Miracle-dz/UniFAR-FTUs huggingface dataset:
Event‐triggered control of quasi‐LPV systems with communication delays

This paper addresses the dynamic periodic event‐triggered control for local stabilization of nonlinear networked control systems with communication delays. Based on a polytopic quasi‐linear parameter‐varying (quasi‐LPV) model of the nonlinear plant and the Lyapunov–Krasovskii stability theory, a local stability analysis condition is established. Then a constructive co‐design condition is proposed to jointly design the state‐feedback control law and the trigger rule. The local asymptotic stability of the closed‐loop equilibrium point of interest is ensured with a guaranteed region of attraction where trajectories remain inside even in the presence of communication delays. An optimization procedure is proposed to perform the co‐design considering the objectives of enlarging the guaranteed region of attraction and reducing the number of transmissions. Numerical examples indicate a trade‐off between these two objectives. Also, the examples illustrate the effectiveness of the proposed dynamic event‐triggered control co‐design approach over both its static counterpart and periodic time‐triggering mechanisms.
On the Fock space representation of functionals of the occupation field and their renormalization

(a) The purpose of this paper is to provide a representation of the occupation field and of its renormalized powers in a suitable Fock space. It develops an attempt made in [9] (which had been inspired by [ 111 and a comparison between [2] and [ 121). The main progress here lies in the representation of the renormalized powers of the occupation field for the two-dimensional Brownian motion. These renormalized powers have been defined by Dynkin [3,4] extending a result of Varadhan [14]. They are related to multiple selfintersections of Brownian paths. A review of this subject is made in [4], including papers by Dynkin, J. Rosen, Yor, and Le Gall. The Fock space we use contains Bose fields @,, $X and Fermi fields $,, 4, associated with the Green function of the process. Functionals of the occupation field L, = fb 6,(X,) ds can be represented in the Fock space by the same functionals applied to $,c$, + 1,5,$~ = 1,. We show that the renormalized powers of L, can be represented by Wick powers of I,. Actually, in two dimensions, the convergence of polynomials of the regularized occupation field can be proved quite naturally by lifting the problem to the Fock space. In [3], Dynkin had already used the connection between gaussian fields and occupation fields. It seems that Fermi fields are needed to get a representation allowing one to lift all computations involving occupation fields to the! Fock space. Most of the algebraic tools used here are standard in quantum field theory, and are often presented in a more operator-theoretical form. We have tried to give a self-contained approach, inspired in some parts by CL 5, 131. 88 0022-1236/88 $3.00
Exploration of Cu/g-C3N4 Nanocomposites as a Cost-Effective High-Performance Asymmetric Supercapacitor Electrode Material

This work reports the synthesis, characterization, and electrochemical analysis of composites comprised of copper nanoparticles grafted on graphitic carbon nitride (g-C<sub>3</sub>N<sub>4</sub>) for cost-effective, high-performance supercapacitor applications. A facile synthesis method was adopted to impregnate copper nanoparticles over g-C<sub>3</sub>N<sub>4</sub> sheets, and structural and morphological characterizations evidenced successful in situ grafting of Cu/g-C<sub>3</sub>N<sub>4</sub>. Different electrochemical investigations were accomplished to estimate the supercapacitive behavior of the designed electrode material. These electrochemical analyses unveiled that the designed nanocomposites showed superior electrochemical performances than pristine g-C<sub>3</sub>N<sub>4</sub>. The equivalent series resistance of 1.61 Ω was obtained for Cu/g-C<sub>3</sub>N<sub>4</sub>, which is lesser than base material g-C<sub>3</sub>N<sub>4</sub> sheets (2.19 Ω) from the Nyquist plot of EIS spectra. An asymmetric solid-state supercapacitor was designed, and a specific capacitance of 265.25 Fg<sup>−1</sup> at 0.5 Ag<sup>−1</sup> current density was found, along with an energy density of 36.87 Wh/kg at a power density of 2.50 kW/kg. Moreover, good cyclic consistency of 79.4% capacitance retention was obtained at 5 Ag<sup>−1</sup> at 5000 cycles. These electrochemical performances indicate that Cu/g-C<sub>3</sub>N<sub>4</sub> nanocomposites have a vast potential to use in energy storage perspective.
Hyperplanes and hamiltonian circuits in Perfect Matroid Designs with fixed basis

