The Power Theory of Exchange and Money (PTEM) refines the economic neoclassical two-equation model of exchange. PTEM replaces the statistical average condition of exchange, which represents the equality of supply and demand for all transactions in the market, with a more specific equation of the equality of the generalized power of the parties in relation to their objects of exchange. The purpose of the article is to show the application of PTEM for the study of various social phenomena. Along with a brief summary of the main statements of this theory, its integration into the existing corpus of theories and ideas in economics and sociology is considered. The conclusions of power theory are then applied to consider the following topics: the objective motivation of exchange by the desire to increase power, the power nature of market equilibrium, the power nature of money, the accumulation of power through profit, the creation of money as a power act, the role of the state in the creation of money, the measure of power as a possible tool for social and political research.

Modern exchange theories model a large market, but do not explain single exchange. The paper considers the phenomenon of single exchange and formulates the general exchange problem in the form of a system of two equations, subjective and objective. Subjective equilibrium is given by the Walras-Jevons marginal utility equation. Objective equilibrium equations by Walras and Jevons are averaged over all transactions in the market and can only give a rough general picture without explaining the specific price of an individual exchange. An exchange micro-condition must be found that, when averaged, will give the Walras market equilibrium macro-condition. The study of the internal structure of exchange leads to the need to consider power. The concept of generalized power is introduced. It is generalized power that serves as the primary comparable and measurable objective basis of exchange. The power theory of exchange provides the objective price-equation. It is demonstrated that money is a measure of generalized power in exchange and a certification of generalized power in subsequent exchanges. The proposed theory is able to uniformly explain any exchange, including a single one, which is impossible with the existing theories of exchange.

This article evaluates the macroeconomic implications of commercial bank seigniorage, which emerges from the commercial banks’ power to create money in a fractional reserves regime. After evaluating the impact on aggregate output of commercial bank money relative to alternative exchange arrangements, the article identifies the determinants of commercial bank seigniorage and analyzes how equilibrium prices are determined in an economy where commercial banks extract seigniorage. The article also identifies the conditions under which commercial banks extract seigniorage, clarifies the relationship between seigniorage from commercial bank money creation and profits from pure financial intermediation, and shows how commercial bank seigniorage changes with different types of interbank payments settlement.

An examination of Emmanuel Levinas’ writings on money reveals his distance from—and indebtedness to—a philosophical predecessor, Georg Simmel. Levinas and Simmel share a phenomenological approach to analyses of the proximity of the stranger, the importance of the face, and the interruption of the dyadic relationship by the third. Money is closely linked to the conception of totality because money is the medium that compares heterogeneous values. Levinas goes beyond Simmel in positing an ethical relation to money permitting transcendence.

Escalation of commitment explains the choice for investing in an option for which great investments have previously been made even though better choices became available. The last 25 years of producing innumerous versions of Alzheimer Disease animal models with virtually no predictive validity should have exposed the fact that using animals for studying AD is clearly a failing course of action and as such should have been abandoned long ago, giving room to other alternatives to flourish. In this assay, I explore the idea that the investment in new animal models for studying Alzheimer (AD) represents a classic case of escalation of commitment, and sunk cost dilemma, in the biomedical research.

Four decades of snooker rankings are analyzed in terms of prize money distributions. In particular, it is investigated how much these rankings are dominated by the top players, and also by players from the UK. The main conclusions are: (1) with an increasing amount of available prize money, the rankings are less dominated by the top players, and (2) players from the UK have historically earned a significantly larger share of the available prize money than could be reasonably expected based on the actual percentage of UK players.

: The phenomenon of dark scleral spots postmortem is well-known in forensic pathology, first de-scribed by Sommers in 1833. Despite this, their presence is currently considered a nonspecific sign, and their pathogenesis has received little attention in forensic literature. In recent years, however, preliminary studies have suggested new mechanisms in their pathogenesis and links to specific types of death. This study aims to create a model for studying scleral spots using an animal model. Thirty-three sheep, already slaughtered for food, were used. After decapitation, the heads were transported to an environment with known temperature and humidity. The right eye underwent eyelid excision, while the left eye's eyelids were sutured. Continuous observation for approximately 24 hours was conducted, with brief interruptions to observe the closed eyes. Macroscopic obser-vation revealed dark scleral spots in 100% (20 out of 20) of the open eyes after an average of 240.96± 58,36 minutes. The spots did not appear in any of the closed eyes. Experimental data indicate that, despite the different location compared to human cadavers, this model serves as an excellent ex-perimental framework for studying postmortem scleral spots.

Eelgrass meadows have attracted a lot of attention not only for their ability to maintain marine ecosystems as feeding grounds for marine organisms, but also for their potential to store atmos-pheric and dissolved CO2 as blue carbon. This study comprehensively evaluated the bacterial and chemical composition data obtained from eelgrass sediments of different scales along the coast of Japan to investigate the sediment effect on the acclimatization of eelgrass. Regardless eelgrass habitat, approximately 1% Anaerolineales, Babeliales, Cytophagales, and Phycisphaerales were present in the bottom sediment. Sulfate-reducing bacteria (SRB) were present at 3.69 % in eelgrass sediment compared to 1.70 % in bare sediment. Sulfur-oxidizing bacteria (SOB) were present at 2.81% and 1.10% in the eelgrass and bare sediment, respectively. Bacterial composition analysis and linear discriminant analysis revealed that sulfur-oxidizing bacteria detoxified H2S in the eelgrass meadows and that the larger-scale eelgrass meadows had a higher diversity of sul-fur-oxidizing bacteria. Our result indicated that one of the following systems detoxifies the H2S in eelgrass meadows microbial oxidation by sulfur-oxidizing bacteria, oxidation by O2 perme-ated by the physical diffusion of benthos. This study indicated the issues of maintaining sustain-able conservation of the eelgrass bed.

Currently, life cannot be imagined without the use of bank cards for purchases or money transfers; however, their use provides new opportunities for money launders and terrorist organizations. This paper proposes a Blockchain-enabled transaction scanning (BTS) method for the detection of anomalous actions. The BTS method specifies the rules for outlier detection and rapid movements of funds, which restrict anomalous actions in transactions. The specified rules determine the specific patterns of malicious activities in the transactions. Furthermore, the rules of the BTS method scan the transaction history and provide a list of entities that receive money suspiciously. Finally, the Blockchain-enabled process is used to restrict the money laundering. To validate the performance of the proposed BTS, the Spring Boot application is built based on the Java programming language. Based on experimental results, the proposed BTS method automates the process of investigating transactions and restricts the money laundering incident.

Money launderers prefer to use financial services as the ideal medium to launder. The study aimed to provide an overview of the global AML/CFT regulations, application and how they should evolve in this dynamic environment. To gather more insight, a qualitative study was undertaken with relevant documents analysed. The main findings were: country implementation of the global AML/CFT regulations differed due to political and economic factors amongst others. While the various AML/CFT enforcements done by sampled countries were mainly cease and desist orders and monetary penalties which were publicized; and drawbacks of global AML/CFT regulations centered on application of these regulations and emerging trends. These include among other definitions of money laundering, reference to the three stage of money laundering, link between penalty and violations, technological innovations and regulations paradigm shift, cyber-attacks and data privacy. The study contributes to application and growing body of knowledge in that the advent of technology has resulted in better consumer experiences, new payment platforms, products, and services. However, these innovations have broadened emerging money laundering risks and risks in general to the financial system. Hence the need to conduct research based FATF Recommendations as risk is dynamic and not static.

The e-commerce sector is in a constant state of growth and evolution, particularly within its subdomain of online food delivery. As such, ensuring customer satisfaction is critical for companies working in this field. One way to achieve this is by providing accurate delivery time estimation. While companies can track couriers via GPS, they often lack real-time data on traffic and road conditions, complicating delivery time predictions. To address this, a range of statistical and machine learning techniques are being employed, including neural networks and specialized expert systems, with different degree of success. One issue with neural networks and machine learning models is their heavy dependence on vast, high quality data. To mitigate this issue we propose two Bayesian generalized linear models to predict time of the delivery. Utilizing a linear combination of predictor variables, we generate practical range of outputs with Hamiltonian Monte Carlo sampling method. These models offer a balance of generality and adaptability, allowing for tuning with expert knowledge. They were compared with PSIS-LOO and WAIC criteria. Results show that both models accurately estimated delivery times from the dataset, while maintaining numerical stability. Model with more predictor variables proved to be more accurate.

We investigate the Friedmann–Lemaitre–Robertson–Walker cosmological models within the framework of Rastall gravity incorporating particle creation. The modified field equations for Rastall gravity are derived and exact solutions are obtained under various choices of scale factors. The qualitative behaviour of our solutions depends on the Rastall coupling parameter ψ=kλ. Following the literature, we have restricted the Rastall coupling parameter ψ(k=1) to the range −0.0001 < ψ < 0.0007 at 68% CL from CMB+BAO data. Further, we have discussed the distinct physical behaviour of the derived models in detail.

The escalating global population and subsequent demand for agricultural products have led to a surge in agricultural waste generation, posing significant disposal challenges. Conventional disposal methods such as burning and dumping not only harm the environment but also jeopardize human health and safety. Recognizing the urgent need for sustainable waste management, researchers have increasingly focused on repurposing agricultural plant waste as a valuable resource. This paper presents a comprehensive review of the potential of agricultural plant waste in wealth creation and sustainable development. It highlights the detrimental impacts of current disposal methods and emphasizes the necessity for alternative approaches. By analyzing the physical, mechanical, and chemical properties of plant fibers, particularly cellulose, hemicellulose, and lignin, this review underscores their suitability for diverse applications. Moreover, it explores the emerging trend of utilizing pineapple leaf fiber, a sustainable and lightweight material, in structural applications such as UAV construction. With its exceptional mechanical properties and biodegradability, pineapple leaf fiber holds promise as a viable alternative to traditional materials, contributing to a more sustainable future. In conclusion, this review advocates for a paradigm shift towards embracing agricultural plant waste as a valuable asset for economic prosperity and environmental sustainability. It underscores the importance of continued research and technological advancements to unlock the full potential of agricultural waste in fostering a circular economy and driving sustainable development globally.

“Money has always been something of an embarrassment to economic theory. Everyone agrees that it is important; indeed, much of macroeconomic policy discussion makes no sense without reference to money. Yet, for the most part theory fails to provide a good account for it.” (Banerjee and Maskin, 1996, p. 955)The debate about whether or not a growth imperative exists in debt based, interest bearing mone- tary systems has not yet been settled. It is the goal of this paper to introduce a new perspective in this discussion.For that purpose an SFC computational model is constructed which simulates a post Keynesian Endogenous Money system without including economic parameters such as production, wages, consumption and savings. A case is made that isolating the monetary system allows for better analysis of the inherent properties of such a system.Loan demands, which are assumed to happen, are the driving force of the model. Simulations can be run in two modes, each based on a different assumption. Either the growth rate of the money stock is assumed to be constant or the loan rate, expressed as a percentage of the money stock, is assumed to be constant.Simulations with varying parameters are run in order to determine the conditions under which the model converges to stability, which is defined as converging to a bounded debt rate.The analysis shows that stability of the model is dependent on net bank profit ratios, expressed relative to their debt assets, remaining below the growth rate of the money stock. Based on these findings it is argued that the question about the existence of a growth imperative in debt based, interest bearing monetary systems needs to be reframed. The question becomes whether a steady state economy can realistically support such a system without destabilising it. In order to answer this question real world behavior of economic actors must be included in the model.It is concluded that there are indications that it might not be feasible for a steady state economy to support a stable debt based, interest bearing monetary system without strong interventions. However, more research is necessary for a definite answer. Real world observable data should be analysed through the lens of the presented model to bring more clarity.

