Since autism was first recognised, prevalence has increased rapidly. The growing economic as well as social cost to society can only be mitigated by effective interventions and supports. It is therefore not surprising that most governments have developed public policy documents to address the management of autism. Over the past 40-50 years, meaningful evidence has accrued showing that interventions based on the scientific discipline of Applied Behaviour Analysis (ABA) can help people with autism reach their potential. In view of this, nearly all of North America has laws to mandate that ABA-based interventions are available through the health care systems. In contrast, across Europe there are no such laws. In fact, the National Institute for Health and Care Excellence (NICE), the body guiding health and social policy in the UK, concluded that it could not find any evidence to support ABA, and therefore could not recommend it. This paper addresses the reasons for these diametrically opposed perspectives. In particular, it examines what happens when health and social care policy is misinformed about effective autism intervention.

Deep learning is an emerging area of machine learning (ML) research. It comprises multiple hidden layers of artificial neural networks. The deep learn- ing methodology applies nonlinear transformations and model abstractions of high level in large databases. The recent advancements in deep learning architec- tures within numerous fields have already provided significant contributions in artificial intelligence. This article presents a state of the art survey on the contri- butions and the novel applications of deep learning. The following review chron- ologically presents how and in what major applications deep learning algorithms have been utilized. Furthermore, the superior and beneficial of the deep learning methodology and its hierarchy in layers and nonlinear operations are presented and compared with the more conventional algorithms in the common applica- tions. The state of the art survey further provides a general overview on the novel concept and the ever-increasing advantages and popularity of deep learning.

The recent outbreak of a new Coronavirus has developed into a global pandemic with about 10,5 million reported cases and over 500,000 deaths worldwide. Our prospective paper reports an updated analysis of the impact that this pandemic had on the Italian agri-food sector during the national lockdown and discusses why and how this unprecedented economic crisis could be a turning point to deal with the overall sustainability of food and agricultural systems in the frame of the forthcoming European Green Deal. Its introductory part includes a wide-ranging examination of the first quarter of pandemic emergency, with a specific focus on the primary production, to be understood as agriculture (i.e. crops and livestock, and their food products), fisheries and forestry. The effect on the typical food and wine exports, and the local environment tourism segments is also taken into account in this analysis, because of their old and deep roots into the cultural and historical heritage of the country. The subsequent part of the paper is centered on strategic lines and research networks for an efficient socio-economic and territorial restart, and a faster transition to sustainability in the frame of a circular bio-economy. Particular emphasis is given to the urgent need of investments in research and development concerning agriculture, in terms of not only a fruitful penetration of the agro-tech for a next-generation agri-food era, but also a deeper attention to the natural and environmental resources, including forestry. As for the rest of Europe, Italy demands actions to expand knowledge and strengthen research applied to technology transfer for innovation activities aimed at providing solutions for a climate neutral and resilient society, in reference to primary production to ensure food security and nutrition quality. Our expectation is that science and culture return to play a central role in national society, as their main actors are capable of making a pivotal contribution to renew and restart the whole primary sector and agri-food industry, addressing also social and environmental issues, and so accelerating the transition to sustainability.

Developing particles of different geometric anisotropic shapes are the hot topic since decades as they guarantee some special features of properties not possible through other means. Again, controlling atoms to develop certain size and shape particle is a quite challenging job. In this study, gold particles of different shapes are developed via pulse-based electronphoton-solution interface process. Here, it is discussed that gold atoms under certain transition state amalgamated at solution surface to develop monolayer assembly around the light glow of electrons and photons, which is known in plasma, generating through flowing argon gas copper capillary, which is known in cathode. The rate of uplifting gold atoms to solution surface is controlled under the fixed optimized entrance of forced energy electron streams and photons of high forcing energy. Uplifting gold atoms dissociated on dissociation of precursor under the dissipating heat energy resulted by propagating photonic current through graphite rod immersed in the solution, which is known in anode. On the other hand, packets of nano shape energy resulted by the controlled tuned pulse protocol developing tiny particles of own shape by binding transition state atoms of compact monolayer assembly. At solution surface, adjusting atoms of monolayer tiny particle into one-dimensional arrays under the disconcerted lateral forces following by their elongation under uniformly exerted opposite poles forces. This results into convert them in a structure of smooth elements where adjacently placed electrons and those in the outer rings of elongated atoms inter-connecting side-to-side by introducing orientational-based stretching of clamped energy knots. Tiny sized particles developed their atoms of one-dimensional arrays in structure of smooth elements exert an immersing force at favorable side tips and where many such tiny particles around the light glow work as one unit for each case resulting into pack by inter-connecting at inside their common point to nucleate the shape of certain particle. Depending on the development zone of such tiny sized particles and their amount of simultaneous packing under naturally maintained orientations develop their different geometric anisotropic shaped particles. At fixed precursor concentration, increasing the process time results into develop particles of low aspect ratio. Under tuned parameters, developing mechanisms of particles of high aspect ratio exhibiting unprecedented features are discussed.

