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Introduction: Down Syndrome (DS) is a common cause of intellectual disability with a possible glial-neuronal disruption. We assessed the effects of Cerebrolysin on the neurodevelopmental outcomes of infants with DS. Methods: This randomized controlled pilot trial included 64 infants with DS. They were allocated into a treatment group (n=32) who received weekly intramuscular Cerebrolysin injections for 12 months and a control group (n=32) who did not receive Cerebrolysin. We assessed the five domains of neurodevelopment (expressive communication, receptive communication, fine motor, gross motor, and cognitive development) for both groups at the ages of 6 months (basal visit), 12 months (first follow-up visit) and 18 months (second follow-up visit), using Bayley Scales of infant and toddler development (third edition). The secondary outcome was to detect the occurrence of Cerebrolysin-related side effects among the treatment group. Kendall's tau-b correlation coefficient, chi-square test, Fisher's exact test, Student's t-test, Mann-Whitney and Wilcoxon signed-rank tests were used for the statistical analysis. Results: Infants of both groups were matched with respect to gender, maternal level of education, their initial growth parameters, nutritional status, and socioeconomic status. No statistically significant differences existed between both groups regarding all neurodevelopmental domains on the basal visit, while on subsequent visits Z-scores improved in the treatment group, but not in the controls. Within the treatment group, there was a significant improvement in all domains at 12 and 18 months of age (p < 0.001). The improvement was mainly during the first 6 months of the study (p < 0.001 for all domains), and was best for fine motor and cognitive development. Only one infant in the treatment group developed fits and was ruled out from the study. Conclusion Weekly intramuscular injections of Cerebrolysin during the first year of life could possibly improve the neurodevelopmental outcomes and mental health in infants with DS. Further, large-scale studies are still needed to evaluate the efficacy and safety of Cerebrolysin among this sector of disabled infants.

The search model suggested in this study uses a unit-speed nanosensor to track the fluid's randomly linear flow particle, starting at the real line's origin. The nanosensor oscillates passing through the origin point (towards right and left) in the presence of a sequence of random points, and the particle's position is always changing with a random waiting time that varies with the Gaussian jump length. We may be able to consider the search distance as a function of a discounted effort-reward parameter (factor) because of this uncertainty. We demonstrate analytically how this parameter affects proving the existence of this model and reducing the expected value of the first collision time before the nanosensor returns a particle to the origin. To demonstrate the effectiveness of this model, a numerical example is provided. [ABSTRACT FROM AUTHOR]

We consider a discrete search problem to detect a hidden target on one of the M-intersected real lines at the origin. The target position is a vector of independent random variables with a known multivariate probability distribution that is symmetric around the origin. From the available information about the probability of the target, we can consider one bounded interval as a search space on each line. To maximize the detection probability, we divide each interval into a number of small subintervals. Some subintervals have low target probabilities; thus, we delete them and distribute their probabilities among the searched subintervals. The problem has a discrete version where each line contains a set of independent search subintervals. The search effort is bounded by a normal distribution. More than obtaining the maximum detection probability, we also need to get the minimum search effort to detect the target. After studying the stability of the minimum search effort, we present an illustrative example to show the effectiveness of our model. [ABSTRACT FROM AUTHOR]

This paper presents a new probabilistic coordinated search technique for finding a randomly located target in n-disjoint known regions using n-searchers. Each region contains one searcher. The searchers use advanced technology to communicate with each other. This paper aims to obtain the candidate utility function, namely the expected value of the time for detecting the target, and minimize this expected value considering a restricted amount of time. We present a particular case when the target has a multinomial distribution, which is essential for searching for a valuable target that is missing at sea or lost in a wilderness area. [ABSTRACT FROM AUTHOR]

This study uses two unit-speed searchers to solve the challenge of finding a randomly located target in a bounded region, such as searching for bodies found under the rubble resulting from the erosion of residential units due to horrific natural disasters. The search procedure begins at$(0,0)$(0,0). The region is subdivided into a limited even number of cells. The target’s position has a symmetric probability distribution. It is preferable to search in an optimal method in order to reduce the predicted time for discovering the target. An algorithm is used to generate the optimal search strategy. We discuss an example when the target has a symmetric truncated normal distribution. We provide an illustrated case to demonstrate this technique’s applicability. [ABSTRACT FROM AUTHOR]