Zoonoses are diseases transmitted from (vertebrate) animals to humans. Control and prevention of these diseases require an appropriate way to measure health for prudent and well-balanced decisions in public health. We propose a framework that aims to explore, understand and open up a conversation about the non-monetary value of animals through environmental and normative ethics. As an example of its application, participants can choose what they are willing to give in exchange for curing an animal in hypothetical scenarios selecting a human health condition to suffer, the amount of money, and lifetime as a tradeoff. We believe that considering animals beyond their monetary value in public health decisions will contribute to a more rigorous assessment of the burden of zoonotic diseases, among other health decisions. This method might help us complement the existing metrics in health, adding more comprehensive values for animal and human health for the “One Health” approach.

Distributional word vector representation orword embedding has become an essential ingredient in many natural language processing (NLP) tasks such as machine translation, document classification, information retrieval andquestion answering. Investigation of embedding model helps to reduce the feature space and improves textual semantic as well as syntactic relations.This paper presents three embedding techniques (such as Word2Vec, GloVe, and FastText) with different hyperparameters implemented on a Bengali corpusconsists of180 million words. The performance of the embedding techniques is evaluated with extrinsic and intrinsic ways. Extrinsic performance evaluated by text classification, which achieved a maximum of 96.48% accuracy. Intrinsic performance evaluatedby word similarity (e.g., semantic, syntactic and relatedness) and analogy tasks. The maximum Pearson (ˆr) correlation accuracy of 60.66% (Ssˆr) achieved for semantic similarities and 71.64% (Syˆr) for syntactic similarities whereas the relatedness obtained 79.80% (Rsˆr). The semantic word analogy tasks achieved 44.00% of accuracy while syntactic word analogy tasks obtained 36.00%

Based on recent popular money priming research results, which conclude that money makes self-sufficient (e.g. less interest in other people), we assumed that people are less interested in finding out whether others are lying or telling the truth. In a laboratory experiment, 163 students (85 women, 78 men, M_Age = 23.08, ranging from 18 to 36 years) were primed by actively handling money (versus paper sheets). Afterwards, they classified 24 video statements as true or deceptive (senders describing their most/least favorite movie), rated their classification confidence for each decision and then answered control questions. Results revealed no influence of priming condition on judgmental bias, classification accuracy, and classification confidence. Also the level of self-reported motivation to find out who lied or told the truth did not differ between conditions. Higher motivation was correlated to higher classification confidence. Additionally, and in line with Reinhard (2010) and Reinhard et al. (2011), higher classification accuracy correlated to a higher use of verbal content cues for classification decisions. Thus, while we were able to replicate these findings, our results contradict the assumption of a money prime influence on lie detection ability. Concluding, our results make self-sufficiency in this context questionable and offer next steps for research.

The recent Planck Legacy release confirmed the existence of an enhanced lensing amplitude in the cosmic microwave background (CMB) power spectra, which endorses the positive curvature of the early Universe with a confidence level exceeding 99%. In this study, the pre-existing curvature is incorporated to extend the field equations where the derived wave function of the Universe is utilized to model Universe evolution with reference to the scale factor of the early Universe and its radius of curvature upon the emission of the CMB. The wave function reveals both positive and negative solutions, implying that matter and antimatter of early Universe plasma evolve in opposite directions as distinct Universe sides. The wave function indicates that a nascent hyperbolic expansion is followed by a first phase of decelerating expansion away from early plasma during the first 10 Gyr, and then, a second phase of accelerating expansion in reverse directions, whereby both Universe sides free-fall towards each other under gravitational acceleration. Simulations of the predicted conformal curvature evolution demonstrate the fast orbital speed of outer stars owing to the external fields exerted on galaxies as they travel through conformally curved space-time. Finally, the wave function predicts an eventual time-reversal phase comprising rapid spatial contraction that culminates in a Big Crunch, signalling a cyclic Universe. These findings reveal that early plasma could have separated and evolved into distinct sides that collectively and geometrically influencing the Universe evolution, physically explanting the effects attributed to dark matter and energy.

Engineers make things, make things work, and make things work better and easier. This kind of knowledge is crucial for innovation, and much of the explicit knowledge developed by engineers is embodied in scientific publications. In this paper, we analyze the evolution of publications and citations in Engineering in a middle-income country such as Mexico. Using a database of all Mexican publications in Web of Science from 2004 to 2017, we explore the characteristics of publications that tend to have the greatest impact; this is the highest number of citations. Among the variables studied are the type of collaboration (no collaboration, domestic, bilateral, or multilateral), the number of coauthors and countries, the language of the article, controlling for a coauthor from the USA and the affiliation institution of the Mexican author(s). Our results emphasize the overall importance of joint international efforts and suggest that publications with the highest number of citations are those with multinational collaboration (coauthors from three or more countries), written in English, and when one of the coauthors is from the USA.

Aymaraism, as a socio-cultural phenomenon, has given rise to components and elements of representativeness in the population of the Andes. However, the dialectic component of the Aymara as a nation is annulled by fundamental historiographical elements that underlie this process of identification. The empirical analysis of the historical data leads us to conclude that the Aymara language and culture contain ambiguous elements that cannot be defined according to the dialectical interpretation and the current narrative. Thus, the analysis of the cultural, linguistic and social elements of this population from the Early Horizon period to the present confirms the historical distortion towards a narrative component of origin and presence in the territory of the Qullasuyu, in the current geographical area of the Collao. In order to understand this phenomenon, this work promotes the complementarity of the analysis through the use of ethnoarchaeological and documentary elements in order to clarify the origin, synthesis and development of the Aymara from a historical perspective, leaving aside the dialectical component of the present.

Techniques for the controlled seeding and growth of cracks are urgently required for non-destructive testing technique evaluation, particularly for additive manufactured (AM) samples. This paper describes a method which uses a combination of tensile load and resonance excitation of notched AM samples, with in-situ monitoring of the resonance frequency serving to track crack dimensions. Mechanical low-cycle fatigue cracks, ranging in length from ~0.3 mm to ~5 mm, are successfully created in five AM samples using this technique. The samples are non-destructively characterized using optical microscopy and Nonlinear Resonance (NLR) testing. The exploitation of resonance enables the concentration of a significant number of stress cycles on the samples in much shorter timespans than conventional fatigue testing, enabling high throughput, while utilising compact components. Furthermore, the tracking of resonance frequency shift throughout the process enables non-invasive and non-contact real-time condition monitoring.

The purpose of this paper is to demonstrate the existence of an artificial magnetic monopole and to introduce new electromagnetic equations by altering an electric field and a magnetic field vectors.As a principle device, a cylindrical condenser is prepared, and a superconducting loop is inserted into it. By this conduction, radial electric fields take a role as the centripetal force and both counterclockwise and clockwise motions are induced. As a result, a stationery wave is formed in which the nodes take a part in creating a monopole as follows.First, employing the Lorentz conservations and because node of the stationary wave has no phases, the momentum k and the vector potential A vanish and instead a magnetic potential appears in order to maintain the Lorentz conservation. This magnetic potential has relationship with an electric potential, and thus consequently, a dependent relationship is obtained between an electric field and a magnetic field vectors. Using this conclusive dependent relationship, we can derive new Maxwell equation assembly which are created by altering the electric field and the magnetic field vectors. In this process, we derive a divergent equation of magnetic fields which is not zero, i.e., the existence of a magnetic monopole. Employing these newly derived Maxwell equation, an electromagnetic wave is derived whose speed is the same as one the existing Maxwell equations provide. As a monopole configuration, this paper discusses the energy gap of the vacuum, which is a result of the Dirac equation and describes a monopole as pairs between two Cooper pairs (i.e. four electrons) whose interaction is a photon. As mentioned, because the total momenta and phases are zero, this paper defines the wave function as the Dirac function and demonstrate the condensation, employing the Bloch’s theorem. Moreover, using the macroscopic basic equations, we retrace the creation of the divergent magnetic field in view of macroscopic phenomenon., which provides results in this paper.In Result section in this paper, we succeeded in demonstrating the distribution of the divergent magnetic field of monopole in terms of both microscopic and macroscopic scales. Furthermore, Discussion section describes properties a magnetic monopole should follow.

The cryopreservation of gametes and embryos is an important element of biodiversity conservation. One species in need of conservation is the honey bee Apis mellifera L. Changing environmental factors, especially the anthropogenic factor, have led to a reduction in the numbers of this insect species. In this study, we provide an example of the creation of a biobank of honey bee drone sperm. For sperm cryopreservation, drones of the most common subspecies of honey bees common in Russia were selected. These were the dark forest bee, Apis mellifera mellifera from the Republic of Bashkortostan, with three subspecies (A. m. carnica, A. m. carpatica, and A. m. caucasica) from the southern regions of Russia, as well as two breeding stocks, the Far Eastern bee and Prioksky bee. For subspecies identification, morphometric and genetic methods were used. The subspecies of the studied samples were confirmed by the analysis of the tRNAleu-COII locus of mitochondrial DNA and nine microsatellite markers of nuclear DNA. It was shown that bees of the Prioksky breeding stock belong to the subspecies A. m. caucasica based on phylogenetic analysis, and the Far Eastern breeding stock is a stable hybrid, descending on the maternal line from the evolutionary lineage C or O. The results of the morphometric analysis are consistent with the results of the genetic analysis. For the cryopreservation of sperm, we used a honey diluent. As a result, the viability of frozen–thawed sperm decreased by 20.3% compared to fresh sperm, and overall motility decreased by 25-fold. The measurement of the sperm concentration in the spermatheca of artificially inseminated queens showed that it varied from 0.22 to 4.4 million/μL. Therefore, the use of honey in sperm cryopreservation has great potential.

The NOSTR is a communication protocol for the social web, based on the w3c websockets standard. Although it is still in its infancy, it is well known as a social media protocol, thousands of trusted users and multiple user interfaces, offering a unique experience and enormous capabilities. To name a few, the NOSTR applications include but are not limited to direct messaging, file sharing, audio/video streaming, collaborative writing, blogging and data processing through distributed AI directories. In this work, we propose an approach that builds upon the existing protocol structure with end goal a decentralized marketplace for federated learning and LLM training. In this proposed design there are two parties: on one side there are customers who provide a dataset that they want to use for training an AI model. On the other side, there are service providers, who receive (parts of) the dataset, train the AI model, and for a payment as an exchange, they return the optimized AI model. The decentralized and censorship resistant features of the NOSTR enable the possibility of designing a fair and open marketplace for training AI models and LLMs.

The anti-money laundering (AML) process has failed both in identifying suspicious cases in due time as in assisting the AML analysts in decision making. Starting from a new generic anti-fraud approach, this article presents the main aspects related to the development of a multi-agent system that goes beyond the capture of suspicious transactions, seeking to assist the human expert in the analysis of suspicious behaviour. First, a transactional behavioural profile of clients is obtained in a data mining process. A set of rules, obtained through data mining over a real database, in conjunction with specific rules based on legal aspects and in the expertise of the AML analysts make up the agents' knowledge base. The cases for which the system was unable to suggest a decision are flagged as requiring more detailed analysis. The system analysed 6 months of real transactions and indicated several suspicious profiles, a set of these suspects was investigated by the AML analysts who proved the suspicion of several cases, including some that had not been identified by the systems in execution.

Enzyme catalysis has traditionally been used by various human cultures for creating value, long before its basic concepts have been uncovered, by preparing useful products through the trans-formation of raw materials available from natural resources. Tremendous scientific and techno-logical progress has been accumulated globally in understanding what constitutes an enzyme, what reactions enzymes can catalyze, and how to search, develop, apply and improve enzymes to make desired products. The exquisite properties of enzymes as nature's preferred catalysts, such as high selectivity, diversity and adaptability, enable their optimal work, whether in single reactions or in multiple reactions. Excellent opportunities for resource efficient manufacturing of compounds needed are provided by the actions of enzymes working in reaction cascades and pathways within the same reaction space, like molecular robots along a production line. Enzyme catalysis plays an increasing role for industrial innovation and responsible production in various areas, such as green and sustainable chemistry, industrial or white biotechnology. Sources of inspiration can be current manufacturing or supply chain challenges, the treasure of natural enzymes or the opportunities of engineering tailor-made enzymes. Making best use of the power of enzyme catalysis is essential for changing the way how current products are manufactured, how renewable biobased resources can replace fossil-based resources, and how the safety, health environment aspects of manufacturing processes can be improved towards cleaner and more sustainable production.

