In the last two decades, gelatin-based hydrogels have been widely used as tissue engineering scaffolds due to their excellent biocompatibility, biodegradability, easy processability, transparency, non-toxicity, and reasonable structural similarity to the natural extracellular matrix (ECM). However, intrinsic low mechanical properties of gelatin are not structurally and mechanically suitable to support cell growth and proliferation. That’s why various crosslinking strategies including physical, chemical, enzymatic and combination of them as well as networking patterns including double network, interpenetrating network and nano reinforcing mechanism have been utilized to enhance the structural stability and mechanical integrity of gelatin. In this review, the advances in modulating the mechanical properties of gelatin-based hydrogels for the design and development of structurally stable scaffolds for tissue engineering are discussed. The optimized crosslinking parameters with the adequate mechanical properties of gelatin-based hydrogels are reviewed. Gelatin-based scaffolds for a wide range of tissue engineering applications, such as bone, cartilage, cardiac, skin, and nerve tissue engineering are also outlined. Lastly, current challenges and future perspectives in this research field are presented.

Regenerative Medicine and Tissue Engineering are interdisciplinary fields that combine cell biology, material science, and bioengineering to develop therapies for tissue repair and regeneration. This field has made significant advances in recent years, particularly in the use of stem cells and biomaterials. Advancements in cell-based therapies have involved the use of cells to repair or replace damaged tissues and organs. Tissue engineering involves using scaffolds and growth factors to promote tissue regeneration. However, a major challenge in this field is the formation of adhesions, which can cause complications, such as intestinal obstruction and chronic pain. Adhesion barriers are used to prevent adhesion of tissues and organs during recovery, thereby reducing the risk of complications. Anti-adhesion materials, such as polysaccharides, proteins, and synthetic polymers, are used to create a physical barrier between tissues and prevent adhesion. These materials can be used alone or in combination, but their effectiveness varies.

β-glucosidases (BGLs) play a crucial role in the degradation of lignocellulosic biomass as well as in industrial applications such as pharmaceuticals, foods, and flavors. However, the application of BGLs has been largely hindered by issues such as low enzyme activity, product inhibition, low stability, etc. Many approaches have been developed to engineer BGLs to improve these enzymatic characteristics to facilitate industrial production. In this article, we review the recent advances in BGL engineering in the field, including the efforts from our laboratory. We summarize and discuss the BGL engineering studies according to the targeted functions as well as the specific strategies used for BGL engineering.

Female gynecological organ dysfunction can cause infertility and psychological distress, decreasing quality of life of affected women. Incidence is constantly increasing due to growing rates of cancer and delaying of childbearing age in the developed world. Current treatments are often unable to restore organ function, and occasionally are the cause for female infertility. Alternative treatment options are currently being developed in order to face the inadequacy of current practices. In this review, pathologies and current treatments of gynecological organs (ovaries, uterus, and vagina) will be described. The state-of-the-art of tissue engineering alternatives to common practices are evaluated with a focus on in vivo models. Tissue engineering is an ever-expanding field, integrating various domains of modern science to create sophisticated tissue substitutes in the hopes of repairing or replacing dysfunctional organs using autologous cells. Application to gynecology has the potential of restoring female fertility and sexual wellbeing.

The digital society is an outcome of the Internet which has nearly made everything connected and accessible no matter where or when. Nevertheless, despite the fact that conventional IP networks are complicated and very hard to manage, they are still widely adopted. The already established policies make the network configuration/reconfiguration a complex process that reacts to errors, load, and modifications. The prevailing networks are vertically integrated which makes things more and more complicated: Data planes and control are strapped together. Software-defined networking is a model that is meant to solve this issue by splitting the vertical integration and detaching the network’s control logic from the implicit routers and switches; this could be achieved by reinforcing centralization of network control and making the network programmable. In this work, we worked to implement MPLS networks with SDN, to enhance the traffic engineering over the network, and to minimize the network delay and latency, with minimum cost using three of the different SDN networks. The experiment results showed the advantage of the proposed approach for reducing the network delay, comparing with previous studies. Where the average of network delay in our approach reaches to 3.01 milliseconds.

Uncertainty is the main source of risk of geological hazards in tunnel engineering. Uncertainty information not only affects the accuracy of evaluation results, but also affects the reliability of decision-making schemes. Therefore, it is necessary to evaluate and control the impact of uncertainty on risk. In this study, the problems in existing entropy-hazard model such as inefficient decision-making and failure of decision-making are analysed, and an improved uncertainty evaluation and control process are proposed. Then the tolerance cost, the key factor in the decision-making model, is also discussed. It is considered that the amount of change in risk value (R1) can better reflect the psychological behaviour of decision-makers. Thirdly, common attribute decision models, such as the expected utility-entropy model, are analysed, and then the viewpoint of different types of decision-making issues that require different decision methods is proposed. The well-known Allais paradox is explained by the proposed methods. Finally, the engineering application results show that the uncertainty control idea proposed here is accurate and effective. This research indicates a direction for further research into uncertainty, and risk control, issues affecting underground engineering works.

Mesenchymal stem cells (MSCs) are an attractive therapeutic tool for tissue engineering and regenerative medicine owing to their regenerative and trophic properties. The best-known and most widely used are bone marrow MSCs which are currently being harvested and developed from a wide range of adult and perinatal tissues. MSCs from different sources are believed to have different secretion potentials and production which may influence their therapeutic effects. To confirm it, we performed a quantitative proteomic analysis based on the TMT technique of MSCs from three different sources: Wharton’s jelly (WJ), dental pulp (DP) and bone marrow (BM). Our analysis focused on MSC biological properties of interest for tissue engineering. We identified a total of 611 differentially expressed human proteins. WJ-MSCs showed the greatest variation compared with the other sources. WJ produced more extracellular matrix (ECM) proteins and ECM-affiliated proteins and appeared more able to modulate the inflammatory and immune response. BM-MSCs displayed enhanced differentiation and paracrine communication capabilities. DP-MSC appeared to promote exosome production. The results obtained confirm the existence of differences between WJ, DP and BM-MSC and the need to select the MSC origin according to the therapeutic objective sought.

It is known that people perceive animacy in objects. However, many studies on animacy and emotional expressions are limited in that the investigated motions were created by experimenters themselves. This makes the objective validity unclear. Moreover, it remains unclear what types of movements can express emotions with animacy due to the limited number of investigations examining both animacy and emotional expressions. Therefore, we investigated the motion elements for both animacy perception and emotional expressions using simple objects that lack features of specific living things, such as eyes, ears, tails, and voices in this study. First, we investigated the motion elements for animacy perception and emotional expressions using a robot simulator that enabled participants to create undulatory motions by tuning parameters for speed, height, and randomness. In total, 64 participants created motions in Normal (neutral), Joy, Sad, Relaxed, and Angry conditions. The results showed that the medians of speed and height in Normal, related only to animacy, were 0.5569[Hz] and 3.050cm at the edges/4.575cm at the center. The differences in Joy were 0.4028[Hz] and 3.348cm/5.022cm, in Sad were −0.1652[Hz] and −0.9982cm/−1.497cm, in Relaxed were −0.1979[Hz] and −0.4902cm/−0.7353cm, and in Angry were 0.5212[Hz] and 4.688cm/7.032cm. Second, we investigated whether the motion elements revealed in the first experiment were sufficient to express emotions with animacy, using a robot simulator that reflected the results of the motion element investigation. In total, 44 online participants observed the simulator. The results showed that participants could understand emotional arousal levels at the same time as animacy, but they did not fully understand emotional valence. Our findings provide design guidelines for robots that exhibit emotional expressions and closely interact with humans.

Regeneration of biological tissues in medicine is challenging, and 3D bioprinting offers an innovative way to create functional multicellular tissues. One common way in bioprinting is bioink which is one type of the cell-loaded hydrogel. For clinical application, however, the bioprinting still suffers from satisfactory performance, e.g. in vascularization, effective antibacterial, immunomodulation and regulation of collagen deposition. Many studies have incorporated different bioactive materials into the 3D printed scaffolds to optimize the bioprinting. Here, we review a variety of additives added to the 3D bioprinting hydrogel. The underlying mechanisms and methodology for biological regeneration are important and will provide useful basis for future research.

Abstract: Chloroplast is a new hotspot in the field of plant transformation system of plant genetic engineering. Initially developed in Chlamydomonas and tobacco, it is now feasible in a broad range of species. They exploit the homologous recombination and segregation pathways acting on chloroplast genomes and are based on direct repeats, transient co-integration or co-transformation and segregation of trait and marker genes. Foreign site-specific recombinases and their target sites provide an alternative and effective method for removing marker genes from plastids.Chloroplast genetic engineering has many advantages over nuclear genetic enginering, especially site-specific introduction of foreign genes ,leading to the absence of gene siliency and positon effect,which providing the available to explore the regulation and mechanism of chloroplast genes`expression in vitro .It also can identify the structure and function of the chloroplast genome , the expression of chloroplast affect the nulear genome. In this paper, the basic methodology of chloroplast transformation, the current techniques and applications, and the future possibilities for Chloroplast genetic engineering was reviewed[1-3].

In this study, 3D printing of poly-l-lactic acid (PLLA) scaffolds reinforced with graphene oxide (GO) nanoparticles via Digital Light Processing (DLP) was investigated to mimic bone tissue. Stereolithography is one of the most accurate additive manufacturing method, but the dominant available materials used in this method are toxic. In this research, a biocompatible resin (PLLA) was synthetized and functionalized to serve the purpose. Due to the low mechanical properties of the printed product with the neat resin, graphene oxide nanoparticles in three levels (0.5, 1, and 1.5 Wt.%) were added with the aim of enhancing the mechanical properties. At first, the optimum post cure time of the neat resin was investigated. Consequently, all the parts were post-cured for three hours after printing. Due to the temperature-dependent structure of GO, all samples were placed in an oven at 85 ° C for different time periods of 0, 6, 12, and 18 hours to increase mechanical properties. The compression test of heat treated samples reveals that the compressive strength of the printed parts containing 0.5,1, and 1.5 % of GO increased by 151,162 ad 235%, respectively. Scaffolds with the designed pore sizes of 750 microns and a porosity of 40% were printed. Surface hydrophilicity test was performed for all samples showing that the hydrophilicity of the samples increased with increasing GO percentage. The degradation behavior of the samples was evaluated in a PBS environment, and it revealed that by increasing GO, the rate of component degradation increased, but the heat treatment had the opposite effect and decreased the degradation rate. Finally, besides improving biological properties, a significant increase in mechanical properties under compression can introduce the printed scaffolds as a suitable option for bone implants.

Scaffolds are widely used in tissue engineering because their manufacture is based on natural and synthetic polymers, which allows them to have properties such as biocompatibility and biodegradability, creating an ideal environment for cell growth on their surface. In this context, among the polymers studied in Tissue Engineering are Chitosan (CH) and Polyvinyl Alcohol (PVA). CH is a versatile polymer obtained from de-acetylation of chitin, which is used for its high biodegradability and biocompatibility, although its mechanical properties must be improved. It has been found that one of the ways to improve the mechanical properties of CH is to mix it with other synthetic polymers such as PVA. PVA is known for its biocompatibility, biodegradability, zero toxicity and ease of preparation due to its solubility in water and excellent mechanical properties, such as tensile strength and ease in the formation of films and barriers. In this study we evaluated the capacity of scaffolds made with CH and PVA in different concentrations (2: 1, 1: 1, 1: 2, respectively) as a possible application in bone regeneration. This was made through different characterization tests such as Infrared Spectroscopy, AFM, Swelling test and Porosity test, where we obtained information about its structural and physicochemical properties. Additionally, a cellular quality control was performed on the material through the MTT assay. The Fourier transform infrared spectroscopy (FTIR) study showed that there are strong intermolecular hydrogen bonds between the chitosan and polyvinyl alcohol molecules. The Swelling and Porosity tests showed favorable results, obtaining maximum values ​​of 5519% and 72.17% respectively. MTT tests determined that the prepared materials are not cytotoxic. These findings suggest that scaffolds possess properties suitable for use in Tissue Engineering.

Herein are reported the main pros and cons of using the conversational Artificial Intelligence (AI) called “ChatGPT” as a tool to write essays in the academic and scientific community. Also, selected mathematical and scientific problems were solved to determine the effectiveness of this platform. To this end, a systematic case study was designed and conducted to obtain data generated by the chatbot that was further analyzed. Six different topics were chosen for the essay evaluation, and the introduction section was created using this AI. Meanwhile, six mathematical problems related to integrals, z-transform, Laplace transform, and resolution of ordinary differential equations were solved. Furthermore, a scientific problem associated with the structural properties of material was also solved. After data analysis, we concluded that the conversational platform could quickly create written essays with well-structured words. Nonetheless, in almost all cases, the chatbot only used basic information to complete the introduction, and no critical writing was obtained. For the mathematical case study, we observed that under the current status of the ChatGPT, this platform has no ability or skills to solve complex equations. Thus, significant changes need to be conducted to improve the performance of ChatGPT for mathematical solutions.

