctuating state of emergency service accessibility is significantly influenced by road traffic capacity. (3) Roads act as “bridges” connecting buildings and emergency service facilities, leading to the redistribution of building flood comprehensive risk and emergency service accessibility, presenting complex dynamic changes over time. Additionally, submerged roads also affect the accessibility of emergency service facilities around flooded buildings, reducing the recovery capacity of flooded buildings, and exhibiting significant heterogeneity characteristics. Future research should consider the complex impacts of floods on urban elements in order to better manage dynamic flood risk.

Biodiversity promotes resistance but dominant species shape recovery of grasslands under extreme drought

Abstract How biodiversity underpins ecosystem resistance (i.e. ability to withstand environmental perturbations) and recovery (i.e. ability to return to a pre‐perturbation state), and thus, stability under extreme climatic events is a timely question in ecology. To date, most studies have focussed on the role of taxonomic diversity, neglecting how community functional composition and diversity beget stability under exceptional climatic conditions. In addition, land use potentially modulates how biodiversity and ecosystem functions respond to extreme climatic conditions. Using an 11‐year time‐series of plant biomass from 150 permanent grassland plots spanning a gradient of land‐use intensity, we examined how taxonomic and functional components of biodiversity affected resistance and recovery of biomass under extreme drought. The association between biodiversity, land use and biomass varied across years, especially in the driest years. Species‐rich or functionally diverse communities (associated with low land‐use intensity) buffered extreme droughts better, while species‐poor communities or those dominated by fast‐growing species (associated with high land‐use intensity) had higher recovery capabilities after a moderate‐to‐extreme drought. Synthesis. Our results show that plant community functional and taxonomic components determine grasslands resistance and recovery under moderate‐to‐extreme drought. In turn, this points to the importance of designing landscapes with both extensively and intensively managed grasslands. Functionally or taxonomically rich communities (favoured under low land‐use intensity) would preserve biomass under extreme droughts, whereas species‐poor or fast‐growing communities (favoured by high land‐use intensity) would restore biomass after extreme droughts.

Coordinated control strategy of electro-mechanical composite braking for four-wheel drive electric vehicles

Regenerative braking energy recovery technology is critical for electric vehicles, which can significantly improve vehicle mileage. In addition, the regenerative braking system is often used with the friction braking system to provide vehicle braking force. This paper presents an electro-mechanical compound brake control strategy for four-wheel drive electric vehicles equipped with an electro-mechanical braking system. Firstly, the configuration of a four-wheel drive electric vehicle with an electro-mechanical braking system is introduced. The mathematical models of the driving motor, battery, and electro-mechanical braking are established. Secondly, a new control method is introduced by optimizing torque allocation based on maximum energy recovery with considering battery limits and a cooperative control method of the electro-mechanical composite braking system. It can be ensured that the braking energy recovery capability and braking comfort. Finally, simulation results indicate that the introduced control strategy can increase the braking recovered energy by 3% and 4%, respectively, under NEDC and WLTC conditions, compared to the ideal braking force distribution strategy. The introduced control method can effectively decrease the braking impact and ensure braking comfort in the coordination control section.

A distortion-free authentication method for color images with tampering localization and self-recovery

For immediate access and online backup, cloud storage has become a mainstream way for digital data storage and distribution. To assure images accessed or downloaded from clouds are reliable is critical to storage service providers. In this study, a new distortion-free color image authentication method based on secret sharing, data compression and image interpolation with the tampering recovery capability is proposed. The proposed method generates elaborate authentication signals which have double functions of tampering localization and image repairing. The authentication signals are subsequently converted into many shares with the use of (k, n)-threshold method so as to increase the multiplicity of authentication signals for reinforcing the capability of tampering recovery. These shares are then randomly concealed in the alpha channel of the to-be-protected image that has been transformed into the PNG format containing RGBA channels. In authentication, the authentication signals computed from the alpha channel are not only used for indicating if an image block has been tampered with or not, but used as a signal to find the corresponding color in a predefined palette to recover the tampered image block. Compared with several state-of-the-art methods, the proposed method attains positive properties including losslessness, tampering localization and tampering recovery. Experimental results and discussions on security consideration and comparison with other related methods are provided to demonstrate the outperformance of the proposed method.