We consider creation of entanglement between the remote electron spins using a magnetic nanoparticle attached to a cantilever tip (CT). We assume that the frequency of the CT vibrations matches the Larmor frequency of the spin (the CT-spin resonance). In the conditions of the CT-spin resonance the CT-spin system is described by the exactly solvable Jaynes-Kummings model. In this work using the evolution operator of the Jaynes-Kummings model we show that a movable CT can create an entangled state between the remote spins. The most striking result is that the entanglement between the remote spins can be achieved without measurement of the vibrational state of the CT.

The commonly quoted bistable Higgs potential is not a proper description of the Higgs field because, among other technical reasons, one of its stable states acquires a negative expectation value in vacuum. We rely on formal catastrophe theory to derive the form of the Higgs potential that admits only one positive mean value in vacuum. No symmetry is broken during the ensuing phase transition that assigns mass to the Higgs field; only gauge redundancy is “broken” by the appearance of phase in the massive state, but this redundancy is not a true symmetry of the massless field. Furthermore, a secondary, certainly amusing conclusion is that, in its high-energy state, the field oscillates about its potential minimum between positive and negative masses; but it is doubtful that such evanescent states can survive below the critical temperature of 159.5 GeV, where the known particles were actually created.

Technology Readiness Levels (TRLs) is a well-established and widely used approach for defining the readiness of new technology. To this extent, it assesses technology maturity against specific benchmarks, ranging from 1 (concept) to 9 (market solution). Although this is a useful classification service, allowing us to establish a common language, there are cases where we find that this conceptual approach fails to adequately highlight the maturity of certain innovative endeavors and effectively steer their development to higher TR levels. We will present an empirical case where the TRL approach presented a critical shortcoming in highlighting the true and effective readiness of a specific technological development and could not suggest the next natural step in ascending the maturity ladder. We will seek to generalize for the case of co-creation at large, analyze why co-creation may be poorly serviced by the current TRL model and suggest an amendment that would allow the observed shortcoming of the traditional TRL approach to be overcome and its use extended also in such co-creative settings.

The advent of social commerce (SC) has transformed the landscape of online consumer behavior, emphasizing the significance of customer-to-customer relations in shaping sustainable relation-ships with customers. This research investigated the intricate relationships between social com-merce dimensions, particularly suggestions and recommendations, forums and communities, and ratings and reviews, and their influence on customer-to-customer value co-creation (C2CVCC) and sustainable customer relationships (SCRs). A questionnaire was designed and administered to 635 respondents. We examined the psychometric properties of the measurements and subse-quently applied Partial Least Squares as a Structural Equation Modeling method (PLS-SEM) for hypothesis testing. The findings reveal that the dimensions of SC significantly impact C2CVCC, with ratings and reviews playing a pivotal role. Furthermore, C2CVCC emerges as a substantial mediator in the path between SC and SCRs. The empirical analysis showcases strong support for the proposed model, with robust path coefficients (β) and p-values confirming direct and indirect effects. These findings offer valuable insights for businesses seeking to leverage SC and customer interactions to enhance SCRs in the digital era. Understanding the dynamics of C2CVCC within the context of SC has become essential for marketers and businesses aiming to thrive in today's competitive online marketplace.

We introduce the Transformation Flower Approach (TFA), a Theory of Change that attends to multiple value creation and institutional change as a dual design challenge. We highlight how the TFA integrates social scientific theories and models relevant for transformative change (in particular focusing on pathways, leverage points, governance, power, and values) and demonstrate its practical value by an application to the ongoing transformation of the Dutch food system. By providing a holistic, transdisciplinary and practically relevant approach that aims to support new social contract formation, the TFA goes beyond other transformative change approaches. Based on the notion of pathways, it offers a toolbox that aids in working towards desired futures, involving both incumbents and challengers in an effort to harness untapped yet proximal potentials in a forward-looking way. By embracing an innovation approach, it not only promises to circumvent resistance to change, but also serves as a step-by-step approach to identify options for multiple value creation and effective cooperation. We demonstrate the analytical and practical value of the TFA by discussing action perspectives at various levels and scales in the context of the Dutch food system transition, including (1) area-oriented approaches, (2) acceleration agendas for specific transformation pathways, and (3) actor-specific transformation flowers. In developing these, we emphasize the importance of interdependencies between leverage points. Our approach helps to identify opportunities to link transformative options (the what), actors (the who) and levers (the how) in dynamic interaction to embark on transformative pathways.

The devastating effects of COVID-19 permeates virtually all aspects of life across geographic boundaries. As the lockdown is eased, and reinstated, across many parts of the world, attention is now shifting towards how to navigate the ‘now normal’ rather than the ‘next normal,’ of doing business with a view to achieving sustainable development. This study highlights some of the challenges and opportunities for micro, small, and medium enterprises (MSMEs) in times of crisis such as COVID-19. Conceptual by orientation, the study provides a broad overview of trends in crises times, drawing upon a range of qualitative accounts. The overarching message is the current direction of travel for MSMEs in sustaining their bottom-line, not after the crisis, but at this particular moment in time. The study highlights some implications for ‘pivoting,’ in order to cushion the impact of the pandemic on efforts to capacitate MSMEs in leveraging value co-creation with the consumers. The implications of the here and now are discussed.

This study offers an in-depth analysis of the COVID-19 pandemic’s trajectory in several member countries of the European Union (EU) to assess similarities in their crisis experiences. We also examine data from the United States to facilitate a larger comparison across continents. We introduce our new approach, which uses a spatio-temporal algorithm to identify five distinct and recurring phases that each country undergoes at different times during the pandemic. These stages include a Comfort Period characterized by minimal COVID-19 activity and limited impacts. The Preventive Situation demonstrates the implementation of proactive measures, with relatively low numbers of cases, deaths, and Intensive Care Unit (ICU) admissions. The Worrying Situation is defined by high levels of concern and preparation as deaths and cases begin to rise and reach substantial levels. The Panic Situation is marked by a high number of deaths relative to the number of cases and a rise in ICU admissions, denoting a critical and alarming period of the pandemic. Finally, the Epidemic Control Situation distinguishes itself by limiting COVID-19 deaths despite a high number of new cases. By examining these phases, we identify the various waves of the pandemic, indicating periods where the health crisis has a significant impact. This comparative analysis highlights the time lags between countries as they transition through these different critical stages and navigate the waves of COVID-19.

This study examines the impact of GenAI tools on the daily tasks of designers within corporations. It investigates both the operational changes and employee anxieties regarding job security. The research employs a qualitative approach: one without the use of ChatGPT and one with its use. The findings indicate significant improvements in operational experience and subjective perceptions across various tasks, as demonstrated through a user experience map. Moreover, the study highlights the potential of AI for enhancing managerial efficiency, streamlining workflows, and improving collaboration. However, it also addresses challenges concerning information authenticity, copyright protection, and professional identity. The goal of this study is to comprehend AI's current role in businesses, evaluate its effects on designers, and offer balanced recommendations that emphasize the integration of AI thinking into future corporate workflows from a human-centric perspective.

The paper deals with the reverse engineering, namely the as built documentation of the actual construction. The input is data measured in field using geodetic methods. In addition to modern methods of surveying 3D objects, such as laser scanning, it is still necessary to use classic surveying using a total station. The bottle neck of the process is the creation of documentation of the construction, which is still created manually in the appropriate CAD/BIM software. The goal of the research was to find a method that would reduce the amount of manual work when drawing documentation in CAD/BIM to a minimum. The core of the solution is the use of a topology that interconnects the points measured in field. The entire procedure has 2 parts: 1. Creating a topo-logical drawing template in a suitable CAD/GIS software (digital sketch), 2. Adding geometry to this sketch and creating a drawing using topological codes. The method was verified in practice by applying it to several specific buildings in the Czech Republic. The practical application of the method demonstrated a 30% time saving, a reduction in work and error rate in the entire process.

In this study, we discuss the properties of absolute vacuum space and how these properties can play a vital role in creating a mechanism in which the very first particle gets created simultaneously everywhere and we find the limit in which when the absolute vacuum volume reaches will lead to the collapse that leads to the creation of the first particle. This discussion is made following to the elementary dimensions theory study that was peer-reviewed at the end of 2020, everything in the universe is made from four elementary dimensions, these dimensions are the three spatial dimensions (X, Y, and Z) and the Vacuum resistant as the factor of change among the four, time itself wasn’t considered as the fourth dimension, rather time corresponds to a factor of change, and during the research it was found out that the Vacuum resistant is the factor of change in the Absolute Vacuum space, where time is a hypothetical concept, that represents changes during certain events compared to a constant change rate event.Therefore, time does exist, but as a factor of change, and as the Vacuum resistant in the absolute vacuum space, Time= factor of change= Vacuum resistant. In the study, the internal and external vacuum resistant volume equivalent is found, External Vacuum resistant=3.2857602*10^15 *mass. This equation is used to identify the amount of Free external vacuum resistant created during nuclear fission and fusion: Initial mass of the excited nucleuses mass of the created new nucleuses+ 3.2857602*10^15 * the lost Mass. In elementary dimensions, the energy created during nuclear reactions is equivalent to the free External vacuum resistant created through nuclear reactions, and mass is equivalent to the internal Vacuum resistant.

Proteins having a variety of functions play many essential roles in maintaining various life activities in organisms. Various methods, by which new protein functions can be artificially produced, have progressed rapidly upon development in recombinant DNA technology and effective screening techniques. However, the obtainable scope of the new functions has been restricted in a narrow range, because only functions of presently existing proteins can be used. On the other hand, it has been considered that it would be impossible to create an entirely new protein, which does not show any meaningful homology with any other amino acid sequences of previously existing proteins. The reason is because one amino acid sequence for a protein cannot be selected out from an extraordinary large amino acid sequence diversity as ~10130. As a matter of course, it is impossible to design an amino acid sequence of a protein in advance and a gene encoding the protein cannot be also formed through random process. Nevertheless, extant organisms have generated a variety of entirely new proteins in some way to make full use of them. This means that extant organisms have equipped a mechanism with which entirely new proteins can be produced under the present core life system composed of protein, tRNA (genetic code) and gene. In this article, first I introduce the mechanism, with which entirely new proteins are created in extant organisms, and further propose a novel strategy for application of the mechanism to protein engineering through creation of entirely new proteins, which could contribute to development of various industries.

A study of Bianchi Type I cosmological model is undertaken in the framework of creation of particles. To accommodate the creation of new particles, the universe is regarded as an Open thermodynamical system. The energy conservation equation is modified with the incorporation of a creation pressure in the energy momentum tensor. Exact solutions of the field equations are obtained (i) for a particular choice of the particle creation function and (ii) by considering the deceleration parameter to be constant. In the first model the behavior of the solution at late times is investigated. The physical aspects of the model have also been discussed. In the case of the second model we have restricted our analysis to the power law behaviour for the average scale factor. This leads to a particular form for the particle creation function. The behavior of the solution is investigated and the physical aspects of the model have also been discussed for the matter dominated era.

The article presents the results of the γ-ray and fast neutrons impact on various rice species, in order to obtain mutant forms resistant to salinity (NaCl) and drought factors (sorbite). They are going to be used as initial forms in synthetic selection when creating varieties, adapted to the stressful conditions of, both, soil and climate in the Kazakhstan Aral Sea. The average lethal doses (LD50) of γ-rays and fast neutrons, as well as, the average NaCl and sorbite lethal concentrations were established. A distinct dependence on the effect of ionizing radiation and stress factors on the number of induced resistant mutant forms has been related to the initial rice variety. The largest number of mutant forms was obtained from the local variety Syr Suluy, followed by Leader and Aikerim varieties. Out of all varieties, only 1% of the initially irradiated by γ-rays seeds survived, while after fast neutron irradiation – 4,3%. M1 mutant plants significantly differ from the initial forms in terms of morphological features – plant height, panicle length, and grain size. They are tolerant to lodging, and have short and highly sterile panicles, indicating that they are mutants.