3D bioprinting is the process of manipulating cell-laden bioinks to fabricate living structures. 3D bioprinting techniques have brought considerable innovation in biomedicine, especially in the field of tissue engineering, allowing the production of 3D organ and tissue models for in vivo transplantation purposes or for in-depth and precise in vitro analyses. Natural-derived hydrogels, especially those obtained from the decellularization of biological tissues, are promising bioinks for 3D printing purposes, as they present the best biocompatibility characteristics. Despite this, many natural hydrogels do not possess the necessary mechanical properties to allow a simple and immediate application in the 3D printing process. In this review, we focus on the bioactive and mechanical characteristics that natural hydrogels may possess to allow efficient production of organs and tissues for biomedical applications, emphasizing the reinforcement techniques to improve their biomechanical properties.

This paper offers a comprehensive examination of the process involved in developing and automating supervised end-to-end machine learning workflows for forecasting and classification purposes. It offers a complete overview of the components (i.e. feature engineering, model selection, etc), principles (i.e. bias-variance decomposition, model complexity, overfitting, model sensitivity to feature assumptions and scaling, output interpretability, etc), models (i.e. neural networks, regression models, etc), methods (i.e. Cross-Validation, data augmentation, etc), metrics (i.e. Mean Squared Error, F1-score, etc) and tools that rule most supervised learning applications with numerical and categorical data, as well as their integration, automation, and deployment. The end goal and contribution of this paper is the education and guidance of the non-AI expert academic community over complete and rigorous machine learning pipelines and data science practices, from problem scoping to design and state-of-the-art automation tools, including basic principles and reasoning in the choice of methods. The paper delves into the critical stages of supervised machine learning workflow development, many of which are often omitted by researchers due to brevity, and covers foundational concepts essential for understanding and optimizing a functional machine learning workflow, thereby offering a holistic view of task-specific application development for applied researchers who are not AI experts.

Hydrogels obtained from the combination of different polymers are an interesting strategy for the development of controlled release system platforms and tissue engineering scaffolds. In this study, the applicability of sodium alginate-g-(QCL-co-HEMA) hydrogels for these biomedical applications was evaluated. Hydrogels were synthesized by free-radical polymerization using different concentration of the components. The hydrogels were characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, and swelling degree; betamethasone release as well as the in vitro cytocompatibility with chondrocytes and fibroblast cells were also evaluated. Scanning electron microscopy confirmed the porous surface morphology of the hydrogels in all cases. The swelling percent was determined at different pH and was observed to be pH-sensitive. The controlled release behavior of betamethasone from the matrices was investigated in PBS media (pH = 7.4) and the drug was released in a controlled manner up to 8 h. Human chondrocytes and fibroblasts were cultured on the hydrogels. The MTS assay shown that almost all hydrogels are cytocompatibles and an increase the proliferation in both cell types after one week of incubation was observed by Live/Dead® assay. These results demonstrate that these hydrogels are attractive materials for pharmaceutical and biomedical applications due to their characteristics, their release kinetics and biocompatibility.

Radish is an annual herbaceous root crop, fruit, and oil crop plant belonging to the Cruciferae family. The important traits for radish breeding include high yield, early maturity, late bolting, pungency, cold-hardiness, drought resistance, heat tolerance, and soil adaptability. For successful radish production, need to the understand nature and behavior of the flower, and very important to identify the S haplotypes of parental lines to produce F₁ hybrids based on self-incompatibility to get rid of laborious hand emasculation in radish. In radish some desirable genes are not present within varieties. Therefore, further breeding programmes depend on inter-specific and intra-specific hybridization, which has a vital role in genomic studies and crop improvement by introducing desirable agronomic characters. It is essential to acquire detailed genetic information on chromosomes and information on inheritance. Genomics is now at the core of crop improvement, and radish crop is exploited to study the underlying differences in genotypes. But some monogenic characters are improved by genetic engineering. A three-decade span following the first documented instance of genetic engineering has witnessed its application's unprecedented growth. Researchers have successfully produced transgenic radishes with various agronomic characteristics over the last decade.

Extensive damage to peripheral nerves is a health problem with few therapeutic alternatives. In this context, the development of tissue engineering seeks to obtain materials that can help recreate environments conducive to cellular development and functional repair of peripheral nerves. Different hydrogels have been studied and presented as alternatives for future treatments to emulate the morphological characteristics of nerves. Along with this, other research proposes the need to incorporate electrical stimuli into treatments as agents that promote cell growth and differentiation; however, no precedent correlates the simultaneous effects of the types of hydrogel and electrical stimuli. In this research, the neural differentiation of PC12 cells we are evaluated, relating the effect of collagen, alginate, GelMA, and PEGDA hydrogels with electrical stimulation modulated in four different ways. Our results show significant correlations for different culture conditions, allowing us to develop new experimental schemes for new materials in peripheral nerve engineering.

Within the past decade, the aerospace engineering industry has evolved outside the constraints of using single, large, custom satellites. Due to increased reliability and robustness of commercial off the shelf (COTS) printed circuit board (PCB) components, missions instead have transitioned towards deploying swarms of smaller satellites. This approach significantly decreases the mission cost by reducing custom engineering and deployment expenses. Nanosatellites are able to be quickly developed with a more modular design at lowered risk. The Alpha mission at Cornell Space Systems Studio is fabricated in this manner. However, for the purpose of this mission, only one satellite was initially developed. This manuscript will discuss a systems engineering approach to the development of this satellite. As a disclaimer, this manuscript is written from a systems perspective. Therefore it will follow many subsystems from a wide range of functionalities. The research in this manuscript was kept broad with the hope to contribute to the mission as a system, through a range of development phases including validation and verification of existing methods. The two systems that will be primarily focused on are the Attitude Control System (ACS) of the carrier nanosatellite (cubesat), and the RF communications on the ex-creted picosatellites (chipsat). Milestones achieved in chipsat RF include chipsat to chipsat communication, chipsat to SDR ground station communication, packet creation, error correction, appending a preamble, and filtering the signal. Achievements on the ACS side included controller traceability/verification and validation, software rigidity tests, hardware endurance testing, Kane damper and IMU tuning. These developments matured the technological readiness level (TRL) of our systems in preparation for satellite deployment.

The applicable conditions and scope of the underground sewage treatment plant include small amount of sewage, less available land on the ground, special requirements for the above-ground landscape, low groundwater level, easy-to-excavate geology, and the buried depth of the sewage return pipe is not very large. It is not under the main road, has certain distance from residential buildings, is not a depression and does not accumulate rainwater, and the sewage discharge requirements are not very strict. The underground sewage treatment plants are suitable in an area, where thermal insulation needs to be considered, less requisitionable land area, and higher environmental requirements The results of underground landscape design study showed that the design of principles, features, styles, water ecologies, combination between community and ecological friendly, operation and maintenance cost of the underground landscape should be emphasized. The construction of ecological complex will lead the sewage treatment plant exchange from minus assets to the ecological positive assets, which will meet the needs of future urban social economic development and environmental protection. The results of development direction exploration study showed that innovation on design concept, breakthroughs of key sewage treatment technology and variation of investment and operation mode can reduce the land occupation investment and operation cost, and the underground sewage plant with large scale and semi-underground mode owes broader prospects for development.

Vehicle safety promises to be one of the Advanced Driver Assistance System (ADAS) biggest benefits. Higher levels of automation remove the human driver from the chain of events that can lead to a crash. Sensors play an influential role in vehicle driving as well as in ADAS by helping the driver to watch the vehicle’s surroundings for safe driving. Thus, the driving load is drastically reduced from steering as well as accelerating and braking for long-term driving. The baseline for the development of future intelligent vehicles relies even more on the fusion of data from surrounding sensors such as Camera, Lidar and Radar. These sensors not only need to perceive in clear weather but also need to detect accurately adverse weather and illumination conditions. Otherwise, a small error could have an incalculable impact on ADAS. As most of the current study is based on indoor or static testing. In order to solve this problem, this paper designs a series of dynamic test cases with the help of outdoor rain and intelligent lightning simulation facilities to make the sensor application scenarios more realistic. As a result, the effect of rainfall and illumination on sensor perception performance is investigated. As speculated, the performance of all automotive sensors is degraded by adverse environmental factors, but their behaviour is not identical. Future work on sensor model development and sensor information fusion should therefore take this into account.

Dental pulp tissue engineering (TE) quests to regenerate dentin/pulp complex by combining a suitable supporting matrix, stem cells, and biochemical stimuli. Such procedures foresee a matrix that can be easily introduced into the root canal system (RCS) and tightly adhere to dentin walls to assure the dentin surface's proper colonization with progenitor cells capable of restoring the dentin/pulp complex. Herein was investigated an injectable self-setting hyaluronic acid-based (HA) hydrogel system, formed by aldehyde-modified (a-HA) with hydrazide-modified (ADH), enriched with platelet lysate (PL), for endodontic regeneration. The hydrogels' working (wT) and setting (sT) times, the adhesion to the dentine walls, the hydrogel's microstructure, and the delivery of human Dental Pulp Cells (DPCs) were studied in vitro. Hydrogels incorporating PL showed a suitable wT and sT and a porous microstructure. The tensile tests showed that the breaking point occurs after 4.13 mm deformation. While in the indentation test after 1.3 mm deformation. Both breaking points occur in the hydrogel extension. The HA/PL hydrogels exhibited supportive properties and promoted cell migration toward dentin surfaces in vitro. Overall, these results support using PL-laden HA injectable hydrogels (HA/PL) as a biomaterial for DPCs encapsulation, thereby displaying great clinical potential towards endodontic regenerative therapies.

Research on Cas9 nucleases from different organisms holds great promise for advancing genome engineering and gene therapy tools as it could provide novel structural insights into CRISPR editing mechanisms, expanding its application area in biology and medicine. The current study focuses on generating a construct to express a compact Cas9 nuclease (AnoCas9) from the thermophilic microorganism Anoxybacillus flavithermus. Next, distinctive AnoCas9 properties are investigated. AnoCas9 gene is expressed in E.coli producing a polypeptide fused with the maltose-binding protein (MBP-AnoCas9). His-Tag in its structure enables purification using metal-chelate chromatography followed by the cleavage of the polypeptide by TEV protease. Bioinformatical analysis of the CRISPR array found in the genome of an Anoxybacillus flavithermus strain helps predict a functional PAM sequence for AnoCas9, which is supported by in vitro experiments. The purified protein demonstrates nuclease activity in the presence of crRNA:tracrRNA duplex in the 37-60 °С range, with maximum activity observed at 45-55 °С. The analysis of FAM-labeled dsDNA substrate cleavage has allowed us to determine the functional AnoCas9 PAM motif as 5’-NNNNCDAA-3’. Thus, AnoCas9 adds to the repertoire of thermophilic Cas9 effectors and its properties suggest application in areas requiring the presence of thermostable CRISPR/Cas systems.

The main purpose of this study was to design a workplace in the conditions of a digital factory. The goal of this study is to compile a proposal for improving the layout solution in the selected enterprise to reduce material flows between individual workplaces. In addition, the workplace research study uses methods of material flow analysis with the application of visTABLE software support, which serves as a tool for designing production processes. The main result of the study was the reduction of the production time of the beam by 10 minutes and the creation of proposals for solutions for the company. The study helped with the visualization of processes within the digital factory to simplify and clarify processes at the workplace.

The goal of the next generation World Wide Web is machine readability through linked databases. To improve web search, integration, and mining in local languages like Urdu, there is a growing need to develop ontologies and vocabulary in these languages. The majority of people use the web in local languages for agriculture, social media interaction, news, etc. How to create agents for the integration of web data. In our country, the literacy ratio is very low and IT literacy is negligible. More comprehensive information for its target audience is only possible through the World Wide Web. Our first target is to improve and enhance the use of social media and the web in local languages. That will encourage its constructive use in Urdu for society and the economy. The Web in natural languages is the source of income for small and medium enterprises. The semantic web is concerned with linked databases and structured data. In this work, we are focused on some selected ontologies to be translated into natural languages. Expertise in Ontology Engineering helps us in job production. Ontology Engineering has extensive freelancing opportunities. Only if the web is correctly interpreted in regional languages is an economic boost achievable. A standardized foundation for data sharing and reuse on the internet is provided by the Semantic Web. In other words, a group of standards and technology that enables computers to comprehend the semantics (meaning) of material on the Web.

The steady-state multiplicity of the porous, non-isothermal, catalyst pellet when two parallel and consecutive chemical reactions take place was analysed in this work. The geometry selected for the catalyst pellet is finite hollow cylinder. A numerical multigrid continuation technique with the preconditioned conjugate gradient squared as coarse grid solver was used. The continuation parameter is the dimensionless adiabatic heat rise (Prater number) for the first chemical reaction. The effect of the other governing parameters was analysed and the results are compared to those provided by the single chemical reaction.

