Combination Of Strength Research Articles

Blockchain Solutions for Secure Healthcare Data Management: A Comprehensive Survey

The paper introduces an innovative approach to healthcare data security, addressing the critical concerns surrounding privacy and data integrity in the modern healthcare landscape. By amalgamating blockchain technology, AWS S3 services, and attribute-based access control (ABAC), the proposed solution offers a robust framework for safeguarding sensitive medical information. Through the implementation of ABAC, the solution enables dynamic and precise access control, ensuring that only authorized entities can access and manipulate healthcare data. Additionally, the utilization of a blockchain-based XML ledger on AWS S3 services enhances data security by providing an immutable and tamper-proof storage mechanism. This comprehensive solution not only addresses the privacy challenges inherent in the digitization of healthcare but also facilitates secure data sharing among authorized parties. By leveraging the combined strengths of ABAC, blockchain technology, and AWS S3 services, the proposed framework delivers a scalable and efficient infrastructure for managing healthcare data securely. It represents a significant advancement in healthcare information security, promising to safeguard patient privacy and maintain the accuracy and reliability of medical data in an increasingly interconnected digital ecosystem. Key Words: AWS S3 Service, Blockchain technology, medical information, XML ledger, Attribute-based access control (ABAC), Tamper-proof

A novel Bagged-CNN architecture for short-term wind power forecasting

ABSTRACT Wind power forecasting plays a pivotal role in ensuring the dependable integration of wind energy into power grids. This research introduces a novel Bagged-CNN architecture tailored for short-term wind power forecasting. This architecture harnesses the combined strengths of the Bagging ensemble technique and Convolutional Neural Networks (CNN) to enhance prediction accuracy and robustness. Our approach demonstrates superior forecasting capabilities by exploiting the spatial and temporal features captured by CNNs. To validate our proposed architecture, we have conducted a comprehensive evaluation across three distinct wind farms, each characterized by unique geographical and climatic conditions. We systematically compared the performance of our Bagged-CNN model against several standalone machine-learning algorithms commonly employed in wind power forecasting. The hyperparameters of our Bagged-CNN model are meticulously optimized using the GRID search algorithm, which systematically explores a predefined parameter space. Notably, our predictions shed light on the substantial impact of training data period length on wind power prediction accuracy. Our research underscores the potential of coupling Bagging and CNN techniques for short-term wind power forecasting. The Bagged-CNN architecture, as proposed, serves as a robust framework for capturing intricate spatial and temporal patterns in wind power data, thereby facilitating more precise and dependable predictions.

Face bonding strength of cross laminated northern hardwoods and softwoods lumber

Producing cross-laminated timber (CLT) has opened a new market for the lumber industry in North America, while few hardwood species have been studied in the U.S. for CLT production. Combining hardwood species in mixed hardwood CLT or in hybrid CLT can be a solution to boost the market of the undervalued hardwoods. However, the knowledge gap on bonding hardwoods needs to be filled to provide evidence of feasibility. This study focused on the face bonding properties of the cross laminations made of seven hardwood species and two softwood species from the Great Lakes region using two commercial structural adhesives, the phenol resorcinol adhesive (the Resorcinol) and the melamine urea formaldehyde adhesive (the Melamine). A total of 45 combinations of the selected species were studied for the bonding strength (shear under compression) and the percentage of wood failure. For single species samples, the bond strength was positively related to the specific gravity of wood and the bond strength of hardwoods was 33% and 82% stronger than that of softwoods bonded with the Resorcinol and the Melamine respectively. The mixed hardwoods showed higher bonding strength (the Melamine: 5.45 MPa, the Resorcinol: 5.28 MPa) than mixed softwoods (the Melamine: 2.8 MPa and the Resorcinol: 2.7 MPa). Among the Resorcinol bonded mixed combinations, 54% had a percentage of wood failure less than 80%, while the Melamine bonded had only 4 out of 22 which had a percentage of wood failure less than 80%. The overall bonding strength of the hybrid combinations was 5% weaker than that of the mixed hardwoods. All hybrid combinations bonded with the Melamine met the 80% wood failure criterium, but some bonded with the Resorcinol had a percentage of wood failure less than 80%. Anatomical features, especially pore distribution, played a key role in the bonding performance. However, the Melamine adhesive consistently achieved over 80% wood failure across all pore distribution types.