The Impact of Digital Development on Port Security Resilience—An Empirical Study from Chinese Provinces

As the world transitions into the post-pandemic era, ports in various countries are experiencing increased activity, leading to significant challenges in ensuring traffic safety within port jurisdictions. It is essential to explore methods to improve port security resilience to maintain regular economic and trade exchanges. This article examines the influence of digital development on port security resilience. Firstly, the provincial digital development level score is objectively evaluated from the perspective of digital infrastructure, digital application, and digital industry development. Secondly, the port safety resilience score is assessed considering water traffic safety, rescue and recovery capabilities, and operational efficiency. Lastly, the focus is on 16 provinces in China’s coastal and Yangtze River Economic Belt, establishing provincial panel data from 2010 to 2019, and empirically analyzing the direct impact of digital development on the resilience of port security. The results indicate that digital development enhances the resilience of port security, with significant heterogeneity and long-term effects observed.

A solid-state lithium-ion battery with micron-sized silicon anode operating free from external pressure

Applying high stack pressure (often up to tens of megapascals) to solid-state Li-ion batteries is primarily done to address the issues of internal voids formation and subsequent Li-ion transport blockage within the solid electrode due to volume changes. Whereas, redundant pressurizing devices lower the energy density of batteries and raise the cost. Herein, a mechanical optimization strategy involving elastic electrolyte is proposed for SSBs operating without external pressurizing, but relying solely on the built-in pressure of cells. We combine soft-rigid dual monomer copolymer with deep eutectic mixture to design an elastic solid electrolyte, which exhibits not only high stretchability and deformation recovery capability but also high room-temperature Li-ion conductivity of 2×10−3 S cm−1 and nonflammability. The micron-sized Si anode without additional stack pressure, paired with the elastic electrolyte, exhibits exceptional stability for 300 cycles with 90.8% capacity retention. Furthermore, the solid Li/elastic electrolyte/LiFePO4 battery delivers 143.3 mAh g−1 after 400 cycles. Finally, the micron-sized Si/elastic electrolyte/LiFePO4 full cell operates stably for 100 cycles in the absence of any additional pressure, maintaining a capacity retention rate of 98.3%. This significantly advances the practical applications of solid-state batteries.

Microfluidic device featuring micro-constrained channels for multi-parametric assessment of cellular biomechanics and high-precision mechanical phenotyping of gastric cells

BackgroundCellular biomechanics plays a significant role in the regulation of cellular physiological and pathological processes. In recent years, multiple methods have been developed to evaluate cellular biomechanics, such as atomic force microscopy (AFM), micropipette aspiration, and magnetic tweezers. However, most of these methods only focus on a single parameter and cannot automate the process at a high-efficiency level. A novel microfluidic method is necessary to achieve the simultaneous multi-parametric measurement of cellular biomechanics and high-precision cellular mechanical phenotyping at high throughput. ResultsTo tackle the issue concerning the low-throughput and cellular single-parameter evaluation, we designed and fabricated a microfluidic chip featuring multiple micro-constrained channels structure, providing a simultaneous multi-parametric assessment of cellular biomechanics, including elastic modulus, recovery capability, and deformability. We compared the biomechanical properties of normal human gastric mucosal epithelial cells (GES-1) and human gastric cancer cells (AGS and MKN-45) by the chip. Results demonstrated that the elastic modulus of GES-1, AGS, and MKN-45 cells decreased sequentially, which was the opposite of their invasiveness and metastasis potential, suggesting the inverse correlation between cellular elastic modulus and malignancy. Meanwhile, the recovery capability and deformability of GES-1, AGS, and MKN-45 cells increased sequentially, demonstrating the positive correlation between cellular deformability and malignancy. Furthermore, multiple parameters were used to distinguish gastric cancer cells from normal gastric cells via machine learning. An accuracy of over 94.8% for identifying gastric cancer cells was achieved. SignificanceThis study provides a deep insight into the biophysical mechanism of gastric cancer metastasis at the single-cell level and possesses great potential to function as a valuable tool for single-cell analysis, thereby facilitating high-precision and high-throughput discrimination of cellular phenotypes that are not easily discernible through single-marker analysis.

