The requirements for efficient replacement of fossil fuel, combined with the growing energy crisis, put hydrogen production into focus. Efficient and cost-effective electrocatalysts are needed for H2 production, and novel strategies for their discovery must be developed. Here we utilized Kinetic Monte Carlo (KMC) simulations to demonstrate that hydrogen evolution reaction (HER) can be boosted via hydrogen spillover to the support when the catalyst surface is largely covered by adsorbed hydrogen under operating conditions. Based on the insights from KMC, we synthesized a series of reduced graphene oxide-supported catalysts and compared their activities towards HER in alkaline media with that of corresponding pure metals. For Ag, Au, and Zn, the support effect is negative, but for Pt, Pd, Fe, Co, and Ni, the presence of the support enhances HER activity. The HER volcano, constructed using calculated hydrogen binding energies and measured HER activities, shows a positive shift of the strong binding branch. This work demonstrates the possibilities of metal|support interface engineering for producing effective HER catalysts and provides general guidelines for choosing novel catalyst-support combinations for electrocatalytic hydrogen production.

We outline and test a new methodology for genuine simulation of stochastic processes with any dependence and any marginal distribution. We reproduce time dependence with a generalized, time symmetric or asymmetric, moving-average scheme. This implements linear filtering of non-Gaussian white noise, with the weights of the filter determined by analytical equations in terms of the autocovariance of the process. We approximate the marginal distribution of the process, irrespective of its type, using a number of its cumulants, which in turn determine the cumulants of white noise in a manner that can readily support the generation of random numbers from that approximation, so that it be applicable for stochastic simulation. The simulation method is genuine as it uses the process of interest directly without any transformation (e.g. normalization). We illustrate the method in a number of synthetic and real-world applications with either persistence or antipersistence, and with non-Gaussian marginal distributions that are bounded, thus making the problem more demanding. These include distributions bounded from both sides, such as uniform, and bounded form below, such as exponential and Pareto, possibly having a discontinuity at the origin (intermittence). All examples studied show the satisfactory performance of the method.

Three-dimensional (3D) printing technologies are transforming the design and manufacture of components and products across a variety of disciplines, however their application in the construction industry is still limited. Material deposition processes can achieve infinite geometries and have advanced from rapid prototyping and model-scale markets to their application in fabricating functional products, large objects and the construction of full-scale buildings. Many international projects have recently been realized and the construction industry is beginning to utilise these dynamic technologies. The potential advantages for integrating 3D printing into house construction are significant, these include the capacity for mass customization of designs and parameters for functional and aesthetic purposes, reduction in construction waste from highly precise material placement, and the use of recycled waste products in layer deposition materials. With the ultimate goal of improving construction efficiency and decreasing building costs, applying Strand7 Finite Element Analysis software, a numerical model was designed specifically for 3D printing in a cement mix incorporated with recycled waste product High Density Polyethylene (HDPE) and found that construction of an arched truss-like roof was structurally feasible without the need for steel reinforcements. The lab sizes prototypes were manufactured based on the destined numerical model by using a 3D printing technology. Currently available 3D printing technologies can be adopted for building construction and this paper discusses the applications, advantages, limitations and future directions of 3D printing as an innovative and viable solution for affordable house construction.

In this paper, the linear nonequilibrium thermodynamic approach is used to analyze energy processes in the wind energy conversion system (WECS), with a directly connected vertical axis wind turbine (VAWT) and vector controlled permanent magnet synchronous generator (PMSG). Both elements are considered as linear universal energy converters (EC) linearized at the points of the given range of common to VAWT and PMSG angular velocity. The dependences on the angular velocity of the coupling coefficients between the ECs input and output and the dimensionless parameters of their operating modes were received. This allows for choosing the optimal points of ECs operation according to the specified criteria and obtaining indicators of their maximum efficiency. To assess the quality of the cascade connection of two ECs, the appropriate coefficient was introduced, the dimensionless parameters and characteristics of the equivalent EC were obtained, and the conditions of its maximum efficiency were determined. Analysis of the VAWT-PMSG connection quality showed reserves for improving WECS efficiency. The impact of VAWT and PMSG variable parameters on the quality of this connection is studied, and further research directions are shown. The proposed thermodynamic approach allows an effective search for solutions for the efficiency improvement of various systems with energy transfer and transformation.