The main obstacle affecting the natural and herbal products industry is the infringement of trade patents. This resulted in losing the opportunity to compete with others in this business. Creating additional value to this business is, therefore, a way of leading to patenting for trade protection for entrepreneurs. This study was conducted to develop the structural equation modeling of guidelines for creating additional value for Thai herbs to support trade patent. The study comprises a mixed method with three parts. In the first part, data comes from interviews with selected 9 specialists. The second part was supported by interviews to create the questionnaire and distributed it to 500 entrepreneurs, the next step was the data analysis using structural equation modeling (SEM). The third part used data from the SEM model to discussion focused on developing the conceptual model by 7 experts. The analysis of the developed model passed the criteria for evaluating consistency and empirical data. All hypotheses proposed in this study were supported, the findings revealed that all factors had a direct effect at a statistically significant level of 0.001. Furthermore, this investigation allows knowing the Brand Identity factor were practically important for creating value of Thai herbs leading to patent protection.

The construction industry in the Kingdom of Saudi Arabia (KSA) is a significant sector in the Middle East, with annual expenditures exceeding USD 120 billion. It employs 15% of the work force and consumes more than 14% of the country’s energy resources. Despite the significant growth in the Saudi construction sector, it faces various challenges due to the rapid launch of mega projects such as NEOM and the Line project, as well as other new projects as part of the Saudi Vision 2030. Challenges might be limited to shortages of skilled labours, rising costs, construction disputes, and material shortages. This study aims to investigate the claims management procedures under traditional practice to be compared with a proposed BIM package as an alternative solution to mitigate construction disputes. The proposed BIM model improves and streamlines the claims process through automation. This study presents prospective and retrospective methods for delay analysis under an accepted program. A questionnaire survey was conducted, and out of a total of 123 practitioners, 79 replied. The findings reveal that 40% of the respondents acknowledged a growing awareness of BIM in the KSA construction industry. 47% agreed that BIM can help reduce potential disputes, and 33% strongly agreed that BIM can reduce overall project cost overruns.

This study addresses the prevalent gap between formal and informal architectural methodologies in software engineering. Recognizing the potential of informal architecture artifacts in analytical processes, we introduce a groundbreaking methodology that efficiently transforms these informal components into structured formal models. This method facilitates a deeper understanding and utilization of informal diagrams and enhances analytical capabilities through graph analysis techniques. By leveraging user-friendly tools like Draw.io, the methodology democratizes the modeling process, making sophisticated architectural analyses accessible to a broader spectrum of professionals without requiring deep expertise in formal methods. The innovative aspects of this methodology lie in its ability to streamline the transformation process, significantly improving both the efficiency and effectiveness of model creation and analysis. These enhancements are demonstrated through a practical application involving a sample architecture diagram, where the resulting model is thoroughly analyzed using advanced graph analysis tools like Python's NetworkX library and Neo4j. This approach bridges the theoretical and practical divides in software architecture and sets a new standard for integrating informal artifacts into systematic engineering workflows. In addition, considerations for Artificial Intelligence developments are discussed.

As a typical form of value co-creation, crowdsourcing has been increasingly applied by firms to generate business value. By engaging a crowd, a platform, and other stakeholders, a crowdsourcer can foster the co-creation of a portfolio of value for diverse stakeholders. In analyzing the value co-creation in crowdsourcing, we propose a framework by combining the theories and frameworks in value co-creation and crowdsourcing. The framework examines the key stakeholders, joint purpose, engaged value co-creation processes, contributions, bidirectional relationships of the engagement, and perceived value, exhibiting a holistic view of the value co-creation in a crowdsourcing project. Results of the analysis reveal the business performance of the crowdsourcing project and identify areas of improvement regarding business sustainability. This is a major theoretical contribution of this study. The research design applied a case study approach to empirically investigate a crowdsourcing project. Both the theoretical and practical implications are discussed.

Introduced in 2009, Bitcoin has demonstrated a huge potential as the world’s first digital currency and has been widely used as a financial investment. Our research aims to uncover the relationship between Bitcoin prices and people’s sentiments about Bitcoin on social media. Among various social media platforms, micro-blogging is one of the most popular. Millions of people use micro-blogging platforms to exchange ideas, broadcast views, and to provide opinions on different topics related to politics, culture, science, and technology. This makes them a potentially rich source of data for sentiment analysis. Therefore we chose one of the busiest micro-blogging platforms, Twitter, to perform sentiment analysis on Bitcoin. We used ELMo embedding model to convert Bitcoin-related tweets into a vector form and SVM classifier to divide the tweets into three sentiment categories - positive, negative, and neutral. We then used the sentiment data to find its relation with Bitcoin price fluctuation using the linear mixed model.

The Interdisciplinary Method of Musical Literacy, Education and Artistic Awareness (MILMESA) is developed and applied essentially in higher education (artistic, cultural and teacher training courses), promoting effective endogenous (interarts) and exogenous interconnection (artistic and other non-artistic areas) of an inter and pluridisciplinary matrix, as well as assuming itself as a privileged vehicle of relationship and extension to the community in the frame of the making of artistic-cultural and pedagogical-didactic events in the European, Luso-Brazilian, Luso-African and Hispanic American territories. It was created, tested and evaluated in five consecutive quadrennia (2002–2023), being regularly adapted, adapted and added according to the observed realities, evolving into the deepening of new concepts and models of intervention in these domains (e.g., Expressive and Proximal Didactics). Using the Ethnographic Method and the Case Study, and having the source of data collection as Document Analysis of written and iconographic or visual sources (n = 1386) and Participant Observation, this study aimed to describe and analyse the application and evolution of MILMESA in terms of education and extension to the community. It was concluded that there was a need to promote, with greater regularity and scope, greater technological interaction via digital platforms and social networks, within the framework of the participation of external specialists (e-DEP) and the very experience of MILMESA’s experiences and initiatives, giving it a more meaningful and participatory range.

This analyses the impact of competition on liquidity creation in the banking industry of the United States. For the purposes of this paper panel data of US banks for the period of 1976-2000 is chosen as a sample. The plausible endogeneity issue is addressed by employing instrumental variables and then implementing two stages least squares method. Besides this, crisis period of 1990-1992 is also analyzed to compare effect with in “normal times”. The results show that decrease in the level of competition negatively affects the liquidity creation ability of banks in the US and this impact is even more negative during the crisis period.

It is agreed that before the creation of particles, space was absolutely devoid of matter and radiation. In this study, we assume that the absolute void comprises four dimensions; three spatial dimensions and a force equivalent representing the factor of change among the elementary dimensions. Our hypothesis is based on the expansion of the spatial dimensions, and the subsequent space instability. We demonstrated that when the outward force equivalent strength exceeds a critical limit, it collapses inward to restore equilibrium in the system. Then, the void inside the collapsed force equivalent acts as a void in a confined system, the energy of the system remains conserved at all stages. With the decrease of the spatial dimensions due to the collapse the energy density increases, at the final stage the energy in the confined system is concentrated forming a solid state of energy. In which, this solid state of energy is a particle become the source of the elementary particles. The created high-energy sources are controlled by the internal and external forces of the source and all entities in its external force field until equilibrium is reached. The article gives the summary of Big bang theory and its problems which are further discussed in inflation. This article will help in understanding that how elementary dimensions play a role in the formation of elementary particles. The quark gluon plasma, inflation, gravitational collapse, and gravitational lensing provide evidence supporting the elementary dimensions theory presented in this paper.

Brand communication and supply chain management are critical components of value co-creation in B2B markets, yet their interplay and implications remain underexplored in current literature. This qualitative study investigates how these elements synergistically contribute to mutual value creation among businesses. Through semi-structured interviews with senior executives and managers from diverse industries, key insights were gleaned regarding the strategic alignment of brand communication strategies with supply chain practices. Findings underscore the importance of authenticity, transparency, and consistency in brand messaging to build credibility and foster stakeholder trust. Supply chain management emerged as pivotal in supporting effective brand communication, facilitated by advancements in AI, blockchain, IoT, and cloud computing, enhancing operational efficiency and responsiveness across global networks. Entrepreneurship and emotional intelligence were identified as crucial drivers of innovation and collaboration within B2B contexts, augmenting organizational agility and resilience. Furthermore, the integration of sustainable practices within supply chain operations was found to enhance brand reputation and mitigate risks associated with environmental and ethical considerations. The study highlights actionable insights for practitioners, emphasizing the strategic integration of brand communication and SCM capabilities to navigate complexities, capitalize on emerging opportunities, and foster sustainable growth. This research contributes to a deeper understanding of the multifaceted dynamics shaping B2B interactions and provides a foundation for future research endeavors. By aligning brand communication strategies with SCM practices and leveraging technological advancements, businesses can enhance competitive advantage, cultivate enduring relationships with stakeholders, and achieve sustainable success in a dynamic global marketplace.

This paper outlines the evolution of a learning technology interface from a Beta version to launch with educators and its alignment to pedagogical theory, designed to maximise collaboration between teacher and student. It explores how the “co-creation” of curricula via textual sources that underpin teaching and learning can be enhanced through interactive e-books and outlines the challenges involved in this praxis. With a number of stakeholders involved in the live use of the platform (including teachers, students, HE educators, course instructors, curriculum designers and software developers), iterative feedback loops informed real-time design improvements to both the interface and the-ory. This collaboration utilised a design-based research (DBR) approach (Wang and Hannafin, 2005), which is outlined here as explanation of how the tool developed and how iterative feedback helped to reconsider the challenges educators face in implementing pedagogical innovation across differing contexts. We propose how speculative design (Lukens and DiSalvo, 2012) and Activity Theory (Engeström, 1987) workshops can methodologically enhance the planning and evaluation phases inherent to DBR approaches, which involve students to prepare for educators’ innovation. Finally, we conclude with how educators can utilise these design principles using stratified approaches to help prepare organisational approaches for innovation.

Rare diseases are characterized by a wide diversity of signs and symptoms and vary not only from disease to disease, but also from person to person, and living with a disease leads patients to peculiar experiences and treatments, without limits of time and space, as they extend to various environments and relationships of their lives. The objective of this study is the theoretical interaction between Value Co-creation (VC) and the Stakeholder Theory (ST) with the Shared Decision Making (SDM) health care theory. It is configured as a multiparadigmatic proposal by enabling the analysis of multiple perspectives of different stakeholders in health care. Thus, Co-created Decision Making (CDM) emerges in a logic dominated by service, with emphasis on intangible aspects and the interactivity of the relationships. It goes beyond the clinical office and the doctor-patient relationships, as studied in SDM, extending to all environments and interactions that add value to the patient's treatment. It was concluded that the essence of this new theory proposed here is neither in patient-centered care nor in patient self-care, but in co-created relationships with and between stakeholders in both directions, including non-health care environments that are important to the patient, such as relationships with friends, family, other patients with the same disease, social media, public policies, and the practice of pleasurable activities.

The research explores the impact of financial indicators on the credit ratings of companies listed on the S&amp;P 500, employing a Sys-GMM Model to address endogeneity concerns. The study investigated three independent variables categorized as market and survival factors alongside with seven control variables sourced from leverage, liquidity, interest coverage, profitability, market, survival, and macroeconomic domains. The sample comprised 2398 observations from Capital IQ Pro, spanning nine years (2013 to 2021) and encompassing 240 public companies. The findings suggest that neither Tobin's Q (TQ) and Total Shareholder Return (TSR) lack significant correlations with credit ratings, implying that stock market performance and total shareholder return do not directly impact credit ratings. In contrast, the Altman Z-score (AZS) emerged as a significant predictor, indicating its importance in assessing credit risk. These insights enhance understanding of financial indicators' impact on credit ratings, aiding financial institutions and companies in prudent lending and financing decisions.