Mechanical insights into jawbone characteristics under chronic kidney disease: A comprehensive nanoindentation approach

The mechanical properties of the jawbone play a critical role in determining the successful integration of dental prostheses. Chronic kidney disease (CKD) has been identified to abnormally accelerate bone turnover rates. However, the impact of CKD on the mechanical characteristics of the jawbone has not been extensively studied. This study sought to evaluate the time-dependent viscoelastic behaviors of rat jawbones, particularly in the scenarios both with and without CKD. We hypothesized that CKD might compromise the bone's innate toughening mechanisms, potentially owing to the time-dependent viscoelasticity of the bone matrix proteins. The maxillary and mandibular bones of Wistar rats were subjected to nanoindentation and Raman micro-spectroscopy. Load-hold-displacement curves from the cortical regions were obtained via nanoindentation and were mathematically characterized using a suitable viscoelastic constitutive model. Raman micro-spectroscopy was employed to identify nuanced vibrational changes in local molecular structures induced by CKD. The time course of indenter penetration onto cortical bones during the holding stage (creep behavior) can be mathematically represented by a series arrangement of the Kelvin–Voigt bodies. This configuration dictates the overall viscoelastic response observed during nanoindentation tests. The CKD model exhibited a reduced extent of viscoelastic contributions, especially during the initial ramp loading phase in both the maxillary and mandibular cortical bones. The generalized Kelvin–Voigt model comprises 2 K–Voigt elements that signify an immediate short retardation time (τ1) and a subsequent prolonged retardation time (τ2), respectively. Notably, the mandibular CKD model led to an increase in the delayed τ2 alongside an increase in non-enzymatic collagen cross-linking. These suggest that, over time, CKD diminishes the bone's capability for supplementary energy absorption and dimensional recovery, thus heightening their susceptibility to fractures.

Coordinated reactive power planning in an industrial park integrated energy system using support vector regression

In this study, we develop and present a comprehensive multi-objective optimization model for reactive power planning in industrial park integrated energy systems (IPIES), addressing the challenges posed by extensive inductive loads. Our model prioritizes enhancing system resilience through three key objectives: minimizing total costs, improving static voltage stability margins, and enhancing voltage recovery capabilities. We employ support vector regression (SVR) to estimate voltage recovery metrics effectively, using reactive power capacity as input. The optimization process leverages the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) for efficient solution finding. Validation on the IEEE-39 bus system demonstrates the model’s effectiveness, with SVR significantly reducing computational demands while maintaining satisfactory accuracy.

Reviewing the potential of anaerobic membrane bioreactors in wastewater treatment