Physical Activity Training Methods to Improve the Physical Condition of Volleyball Players: A Systematic Review

Study purpose. The study was aimed to identify exercise techniques used to improve the physical condition of volleyball players through literature studies. Materials and methods. A systematic review of these previous studies was conducted. We studied articles published between 2014 and 2023 that explained how to prepare volleyball players to have better physical condition. Scopus, Web of Science, Google Scholar, and PubMed were used for the electronic search. We collected all the articles that discussed how to improve physical performance through exercise. Results. To improve the physical condition of volleyball players, 50 publications used exercise techniques, which were categorized based on the physical condition that was evaluated and repaired. The following techniques are some of the ones that can be used: Neuromuscular, unilateral and bilateral, ballistic, plyometric exercises, combined weight and plyometric, mixed training with optimal load, COD & plyometric complex, strength, combined strength, eccentric trainings, repetitive sprint, resistant/non-resistant sprint, resistance training, exercises with elastic band, core training, combined core training; small-sided games training, aerobic interval training, blood flow restriction, intermittent training, and anaerobic speed endurance. Conclusions. Following a thorough analysis, a number of training regimens were found to be effective in enhancing volleyball players’ physical attributes, including muscular strength, aerobic and anaerobic endurance, speed and acceleration, explosive power, flexibility, agility, and balance.

Tough Hydrogels with Different Toughening Mechanisms and Applications.

Load-bearing biological tissues, such as cartilage and muscles, exhibit several crucial properties, including high elasticity, strength, and recoverability. These characteristics enable these tissues to endure significant mechanical stresses and swiftly recover after deformation, contributing to their exceptional durability and functionality. In contrast, while hydrogels are highly biocompatible and hold promise as synthetic biomaterials, their inherent network structure often limits their ability to simultaneously possess a diverse range of superior mechanical properties. As a result, the applications of hydrogels are significantly constrained. This article delves into the design mechanisms and mechanical properties of various tough hydrogels and investigates their applications in tissue engineering, flexible electronics, and other fields. The objective is to provide insights into the fabrication and application of hydrogels with combined high strength, stretchability, toughness, and fast recovery as well as their future development directions and challenges.

Association between urinary glyphosate levels and hand grip strength in a representative sample of US adults: NHANES 2013-2014.

Glyphosate, a widely utilized herbicide globally, has been linked to various health issues, including cancer, birth abnormalities, and reproductive issues. Additionally, there is growing experimental support indicating potential harm to skeletal muscles. Despite this, the impact of glyphosate on human muscle health remains unclear. We examined information gathered from the 2013-2014 National Health and Nutrition Examination Survey (NHANES), which included 1466 adults aged 18 or older. Our primary aim was to investigate the relationship between glyphosate exposure and hand grip strength, as well as its influence on lean muscle mass. Our investigation uncovered a detrimental correlation between glyphosate exposure and all measures of grip strength, except for the second test of the first hand. Specifically, we observed a statistically significant adverse association between glyphosate exposure and combined grip strength, which is calculated as the sum of the highest readings from both hands (ß coefficient of -2.000, S.E. = 0.891, p = 0.040). We did not observe a significant correlation between glyphosate levels, lean muscle mass, and the likelihood of reaching maximum grip strength meeting sarcopenia criteria. Additionally, we observed an interaction between age and glyphosate, as well as between body mass index (BMI) and glyphosate, concerning the association with combined grip strength. In this comprehensive analysis of NHANES data, our study reveals a potential association between glyphosate exposure and hand grip strength in the adult population. Our findings suggest the need for deeper exploration into the health effects of glyphosate exposure and its impact on muscle strength, shedding light on possible public health concerns.