The determinants of enterprises providing ICT training in Europe are analyzed in this article. Data are collected from the European Innovation Scoreboard-EIS of the European Commission for 36 European countries in the period 2000-2019. Data are analyzed with Panel Data with Fixed Effects, Panel Data with Random Effects, Dynamic Panel, WLS and Pooled OLS. Results show that the number of enterprises providing ICT training in Europe is positively associate with “Innovation Index”, “Innovators”, “New Doctorate Graduates”, “Tertiary Education” and negatively associated with “Government Procurement of Advanced Technology Products”, “Human Resources”, and “Marketing or Organisational Innovators”. In adjunct a cluster analysis is performed by using k-Means algorithm optimized with the Silhouette Coefficient and we find the presence of four clusters. Finally, we use eight different machine learning algorithms to predict the value of the enterprises providing ICT training in Europe. We found that the Simple Tree Regression is the best predictor and that the number of enterprises providing ICT training in Europe is expected to growth of the 5,02%.

This article attempts to identify factors impacting on the quantity of municipal waste in Polish 2478 communes (LAU-2), taking into account the variability of particular determinants influence depending on their regional diversification. The analysis covers the years 2005-2018. The dependent variable is the volume of municipal waste in kg per capita, whereas the group of determinants include: economic and human development, uncontrolled dumping sites, population density, population at the working age, migration, tourism, urbanization, dwellings and housing, retail sales, entities, education and investments in waste management; The geographically weighted regression with spatial error term (GWR-SEM) was employed in this study. The model enabled not only the specification of the waste production determinants, but also the analysis of the variability in the strength and direction of dependencies occurring between the examined variables in individual communes. The results proved that the higher the level of education the less waste is generated (in the north-central Poland); the business entities and working-age population are crucial for the waste quantity in communes of eastern Poland; the factors most considerably as to regional range affecting the waste quantity are urban and business development; as to strength–higher education and the share of working age individuals;

Construction Design Management (DM) involves the coordination of design process and activity to ensure quality project design, yet it involves many challenges. This work reports on a collaborative Knowledge Transfer Project (KTP) that tackled several challenges faced by construction design management practitioners. Employing a design science research methodology (DSRM), qualitative analysis of semi-structured interviews with purposively identified design managers first uncovered real world concerns around design coordination, and designer performance monitoring. Then to address these concerns, a web-based design management prototype dashboard was developed which uses typical project data to aid the management of design coordination activity and facilitate design management task prioritization and reporting functionalities. By digitalizing selected design management processes to improve efficiency, and productivity, the visual reporting capability of the dashboard enables design production to be monitored at project and portfolio levels; trends in designer performance to be assessed and focus to be retained on technical queries (TQs) and requests for information (RFIs). By reporting on the development of this web-based Design Management prototype dashboard and illustrating how it can enhance design management productivity in construction firms, this work also provides further evidence of how employing a design science research methodology in construction can produce practical solutions that address real world construction concerns.

We examined special roles of the Central Nervous System (CNS) in an attempt to resolve the puzzle that chronic diseases cannot be cured by medicine. By exploring a skill-learning model, we found that the CNS is able to remember certain information reflecting biochemical and cellular (B&C) processes in the body. From the skill using ability, we found that the CNS is able to control basic B&C processes that drive and power the skill. From the ability to adjust forces and force direction of a physical act, we found that the CNS is able to adjust B&C processes that drive the physical act. From this adjustment capability, we further inferred that the CNS must also store information on the baseline B&C processes. As a whole, we found that the CNS can maintain information on baseline B&C processes, up-regulate or down-regulate the processes, and make comparisons in performing its regulatory functions. We found that chronic diseases are the results of deviated baseline B&C processes. Per the proved hypothesis, the CNS maintains deviated baseline B&C processes, and thus protects the body states of fully developed diseases. We then used the three CNS roles to explain that cancer progresses with increasing malignancy, cancer quickly returns after a surgery, cancer cells repopulate after chemotherapy and radiotherapy, cancer develops drug resistance inevitably, immune cells rebound after suppression, generally poor benefits of cancer drugs such as beta-blockers, etc. We further showed that long-term exercises generally push most, if not all, baseline B&C processes in diametrical opposing directions against the diseased B&C processes, implying that exercises play unique roles in reversing chronic diseases. Finally, we proposed several strategical approaches to resetting the CNS’ state memory as the essential condition for curing chronic diseases.