Despite knowledge concerning stakeholders and the economic advantages of consultation, collaboration and innovation, analysis of the sustainability implications of the geothermal industry has tended to take a high-level or systemic overview of national performance. This study seeks to begin to fill this gap in the academic and grey literature, investigating the following research question: how do projects in the Icelandic geothermal energy sector create co-benefits with stakeholders and reflect the integration of sustainable energy development (SED)? The focus of its analysis is on identifying who are the stakeholders, what are the sustainability benefits co-created with stakeholders, and when in the project lifecycle do these occur. Based on eleven semi-structured interviews with project managers in Iceland’s geothermal industry, the study identifies a broad array of stakeholders in the sector, including national and municipal governments and public sector institutions, businesses, the public, employees and landowners. The sustainability co-benefits of Iceland’s geothermal power projects are broad and cut cross all six themes of SED and multiple phases of the project lifecycle. Although the sustainability benefits are very apparent, trade-offs are reported between the pursuit of an economically efficient energy system and nature conservation. This relates to unsustainable utilization of the resources and the environmental externalities of power production and consumption. Efforts to mitigate these effects are ongoing and the further pursuit of SED is likely in Iceland given its recognition within the nation’s new energy policy and to meet ambitious greenhouse gas emissions reduction targets in the government’s climate action plan. These are issues that are prominent in other nations seeking to decarbonize energy systems through increased utilization of geothermal resources.

Community co-creation is increasingly crucial to the building of sustainable societies. Communities must proactively and independently create value chains in the face of many wicked problems. However, practical frameworks and tools for facilitating community co-creation require further development. As such, for this paper, we propose a theoretical framework for analyzing community co-creation value chain mechanisms based on a narrative review of literature on Collective Impact, social impact assessment, and Community Capital from the perspective of collective impact, a framework with a fair amount of previous research. We argue for the importance of applying knowledge of social impact assessment, particularly for the collective impact conditions of common agenda and shared measurement system. We discuss its relationship with the Theory of Change and the use of systems thinking to mitigate the subjectivity and arbitrariness of design thinking. Furthermore, we emphasize the value of employing the community capital concept as a framework for analyzing interrelationships among elements. By integrating multiple concepts, we enhance the collective impact framework and outline potential avenues for future research on analyzing and effectively implementing co-creation value chain mechanism in a community-based approach.

The upsurge of Generative Adversarial Networks (GANs) in the previous five years has led to advancements in unsupervised data manipulation, sourced feature translation, and precise input-output synthesis through a competitive optimization of the discriminator and generator networks. More specifically, the recent rise of cycle-consistent GANs enables style transfers from a discrete source (input A) to target domain (input B) by preprocessing object features for a multi-discriminative adversarial network. Traditionally, cyclical adversarial networks have been exploited for unpaired image-to-image translation and domain adaptation by determining mapped relationships between an input A graphic and an input B graphic. However, this integral mechanism of domain adaptation can be applied to the complex acoustical features of human speech. Although well-established datasets, such as the 2018 Voice Conversion Challenge repository, paved way for female-male voice transformation, cycle-GANs have rarely been re-engineered for voices outside the datasets. More critically, cycle-GANs have massive potential to extract surface-level and hidden feature to distort an input A source into a texturally unrelated target voice. By preprocessing, compressing, and packaging unique acoustical voice properties, CycleGANs can learn to decompose speech signals and implement new translation models while preserving emotion, the intent of words, rhythm, and accents. Due to the potential of CycleGAN’s autoencoder in realistic unsupervised voice-voice conversion/feature adaptation, the researchers raise the ethical implications of controlling source input A to manipulate target voice B, particularly in cases of defamation and sabotage of target B’s words. This paper analyzes the potential of cycle-consistent GANs in deceptive voice-voice conversion by manipulating interview excerpts of political candidates.

Law of conservation of energy is the most well-established law of modern physics. But, inflationary cosmological model which assumes the universe to be created from a point of singularity has not been able to identify the source of energy for creation of this universe. As per uncertainty principle, a quantum vacuum fluctuation can at most create energy of ~10^-8 kg in a Planck time of ~5.4 ×10^-44 s whereas total positive energy due to matter/vacuum existing in the universe is more than ~10⁵⁴ kg. To solve this problem, we have recently published a new cosmological model (Biswaranjan Dikshit, Canadian Journal of Physics, 100, 218-225, [2022]) in which we have mathematically proved that the total energy of the universe can be zero right from the beginning of the universe to till date due to negative gravitational potential energy and thus law of conservation of energy can be satisfied during creation of the universe from nothing. In this article, starting from a simple argument, we explain why net energy of the universe can be zero only in our model, not in standard cosmological model. An interesting fact pointed out in this paper is that the factor ~10⁶² by which radius of universe has increased from its starting value of ~10^-36 m to present value of ~10²⁶ m is same as the factor by which positive energy has increased from Planck energy ~10^-8 kg to present value ~10⁵⁴ kg. This is in agreement with our new model that predicts the positive energy of universe to be proportional to the radius of universe. We also bring out to the notice that zero energy universe is possible only if smallest possible length in nature is, l_min=l_p(π/2)^1/2 = 2.0×10^-35 m. Minimum possible length is important in theory of quantum gravity and string theory.

In the modern days the data is coming from various devices like mobiles, tabs, laptops, computers, IOT devices e.tc and is stored in the electronics form in the systems using the concept of files or data bases. Clustering Technique is used to extract data from these sources. Improving the accuracy of the model is improved using the feature selection or feature engineering or both. The feature engineering is used to add a new feature based on the global mean. Along with that new feature in addition to the feature selection increase the overall accuracy of the model.

The evaluation of the possibility of obtaining dihaploids by the method of anther culture in vitro to accelerate selection for resistance to prolonged flooding of seeded rice with water was carried out. The object of research is rice hybrids F2 of the Rice Breeding and Seed Production Laboratory of the “Donskoy” ASC, obtained as a result of interbreeding the best economically valuable varieties with samples bearing genes of resistance to prolonged flooding with water. Basic nutrient medium with an optimal composition of nutrition elements and growth hormones stimulating callo- and morphogenesis were used. For the induction of callus formation, 12604 anthers were planted, according to 26 hybrid combinations represented by 68 plants, as a result, 716 neoplasms were obtained, including 586 non–morphogenic callus, 130 regenerating plants. Cultivation of anthers revealed large genotypic differences in the samples. According to the responsiveness to neoplasms, 60% of the panicles showed a positive result, the rest did not give callus. The most responsive to the formation of callus were hybrid combinations: 5009/2 – 84 pcs., 5010/2 – 94 pcs., 4565/3 – 85 pcs., 4641/2 – 69 pcs. They also showed the ability to morphogenesis. Androgenic plants were obtained by 14 hybrid combinations, their share was 1.03% of the total number of inoculated anthers. 30 green regenerative lines from four rice hybrids were obtained, differing in visual morphological assessment: 5009/2 - 5 pcs., 5010/2 – 5 pcs., 4565/3 – 2 pcs., 4641/2 – 18 pcs. The isolated lines are characterized by good responsiveness in the culture of anthers in vitro, carry genes for resistance to prolonged flooding, and can be used in rice breeding programs using DG technologies.

As time progresses and technology improves, biological data sets are continuously increasing in size. New methods and new implementations of existing methods are needed to keep pace with this increase. In this paper, we present a high performance computing(HPC)-capable implementation of Iterative Random Forest (iRF). This new implementation enables the explainable-AI eQTL analysis of SNP sets with over a million SNPs. Using this implementation we also present a new method, iRF Leave One Out Prediction (iRF-LOOP), for the creation of Predictive Expression Networks on the order of 40,000 genes or more. We compare the new implementation of iRF with the previous R version and analyze its time to completion on two of the world's fastest supercomputers Summit and Titan. We also show iRF-LOOP's ability to capture biologically significant results when creating Predictive Expression Networks. This new implementation of iRF will enable the analysis of biological data sets at scales that were previously not possible.

Informal dementia home caregiving is viewed negatively and can result in caregiver depression and anxiety from burnout, potentially compromising caregiving. Solutions are unclear, as caregiving relationships are unique—caregiver creation of a graphic memoir may help to mitigate the negative dementia narrative and reduce experienced burnout. This investigation examines the writing of a graphic memoir by one informal dementia home caregiver, created with the help of a cartoon illustrator and a publisher who edited, printed, and made the graphic memoir available at the psychiatric bookstore considered the largest in North America. Mother of the illustrator and the editor and publisher of this graphic memoir, this author provides the perspective taken in this investigation. The analysis, developed by this author, represents psychoanalytic narrative research, serving as the historical method. Aided by email threads between the publisher/caregiver, publisher/printer, and publisher/bookseller, and a published interview with the dementia caregiver are answers to how writing, illustrating, and publishing the graphic memoir affected the caregiver’s narrative reconstruction and burnout. Providing an example for other informal dementia home caregivers similarly to write and illustrate a publishable graphic memoir for their positive narrative reconstruction and to help decrease their depression and anxiety from burnout is the aim.

Gastrotricha are microscopic benthic animals found in almost all water bodies. To date, about 870 species distributed in 71 genera, 18 families, and two orders are known. Known freshwater species are 359, several of which found also in Italy; however, a compendium of the studies carried out so far and a georeferenced distribution of the species still needs to be provided. This project aims to summarize information about Italian gastrotrichs' diversity and geographic distribution. Diversity data, acquired over 239 years, were reviewed and corrected based on taxonomic and nomenclatural updates and, in addition to distribution information, were organized into a data matrix useful for statistical analysis and to be feed to a Geographic Information System software to easily understand the overall figures. Results indicate Italy as one best-known country regarding freshwater gastrotrich, with 88 species in 16 genera and 3 families from 59 investigated localities; the Nation counts 16 type localities and 19 endemic species. Despite its censed biodiversity, many Italian regions remain still poorly or not investigated where future research should focus. Implementing a web mapping plugin enabled the creation of interactive maps for an easy and modern sharing of the work done and information acquired.

In the present study, the efficiency of a biomimetic approach by coating demineralized bone matrix (DBM) amorphous calcium phosphate (DBM+CaP), including its combination with serum albumin (DBM+CaP+BSA), was investigated. The intact structure of DBM promotes the transformation of amorphous calcium phosphate (CaP) into DPCD with a characteristic plate shape and particle size of 5–35 µm. The inclusion of BSA in the coating resulted in a better and more uniform distribution of CaP on the surface of DBM trabeculae. MG63 cells showed that both the obtained forms of CaP and its complex with BSA did not exhibit cytotoxicity up to a concentration of 10 mg/ml in vitro. Ectopic (subcutaneous) implantation in rats revealed pronounced biocompatibility, as well as strong osteoconductive, osteoinductive, and osteogenic effects for both DBM+CaP and DBM+CaP+BSA, but more pronounced effects for DBM+CaP+BSA. In addition, for the DBM+CaP+BSA samples, a pronounced full physiological intrafibrillar biomineralization and proangiogenic effect with the formation of bone-morrow-like niches, accompanied by pronounced processes of intramedullary hematopoiesis, indicating a powerful osteogenic effect of this composite have been achieved.

