In an era characterized by rapid technological advancements, economic fluctuations, and global competition, adaptability and resilience have become critical success factors for businesses navigating uncertainty and complexity. This article explores the role of enterprise agility in today’s business landscape at Latam branch of Tata Consultancy Services (TCS), where organizations face complex and diverse operations. We aim to examine how companies can become more agile in the face of emerging challenges and seize opportunities swiftly to drive growth and deliver value. Since 2014, the division has embarked on an agile transformation journey to drive growth, deliver value, foster innovation, and build resilience in an increasingly dynamic environment. We scrutinize an approach to measuring and enhancing enterprise agility, employing statistical analysis and continuous improvement methodologies to tackle real-world challenges while offering valuable insights and recommendations for organizations aiming to implement similar systems. The results of an agile transformation in a certain company’s Latam branch serve as a compelling case study, demonstrating how the implementation of targeted measures and continuous improvement can significantly bolster enterprise agility. Methodologically, our work applies a novel sequence of parametric statistical tests which, to the best of our knowledge, have not been used in the industry to validate the results of business agility metrics. In future work, we aim to create a new workflow considering non-parametric tests to address data with other statistical distributions. We conclude our work by proposing a sequence of steps for organizations to implement business agility metrics.

Digital transformation can become a complex process when workers have insufficient skills, which makes training in the digital field essential. Herein, we intended to relate digital literacy perceived by workers with their training needs for the Portuguese public sector context. Additionally, based in the Human capital theory, we also investigate which professional/demographic characteristics increase training propensity in digital fields. Through an online questionnaire, a dataset with information on 573 workers was obtained. Data analysis was made by using a probabilistic regression model and additional statistical techniques. The results revealed that workers with higher levels of education and higher professional skills have higher probability of participating in training in the digital field. On average, workers reveal low levels of digital knowledge and low participation in training in the digital fields, but the majority present a willingness to participate in future training sessions, especially in the fields of Dataset management, Cybersecurity and Communication systems. This study provides information on training in the digital field of workers in the public sector, which is essential for public organizations to better prepare for digital transformation. Additionally, it contributes to a very recent literature on digital learning, and it can be extended to other contexts.

In this non-exhaustive review, we discuss the importance of invariant vectors in atomic physics, such as the Laplace-Runge-Lenz vector, the Redmond vector in the presence of an electric field, the Landau-Avron-Sivardière vector when the system is subject to a magnetic field, and the supergeneralized Runge-Lenz vector for the two-center problem. Application to Stark and Zeeman effects are outlined. The existence of constants of motion in the charge-dyon system is also briefly mentioned.

This study examines the unique circumstances surrounding state-owned equity participation in non-state-controlled enterprises in China. Specifically, this study examines the impact of state-owned equity participation on the environmental, social, and governance (ESG) performance of non-state-controlled enterprises. Focusing on A-share listed firms on the Shanghai and Shenzhen Stock Exchanges and using data from 2013 to 2021, empirical testing shows that state-owned equity participation can significantly improve the ESG performance of non-state-controlled enterprises, with this conclusion remaining reliable after a series of robustness tests. Top management incentives is a mediating mechanism for state-owned equity participation in enhancing ESG performance. This study also finds that when state-owned equity participates in large enterprises or companies with a high degree of digital transformation, the effect on ESG performance is greater than that of small to medium-sized enterprises (SMEs) or enterprises with a low level of digital transformation. The findings of this study add to the current body of the existing field of research on the factors influencing corporate ESG performance and the impact of state-owned equity on corporate non-financial performance.

The paper examines common elements between Lévai’s and Milson’s potentials obtained by Liouville transformations of two rational canonical Sturm-Liouville equations (RCSLEs) with even density functions which are exactly solvable via Jacobi polynomials in a real or accordingly imaginary argument. We refer to the polynomial numerators of the given rational density function as ‘tangent polynomial’ (TP) and thereby term the aforementioned potentials as ‘e-TP’ A special attention is given to the overlap between the two potentials along symmetric curves which represent two different forms of the Ginocchio potential exactly quantized via Gegenbauer and Masjed-Jamei polynomials respectively. Our analysis reveals that the actual interconnection between Lévai’s parameters for these two rational realizations of the Ginocchio potential is much more complicated than one could expect based on the striking resemblance between two quartic equations derived by Lévai for ‘averaged’ Jacobi indexes.

With the advancement of the economy and society, policymakers acknowledge the significance of improving rural households' well-being as a crucial factor in promoting sustainable economic and social development. Based on the matching data of China Household Finance Survey and Digital Rural County Index, this study empirically examines the effect and mechanisms of digital village construction on subjective well-being of rural households. The results revealed that digital village construction has a significant improvement in their subjective well-being. The impact of digital village construction is particularly significant in rural areas located in the western regions of China, as well as among households possessing higher levels of human capital. The process through which digital village construction enhances the subjective well-being of rural households involves the augmentation of household income, the promotion of non-farm employment opportunities, and the enhancement of rural governance. This study provides robust micro-empirical evidence highlighting the positive welfare effects of digital rural construction. This study provides insights into the digital village construction within the happiness economy framework, offering a new perspective. The imperative to strengthen rural digital infrastructure and improve farmers' proficiency in modern information skills is a strategic policy aimed at enhancing well-being of rural households.

The theory of special relativity has reexamined and reconstructed the concepts of space and time, which are indispensable for describing physical laws, consequently instigating a major revolution in physics in general. Although the correctness of the special theory of relativity has been con-firmed by many observations and experiments, it is unclear why the "principle of relativity" and the "principle of the constant speed of light," which form the basis of the idea, are valid. Moreo-ver, although special relativity has advanced our understanding of time, our understanding of the fundamental question, "What is time?" is still limited. The theory of special relativity regards space as a four-dimensional construct consisting of one-dimensional time and three-dimensional space. This paper proposes an alternative framework, wherein real space is uniform and isotropic four-dimensional space, and elementary particles are waves that propagate through this four-dimensional space at a constant speed. This new perspective provides evidence to support two of Einstein’s key principles—the "principle of relativity" and the "principle of the constant speed of light." Furthermore, this model clarifies what time is and why time flows at a constant rate from the past to the future.

The complex adaptive systems (CAS) research study investigates into the theoretical link of a sustained economic growth as a critical pathway to lift people out of poverty and improve their quality of life. The results show a left-skewed global behavior of an economy-driven human development of 189 countries with 20% or 27 countries obtaining low human development; 80% or 162 countries obtaining medium to very high human development of which 21.16% or 39 countries with medium HDI, 53 or 28.04% or 53 countries with high HDI, and 31.22% or 59 countries with very high HDI. Using the Log (GDP) for visual transformation, closer investigation into the scatterplot diagram reveals that there are also bimodal patterns where countries in the high amplitude and low amplitude groups obtained different human development outcomes despite less or more on economic growth variances mirror on the government policy priorities resulting in four differentiating conditions. Very few countries experience virtuous cycles where both growth and human development are successful; few countries with vicious cycles where both are weak; and many countries with lopsided conditions where the economy is strong but human development is weak, or conversely ones where human development is strong but the economy is weak. The global pattern of economy and human development illustrated by an upward sinusoid or sine wave refutes the conventional linear approach. Uniquely and most importantly, the sinusoidal wave illustrates a decreasing amplitude and decreasing periods as countries manifest apparently complex behaviors that emerge as a result of often nonlinear spatio-temporal interactions among a large number of component systems at different levels of organizations and governments leading to an emergence of a behavior characterizing of a complex adaptive system.

In this paper, we propose an imagined speech-based brain wave pattern recognition using deep learning. Multiple features were extracted concurrently from eight-channel Electroencephalography (EEG) signals. To obtain classifiable EEG data with fewer number of sensors, we placed the EEG sensors on carefully selected spots on the scalp. To decrease the dimensions and complexity of the EEG dataset and to avoid overfitting during the deep learning algorithm, we utilized the wavelet scattering transformation. A low-cost 8-channel EEG headset was used with MATLAB 2023a to acquire the EEG data. The Long-Short Term Memory Recurrent Neural Network (LSTM-RNN) was used to decode the identified EEG signals into four audio commands: Up, Down, Left, and Right. Wavelet scattering transformation was applied to extract the most stable features by passing the EEG dataset through a series of filtration processes. Filtration has been implemented for each individual command in the EEG datasets. The proposed imagined speech-based brain wave pattern recognition approach achieved a 92.50% overall classification accuracy. This accuracy is promising for designing a trustworthy imagined speech-based Brain-Computer Interface (BCI) future real-time systems. For better evaluation of the classification performance, other metrics were considered, and we obtained 92.74%, 92.50% and 92.62% for precision, recall, and F1-score, respectively.

Elastic properties of materials and their changes with temperature are important for their applications in engineering. A study on the influence of phase composition of AISI 4130 alloy on Young's modulus (Ed), shear modulus (Gd), and damping (Q-1) was carried out by Impulse Excitation Technique (IET). The material characterization was carried out using confocal microscopy, XRD, MET, HV, and dilatometry. A stable structure, composed of ferrite (BCC) and pearlite (α-Fe+Fe3C), was obtained by annealing. Metastable structure of martensite (BCT) was obtained by quenching. The Ed, Gd, and Q-1 were measured, varying the temperature from RT to 900 °C. The values of Ed and Gd, at RT, were determined as 201.5 and 79.2 GPa (annealed), and 190.13 and 76.5 GPa (quenched), respectively. In the annealed steel, the values Ed and Gd decrease linearly on heating up to 650 °C, with the thermal expansion. In the quenched steel, weak changes in the dilatometric curve, Ed, Gd, and Q-1, in the range of 350-450 °C, indicated decompositions of the martensitic phase. Sharp decrease in the moduli and high peak of Q-1, was observed for both samples around 650-900 °C, revealing low lattice elastic stability of the phases during transformations α(BCC)+Fe3C↔γ(FCC).

In this paper, a new method by combining cold drawing and martensitic transformation was proposed to produce ultrahigh-strength steel wire, and the effect of austenitizing heating rate on microstructure and mechanical properties was studied. Compared with Muffle furnace heating, salt bath heating has a much higher austenitizing heating rate, which is beneficial to obtain ultrafine-grained martensite for steel wire with a larger section. By salt bath hardening and low-temperature tempering, an ultrahigh strong (strength of 2.48 GPa) and tough (elongation of 6.0%) steel wire was produced. Moreover, to explore whether is it possible to replace long-time low-temperature tempering with short-time tempering at elevated temperatures to improve the tempering efficiency, the effect of tempering time on the evolution of microstructure and mechanical properties of the steel wires tempered at 350 °C was systematically studied. The results demonstrate that tempering at 350 °C for 30 s can endow the steel wire with comparable mechanical properties to that of the one tempered at 250 °C for 2 h. With tempering time prolonging, the strength decreases gradually with the precipitated phase transition from χ-Fe5C2 carbide into θ-Fe3C carbide and coarsening, which plays a major role in the strength decrease.

Bacterial transformation is the essential tool for introducing foreign DNA into bacterial cells in a host of recombinant technology applications useful for biomanufacturing and drug production. Thus far, chemically competent cells remain an important enabling technology for bacterial transformation given its facile transformation approach. However, many parameters affect transformation efficiency, and there is relatively little documentation of their cross-interacting effect in the literature. This work explores the roles played by incubation time on ice, competent cell concentration, and plasmid-to-cell ratio on transformation efficiency in Escherichia coli DH5α. Results revealed that increases in incubation time improve transformation efficiency, but 2 minutes incubation still yield appreciable efficiency. On the other hand, low concentration competent cells (10⁶ CFU/mL) yielded significant improvement in transformation efficiency compared to high concentration competent cells (10⁸ CFU/mL). In terms of plasmid-to-cell ratio, higher ratio increases transformation efficiency. Overall, bacterial transformation is incompletely understood particularly in the area of cross-interacting parameters. Experiments reported here revealed the possibility of short duration transformation where lower competent cell concentration and higher plasmid-to-cell ratio could improve transformation.

