Recurrent neural networks (RNNs) transmit information over time through recurrent connections. In contrast, biological neural networks use many other temporal processing mechanisms. One of these mechanisms is the inter-neuron delays caused by varying axon properties. Recently, this feature was implemented in echo state networks (ESNs), a type of RNN, by assigning spatial locations to neurons and introducing distance-dependent inter-neuron delays. These delays were shown to significantly improve ESN task performance. However, thus far it is still unclear why distance-based delay networks (DDNs) perform bettern than ESNs. In this paper, we show that by optimizing inter-node delays, the memory capacity of the network matches the memory requirements of the task. As such, networks concentrate their memory capabilities to the points in the past which contain the most information for the task at hand. Moreover, we show that DDNs have more total linear memory capacity, with the same amount of non-linear processing power.

When researching rock blasting, the design parameters used for the analysis are usually the ge-ometric and charging ones. This study is based on a different approach, and focuses on the effect of timing, in specific the role of delays in the initiation sequence. The data come from the results of full-scale blasts. The experimental setting and location allowed to consider all parameter other than the number of delays as a constant. The experimental results are analyzed relating the delay var-iables to fragmentation and KPIs of downstream operations. It is shown how increasing the number of delays per unit of blasted rock and reducing simultaneous adjacent holes produces finer fragmentation, reduces the amount of fines, facilitates the secondary operations and reduces the risk of flyrock.

This research revealed the children with difficulties in attentional functions in healthy children attending primary school and aimed to identify the possible socio-demographic factors such as child’s age, gender and school’s grade that could influence attentive performance. The participants were 105 children aged 6-10 years (M age=8.6; SD=1.04), 57 females, attending primary schools. Family economic condition attested mostly at a medium level (63.5%) and parents had more frequently 13 years of schooling. The computerized test KiTAP was administered to children to assess attentional functions. Results showed higher frequency of omissions and false alarms and a reduced speed in Alertness, Go/No go and Sustained Attention tasks comparing to Italian norms. A series of hierarchical regression analyses were run with school grade, gender and current age as independent variables and mean reaction times (and standard deviation), number of omissions and of false alarms as dependent ones. Results showed male gender and attending a lower primary school grade impacting on lower attentional performance in several subtests. Females showed the best performances in distractibility and impulsive reaction tendencies tests, while higher school grade positively influenced the divided and sustained attention. These results could be useful to identify children with major attentional difficulties and some recommendations for futures studies and implement attention empowerment programmes were proposed.

This paper is concerned with the optimal linear quadratic Gaussian (LQG) control problem for discrete time-varying system with multiple input delays and multiplicative noises. The main contributions are two-fold. Firstly, when the state variables can be observed exactly, we obtain a necessary and suffcient condition for the multiple-delays system in terms of the non-homogeneous relationship between the state and costate, which is the solution to the coupled forward and backward stochastic difference equations. Secondly, when the state variables are partially observed, we derive a suboptimal linear output feedback controller for the discrete-time system based on the obtained results of the optimal LQG control. Numerical examples are shown to illustrate the proposed algorithm.

Delayed discharge for non-clinical reasons is defined as a period of stay that continues after a patient has been deemed medically fit to leave the hospital but is unable to do so for non-medical reasons. This circumstance overburdens the healthcare system and constitutes a major problem for healthcare systems and the patients themselves in this situation.The aim of this study was to evaluate the delay in effective discharge for non-medical reasons in patients admitted to acute care hospitals in Spain. A scoping review was conducted in order to revise and obtain an up-to-date review. The initial search strategy identified a total of 123 references, which were successively screened to a final selection of 13 studies. To conclude, delayed discharge from hospital for non-clinical reasons is a multifactorial problem. It may be due to factors internal or external to the hospital, as well as personal factors. The main causes of the delay are similar among the studies found, as are the clinical characteristics of the patients, most of whom are elderly, frail, and more dependent due to declining functional capacities. Further studies addressing the socio-familial characteristics of the patients and the perspective of the patient and families would be necessary.

Why do neurons communicate through spikes? By definition, spikes are all-or-none neural events which occur at continuous times. In other words, spikes are on one side binary, existing or not without further details, and on the other can occur at any asynchronous time, without the need for a centralized clock. This stands in stark contrast to the analog representation of values and the discretized timing classically used in digital processing and at the base of modern-day neural networks. As neural systems almost systematically use this so-called event-based representation in the living world, a better understanding of this phenomenon remains a fundamental challenge in neurobiology in order to better interpret the profusion of recorded data. With the growing need for intelligent embedded systems, it also emerges as a new computing paradigm to enable the efficient operation of a new class of sensors and event-based computers, called neuromorphic, which could enable significant gains in computation time and energy consumption — a major societal issue in the era of the digital economy and global warming. In this review paper, we provide evidence from biology, theory and engineering that the precise timing of spikes plays a crucial role in our understanding of the efficiency of neural networks.