As Solar Photovoltaics in buildings reaches maturity, grid integration and economic yield are topics of greater interest. The traditional design of photovoltaic installations has considered the optimal orientation of photovoltaic modules to be that which yields the maximum annual energy production. The influence of the consumption patterns and the hourly-variable electricity prices implies that this traditional optimal design might not be the most profitable. Using a full-year dataset for a residential installation, alternative installations using canopies and modules attached to the façades are simulated. Simulating the energy balances for different annual consumptions, it is found that the canopy and façade installations offer better self-consumption of the PV produced energy, reflected in a 9% higher self-consumption degree using modules on façades and a 5% using canopies. The economic evaluation under the new electricity tariffs in Spain shows a better profit for PV self-consumption, reducing by more than 2 years the time of return on investment. The analysis of different alternatives for an industrial PV has allowed us to identify several benefits for these orientations, such as an increase in annual energy production of up to 59% over the optimal-producing orientation, that are confirmed after several months of operation.

When considering implementation of shallow geothermal energy as a renewable source for heating and cooling of the building, special care should be taken in hydraulic design of borehole heat exchanger system. Laminar flow can occur in pipes due to usage of glycol mixture at low temperature or inadequate flow rate. This can lead to lower heat extraction and rejection rates of the exchanger because of higher thermal resistances. Furthermore, by increasing flow rate to achieve turbulent flow and satisfactory heat transfer rate can lead to increase the pressure drop of the system and oversizing of circulation pump which leads to impairment of seasonal coefficient of performance at the heat pump. Most frequently used borehole heat exchanger system in Europe is double-loop pipe system with smooth inner wall. Lately, development is focused on implementation of different configuration as well as with ribbed inner wall which ensures turbulent flow in the system, even at lower flow rates. At a location in Zagreb, classical and extended thermal response test was conducted on three different heat exchanger configurations in the same geological environment. With classic TRT test, thermogeological properties of the ground and thermal resistance of the borehole were determined for each smooth or turbulator pipe configuration. Extended Steady-State Thermal Response Step Test (TRST) was implemented, which incorporate series of power steps to determine borehole extraction rate at the define steady-state heat transfer conditions of 0/-3°C. Results show that heat exchangers with ribbed inner pipe wall have advantages over classic double-loop smooth pipe design, in terms of greater steady state heat extraction rate and more favorable hydraulic conditions.

Usually, in ground-penetrating radar (GPR) datasets the user defines the limits between the useful signal and the noise through standard filtering to isolate the effective signal as much as possible. However, there are true reflections that mask the coherent reflectors that can be considered noise. In archaeological sites these clutter reflections are caused by scattering with origin in subsurface elements (e.g., isolated masonry, ceramic objects and archaeological collapses). Its elimination is difficult because the wavelet parameters similar to coherent reflections and there is a risk of creating artifacts. In this study a procedure to filtering the clutter reflection noise (CRN) from GPR datasets is presented. The CRN filter is a singular value decomposition-based method (SVD), applied in the 2D spectral domain. This CRN filtering was tested in a dataset obtained from a controlled laboratory environment, to establish a mathematical control of this algorithm. Also, it has been applied in a 3D-GPR dataset acquired in the Roman villa of Horta da Torre (Fronteira, Portugal), which is an uncontrolled environment. The results show an increase in the quality of archaeological-GPR planimetry that were verified via archaeological excavation.