Acute kidney injury (AKI), especially if recurring represents a risk factor for future chronic kidney disease. In intensive care units, increased intraabdominal pressure is well-recognized as a significant contributor of AKI. However, the importance of transiently increased intra-abdominal pressures procedures is less commonly appreciated during laparoscopic surgery, the use of which has rapidly increased over the last few decades. Unlike the well-known autoregulation of the renal cortical circulation, medulla perfusion is modulated via partially independent regulatory mechanisms and strongly impacted by changes in venous and lymphatic pressures. In our review paper, we will provide a comprehensive overview of this evolving topic, covering a broad range from basic pathophysiology up to and including current clinical relevance. Key regulators of oxidative stress such as ischemia-reperfusion injury, the activation of inflammatory response and humoral changes interacting with procedural pneumoperitoneum formation and AKI risk will be recounted. Moreover, we present an in-depth review of the interaction of pneumoperitoneum formation with general anesthetic agents and animal models of congestive heart failure. A better understanding of the relationship between pneumoperitoneum formation and renal perfusion will support basic and clinical research, leading to improved clinical care and collaboration among specialists.

The article presents research results of the γ-ray and fast neutrons impact on various rice species, in order to obtain mutant forms resistant to salinity (NaCl) and drought factors (sorbitol. They are going to be used as initial forms in synthetic selection when creating varieties, adapted to the stressful conditions of, both, soil and climate in the Kazakhstan Aral Sea. The average lethal doses (LD50) of γ-rays and fast neutrons, as well as the average NaCl and sorbitol lethal concentrations were established. Such environment is best suited for clear manifestation of the mutagenic effect of ionizing radiation and the resistance of rice plants to salinity and drought. A distinct dependence in the effect of ionizing radiation and stress factors on the number of induced resistant mutant forms has been related to the initial rice sort. The largest number of mutant forms was obtained from the local variety Syr Suluy, followed by Leader and AyKerim varieties. From all varieties, the number of mutants obtained from exposure to γ-rays was 43 pieces out of 4500 grains, and from the impact of fast neutrons - 115 pieces out of 2700 grains. M1 mutant plants significantly differ from the initial forms in terms of morphological features – plant height, panicle length, grain size Most plants are characterized by short growth and even dwarfism (˂80 cm). They are lodging tolerant, have short and highly sterile panicles, indicating that they are mutants and resistant to salinity, drought, or both.

The science behind the curing process and the sous-vide cooking technique has advanced significantly in recent years. Variables such as temperature, time, and microbial growth, among others, have a substantial impact on the preparation and acceptance of culinary creations. This study focused on evaluating the dry aging method and the sous-vide cooking technique applied to various cuts of bone-in beef (Rack, Tomahawk, New York, and Rib Eye) subjected to different aging periods (28, 32, 42, and 45 days) under controlled temperature and storage conditions. The resulting samples underwent microbiological analysis after the curing method and the sous-vide cooking process, and they were also used in different culinary preparations to measure their degree of acceptability.

This study examines Tim Rowett's YouTube channel, "Grand Illusions," which captures and maintains positive viewer engagement in the digital domain. Through a comprehensive YouTube channel analysis, this paper identifies key factors contributing to its success, including collaboration and influence, educational impact, legacy and continuity, personal style, and community engagement. Rowett, known for his extensive toy collection and in-depth knowledge of their mechanics and history, employs an educational and engaging presentation style that fosters a positive and inclusive online community. His approach entertains and educates, making him a valuable digital resource that inspires viewers of all ages. This research proposes the CECCE (Collaboration, Education, Continuity, Community Engagement) model as a framework for content creators seeking to replicate the success of "Grand Illusions." The study emphasizes the potential of tailored, passionate content to cultivate healthy digital communities and underscores the significant role of digital content creators in shaping online culture. The proposed framework will guide creators to achieve similar success.

Humanity, culture, societal development and language issues are mutually reinforcing much as they are intricately interwoven in a non-ceasing dynamic interrelationships within the matrix defined by language standardization or development, acquisition and use that mostly take up central place as unifying and propelling forces in language discourse. Within the confines of globalization which is neither homogenization nor convergence; but the beginning of drawing on the strength of indigenous capabilities to create knowledge ecology that would enliven socio-economic and scientific development of the world in far reaching interconnectivities and relationships across every clime, issues pertaining to language development, acquisition and use become imperative. It is against this background that this paper examines the development/standardization, acquisition and use of Esan language as one of several Nigerian indigenous languages to promote scientific and technological development through knowledge creation, preservation and dissemination. The obsession of using western model and epistemological outlook to achieve appropriate scientific and technological development to the utter neglect of home grown and culturally distilled efforts were also examined. In the light of the dare consequences and the harsh conditions globalization imposes on developing nations, this paper highlights standardization and use of indigenous languages in chatting appropriate trajectory for effectual developmental efforts in fast shrinking contemporary world.

Laser in situ keratomileusis (LASIK) is the gold standard in the surgical correction of refractive errors on the cornea. It entails the creation of a superficial hinged corneal flap by a femtosecond laser, ablation of the underlying stromal bed by an excimer laser, and reposition of the flap. The corneal flap can be build in a 2-dimension (2D) fashion with tapered edges, or in a 3-dimension (3D) fashion, with angled sidecut. The latter reduces the risk of flap dislocation and infiltration of epithelial cells. This retrospective study compares with optical coherence tomography 3D and 2D flaps, and respective intra- and early post-operative complications. Four hundred consecutive eyes were included, 200 for each group. In the 3D group, the mean edge angle was 92°. The procedure was in average 5.2 seconds slower in the 3D group (p=0). Non visually significant flap folds were found in 13 eyes of the 2D group and in 7 eyes of the 3D group (p= 0.17). An intracorneal opaque bubble layer induced by laser photodisruption was more commonly observed in the 3D group (9 eyes vs. 2; p=0.03). In conclusion, the creation of a LASIK flap by a 3D-femtosecond laser cut was safe and effective.

(1) Background: Presentation of the method of increasing the competitiveness of the mining industry through the demonstration of the possibility and potential in closing the loop of supply chains through waste management; (2) Methods: The source literature analysis and an arithmetic analysis of the data of statistical materials and data obtained from business in static and dynamic perspectives; (3) Results: According to the latest data available, in Poland, mining wastes account for over a half of industrial wastes, while the annual growth of mining wastes is on the level of 4%. The recorded recovery of mining wastes is on the level of ca. 19%. The exemplary company that deals with the recovery of carbon wastes recovers ca. 80% of material, which is handed over for utilization (4) Conclusions: It has been found that the structure of the level of mining wastes and the level of their recovery rates demonstrate a large potential of closing the loop of chains in this industry and, at the same time, a potential to extend the chains through directing the material from recovery to various sectors. This constitutes an example of the direction of activities that are in line with the EU strategies for the economies of other states which possess this type wastes.

Onion skin waste (OSW), the primary non-edible byproduct from onion processing, offers a renewable source of bioactive compounds. This study aims to valorize OSW through subcritical water extraction (SWE), aligning with circular economy and biorefinery principles. SWE was carried out at 145 °C, 50 bar and 50 min in a discontinuous reactor, producing a phenolic-rich extract (32 ± 3 mg/g), dominated by protocatechuic acid (20 ± 3 mg/g), quercetin-4´-O-glucoside (7.5 ± 0.2 mg/g), and quercetin (3.2 ± 0.6 mg/g). Additionally, it contains sugars (207 ± 20 mg sucrose-Eq/g), proteins (22.8 ± 1.6 mg BSA-Eq/g) and free amino acids (20.4 ± 1.2 mg arginine-Eq/g). Its phenolic richness determines its scavenging activity against ●NO and O2●- radicals, and its α-glucosidase and aldose-reductase inhibition without affecting α-amylase. Notably, the extract demonstrates significant α-glucosidase inhibition (IC50 = 76 ± 4 µg/mL), surpassing acarbose (IC50 = 129.5 ± 1.0 µg/mL), in both pure enzyme and cell culture tests without showing cytotoxicity on AGS, HepG2 and Caco-2 human cell lines. The extract’s bioactivity and nutritional content make it suitable for developing antioxidant and antidiabetic nutraceutical/food components, highlighting the SWE potential for OSW valorization without using organic solvents.

This research aims to enhance scholarly understanding Analysis of potential Value Creation research on managing transit oriented that may arise from Mass Rapid Transit resources through an extensive literature review, analyzing 235 papers from the Scopus database spanning 2011-2024, with a specific focus on value creation managing transit-oriented area. Data collection was conducted on January 1, 2024, using Harzing's Publish or Perish tool. The selected studies are associated with keywords such as 'managing transit orientation (154 papers), Value creation MRT (45 papers), Innovation MRT (36 papers)/ In the filtering process, 235 papers were assessed, excluding those unrelated to the research focus on the cash flow statement. The inclusion of 31 carefully selected articles reflects a targeted approach, ensuring alignment with the research focus on value creation in managing transit orientation a relevant dataset for analysis. This article was created by accessing several scientific articles regarding the application of identification in managing transit orientation using Vos viewer. Value creation research in managing transit oriented is needed to explore the following areas: Long-term sustainability of identified core competencies, Competitive Imitation, Organizational Adaptability, Industry Specific Applications, Performance Measurement, Dynamic Capability Development, Cross-Cultural Perspective. Potential areas for further research include Incorporate additional contingent factors into the model, such as environmental dynamism and competitiveness, to test the validity of the Resource-Based View (RBV) model. Extend the analysis to small and medium-sized businesses to examine how organizational structure and competitive strategy impact performance in this context.

Fluorinated compounds and co-enzymes are being widely researched and employed throughout research community because of their versatile physical, chemical and biological properties. In this work, we synthesized NiS-NiO/S-g-C3N4, a highly effective photocatalyst for C(sp3)-F bond activation and the regeneration of coenzyme (1,4-NADH) employing a new and ecologically acceptable route. The obtained photocatalyst exhibited important photocatalytic properties, such as good solar light harvesting ability, suitability of the optical band-gap, and facilitating efficient charge migrations. As a result, the newly designed NiS-NiO/S-g-C3N4 photocatalyst shows the excellent yield for regenerations of 1,4-NADH (51%). Further, a method of combining C(sp3)-F bond activation with photocatalysis has been demonstrated that represents a very powerful and sustainable approach, that can be a major breakthrough for the field of pharmaceutical.

Background: HIV self-testing (HIVST) is one of the recommended approaches for HIV testing services, particularly for helping reach populations who would not normally access facility-based HIV testing. HIVST must be tailored to different populations to ensure uptake. Objective: The main objective of this study was to develop an acceptable HIVST delivery strategy to help improve urban men’s engagement with HIV services. Methods: We invited key stakeholders for urban men’s HIV services to participate in a co-creation workshop aimed at developing HIVST delivery approaches for urban men, using eThekwini municipality as a study setting. We conducted purposive sampling to include health care users and health care providers, representing a range of views across the public sector and voluntary sector. We employed the Nominal Group Technique (NGT) method for data collection. The NGT workshop was conducted in two consecutive phases: phase one was focused on determining barriers for men’s engagement with the current/facility-based HIV testing services; phase two was aimed at determining HIVST delivery strategies. We used the results of the NGT to design a tailored HIVST strategy for urban men in eThekwini District. Results: Participants identified the following psychological factors as the most important barriers to uptake of HIV testing services by urban men: stigma, ignorance about the importance of testing and testing process as well as fear of positive test results. Key stakeholders suggested internal motivation strategies as a potentially effective approach to support HIVST delivery strategy. Guided by the NGT results, we designed a HIVST delivery strategy that is supported by a risk communication approach Conclusion: We designed an evidence-based risk communication mobile health (mHealth) strategy coupled with SARS COV-2 self-testing tailored to improve men’s uptake of HIVST. A follow-up study to evaluate the feasibility of implementing these approaches is recommended.

Myocardial infarction (MI) is a serious cardiovascular disease that can lead to death. Cardiac troponin I (cTnI) is a biomarker of MI in the circulation system. For detection cTnI protein, many method suffer the same problem, time-consuming. Main drawbacks are time consuming, have tedious operation, require an expensive reader for translating signals, and require non-accessible reagents. Our goal is to create a kit for cTnI protein testing, that the result can easily be read by color difference. The main breakthrough is, the resolution between different concentration can be told by eyes. The result will be future used to create a commercial, potable, convenient, daily-used rapid-test kit. In this study, a cTnI biosensor is proposed that can be read by the naked eye, performs diagnosis based on the pattern color, does not require a reader machine, is easy to operate, and is portable. Our work proposed a device that shortens the diagnosis time, has a quantitative analysis range of 0.32 –200 ng/mL in the human serum matrix, has a 0.32 ng/mL limit of detection (LOD), and shows many advantages comparing to traditional cTnI ELISA plate.