In this study, we used the natural and anthropogenic characteristics of a coastal region to generate risk maps showing vulnerability and potential hazards, and proposed design criteria for coastal defense and land use for the various kinds of risks faced. The Yunlin coast: a first-level protection area in mid-west Taiwan, was then used as an example to illustrate the proposed design criteria. The safety of the present coastal defenses and land use of the Yunlin coastal area was assessed, and coastal protection measures for hazard prevention were proposed based on the generated risk map. The results can be informative for future coastal management and the promotion of sustainable development of coastal zones.

Object-Oriented Programming (OOP) has long been a dominant paradigm in software development, but it's not without its challenges. One major issue is the problem of tight coupling between objects, which can hinder flexibility and make it difficult to modify or extend code. Additionally, the complexity of managing inheritance hierarchies can lead to rigid and fragile designs, making it hard to maintain and evolve the software over time. This paper introduces a software development pattern that seeks to offer a renewed approach to writing code in Object-Oriented (OO) environments. Addressing some of the limitations of the traditional approach, the Puzzle Pattern focuses on extreme modularity, favoring writing code exclusively in interfaces. Concrete classes are subsequently assembled through the implementation of those interfaces, reducing coupling and introducing a new level of flexibility and adaptability in software construction. The highlighted pattern offers significant benefits in software development, promoting extreme modularity through interface-based coding, enhancing adaptability via multiple inheritance, and upholding the SOLID principles, though it may pose challenges such as complexity and a learning curve for teams.

The evaluation of nanostructured biomaterials and medicines is associated with 2D cultures that provide insight into the biological mechanisms at the molecular level, while critical aspects of the tumor microenvironment (TME) are provided by the study of animal xenograft models. More realistic models that can histologically reproduce human tumors are provided by tissue engineering methodologies of co-culturing cells of varied phenotypes, to provide 3D tumor spheroids that recapitulate the dynamic TME in 3D matrices. The novel approaches of 3D tumor models are combined with tumor tissue engineering (TTE) scaffolds including hydrogels, bioprinted materials, decellularized tissues, fibrous and nanostructured matrices. This review focuses on the use of nanostructured materials in cancer therapy and regeneration, and the development of realistic models for studying TME molecular and immune characteristics. Tissue regeneration is an important aspect of TTE scaffolds for restoring the normal function of the tissues, while providing cancer treatment. Thus, this article reports recent advancements on the development of 3D TTE models for antitumor drug screening, studying of tumor metastasis, and tissue regeneration. Also, this review identifies the great opportunities of 3D TTE scaffolds in the evaluation of the immunological mechanisms and processes involved in the application of immunotherapies.

In an increasingly complex world there is a real, urgent need for methodologies to enable engineers to model complex sociotechnical systems, as these now seem to describe the majority of systems in use today. This is of course exacerbated by the increasing involvement and augmentation with “black box” AI contributions. Hollnagel produced a methodology, (FRAM) which did allow the analyst in-sights into these systems’ behaviour, but the model-based system engineering applications demand numbers and a quantitative ap-proach. In the last 10 years, this original approach developed to model systems as sets of interactive, interdependent “functions”, (abstracted from agent or component details), has been further developed to the point where it can take the basic data and structures from the current component focussed system engineering “models”, and can pull it all together into dynamic models, (as opposed to static, fixed System Theoretic Process Accimaps), from which analysts can discern how they really work in practice, and predict the emergent behaviours characteristic of complex systems. This paper describes how the FRAM methodology has now been extended to provide these extra, essential attributes. It also describes its implementation using an open-source software, freely available for use and verification on the GitHub site.

3D Printing (3DP) technology has revolutionized the field of the use of bioceramics for maxillofacial and periodontal applications, offering unprecedented control over the shape, size, and structure of bioceramic implants. In addition, bioceramics have become attractive materials for these applications due to their biocompatibility, biostability, and favorable mechanical properties. However, despite their advantages, bioceramic implants are still associated with inferior biological performance issues after implantation, such as slow osseointegration, inadequate tissue response, and increased risk of implant failure. To address these challenges, researchers have been developing strategies to improve the biological performance of 3D printed bioceramic implants. The purpose of this review is to provide an overview of 3DP techniques and strategies for bioceramic materials designed for bone regeneration. The review also addresses the use and incorporation of active biomolecules in 3D printed bioceramic constructs to stimulate bone regeneration. By controlling the surface roughness, and chemical composition of the implant, the construct can be tailored to promote osseointegration and reduce the risk of adverse tissue reactions. Additionally, growth factors, such as bone morphogenic proteins (rhBMP-2) and pharmacologic agent (dipyridamole), can be incorporated to promote the growth of new bone tissue. Incorporating porosity into bioceramic constructs can improve bone tissue formation and the overall biological response of the implant. As such, by employing surface modification, combining with other materials, and incorporation of 3DP workflow can lead to better patient healing outcomes.

Focal cartilage defects are a prevalent knee problem affecting people of all ages. Due to its avascular nature, cartilage has limited self-repair capacity, and osteochondral defects can lead to pain and long-term complications such as osteoarthritis. Autologous chondrocyte implantation (ACI) has been a successful surgical approach for repairing osteochondral defects over the past two decades. However, a major drawback of ACI is the de-differentiation of chondrocytes during their in vitro expansion. In this study, we isolated ovine chondrocytes and cultured them in a two-dimensional environment as for ACI procedures. We hypothesised that the 3D scaffolds would support the cells re-differentiation without the need for growth factors and so we encapsulated them into soft collagen and alginate (col/alg) hydrogels. Chondrocytes embedded into hydrogels were viable and proliferated. After 7 days they acquired a rounded morphology and started to aggregate. Gene expression studies showed that the genes associated with chondrogenesis started to be up regulated as early as day one. At 21 days chondrocytes had extensively colonized the hydrogel, forming large cell clusters and started to deposit collagen II and aggrecan with limited collagen type I deposition. These findings highlight the potential of soft col/alg hydrogels to enhance ACI outcomes by creating a favourable microenvironment for chondrocyte reprogramming and re-differentiation, eliminating the dependency on growth factors.

The main purpose of tissue engineering is to fabricate and exploit engineered constructs suitable for the effective replacement of damaged tissues and organs, and able to perfectly integrate with the host’s organism without eliciting any adverse reaction. Ideally, autologous materials represent the best option, but they are often limited due to the low availability of compatible healthy tissues. So far, one therapeutic approach relies on the exploitation of synthetic materials: they exhibit good features in terms of impermeability, deformability and flexibility, but present chronic risks of infections and inflammations. Alternatively, biological materials, including naturally derived ones and acellular tissue matrices of human or animal origin, can be used to induce cells growth and differentiation, which are needed for tissue regeneration: however, this kind of materials lacks satisfactory mechanical resistance and reproducibility, affecting their clinical application. In order to overcome the above-mentioned limitations, hybrid materials, which can be obtained by coupling synthetic polymers and biological materials, have been investigated with the aim to improve biological compatibility and mechanical features. Currently, the interest in these mate-rials is growing, but the ideal ones have not been found yet. The present review aims at exploring some applications of hybrid materials, with particular mention to urological and cardiovascular fields: in the first case, the efforts to find a construct that can guarantee impermeability, mechanical resistance and patency will be herein illustrated; in the second case, the search for impermeability, hemocompatibility and adequate compliance will be been disclosed.

Antimicrobial resistance (AMR) is a major global concern; antibiotics and other regular treatment methods have failed to overcome the increasing number of infectious diseases. Bacteriophages (phages) are viruses that specifically target/ kill bacterial hosts without affecting other human microbiome. Phage therapy provides optimism in the current global healthcare scenario with a long history of its applications in humans that has now reached various clinical trials. Phages in clinical trials have specific requirements of being exclusively lytic, free from toxic genes with an enhanced host range that adds an advantage to this requisite. This review explains in detail the various phage engineering methods and their potential applications in therapy. To make phages more efficient, engineering has been attempted using techniques like conventional homologous recombination, Bacteriophage Recombineering of Electroporated DNA (BRED), clustered regularly interspaced short palindromic repeats (CRISPR)-Cas, CRISPY-BRED/Bacteriophage Recombineering with Infectious Particles (BRIP), chemically accelerated viral evolution (CAVE), and phage genome rebooting. Phages are administered in cocktail form in combination with antibiotics, vaccines, and purified proteins, such as endolysins. Thus, phage therapy is proving to be a better alternative for treating life-threatening infections, with more specificity and fewer detrimental consequences.

Nano/micron-sized bioactive glass (BG) particles are attractive candidates for both soft and hard tissue engineering. They can chemically bond to the host tissues, enhance new tissue formation, activate cell proliferation, stimulate the genetic expression of proteins, and trigger unique an-ti-bacterial, anti-inflammatory, and anti-cancer functionalities. Recently, composites based on bi-opolymers and BG particles have been developed with various state-of-the-art techniques for tis-sue engineering. Gelatin, a semi-synthetic biopolymer, has attracted the attention of researchers because it is derived from the most abundant protein in the body, viz., collagen. It is a polymer that can be dissolved in water and processed to acquire different configurations, such as hydro-gels, fibers, films, scaffolds, etc. Searching "bioactive glass gelatin" in the tile on Scopus renders 80 highly relevant articles published in the last ~10 years, which signifies the importance of such composites. First, this review addresses the basic concepts of soft and hard tissue engineering, in-cluding the healing mechanisms and limitations ahead. Then, current knowledge on gelatin/BG composites including composition, processing and properties is summarized and discussed both for soft and hard tissue applications. This review explores physical, chemical and mechanical features and ion-release effects of such composites concerning osteogenic and angiogenic respons-es in vivo and in vitro. Additionally, recent developments of BG/gelatin composites using 3D/4D printing for tissue engineering are presented. Finally, the perspectives and current challenges in developing desirable composites for the regeneration of different tissues are outlined.

Laser patterning of implant materials for bone tissue engineering purposes has shown to be a promising technique to control cell properties such as adhesion or differentiation, resulting in an enhanced osteointegration. However, the perspective of patterning the bone tissue side interface to generate microstructure effects has never been investigated. In the present study, three different laser-generated patterns were machined on the bone surface with the aim to identify the best surface morphology compatible with osteogenic-related cells recolonization. The laser patterned bone tissue was characterized by electron scanning microscopy and confocal microscopy in order to obtain a comprehensive picture of the bone surface morphology. Cortical bone patterning impact upon cell compatibility and cytoskeleton rearrangement to the patterned surfaces was performed with Stromal Cells from Apical Papilla (SCAPs). Results indicated that laser machining had no detrimental effect upon consecutively seeded cells metabolism. Orientation assays revealed that surface patterning characterized by larger hatch distances was correlated with a higher cell cytoskeletal conformation to the laser-machined patterns. For the first time, to our knowledge, bone is considered and assessed here as a potentially engineered-improvable biological interface. Further studies shall focus on in vivo implications of this direct patterning.

Decision making as a result of system dynamics analysis requires, in practice, a straightforward and systematic modelling capability as well as a high-level of customisation and flexibility to adapt to situations and environments that may vary very much from each other. While in general terms a completely generic approach could be not as effective as ad-hoc solutions, the proper application of modern technology may facilitate agile strategies as a result of a smart combination of qualitative and quantitative aspects. In order to address such a complexity, we propose a knowledge-based approach that integrates the systematic computation of heterogeneous criteria with open semantics. The holistic understanding of the framework is described by a reference architecture and the proof-of-concept prototype developed can support high-level system analysis, as well as it suitable within a number of applications contexts - i.e. as a research/educational tool, communication framework, gamification and participatory modelling. Additionally, the knowledge-based philosophy, developed upon Semantic Web technology, increases the capability in terms of holistic knowledge building and re-use via interoperability. Last but not least, the framework is designed to constantly evolve in the next future, for instance by incorporating more advanced AI-powered features.

Glaucoma is a blinding disease largely caused by increased resistance to drainage of fluid from the eye’s anterior chamber, resulting in elevated intraocular pressure (IOP). A major site of fluid outflow regulation and pathology is the trabecular meshwork (TM) at the entrance of the eye’s drainage system. We aimed to characterize the structural and functional properties of a newly developed tissue-engineered anterior segment eye culture model. We hypothesized that repopulation of a decellularized TM with non-native TM cells could restore aspects of normal TM. The decellularization protocol removed all cells and debris while preserving the ECM. Seeded cells localized to the TM region and progressively infiltrated the meshwork ECM. Cells reached a distribution comparable to control TM after four days of perfusion culture. After a perfusion rate increase challenge, tissue-engineered cultures reestablished normal IOPs (reseeded = 13.7±0.4 mmHg, decellularized = 35.2±2.2 mmHg, p < 0.0001). eGFP expressing CrFK control cells caused a high and unstable IOP (27.0±6.2 mmHg). In conclusion, we describe a readily available, storable, and biocompatible scaffold for anterior segment perfusion culture of non-native cells. Tissue-engineered organs demonstrated similarities to native tissues and may reduce the need for scarce donor globes in outflow research.