We study the number of hamiltonian circuits, containing a fixed basis, and the number of hyperplanes, which do not contain a fixed basis in perfect matroid designs. Projective and affine finite geometries are considered as examples of such matroids. We give algorithms to find the hyperplanes and the hamiltonian circuits in such cases.
Old Tails and New Trails in High Dimensions

Summary We discuss the motivation for dimension reduction in the context of the modern data revolution and introduce a key result in this field, the Johnson-Lindenstrauss flattening lemma. Then we leap into high-dimensional space for a glimpse of the phenomenon called concentration of measure, and use it to sketch a proof of the lemma. We end by tying this classical pure result to a current, revolutionary application.
Effect of add-on Gabapentin premedication on hemodynamic response to skull pin insertion

Background and Aims: Effectiveness of oral gabapentin premedication in suppressing response to laryngoscopy and tracheal intubation suggests its potential for attenuating skull pin insertion response. The present study was therefore planned to evaluate the effect of add-on oral gabapentin premedication to local anesthetic injection at pin insertion site in obtunding hemodynamic response. Material and Methods: Sixty adult patients posted for elective craniotomy were enrolled for a prospective, randomized and double-blinded study. Group I patients received gabapentin 900 mg orally as premedication whereas Group II patients received oral placebo. Both groups were administered subcutaneous (s.c.) injection (Inj) 2% lignocaine 2 mL at all four pin insertion sites. Mean arterial pressure (MAP) and heart rate (HR) were measured every 30 s for the initial 10 min. Increases in HR beyond 20% and MAP 30% above baseline were treated with bolus intravenous (IV) Inj propofol 30 mg. Quantitative data was compared using Student’s t-test and Mann Whitney U test, while categorical data was compared using Chi-square (χ2) test. Results: The increase in HR and MAP from baseline was significantly greater and it remained above baseline levels longer in Group II as compared to Group I. Twenty-one patients (70%) received rescue boluses of propofol with a mean dose of 45.00 ± 39.98 mg in Group II as compared to nine (30%) patients receiving mean of 18.20 ± 29.04 mg in Group I. (P = 0.015). The mean emergence time and sedation scores in both the groups were statistically similar (P = 0.060). The incidence of adverse effects like hypotension, bradycardia, nausea/vomiting, sedation or dry mouth were similar in both the groups. Conclusion: Add-on oral gabapentin premedication potentiates the effect of s.c. lignocaine Inj for suppression of skull pin insertion response.
Short-Term Oxygen Therapy Outcomes in COPD

Rationale Short-term oxygen therapy (STOT) is often prescribed to allow patients with chronic obstructive pulmonary disease (COPD) to be discharged safely from hospital following an acute illness. This practice is widely accepted without being based on evidence. Purpose Our objective was to describe the characteristics and outcomes of patients with COPD who received STOT. Patients and Methods The study was a secondary analysis of the INOX trial, a 4-year randomised trial of nocturnal oxygen in COPD. The trial indicated that nocturnal oxygen has no significant effect on survival or progression to LTOT, allowing our merging of patients who received nocturnal oxygen and those who received placebo into a single cohort to study the predictors and outcomes of STOT regardless of the treatment received during the trial. Results Among the 243 participants in the trial, 60 required STOT on at least one occasion during follow-up. Patients requiring STOT had more severe dyspnoea and lung function impairment, and lower PaO2 at baseline than those who did not. STOT was associated with subsequent LTOT requirement (hazard ratio [HR]: 4.59; 95% confidence interval [CI]: 2.98–7.07) and mortality (HR: 1.93; 95% CI: 1.15–3.24). The association between STOT and mortality was confounded by age, disease severity and comorbidities. Periods of STOT of more than one month and/or repeated prescriptions of STOT increased the probability of progression to LTOT (OR: 5.07; 95% CI: 1.48–18.8). Conclusion Following an acute respiratory illness in COPD, persistent hypoxaemia requiring STOT is a marker of disease progression towards the requirement for LTOT.
Improve the Detection and Segmentation of Lung Nodule X-ray Images