Interlaminar Adhesion Study of Fused Filament Fabrication (FFF)-Printed Soft and Rigid Bilayer Structure with Composites

Multi-material Additive manufacturing (AM) has opened new opportunities for the creation of multifunctional structures that enables value-added structural product designs. Among the multi-material AM techniques, multi-nozzle fused filament fabrication which is a type of material extrusion technique is found to be the more popular choice for multi-material polymer fabrication. One major challenge of multi-material additive manufacturing of polymers is the poor mechanical strength at the interface of the dissimilar materials such as polylactic acid (PLA) and thermoplastic polyurethane (TPU) due to the lack of chemical affinity. Therefore, understanding the mechanical strength at the interface of these dissimilar materials becomes an important topic as it allows product designers to do necessary tweak to the design to compensate for the weaker link in the structural design. In this work, we investigated the tensile strength and the shear strength of different combinations of PLA and TPU and their respective nanocomposites, as well as the fatigue analysis of the bi-layer structures made of these dissimilar materials in a 3-point bending test configuration. Generally, when functional fillers or particles are added to the polymer in composites, they tend to adversely affect the interlaminar adhesion property and fatigue life of the soft-rigid bilayer structure. It was found, that the interlaminar tensile strength and the interlaminar shear strength can reduce as high as 44% and 78%, respectively, compared to the baseline samples with no fillers.

A STUDY OF COST VARIATION ANALYSIS OF ORAL HYPOGLYCEMIC DRUGS AVAILABLE IN INDIAN PHARMACEUTICAL MARKET

Objectives: A large number of oral hypoglycemic drugs as single or fixed dose combinations are available for the treatment of diabetes mellitus which has a wide range of price variation and becomes a constraint in the treatment for both physician and patient. However, very few studies have been done to reveal such price variations. The objective of this study was to find out the cost variation among the different brands of various classes of oral hypoglycemic drugs in similar strength and dosage forms of single therapy and fixed-dose combinations. Methods: Cost of a particular drug being manufactured by different companies in the same strength, number, and dosage form was compared from the Current Index of Medical Specialties (CIMS) (January 2022–April 2022) and Indian Drug review 2022. The difference in the maximum and minimum price of the same drug manufactured by different pharmaceutical companies and the percentage variation in price was calculated. Results: Among single drug therapy, Glimepiride (1 mg) shows a maximum percentage variation in price of 3450%. Among Sulfonylureas-glimepiride (1 mg) shows a maximum price variation of 3450%, in Biguanides–metformin (500 mg), in Thiazolidinediones – Pioglitazone (15 mg) shows a maximum price variation of 900%, and 300%, respectively, and among the glucosidase inhibitors, Voglibose (0.3 mg) shows maximum price variation of 571.2%. Among combination formulation, glimepiride (1 mg) + metformin SR (500 mg) shows a maximum percentage of price variation of 262.1%. Conclusion: It is observed from our results that there is a wide variation in prices of drugs manufactured by different pharmaceutical companies. Hence, it is very necessary for regulatory authorities to regulate the wide variation in drug prices to maximize the benefits of the treatment. It is recommended that the appraisal and management of marketing drugs should be well-regulated.

A hybrid deep learning technique for spoofing website URL detection in real-time applications

Website Uniform Resource Locator (URL) spoofing remains one of the ways of perpetrating phishing attacks in the twenty-first century. Hackers continue to employ URL spoofing to deceive naïve and unsuspecting consumers into releasing important personal details in malicious websites. Blacklists and rule-based filters that were once effective at reducing the risks and sophistication of phishing are no longer effective as there are over 1.5 million new phishing websites created monthly. Therefore, research aimed at unveiling new techniques for detecting phishing websites has sparked a lot of interest in both academics and business with machine and deep learning techniques being at the forefront. Among the deep learning techniques that have been employed, Convolutional Neural Network (CNN) remains one of the most widely used with high performance in feature learning. However, CNN has a problem of memorizing contextual relationships in URL text, which makes it challenging to efficiently detect sophisticated malicious URLs in real-time applications. On the contrary, Long Short-Term Memory (LSTM) deep learning model has been successfully employed in complex real-time problems because of its ability to store inputs for a long period of time. This study experiments with the use of hybrid CNN and LSTM deep learning models for spoofing website URL detection in order to exploit the combined strengths of the two approaches for a more sophisticated spoofing URL detection. Two publicly available datasets (UCL spoofing Website and PhishTank Datasets) were used to evaluate the performance of the proposed hybrid model against other models in the literature. The hybrid CNN-LSTM model achieved accuracies of 98.9% and 96.8%, respectively, when evaluated using the UCL and PhishTank datasets. On the other hand, the standalone CNN and LSTM achieved accuracies of 90.4% and 94.6% on the UCL dataset, while their accuracies on the PhishTank dataset were 89.3% and 92.6%, respectively. The results show that the hybrid CNN-LSTM algorithm largely outperformed the standalone CNN and LSTM models, which demonstrates a much better performance. Therefore, the hybrid deep learning technique is recommended for detecting spoofing website URL thereby reducing losses attributed to such attacks.