Anaerobic membrane bioreactors (AnMBRs) represent an innovative approach to wastewater treatment, combining anaerobic digestion with membrane filtration to achieve efficient organic pollutant removal and resource recovery. This review critically examines the potential of AnMBRs in wastewater treatment, highlighting their principles, advantages, challenges, recent advancements, and future prospects. AnMBRs offer several advantages over traditional aerobic treatment methods, including higher organic loading rates, reduced energy requirements, and biogas production through methane generation. However, challenges such as membrane fouling, reactor complexity, and operational costs have limited their widespread adoption. Recent advancements in membrane materials, fouling mitigation strategies, and process optimization have improved AnMBR performance and feasibility. Novel membrane materials with enhanced fouling resistance and durability have been developed, while innovative cleaning techniques and operational protocols have been implemented to mitigate membrane fouling and prolong membrane lifespan. Process optimization strategies, including reactor design modifications and operational parameter adjustments, have enhanced treatment efficiency and reduced energy consumption in AnMBRs. Future research directions in AnMBR technology focus on optimizing reactor configurations, exploring novel membrane materials and fouling control strategies, and conducting comprehensive techno-economic assessments to evaluate the environmental and economic sustainability of AnMBRs. Integration of AnMBRs with emerging technologies such as membrane distillation, forward osmosis, and bioelectrochemical systems holds promise for further enhancing treatment performance and resource recovery capabilities. Additionally, addressing knowledge gaps in membrane fouling mechanisms, microbial community dynamics, and long-term system stability is crucial for advancing AnMBR technology and facilitating its widespread implementation in wastewater treatment. Overall, AnMBRs offer significant potential for sustainable wastewater treatment, providing opportunities for organic pollutant removal, energy recovery, and resource reuse. By addressing technical challenges, optimizing process parameters, and conducting interdisciplinary research, AnMBRs can contribute to the development of efficient, cost-effective, and environmentally friendly wastewater treatment solutions, ultimately supporting the goal of achieving cleaner water resources and a more sustainable future.

Seismic performance investigation on self-centering friction frames: Collapse capacity and post-earthquake recovery

Self-centering technology is a promising approach to enhance seismic resilience of frame structures. Despite extensive experimental and theoretical research on various self-centering components, there has been relatively limited quantitative study on the collapse and post-earthquake recovery capabilities of self-centering frame structures. Therefore, this paper introduces a self-centering friction beam-column joint (SCFJ) and develops a simplified analytical model for the joint. Then a series of RC frames with SCFJ are designed, and their seismic resilience and post-earthquake recovery performance are conducted. Finally, this study quantitatively investigates the contribution of SCFJ to the seismic safety and post-earthquake recovery capabilities of RC frames with varying stories. The results indicate that under maximum considered earthquake, the peak floor accelerations and inter-story drift ratio of self-centering friction frames (SCFF) are comparable to those of ordinary RC frames (ORCF). However, the overall residual deformation of the SCFFs can be reduced by 85%–94%. Furthermore, their seismic collapse resistance is improved by 8%–23%. Immediate occupancy and reparability of SCFFs are enhanced by 41%–72% and 29%–35%, respectively. Notably, the enhancement in collapse capacity and post-earthquake recovery performance of SCFFs becomes more pronounced as the number of stories increases.

Preparation and Properties of Soft-/Hard-Switchable Transparent Wood with 0 °C as a Boundary

Transparent wood has excellent optical and thermal properties and has great potential utilization value in energy-saving building materials, optoelectronic devices, and decorative materials. In this work, transparent wood with soft-/hard-switchable and shape recovery capabilities was prepared by introducing an epoxy-based polymer with a glass transition temperature of about 0 °C into the delignified wood template. The epoxy resin was well filled in the pore structure of the delignified wood, and the as-prepared wood exhibited excellent transparency; the optical transmittance and haze of the transparent wood with a thickness of 2.0 mm were approximately 70% and 95%, respectively. Because the glass transition temperature of the epoxy-based polymer was about 0 °C, the prepared transparent wood was rigid below 0 °C and flexible above °C; meanwhile, the transparent wood exhibited shape change and shape recovery properties. Incorporating optical transparency and soft-/hard-switchable ability into the transparent wood opens a new avenue for developing advanced functional wood-based materials.