The open communication is an exigent need for future power system where the time delay is unavoidable. In order to secure the stability of the grid, the frequency must remain within its limited range which is achieved through the load frequency control. The load frequency control signals are transmitted through communication networks which induces time delay that could destabilize the power systems. So, in order to guarantee the stability the delay margin should be computed. In this paper, we present a new method for calculating the delay margin in load frequency control systems. The transcendental time delay characteristics equation is transformed to frequency dependant equation. The spectral radius is used to find the frequencies at which the roots crosses the imaginary axis. The crossing frequencies are determined through the sweeping test and the binary iteration algorithm. A one-area load frequency control system is chosen as case study. The effectiveness of the proposed method has been proved through comparing with the most recent published methods. The method shows its merit with less conservativeness and less computations. The PI controller gains are preferable to be chosen large to reduce the damping, however, the delay margin decreases with increasing the PI controller gains.

Over-capacity flight scheduling by commercial airlines due to the surging demand in recent years creates congestion and significant delays at major airports. This maximizing throughput attitude calls for tactical flight rescheduling to comply with airports’ capacity limitations and distribute the peak hour demand over the course of a day. Such displacements of flights may cause significant problems and costs for airlines and some cancellations or missed connections for the passengers. This paper presents an optimization model for flight rescheduling at a schedule-coordinated airport to minimize congestion and flight delays. The optimization model is used to make better scheduling intervention decisions considering the airport resource constraints and safety of operation. We have also developed a simulation method to replicate arrival and departure processes in such an airport. The simulation adheres to a first come first served (FCFS) discipline and enforces runway capacity constraints and minimum turnaround times. We compare the delays caused by an ad hoc FCFS operation with those obtained by the optimization model. Computational results from a case study demonstrate that a reduction of 40.7% and 61.6% in total delay times for the arrival and departure flights can be achieved by the optimization model. It also facilitates implementing a collaborative decision-making system for better coordination with commercial airlines.

In this paper, initially a mathematical model is formulated for transient frequency of power system considering time delays which occur while transmitting the control signals in open communication infrastructure. Time delay negligence in a power system leads to improper measurement of frequency variation in power system. The study of impact of time delays on the stability of power system is performed by estimating the decay rate of frequency wave form using Kalman Filter (KF). In power system, there is a possibility of multiple time delays. This paper also focusses on developing Interacting Multiple Model (IMM) Algorithm with multiple model space using Kalman Filter (KF) as state estimator tool. The multiple time delays in power system is considered as multiple model space. The result shows that KF provides better estimate of correct model for a particular input-set. The qualitative properties of Riccati difference equation (RDE) in terms of state error covariance of IMMKF are also analyzed and presented.

Maternal infectious disease may pose considerable challenges to the fetal health due to the distribution of important elements of the sanguine and lymphatic system from the mother via the umbilical cord. The mother and the fetus have a degree of interdependence that is similar to the one between the eukaryotic cell and the mitochondrion, particularly during the first half term of the pregnancy, which explains the increased appetite of the expecting mother during the first stages of the fetal development. There is a solid bridge between the adaptive immune system and the encephalon that was only discovered a few decades ago. As a result, scientists may still be in the introductory stages of research, and there might be a significant and profound degree of association between the immune system and a healthy neurological development. There is a significant link between the onset of significant maternal infectious disease and the onset of neurodevelopmental disease in the fetus, and virtually all immune cells play major roles in the promotion and inhibition of neurogenesis alike. Likewise, there is a probability that maternal infectious diseases during pregnancy represent a risk factor of fetal neurodevelopmental disease, as a pressurised development of the adaptive immune memory could result in a pressurised or inhibited neurological development, which both can result in a delayed development of certain sub-regions of the brain. For example, the fetus may display poorer social abilities and sharp analytical skills later in life, which is an important sign of neurodevelopmental disease. A pressurised development of the adaptive immune memory could not require the development of a significant form of disease, but rather just a sharp rate of immune preparation against several important pathogenic agents during the introductory stages of life, when the encephalon experiences the sharpest increase rate in development. The problem per se is not the process of immunisation, but a much sharper process of immunisation over the first stages of life in case of an exposure to one dangerous pathogen or more numerous kinds of pathogens and antigens that normally cause moderate disease morbidity. The more dangerous the microbe is, the sharper the development of the adaptive immune memory will be, and the same happens in the case of an increased number of infectious microbes and antigens that infected the cells of the mothers and the fetuses in cause, and this may, in the majority of the situations, still be the case even if the pathogens are already significantly weakened or lifeless, given that the gain of adaptive immune memory alone constitutes an important factor of neurogenesis and an increased rate of neurological development, and that the infant will become almost or fully protected against the pathogens in cause, despite not having had experienced the disease beforehand. In this case, neurodevelopmental delays are possibly not caused by an impaired neurogenesis, but by an excessive one, whilst maternal infection-associated neurodevelopmental delays may be caused by an impaired neurogenesis. Nevertheless, the aetiology of immunity-related neurodevelopmental delays may be more complex in nature and implicate a chronological and spatial sequence of induced excedentary and deficitary rates of neurogenesis, hence reflecting the incredibly complex nature and various forms of neurodevelopmental disease. It is important to mention that a single dose of infant immunisation brings significantly lower risks of adverse neurological events than the onset of a significant maternal infectious disease during pregnancy. The objective of paediatric neuro-immunological studies may be to improve the understanding of the association between a healthy immune developmental rate and a balanced ratio of the developmental rates of important brain regions and sub-regions.