The search for growth and sustainability in any organization largely depends on its ability to carry out digital transformation and agility processes. These processes are essential to adapt to an increasingly changing and competitive business environment, allowing companies to be more efficient and effective in creating an unbreakable bond with their customers. This manuscript addresses the importance of detecting and eliminating anti-patterns in organizational culture for a successful digital and agile transformation. During the early stages of the transformation process, prejudices and paradigms rooted in the organization can become an obstacle to change. The goal of this writing is to offer a practical guide for leaders and teams in organizations seeking successful cultural transformation. Effective strategies are proposed to overcome the challenges faced by organizations during this early stage. In summary, the key steps to be followed in the initial stages of digital transformation with agility are described, including the importance of establishing strong leadership, defining a clear vision and scope of the transformational process, among others. A set of recommendations will be provided to overcome recurring anti-patterns, such as lack of stakeholder participation and commitment, lack of proper planning, and confusion of roles and responsibilities.

This paper introduces extensions H4,p and X8,p of Horn’s double hypergeometric function H4 and Exton’s triple hypergeometric function X8, taking into account recent extensions of Euler’s beta function, hypergeometric function, and confluent hypergeometric function. Among the numerous extended hypergeometric functions, the primary rationale for choosing H4 and X8 is their comparable extension type. Next, we present various integral representations of Euler and Laplace type, Mellin and inverse Mellin transforms, Laguerre polynomial representation, transformation formulae and a recurrence relation for the extended functions. In particular, we provide a generating function for the X8,p and several bounding inequalities for the H4,p and X8,p.

Industrial nameplates serve as a means of conveying critical information and parameters. In this work, we propose a novel approach for rectifying industrial nameplate pictures utilizing a probabilistic Hough transform. Our method effectively corrects for distortions and clipping, and features a collection of challenging nameplate pictures for analysis. To determine the corners of the nameplate, we employ a progressive probability Hough transform, which not only enhances detection accuracy but also possesses the ability to handle complex industrial scenarios. The results of our approach are clear and readable nameplate text, as demonstrated through experiments that show improved accuracy in model identification compared to other methods.

Abstract Most Asian countries like South Korea have transformed themselves from poor agrarian nations into one of the fastest-growing industrialized economies in the world. Rural transformation poses great challenges to rural people and areas, but also it also provides great opportunities for sustainable rural development. The evolution of South Korea's rural policies is embedded through the different national institutions with different sectors. Diversification of rural economic opportunities may further extend to the industries for economic development in rural regions alongside efforts to improve living. Examining the rural transformation in South Korea, mainly the rural development with land, agriculture, truism, politic,s and strategy they used that shaped the structure of the rural transformation and its activities over time and Ethiopia takes lessons is the objective of the study. Document analysis is a tool for achieving information. Ethiopia takes lessons from South Korea from the general sector of rural development to the particular agricultural development sector, rural truism development, land reform which is the core asset for the world people, health care reform, and market and trade transformation (indicates that the base for developed country development was trade reform from import to export), rural job employment transformation (which have the multidimensional impact to the development of nation) and rural political transformation are the basic areas of rural transformation in which Ethiopia focused to do. The country can grow with the integrated/ collaborative work of the stakeholders. The government of Ethiopia applying a functional regional strategy to shape the socio-economic and cultural changes of the rural people and working with civil societies and other non-governmental stakeholders must be the primary tasks

First came the digital banks without offices, and then the “fintech” companies that combined technology and finance to achieve greater efficiency and new business models. Later was the turn of transport and logistics, understood as the sector whose economic activities derived from the transport of people and goods, while on the one hand, it has had a new spring thanks to factors such as online sales. Then, perhaps catalyzed by the pandemic scenario, the turn has reached education, where years ago was only a complement of traditional education, now is a central part with multiple modern methodologies. Numerous studies exist about using or implementing these e-learning procedures, but technical analysis is barely found in references. This work aims to analyze the digital transformation of the main sectors of our society, including finances, transport, and education, together with several examples of how technology was helping to fight the pandemic scenario.

The present paper introduces a method of basis transformation of vector fields that is specifically applicable to polynomials space and differential equations with certain polynomials solutions such as Hermite, Laguerre and Legendre polynomials. The method based on separated transformation of vector space basis by a set of operators that are equivalent to the formal basis transformation and connected to it by linear combination with projection operators. Applying the Forbenius covariants yields a general method that incorporates the Rodrigues formula as a special case in polynomial space. Using the Lie algebra modules, specifically , on polynomial space results in isomorphic algebras whose Cartan sub-algebras are Hermite, Laguerre and Legendre differential operators. Commutation relations of these algebras and Baker-Campbell-Hausdorff formula gives new formulas for special polynomials

Novel strategies in coastal protection are needed to cope with climate change-induced sea level rise. They aim at the sustainable development of coastal areas in light of an intensification and land use changes. A promising approach is the design of nature-based solutions (NbS), complementing the safety levels of technical infrastructures. However, NbS lack a widespread and large-scale implementation. To address this deficit, co-design concepts are needed that combine experiences from science and practice. This work presents and discusses the approach of a coast-specific real-world laboratory (RwL) addressing the inclusive design of ecosystem-based coastal protection. Strategies of RwLs are applied for the first time in a coastal context along the North Sea coastline in Germany. We found the concept of RwLs suitable for coastal transdisciplinary research, although adaptions in the spatial reference level or flexibility in location and time of experimentation are necessary. A profound actor analysis is indispensable to specify participatory processes and interaction levels. A criteria-based cooperative selection of RwL sites helps to reveal and solve conflicting interests to achieve trust between science and practice. Addressing site-specific characteristics and practitioners’ needs, our coastal RwL provides a mutual learning space to develop and test NbS to complement technical coastal protection.

In recent years, Chinese manufacturing enterprises compete to chase the wave of "digital revolution", digital empowerment has become an important strategic path of technological reform for many manufacturing enterprises. Based on the micro data of listed companies, this paper investigates the impact of digital transformation of Chinese listed companies on the quality of their export products. It is found that digital transformation can significantly improve the quality of enterprises' export products. After a series of robustness tests, this conclusion is still valid, and there are two ways to improve innovation performance and total factor productivity. The export product quality enhancement effect of enterprise digital transformation also has the heterogeneity of ownership, region and industry. In the further study, this paper also examines the impact of digital transformation on the internal salary gap of enterprises, and finds that digital transformation may increase the internal salary gap of enterprises, and form a "masking effect" on the quality of export products. To a certain extent, this paper deepens the understanding of the study of enterprise digital transformation on the quality of export products and its differences, and provides certain guidance for enterprises to implement the strategy of digital transformation.

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

In order to counter the impending shortage of skilled professionals in the aging societies of our time in many western countries such as Germany, solutions for business and society are urgently needed. Here, artificial intelligence (AI) can play an important role in mitigating the problem with the help of diverse applications. At the same time, it is important to consider both the needs of the respective employee1 and the company to ensure that the use of AI has a positive impact on the organization and finds social acceptance. In this article, we describe the newly developed OSQE model (Optimize, Secure, Qualify, Expand), which for the first time outlines an AI cycle against the shortage of skilled professionals in a holistic approach that focuses equally on people and companies. This can serve organizations as a guide for strategy development, decision-making for and implementation of AI-supported measures in an entire cycle of an employee's affiliation with a company. The model takes three driving forces into account: companies, professionals, and AI applications. In the model, the measures to be implemented are prioritized with ascending numbering based on what would be most urgent for a company to implement. All measures relate to areas of action that place people at the center and can be assigned to the classic cycle of belonging of an employee in the company. In this regard, the opportunities that AI offers to professionals and companies are highlighted.

This study aims to determine the role of Industry 4.0 sensors in digital transformation. Using a systematic literature review with a bibliometric analysis, we examine a sample of 52 studies from the SCOPUS database to identify research activity on this topic until December 2022. We find that 2022 was the year with the highest number of peer-reviewed documents on the subject, with 18 publications. We also examine current themes and find that sensors can connect multiple systems and devices, thus enabling machine-to-machine communication and facilitating great precision during product designing, development, and production, thus enabling customization and improving quality. However, despite these benefits, the current sensor technologies face multiple challenges that undermine their maximum adoption.

Digital transformation of companies is often referred to as a future track and a strategic path towards ensuring the survival and sustainability of companies. In this paper, we aim to outline this transformation process in Tunisian companies and identify its driving factors and finally explain its key success factors. To this end, we examine a sample of 70 companies operating in all economic sectors. The results indicate that such a digital strategy has a significant and a positive effect on the success of digital transformation of companies. Leadership has an effect at a low level of digital maturity. On the other hand, corporate culture does not have a significant effect on digital transformation. These results contribute to explaining this emerging phenomenon by focusing on the driving factors as well as the factors that contribute to its success.

Digital federated platforms and data cooperatives for secure, trusted and sovereign data exchange will play a central role in the construction industry of the future. With the help of platforms, cooperatives and their novel value creation, the digital transformation and the degree of organization of the construction value chain can be taken to a new level of collaboration. The goal of this research project was to develop an experimental prototype for a federated innovation data platform along with a suitable exemplary use case. The prototype is to serve the construction industry as a demonstrator for further developments and form the basis for an innovation platform. It exemplifies how an overall concept is concretely implemented along one or more use cases that address high-priority industry pain points. This concept will create a blueprint and a framework for further developments, which will then be further established in the market. The research project illuminates the perspective of various governance innovations to increase industry collaboration, productivity and capital project performance and transparency as well as the overall potential of possible platform business models. However, a comprehensive expert survey revealed that there are considerable obstacles to trust-based data exchange between the key stakeholders in the industry value network. The obstacles to cooperation are predominantly not of a technical nature, but of a competitive, predominantly trust-related nature. To overcome these obstacles and create a pre-competitive space of trust, the authors therefore propose the governance structure of a data cooperative model, which is discussed in detail in this paper.

Lamb waves occur in thin-walled structures in two wave modes, the symmetric and antisymmetric mode. Their oscillation on the structures‘ surfaces is either in phase (symmetric) or shifted by a phase angle of π (antisymmetric). In this work, a method is developed to compare the surfaces‘ oscillation phase relation. It is based on the evaluation of time signals regarding the instantaneous phase angle using the continuous wavelet transformation and as a comparative method the short-time Fourier transformation. For this purpose, numerical simulations utilizing the finite element method provide time signals from the top and bottom surface of different thin-walled structures. They differ with respect to their material settings and laminate configurations. The numerically obtained time signals are evaluated by the developed methods. The occurring oscillation phase differences on the top and bottom surface are studied and both methods are compared. Subsequently, the oscillation phase is evaluated experimentally for the wave propagation in a fiber metal laminate. It is shown that the method based on the continuous wavelet transformation is suitable for the evaluation of oscillation phase relations in time signals. Additionally, it is proven that fiber metal laminates show only two phase relations which indicates the occurrence of Lamb waves.