Exploring the interplay of LSPR and CT: Hierarchical shell thickness optimization for advanced SERS sensing using AgNW@ZIF-8 Core@Shell substrates

Synergistic surface-enhanced Raman spectroscopy (SERS) substrates, leveraging the combined strengths of electromagnetic enhancement (EM) and chemical enhancement (CM), have been extensively explored in the literature. In this study, we introduce a distinctive approach to fabricating core@shell structures, specifically employing silver nanowire @ zeolite imidazole framework-8 (AgNW@ZIF-8) as synergistic SERS substrates. Notably, these substrates offer meticulous control over shell thickness through a straightforward post-synthesis procedure. Utilizing Ag nanowires as the plasmonic core, selected for their broader localized surface plasmon resonance (LSPR) absorption range compared to nanoparticles, we encapsulate them within ZIF-8, a metal-organic framework (MOF) recognized for its proficient charge transfer (CT) properties. Our investigation encompasses the SERS performance across various Raman-active molecules, considering their diverse sizes and distinct frontier molecular orbitals (FMO) energy levels. Additionally, we systematically explore the influence of alterations in shell thickness on SERS outcomes and scrutinize the impact of probe orientation. This comprehensive study not only advances the understanding of synergistic effects intrinsic to MOFs-metal SERS substrates but also provides valuable insights for the rational design of highly sensitive substrates tailored for practical applications.

Impact on weight loss and body composition of a food education intervention associated with Liraglutide treatment to address obesity

Introduction: clinical practice guidelines recommend considering pharmacological treatment of obesity only as a complement to lifestyle modification. Drugs alone are usually ineffective in the long term after discontinuation, so pharmacological weight loss strategies should always be accompanied by lifestyle modifications. Objective: to analyze the changes in weight, body mass index and body composition by means of electrical bioimpedance after a 32-week treatment with liraglutide in patients with obesity, associated or not with a food education program. Materials and methods: the study involved 68 patients who were randomly divided into 2 groups. One group received treatment with liraglutide 3.0 mg/day along with individual dietary education, and the other group was treated with liraglutide 3.0 mg/day and standard medical follow-up for 32 weeks. The data collected were weight (kg), height (m) (Seca® brand), body mass index (kg/m2) and body composition using multifrequency bioimpedance (SECA 112® brand). The variables were analyzed at the beginning and at the end of the treatment. Results: after 32 weeks of treatment, both study groups lost weight significantly. The group treated with liraglutide and individual dietary education had a reduction of 8.77 kg (9.08 %) (p < 0.001) and the group treated with liraglutide without education had a reduction of 3.55 kg (3.45 %) (p < 0.001). The BMI of the participants treated with liraglutide and education decreased by -4,04 kg/m2 (10.35 %) (p < 0.001) and in the group without education it decreased by -3.22 kg/m2 (8.30 %) (p = 0.003). In the educated group, fat mass decreased by -7.65 kg (15.89 %) (p < 0.001), although skeletal muscle mass also decreased by -1.62 kg (6.8 %) (p < 0.001). In those treated with liraglutide without education, a reduction in fat mass and skeletal muscle mass was also observed - fat mass by -4.72 kg (9.43 %) (p < 0.001) and skeletal muscle mass by -0.17 kg (0.70 %) (p < 0.001). Differences were also observed between groups, observing a greater reduction in weight, BMI, fat mass and skeletal muscle mass in the group with liraglutide and education compared to the group without education, although these differences were not statistically significant. Conclusions: dietary education associated with liraglutide treatment may contribute to increasing weight and fat mass losses. However, it was also associated with an unwanted loss of skeletal muscle mass, probably related to the greater intensity of weight loss, which will have to be reversed in future therapeutic approaches. Habit modification through multidisciplinary treatment, including nutritional education, combined strength and resistance exercise, and cognitive-behavioral therapy, could be an effective way to treat obesity and maintain weight, body composition, and adherence to a lifestyle.