Objective: Taiwan Government’s organizations have endeavored to promote the applications of big data and open data. The “My Health Bank” is one of the measures promoted by the National Health Administration, Ministry of Health and Welfare. This study proposes the perspective of the “value co-creation” with the attempt to extend the concept of service ecosystem and apply it on the platform of My Health Bank to examine whether people (patients, families, and caregivers) can promote their health literacy? Method: This cross-sectional study, with people that have registered at “My Health Bank” as subjects. Complying with the inclusion criteria, 401 questionnaires were delivered, with 391 valid ones, excluding those incompletely and inaccurately filled. Result: That the affecting factors of the co-creation of values: age, education level, annual income, and platform operation show to be significant ( p＜0.05); and gender, occupation, and resource exchange do not reach the significant level (p＞0.1). Conclusion: We found My Health Bank changed the inertia of “value creation” in the traditional medical value, it allows the traditional medical and healthcare industry to expose to the impacts of the mega trend of the internet, the transformation of the platform in a necessary trend.

Background: Early diagnosis of postoperative complications is an urgent task, allowing timely prescribing of appropriate therapy and reducing the cost of patient treatment. Prognostic models based on various data could help in the early diagnosis of postoperative complications after cardiac surgery. Objectives: The purpose of the study was to determine whether an integrated approach based on clinical data along with metabolites and biomarkers had greater predictive value than the models built on less data. Methods: The study included patients (n=62) admitted for planned cardiac surgery (coronary artery bypass grafting with cardiopulmonary bypass), who were retrospectively divided into two groups depending on the presence (n=26) or absence (n=36) of postoperative complications of all types. Clinical and laboratory data on the first day after surgery were analyzed. Additionally, patients' blood samples were collected before and on the first day after surgery to determine biomarkers (interleukin-6, procalcitonin, NT-proBNP, high-sensitivity troponin T) and metabolites (8 aromatic and 2 dicarboxylic acids were detected using gas chromatography-mass spectrometry). Results: Patients before surgery, compared with healthy donors, differed in the concentration of metabolites (p &lt; 0.05), and had concentrations of a number of biomarkers exceeding the corresponding reference values. Multivariate PLS-DA models, predicting the presence or absence of postoperative complications, were built using clinical data (ROC-AUC=0.71), concentrations of metabolites and biomarkers (ROC-AUC=0.60), and the entire data set (ROC-AUC=0.75). For comparison we built univariate models using the EuroScore2 (ROC-AUC=0.59) and SOFA (ROC-AUC=0.76) scales; concentrations of lactate (ROC-AUC=0.71), the dynamic changes of 4-hydroxyphenyllactic acid (ROC-AUC=0.69), and the sum of three sepsis-associated metabolites (ROC-AUC=0.70). The proposed complex model using entire data set was comparable to the SOFA scale, which confirms the expediency of searching for new predictive models based on a variety of factors.

Milk serves as a crucial source of natural bioactive compounds essential for human nutrition and health. The gastrointestinal digestion of milk proteins releases various biologically active peptides that positively impact human health and enhance physiological performance. With the growing production of cheese, Greek yogurt, and other dairy products, the volume of unutilized acid whey is significantly increasing. Acid whey, containing almost all whey proteins and approximately one-quarter of casein, presents a valuable raw material for generating peptides with potential health benefits. These peptides exhibit properties such as antioxidant, antimicrobial, anti-inflammatory, anticarcinogenic, antihypertensive, antithrombotic, opioid, mineral-binding, and growth-stimulating activities, contributing to improved human immunity and the treatment of chronic diseases. Enzymatic hydrolysis of milk proteins has been developed as a method to produce these peptides, facilitating their use in food fortification. To incorporate whey into functional beverages, it undergoes fermentation by lactic acid bacteria with proteolytic activity. To specifically enrich these beverages with peptides exhibiting targeted bioactivities, it is essential to select lactic acid bacteria strains possessing the requisite protease profiles. Additionally, the sensory properties of the final product can be enhanced using starter cultures with diverse metabolic capabilities, even in the absence of added flavoring agents. Given the imperative to develop waste-free technologies and enhance the profitability of the dairy industry, there is a growing need to efficiently utilize and transform acid whey into a broad spectrum of valuable products and food additives. This approach is justified not only by the nutritional benefits of the bioactive components in whey but also by the commercial potential of safe and health-enhancing products.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

In order to shorten the detection time and improve the average precision on embedded devices, A lightweight and high accuracy model is proposed for passion fruit in complex environments (backlight, occlusion, overlap, sunny, cloudy, rainy). Firstly, replacing the backbone network of YOLOv5 with a lightweight GhostNet model reduces the number of parameters and computation while improving detection speed. Secondly, a new feature branch is added to the GhostNet network, and the feature fusion layer in the neck network is reconstructed to effectively combine the lower-level and higher-level features, which not only improves the accuracy of the model but also maintains its lightweight. Finally, the knowledge distillation methods are used to transfer the knowledge from the more capable teacher model to the less capable student model, which significantly improving the detection accuracy. The improved model is denoted as G-YOLO-NK. The average accuracy of the G-YOLO-NK network is 96.00%, which is 1.00% higher than the original YOLOv5s model. Furthermore, the improved model size is 7.14MB, reduced to half of the original model, and the real-time detection frame rate is 11.25 FPS on the Jetson Nano. Compared to the state-of-the-art model, the proposed model outperforms them in terms of average precision and detection performance. The present work provides an effective model for real-time detection of passion fruits in complex orchard scenes, which can provide valuable technical support for the development of orchard picking robots and greatly improve the intelligence level of orchards.

The impact of interaction SS with MJO on rainfall along Java Island to East Nusa Tenggara has been studied using daily rainfall observation data from 2140 weather observation stations, which are also equipped with GSMaP, OLR, and ERA5 data. There were 61 SS events found, 17 during active MJO and 44 in inactive MJO. Rainfall increases more in the western study area when the active MJO and more in the eastern study area when the inactive MJO is due to SS. SS reduces rainfall in the Jakarta region, regardless of the activity or inactivity of the MJO. SS causes extreme rainfall to only occur in a small part of certain areas, so it tends to significantly reduce the possibility of extreme rainfall. In the southern part of the IMC, SS predominates over MJO in supporting increased water vapor transport. Large-scale synoptic circulations like the monsoon, SS, and MJO can interact with local land-sea wind circulation to produce spatiotemporal variability in rainfall on Java Island. Rainfall mostly increases in the afternoon and decreases in the morning when SS occurs, whether there is MJO or not. Convective instability analysis indicates that SS increases precipitation, most likely by lowering CIN and raising VIMFC.

The Simultaneous Localization And Mapping (SLAM) scanner is an easy and portable Light Detection And Ranging (LiDAR) data acquisition device. Its main output is a 3D point cloud covering the scanned scene. Regarding the importance of accuracy in the survey domain, this paper aims to assess the accuracy of two SLAM scanners: the NavVis VLX and the BLK2GO Scanner. This assessment is conducted for both outdoor and indoor environments. In this context, two types of reference data are used: the Total Station (TS) and the static scanner Z+F Imager 5016. To carry out the assessment, four comparisons are tested: cloud to cloud, cloud to mesh, mesh to mesh, and edge detection board assessment. However, the results of the assessments confirm that the accuracy of indoor SLAM scanner measurements (5 mm) is greater than that of outdoor ones (between 10 mm and 60 mm). Moreover, the comparison of cloud to cloud provides the best accuracy regarding direct accuracy measurement without manipulations. Finally, based on the high accuracy, scanning speed, flexibility, and the accuracy differences between tested cases, it is confirmed that SLAM scanners are effective tools for data acquisition.

In recent years, electroencephalogram (EEG) emotion recognition has emerged as a research hotspot in the field of artificial intelligence (AI). Despite advancements in EEG-based emotion recognition, room for enhancing performance persists due to EEG signal redundancy and limitations in feature extraction, leading to inefficient models and emotional information loss. To fully utilize EEG's emotional information and improve recognition accuracy while reducing computational costs, this paper proposes a Convolutional-Recurrent Hybrid Network with a dual-stream adaptive approach and an attention mechanism (CSA-SA-CRTNN). Firstly, the model utilizes a CSAM module to assign corresponding weights to EEG channels. Then, an adaptive dual-stream convolutional-recurrent network (SA-CRNN and MHSA-CRNN) is applied to extract local spatial-temporal features. After that, the extracted local features are concatenated and fed into a temporal convolutional network with a multi-head self-attention mechanism (MHSA-TCN) to capture global information. Finally, the extracted EEG information is used for emotion classification. We conducted binary and ternary classification experiments on the DEAP dataset, achieving 99.26% and 99.15% accuracy for arousal and valence in binary classification, and 97.69% and 98.05% in ternary classification, surpassing relevant algorithms. Additionally, the model's efficiency is significantly higher than other models, achieving better accuracy with lower resource consumption.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4,202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 27 for fiber length (FL), 16 for fiber strength (FS), 24 for micronaire (MC), 17 for fiber uniformity (FU), and 24 for fiber elongation rate (FE). Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosome D1 and D11. Each QTL contributed 1.98%–21.45% to the phenotypic variation (PV), including 13 major effect QTLs that contributed more than 10% toward PV. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18%–21.45% of PV, qFS-A11-1 in F2:3, F2:4 and F2:5 with 6.05%–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality.

Currently there are fewer depth models applied to pepper picking detection, while the existing generalized neural networks have problems such as large model parameters, long training time, and low model accuracy.In order to solve the above problems, this paper proposes a Yolo-chili target detection algorithm for chili pepper detection. First, the classical target detection algorithm yolov5 is used as a benchmark model, and an adaptive spatial feature pyramid structure combining the attention mechanism and the idea of multi-scale prediction is introduced to improve the model's detection effect on occluded peppers and small target peppers. Secondly, a three-channel attention mechanism module is introduced to improve the algorithm's long-distance recognition ability and reduce the interference of redundant testers. Finally, the quantized pruning method is used to reduce the model parameters and realize the lightweight processing of the model. Applying the method to the homemade chili pepper dataset, the AP value of chili pepper reaches 93.11%; the accuracy rate is 93.51% and the recall rate is 92.55%.The experimental results show that yolo-chili is able to achieve accurate and real-time pepper detection under complex orchards.

The temporary immersion system bioreactor named GreenTray®[2], [3]presents advantages over the existing ones. Firstly, there is no need to use forceps to move the shoots or plantlets in or out of the recipient, neither the use of scalpel to divide them. Secondly, the basis of the shoot can remain in the GreenTray® and can sprout again in several cycles of growth. These two characteristics reduce the costs in the process of micropropagation. Besides, shoots or plantlets development is enhanced by the aeration of the recipient, thus enriching with CO2 the recipient atmosphere. The chapter describes and provides images and values of interest in (1) the micropropagation process of some commercial Prunus or Pyrus rootstocks; (2) the plantlet growth under autotrophic conditions; and (2) the inoculation of plants with pathogens that reproduce in vitro the symptoms observed in vivo, using the GreenTray® bioreactor.