This article objectively assesses, the hypothesis of the streamline's shape theory and its formulated equation. The deduction of proof uses algebra rather than first-order partial differential equations to address the specific hypothesis of "Streamline's shape theory" from the fundamental perspective of applied mathematics and scientifically derives mathematical relations of the axioms and corollaries in the field of fluid dynamics. The algebraic methods employed provide progressively more distinct and precise solutions compared to first-order partial differential equations. The foremost objective of this work is to evaluate if the formulations of the streamline's shape theory can have solutions for inviscid-incompressible and viscid-compressible flows of Newtonian fluids and to identify their nature. Secondly, to understand how the topology of the body and the free-stream conditions affect these solutions with due regards to the shape and size of the body interacting with the fluid flow. Finally, to explore the possibility of this theory to develop a CFD solver for streamline simulation to reduce the experimentation in the analysis of flow-structure interactions of Newtonian fluids and also to identify its scope of applications and limitations.

(1) Background: Applied health services research (AHSR) relies upon coordination across multiple organizational boundaries. Our aim was to understand how competing organizational and professional goals enhance or impede the conduct of high quality AHSR. (2) Methods: A qualitative study was conducted in two local health care systems in the UK, linked to a feasibility trial of a clinic-based intervention in secondary care. Data collection involved 24 semi-structured interviews with research managers, clinical research staff, health professionals, and patients. (3) Results: This study required a dynamic network of interactions between heterogeneous health and social care stakeholders, each characterized by differing ways of organizing activities which constitute their core functions; cultures of collaboration and interaction and understanding of what research involves and how it contributes to patient care. These interrelated factors compounded the occupational and organizational boundaries that hindered communication and coordination. (4) Conclusions: Despite the strategic development of multiple organizations to foster inter-professional collaboration, the competing goals of research and clinical practice can impede the conduct of high quality AHSR. To remedy this requires the alignment and streamlining of organizational goals, so that all agencies involved in AHSR develop a shared understanding and mutual respect for the progress of evidence-based medicine and the complex and often nuanced environments in which it is created and practiced.

Several problems of radiative transfer are yet unsolved because of the difficulties of the calculations involved in them, especially if the intervening shapes are geometrically complex. The main goal of our investigation in this domain is to convert the formulas that were previously derived, into a graphical interface based on the projected solid-angle principle. Such procedure is now feasible by virtue of several widely diffused programs for Algorithms Aided Design (AAD). Accuracy and reliability of the process is controlled by means of the analytical software DianaX developed at an earlier stage by the authors. With this new approach the often cumbersome procedure of lighting and thermal exchange calculations can be simplified and made available for the neophyte, with the undeniable advantage of reduced computer time.

Pandemic scenario has significantly changed several factors of life, including teaching, and learning at university. The development of suitable teaching materials to support university studies is mandatory to overcome distance learning difficulties and improve traditional teaching methodologies. This work explains a novel method for the preparation of teaching materials for medical sciences, but also plausible for other learning fields. An encephalon was extracted and prepared by using this methodology for teaching purposes. More than 200 students evaluated several factors of the material prepared this way, indicating a better understanding (up to 80%) of theoretical contents related to this human section, together with a high usability and good physical appearance

We examine here the discrepancy between the radiated power, calculated from the Poynting flux at infinity, and the power loss due to radiation reaction for an accelerated charge. It is emphasized that one needs to maintain a clear distinction between the electromagnetic power received by distant observers and the mechanical power loss undergone by the charge. In literature both quantities are treated as almost synonymous, the two in general could, however, be quite different. It is shown that in the case of a periodic motion, the two formulations do yield the power loss in a time averaged sense to be the same, even though, the instantaneous rates are quite different. It is demonstrated that the discordance between the two power formulas merely reflects the difference in the power going in self-fields of the charge between the retarded and present times. In particular, in the case of a uniformly accelerated charge, power going into the self-fields at the present time is equal to the power that was going into the self-fields at the retarded time plus the power going in acceleration fields, usually called radiation. From a comparison of the far fields with the instantaneous location of the uniformly accelerated charge, it is shown that all its fields, including the acceleration fields, remain around the charge and are not radiated away from it.