Multiple types of microorganisms impact people with immunological illnesses simultaneously. In the presence of antibiotic resistance and random fluctuations such as rapid changes in the environment, the synchronization growth density varies stochastically from one species to another. Therefore, in this work, we study the multivariate probability distribution of the density of all species at the same time. Using the principle of independence of growth density for each species, we provide the statistical properties of this distribution. Furthermore, we estimate the parameters of the intrinsic rates of antibiotic action and bacterial cell growth for each variety, along with the strength of the intra-competitive pressures influencing this distribution. [ABSTRACT FROM AUTHOR]

In this paper, we consider one of the most important missing target search problems, in which the bounded linear search interval has been divided into a number of small sub-intervals. The probability of the target was calculated in each sub-interval through the distribution function of the target position; after truncation, the sub-intervals with a low probability of the target being present were removed. After that, the problem was transformed into a discrete search problem where the target resides in one of a set of sub-intervals. This problem has been solved to obtain the minimum effort required for target detection, where this effort is limited by a normal distribution. In addition, we obtain the maximum value of the target detection probability and also study the stability of the minimum search effort. Finally, we present an example to show the effectiveness and applicability of our model. [ABSTRACT FROM AUTHOR]

In order to detect radionuclides and dangerous substances in a fractured medium with the least amount of time and maximum probability, this paper provides a revolutionary tracking model. It relies on a coordinated tracking strategy using set of programmed nano-sensors. The radionuclide particle has a linear flow from d-directions to spread in a single direction with Random Walk process. We assume that this particle has been spread over a short period of time along phantomic cylindrical path inside the fluid. Two nano-sensors will track or search along each cylinder's route, starting from any location in the fragmented medium (space). A vector of random variables with a known probability distribution makes up the particle's initial position. We add the discounted effort-reward track as a reduction parameter in the distance function. The expected value of the first meeting time between one of the nano-sensors and a Random walk target will be reduced as a result. We extract various supplementary results regarding the optimal tracking strategy in addition to presenting the analytical solution that demonstrates the existence of a finite tracking technique. [ABSTRACT FROM AUTHOR]

This work presents the multivariate distribution of an n-dimensional independent Brownian particle's position at any time t in the fluid. To know the diffusion properties of particle in a fluid, we study some statistical properties of this distribution. Besides that, we study the estimated value of the diffusion coefficient to present more information about the particle's motion in the fluid. [ABSTRACT FROM AUTHOR]

Postoperative pulmonary complications (PPCs) are a challenge for anesthesiologists, especially following major surgeries. Using a high-flow nasal cannula (HFNC) postoperatively may decrease this challenge. The study aimed to assess the clinical effect of HFNC after extubation compared with simple face mask oxygen following major elective upper abdominal surgeries regarding PPCs, the need to escalate the respiratory support, days of intensive care unit stay, and days of hospital stay. Eighty adult patients were randomly assigned to two groups (each with 40 patients): group I received HFNC, while group II received a standard oxygen face mask. Five days later, postoperative pulmonary problems were evaluated. There was statistically significantly less lung atelectasis in the HFNC group than in the face mask group. The p-value was 0.029. There was no statistically significant difference concerning the need to escalate the respiratory support. The length of hospital and ICU stay days for the HFNC group was statistically significantly lower than for the face mask group. HFNC is more efficient than a simple oxygen face mask in lowering lung atelectasis following major upper abdominal procedures, improving oxygenation with decreasing respiratory rate and reducing ICU and hospital days of stay. [ABSTRACT FROM AUTHOR]

This paper presents the stronger moment conditions which are sufficient to show the finiteness of the first collision time between N -dimensional Gaussian jump particle and another N -dimensional Brownian particle in a fractured medium. To obtain these conditions, we use the triangular arrays of the random sequence vector which gives all probable positions of the first collision at any time. This study is an extension of the analytical study which is detailed in Alzulaibani and El-Hadidy [Int. J. Mod. Phys. B 33(28) (2019) 1950334] using the uniform integrability conditions. [ABSTRACT FROM AUTHOR]