The present-day financial system is being influenced by the rapid development of Fintech (financial technologies), which are technologies created to improve and automate traditional forms of finance for businesses and consumers. The topic of Fintech as a financial disruptor is gaining popularity in line with the swift spread of digitalization across the banking industry, whereby this paper contributes to the field by presenting a novel bibliometric analysis of academic literature related to Fintech as a financial disruptor. The analysis is based on metadata extracted from the Scopus database through the VOSviewer and Biblioshiny software. The bibliometric analysis of 363 documents identified the most impactful sources of publication, keywords, authors, and most cited documents on the topic of Fintech as a financial disruptor. As our analysis demonstrates the number of publications on the given topic increases, defining both the interest among academia and potential for future research.

As China put forward its “carbon emissions peak and carbon neutrality” goals, how to achieve carbon reduction had become a key for China’s goal. The manufacturing industry is an important source of carbon dioxide emissions. For a manufacturing country like China, adjustments in various aspects of the industry would have a huge impact on carbon emissions. As an important reform of contemporary production mode, the process of production automation in China will inevitably affect China's carbon emissions. Therefore, the analysis of the impact of production automation on carbon dioxide emissions was an important basis for judging the future carbon reduction in China. Refer to the traditional study of carbon Kuznets curve, this paper analyzed the impact of average wage on production automation and the role of production automation in the carbon Kuznets curve(CKC). This paper proposed that production automation plays a mediating role in the process of carbon emissions, and gives a verification model of the mediating role. By analyzing the relationship between average wage and production automation process, the U-shaped curve relationship between them was verified. By examining the relationship between carbon dioxide emission data and production automation industry in China, we verified that production automation plays a partial mediating role in the change of carbon Kuznets curve. Combined with the analysis of the two parts, this paper believed that with the continuous development of China's intelligent manufacturing industry, China's carbon reduction prospects were more optimistic, and there was a good industrial foundation to achieve the “carbon peaking and carbon neutrality” goals. Finally, this paper proposes policy suggestions as increase research investment in production automation, help promote the application of production automation, encourage the research and application development of low-carbon technology, especially encourage modular design, so as to give full play to the role of production automation in the process of carbon neutrality in China.

It has been proposed that tumourigenicity was an intrinsic feature of embryonic/germ cell developmental axis as well as embryonic/germ cell-related genes play a crucial role in tumourigenicity. Our previous studies indicated that primordial germ cell (PGC)-like potential could be reactivated in tumourigenesis. In this study, 4T1, 168FARN and 67NR cells which originated from the same mouse breast cancer were studied and the results indicated that the acquisition of embryonic/germ cell-like state is essential for tumourigenicity. We further demonstrated that somatic to PGC-like transformation (SPLT) was activated in 4T1 cells and that inhibition of PGC-like cell formation by depleting pluripotency and/or PGC specification-related genes markedly repressed SPLT and the tumourigenicity. Collectively, our findings reveal that tumourigenicity is linked to the acquisition of PGC-like state through SPLT in 4T1 cells, provide new insight into deeper understanding the biological nature of tumours and novel therapeutical strategies for cancer targeting.

This work investigates how integrated polyimide inlays with applied sensor bodies influence the guided ultrasonic wave propagation in narrow glass fiber-reinforced polymer specimens. Preliminary numerical simulations indicate that in a damping-free specimen, the inlays show reflections for the S0-mode propagation. Hence, an air-coupled ultrasonic technique and a 3D laser Doppler vibrometer measurement are used to measure different parts of the propagating waves’ displacement field after burst excitation at different frequencies. No significant reflections on the inlay can be seen in the experiments. However, it is shown that the reflections from the strip specimen’s narrow width cause periodical reflections that superimpose with the excited wave fronts. A continuous wavelet transformation in the time-frequency domain filters discontinuities from the measurement signal and is used for reconstruction of the time signals. The reconstructed signals are used in a spatial continuous wavelet transformation to identify the occurring wavelengths and hence to prove the assumption of reflections from the narrow edges. Since the amplitude of the reflections identified in the numerical data at the polyimide inlays are an order of magnitude smaller than the excited wave packages, it is concluded that material damping of the epoxy resin matrix extincts possible reflections from the inlays.

Brain tumors are abnormal cells growth in the brain tissues that can be cancerous, or not. In any case, they could be a very aggressive disease that should be detected as early as possible. Usually, magnetic resonance imaging (MRI) is the main tool commonly adopted by neurologists and radiologists to identify and classify any possible anomalies present in the brain anatomy. In the present work, an automatic unsupervised method called Z2-$\gamma$, based on the use of adaptive finite-elements and suitable pre-processing and post-processing techniques, is introduced. In particular, the proposed methodology is able to automatically classify whether a given MR image represents a healthy or a diseased brain and in this latter case, is able to locate the tumor area.

The article is devoted to algebraic modeling of universal rules of stochastic organization of genomic DNA of higher and lower organisms, previously published by the author. The proposed algebraic apparatus, which uses formalisms of quantum mechanics and quantum informatics and which is based on the so-called tensor-unitary transformations of vectors that generate families of interrelated stochastic-deterministic vectors of increased dimensions. The features of the vectors' interconnections in these families model the stochastic-deterministic properties of the named phenomenological rules. There are new approaches to modeling of developing multi-parameter biosystems, whose number of parameters increases in the course of step-by-step development. In the light of the presented materials, the issues of fractal-like organization in genetically inherited biosystems are considered. The development of the theory of stochastic determinism as an antipode of deterministic chaos is discussed.

Real-world optimization problems are often gov- erned by one or more constraints. Over the last few decades, extensive research has been performed in Constrained Opti- mization Problems (COPs) fueled by advances in computational power. In particular, Evolutionary Algorithms (EAs) are a preferred tool for practitioners for solving these COPs within practicable time limits. We propose a novel hybrid Evolutionary Algorithm based on the Differential Evolution algorithm and Adaptive Parameter Gaining Sharing Knowledge-based algo- rithm to solve global real-world constrained parameter space. The proposed CHAGSKODE algorithm leverages the power of multiple adaptation strategies concerning the control parameters, search mechanisms, as well as uses knowledge sharing between junior and senior phases. We test our method on the benchmark functions taken from the CEC2020 special session & competition on real-world constrained optimization. Experimental results indicate that CHAGSKODE is able to achieve state-of-the- art performance on real-world constrained global optimization when compared against other well-known real-world constrained optimizers.

The new SARS-CoV-2 coronavirus has brought with it an increase in the use of digital platforms and an exponential increase in the number of scientific papers worldwide. The purpose of this study is to show a global overview of the digital transformation from 1975 to the present (2021). The main collection of the Web of Science database was used to retrieve global scientific production on digital transformation. Bibliometric indicators of production, visibility, impact, and collaboration were analyzed to assess research progress on the topic. The results show that digital transformation is a construct of recent development, increasingly relevant and transdisciplinary, with a clear growth after the declaration of the global COVID-19 pandemic.

This paper proposes a parameter coordination optimization design of Power System Stabilizer (PSS) based on an improved Quasi-Affine Transformation Evolutionary (QUATRE) algorithm to suppress low-frequency oscillation and improve the dynamic stability of power system. To begin, the Simulated Annealing (SA) algorithm randomly updates the globally optimal solution of each QUATRE iteration and matches the inferior solution with a certain probability to escape the local extreme point. This new algorithm is first applied to power system. Second, Since damping ratio is one of the criteria to measure the dynamic stability of power system, this paper sets the objective function according to the principle of maximization of damping coefficient of electromechanical mode, and uses SA-QUATRE to search a group of global optimal PSS parameter combinations to improve the stability margin of the system as much as possible. Finally, the method's rationality and validity were validated by applying it to the simulation examples of IEEE 4-machine 2-area system with different operation states. The comparison with the traditional optimization algorithm shows that the proposed method has more advantages for multi-machine PSS parameter coordination optimization, and can restrain the low-frequency oscillation of power system more effectively and enhance the system stability.

Deep neural networks (DNNs), founded on the brain's neuronal organization, can extract higher-level features from raw input. However, complex intellect via autonomous decision-making is way beyond current AI design. Here we propose an autonomous AI inspired by the thermodynamic cycle of sensory perception, operating between two information density reservoirs. Stimulus unbalances the high entropy resting state and triggers a thermodynamic cycle. By recovering the initial conditions, self-regulation generates a response while accumulating an orthogonal, holographic potential. The resulting high-density manifold is a stable memory and experience field, which increases future freedom of action via intelligent decision-making.

The ageing transformation of digital health services faces issues of how to distinguish influencing factors, redesign services, and effectively promote measures and policies. In this study, in-depth interviews are conducted and grounded theory applied to open coding, main axis coding, and selective coding to form concepts and categories. Trajectory equifinality modeling clarified the evolution logic of digital transformation. Based on the theory of service ecology, a digital health service ageing model is constructed from the "macro-medium-micro" stages and includes governance, service, and technology transformation paths. The macro stage relies on organizational elements to promote the institutionalization of management and guide the transformation of governance for value realization, including the construction of three categories: mechanism, indemnification, and decision-making. The meso stage relies on service elements to promote service design and realize service transformation suitable for aging design, including the construction of three categories: organization, resources, and processes. The micro stage relies on technical elements to practice experiencing humanization, including the construction of three categories: target, methods, and evaluation. These results deepen the understanding of the main behaviors and roles of macro-organizational, meso-service, and micro-technical elements in digital transformation practice and have positive significance for health administrative agencies to implement action strategies.

Although several protocols for genetic transformation of citrus have been published, it is highly desirable to further improve its efficiency. Here we report treatments of Agrobacterium cells and citrus explants prior to and during co-cultivation process to enhance transformation efficiency using a commercially used rootstock 'Carrizo' Citrange as a model plant. We pre-cultured Agrobacterium cells in a 1/10 MS, 0.5 g/L 2-(N-morpholino) ethanesulfonic acid (MES) and 100 µM acetosyringone liquid medium for 6 hours at 25 ℃ before used to infect citrus explants. We incubated epicotyl segments in an MS liquid medium containing 13.2 µM 6-BA, 4.5 µM 2,4-D, 0.5 µM NAA for 3 hours at 25℃ prior to Agrobacterium infection. In the co-cultivation medium, we added 30 µM paclobutrazol and 10 µM lipoic acid. Each of these three treatments significantly increased the efficiencies of transformation. When the three treatments were combined, we observed that the transformation efficiency was enhanced from 11.5% to 52.3%. The improvement of genetic transformation efficiency mediated by these three simple treatments may facilitate more efficient applications of transgenic and gene editing technologies for functional characterization of citrus genes and for genetic improvement of cultivated citrus varieties.

Since the 21st century, China's urbanization process has been rapid development, the concept and function of urban public space in the city has been gradually paid attention to. In order to guarantee life and water, most urban construction relies on rivers, and Bridges are the most important way to communicate between urban areas. The main functional part of the bridge is the span structure, that is, the bearing structure of the bridge, and the lower part of the "gray" space formed by the bridge structure. Considering the social level, with the economic growth and urbanization development, people have brought a better living environment and quality of life, and also improved the requirements for urban public environment. In the increasingly tense urban space, how to use and transform the space under the bridge is a problem that needs to be considered and solved. In view of this problem, in this study, we try to solve the micro-transformation of space under Bridges in cities through public art from the perspective of "regional culture" and "art for all". This paper analyzes the micro-transformation of space art under Bridges in two large cities of Shanghai and Foshan, namely, the space under Bridges under Songhong Road in Shanghai, the space under Bridges under Central Of Suzhou River and the space under Bridges under Pingsheng Bridge in Foshan. This paper discusses the cultural intervention of "regional culture" in the micro-transformation of the space under the bridge, and the influence and effect of "art for all" on the public art space under the bridge after the transformation to the community and the public.