Effects of in-process surface finishing on part strength in polymer material extrusion additive manufacturing

Material extrusion additive manufacturing suffers from limitations in surface finish, dimensional accuracy, and part strength. Hybrid manufacturing, which in this context integrates material extrusion with in-process surface finishing, offers a potential solution to address these issues. This study presents two critical aspects of a polymer-based hybrid manufacturing process. First, it quantifies the impact of the interfacial temperature drop during the finishing cycle on part strength. Secondly, it investigates the influence of surface finishing on part strength, considering two finishing methods: machining and a combination of machining and chemical polishing. The results reveal that temperature plays a major role in influencing the part strength and must be regulated to preserve interfacial bonding. An interfacial temperature drop beyond the material’s glass transition temperature can lead to a 50% reduction in part strength. However, slowing down the printing speed at the interface could induce localized heating, partially offsetting this loss. Furthermore, in-process surface finishing can mitigate potential sites for crack initiation, thereby increasing part strength. The results indicate that the machining-only scenario increases the part strength by 70.6% compared to the as-printed condition, while the combined machining and chemical polishing further increase part strength by 163.3%. This research underscores the multifaceted benefits of surface finishing in a polymer hybrid manufacturing setting while highlighting the potential challenge of temperature management.

Enhancing Fake Image Detection: A Novel Two-Step Approach Combining GANs and CNNs

The proliferation of fake images in today's digital landscape poses a significant threat to various domains, including media integrity, social media, and online security. Recognizing the urgent need to distinguish real images from their deceptive counterparts, this paper underscores the importance of developing a robust detection system. While substantial efforts have been made in the realms of computer vision and deep learning, the advent of Generative Adversarial Networks (GANs) has added a new layer of complexity to this challenge. In response to these evolving threats, we present a novel two-step methodology for detecting fake images, with a specific focus on those generated by GANs. Our approach harnesses the combined strengths of GANs and traditional Convolutional Neural Networks (CNNs), offering a comprehensive solution that significantly enhances accuracy in identifying both fake images and machine-generated fake images. The results of our experiments demonstrate the efficacy of our methodology. Using CNNs alone, we achieved a training accuracy of 87%. However, when employing the collaborative power of GANs and CNNs, our model exhibited a remarkable accuracy rate of 94.4%. This substantial improvement underscores the superiority of the GANs+CNN approach, suggesting its potential as a groundbreaking solution in the realm of fake image detection. This research opens up new horizons in fields such as media forensics, social media monitoring, and online security, where the ability to discern genuine content from manipulated or synthetic media is of paramount importance. The promising outcomes of this study not only provide an immediate and effective solution but also pave the way for further exploration and innovation in this critical area of digital security.

Flow-electricity coupling fields enhance microfluidic platforms for efficient exosome isolation.

Recently, exosomes have emerged as important biomarkers for cancer diagnosis, playing a significant role in disease diagnosis. Consequently, efficient isolation of exosomes from complex body fluids is now a critical focus in clinical research. We have designed and fabricated an exosome separation chip, leveraging the synergies of flow and electric fields through 3D printing technology. This approach harnesses the combined strengths of both fields, substantially enhancing separation efficiency and purity. This also effectively reduced the voltage required to form an electric field (from 120 V down to 10 V), minimizing the risk of Joule heating, thereby preserving the structural integrity and biological activity of the exosomes. Compared with the standard exosome separation method of ultracentrifugation (UC), our chip offers numerous benefits: it is cost-effective (under 50 RMB), boasts a high recovery rate (64.8%) and high purity (almost 100%), achieves remarkable separation efficiency (within 30 minutes), and is straightforward to operate. Moreover, since an unmarked separation method is used, the separated exosomes can be directly used for downstream detection and analysis, which has certain practicality for future clinical research and application.