With the increase in life expectancy and consequent aging of the world’s population, the prevalence of many neurodegenerative diseases is increasing, without concomitant improvement in diagnostics and therapeutics. These diseases share neuropathological hallmarks, including mitochondrial dysfunction. In fact, as mitochondrial alterations appear prior to neuronal cell death at an early phase of the disease onset, the study and modulation of mitochondrial alterations rise as promising strategies to predict and prevent neurotoxicity and neuronal cell death before the onset of cell viability alterations. In this work, differentiated SH-SY5Y cells were treated with the mitochondrial-targeted neurotoxicants 6-hydroxydopamine and rotenone. These compounds were used at different concentrations and for different time points to understand the similarities and differences in their mechanisms of action. To accomplishing this, data on mitochondrial parameters was acquired and analyzed using unsupervised (hierarchical clustering) and supervised (decision tree) machine learning methods. Both biochemical and computational analyses resulted in an evident distinction between the neurotoxic effects of 6-hydroxydopamine and rotenone, specifically for the highest concentrations of both compounds.

INT-FFT algorithm presented in this work uses an interpolation methodology to densify 3D-GPR datasets to sharpen images obtained in GPR surveys obtained in an archaeological context. It allows the reconstruction of missing data from the combined use of mathematical transforms (e.g., the Fourier and Curvelet transform) and predictive filters. This technique makes it possible to calculate the missing signal simply by meeting two requirements: the data in the frequency domain must be limited in a range of values and must be able to be represented by a distribution of Fourier coefficients (verified conditions). The INT-FFT algorithm uses an open-access routine (Suinterp, Seismic Unix) to interpolate the GPR profiles based on seismic trace interpolation. This process uses automatic event identification routines by calculating spatial derivatives to identify discontinuities in space by detecting very subtle changes in the signal, thus allowing for more efficient interpolation without artifacts or signal deterioration. We successfully tested the approach using GPR datasets from the Roman Villa of Horta da Torre (Fronteira, Portugal). The results show an increase in the geometric sharpness of the GPR reflectors and have not produced any numerical artifacts. The tests performed to apply the methodology to GPR-3D data allowed for assessing the interpolation efficiency, the level of recovery of missing data, and the level of information lost when one chooses to increase the distance between profiles in the acquisition stage of the data.

The field of applied behavior analysis has been directly involved in both research and applications of behavioral principles to improve the lives of captive zoo animals. Thirty years ago, Forthman and Ogden (1992) wrote one of the first papers documenting some of these efforts. Since that time, considerable work has been done using behavioral principles and procedures to guide zoo welfare efforts. The current paper re-examines and updates Forthman and Ogden’s original points, with attention to the five categories they detailed: (1) promotion of species-typical behavior, (2) reintroduction and repatriation of endangered species, (3) animal handling, (4) pest control, and (5) animal performances. In addition, we outline three current and future directions for behavior analytic endeavors: (i) experimental analyses of behavior and the zoo, (ii) applied behavior analysis and the zoo, and (iii) within-subject methodology and the zoo. The goal is to provide a framework that can guide future behavioral research in zoos, as well as create applications based on these empirical evaluations.

Research background – Learning and growth is one of the essential tools that companies ought to use in today's market economy in order to ensure their sustainable development in the long-term and, consequently, to achieve their maximum market value.Purpose – This article is predominantly of theoretical nature and considers the possibility of using the applied strategic analysis technique that was developed by the author to analyze learning and growth in the course of a study of strategic aspects of learning growth. The technique is based on the balanced scorecard system of the same name. Design/methodology/approach – Methodologically, the study is based on Kaplan and Norton's balanced scorecard concept and the author's concept of applied strategic analysis. Findings – It is shown that applied strategic analysis of learning and growth envisages comparative evaluation, diagnostics of deviations and predictions of the values of the balanced scorecard metrics of learning and growth in the dimension of strategic objectives. It includes analysis of the level of motivation in employees, the volume of authroity delegation and whether their personal goals match company goals; analysis of the expansion capacity of information systems, and analysis of the quality of retraining and the creativity level of employees. The applied strategic analysis of learning and growth with comparative evaluation of the metrics of the level of motivation in employees, the volume of delegation to them and of the match between their personal and corporate goals, and concludes with a prediction of the values of factor measures of the quality of retraining and creativity development in employees.Originality/value – The author comes to a conclusion that applied strategic analysis of learning and growth is a new and sufficiently effective instrucment for studying the strategic aspects of companies' performance that is associated with the training and development of their personnel. The instrument provides analytical support to strategic management as regards personnel training and development in today's conditions. Its results might be useful when working out managerial decisions for the company's short-term, medium-term and long-term plans in the area of learning and growth.