Uganda possesses natural rainforests that serve enormous environmental ecosystems and biodiversity services. Moreover, the country is known for its various tropical rainforest hardwoods, birds, and animal species. Over the years, the trend in the natural forest land has declined at an alarming rate; hence need to investigate the possible drivers. The loss of such biodiversity and ecosystems risks desertification and extreme climatic condition. As the world moves towards Zero Deforestation 2030, understanding the determinants of deforestation and forest degradation is paramount. Therefore, the main objective of this study was to understand the impact and relationships between net forest conversion, energy emission, agriculture, and forest production of Roundwood. We used data from FAO for the period 2004-2016. Using the ADF and KPSS test, we checked for the unit root presence in the variables. Also, the study used two different regression models: multiple linear regression and dynamic linear model. To analyze the determinants of deforestation, we used net forest conversion in Uganda. There was 94 % variation in the dependent variable (Net Forest conversion). The outcome of the dynamic linear regression showed that agriculture and energy emission positively impact net forest conversion. Based on our findings, this study recommended the modernization of agriculture by the government of Uganda to stop cutting down the forests on a big scale. Also, the study suggested that the government strictly legislate Roundwood and wood fuels/charcoal and firewood to reduce huge dependency on forests toward Zero-Deforestation by 2030. If well-structured and implemented, government policies could solve the unnecessary over dependency on the rainforest, the heart of the region's climatic conditions.

Since the Paris Agreement in 2016, the goals of limiting climate change and moving toward climate resilience stand. With a share of about \SI{80}{\percent} of global \ce{CO2} emissions, the energy sector is an essential driver for these goals. A shift to low-carbon energy production and a decentralized system for more efficient energy transmission distribution is necessary. In this paper, we present our work on Modeling of Power Exchanges, Algorithms for \ac{LEM}, Competitiveness of \ac{CHP} and Energy Feedback Devices. The study was conducted considering technical, economic, social and regulatory framework. For easy integration into energy simulations or a \ac{DEMS}, a model for power exchanges was created that allows flexible input or deterministic price patterns. The algorithm handles the clearing of an \ac{LEM} by a district aggregator using limit orders with the goal of increasing the share of locally consumed electricity using economic incentives. An investigation was conducted into the operation of flexible \acp{CHP} in low-carbon power systems to balance the volatility of renewable energy. An energy signal light was developed as an energy feedback device, which is integrated into the \ac{DEMS} in a living lab and allows individual configuration. In summary, the results presented should be compared with those of other research approaches in the future and require qualitative and quantitative evaluation.

During the few years, various algorithms have been developed to extract features from high-resolution satellite imagery. For the classification of these extracted features, several complex algorithms have been developed. But these algorithms do not possess critical refining stages of processing the data at the preliminary phase. Various satellite sensors have been launched such as LISS3, IKONOS, QUICKBIRD, and WORLDVIEW etc. Before classification and extraction of semantic data, imagery of the high resolution must be refined. The whole refinement process involves several steps of interaction with the data. These steps are pre-processing algorithms that are presented in this paper. Pre-processing steps involves Geometric correction, radiometric correction, Noise removal, Image enhancement etc. Due to these pre-processing algorithms, the accuracy of the data is increased. Various applications of these pre-processing of the data are in meteorology, hydrology, soil science, forest, physical planning etc. This paper also provides a brief description of the local maximum likelihood method, fuzzy method, stretch method and pre-processing methods, which are used before classifying and extracting features from the image.

This paper considers the principles of building a circuit model of film resistor cutting. The conductive resistive medium is defined with the component equations and the topology of the circuit model. A method of estimating the electric parameters of a resistor operating in the system with a measuring voltage source is shown. An equation system for the node voltages is defined, and the resistive layer parameters are analyzed as the circuit model structure changes during the cutting process.

The exact similarity solutions (also called as special exact solutions) of two dimensional laminar boundary layer were obtained by Blasius in 1908, however, no similarity solutions for two dimensional turbulent boundary layers have been reported in the literature. With the help of dimensional analysis and invariance principle, Prandtl mixing length $\ell=\kappa y$ for one dimensional turbulent boundary layer is extended to $\ell(x,y)=\kappa y (1-\frac{y}{\delta})\sqrt{\frac{\nu}{U\delta}} $ for the two dimensional turbulent boundary layers, furthermore, with a similarity transformation, we successfully transform the two dimensional turbulent boundary layers partial differential equations into a single ordinary differential equation $f'''+ ff''+\beta(1-f'^2)+\kappa^2[\eta^2(1-\eta)^2f''|f''|]'=0$. As an application, similarity solutions of the two dimensional turbulent boundary layer on a flat plate at zero incidence have been studied in detail. To solve the ordinary differential equation numerically, a complete Maple code is provided.

The exact similarity solutions of two dimensional laminar boundary layer were obtained by Blasius in 1908, however, for two dimensional turbulent boundary layers, no similarity solutions (special exact solutions) have ever been found. In the light of Blasius' pioneer works, we extend Blasius similarity transformation to the two dimensional turbulent boundary layers, and successfully transform the two dimensional turbulent boundary layers partial differential equations into a single ordinary differential equation. By author's Maple code, we numerically solve the ordinary differential equation and produce some useful quantities.

The building sector of most tropical countries still use predominantly primary biomass as the principal fuel. This has adverse effects like CO2 emission and deforestation and is associated with issues like poverty, ill-health, and low standard of living. Therefore, energy policies try to improve on the efficiency of firewood and charcoal end-use technologies, to palliate the negative effects. In this research, the global change assessment model (GCAM) is used, to investigate the impact of efficiency improvement on the energy consumption pattern of the building sector of developing countries. The aim of the study is to provide empirical data that would better inform policymakers on the effects of modernizing these primary fuels. The study developed three scenarios with different levels of efficiency improvements. The results show that efficiency improvement rather increases primary biomass consumption and CO2 emission. However, there is a fall in the consumption of traditional biomass in the second half of the modelling period. The increase in biomass-based fuels consumption was seen to be linked to their affordability. Therefore, policymakers need not only elaborate policies that improve biomass efficiency, but also introduce and motivate other clean cooking fuels like butane, biogas, and electricity.

Conventional academic debate on sustainability and transformation has begun to be disputed by researchers, policymakers and other stakeholders from the private sector. The complexity of linking sustainability with transformation necessitates the development of new ways of understanding and explaining actors, processes, issues, structures, and outcomes related to transformation to sustainability (T2S). A persistent problem in understanding and managing the T2S is the implied notion of a monolithic transformation to achieve sustainability. This notion underestimates the diversity of actors as well as the historical contexts of transformations. At the same time, achieving T2S is highly dependent on technical solutions as well as policies that can stir needed behavioural change, whereas these technical solutions and policies are not always socially acceptable or politically implementable. Therefore, achieving T2S also calls for evaluating normative foundations of policies and actions needed to advance T2S. This article argues that T2S is composed of different phases, each of which having a different set of actors, resources and audience. This article explains how collective decision can be achieved through multiple levels and types of negotiations that occur in an orchestrated manner. To understand this, this article introduces a theoretical model as an analytical framework to structure how T2S unfolds. This model uses insights from negotiation studies to focus on the actors’ perspectives on T2S. It proposes the division of the transformation process into phases – entry point, learning, sequencing, disrupting and fortifying. Using the Germany’s energy transition (Energiewende), each of these phases is analysed to determine the “quality” of cooperation that can help fulfil the tasks required to master the so-called “cognitive games” of T2S (ripeness game, power game, bargaining game, policy game, scaling game). Moreover, insights are presented to explain how the designated milestone can be achieved that indicates the advancing to the next phase and eventually entrench the transformation process. The lessons and findings resulting from the analysis of the phases of T2S suggest that there is also the need to revisit underlying assumptions on negotiations, sustainability and transformation.

The COVID-19 crisis has emphasized the importance of digital transformation of SMEs and has served as an accelerator. Digital transformation empowers SMEs to rethink the way they make decisions and apply technology in meaningful and sustainable ways. The purpose of this study is to explore the role of digital transformation, fostered by COVID-19, and its potential contribution to the sustainability of SMEs. This paper examines a new conceptual framework designed on resource-based theory perspectives by using a survey data of 246 SMEs in Latvia and employing mediation analysis. The main findings of the study are that digital orientation and digital capability have direct positive effects on digital transformation; higher levels of digital orientation and capability, mediated by digital transformation, lead to higher revenue; as well as a more sophisticated business model in the case of digital orientation. Even if we cannot confirm that higher digital capability, mediated by digital transformation, leads to a more sophisticated business model, we found statistically significant direct effects from digital capability to digital transformation and from digital transformation to business model. These findings can be useful for policymakers, managers and practitioners to clarify how digital orientation, digital capability intermediated through digital transformation affect sustainability of SMEs.

This paper presents the results of an experimental study of the patterns of steel and lead shot transformation under the impact of environmental factors (two types of shot exposed alone and in combination with each other). The analyzed environmental factors include atmospheric precipitation of various acidity and soil solutions with a higher content of organic acids. This research demonstrated that steel shot is characterized by a high transformation rate that is an order of magnitude higher on average than the transformation rate of lead under the same conditions. The prevalence of the suspended iron form (excluding the interaction with organic acids) presents risks for such environmental components as soils and sediments and may be hazardous to the ambient air and natural waters in case of wind erosion and surface runoff from the catchment area. Furthermore, the joint presence of steel and lead shot mutually accelerates the corrosion of both metals, thus increasing the environmental risks.

The food system represents a key industry for Europe and particularly Germany. However, it is also the single most significant contributor to climate and environmental change. A food system transformation is necessary to overcome the system's major and constantly increasing challenges in the upcoming decades. One possible facilitator for this transformation are radical and disrup-tive innovations that start-ups develop. There are many challenges for start-ups in general and food start-ups in particular. Various support opportunities and resources are crucial to ensure the success of food start-ups. One aim of this study is to identify how the success of start-ups in the food system can be supported and further strengthened by players in the innovation ecosystem in Germany. There is still room for improvement and collaboration toward a thriving innovation ecosystem. A successful innovation ecosystem is characterised by a well-organised, collaborative, and supportive environment with a vivid exchange between the members in the ecosystem. The interviewees confirmed this, and although the different actors are already cooperating, there is still room for improvement. The most common recommendation for improving cooperation is learning from other countries and bringing the best to Germany.

Oral squamous cell carcinoma often arises from an oral potentially malignant disorder called oral leukoplakia (OL). With this work we aimed to develop a novel data-driven predictive model based on gene expression profiles to distinguish OL patients who underwent malignant transformation from those who did not. We used the Tree Augmented Naïve (TAN) Bayes classifier to predict the posterior probability of having oral cancer given the data. 86 patients were included with a median follow-up of 7.11 years. Fifty-one patients (51/86; 59%) underwent malignant transformation. We found that 16 genes were predictors of oral cancer in patients with OL and these included SLC7A11, SPINK6, SERPINA12, VIT, ATP1B3, CST6, FLRT2, ELMOD1, AZGP1, RNASE13, DIO2, ECM1, CYP4F11, SYTL4, AKR1C1, and AKR1C3. In conclusion, we showed that Bayesian gene networks are a data-driven approach which could be used also in other predictor models in oncology.