Effectiveness of Task-Specific Training combined with Strength Training on Upper Limb Recovery, Activities and Participation after Stroke: A Systematic Literature Review

Strength training in stroke focuses more on improving the impairment of muscle weakness after stroke. Task specific training along with strength training may improve upper limb impairment, functional outcome and participation after stroke. A systematic review was conducted to analyse the available evidence on task specific training combined with strength training on upper limb performance post stroke. Databases like The Cochrane Central Register of Trials (CENTRAL), PubMed, PEDro, Clinical Trial Registry of India and OTseeker were searched in order to find the required studies. Stroke, task-specific training, functional strength training, task-oriented strength training, task-specific strength training, upper limb performance, activities, and participation were the key search terms. Studies published in English language up to October 2023 were taken into consideration. For the purpose of the review, studies that examined the efficacy of combined strength training and task specific training on upper limb recovery, activity and participation post stroke were taken into account. The studies of other combinations with task specific training were excluded. Outcome measures measuring upper limb motor recovery, functional performance, activities and participation post stroke were considered in the review. Five studies were selected for the current systematic review out of the 384 studies screened. Task specific training combined with strength training functional strength training were reviewed in the selected studies. The review conclude that a combined therapeutic strategy using task specific training and strength training addressing improvement of upper limb recovery can be more effective in comparison to the standard therapy.

Kenya’s Peace Diplomacy in Eastern Africa: Regional Hegemon?

Kenya’s Peace Diplomacy in Eastern Africa: Regional Hegemon?

Dynamic behaviors and bolt-strengthening effect of sand-powder 3D printing rock analog under static and dynamic coupled loading

In deep mining, surrounding rock mass are subjected to high in-situ stress and dynamic loading, which leads to the difficulties in maintaining the roadway stability. Therefore, it is important to investigate the mechanical characteristics of rock bolts and their ability to enhance stability when exposed to static and dynamic coupled loading (SDCL). 3D printing technology can effectively address the challenges of preparing weak rock specimens and overcoming high variability. Consequently, the Split Hopkinson pressure bar (SHPB) is used to conduct SDCL testing on 3D printing specimens with varying bolted lengths. The similarity in mechanical performance between sand-powder 3D printed specimens and natural coal specimens has been validated. The rock dynamic characteristics with different bolted lengths under SDCL of specimens were explored. The macroscopic fragmentation and microscopic electron microscope scanning were used to reveal the dynamic failure characteristics of specimens. The study shows that static, dynamic and combined strength are positively correlated with bolted length. The dynamic strength is negatively correlated with the axial stress, and the combined strength initially increases and then subsequently decreases as the axial stress increases. The dynamic strength and the combined strength are positively correlated with the impact pressure. Efficient prevention of specimen fracture was achieved by increasing the length of the bolted connection. It can be found that at the meso-scale, when the specimen is only under the static loads, the cross-section particles are fractured along particle bonding, and under the SDCL, there are fractured along particle bonding and fractured through particle. The conclusions obtained can offer a foundation for conducting dynamic rock mechanics experiments using sand-powder 3D printed specimens and for controlling the surrounding rock in dynamic pressure roadways.

Illuminating Oxygen Reduction Reaction Kinetics in High Temperature Polymer Electrolyte Membrane Fuel Cells Using EIS