Multifunctional fire-resistant and flame-triggered shape memory epoxy nanocomposites containing carbon dots

Carbon quantum dots (CDs) are widely used as semiconductor systems, due to their facile synthesis and optical characteristics. CDs have been employed to enhance the light emission, UV resistance, and anticorrosive performances of epoxy nanocomposites (ENCs). Herein, we investigated the use of CDs to prepare multifunctional cycloaliphatic ENCs showing shape recovery capability. Following a waste-to-wealth approach, CDs were obtained from humic acid by a hydrothermal route. ENCs containing CDs exhibited photoluminescence, while the simultaneous addition of CDs and hexadecyltrimethoxysilane accounted for heat/flame-triggered shape recovery capability and hydrophobicity (contact angles as high as 137°). The polar character of silane-functionalized CDs allowed for their segregation at the surface of ENCs, making them very fire resistant. In particular, the CDs exerted an outstanding thermal shielding effect on the surface of ENCs, lowering the heat transfer at the boundary layer and increasing the time to flaming combustion up to ∼ 76 %. Besides, the graphitic nature of CDs and their charring behavior led to a huge increase in the back temperature at the ignition point (up to ∼ 30 %) during burn-through tests. Notwithstanding the low loadings (not exceeding 0.3 wt%) of CDs, ENCs lost their structural integrity only after almost 1 min of blowpipe flame application to their surface, whereas the resin counterpart degraded in less than 20 s. Besides, cone calorimetry tests carried out on ENCs highlighted a significant reduction of total smoke release (up to ∼ 40 %) compared to unfilled epoxy. Finally, we demonstrated the possibility of using multifunctional ENCs containing CDs as unique identification technology for polypropylene packaging, opening new perspectives on the effective protection of genuine products from counterfeiting.

An integrated group decision-making framework for evaluating the urban fire emergency management capability based on PDHLWPHM and PDHLWPGHM operator

Urban fire accident is a common dangerous accident in urban sudden accidents, which threatens the safety of people’s lives and property. For this reason, in recent years, all cities have incorporated the prevention and emergency management of urban fire accidents into their urban development planning, and actively improved their fire accident emergency management capabilities. However, how to evaluate the urban fire accident emergency management capacity of each city to ensure that people’s lives and property are protected to the greatest extent is an urgent problem to be considered and solved. Therefore, this paper defines a class of probabilistic double hierarchy linguistic Heronian mean (PDHLHM) operator, probabilistic double hierarchy linguistic Power Heronian mean (PDHLPHM) operators, and their dual operators that can reflect the relationship between two attributes during aggregation. Taking urban fire accident risk monitoring and early warning capability, fire infrastructure and communication system, fire-fighting and rescue capability, recovery and reconstruction capability as evaluation attributes, the probabilistic double hierarchy linguistic weight Power Heronian mean (PDHLWPHM) operator model and the probabilistic double hierarchy linguistic weight Power geometric Heronian mean (PDHLWPGHM) operator model are constructed for group decision-making. In addition, the idempotence, boundedness and monotonicity of these operators are studied, and the sensitivity of the parameters involved in the operator model is analyzed. Finally, the new model proposed in this paper is compared with the existing model to verify its scientificity.

Real-Time Tracking of Carbon Dioxide Concentration Using an Optical Microsphere Resonator Sensor.

Whispering gallery mode resonator sensors are nondisruptive optical sensors that can detect and monitor perturbations in a gaseous environment. Through its resonant properties of peak wavelength, amplitude, and quality factor (Q factor), changes in concentration can be quantified within seconds and monitored over days with great stability. In addition, the small footprint, low cost, and high sensitivity are ideal properties for a disposable sensor that can be utilized in extreme environments. The large Q factor of the resonant cavity enables long interaction lengths and amplifies the effect of small changes in the background refractive index, which is detectable in picometer shifts of the resonance wavelength. However, this measurement is susceptible to changes in other environmental factors such as temperature, pressure, and humidity, which manifest on the picometer wavelength scale, reinforcing the need to decouple the variables. In this work, we compare the spectral response of different diameter resonators to carbon dioxide, nitrogen, and its mixtures, observing the spectral shifting and broadening of the cavity resonance near 1550 nm. In addition, the effect of environmental temperature on spectral shifting due to the thermo-optic effect is characterized and quantified. Lastly, the gas concentrations are changed in real time to showcase the tracking and recovery capabilities of the resonator sensor.