At the start of 2020 the rapid onset of the coronavirus pandemic forced higher education institutions across the world to pivot from face to face to remote teaching. For teaching methods that involve the transmission and dissemination of verbal/visual information between academic staff and students, video technologies provided immediate methods to respond to the restricted access to campus. Practical activities, that usually involve interaction with equipment, presented a greater challenge to adapt for remote delivery. With restrictions on higher education being partially lifted, many institutions worldwide intend to offer blended learning, prioritizing in-person activities that are troublesome to deliver online, such as practicals. Social distancing measures are reducing capacity and placing increased pressure on space, creating a need to optimise limited time students have in the lab and strategies to determine which activities can best utilize this limited resource. Time is constrained, leaving little opportunity to make radical changes to learning and teaching structures. In this publication, The department of Mulicdipalnary Engineering Education (MEE) at the University of Sheffield, utilise their experiences in practical teaching to provide simple, implementable ideas for blended practicals which maximize students’ learning and experiences within the envelope of available resources.

Multidisciplinary Engineering Education (MEE) at the University of Sheffield is dedicated to delivering, at scale, practical teaching to students in the Faculty of Engineering. The COVID-19 pandemic initiated the sudden suspension of face to face teaching required MEE to translate over 600 in-lab practicals to a remote delivery format. With little opportunity to coordinate, academic staff independently adopted a variety of tactics to ensure practical learning outcomes were maintained. Following the reactive response, a proactive reflection was conducted and six categories of tactics for remote practicals have been established. These categories are Provide digital artefacts; Simulated practicals; Synchronous remote participation; Asynchronous participation by proxy; Perform procedure in alternative environment; Remote staff support. The advantages and drawbacks of each of these categories is discussed and it is suggested which tactics are appropriate for particular learning outcomes or operational and environmental outcomes of equivalent in-lab practicals. Further work to comprehensively align outcomes to tactics is proposed and lasting benefit from the analysis can be realized by adopting a principle of Remote Enhanced Practicals.

Organ-on-Chip is a game-changing technology born from the convergence of tissue engineering and microfluidic technology. Organ-on-Chip devices (OoCs) are expected to offer effective solutions to persisting problems in drug development and personalized disease treatments. This opinion paper surveys the current landscape in research, development, application and market opportunities for OoCs to help establishing a global and multi-stakeholder OoC ecosystem. Based on a bibliometric study, a market analysis, expert interviews, and panel discussions held at the ORCHID Vision Workshop (Stuttgart, 23 May 2018), we outline presently unmet needs, key challenges, barriers and perspectives of the field, and finally propose recommendations towards the definition of a comprehensive roadmap that could render OoCs realistic models of human (patho)physiology in the near future.

The challenges to sustainability governance across multiple geographical/cultural contexts lead us to the “piecemeal engineering” idea advocated by the philosopher Karl Popper, which explicitly considers context. We argue for adopting the piecemeal engineering approach, augmented by adaptive policies and modern (online) collaboration platforms to maximize the prospects of sustainable practices worldwide. This recommended course is not intended to be a theory in itself. Rather, it is a well-grounded, practical and practicable stop-gap measure in times when complexity and change outpace theories and strategies. We present a philosophical foundation for this “Augmented Popperian Experimentation.” Focusing on The Water Network (the largest collaborative platform for water researchers and professionals), we show that sustainability-oriented organizations in the water realm and others are inching toward the practice we advocate. We discuss implications.

The combination of increased pressures for high-volume, high-impact publications in English language with the high rejection rates of submitted manuscripts for publications presents an often unsurpassable obstacle for (early career) researchers. At the same, the register requirements of peer-reviewed journals -that can contribute to whether a paper is accepted for publication- has received little attention. This paper redresses this gap, by investigating the linguistic choices in 60 published manuscripts in four journals, with impact factor (IF) above 2; all 4 journals, publish original research papers in the field of chemical engineering science and specifically focus on wastewater treatment. Our survey shows that chemical engineering research publications tend to comply to a set of unwritten requirements: multidisciplinarity, brevity, co-authorship, focus on the description of practical results (rather than methods), and awareness of non-specialised audiences. It is found that less discipline-specific vocabulary was used in higher IF journals and this is interpreted within the current context of manuscript publication and consumption. Also, a complex relationship between the advertised scope of each journal and the actual published papers exists, indicating that guide for authors and aims and objective published by the journal's editorial office should be critically evaluated.

Adipose stem cells (ASCs) have multilineage differentiation capacity and hold great potential for regenerative medicine. Compared to bone-marrow-derived mesenchymal stem cells (bmMSCs), ASCs are easier to isolate from abundant sources with significantly higher yields. It is generally accepted that bmMSCs show age-related changes in their proliferation and differentiation potentials, whereas this aspect is still controversial in the case of ASCs. In this review, we evaluated the existing data on the effect of donor age on the osteogenic potential of human ASCs. Overall, a poor agreement has been achieved because of inconsistent findings in the previous studies. Finally, we attempted to delineate the possible reasons behind the lack of agreements reported in the literature. ASCs represent a heterogeneous cell population and the osteogenic potential of ASCs can be influenced by donor-related factors such as age, but also gender, lifestyle, and the underlying health and metabolic state of donors. Furthermore, future studies should consider experimental factors in in-vitro conditions, including passaging, cryopreservation, culture conditions, variations in differentiation protocols, and readout methods.

Hybrid scaffolds based on bioactive glass (BAG) particles (<38µm), covalently linked to the gelatin (G*), using 3-glycidoxypropyltrimethoxysilane (GPTMS), have been studied for bone bioengineering. In this study, two glass compositions (13-93 and 13-93B20 [where 20% of the SiO2 was replaced with B2O3]) were introduced in the gelatin matrix. The Cfactor (Gelatin/GPTMS molar ratio) was kept constant at 500. The hybrids obtained were found to be stable at 37°C, in solution; condition at which pure gelatin is liquid. All hybrids were characterized by in vitro dissolution in TRIS solution (for up to 4 weeks) and Simulated Body Fluid (SBF) (for up to 2 weeks). Samples processed with 13-93B20 exhibit a faster initial dissolution and significantly faster precipitation of a hydroxyapatite (HA) layer. The faster ion release and HA precipitation recorded from the G*/13-93B20 samples, is attributable to the higher reactivity of borosilicate compared to the silicate glass. MC3T3-E1 cells behavior, in direct contact with the hybrids, was investigated, showing that the cells were able to proliferate and spread on the developed biomaterials. Tailoring the glass composition allows to better control the material’s dissolution, biodegradability, and bioactivity. Bioactive (especially with 13-93B20 BAG), and biocompatible, the hybrids are promising for bone application.

In the software development process, the decision-maker (DM) has a range of problems inherent to its function. Wrong choices during software planning can bring great risk to the project. Therefore, the planning of software releases to be delivered to the customer should be well done. This is not an easy task because releases are made up of many requirements that contain complex variables that must be considered, such as precedence, cost, requirement stability, among other features that make the requirements-selection process challenging. To make this process less exhaustive, DM can use tools that facilitate this work. In software engineering, we can find fields of research specialists in this context, such as Search-Based Software Engineering (SBSE). The SBSE makes use of advanced metaheuristics to search for optimal solutions or the closest to it. In this work, we try to use another field of research to solve this same problem type, the Verbal Decision Analysis (VDA). To do this, we elaborate a workflow that will use the same source data, execute two solutions using the two search fields (SBSE and VDA) and compare the results. In the end, we evaluated and commented on the results.

The last two decades have witnessed a surge in investigations proposing stem cells as a promising strategy to treat stroke. Since growth factor release is considered as one of the most important aspects of cell-based therapy, stem cells over-expressing growth factors are hypothesized to yield higher levels of therapeutic efficiency. In pre-clinical studies of the last 15 years that were investigating the efficiency of stem cell therapy for stroke, a variety of stem cell types were genetically modified to over-express various factors. In this review we summarize the current knowledge on the therapeutic efficiency of stem cell-derived growth factors, encompassing techniques employed and time points to evaluate. In addition, we discuss several types of stem cells, including the recently developed model of epidermal neural crest stem cells, and genetically modified stem cells over-expressing specific factors, which could elevate the restorative potential of naive stem cells. The restorative potential is based on enhanced survival/differentiation potential of transplanted cells, apoptosis inhibition, infarct volume reduction, neovascularization or functional improvement. Since the majority of studies have focused on the short-term curative effects of genetically engineered stem cells, we emphasize the need to address their long-term impact.

Considering the dynamic stall effects in engineering calculations is essential for correcting the aerodynamic loads acting on wind turbines, both during power production and stand-still cases, and impacts significantly the turbine aeroelastic stability. The employed dynamic stall model needs to be accurate and robust for a wide range of airfoils and range of angle of attack. The present studies are intended to demonstrate the performance of a recently implemented "IAG dynamic stall" model in a wind turbine design tool Bladed. The model is transformed from the indicial type of formulation into a state-space representation. The new model is validated against measurement data and other dynamic stall models in Bladed for various flow conditions and airfoils. It is demonstrated that the new model is able to reproduce the measured dynamic polar accurately without airfoil specific parameter calibration and has a superior performance compared to other models in Bladed.

Cell free systems are a widely used research tool in systems and synthetic biology and a promising platform for manufacturing of proteins and chemicals. In the past, cell free biology was primarily used to better understand fundamental biochemical processes. Notably, E. coli cell free extracts were used in the 1960s to decipher the sequencing of the genetic code. Since then, the transcription and translation capabilities of cell free systems have been repeatedly optimized to improve energy efficiency and protein yield. Today, cell free systems, in combination with the rise of synthetic biology, have taken on a new role as a promising technology for just in time manufacturing of therapeutically important biologics and high-value small molecules. They have also been implemented in an industrial scale for the production of antibodies and cytokines. In this review, we discuss the evolution of cell free systems, advancements in cell free protein synthesis, and cell free metabolic engineering, and conclude with discussing the importance and feasibility of mathematical modeling in cell free systems.

The aim of performed studies was to fabricate an antibacterial and degradable scaffold that may be used in the field of skin regeneration. To reach the degradation criterion the biocompatible polyurethane (PUR), obtained by using amorphous macrodiol α,ω-dihydroxy(ethylene-butylene adipate) macrodiol (PEBA), was used and processed with so-called “fast-degradable” polymer polylactide (PLA) (5 wt% or 10 wt%). To meet the antibacterial requirement obtained hybrid PUR-PLA scaffolds (HPPS) were modified with ciprofloxacin (Cipro) (2 wt% or 5 wt%), the fluoroquinolone antibiotic inhibiting growth of bacteria such as Pseudomonas aeruginosa, Escherichia Coli and Staphylococcus aureus, which are main cause of wound infections. Obtained unmodified and Cipro-modified HPPS were studied towards their chemical composition to detect presence or absence of characteristic functional groups of PUR, PLA and Cipro, and as well to indicate the participation of hydrogen bonds in the HPPS structure in dependence on PLA addition and ciprofloxacin modification. Mechanical properties were studied to determine the possible application of HPPS as a skin tissue scaffold. Scanning electron microscopy (SEM) was used to study morphology of unmodified and Cipro-modified HPPS and to performed elementary analysis by using energy-dispersive x-ray spectroscopy (EDX) of obtained materials. Finally, the microbiological tests were performed to indicate the antibacterial effect of Cipro-modified HPPS on S.aureus growth. Performed studies showed that Cipro-modified HPPS, obtained by using 5 % of PLA, possess suitable mechanical characteristic, morphology, degradation rate and demanded antimicrobial properties to be further developed as a potential scaffolds for skin tissue engineering.

Over the past decade, studies have demonstrated the importance of bioactive metabolites derived from the microbiota in the regulation of physiological processes essential for homeostasis and the maintenance of human health. Strategies to modulate the production of these metabolites in the gastrointestinal tract hold promise for combating dysbiosis or inflammatory bowel disease. Metabolic engineering of probiotics could be one of these solutions. In this work, we engineered Escherichia coli Nissle 1917 (EcN) to overproduce spermidine, a metabolite known for its anti-immunosenescence and anti-inflammatory properties. Using a rational synthetic biology approach coupled with analysis by high resolution mass spectrometry, we designed in several steps and validated engineered probiotics overproducing and excreting spermidine. Based on our results, we first added the enzyme substrate putrescine and showed the overproduction of spermidine and decided to add a transporter limiting the production of the acetylated form of spermidine. Next, we used untargeted metabolomics to study the impact of engineering on the central metabolism of E. coli Nissle. Untargeted metabolomics appears to be a good strategy to optimize the metabolic engineering of probiotic strains and thus accelerate their development for personalized medicine.