Owing to their notable power efficiency and zero greenhouse emissions, High Temperature Polymer Electrolyte Membrane Fuel Cells (HTPEMFCs) hold immense promise as a prospective candidate for generating clean energy. However, their commercialization is still impeded by the cathodic Oxygen Reduction Reaction (ORR) kinetics, which after almost half a century not only remain elusive, but constitute the most energy-intensive process, requiring large amounts of the expensive Pt catalyst to mitigate.In this work we provide solid experimental evidence, that the simple three elementary step Dissociative Adsorption Pathway (DAP) with two intermediate species (Oad and OHad), can accurately capture both the steady state (IV) and the Electrochemical Impedance Spectra (EIS) as well.Detailed EIS and IV experimental data were recorded at 180 °C under differential conditions, using a single serpentine HTPEMFC with a 4 cm2 active area. The fuel cell operated at the activation regime, where ORR potential losses dominate but mass transport limitations are negligible. The experimental data were successfully fitted with the derived analytic IV and EIS microkinetic model.The use of the DAP in accordance with the Transitions State Theory (TST), allowed the extraction and analysis of ORR kinetics and energetics. The deconvoluted EIS outlined the important role of the intrinsic kinetic inertia , i.e. the outcome of the competitive nature of the elementary reaction steps on the adsorbed intermediate species. Kinetic inertia not only dominated EIS and the polarization resistance, but demonstrated that the commonly used Butler Volmer and apparent Tafel slope kinetic approach is incapable of describing the multistep ORR kinetics. With the help of the Degree of Rate Control (DRC) analysis, we successfully identified the O2(g) dissociative adsorption as the rate limiting step.Finally, from an energetics perspective, by employing the TST kinetics formulation, we were able to calculate the free Gibbs’ transition states activation (kinetics) and reaction steps’ energies (thermodynamics). These results clarified that, the high ORR overpotential losses stem from the combined strength of both kinetically and thermodynamically imposed barriers, which originate from the high bonding strength of Oad on the Pt surface and the rather high activation energy of the O2(g) adsorption step.

Enzyme-Mineralized PVASA Hydrogels with Combined Toughness and Strength for Bone Tissue Engineering.

Enzymatic mineralization is an advanced mineralization method that is often used to enhance the stiffness and strength of hydrogels, but often accompanied by brittle behavior. Moreover, the hydrogel systems with dense networks currently used for enzymatic mineralization are not ideal materials for bone repair applications. To address these issues, two usual bone repair hydrogels, poly(vinyl alcohol) (PVA) and sodium alginate (SA), were selected to form a double-network structure through repeated freeze-thawing and ionic cross-linking, followed by enzyme mineralization. The results demonstrated that both enzymatic mineralization and double-network structure improved the mechanical and biological properties and even exhibited synergistic effects. The mineralized PVASA hydrogels exhibited superior comprehensive mechanical properties, with a Young's modulus of 1.03 MPa, a storage modulus of 103 kPa, and an equilibrium swelling ratio of 132%. In particular, the PVASA hydrogel did not suffer toughness loss after mineralization, with a high toughness value of 1.86 MJ/m3. The prepared hydrogels also exhibited superior biocompatibility with a cell spreading area about 13 times that of mineralized PVA. It also effectively promoted cellular osteogenic differentiation in vitro and further promoted the formation of new bone in the femur defect region in vivo. Overall, the enzyme-mineralized PVASA hydrogel demonstrated combined strength and toughness and great potential for bone tissue engineering applications.

A Numerical Simulation Study and Effectiveness Evaluation on the Flow Field Effect of Trapezoidal Artificial Reefs in Different Layouts

The combined release of artificial reefs in different quantities and arrangements leads to different flow field effects. This study designs a small trapezoidal artificial reef. To optimize the quantity and layout of these reefs, trapezoidal reefs in three different layouts were selected for analysis at five different velocity gradients (0.1, 0.5, 1.0, 1.5, and 2.0 m/s). The effects of disposal spacing and layout on the flow field effect of trapezoidal artificial reefs at different flow velocities were simulated using Ansys Fluent. According to the findings: after simulation, flow velocity could indirectly reflect the distribution of upwelling and back eddy, the scale and strength of upwelling increased as flow velocity increased, and the back eddy showed no obvious variation with flow velocity. In transverse combination mode, both the scale and strength of the upwelling and back eddy were maximized when the reef spacing was 1.0 L; in longitudinal combination mode, upwelling and back eddy reached maximum scale and strength when the disposal spacing of the reefs was 1.5 L of a single reef. In 2020, flow mapping and fishery surveys were carried out in the engineering pilot area. The results showed that the number and species of fish populations with 1.5 L spacing in the vertical combination method were significantly higher than those in other forms, and the structure of the fish reef was stable without any flipping or sliding phenomenon. This study can provide a theoretical reference for the design and the actual deployment of artificial reefs to improve the ecological restoration of the water.