Aiming at the problems of inaccurate segmentation of long object and information loss of small object in real-time semantic segmentation algorithm, this paper proposes a lightweight multi-branch real-time semantic segmentation network based on BiseNetV2. The new auxiliary branch makes full use of spatial details and context information to cover the long object in the field of view. Meanwhile, in order to ensure the inference speed of the model, the asymmetric convolution is used in each stage of the auxiliary branch to design a structure with low computational complexity. In the multi-branch fusion stage, the alignment and fusion module is designed to provide guidance information for deep and shallow feature mapping, so as to make up for the problem of feature misalignment in the fusion of information at different scales, and thus reduce the loss of small target information. In order to further improve the model’s awareness of key information, a global context module is designed to capture the most important features in the input data. The proposed network uses NVIDIA GeForce RTX 3080 Laptop GPU experiment, on the road street view data set Cityscapes and CamVid average occurring simultaneously ratio reached 77.1% and 78.4% respectively, with running speed of 127 frames/s respectively and 112 frames/s. The experimental results show that the proposed algorithm can achieve real-time segmentation and improve the accuracy significantly, showing good semantic segmentation performance

Excess nitrogen in agricultural drainage poses a serious threat to the water quality safety of the Yellow River basin. Utilizing aquatic plants to modify the rhizosphere microbial community structure and facilitate nitrogen transformation is a crucial strategy for mitigating regional water eutrophication. Our results revealed that the denitrification rate (DR), dissimilatory nitrate reduction to ammonium rate (DNRAR) and nitrogen fixation rate (NFR) of rhizosphere sediments exhibited a significant increase in artificially cultivated ditch. Compared with those in natural ditches, the richness of the bacterial community and the relative abundances of Bacteroidota, Verrucomicrobiota, Firmicutes, Anaeromyxobacter and Geobacter, which are involved mainly in the nitrogen cycle, in the rhizosphere sediments of artificially cultivated ditch were significantly greater due to improvements in environmental conditions. In artificially cultivated ditch, the dominant functional genes affecting DRNARs in the rhizosphere sediments of P. australis were nrfC and nrfA, while DRs were driven mainly by norB and napA, which were influenced by the nitrogen and carbon levels; and the dominant functional genes affecting NFRs in the rhizosphere sediments of T. orientalis were nifD, nifK and nifH. Our results provide a scientific basis for the use of aquatic plants for mitigating excess nitrogen levels in agricultural drainage.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

In this paper we study a class of impulsive delayed neural networks with parameter uncertainties and reaction-diffusion terms. Using the properties of M-matrices and some inequality techniques, some sufficient conditions are derived to guarantee the global exponential stability of the given system. The results obtained are presented by simple algebraic inequalities, which are certainly more concise than previous methods. Finally, the validity and usefulness of our results are illustrated by arithmetic examples.

Pyrops candelaria is one of the common pests of fruit trees, but the research on the pathogenic microorganisms it may carry is very limited. Therefore, it is essential to reveal the pathogenic microbes it carries and their potential hazards. This study found a new virus from the transcriptome of P. candelaria, which was first reported in P. candelaria and named as PyCaV (Pyrops candelaria associated virus). RACE and bioinformatics assay revealed that the full-length of PyCaV is 10855 bp with the polyA tail, containing a single open reading frame (ORF) encoding a polyprotein consisting of 3171 amino acid (aa). The virus has a typical Iflavirus structure, including two rhv domains, a RNA helicase domain (HEL), a 3C cysteine protease domain (Pro), and a RNA-dependent RNA polymerase domain (RdRp). Further phylogenetic analysis revealed that this virus belongs to family Iflaviridae and sequence alignements analysis suggedted PyCaV is new member in unassigned genus of family Iflaviridae. Further in-depth analysis of virus-infection-part showed that PyCaV is distributing in the whole longan lanternfly, including its head, chest, and abdomen, but more PyCaV was identified in the chest. The distribution of PyCaV in different parts of P. candelaria was further explored, which showed that more PyCaV were detected in its piercing-sucking mouthparts and chest viscera. Statistical analysis showed that the PyCaV infection was affected by time and locations.

Apis mellifera, especially weak ones, are highly vulnerable to Carpoglyphus lactis mites, which can rapidly infest and consume stored pollen, leading to weakened colonies and potentially colony collapse. This study aimed to ascertain and investigate the prevalence of this mite in honeybee colonies across 9 provinces in the Republic of Korea (ROK). A total of 615 honeybee colonies were collected, from 66 apiaries during the spring and 58 apiaries during the summer of 2023. A 1,242 bp segment of the the Cytochrome c oxidase subunit 1 (COI) gene was amplified using the polymerase chain reaction method. The detection levels of C. lactis in the honeybees were compared between winter and summer. Based on the COI sequence analysis, the nucleotide sequence similarity of C. lactis mites isolated in the ROK with those from China (NC048990.1) was found to be 99.5%, and with those from the United Kingdom (KY922482.1) was 99.3%. This study is the first report of C. lactis in Korean apiaries. The findings in this study demonstrate a significantly higher detection rate in winter, which is 4.1 times greater than that in summer (p &lt; 0.001). Furthermore, the results underscore the usefulness of molecular diagnostic techniques for detecting C. lactis mites.

With the burgeoning growth of online retail, the issue of counterfeit products has become a significant threat to both consumer trust and brand integrity, posing challenges to sustainable market practices. Online retail platforms are promoted to redesign their channel structures and enhance brand traceability to tackle counterfeits using blockchain technology. To investigate the interactions between blockchain technology and the channel structures of online retail platforms, we design a game theory model incorporating a manufacturer with(out) blockchain participation selling products via an online retail platform that operates an agency channel and/or a reselling channel. We show that the critical trade-off of blockchain participation comprises the brand assurance effect of the blockchain, the channel competition intensification effect, and the blockchain adoption cost. The platform is capable of strategically designing the channel structure to encourage (while discouraging) blockchain participation by the manufacturer. Our analysis highlights the complementarity between blockchain participation and the channel structure. Furthermore, the effect of the consumer’s belief in the reselling channel, the commission fee in the agency channel, and the substitutability between channels are investigated in depth. The research provides valuable insights for online retail platforms and policymakers seeking to foster a sustainable and trustworthy e-commerce ecosystem.

In this paper, we extend the KdVSKR equations in (1+1)-dimension and (2+1)-dimension to fractional KdVSKR equations with modified Riemann-Liouville derivative. The (2+1)-dimensional KdVSKR equation, which is a recent extension of (1+1)-dimensional KdVSKR equation, can model the resonances of solitons in shallow water. By means of the Hirota bilinear method, finite symmetry group method and consistent Riccati expansion method, many new interaction solutions have been derived. Soliton-cnoidal interaction solution of the (1+1)-dimensional fractional KdVSKR equation has been derived for the first time. For the (2+1)-dimensional frac-tional KdVSKR equation, two-wave interaction solutions and three-wave interaction solutions, including dark-soliton-sine interaction solution, bright-soliton-elliptic interaction solution, and lump-hyperbolic-sine interaction solution, have been derived. Impact of the fractional order on the shapes of these solutions has been illustrated by figures. Three-wave interaction solutions of fractional systems have not been reported in the existing references. The research idea in this paper can be applied to other fractional differential equations.

COX II containing a dual core CuA active site is one of the three core subunits of mitochondrial Cco, which plays a significant role in the physiological process. In this report, the full-length cDNA of COXⅡ gene was cloned from Sitophilus zeamais, which had an ORF of 684 bp encoding 227 amino acids residues. The predicted COXⅡ protein had a molecular mass of 26.2 kDa with pI value of 6.37, and multiple sequence alignment and phylogenetic analysis indicated that Sitophilus zeamais COXⅡ had high sequence identity 78.51% with the COXⅡ of other insect species, especially similarity to sitophilus oryzae. This gene was subcloned into the prokaryotic expression vector pET-32a, and induced by IPTG in E.coli Transetta (DE3) expression system. Finally the COXⅡ with 6-His tag was purified using affinity chromatography with Ni²⁺-NTA agarose. WB showed the recombinant COXⅡ was about 44 kD, and the concentration of fusion protein was 50μg/mL. UV-spectrophotometer and infrared spectrometer analysis showed that recombinant COXⅡ could catalyze the oxidation of substrate Cytc, and influenced by AITC. It was found that AITC could form a hydrophobic region with COXⅡ protein via molecular docking, besides, a sulfur atom of AITC structure could form a length of 2.9 Å hydrogen bond with Leu-31. These results will provide valuable information for elucidating the role of COXⅡ in Sitophilus zeamais responses to AITC, meanwhile, it will helpful to carry out a point mutation in AITC binding sites for the future research.

The properties of the annual, semiannual and triennial oscillations (AO, SAO and TO) in the middle atmosphere have been investigated using the TIMED/SABER temperature data. The Lomb-Scargle and wavelet spectra were used to determine the dominant oscillations in the background temperature field. The AO is prominent at the mid-latitudes. The AO amplitudes present an asymmetry between the two Hemispheres, being larger in the mesosphere than in the stratosphere. The SAO dominates the tropical regions, with three amplitude maxima at altitudes of 45, 75, and 85 km. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K at each equinox, contributing to the lower mesospheric inversion layer. The TO is significant in the tropical region, with amplitude being maximum at 35, 45 and 85 km. Result shows that there may be potential interaction by the TO with SAO at 85km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The real origin of the TO may lie in the wave-mean-flow interaction.

As the world population grows, fulfilling the need for biomaterials in the healthcare system becomes increasingly important. Biomaterials, which include metals, polymers, ceramics, and composites, play an important role in the creation of medical devices that improve people's lives. The European Society for Biomaterials described biomaterials as non-biological materials used in medical devices to interact with biological systems. This definition has developed to encompass materials that treat, assess, or replace tissues or bodily functions. Biocompatibility, as defined by the FDA, is a key feature of biomaterials, as is the requirement to fulfil design requirements such as mechanical performance, geometry, and electrical control. Over the last decade, advances in regenerative medicine and tissue engineering have boosted biomaterials' usage in medical applications dramatically. Despite its promise, scientists, engineers, and physicians continue to face significant challenges due to the complexity of biomaterials. Biomaterials have various benefits, including biodegradability, non-toxicity, and biocompatibility, making them extremely useful for replacing, sustaining, or improving biological activities in damaged tissues. They are used in a wide range of applications, including tissue engineering implants, human tissue healing and regeneration, medication delivery systems, and biosensors. This study gives insights into the fundamental characteristics, case studies, and ethical issues associated with the usage and use of biomaterials, further examining their potential and significance in healthcare and medicine.

The paper describes the new method for image compression based on coordinated group signal transformation. The algorithm is a type of difference coding. Coordinated processing significantly simplifies the difference signal conversion scheme using a single group codec for all signals. The described method considers color channels as correlated signals of a multi-channel communication system. The specifics of the processed data required modification of the coordinated group processing algorithm. First, we changed how to calculate the difference signals to prevent data loss. Secondly, the group codec was supplemented with a neural network to improve the quality of reconstructed images. We considered the following types of neural networks: fully connected, recurrent, convolution, and convolution in the Fourier space. Based on the simulation results, it is best to use fully connected neural networks if the goal is to minimize processing delay time. These networks have a response time of 13 ms. On the other hand, if the priority is to improve quality in cases where delays are not critical, then convolution neural networks in the Fourier space should be used. These networks have a response time of 140 ms and are of significant interest.

In electromagnetic ultrasonic testing, it is difficult to recognize small-size bottom cracks by time of flight (ToF), and the lift-off fluctuation of the probe affects the accuracy and consistency of the inspection results. In order to overcome the difficulty, a novel EMAT (electromagnetic acoustic transducer)-PEC (pulse eddy current) composite sensor is designed. We use amplitude of bottom echo recorded by EMAT to identify the tiny bottom crack as well as the amplitude of PEC signals picked up by the integrated symmetric coils to measure the average lift-off of the probe in real time. Firstly, the effects of lift-off and bottom cracks on amplitude of bottom echo are distinguished combining the theoretical analysis and finite element method (FEM). And then an amplitude correction method based on the fusion of EMAT and PEC signals is proposed to reduce the impact of lift-off on the defect signal. The experimental results demonstrate that the designed composite sensor can effectively detect the bottom crack as small as 0.1mm* 0.3mm. The signal fusion method can accurately correct the amplitude of defect signal and the relative error is less than ±8%.