Magnesium (Mg)-based biomaterials are promising candidates for bone and tissue regeneration. Alloying and surface modifications provide effective strategies for optimizing and tailoring their degradation kinetics. Nethertheless, biocompatibility analyses of Mg-based materials are challenging due to its special degradation mechanism with continous hydrogen release. In this context, the hydrogen release and the related (micro-) milieu conditions pretend to strictly follow in vitro standards based on ISO 10993-5/-12. Thus, special adaptions for the testing of Mg materials are necessary, which have been described in a previous study from our group. Based on these adaptions, further developments of a test procedure allowing rapid and effective in vitro cytocompatibility analyses of Mg-based materials based on ISO 10993-5/-12 are necessary. The following study introduces a new two-step test scheme for rapid and effective testing of Mg. Specimens with different surface characteristcis were produced by means of plasma electrolytic oxidation (PEO) using silicate-based and phosphate-based electrolytes. The test samples were evaluated for corrosion behavior, cytocompatibility and their mechanical and ostogenic properties. Thereby, two PEO ceramics could be identified for further in vivo evaluations.

The paper deals with the design of a systematic procedure for implementing strategy changes into internal business processes for a project-oriented production type of organization. In the first part of the contribution, a summary of the theoretical starting points for the field of strategic management and change management is presented. In the second part, the contribution deals with the analysis of the current situation in the area of the impact of the change of strategy on the management of business processes. In the last part, the proposal of the procedure for implementing strategy changes into internal business processes and the verification results are presented. The proposed procedure includes steps where the selection and verification of key performance indicators at individual levels of management plus the quantification of the impact of the change in strategy on the processes takes place. The management can thus monitor and evaluate the chosen processes in accordance with the fulfilment of the chosen strategy of the company. The last chapter presents the verification of the proposal for the systematic introduction of changes into the processes.

Genetic diversity is the foundation of evolutionary resilience, adaptive potential, and the flourishing vitality of living organisms, serving as the cornerstone for robust ecosystems and the continuous evolution of life on Earth. The landscape of directed evolution, a powerful biotechnological tool inspired by natural evolutionary processes, has undergone a transformative shift propelled by innovative strategies for generating genetic diversity. This shift is fuelled by several factors, encompassing the utilization of advanced toolkits like CRISPR-Cas and base editors, enhanced comprehension of biological mechanisms, cost-effective custom oligo pool synthesis, and the seamless integration of artificial intelligence and automation. This comprehensive review looks into the myriad methodologies employed for constructing gene libraries, both in vitro and in vivo, categorized into three major classes: random mutagenesis, focused mutagenesis, and DNA recombination. The objectives of this review are threefold: firstly, to present a panoramic overview of recent advances in genetic diversity creation, secondly, to inspire novel ideas for further innovation in the genetic diversity generation, and thirdly, to provide a valuable resource for individuals entering the field of directed evolution.

A frequent problem in Geotechnics is the soils with inadequate physical-mechanical properties before the efforts to which they will be subjected by the constructions, incurring cost overruns caused by their engineering improvement. The need to improve the engineering properties of soils is not recent, currently observing that the most common alternatives are binders such as cement and lime. The climate change observed in recent decades and the uncontrolled emission of greenhouse gases have motivated Geotechnical and Geoenvironmental researchers to seek mechanisms for soil reinforcement from a more sustainable and environmentally friendly approach by proposing the use of recycled and waste materials. An alternative is natural fibers, which can be obtained as waste from many agro-industrial processes, implying their high availability and low cost. Sawdust as a by-product of wood processing has a rough texture that can generate high friction between the fiber and the matrix of the soils, leading to a significant increase in its shearing strength and bearing capacity. This concept of improving the properties of soils using natural fibers distributed randomly is inspired by the natural phenomenon of grass and/or plants that when growing on a slope can effectively stabilize a said slope.

We show how the excitonic features of biaxial MoS₂ flakes are very sensitive to biaxial strain. We find a lower bound for the gauge factors of the A exciton and B exciton of (-41 ± 2) meV/% and (-45 ± 2) meV/% respectively, which are larger than those found for single-layer MoS₂. Interestingly, the interlayer exciton feature also shifts upon biaxial strain but with a gauge factor that is systematically larger than that found for the A exciton, (-48 ± 4) meV/%. We attribute this larger gauge factor for the interlayer exciton to the strain tunable van der Waals interaction due to the Poisson effect (the interlayer distance changes upon biaxial strain).

Hydrogen is useful as a fuel and could be produced by a variety of means. One approach uses artificial photosynthesis where energy from sunlight powers the splitting of water into hydrogen and oxygen. But, biological methods for producing hydrogen has emerged strongly over the past decades. In particular, specific microorganisms could use different substrates to produce hydrogen at differing yields. Such fundamental discoveries with industrial applications thus motivated the use of metabolic engineering approaches and methodologies in enhancing biological hydrogen production through a series of enzyme over-expression, pathway debottlenecking, and gene deletion. However, such approaches heavily rely on the selection of an appropriate microbial chassis for biohydrogen production. With the proper strain in hand, use of alternative substrates may engender greater hydrogen productivities. But learning from the bioprocessing field, co-culture of two compatible microorganisms have been sought after for improving biohydrogen production. In addition, thermophilic microbes may also be useful candidates for exploiting hydrogen production from composting. Future outlook in the field looks into filling our gaps in understanding of the metabolic network that feeds into hydrogen production in different organisms. But, more importantly, problems such as reduced growth rate in engineered microbes point to fundamental issues with using genetically engineered microorganisms for improved biohydrogen production, to which clever bioprocess engineering may yield solutions.

To solve the benefit allocation problem between the subjects of the supply chain of general contracting projects. The Cobb-Douglas function is applied to establish the benefit distribution model when the two cooperate in the supply chain system, analyze the optimal benefit situation of one-time cooperation between the two parties under two modes of egoistic decision and collectivistic decision as well as the benefit distribution problem of multiple cooperation, and conduct numerical simulation to calculate the functional relationship between each decision variable and the contribution degree of the general contractor under different effort cost coefficients. The results show that：In the case of one-time cooperation between general contractors and subcontractors, regardless of the decision mode, the degree of effort of both parties is positively related to their own contributions and negatively related to each other's contributions; the overall benefit of the supply chain system is positively proportional to the degree of contribution of the general contractor and inversely proportional to the share of benefit distribution of the subcontractor; in multiple cooperation, the equilibrium result of both parties achieving Pareto optimality at each stage is that both parties choose to cooperate.

The paper concerns with the identification of current communication technologies and software functionalities from the field of digitalization and Industry 4.0, from the point of view of benefits and applicability for the machine manufacturer. In order to identify the relevant technologies and functionalities, both a descriptive and statistical literature research was carried out. As a result, both the currently most widespread technologies and eleven IT functionalities relevant to mechanical engineers were identified and described in terms of their application and implementation. In addition, a knowledge gap in the area of industry transfer in the field of Industry 4.0 / Digitalization was identified

Amid global energy challenges, hydrogen evolution reaction (HER) is gaining traction for green hydrogen production. While catalyst research is ongoing, recognizing electrolyte effects remains crucial for sustainable hydrogen production via renewable-powered water electrolysis. This review delves into the intricate effects of electrolytes on the kinetics of HER. It examines key factors, including pH, cations, anions, impurities, and electrolyte concentration. It is discussed that electrolyte pH alters catalyst-electrolyte interactions and proton concentrations, thereby influencing factors such as hydrogen binding energy, water adsorption, and the overall reaction kinetics. Moreover, it is briefed that electrolyte cations, such as Li+, can impact HER positively or negatively, offering opportunities for improvement based on the metal substrate. Interestingly, there is a potential that HER can be tuned using Li+ ions to modify M-H bond energy, demonstrating flexibility beyond pH levels and counter ions. Varied adsorption energies of metal cations on metal electrodes are also found to influence HER kinetics. The effects of electrolyte anions and impurities are also discussed, emphasizing both positive and negative impacts on HER kinetics. Moreover, it is pointed out that the electrolyte engineering approach enhances the HER kinetics of both metal and carbon-based electrodes without permanent catalyst surface modifications. This review underscores the importance of electrolyte composition, highlighting both challenges and potential solutions in advancing HER research for sustainable energy production.

The increased complexity of modern systems is calling for an integrated and comprehensive approach to system design and development and in particular, a shift towards Model-Based Systems Engineering (MBSE) approaches for system design. The requirements that serve as the foundation for these intricate systems are still primarily expressed in Natural Language (NL), which can contain ambiguities and inconsistencies that hinder their direct translation into models. The colossal developments in the field of Natural Language Processing (NLP) in general and Large Language Models (LLMs) in particular can serve as an enabler for the conversion of NL requirements into semi-machine-readable requirements. This is expected to facilitate their standardization and use in a model-based environment. This paper discusses a two-fold strategy for converting NL requirements into semi-machine-readable requirements using language models. The first approach involves creating a requirements table by extracting information from free-form NL requirements. The second approach is an agile methodology that facilitates the identification of boilerplate templates for different types of requirements based on observed linguistic patterns. For this study, three different LLMs were utilized. Two of these models were fine-tuned versions of Bidirectional Encoder Representations from Transformers (BERT), specifically aeroBERT-NER and aeroBERT-Classifier, which were trained on annotated aerospace corpora. Another LLM, called flair/chunk-english, was utilized to identify sentence chunks present in NL requirements. All three language models were utilized together to achieve the standardization of requirements. To demonstrate the effectiveness of the methodologies, requirements from Parts 23 and 25 of Title 14 Code of Federal Regulations (CFRs) were employed, and a total of two, five, and three boilerplate templates were identified for design, functional, and performance requirements, respectively.

In the context of food packaging design, customization enhances the value of a product by meeting the needs of the consumer. Personalization is also linked to adaptation. This makes it possible to improve the properties of the packaging from various points of view: functional, aesthetic, economic and ecological. Currently the functional and formal properties of packaging are not investigated among themselves, however the study of both properties are the basis for creating a new concept of personalized and sustainable product. In accordance with this approach, the conceptual design procedure of packaging with personalized and adapted geometries based on the digitization of fresh food is proposed in this work. This study is based on the application of advanced technologies for the design and development of food packaging, in this case apples, in order to improve the quality of the packaging. The results obtained show that it is possible to use advanced technologies in the early stages of product design in order to obtain competitive products adapted to new emerging needs.

As a 21st century trend, sustainability has encompassed the entire world economy, including industry. Today the concept of "Industry 4.0" is known, resulting from advances in ICT (information and communication technologies). In recent years, companies in the metal materials industry have also implemented strategies and technologies belonging to the Industry 4.0 concept. The main purpose of the manuscript is to identify the key issues in the evolution of the development of the metal materials industry. The transition to a higher level of its evolution is based on two vectors, namely: the ecological paradigm, as a vector of in-depth knowledge, and sustainable material, as a vector that ensures sustainability in the areas of convergence of systems in the spheres of life and social consciousness. The systems that have an impact on the sustainable development of the metallic materials industry, through the interactions between them, are: the technological system, the social system and the natural-ecological system. Global knowledge re-quires the use of all inter and multidisciplinary knowledge, which ultimately contributes to the definition and characterization of new intersystem scientific branches: Ecometallurgy, Metallurgical Economics, Metallurgical Ecosociology and Sustainable Materials Engineering. The paper is considered a research study based on elements such as: literary foundations, using databases such as Web of Science (WoS), Scopus, Google Scholar, sustainable universal principles and legislative parameters.

The construction safety risks (such as landslides or slumps) of the high-fill subgrade are characterized by uncertainty and variability. In order to ensure the construction safety of the high-fill subgrade of the expressway, a comprehensive risk assessment model of high-fill subgrade construction according to the combination weighting method based on game theory was established. Firstly, settlement rate, lateral differential settlement, horizontal displacement at the foot of the slope, deep horizontal displacement, and excess pore pressure were selected as evaluation indicators, and an evaluation index system of high-fill subgrade was constructed. Secondly, the subjective and objective weights were obtained via the analytic hierarchy process and entropy method. Furthermore, the optimized weights were obtained by introducing game theory, and the construction risk of the high-fill subgrade was evaluated and analyzed using the fuzzy comprehensive evaluation method. Finally, based on the high-fill section of the Zhijiang-Tongren Expressway in Hunan Province (China), the evaluation model was validated through field measurement data. The results show that the safety scores obtained using the three methods of analytic hierarchy process, entropy method, and combination weighting method based on game theory are similar. The combination weighting evaluation model can correct the evaluation result error caused by a single weight and avoid information delay caused by the manual processing and analysis of monitoring data. The high-fill subgrade safety evaluation grade based on the combination weighting method and game theory is consistent with the engineering situation, and its fault tolerance range is within 20%. The evaluation model proposed in this study can scientifically and effectively evaluate the safety risks of high-fill subgrade construction, significantly improving the safety and reliability during the construction process.