Local Productive Systems (hereinafter LPS) based on agro-food industries constitute alternative models of development in peripheral rural areas that are subject to internal and external dynamics and processes. The main objective of the research is to investigate the processes and their consequences on four SPLs based on the Iberian Pig Transformation Industry (hereinafter LPS-IPTI) in SW Spain: Fregenal de la Sierra, Higuera la Real, Cumbres Mayores and Jabugo. Using secondary data, a comparison is made between 2002 and 2020 to establish the changes, causes and consequences on the LPS-IPTI studied. The results obtained indicate (1) business and territorial concentration of LPS-IPTI; (2) productive and territorial specialisation in standardised products and quality products; (3) simplification of industrial processes; (4) loss of employment, especially female; (5) external control of companies in the sector which, accordingly, results in the loss of prominence of local actors in favour of foreign companies, reduced social capital and the progressive loss of ownership of the LPS.

How robust is our assessment of impacts to ecosystems and species from a rapidly changing climate during the 21st century? We examine the challenges of uncertainty, complexity and constraints associated with applying climate projections to understanding future biological responses. This includes an evaluation of how to incorporate the uncertainty associated with different greenhouse gas emissions scenarios and climate models, and constraints of spatiotemporal scales and resolution of climate data into impact assessments. We describe the challenges of identifying relevant climate metrics for ecological models and evaluate the usefulness and limitations of different methodologies of applying climate change to both quantitative and qualitative ecological response models. We discuss the importance of incorporating extreme climate events and their stochastic tendencies in assessing ecological impacts and transformation, and provide recommendations for better integration of complex climate-ecological interactions at relevant spatiotemporal scales. We further recognize the compounding nature of uncertainty when accounting for our limited understanding of the interactions between climate and biological processes. Given the inherent complexity in ecological processes and their interactions with climate, we recommend integrating quantitative modeling with expert elicitation from diverse disciplines and experiential understanding of recent climate-driven ecological processes to develop more robust understanding of ecological responses under different scenarios of future climate change. Inherently complex interactions between climate and biological systems also provide an opportunity to develop wide-ranging strategies that resource managers can employ to prepare for the future.

The human papillomavirus (HPV) type 16 E7 oncogene is critical to carcinogenesis and highly conserved. Previous studies identified a preponderance of non-synonymous E7 variants amongst HPV16-positive cancer-free controls compared to those with cervical cancer. To investigate the function of E7 variants, we constructed full-length HPV16 E7 genes and tested variants at positions H9R, D21N, N29S, E33K, T56I, D62N, S63F, S63P, T64M, E80K, D81N, P92L, and P92S (found only in controls); D14E, N29H (CIN2), and P6L, H51N, R77S (CIN3). We determined the steady-state level of cytoplasmic and nuclear HPV16 E7 protein. All variants from the controls showed a reduced level of steady-state E7 protein, with 7/13 variants having deficient protein levels. In contrast, 2/3 variants from the CIN3 precancer group had near-normal E7 levels. We assayed the activity of representative variants in stably transfected NIH3T3 cells. The H9R, E33K, P92L, and P92S variants found in control subjects had lower transforming activity than D14E and N29H variants (CIN2); and the R77S (CIN3) had activity only slightly reduced from wildtype E7. In addition, R77S and WT E7 caused increased migration of NIH3T3 cells in a wound-healing assay as compared with H9R, E33K, P92L, and P92S (controls) and D14E (CIN2). These data provide evidence that the E7 variants found in HPV16-positive cancer-free women are partially defective for transformation and cell migration further demonstrating the importance of fully active E7 in clinical cancer development.

We assessed how close human perceptions of landscape modification matched a multivariate index based on remotely sensed data of the same locations. Using a Human Footprint (HF) map of the continental U.S. (scaled 0-100), we created three series of aerial images, each with ten images distributed evenly across the 10 deciles of HF score. Using a web-based survey, 290 members of the global public ranked the images in one series based on their perception of the degree of human modification. Respondents also reported age, sex, and country. The degree of correspondence between rankings by respondents and by HF score was high, an average of 1.29 units of difference out of a maximum possible of 5.0. Differences among respondents were not explained by age, sex, or general geographic location. These results suggest that human perception of relative landscape modification conforms closely with the relative ranking made by a multivariate, analytical index.

Most Acinetobacter baumannii strains are naturally competent. Although some information is available about factors that enhance or reduce the frequency of transformation of this bacterium, the regulatory elements and mechanisms are barely understood. In this article, we describe studies on the role of H-NS in the regulation of expression of genes related to natural competency and the ability to uptake foreign DNA. The expression levels of the natural transformation-related genes pilA, pilT, pilQ, comEA, comEC, comF, and drpA were significantly increased in a Δhns derivative of Acinetobacter baumannii A118. Complementation of the mutant with a recombinant plasmid harboring hns restored expression levels of six of these genes (pilT remained expressed at high levels) to those of the wild-type strain. The transformation frequency of the A. baumannii A118 Δhns strain was significantly higher than that of the wild-type. Similar, albeit not identical, effects occurred when hns was deleted from the hypervirulent A. baumannii AB5075 strain. Reduction of gene expression in a few cases was not as pronounced as to reach wild-type levels, and expression of comEA was enhanced further. In conclusion, the expression of all seven transformation-related genes was enhanced after deleting hns in A. baumannii A118 and AB5075, and these modifications are accompanied by an increase in the cells’ transformability. The results demonstrate a role of H-NS in A. baumannii’s natural competence.

Carbon nanomaterials with a different character of the chemical bond – graphene (sp2) and nanodiamond (sp3) are the building bricks for a new class of all-carbon hybrid nanomaterials, where the two different carbon networks with the sp3 and sp2 hybridization coexist, interact and even transform into one another. The unique electronic, mechanical, and chemical properties of the two border nanoallotropes of carbon ensure the immense application potential and versatility of these all-carbon graphene – diamond nanomaterials. The review gives an overview of the current state of the art of graphene – diamond nanomaterials, including their composites, heterojunctions, and other hybrids for sensing, electronic, energy storage, and other applications. Also, the graphene-to-diamond and diamond-to-graphene transformations at the nanoscale, essential for innovative fabrication, and stability and chemical reactivity assessment are discussed based on extensive theoretical, computational, and experimental studies.

In today’s world face detection is the most important task. Due to the chromosomes disorder sometimes a human face suffers from different abnormalities. For example, one eye is bigger than the other, cliff face, different chin-length, variation of nose length, length or width of lips are different, etc. For computer vision currently this is a challenging task to detect normal and abnormal face and facial parts from an input image. In this research paper a method is proposed that can detect normal or abnormal faces from a frontal input image. This method used Fast Fourier Transformation (FFT) and Discrete Cosine Transformation of frequency domain and spatial domain analysis to detect those faces.

Specific climate adaptation and resilience measures can be efficiently designed and implemented at the regional and local level. Climate and environmental databases are of critical importance to achieving sustainability goals (SDGs) and for the efficient planning and implementation of suitable mitigation measures: Available databases can serve municipalities as a vital starting points to determine requirements, prioritize resources and allocate investments under consideration of commonly tight budget restrictions. High-quality geo, climate and environmental data are now available – data from remote sensing, i.e. Copernicus services will be of crucial importance. Forward-looking approaches exist to using such data to derive forecasts for urban planning process optimization for municipal administrations. On municipal level, however, the existing data have so far only been used to a limited extent, since there are no practical tools for urban planning that can be used to merge and meaningfully combine remote sensing data with local data and to further process and apply in municipal planning processes. Therefore, our project CoKLIMAx aims at the development of new digital products, advanced urban services and procedures, such as the development of practice-oriented technical tools that acquire various remote sensing and in-situ data sets for validation and further processing.

Time evolution operators of a strongly ionizing medium are calculated by a time-dependent unitary transformation (TDUT) method. The TDUT method has been employed in quantum mechanical system composed of discrete states. This method is especially helpful for solving molecular rotational dynamics in quasi-adiabatic regimes because the strict unitary nature of the propagation operator allows us to set the temporal step size large; a tight limitation on the temporal step size ($\delta t <<1$) can be circumvented by the strict unitary nature. On the other hand, in a strongly ionizing system where the Hamiltonian is not Hermitian, the same approach cannot be directly applied because it is demanding to define a set of field-dressed eigenstates. In this study, the TDUT method was applied to the ionizing regime using the Kramers-Henneberger frame, in which the strong-field-dressed discrete eigenstates are given by the field-free discrete eigenstates in a moving frame. Although the present work verifies the method for a one-dimensional atom as a prototype, the method can be applied to three-dimensional atoms, and molecules exposed to strong laser fields.

ABSTRACT Education is the most important instrument in human life because education can increase human dignity. In addition, education can also be a benchmark for human quality and an example of the progress of a nation. The history of education in Indonesia has evolved from the colonial era to the digital era. These developments have influenced government policies in every era. In the 21st century, the development of education in Indonesia is starting to show progress. This is because it is supported by the rapid growth of information and technology. This research article aims to analyze the educational policies carried out by the government from the colonial era to the digital era to be used as evaluation material at this time so that in the future education in Indonesia is even better. To achieve this goal, this research focuses on the question of how is the transformation of education in Indonesia from the colonial era to the digital era? and what is the paradigm of education in Indonesia when viewed from a historical perspective?. The research method used is the Literature Review method from 27 sources in journal articles, websites, and data reports for 2019-2021. The results of this study found that changes in the Indonesian education system from time to time have a positive influence on the progress of the Indonesian nation. The development of education in Indonesia also has an impact on increasing the Human Development Index (HDI). This shows that the quality of Indonesian society is increasing. Based on the results obtained, it is hoped that it can provide information about the transformation of education in Indonesia from the colonial era to the digital era from a historical perspective. This article is suitable as a reference source for education observers in Indonesia to know the history of education and its policies from the colonial era to the digital era and useful for academics to know the history of education in Indonesia. This research has limitations, namely this research is only limited to the development of education in Indonesia from the colonial era to the digital era and the paradigm of education development in Indonesia from a historical perspective.

The energy sector plays an important role in Mexico’s development trajectory. Mexico makes an interesting case study, because it shows how difficult it is to reduce fossil energy dependence despite geographic and climatic conditions that favour renewable energy deployment and use. Resolving path dependencies and the related carbon lock-in are key to Mexico’s sustainable energy transition. This case study aims to identify and discuss how carbon lock-in affects Mexico’s sustainable energy transition. Mexico’s carbon lock-in involves oil and oil-run power plants that are costly to build but relatively inexpensive to operate. This case study identifies potential entry points for transitioning towards sustainable energy in Mexico – resources that can promote the use of clean energy despite carbon lock-in. For example, focusing on electrification – particularly of the carbon-intensive sectors – can help Mexico transit towards sustainable energy despite institutional constraints. Complementing this case study is a teaching guide with recommendations for using Mexico’s energy transition in courses on sustainability. It introduces a “learning activation framework” to identify emerging opportunities that can advance sustainable energy transitions in different cases of carbon lock-in. Finally, the framework also gives students a chance to help dismantle or cope with carbon lock-ins.

Indonesia is an interesting case study for students of sustainable development and sustainable energy due to its ability to connect the multiple “worlds” it has become part of. Indonesia is an important bridge to Muslim countries, the voice of the Global South in the G20 and a main pillar of the 134-country-strong G77. Indonesia’s development trajectory is also key to the achievement of the Paris Climate Agreement as well as of the 2030 Agenda. Students can learn from how Indo-nesia address contradictions that would have been unsurmountable for other countries. Indone-sia’s energy transition offers helpful lessons, because of its aspiration to become a developed country by 2045. This goal is only possible when a country is able to effectively address barriers and caveats to sustainable energy. It is interesting how Indonesia focuses on silver linings and come up with pragmatic solutions to energy-related issues. This is followed by the “teaching guide,” which provides recommendations how the lessons from Indonesia can be embedded into a learning experience. The “learning activation approach” is introduced, which encourages stu-dents to systematically reflect on the complexity of selected contexts and understand this com-plexity by looking at the technical issues and processes that allow decision-making.