Synthesis of magnetic bifunctional monomer molecularly imprinted polymers for highly selective separation of paclitaxel from Taxus cuspidata

Paclitaxel (PTX), an active anticancer compound derived from Taxus cuspidata, possesses considerable economic value. Given the abundance of structural analogs, the selective separation of PTX from T. cuspidata presents a formidable challenge. In this study, the bifunctional monomers magnetic molecular imprinted polymers (MMIPs) with multiple active sites were synthesized using Fe3O4 as the magnetic carrier, PTX as the template, 4-vinylpyridine (4-VP) and methacrylic acid (MAA) as the first-stage and the second-stage pre-assembly functional monomer, respectively. The results indicated that MMIPs exhibited excellent magnetic recovery capability and high adsorption capacity for PTX. Furthermore, the adsorption behaviors were more consistent with Langmuir isotherm model and pseudo-second-order kinetic model. The MMIPs possessed significantly higher selectivity for PTX than five structural analogs (Docetaxel, Baccatin III, 10-Deacetylbaccatin III, and Glucose) and recyclability for up to six cycles. Additionally, the adsorption mechanism analysis indicated that the excellent performance of MMIPs primarily arises from the multiple active binding sites involving hydrogen bonding and π-π stacking. Finally, MMIPs were used for PTX recognition and separation in T. cuspidata extracts. This study provides an efficient method and valuable theoretical basis for the highly selective separation of PTX from T. cuspidata.

Efficient and selective gold recovery using amine-laden polymeric fibers synthesized by a steric hindrance strategy

Various alkylamines are commonly used for efficient Au recovery; however, their high hydrophilicity can result in dissolution in water, hindering effective Au recovery and potentially causing environmental contamination. Currently, the forms in which alkylamines are immobilized on supports provide unsatisfactory Au recovery capabilities and exhibit low structural stability. This study proposes a pragmatic approach for synthesizing amine-laden polymeric fiber (ALPF) adsorbents with efficient Au recovery capabilities and superior structural stability. Polyacrylonitrile fibers (PANF) were employed as a supportive matrix to immobilize the alkylamine molecules chemically. The densely grafted amine groups on the ALPF adsorbed significant amounts of Au ions and reduced them to Au(0) crystals. This chelation–precipitation hybrid method achieved a Au recovery efficiency of nearly 100 % over a wide pH range of 1–4. In addition, it demonstrated an exceptional Au adsorption capacity of 1463 mg/g, surpassing the values reported for other adsorbents categorized by size and shape. Even in the presence of 14 different coexisting metal ions, the ALPF showed a Au recovery efficiency above 99.9 %. It also exhibited excellent reusability, maintaining a Au recovery rate of ∼91 % after 10 cycles. Furthermore, fibrous adsorbents alleviated the pressure drop in columns filled with adsorbents, thereby enabling energy-efficient and environment-friendly processes.

Maximizing wind farm power output with the helix approach: Experimental validation and wake analysis using tomographic particle image velocimetry

AbstractWind farm control can play a key role in reducing the negative impact of wakes on wind turbine power production. The helix approach is a recent innovation in the field of wind farm control, which employs individual blade pitch control to induce a helical velocity profile in a wind turbine wake. This forced meandering of the wake has turned out to be very effective for the recovery of the wake, increasing the power output of downstream turbines by a significant amount. This paper presents a wind tunnel study with two scaled wind turbine models of which the upstream turbine is operated with the helix approach. We used tomographic particle image velocimetry to study the dynamic behavior of the wake under the influence of the helix excitation. The measured flow fields confirm the wake recovery capabilities of the helix approach compared with normal operation. Additional emphasis is put on the effect of the helix approach on the breakdown of blade tip vortices, a process that plays an important role in re‐energizing the wake. Measurements indicate that the breakdown of tip vortices and the resulting destabilization of the wake are enhanced significantly with the helix approach. Finally, turbine measurements show that the helix approach was able to increase the combined power for this particular two‐turbine setup by as much as 15%.