A smart city is a futuristic approach that evolves with new technologies. It can start as a simple community and evolve into future cities. In most developing countries, where the population growth is faster, and where the organization and the urbanization are slower, there is a serious need for a framework for progressive change towards sustainable cities. This article discusses the level of intelligence of smart city components and proposes indicators as well as a methodology for measuring intelligence based on the objectives to be achieved as well as a certain number of technical requirements and some cognitive processes implemented.

The pH-related metabolic paradigm has rapidly grown in cancer research and treatment. In this contribution, this recent oncological perspective has been laterally for the first time in order to integrate neurodegeneration within the energetics of the cancer acid-base conceptual frame. At all levels of study, molecular, biochemical, metabolic and clinical, the intimate nature of both processes appears to be opposite mechanisms occurring at the far ends of a physiopathological intracellular pH/extracellular pH (pHi/pHe) spectrum. This wide-ranged original approach now permits an increase in our understanding of these opposite processes, cancer and neurodegeneration, and, as a consequence, allows to propose new avenues of treatment based upon the intracellular and microenvironmental hydrogen ion dynamics regulating and deregulating the biochemistry and metabolism of both cancer and neural cells. Under the same perspective, the etiopathogenesis and special characteristics of multiple sclerosis (MS) becomes an excellent model for the study of neurodegenerative diseases and, utilizing this pioneering approach, we find that MS appears to be a metabolic disease even before an autoimmune one. Also within this paradigm, several important aspects of MS, from mitochondrial failure to microbiota functional abnormalities, are analyzed in depth.

Neurodegeneration is a major problem in neuroscience and medicine as it causes and worsens many neurological and psychiatric disorders. It involves gradual loss of neurons at different levels of the brain, affecting cognition, emotion, behavior, consciousness, and attention. Understanding the causes and consequences of neurodegeneration is crucial for identifying the risk factors, biomarkers, and treatments. However, the current therapies are mostly symptomatic and ineffective. Therefore, new and innovative methods, such as noninvasive brain stimulation (NIBS), are needed to modulate brain activity and plasticity in a safe and reversible manner. This field is rapidly developing, with a focus on exploring new clinical applications, mechanisms, and combinations of NIBS and drugs. This special issue covers the latest progress and challenges in the study of neurodegeneration in cognitive impairment and mood disorders from the experimental, clinical, and translational perspectives. It addresses the complexity and diversity of these conditions, the lack of disease-modifying treatments, the ethical and practical issues of conducting research in vulnerable and diverse populations, the integration and interpretation of data from multiple sources and modalities, and the development and validation of novel methods such as NIBS, artificial intelligence, and drug repurposing. Collaborative efforts among various stakeholders are needed to improve our knowledge and treatment of neurodegeneration underlying cognitive impairment and mood disorders.

L\'evy walks represent important modeling tools for variety of real life processes. Their natural scaling limits are known to be described by the so-called material fractional derivatives. So far these scaling limits were derived for spatially homogeneous walks, where Fourier and Laplace transforms represent natural tools of analysis. Here we derive the corresponding limiting equations in the case of position depending times and velocities of walks, where Fourier transforms cannot be effectively applied. In fact, we derive three different limits (specified by the way the process is stopped at an attempt to cross the boundary), leading to three different multi-dimensional versions of Caputo-Dzherbashian derivatives, which correspond to different boundary conditions for the generators of the related Feller semigroups and processes. Some other extensions and generalisations are analysed.

Backward electromagnetic waves are extraordinary waves with contra-directed phase velocity and energy flux. Unusual properties of the coherent nonlinear optical coupling of the phase-matched ordinary and backward electromagnetic waves with contra-directed energy fluxes are described which enable greatly-enhanced frequency and propagation direction conversion, parametrical amplification, as well as control of shape of the light pulses. Extraordinary transient processes that emerge in such metamaterials in pulsed regimes are described. The results of the numerical simulation of particular plasmonic metamaterials with hyperbolic dispersion are presented, which prove the possibility to match phases of such coupled guided ordinary and backward electromagnetic waves. Particular properties of the outlined processes in the proposed metamaterial are demonstrated through numerical simulations. Potential applications include ultra-miniature amplifiers, frequency changing reflectors, modulators, pulse shapers, and remotely actuated sensors.