In this paper, the deformation and phase transformation of disorder α phase at (α + γ) two phase region in as-forged Ti-44Al-8Nb-(W, B, Y) alloy are investigated by hot compression and hot packed rolling. Detailed microstructural evolution demonstrates that the as-deformed microstructure is significantly affected by deformation conditions. The mircrostructure differences are mainly due to temperature drop and strain rate. The evolution of α lamelae into α grains is detailed descripted. Moreover, the disorder α lamellae can also be decomposed into some new α grains by the assisted decomposition mechanism of γ grains. Microstructure evolution model of current TiAl alloy at 1250 °C during hot rolling is built.

We present a new analytical method to find the asymptotic stable equilibria states based on the Markov chain technique. We reveal this method on the SIR-type epidemiological model that we developed for viral diseases with long-term immunity memory pandemic. This is a large-scale model containing 15 nonlinear ODE equations, and classical methods have failed to analytically obtain its equilibria. The proposed method is used to conduct a comprehensive analysis by a stochastic representation of the dynamics of the model, followed by finding all asymptotic stable equilibrium states of the model for any values of parameters and initial conditions.

For most professionals to be successful in the current job market, they need some entrepreneurial skills (ES). This study aimed to describe and systematize these skills, considering the current globalization and digital transformation phenomena. The documental analysis and the critical reflection on the collected data allowed us to identify the socio-economic and socio-cultural reasons for the relevance of this problem. Consequently, to elaborate a frame of reference that is intended to be adequate to the needs of the professionals of the current global and digital era. The results pointed to a tripartite ES model - to be open to novelty, to create solutions to emerging problems, and to communicate effectively - which integrates the following skills: creativity and innovation, the spirit of initiative, self-efficacy and resilience, strategic planning, and evaluation, resolution of problems and decision-making, transformational leadership, clear and visual communication, teamwork and networking, and digital communication. In the continuation of this study, an ES scale will be created and validated according to this model, which will make it possible to measure the degree of development of these competencies.

The article presents results of research consisting in an attempt to assess the influence of temperature, heating time and cooling method on microstructure and residual strength properties of steel previously tempered during the production process. Simulated environmental conditions to which high-strength bolts, commonly used in steel construction, were subjected, were intended to reflect conditions of a natural fire that may occur in public facilities where the obligation to ensure safety of users and rescue teams is of key importance, also required by law. Furthermore, the tests carried out also comprised a simulated effect of a rescue and firefighting operation using shock, rapid cooling of some of the heated bolts. Samples cut out from the tested bolts, after they were properly prepared, were subjected to microstructural tests using light microscopy, scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), phase analysis with the use of an X-ray diffractometer (XRD) and quantitative analysis of the microstructure involving, inter alia, measuring the surface area of grains, their equivalent diameter and mean diameter. As a result of the tests, considerable microstructure changes were identified occurring in the bolt material as a result of exposing it to fire conditions, leading to a change in key, from the point of view of structural safety, mechanical properties. The results of the microstructure tests were compared with the results of previous strength tests, including hardness of the material after the heat treatment and the residual tensile strength of the material Rm. A conducted comparative analysis showed a significant effect of all such factors as the temperature level of the simulated fire, its duration and the fire-fighting method on the mechanical properties of bolts. Results obtained were provided with required comments and the concept of using the microstructure for the post-fire assessment of steel structures was referred to.

Abstract:Shown is the derivation of Lorentz-Einstein k-factor in SRT as an amplitude-term of oscillation-differential equations of second order.This case is shown for classical Lorentz-factor as solution of an equation for undamped oscillation as well as the developed theorem as a second solution for advanced SRT of fourth order with an equation for damped oscillation-states.This advanced term allows a calculation for any velocities by real rest mass

The morphological transformation of an arched ribbon driven by torsion is a scientific problem that is connected with daily life and requires thorough analysis. An arched ribbon can achieve an instantaneous high speed through energy transformation and then return to the original shape of the structure. In this paper, based on the characteristics of the ribbon structure, the dynamic mathematical model of the arched ribbon driven by torsion is established from the Kirchhoff rod equation. The variations of the Euler angle of each point on the center line of the ribbon with the arc coordinate s and the rotation angle of the supports $\phi$ was examined. The relationship between the internal force distribution of each point in the direction of $\hat{d}_{a}$ and the material, cross-sectional properties, and rotation angle of the supports was obtained. We used ABAQUS, a nonlinear finite element analysis tool, to simulate the morphological transformations of the ribbons, verified our theory with simulation results, and reproduced the experimental results of Sano. Furthermore, we redefined the concept of the ``critical flipping point'' of Sano. In this paper, the dimensional analysis method was used to fit the simulation data. The following relationship between the critical width $ w ^{*} $, thickness h, and the radius R of the ribbon with different cross sections was obtained: $w^{*}=A\cdot R\left(h/R\right)^{0.6}$, where A is 3.19 for rectangular cross sections and 3.06 for elliptical cross sections. By analyzing the simulation data, we determined the variation behavior of the out-of-plane deflection of the center point of the ribbon with the radius R, width w, and thickness h. Our research has guiding significance for understanding and designing arched ribbons driven by torsion, and the results can be applied to problems of different scales.

The influence of the hot isostatic pressing (HIP) post-processing step on structural and phase changes, porosity healing and mechanical strength in a powder metallurgy Ti35Nb2Sn alloy was studied. Powders were pressed at room temperature at 750 MPa, and then sintered at 1,350°C in a vacuum for 3 h. The standard HIP process at 1,200°C and 150 MPa for 3 h was performed to study its effect on a Ti35Nb2Sn powder metallurgy alloy. The influence of the HIP process and cold rate on density, microstructure, the quantity of interstitial elements, mechanical strength and Young's modulus was investigated. HIP post-processing for 2 h at 1,200°C and 150 MPa led to greater porosity reduction and a marked retention of the β phase at room temperature. The slow cooling rate during the HIP process affected phase stability, with a large amount of α”-phase precipitate, which decreased the titanium alloy’s yield strength.

Abstract: Intensity of natural and man-made disasters is increasing day by day. Disaster is one of the major threats that affects the sustainable development of tourist attractions. Big data and Internet of Things(IoT) will greatly improve the disaster management. Based on the Big Data and IoT, a tourism attraction disaster management system is designed, divided into several stages namely pre-disaster early warning prevention, disaster mitigation, recovery and reconstruction after disaster and updating disaster planning. Then, the system flow is analysed, as well as the system structure is constructed. Additional, system function and its operation flow are introduced, including disaster warning, disaster relief, disaster assessment, real-time monitoring and supporting disaster planning functions. Finally, an application case is introduced. Research intends to improve tourism area disasters management.

From the wide range of engineering materials traditional Stellite 6 alloy exhibits excellent cavitation erosion (CE) resistance. In this work, the effect of nitrogen ion implantation of HIPed Stellite 6 on the improvement of CE resistance and both cobalt-rich matrix phase transformation due to nitrogen implantation and CE were stated. The CE resistance of stellites ion-implanted by 120 keV N+ ions two fluences: 5x1016 cm-2 and 1x1017 cm-2 were comparatively analysed with the unimplanted stellite and AISI 304 stainless steel. CE tests were conducted according to ASTM G32 with stationary specimen method. Erosion rate curves and mean depth of erosion confirm that the nitrogen implanted HIPed Stellite 6 two times exceeds the resistance to CE than unimplanted stellite, and has almost 10 times higher CE reference than stainless steel. The X-ray diffraction (XRD) confirms that HIPed Stellite 6 nitrogen ion implantation favours transformation of the ɛ(hcp) to γ(fcc) structure. Unimplanted stellite ɛ-rich matirx is less prone to plastic deformation than γ and consequently, increase of γ phase effectively holds carbides in cobalt matrix and prevents Cr7C3 debonding. This phenomenon elongates three times the CE incubation stage, slows erosion rate and mitigates the material loss. Metastable γ structure formed by ion implantation consumes the cavitation load for work-hardening and γ → ɛ martensitic transformation. In further CE stages, phases transform as for unimplanted alloy namely, the cavitation-inducted recovery process, removal of strain, dislocations resulting in increase of fcc phase. The CE mechanism was investigated using a surface profilometer, atomic force microscopy, SEM-EDS and XRD. HIPed Stellite 6 wear behaviour relies on the plastic deformation of cobalt matrix, starting at Cr7C3/matrix interfaces. Once the Cr7C3 losing their restrain, are debonding and removed. Carbides detachment creates cavitation pits which initiate cracks propagation through cobalt matrix, the loss of matrix phase and CE proceeds with a detachment of massive chunk of materials.

China is out of extreme poverty in 2020 on schedule and one decade in advance to fulfill the UN 2030 Agenda for Sustainable Development Goals (SDGs), and became the first developing country to alleviate poverty in half century. Therefore, a large numbers of effective approaches are emerging, and the intellectual’s technology-led poverty reduction, which locally known as the “Straw Hat University”initiated by “Farmer's professor”mode, is the most tried and tested approach motivated by the intellectual’s “Serve the people” tradition and supported by the all nation. This research conduct case analysis with three most remarkable organic intellectuals as Agronomist Yuan longping, Mycologist Lin Zhanxi and Plant pathologist Zhu Youyong with their bridging gaps in food security, regional imbalance and ethnic disparity respectively to sort out the sustainable modules and universal experiences. The conclusion indicates that“Farmer's Professor” Initiated “Straw Hat University” is an effective approach to solve human beings’ development problems and benefit the livelihoods, especially in the under development regions; and the authentic down to earth experiments into productivity as well as the Intellectual property transformation is the perfect path to deploy offline and online resources building the effective production and supply chain to integrate industries by intellectual’s critical innovation.

Given a quasi-definite linear functional u in the linear space of polynomials with complex coefficients let us consider the corresponding sequence of monic orthogonal polynomials (SMOP in short) (Pn)n≥0. For the Christoffel transformation u˜=(x−c)u with SMOP (P˜n)n≥0, we are interested to study the relation between u˜ and u(1)˜, where u(1) is the linear functional for the associated orthogonal polynomials of the first kind (Pn(1))n≥0 and u(1)˜=(x−c)u(1) is its Christoffel transformation. This problem is also studied for the Geronimus transformations.

This work is concerned with the existence and uniqueness of boundary value problems defined on semi-infinite intervals. These kinds of problems seldom admit exactly known solutions and, therefore, the theoretical information on their well-posedness is essential before attempting to derive an approximate solution by analytical or numerical means. Our utmost contribution in this context is the definition of a numerical test for investigating the existence and uniqueness of solutions of boundary problems defined on semi-infinite intervals. The main result is given by a theorem relating the existence and uniqueness question to the number of real zeros of a function implicitly defined within the formulation of the iterative transformation method. As a consequence, we can investigate the existence and uniqueness of solutions by studying the behaviour of that function. Within such a context the numerical test is illustrated by two examples where we find meaningful numerical results.