Alkaloids are the most diversified nitrogen-containing secondary metabolites having antioxi-dant, and antimicrobial properties and are extensively used in pharmaceuticals to treat different types of cancer. Nicotiana serves as a reservoir of anticancer alkaloids and is also used as a model plant for the de novo synthesis of various anti-cancer molecules through genetic engineering. Up to 4% of the total dry weight of Nicotiana was found to be composed of alkaloids where nicotine, nornicotine, anatabine, and anabasine are reported as the dominant alkaloids. And, among the alkaloids present in Nicotiana, β-carboline (Harmane and Norharmane), Kynurenines are found to show anti-tumor effects, especially in the case of colon and breast cancer. Creating new or shunting of existing biosynthesis pathways in different species of Nicotiana resulted in de novo or increased synthesis of different anti-tumor molecules or their derivatives or precursors includ-ing Taxadiane (~22.5 µg/g), Artemisinin (~120 μg/g), Parthenolide (~2.05 ng/g), Costunolide (~60 ng/g), Etoposide (~1 mg/g), Crocin (~400 µg/g), Catharanthine (~60 ng/g), Tabersonine (~10 ng/g), Strictosidine (~0.23 mg/g), etc. Enrich precursor pool especially Dimethylallyl Diphos-phate (DMAPP) and down-regulating of other bi-product pathways, compartmentalization or metabolic shunting, or organelle-specific reconstitution of the precursor pool might trigger the enhanced accumulation of the targeted anticancer alkaloid in Nicotiana.

In bone tissue engineering, ceramics have been the choice due to their excellent biological properties. But the paradigm changed with the discovery of bioactive glasses (BGs) in 1969 by Larry Hench and co-workers, due to their ability to bond to living tissues through the formation of an interfacial bone-like hydroxyapatite layer when the bioglass was put in contact with biological fluids in vivo. Among a number of tested compositions, the one exhibiting the highest bioactivity index is the well-known trademarked 45S5 Bioglass®. The topic received increasing attention particularly after 1985 when this material entered in the market of biomedical devices, inspiring many other investigations aiming at further exploring the in vitro and in vivo performances of this BG, or developing other related BG compositions. The research efforts gradually revealed a number of shortcomings of 45S5 Bioglass®, mostly derived from its high sodium content, initially intended to decrease the melting temperature and accelerating the degradation of the silicate network over time. But the extensive release of sodium from 45S5 Bioglass® in the biological fluids creates a high pH cytotoxic environment. Other serious drawbacks include a fast degradation rate, and a poor sintering ability, which hinders the reliable fabrication of porous scaffolds. Therefore, sol-gel was regarded as an attractive alternative to prepare alkali-free BG compositions. The process uses inorganic and/or organic precursors, which undergo hydrolysis and condensation at room-temperature, being less costly. When properly conducted, the sol-gel process might result in amorphous structures with all the components intimately mixed at the atomic scale. Moreover, developing new better performing materials for bone tissue engineering is a growing concern, as the ageing of the world’s population leads to lower bone density and osteoporosis. This work describes the sol-gel synthesis of a novel quaternary silicate-based BG with the composition 60 SiO2 – 34 CaO – 4 MgO – 2 P2O5 (mol%) was prepared using acidified distilled water as single solvent. By controlling the kinetics of the hydrolysis and condensation steps, an amorphous glass structure could be obtained. The results of XRD of samples calcined within the temperature range from 600-900 ºC demonstrated that amorphous nature was maintained until 800 ºC, followed by partial crystallization at 900 ºC. The specific surface area, an important factor in osteoconduction, was also evaluated over different temperatures, ranging from 160.6 ± 0.8 m2/g at 600 ºC down to 2.2 ± 0.1 m2/g at 900 ºC, being accompanied consistent changes in average pore size and agreeing pore size distribution. The immersion of the BG particles in simulated body fluid (SBF) led to the formation of an extensive apatite layer on its surface. These overall results indicate the proposed material is very promising for biomedical applications in bone regeneration and tissue engineering.

Gastroparesis (GP) is associated with depletion of interstitial cells of Cajal (ICC) and enteric neurons, which leads to pyloric dysfunction followed by severe nausea, vomiting and delayed gastric-emptying. Regenerating these fundamental structures with stem cell therapy, would be helpful to restore gastric function in GP. Mesenchymal stem cells (MSC) have been successfully used in animal models of other gastrointestinal (GI) diseases including colitis. However, no study has been performed with these cells on GP animals. In this study, we explored if mouse MSC can be delivered from a hydrogel-scaffold to the luminal surfaces of GP mice stomach. Mouse MSC was seeded atop alginate-gelatin, coated with poly-L-lysine. These cell-gel constructs were placed atop stomach explants facing the luminal side. MSC grew uniformly all across the gel surface within 48 hr. When placed atop the lumen of the stomach, MSC migrated from the gels to the tissues as confirmed by positive staining with Vimentin and N-cadherin. The feasibility of transplanting a cell-gel construct to deliver stem cells in the stomach wall was successfully shown in a mice GP model, thereby making a significant advance towards envisioning the transplantation of an entire tissue-engineered ‘gastric patch’ or ‘microgels’ with stem cells, and growth factors.

The contemporary landscape of education is witnessing a paradigm shift towards innovative instructional methods, with the flipped learning approach gaining considerable attention. The purpose of this research was to investigate the impact of the flipped learning approach on students' perception and acceptance throughout an entire semester in the 'Introduction to Programming with Java' course, using a research design with a quantitative approach, ultimately aiming to inform educational practice and advance our knowledge of innovative teaching methods in higher education. This study was conducted at a university with 174 students involved, divided into two groups, 87 students in the experimental group and 87 students in the control group. The data collected through the scales were analyzed by using descriptive and inferential statistical analysis techniques in statistical software. At the end of the measurements, the technology acceptance level and self-directed learning perceptions of engineering students who received education with flipped learning were high. The results suggest that educators should consider students' readiness for self-directed learning when implementing the flipped learning approach and focus on creating an environment that supports their autonomy and engagement. This research offers valuable guidance for instructors, curriculum designers, and educational policymakers seeking to enhance the effectiveness of flipped learning in higher education courses.

Safety management assessment systems for national level units’ in South Korea focus on responding capacity to cope with impending accident occurrence and danger occurrence. Since the four stage systems for prevention-preparation-response-recovery, which are core elements of national disaster management, assess the capacities by item such as those of individuals, disaster management departments, institutions, and management networks, there is no assessment function for the organic operation states of the entire systems. Therefore, for efficient disaster management, systematic evaluation indices that will enable active pre-checks in departments in organizations should be developed in place of the existing simply checking methods. In this study, an assessment model that will enable active disaster management centered on practice was developed using resilience engineering techniques. This model consists of disaster management items from the viewpoint of proactive responses instead of prevention. A total of 56 items that constitute four capacities; which are prediction (13 items), monitoring (14 items), proactive response (15 items), and safety learning (14 items) capacities were adopted in this model through Delphi analysis. Institutional capacities for infectious disease disaster management were evaluated based on this model and the resultant scores were prediction 4.41, monitoring 4.63, proactive response 4.69, safety learning 4.56 out of the full score of 5.0 points with an overall average of 4.51. This is an excellent capacity management score comparable to the score 4.57 of diagnosis of similar capacities by the WHO\_JEE (The Joint External Evaluation) in 2017. In fact, in 2015, when infectious disease capacity management was poor, in case of MERS (Middle East Respiratory Syndrome) infectious disease spread in South Korea, 36 patients died and 6,729 patients were isolated. However, through capacity reinforcement, in the case of MERS occurrence in South Korea in September 2018, a management capacity that prevented spread was shown as one confirmed case was completely cured in 10 days and 21 contacts were isolated and tested negative. Therefore, this capacity management assessment model is judged to be usable in enhancing disaster response and management capacities.

In recent years, the class of metal-organic framework (MOF) materials emerged. These materials' unique properties can be assigned to their structure, containing inorganic nodes connected with organic linkers. Due to their porosity and flexibility, MOFs have become suitable for various energy-related applications, including gas storage, hydrogen production and heterogeneous catalysis, and photocatalysis. Using DFT+U calculations, we show that the substitution of metal centers in inorganic nodes and the strain engineering of UiO-66 alters the electronic and optical properties of this material. We show that applying mechanical strain on UiO-66 enables the control of absorption coefficient in the UV-Vis spectrum and the photocatalytic processes' selectivity when reactants for several photocatalytic processes are present. The presented findings could lead to general strategies for designing novel MOFs for sustainable energy conversion applications.

In his Cynefin classification of system behaviours, Snowden (2007), posits that his Simple (Clear ) and even Complicated system categories are sufficiently understandable to be amenable to the traditional methods of system analysis and modelling. Here, relationships between entities in the system are clear and unambiguous and they behave predictably. So, we can build mathematical “models” to describe how the system is expected to function in different situations. Leaving aside his fourth category, Chaotic, as too hard for the moment, this paper focusses on the third category, Complex systems. Yaneer Bar-Yam [1998] defined "complex systems" as systems that "have multiple interacting components, whose collective behaviour cannot be simply inferred from the behaviour of components." So, the traditional system modelling approach of decomposition into components and attempting to build up a picture of system performance from individual pieces, alone, is no longer appropriate for this class. The problem is that most of the methods we currently employ, and particularly the methods that attempt to make the case that these systems are safe, (such as Fault trees, FMEA. and Root Cause Analysis), rely on this decomposition into components and attempt to make the parts more reliable individually. Even the more systemic approaches, such as Reason’s (1990) Swiss Cheese Model, and Leveson’s System Theoretic Analysis (STPA) (2004), encourage adding layers of protection, barriers, strengthened control loops and better safety critical systems, in the hope that they are making the systems safer. But without a valid model to test the effectiveness of these add-ons, we cannot be sure that they will not have an opposite effect, of making the systems even more complex, unreliable and unpredictable. For complex systems, the careful gathering and documentation of system components and their relationships is still a necessary first step, but we need an additional capacity to model these complex systems to test out and prove they work safely and successfully in the real world. (not just draw fixed component relationships as system “models” (wiring diagrams)) In the last 10 years, an original approach developed by Hollnagel, (2012), to model systems as sets of interactive, interdependent “functions”, (abstracted from and independent of component details), has now been developed to the point where it can take the basic data and structures from the current component focussed system engineering “models”, such as MBSE( Goldberg (1994)), and can pull it all together in a dynamic system model from which analysts can discern how it really works in practice, and predict the emergent behaviours characteristic of complex systems. The paper describes how this methodology developed and how it is currently used to model real situations, to analyse incidents and anticipate events.

The following are three successful case studies that affected humanity during the COVID-19 pandemic. The key to their success was their swift adaptability to the new confinement regulations and the unyielding determination of those carrying out their plans. Various extraordinary and prompt efforts were required to make the essential logistical preparations and practice for distance learning a reality. The research activities were also reorganized so the thesis students might carry out a few simple experiments at home under the strict supervision of their advisers and supervisors. The findings revealed that the students who participated in these projects applied all the abilities they had gained before the epidemic. In addition, they included crucial knowledge about the project, problem-based, and research-based learning. Furthermore, because they were the primary implementers of the trials, they learned by planning and performing experiments. The culmination of these efforts was displayed in three scientific publications that were published in index journals with a high level of impact. This latter factor is essential for the prestige and visibility of the university, in addition to the acquisition of financing and grants for scientific research.

Critical sized bone defects and articular cartilage injuries resulting from trauma, osteonecrosis or age-related degeneration are often nonhealing by the physiological repairing mechanisms, thus representing a clinic issue due to the relevant epidemiological incidence. Current treatment approaches consist of autologous or allogenic grafting, which are associated with painfulness, morbidity, risk of infections and rejection. Novel tissue-engineering approaches, aiming at the reconstruction of damaged tissues, have been proposed as alternative solutions to these conven-tional methods. These approaches are based on the combination of three fundamental compo-nents: autologous or allogenic cells, a scaffold and growth-stimulating signals, which are gener-ally referred to as the tissue engineering triad. Three-dimensional polymer networks are fre-quently used as scaffolds to allow cell proliferation and tissue regeneration. In this scenario, cryogels are giving promising results as cell scaffolds over other polymer networks, thanks to their peculiar properties. In particular, cryogels possess an interconnected porous structure and a typical sponge-like behaviour, which facilitate the cellular infiltration and ingrowth. Their properties can be appropriately adjusted to match the requirements of the specific tissue or or-gan that it is intended to regenerate. In this review it is reported the state of the art on the fabri-cation and employment of cryogels in supporting osteo or chondro-genic differentiation for the re-building of more organized tissues. Moreover, it will highlight current progress and future perspectives in the implementation of this technology in the clinical practice.

This research examines the impact of social equity on energy consumption. We constructed a digital twin for residential energy consumption by enriching the synthetic population with real-world surveys and feeding them with other environmental and appliance data to the energy modeling framework. We analyzed household hourly energy consumption data from Albemarle County and Charlottesville City in Virginia, USA, for the year 2019. We used clustering analysis to identify patterns in social equity and energy consumption. The results demonstrated the impact of different residential attributes on energy poverty. Statistical analyses, including ANOVA and Chi-Squared tests, were conducted to test for significant differences between racial groups in quantitative and categorical variables. The study found that race is significant in determining the location and quality of housing. People of color often live in areas with higher pollution and less access to green spaces. Additionally, income levels and the age of the house are influential factors in determining energy efficiency. Future work should focus on collecting and analyzing data at the country level and using qualitative data collection methods to gain a more comprehensive understanding of social equity issues concerning energy consumption. Overall, this study provides valuable insights into the relationship between different residential attributes and energy consumption, which can inform policy development to promote more equitable and sustainable communities.