Background The high prevalence rates and persistently increasing burden of depression indicate that there are still many unmet needs in the management of depression. Interpersonal psychotherapy (IPT) is one of the main evidence-based psychotherapeutic interventions for depression. Aim To evaluate the efficacy of short-term individual IPT in combination with pharmacotherapy, compared with pharmacotherapy alone, in the treatment of depression and assess its role in improving social functioning. Setting and design This study was conducted in Mansoura University hospitals and was an interventional randomized controlled trial. Patients and methods A total of 40 patients were recruited and randomized into either the interventional group or the control group. The interventional group received IPT in combination with selective serotonin reuptake inhibitor. IPT was in the form of once weekly session for 12 weeks. Patients in the control group received treatment with an selective serotonin reuptake inhibitor with appointments once every 2 weeks. Patients from both groups were assessed by the Montgomery–Asberg Depression Rating Scale and the Social Adjustment Scale Self-Report at the beginning and after 12 weeks. Statistical analysis IBM SPSS Statistics version 20.0 was used for statistical analysis. Results There were highly statistically significant improvements in depressive symptoms and in social functioning between the baseline assessments and after 12 weeks on the used scales in both groups. There was a trend for better improvement in the interventional group (IPT+pharmacotherapy) in depressive symptoms and in overall and specific domains of social functioning when compared with the control group. The interventional group showed statistically significant better improvements in social functioning when compared with the control group. Conclusions Combined IPT and pharmacotherapy shows clear benefits over pharmacotherapy alone, in both alleviating depressive symptoms and improvement of social functioning. [ABSTRACT FROM AUTHOR]

This paper aims to get a needed service by making the best decision of choosing one suitable company (queue) from K-independent Markovian queues (companies). The customers arrive at each queue according to a Poisson process. The service time of each customer has an exponential distribution. In a steady-state, the best decision depends on the minimum cost of detecting the suitable company which provides the best service with high speed (maximum service rate). To minimize the detection cost and maximize the probability of detection, we consider the search effort bounded by a Gaussian distribution as a function with a discounted parameter. The effectiveness of this model appears in a simulation study and the comparison with other models. [ABSTRACT FROM AUTHOR]

This paper discusses the existence of the tracking technique for a two-dimensional Brownian particle on a planar surface. The tracking process starts from the origin of the plane (intersection point of x and y axes). Accordingly, we derive the conditions that make the expected value of the first meeting time between the sensor and the particle finite. Also, we calculate the approximated expected value of the first meeting time. [ABSTRACT FROM AUTHOR]

We present an exact distribution for the bounded range of a Wiener process by using the truncation method of the probability distributions. Rather than deriving some statistical properties of this distribution including reliability properties, moments, stress-strength parameter, order statistics, Bonferroni curve, Lorenz curve, and Gini's index, a dataset is analyzed to clarify the effectiveness of this distribution. [ABSTRACT FROM AUTHOR]

This paper presents a novel tracking model to detect a d -dimensional random walk radionuclides and toxic chemicals in a fractured medium with minimum time and maximum probability. This model improves the physical and chemical properties of a fractured medium for a long time. It depends on a coordinated search technique with multiple sensors. The radionuclide particle has a linear flows on one direction from d -directions to spread. We consider this particle dispersed through a cylinder path in a very small time. The tracking or searching process in each cylinder path will be done by two sensors which start from any point in the fractured medium (space). The particle's initial position is a vector of random variables with a known probability distribution. More than presenting the analytical solution which shows the existence of a finite tracking technique, we derive some auxiliary results related to optimal tracking technique. Besides that, we derive this optimal tracking technique which minimizes the expected value of the first meeting time between one of the sensors and the radionuclide or the toxic chemical particle. The effectiveness of this model appears in some numerical results. [ABSTRACT FROM AUTHOR]

This paper discusses some methods based on the random search problem over the bound domain. The particle moves randomly with a bounded two-dimensional stochastic process in a bounded area. The physical phenomenon determines the boundaries of this area. We have a smart nanosensor tracks randomly for this particle. The necessary condition that maximizes the probability of the first meeting time between the nanosensor and the particle is derived. [ABSTRACT FROM AUTHOR]

This paper presents the discrete search technique on multi zones to detect a lost target by using k sensors. The search region is divided into k zones. These zones contain an equal number of states (cells) not necessarily identical. Each zone has a one sensor to detect the target. The target moves over the cells according to a random process. We consider the searching effort as a random variable with a known probability distribution. The detection function with the discounted reward function in a certain state j and time interval i are given. The distribution of the optimal effort that minimizes the probability of undetection is obtained after solving a discrete stochastic optimization problem. An algorithm is constructed to obtain the optimal solution as in the numerical application. [ABSTRACT FROM AUTHOR]