A plenty of theories on the origin of genetic codes have been proposed so far, yet all ignored the energetic driving force, its relation to the biochemical system, and most importantly, the missing “matchmaker” between proteins and nucleic acids. Here, a new hypothesis is proposed, according to which ATP is at the origin of the primordial genetic code by driving the coevolution of the genetic code with the pristine biochemical system. This hypothesis aims to show how the genetic code was produced e.g. by photochemical reactions in a protocell that derived from a lipid vesicle enclosing various life’s building blocks (e.g. nucleotides and peptides). At extant cell, ATP is the only energetic product of photosynthesis, and is at the energetic heart of the biochemical systems. ATP could energetically form and elongate chains of both polynucleotides and polypeptides, thus acting a “matchmaker” between these two bio-polymers and eventually mediating precellular biochemical innovation from energy transformation to informatization. ATP was not the only one that could drive the formation of polynucleotides and polypeptides, but favored by precellular selection. The protocell innovated a photosynthesis system to produce ATP efficiently and regularly with the aids of proteins and RNA/DNA. The completion of permanently recording the genetic information by DNA marked the dawn of cellular life operated by Darwinian evolution. The ATP hypothesis assumes or supports the photochemical origin of life, shedding light on the origins of both photosynthetic and biochemical systems, which remains largely unknown thus far. Based on ATP hypothesis, virus (like the new coronavirus) could not be the earliest life on Earth, as it has neither biochemical systems nor lipid bilayer membrane that provided relatively isolated environment for the development of protobiochemical reactions, although it owns the genetic code of a cellular life. Virus could not be a bridge between life and non-life, but is an anti-life substance, as it depletes cellular material for its own replication, and then spreads by destroying the host cells. It can be imagined that if cellular life are completely wiped out by the virus, the complete destruction of life on Earth would be inevitable.

Research professors develop scientific products that impact and benefit society, but their competencies in doing so are rarely evaluated. Therefore, employing a mixed two-stage sequential design, this study developed a self-assessment model of research professors’ competencies with four domains, seven competencies, and 30 competency elements. Next, we conducted descriptive statistical analysis of those elements. In the first year, 320 respondents rated themselves on four levels: initial, basic, autonomous, and consolidated. In the assessment model’s second year, we compared 30 respondents’ results with those of their initial self-assessment. The main developmental challenge was Originality and Innovation, which remained at the initial level. Both Training of Researchers and Transformation of Society were at the basic level, and Digital Competency was at the autonomous level. Both Teaching Competence and Ethics and Citizenship attained the consolidated level. This information helps establish priorities for accelerating researchers’ training and the quality of their research.

This study deals with vibrational and crystallographic aspects of the thermally induced transformation of serpentine-like garnierite into quartz, forsterite, and enstatite occurring at about 620 °C. Powder specimens of garnierite have been annealed in static air between room temperature and 1000 °C. The resulting products from the transformations detected based on thermogravimetric and differential thermal analysis, have been extensively characterized via microRaman spectroscopy, and X-ray diffraction. Our study shows that serpentine-like garnierite consists of a mixture of different mineral species. Furthermore, these garnierites and their composition can provide details based on the mineralogy and the crystalline phases resulting from the thermal treatment.

Nature-based Solutions (NbS) have rapidly been gaining traction across the research, policy, and practice spheres, touted as transformative actions to jointly address biodiversity loss and climate change. However, there are multiple, alternative ways to imagine NbS in those three spheres. To inform the NbS discourses across these three spheres, we critically reflect on the prevailing framing of NbS and consider the potential of a different framing of NbS to support transformations towards regenerative relationships between humans and nature. Such reflection is urgently needed to ensure that research, policy, and practice delivers on the transformative ambitions of NbS. We propose a novel “core framing” of NbS, charting two pathways for how such a framing can support a human value-based transformation – first through influencing individual beliefs and values, and second through the communication and application of the NbS concept in research, policy, and practice. We argue that for NbS to support transformation, it must support a reframing of human-nature relationships, one where the interdependencies between people and nature are recognized as essential for social and environmental well-being. We elaborate on how such a framing is key to support inclusivity and collaboration between diverse research perspectives, policy objectives across scales, and implementation practices, to deliver successful NbS.

The management of a cultural change in higher education is becoming necessary and unavoidable: changes in teaching, changes in research and changes in governance. Digital transformation is an essential part of many countries’ modernisation agendas. The aim of this non-experimental, descriptive, survey-based study was to explore the perceptions of university students toward the digital transformation that took place in university teaching as a consequence of COVID-19. The specific objectives proposed were to: a) analyse the perceptions of students toward digital transformation in university teaching; b) determine the valuation of students about the digital transformation that occurred in university teaching as a result of COVID-19; and c) explore the resources (hardware-software), professional collaboration, digital pedagogy and student empowerment (motivation) with respect to digital education and the recent changes in university teaching due to the pandemic. The results show that a large number of items are positively correlated. In conclusion, further research should delve into motivation, collaboration, reflective experience sharing, self-learning and initiatives that promote the development of competences in future teachers.

The Internet-of-Things (IoT) triggers new types of cyber risks. Therefore, the integration of new IoT devices and services requires a self-assessment of IoT cyber security posture. By security posture this article refers to the cybersecurity strength of an organisation to predict, prevent and respond to cyberthreats. At present, there is a gap in the state-of-the-art, because there are no self-assessment methods for quantifying IoT cyber risk posture. To address this gap, an empirical analysis is performed of 12 cyber risk assessment approaches. The results and the main findings from the analysis is presented as the current and a target risk state for IoT systems, followed by conclusions and recommendations on a transformation roadmap, describing how IoT systems can achieve the target state with a new goal-oriented dependency model. By target state, we refer to the cyber security target that matches the generic security requirements of an organisation. The research paper studies and adapts four alternatives for IoT risk assessment and identifies the goal-oriented dependency modelling as a dominant approach among the risk assessment models studied. The new goal-oriented dependency model in this article enables the assessment of uncontrollable risk states in complex IoT systems and can be used for a quantitative self-assessment of IoT cyber risk posture.

The management of a cultural change in higher education is becoming necessary and unavoidable: changes in teaching, changes in research and changes in governance. Digital transformation is an essential part of many countries’ modernisation agendas. The aim of this non-experimental, descriptive, survey-based study was to explore the perceptions of university students toward the digital transformation that took place in university teaching as a consequence of COVID-19. The specific objectives proposed were to: a) analyse the perceptions of students toward digital transformation in university teaching; b) determine the valuation of students about the digital transformation that occurred in university teaching as a result of COVID-19; and c) explore the resources (hardware-software), professional collaboration, digital pedagogy and student empowerment (motivation) with respect to digital education and the recent changes in university teaching due to the pandemic. The results show that a large number of items are positively correlated. In conclusion, further research should delve into motivation, collaboration, reflective experience sharing, self-learning and initiatives that promote the development of competences in future teachers.

A new method in which completely eliminated the negative value of the scattering power is proposed in this paper. Primarily, here are presented the Freeman-Durden decomposition of the scattering powers, which are computed by using the coherency matrix elements with rotation and without rotation. Secondly, this paper investigates the reasons of the occurrence of negative values of the scattering powers. Then using the modification like in algorithm proposed by Yamaguchi for G4U, it was applied for the algorithm of Freeman-Durden decomposition to eliminate negative values. In this research, Radarsat-2 radar remote sensing data were used, which are acquired for study area Yushu County, Qinghai province, China. At the end, the comparison results of Yamaguchi G4U and a modified Freeman-Durden decompositions were presented.

Long-term, high-accuracy mapping of built-up land dynamics is essential for understanding urbanization and its consequences for the environment. Despite advances in remote sensing and classification algorithms, built-up land mapping using early satellite imagery (e.g., from the 2000s and earlier) remains prone to uncertainty. We mapped the extent of built-up land in the North China Plain, one of China’s most important agricultural regions, from 1990 to 2019 at three-year intervals. Using dense time-stack Landsat data, we applied discrete Fourier transformation to create temporal predictors and reduce mapping uncertainties for early years. We improved overall accuracy by 8% compared to using spectral and indices predictors alone. We implemented a temporal correction algorithm to remove inconsistent pixel classifications, further improving accuracy to a consistently high level (>94%) across years. A cross-product comparison showed that our study achieved the highest levels of accuracy across years. Total built-up land in the North China Plain increased from 37,941 km² in 1990–1992 to 131,578 km² in 2017–2019. Consistent, high-accuracy built-up land mapping provides a reliable basis for policy planning in one of the most rapidly urbanizing regions of the planet.

Diamond is a material with excellent performances which attracts the attention from researchers for decades. Pt (111), owing to its catalytic activity on diamond synthesis, is regarded to be a candidate for diamond hetero-epitaxity, which can enhance nucleation density. Molten surface at diamond growth temperature can also improve mobility and aggregation capability of primitive nuclei. Generally, (100)-oriented is welcomed for the achivement of high quality and large size diamond, since the formation of defects and twins are prevented. First-principle calculations and experimental researches were carried out for the study of transformation of orientation. The transformation from {111} to {100}-oriented diamond has been observed on Pt (111) substrate, which can be promoted by the increase of carbon source concentration and substrate temperature. The process is energetic favorable, which may provides a way towards large-scale (100) diamond films.

There are many theories of carcinogenesis arguing against the orthodox mutation theory, debating on such as “epigenetic alteration” that is inheritable and yet, theoretically, reversible. Our integrated theory describes that any extracellular, intracellular, or intranuclear stressors, mutagenic or not, can initiate a lengthy tumorigenesis to engender a benign or malignant tumor, but the aberrations directly establishing cellular immortality and autonomy may be epigenetic or genetic alterations in the genomic DNA. A neoplasm is considered a semi-new organism with autonomy; it therefore should have genetic mutations to be “new”. We may be able to direct cancer cells towards differentiation as a remedy, because the extracellular milieu may control the phenotype of a cell and the tissue or organ made of the cell’s progenies, and the cytoplasm of a cell may override the nucleus in the phenotypic control. However, the nucleus retains the capacity to manifest itself if allowed by the microenvironment, which then allows the already reversed cells to revert back to tumor cells again. Neoplasms are malignant if they bear epigenetic or genetic anomalies in mutator genes defined as those whose alterations allow or accelerate alterations to occur in other genes, whereas neoplasms are benign if they bear epigenetic or genetic aberrations only in non-mutator genes. It is imperative to identify the immediate tumor-causing cellular alterations defined as those directly responsible for immortality and autonomy, and for treatment purposes to identify the extracellular and intracellular factors that control the phenotype of cancer cells.

Seismic imaging is the main technology used for subsurface hydrocarbon prospection. It~provides an image of the subsurface using the same principles as ultrasound medical imaging. As for any data acquired through hydrophones (pressure sensors) and/or geophones (velocity/acceleration sensors), the raw seismic data are heavily contaminated with noise and unwanted reflections that need to be removed before further processing. Therefore, the noise attenuation is done at an early stage and often while acquiring the data. Quality control (QC) is mandatory to give confidence in the denoising process and to ensure that a costly data re-acquisition is not needed. QC is done manually by humans and comprises a major portion of the cost of a typical seismic processing project. It is therefore advantageous to automate this process to improve cost and efficiency. Here, we propose a supervised learning approach to build an automatic QC system. The~QC system is an attribute-based classifier that is trained to classify three types of filtering (mild = under filtering, noise remaining in the data; optimal = good filtering; harsh = over filtering, the signal is distorted). The attributes are computed from the data and represent geophysical and statistical measures of the quality of the filtering. The system is tested on a full-scale survey (9000 km²) to QC the results of the swell noise attenuation process in marine seismic data.