This research paper describes the social engineering concepts, techniques, and security countermeasures. This research aims to study various social engineering techniques to find the best countermeasures that would help to reduce social engineering attacks.

We set a feasible method to produce tailored collagen scaffolds and analyzed its potential for corneal engineering. Collagen-vitrigel membranes (CVM) were produced with a 1:1 ratio of Dulbecco’s Modified Eagle’s medium (DMEM), 1% antibiotics and 8% fetal bovine serum, and 5mg/mL collagen type I. Three volumes of collagen were used: 1X (2.8 L/mm2 of collagen), 2X, and 3X. Vitrification was done at 40% relative humidity (RH), 40° C, and 30 rpm using a matryoshka system set with a shaking-oven and a desiccator with a saturated K2CO3 solution. The CVM was characterized for width, microstructure, transparency, and biocompatibility using NIH3T3 cells. Surgical manipulation was assessed in an ex vivo corneal model. Constructs of corneal endothelial cells (CECs) and 2X-CVM were transplanted into five 18-month-old White New Zealand rabbits. CVM exhibited homogeneous surface and laminar organization. Membrane width increased with gel volume from 3.65µm to 7.2µm. 1X and 2X-CVM exhibited a 99% transmittance. NIH3T3 cells concentration increased 3-fold within 48 h with no significant difference among the 3 CVM (p = 0.323). The 2X-CVM was surgically manipulable. Transplantation of corneal endothelial cells (CECs) seeded over 2X-CVM restored corneal endothelium. The matrioshka system is a feasible method that yields CVM suitable for corneal engineering.

As consequence of the digital transformation, e-learning methodologies have become an inseparable part of the standard classes in schools and universities, assuming an increasingly significant role in compensating for the difficulties resulting from the COVID-19 pandemic. Numerous pedagogical methodologies and strategies can be easily implemented in high education, promoting students’ motivation and interest in learning. This research study analyses the implementation of gamification pedagogical strategy on 50-60 undergraduate chemical engineering students at the university, by evaluating its effect on the success rate on a specific topic of Chemical Reactions Engineering subject and the motivation effect for the following topics. Our results show a significant positive effect of the gamification strategy on university lectures, increasing up to 25-30 % of the success ratio with an apparent motivation effect. During the subsequent years, the changes in the lifestyle of study also play a role in students’ performance. Therefore, it is necessary to evaluate case studies such as the one presented here to understand better the use of these pedagogical methods and strategies in high education, especially in technical subjects described in this paper.

There is need to address the challenges of organ shortage, through development of tissues and organs with alternatives to those of the allograft-kind. This illustrates the quest behind novel biofabrication strategies such as 3D bio-printing, which is necessary to create artificial multi-cellular tissues/organs. Several findings have been reported in this review. First, the role of ECM components in tissue regenerative medicine is presented. Different ECM components such as collagen, gelatin, elastin, fibronectin, laminins and glycosaminoglycans are concisely examined for their tissue regenerative medicine applications. Next, current state of research on extrusion-based 3D bio-printing techniques and their limitations are reviewed. For example, we show that cell viability is still a challenge with extrusion, while the use of natural polymers such as collagen in improving composites’ mechanical properties is limited. Lastly, we examine unresolved research questions necessary to advance the present state of research in the field.

The national study analyzes sea level rise (SLR) impacts based on 36 different SLR and storm surge scenarios across 5.7 million geographic locations and 3 time periods. Taking an approach based on engineering design guidelines and current cost estimates, the study details projected cost impacts for states, counties, and cities. These impacts are presented from multiple perspectives including total cost, cost per-capita, and cost per-square mile. The purpose of the study is to identify specific locations where infrastructure is vulnerable to rising sea levels. The study finds that Sea Level Rise (SLR) and minimal storm surge is a $400 billion threat to the United States by 2040 that includes a need for at least 50,000 miles of protective barriers. The research is limited in its scope to protecting coastal infrastructure with sea walls. Additional methods exist and may be appropriate in individual situations. The study is original in that it is a national effort to identify infrastructure that is vulnerable as well as the cost associated with protecting this infrastructure.

Inteins are prevalent among extremophiles. Mini-inteins with robust splicing properties are of particular interest for biotechnological applications due to their small size. However, biochemical and structural characterization has still been limited to a small number of inteins, and only a few inteins serve as widely used tools in protein engineering approaches. We determined the crystal structure of a naturally-occurring Pol-II mini-intein from Pyrococcus horikoshii and compared it with two other natural mini-inteins from Pyrococcus horikoshii. Despite the similar sizes, the comparison revealed distinct differences in insertions and deletions, implying specific evolutionary pathways from distinct ancestral origins. Our studies suggest that sporadically distributed mini-inteins might be more promising for further protein engineering applications than the highly conserved mini-inteins. Structural investigations of more inteins could guide the shortest path to finding novel robust mini-inteins suitable for protein engineering purposes.

Innovative tissue engineering biomimetic hydrogels based on hydrophilic polymers have been investigated for their physical and mechanical properties. 5% to 25% by volume loading PHEMA-nanosilica glassy hybrid samples were equilibrated at 37°C in aqueous physiological isotonic and hypotonic saline solutions (0.15 and 0.05 M NaCl) simulating two limiting possible compositions of physiological extracellular fluids. The glassy and hydrated hybrid materials were characterized both for dynamo-mechanical properties and equilibrium absorptions in the two physiological-like aqueous solutions. Mechanical and the morphological modifications occurring in the samples have been described. The 5% volume nanosilica loading hybrid nanocomposite composition showed mechanical characteristics in the dry and hydrated states that were comparable to those of cortical bone and articular cartilage, respectively, and then chosen for further sorption kinetics characterization. Sorption and swelling kinetics were monitored up to equilibrium. Changes in water activities and osmotic pressures in the water-hybrid systems equilibrated at the two limiting solute molarities of the physiological solutions have been related to the observed anomalous sorption modes using the Flory-Huggins interaction parameter approach. The bulk modulus of the dry and glassy PHEMA-5% nanosilica hybrid at 37°C has been observed to be comparable with the values of the osmotic pressures generated from the sorption of isotonic and hypotonic solutions. The anomalous sorption modes and swelling rates are coherent with the difference between osmotic swelling pressures and hybrid glassy nano-composite bulk modulus: the lower the differences the higher the swelling rate and equilibrium solution uptakes. Bone tissue engineering benefits of use of tuneable biomimetic scaffold biomaterials that can be “designed” to act as biocompatible and biomechanically active hybrid interfaces are discussed.

Ustilago maydis, member of the Ustilaginaceae family, is a promising host for the production of several metabolites including itaconic acid. This dicarboxylate has great potential as a bio-based building block in the polymer industry, and is of special interest for pharmaceutical applications. Several itaconate overproducing Ustilago strains have been generated by metabolic and morphology engineering. This yielded stabilized unicellular morphology through fuz7 deletion, reduction of by-product formation through deletion of genes responsible for itaconate oxidation and (glyco)lipid production, and the overexpression of the regulator of the itaconate cluster ria1 and the mitochondrial tricarboxylate transporter encoded by mttA from Aspergillus terreus. In this study, itaconate production was further optimized by consolidating these different optimizations into one strain. The combined modifications resulted in itaconic acid production at theoretical maximal yield, which was achieved under biotechnologically relevant fed-batch fermentations with continuous feed.

A novel software engineering platform called the Dynamic Nuchwezi Architecture Platform (DNAP) is introduced, specified and its novelties explained. The unique features of this platform are explained and several new concepts and abstractions upon which its implementation, usage, and analysis are hinged also elaborately discussed. The motivations for this new approach to building especially tools used in data engineering are spelled out and the platform is contrasted against other existing technologies of a similar kind. Finally, it is shown what known limitations DNAP suffers, as well as what room for further research and improvement there is in this field.

We show that an experimentally plausible system consisting of a modulated wire medium hosted in a metal cavity can preserve the longitudinal field profile shaping predicted by Boyd et al. (2018) on the basis of a perfectly periodic wire-only structure. These new frequency domain numerical results are a significant step towards justifying the construction of an experimental apparatus to test the field profile shaping in practise.

Vehicle driveability is one of the important vehicle attributes in range-extender electric vehicles due to the electric motor torque characteristics at low-speed events. The process of validating and rectifying vehicle driveability attributes is typically utilised by a physical vehicle prototype that can be expensive and required several design iterations. In this paper, a model-based energy method to assess vehicle driveability is presented based on a high-fidelity 49 degree-of-freedom powertrain and vehicle systems. Multibody dynamics components were built according to their true centre of gravity relative to the vehicle datum for providing an accurate system interaction. The work covered a frequency at less than 20 Hz. The results that consisted of the component frequency domination are structured and examined to identify the low-frequency sensitivity based on different operating parameters such as a road surface coefficient. An energy path technique was also implemented on the dominant component by decoupling its compliances to study the effect on the vehicle driveability and low-frequency response. The outcomes of the research provided a good understanding of the interaction across the sub-systems levels. The powertrain rubber mounts were the dominant components that controlled the low-frequency contents (< 15.33 Hz) and can change the vehicle driveability quality.

Well deliverability optimization is essential for oil and gas production and nodal analysis is a common tool used for selecting suitable production parameters. To accurately calculate upstream and downstream pressures at various production rates at a certain selected node, proper modeling of multiphase flow in wellbores is necessary. However, this process is complex due to the inconsistent velocities of the fluids (i.e., oil, gas, and water) and the interaction between the liquids under high temperature and pressure. Empirical models, such as Hagedorn and Brown (1965), Beggs and Brill (1973), and Mukherjee and Brill (1983 and 1985), and the drift-flux model (Zuber 1965) are commonly used for multiphase flow calculations in wellbores. In this paper, we programmed and evaluated three multiphase flow models (Hagedorn-Brown, Mukherjee-Brill, and drift-flux) using Matlab. The programming includes holdup calculation, pressure gradient calculation, pressure traverse calculation, inflow curve determination, inflow performance relationship (IPR) curve determination, and well deliverability determination. Additionally, we conducted a case study to examine the sensitivity of parameters and compare and analyze the results of pressure traverse, tubing intake curve, and deliverability determination between the drift-flux and Mukherjee-Brill models. Sensitivity analysis was conducted on two of the seven parameters in the drift-flux model, and the effects of production and reservoir parameters on well deliverability were analyzed. The case study results indicated that the Mukherjee-Brill model predicted slightly higher bottomhole pressure compared to the drift-flux model at a fixed oil flow rate, but its well deliverability determination was lower. Furthermore, the drift-flux model showed that the pressure increased with an increase in the distribution coefficient for bubble flow (C0_bubble), while the beta parameter had little impact on the calculated pressure in the studied range. The well deliverability increased when the tubing size and reservoir pressure increased, or the tubing head pressure decreased.

The world of science is drowned in a wealth of information. How to make sense of this wealth of published articles, blog posts and abstracts has become an important challenge given the importance of science to different aspects of societal function. At the crux of the issue lies the increasing trend where scientific discovery informs decision making at the societal level. One example, is the elucidation of the ozone hole to the promulgation of the Montreal Protocol in 1987, and documenting increasing atmospheric carbon dioxide concentration led to climate action and signing of the Paris Agreement in 2015. Hence, understanding a research field becomes an important need for many decision makers across different sectors of society. But, the scientific literature is cryptic and esoteric, and presents a significant barrier to comprehension. One approach to ameliorate the problem is statistical machine reading, which provides the critical capability of identifying key concepts that underpins a research field. Such important concepts help provide an incision point to gain further understanding of the field and initiating further conversation about the field. This work sought to validate the concept of whether applying statistical machine reading to a body of literature comprising short blog posts and abstracts of published articles help in understanding the field of metabolic engineering. One important angle pursued in this research is whether the tabulated list of terms and phrases identified by statistical machine reading could be creatively analyzed to gain a deeper understanding of the research field. For example, the most frequently occurring terms and phrases could describe key concepts of the research field. Moving down in frequency occurrence would be terms and phrases that describe methodologies and approaches of the field. Finally, less frequently occurring terms and phrases may be tools and resources used in the research field. Results validated the utility of statistical machine reading in identifying important terms and phrases associated with the research field. But the small dataset of blog posts and abstracts used in this study severely hampered the identification of most of the key concepts of metabolic engineering, which is a fairly broad field of research. Overall, statistical machine reading shows utility in identifying terms and phrases that could describe a field. However, the level of understanding is closely tied in to the breadth and depth of reading material available, which meant that the methodology is data intensive in nature. Future use of supercomputing or quantum computing could help alleviate constraints of computational capacity, and help tackle the exponential rise in computational complexity as the size of the reading material for machine reading expands.