Brain-derived neurotrophic factor and stroke: perspectives on exercise as a health care strategy

PurposeStroke is the second most common cause of mortality worldwide and the third most common cause of motor disability. From another perspective, brain-derived neurotrophic factor (BDNF) is a metabolite that plays several neuroprotective roles. While cardiometabolic diseases are the leading cause of stroke, BDNF represents a target factor in the prevention and/or recovery from stroke. Aim: In this narrative review, I have summarised the clinical evidence of BDNF participation in the recovery from a stroke and discuss the potential use of exercise as a rehabilitation tool.MethodsMultiple combinations of the terms ‘brain infarction’, ‘cerebral infarction’, ‘hemorrhagic stroke’, ‘ischemic stroke’, ‘embolic stroke’ or ‘thrombotic stroke’ AND ‘BDNF’ or ‘pro-BDNF’ were used in PubMed databases. Studies not available in the English language or addressing animal experiments were excluded.Results and prospectsSeventeen clinical studies published up to June 30th of 2023 were included in this review. Changes in the patients circulating BDNF levels represent their capability of recovery from the stroke outcomes. A subtle, but consistent, negative influence of the presence of the 66Met-allele in BDNF on motor and cognitive competencies is seen in patients recovering from a stroke throughout the studies – an effect that is not reportedly detectable in other neuropathological conditions. Exercise exerts a positive modulation on BDNF levels that accompanies improvements in stroke recovery and might exert a preventive role against the severity of stroke outcomes.

Experimental Study on Dynamic Modulus of High Content Rubber Asphalt Mixture

Currently, the research on the mechanical properties of rubber-modified asphalt mixtures primarily focuses on small-scale investigations, with insufficient exploration into the performance of rubber particles and their relationship with the mechanism and properties of modified asphalt mixtures. Limited studies have been conducted on large-scale rubber modification in asphalt mixtures. Due to frequent use and subsequent high damage to existing asphalt pavements, incorporating rubber-modified asphalt mixtures can partially alleviate premature deterioration. Dynamic modulus tests were conducted using MTS equipment under unconfined conditions to investigate the viscoelastic behavior of rubber-modified asphalt mixtures with high rubber content and elucidate the influence of rubber particle content on the elastic deformation and recovery capability. The dynamic mechanical properties of the mixtures were determined at different loading rates, temperatures, and types of rubber-modified asphalt mixtures. Based on the test data, variations in the dynamic modulus, phase angle, storage modulus, loss modulus, loss factor, and rut factor of the rubber-modified asphalt mixtures under different loading frequencies, temperatures, and types were analyzed. The results demonstrate the pronounced viscoelastic behavior of rubber-modified asphalt mixtures. The mixtures exhibit enhanced elasticity at low temperatures and high frequencies, while their viscosity becomes more prominent at high temperatures and low frequencies. Under constant test temperatures, an increase in load loading frequency leads to a higher dynamic modulus; conversely, a decrease in dynamic modulus is observed with increasing test temperatures. The dynamic modulus of ARHM-25 at a frequency of 10 Hz is found to be 12.99 times higher at 15 °C compared to that at 60 °C, while at 30 °C, the dynamic modulus at 25 Hz is observed to be 2.72 times greater than that at 0.1 Hz. Furthermore, the rutting resistance factors of the asphalt mixtures increase with loading frequency but decrease with temperature. The rutting factor for ARHM-13 at a frequency of 10 Hz is found to be 22.98 times higher at 15 °C compared to that at 60 °C, while at a temperature of 30 °C, the rutting factor for this material is observed to be 3.09 times greater at a frequency of 25 Hz than at 0.1 Hz. These findings suggest that rutting is most likely when vehicles drive at low speeds in hot weather conditions.