The urgency to address the adverse impacts of climate change on livelihoods and ecosystems has seen an increase in global driven initiatives. However, shifting vulnerabilities associated with land use resource based adaptation and maladaptive feedback loops they create have been given low attention. Policy discourses that frame adaptation as a local responsibility and bias towards reducing industrial Greenhouse gas (GHG) emissions at the expense of Agricultural emissions across scale are thought to account for the undesirable situation. This calls for a reflective policy framework and climate policy innovation. We provide counter arguments using Drivers, Pressure, State, Impact, Response (DPSIR) model and telecoupling principles to suggest use of resilience as an integrative lens in visualising the proposal. Using a case study on resource constrained smallholder dairy production systems, western Kenya, we analyse the critical issues in the context of decision making and environmental externalities. The effect of price risks on dairy cattle feeding strategies and ultimately carbon footprints and ecoefficiencies were examined through methane simulation and gross margin analysis (GM). The lowest ecoefficiency was associated with exclusively local coping strategies i.e. Maize Stover (Ms), while the highest ecoefficiency was observed in feeding strategies that utilise external resources and/or legume fodders. We conclude that management of externalities need to capture institutional, economic processes and incentive systems, as well as organizational and policy coherence to shape the interests and behaviour of individual land user. In particular, policy innovation should focus on price and market risks as critical factors that mediate actor decision making at implementation level as they impact GHG emissions which transcend individual decision boundaries.

Most mature companies have started some kind of “transformation”, either digital, or agile transformations, to cope with changes in the environment, yet most fail, ending up delivering nothing or just one more reorganization. We postulate that considering the Organization as a self-aware Complex Adaptative System (CAS) is paramount, as the common conception (Industrial: mechanistic and predictive) results in bringing the systems in a frozen or defensive mode. Stimulating the system enables us to use its adaptative power to develop new capabilities, and all layers should be tackled simultaneously, to prevent the system from collapsing back into its original state. To ensure this, it is necessary to create a seed per level, and a mechanism to propagate the transformation, with a focus on development instead of growth, that is qualitative change rather than quantitative. A common vocabulary should also be provided, so conversations can occur at every level. Finally, changing mindsets is key, and both concepts and techniques should be provided as enablers to the adequate mindset level. We detail one such transformation that resulted in distributed leadership and more intrinsic motivation, providing both an account of the transformation itself and a model to read it.

Nowadays, model checking is applied as an accurate technique to verify software systems. The main problem of model checking techniques is the state space explosion. This problem occurs due to the exponential memory usage by the model checker. In this situation, using meta-heuristic and evolutionary algorithms to search for a state in which a property is satisfied/violated is a promising solution. Recently, different evolutionary algorithms like GA, PSO, etc. are applied to find deadlock state. Even though useful, most of them are concentrated on finding deadlock. This paper proposes a fuzzy algorithm in order to analyze reachability properties in systems specified through GTS with enormous state space. To do so, we first extend the existing PSO algorithm (for checking deadlocks) to analyze reachability properties. Then, to increase the accuracy, we employ a Fuzzy adaptive PSO algorithm to determine which state and path should be explored in each step to find the corresponding reachable state. These two approaches are implemented in an open-source toolset for designing and model checking GTS called GROOVE. Moreover, the experimental results indicate that the hybrid fuzzy approach improves speed and accuracy in comparison with other techniques based on meta-heuristic algorithms such as GA and the hybrid of PSO-GSA in analyzing reachability properties.

Based on electromagnetic heat transfer and metal phase transformation co-simulations, we modeled an AISI 1045 specimen under high-frequency heat treatment. Hardening zone predictions were confirmed through cooling and metal phase transformation simulations after obtaining the results from electromagnetic heat transfer simulations. The cooling process was modeled by applying the cooling coefficient of the cooling water in the same way as the actual heat-treatment process. To obtain the current flowing through the coil during high-frequency induction heating, the voltage was measured and applied using the resistance–inductance–capacitance circuit calculation method. Experimental and simulated results of the heating temperature and curing depth of an AISI 1045 specimen with a carbon content of 0.45% were compared; the comparison indicated good agreement between the two. Using the simulation results, we established a method for obtaining the current flowing through the induction coil for predicting the extent and depth of the hardening zone during high-frequency induction heat treatment.

Seismic imaging is the main technology used for subsurface hydrocarbon prospection. It provides an image of the subsurface using the same principles as ultrasound medical imaging. It is based on emitting a sound (pressure) wave through the subsurface and recording the reflected echoes using hydrophones (pressure sensors) and/or geophones (velocity/acceleration sensors). Contrary to medical imaging, which is done in real time, subsurface seismic imaging is an offline process that involves a huge volume of data and needs considerable computing power. The raw seismic data are heavily contaminated with noise and unwanted reflections that need to be removed before further processing. Therefore, the noise attenuation is done at an early stage and often while acquiring the data. Quality control (QC) is mandatory to give confidence in the denoising process and to ensure that a costly data re-acquisition is not needed. QC is done manually by humans and comprises a major portion of the cost of a typical seismic processing project. It is therefore advantageous to automate this process to improve cost and efficiency. Here, we propose a supervised learning approach to build an automatic QC system. The QC system is an attribute-based classifier that is trained to classify three types of filtering (mild = underfiltering, noise remaining in the data; optimal = good filtering; harsh = overfiltering, the signal is distorted). The attributes are computed from the data and represent geophysical and statistical measures of the quality of the filtering. The system is tested on a full-scale survey (9000 km2) to QC the results of the swell noise attenuation process in marine seismic data. The results are encouraging and helped identify localized issues that were difficult for a human to spot.

This article explores the impact of farmers’ vocational training on their income. Survey data concerning agricultural product quality and agricultural product sales were collected by the research team in Yantai City, China. An endogenous transformation regression model (ESR) was then used to analyze the impact of training on farmers’ family income, and the income mechanism was further tested. The results from the empirical analysis suggest that (1) Participating in training can significantly increase farmers’ income; (2) Farmers who pay more attention to the quality of their agricultural products during the production process are more likely to see their incomes increase after participating in the training.

In personalized healthcare, an ecosystem for the manipulation of reliable and safe private data should be orchestrated. This paper describes a first approach for the generation of fake electrocardiograms (ECGs) based on Generative Adversarial Networks (GANs) with the objective of anonymizing users’ information for privacy issues. This is intended to create valuable data that can be used both, in educational and research areas, while avoiding the risk of a sensitive data leakage. As GANs are mainly exploited on images and video frames, we are proposing general raw data processing after transformation into an image, so it can be managed through a GAN, then decoded back to the original data domain. The feasibility of our transformation and processing hypothesis is primarily demonstrated. Next, from the proposed procedure, main drawbacks for each step in the procedure are addressed for the particular case of ECGs. Hence, a novel research pathway on health data anonymization using GANs is opened and further straightforward developments are expected.

Climate change, biodiversity loss, and other social and environmental problems pose grave risks. Progress so far has been incremental and insufficient, and as a result scientists, global policy experts, and the general public increasingly conclude that bold change is required across all sectors of society. At least two kinds of bold change are conceivable: reform of existing societal systems (e.g., financial, economic, legal, and governance systems), including their institutions, policies, rules, and priorities; and transformation, understood as the de novo development of and migration to new, improved systems. This paper is the second in a series of three that together propose a novel science-driven research and development program aimed at societal transformation. Moreover, the series advances a conceptual framework and formal mechanics by which societal transformation might be approached. Two of the underlying hypotheses are that new societal systems can be developed in a science-driven process to be fit for purpose, and system fitness can be compared across designs. Societies are viewed as superorganisms, and systems are viewed as a societal cognitive architecture. The first paper in the series provides definitions, aims, hypotheses, and a worldview. This paper discusses motivations, the role of science in societal transformation, a theory of change, and fitness metrics. The proposed R&amp;D program and theory of change are sound, viable, and affordable. The local-global-viral strategy invites the global science community to play a unique co-leadership role with local communities in the development, testing, and monitoring of new societal systems. Systems are implemented via a novel civic club model, where participation is voluntary. Clubs grow and replicate based on merit and aided by club networks, whose systems are also viewed as societal cognitive architectures. Benefits of the program and strategy are discussed.

We consider mixture experiments in which the proportions of the components must be non-negative and their sum must equal one. Thus, the experimental region for a mixture of components is a simplex. Li and Zhang (2017) made the conjecture that the pseudo component transformation of the lattice points in the simplex has a special property. In this paper, we show that this conjecture is not true in general. Furthermore, we refine this conjecture and prove the refined conjecture.

Humanity faces serious social and environmental problems, including climate change and biodiversity loss. Risks are increasing and conditions deteriorating. Increasingly, scientists, global policy experts, and the general public conclude that incremental approaches are insufficient and transformative change is needed across all sectors of society. However, the meaning of transformation is still unsettled in the literature, as is the proper role of science in fostering it. This paper is the first in a three-part series that adds to the discussion by proposing a novel science-driven research-and-development program aimed at societal transformation. More than a proposal, it offers a perspective and conceptual framework from which societal transformation might be approached and understood. While acknowledging the necessity of reform to existing societal systems (e.g., governance, economic, and financial systems), the focus of the series is on transformation understood as systems change or systems migration—the de novo development of and migration to new societal systems. The series provides definitions, aims, reasoning, worldview, and a theory of change, and discusses fitness metrics and design principles for new systems. This first paper proposes a worldview built using ideas from evolutionary biology, complex systems science, cognitive sciences, and information theory that is intended to serve as the foundation for the R&amp;D program.

For more than one hundred years, scientists dispute the correct interpretation of Lorentz transformations within the framework of the special theory of relativity of Albert Einstein. On the one hand, the changes in length, time and mass with increasing velocity are interpreted as apparent due to the observer dependence within special relativity. On the other hand, real changes are described corresponding to the experimental evidence of mass increase in particle accelerators or of clock delay. This ambiguity is accompanied by an ongoing controversy about valid Lorentz-transformed thermodynamic quantities such as entropy, pressure and temperature. In this paper is shown that the interpretation problem of the Lorentz transformations is genuinely anchored within the postulates of special relativity and can be solved on the basis of the thermodynamic approach of matter-energy equivalence, i.e. an energetic distinction between matter and mass. It is suggested that the velocity-dependent changes in state quantities are real in each case, in full agreement with the experimental evidence.

The study sought to gauge the impact of COVID-19 pandemic in unleashing digital transformation in the education sector in South Africa. In order to gauge the impact, the study tracked the rate at which the 4IR tools were used by various institutions during the COVID-19 lockdown. Data were obtained from secondary sources, mainly newspaper articles, magazines and peer-reviewed journals. The findings are that, in South Africa, during the lockdown, a variety of 4IR tools were unleashed from primary education to higher and tertiary education where educational activities switched to remote learning (online learning). These observations point to the fact that South Africa generally has, some pockets of excellence to drive the education sector into the 4IR, which has the potential to increase access. Access to education, particularly at a higher education level, has always been a challenge due to a limited number of spaces available. Much as this pandemic has brought with it massive human suffering across the globe, there is an opportunity to assess successes and failures of deployed technologies, costs associated with them, and scaling these technologies to improve access.

This paper presents a physical and mathematical model that has been developed in the framework of the approach used in the computational mechanics of materials. The model is designed to enable the study of the patterns of deformation and fracture of ceramic composites with a transformation-hardened matrix that are obtained by additive technologies at the mesoscopic and macroscopic levels under intense dynamic loading. The influence of the loading rate on the formation of the fracture and energy dissipation fronts for composite materials, based on the Al2O3 20%ZrO2 system, is shown. Nonlinear effects under intense dynamic loading in the considered composites are associated with the processes of self-organization of structural fragments at the mesoscopic level, as well as the occurrence of martensitic phase transformations in matrix volumes adjacent to the strengthening particles.