The target of an antibody plays a significant role in the success of antibody-based therapeutics and diagnostics, and to an extent, that of vaccine development. This importance is focussed on the target binding site – epitope, where epitope selection as a part of design thinking beyond traditional antigen selection using whole cell or whole protein immunisation can positively impact success. With purified recombinant protein production and peptide synthesis to display limited/selected epitopes, intrinsic factors that can affect the functioning of resulting antibodies can be more easily selected for. Many of these factors stem from the location of the epitope that can affect accessibility of the antibody to the epitope at a cellular or molecular level, direct inhibition of target antigen activity, conservation of function despite escape mutations, and even non-competitive inhibition sites. Through the incorporation of novel computational methods for predicting antigen changes to model-informed drug discovery and development, superior vaccines and antibody-based therapeutics or diagnostics can now be more easily designed to mitigate failures. With detailed examples, this review highlights the new opportunities, factors and methods of predicting antigenic changes for consideration in sagacious epitope selection.

Requirements are predominantly written in Natural Language (NL), which makes them accessible to stakeholders with varying degrees of experience, as compared to a model-based language which requires special training. However, despite its benefits, NL can introduce ambiguities and inconsistencies in requirements, which may eventually result in system quality degradation and system failure altogether. The system complexity that characterizes current systems warrants an integrated and comprehensive approach to system design and development. This need has brought about a paradigm shift towards Model-Based Systems Engineering (MBSE) approaches to system design and a departure from traditional document-centric methods. While, MBSE shows great promise, the ambiguities and inconsistencies present in NL requirements hinder their conversion to models directly. The field of Natural Language Processing (NLP) has demonstrated great potential in facilitating the conversion of NL requirements into a semi-machine-readable format that enables their standardization and use in a model-based environment. A first step towards standardizing requirements consists of classifying them according to the ``type'' (design, functional, performance, etc.) they represent. To that end, a language model capable of classifying requirements needs to be fine-tuned on labeled aerospace requirements. This paper presents the development of an annotated aerospace requirements corpus and its use to fine-tune BERT$_\text{BASE-UNCASED}$ to obtain aeroBERT-Classifier: a new language model for classifying aerospace requirements into design, functional, or performance requirements. A comparison between aeroBERT-Classifier and bart-large-mnli (zero-shot text classification) showcased the superior performance of aeroBERT-Classifier on classifying aerospace requirements despite being fine-tuned on a small labeled dataset.

CRISPR-Cas allows us to introduce desired genome editing, including mutations, epitopes, and deletions with unprecedented efficiency. The development of CRISPR-Cas has progressed to such an extent that it is now applicable in various fields with the help of model organisms. C. elegans is one of the pioneering animals in which numerous CRISPR-Cas strategies have been rapidly es-tablished over the past decade. Ironically, the emergence of numerous methods makes the right choice of method difficult. Choosing an appropriate selection or screening approach is the first step in planning a genome modification. This report summarizes the key features and applications of CRISPR-Cas methods using C. elegans and illustrates key strategies. Our overview of significant advances in CRISPR-Cas will help readers to understand current advances in genome editing and navigate various methods of CRISPR-Cas genome editing.

Multiple sclerosis is an autoinflammatory condition that results in damage of myelinated neurons in affected patients. While disease-modifying treatments have been successful in slowing the progression of relapsing remittent disease, most patients still progress to secondary progressive disease that is largely unresponsive to disease-modifying treatments. Similarly, there is currently no effective treatment for patients with primary progressive MS. Innate and adaptive immune cells in the CNS play a critical role in initiating an autoimmune attack and in maintaining the chronic inflammation that drives disease progression. In this review, we will focus on recent insights into the role of T cells with regulatory function in suppressing the progression of MS, and, more importantly, in promoting the remyelination and repair of MS lesions in the CNS. We will discuss the exciting opportunity to genetically reprogram regulatory T cells to achieve immune suppression and enhance repair locally at sites of tissue damage, while retaining a fully competent immune system outside the CNS. In the future, reprogramed regulatory T cells with defined specificity and function may provide life medicines that can persist in patients and achieve lasting disease suppression after one cycle of treatment.

Thermoplastic molded regenerated silk was proposed as structural material in tissue engineering applications, mainly for application in bone. The protocol allows to obtain a compact non-porous material with a compression modulus in the order of a Giga Pascal starting from silk fibroin by compressing a silk fibroin lyophilized sponge of powder in mold at temperature higher than the glass transition temperature (Tg). The main purpose of the produced resin was the osteofixation and other structural applications in which the lack of porosity was not an issue. In this work, we introduced the use of citric acid in the thermoplastic molding protocol of SF to obtain a porosity inside the structural material. In addition to the previously developed protocols the addition of citric acid allowed us to obtain a structural material. The CA powder during the compression acted as a template for the pore formation. In addition, the CA was able to effectively crosslink the SF chain improving the mechanical strength. This effect was proved both evaluating the compression modulus and by studying the spectra obtained by Fourier infrared spectroscopy (FTIR). This protocol may be applied in the near future to the production of a structural bone scaffold.

In this study, we demonstrate how the incorporation of appropriate feature engineering together with the selection of a Machine Learning (ML) algorithm that best suits the available dataset, leads to the development of a predictive model for transformation temperatures that can be applied to a wide range of shape memory alloys. We develop a gradient boosting ML surrogate model capable of predicting Martensite Start, Martensite Finish, Austenite Start, and Austenite Finish transformation temperatures with an average accuracy of more than 95% by explicitly taking care of potential distribution changes when modeling different alloy systems. We included heat treatment, rolling, extrusion processing parameters, and alloy system categorical features in the model input features to achieve more accurate and realistic results. In addition, using Shapley values, which are calculated based on the average marginal contribution of features to all possible coalitions, this study was able to gain insights into the governing features and their effect on predicted transformation temperatures, providing a unique opportunity to examine the critical parameters and features in martensite transformation temperatures.

In recent decades, porous scaffolds for bone tissue engineering (BTE) have gained significant attention. Considerable research efforts have been dedicated to investigating the impact of scaffold pore size on a diverse array of biological processes, including cell-scaffold interactions, substance transportation, and vascularization. However, the multi-scale hierarchical porosity, a key structural characteristic of natural bone, has rarely been replicated in BTE scaffolds due to the challenges of controlling the scaffold structure across multiple length scales. With the advancement of manufacturing technology, there has been increasing research on biomimetic multi-scale hierarchical materials, which are also gaining favor in the field of BTE. Therefore, there is an urgent need to review multi-scale hierarchical porous BTE scaffolds. This paper aims to review the role and fabrication methods of multi-scale porous BTE scaffolds at different length scales, the design and manufacturing of new BTE scaffolds for bone regeneration.

In this research, we present a comprehensive methodology to categorize perfumes based on their fragrance profiles and subsequently aid in creating innovative odoriferous molecules using advanced neural networks. Drawing from data on Parfumo and the Good Scents Company webpage (Parfumo, 2008; The Good Scents Company, 2021), the study employs sophisticated web scraping techniques to gather diverse perfume attributes. Following this, a k-means algorithm is applied for perfume clustering, paving the way for recommending similar scents to consumers. The process then bridges customer preferences to molecular design by incorporating their feedback into generating new molecules via graph neural networks (GNNs). Through converting the Simple Molecular Input Line Entry System (SMILES) representation into graph structures, the GNN facilitates the creation of new molecular designs attuned to consumer desires. The proposed approach offers promising avenues for consumers to pinpoint similar perfume choices, incorporating feedback, and for manufacturers to conceptualize new fragrant molecules with a high likelihood of market resonance.

Porous tantalum (Ta) is a promising biomaterial and has been applied in orthopedics and dentistry for nearly two decades. The high porosity and interconnected pore structure of porous Ta promise fine bone ingrowth and new bone formation within the inner space, which further guarantee rapid osteointegration and bone-implant stability in long term. Porous Ta has high wettability and surface energy that can facilitate adherence, proliferation and mineralization of osteoblasts. Meanwhile, low elastic modulus and high friction coefficient of porous Ta can effectively avoid stress shield effect, minimize marginal bone loss and ensure primary stability. Accordingly, the satisfactory clinical application of porous Ta based implants or prostheses are mainly derived from its excellent biological and mechanical properties. With the advent of additive manufacturing, personalized porous Ta based implants or prostheses have shown their clinical value in the treatment of individual patient who need specially designed implant or prosthesis. In addition, many modification methods have been introduced to enhance the bioactivity and antibacterial property of porous Ta with promising in vitro and in vivo research results. In any case, choosing suitable patients is of great importance to guarantee surgical success after porous Ta insertion.

Hydrogen peroxide is an important chemical of increasing demand in today’s world. Currently, the anthraquinone autoxidation process dominates the industrial production of hydrogen peroxide. Herein, hydrogen and oxygen are reacted indirectly in the presence of quinones to yield hydrogen peroxide. Owing to the complexity and multi-step nature of the process, it is advantageous to replace the process with an easier and straightforward one. The direct synthesis of hydrogen peroxide from its constituent reagents is an effective and clean route to achieve this goal. Factors such as water formation due to thermodynamics, explosion risk, and the stability of the hydrogen peroxide produced hinder the applicability of this process at an industrial level. Currently, the catalysis for the direct synthesis reaction is palladium based and the research into finding an effective and active catalyst has been ongoing for more than a century now. Palladium in its pure form, or alloyed with certain metals are some of the new generation of catalysts that are extensively researched. Additionally, to prevent the decomposition of hydrogen peroxide to water, the process is stabilised by adding certain promoters such as mineral acids and halides. A major part of today’s research in this field focusses on the reactor and the mode of operation required for synthesising hydrogen peroxide. The emergence of microreactor technology has helped in setting up this synthesis in a continuous mode, which could possibly replace the anthraquinone process in the near future. This review will focus on the recent findings of the scientific community in terms of reaction engineering, catalyst and reactor design in the direct synthesis of hydrogen peroxide.

High porosity and mass transport properties of microfiltration polymeric membranes benefits nutrients supply to cells when used as scaffolds in interstitial perfusion bioreactors for tissue engineering. High nutrients transport is assumed when pore size and porosity of the membrane are in the micrometric range. The present work demonstrates that the study of membrane fouling by proteins present in the culture medium, though not done usually, should be included in the routine testing of new polymer membranes for this intended application. Two poly(ε-caprolactone) microfiltration membranes presenting similar average pore size (~0.7µm) and porosity (>80%) but different external surface porosity and pore size have been selected as case study. The present work demonstrates that a membrane with lower surface pore abundance and smaller external pore size (~0.67 µm), combined with adequate hydrodynamics and tangential flow filtration mode is usually more convenient to guarantee high flux of nutrients. On the contrary, having large external pore size (~1.70µm) and surface porosity would incur in important internal protein fouling that could not been prevented with the operation mode and hydrodynamics of the perfusion system. Additionally, the use of glycerol in the drying protocols of the membranes might cause plasticization and a consequent reduction of mass transport properties due to membrane compaction by the pressure exerted to force perfusion. Therefore, preferentially, drying protocols that omit the use of plasticizing agents are recommended.

The dynamic development of electromobility poses challenges to designers regarding not only the efficiency of energy transformation but also the battery life, which is influenced by the stability of its operating temperature. Designing cooling systems is connected not only with the optimization of energy management but also with other environmental parameters, such as noise emission. The paper presents the numerical optimization of an innovative radiator for use in electric buses in terms of energy consumption and noise emission. The results of the numerical studies were verified in laboratory and field conditions, showing a very good convergence of the model with the results of the experiments.

The swift progress in low-dimensional nanocarbons, specifically in the realm of the authentic one-dimensional carbon chain featuring sp¹ hybridization, has unveiled exciting prospects for integrating them into cutting-edge technologies across diverse industries. To fully harness their potential, precise control over the growth process is necessary to obtain desired nanostructure and functionality. However, optimizing properties through traditional approaches has been challenging due to complex interactions. To address this, we implement a focused data-driven strategy for nanocarbon inverse design by leveraging a state-of-the-art data-driven nanocarbon genome approach (NCGA). By uncovering relationships between growth parameters and resultant traits, this serves as an expedient catalyst in engineering nanostructures with tailored attributes. We introduce an extensive array of technological approaches aimed at precisely controlling the growth process. These methods encompass stimulating and precisely adjusting synergistic effects, coordinating atomic vibrations at a collective level through the implementation of multilayer nano-interfaces, harnessing the potential of active screen plasma surface engineering, utilizing nano-patterning and allotropic phase transformations, incorporating heteroatom doping, and effectively directing self-assembly. These aim to unlock nanomaterials' latent potential and reveal novel neural pathways within the data-driven NCGA, enhancing its predictive capabilities. Specifically, triggering self-organization during growth can potentially unlock previously unexplored neural pathways. The data-driven NCGA offers a paradigm shift, accelerating discovery and design of nanocarbons with optimized, application-specific properties.