A combination of three lung nodule detectors has been proposed in this paper, also a new combination of lung nodule segmentation algorithm has been proposed. The proposed detector called Combined Lung Nodule Detector and the proposed segmentation is called Combined Distance Threshold (CDT). The dataset images used in this paper to evaluate lung nodule detection and segmentation is Japanese Society of Radiological Technology (JRST) which consist of 100 malignant cases plus 54 benign cases containing one nodule each. It is clear from results that the results of the CLND detector and CDT segmentation are better than the common traditional methods. As show in Fig. 7 (which represent as prove of concept) that the new proposed detector and the lung nodule segmentation algorithm can enhance the performance of Computer Aided Diagnoses system (CAD) which increase the performance of early detection of cancered lung nodule so can be treated early.
Effect of Adding Lecithin to Diets on Productive Performance of Laying Hens

This study was conducted in the poultry farm of the Department of Animal Production / College of the Agriculture / University of Anbar, during the period from 20/7/2021 to 15/10/2021, with the aim of studying the effect of adding lecithin to the diet on the productive performance of laying hens. 60 layer hens of the Lohmann Brown breed, aged 43 weeks were used in this experiment. The layer hens were distributed randomly into five treatments with four replicates per treatment (3 hens/repeat). Birds fed balanced diets contain 5 levels of lecithin as below: T1 (control groups ), T2, T3, T4 and T5 adding 0.25, 0.50, 0.75 and 1.0% of lecithin respectively to the basic diet. The results showed the superiority of the additional treatments in the productive traits during most of the production periods, As all the additional treatments during the most stages of production. All additive treatments showed superiority significantly during the third productive period, When calculating the general average, treatments T2 and T5 were significantly superior to the control treatment in the percentage of egg production (Hen Day Production%). Also, T5 showed superiority in the average egg weight during the second and third periods, and in the general average.T5 and T4 showed an increase in the egg mass-produced during the second period and three periods and with the general average. The results showed that there were significant differences between the different treatments in the rates of feed consumption during all stages of production. Also, the additive treatmentT5 showed the best feed conversion ratio during the second and third production periods and in the general average.
Stretchable inorganic nanomembrane electronics for healthcare devices

Flexible or stretchable electronic devices for healthcare technologies have attracted much attention in terms of usefulness to assist doctors in their operating rooms and to monitor patients’ physical conditions for a long period of time. Each device to monitor the patients’ physiological signals real-time, such as strain, pressure, temperature, and humidity, etc. has been reported recently. However, their limitations are found in acquisition of various physiological signals simultaneously because all the functions are not assembled in one skin-like electronic system. Here, we describe a skin-like, multi-functional healthcare system, which includes single crystalline silicon nanomembrane based sensors, nanoparticle-integrated non-volatile memory modules, electro-resistive thermal actuators, and drug delivery. Smart prosthetics coupled with therapeutic electronic system would provide new approaches to personalized healthcare.
Underdetermined DOA Estimation Using Arbitrary Planar Arrays via Coarray Manifold Separation

Conventional direction-of-arrival (DOA) estimation algorithms like MUSIC only allow localization of fewer number of sources than the number of physical sensors. In this paper, underdetermined azimuth localization (localizing more sources than the number of sensors) using arbitrary planar arrays has been proposed, using only second-order statistics of the received data. To achieve this, we utilize the difference coarray of the actual array and express the elements of the array covariance matrix as the signal received by the virtual sensors of the coarray. We explore the structure and geometry of the difference coarray of an $N$-element planar array and show that the coarray can provide an increased degree-of-freedom (DOF) of $\mathcal {O}(N^{2})$ which enables underdetermined localization. Then, we extend the manifold separation (MS) technique to the coarray to express the coarray steering matrix in terms of a Vandermonde structured matrix by designing a signal independent coarray characteristic matrix. As the signal model of a coarray is a single snapshot model, the Vandermonde structure enables us to perform a spatial smoothing type operation to restore the rank of the coarray covariance matrix. This allows us to propose a novel subspace-based algorithm, which we call the coarrayMS-MUSIC, to perform underdetermined source localization using arbitrary planar arrays. We have also introduced the polynomial rooting version of our algorithm called the coarrayMS-rootMUSIC. Finally, we have conducted extensive numerical simulations to verify the effectiveness and usefulness of the proposed methods.
Carbon nano tube field effect transistor based BBL-PTL full adders with level restorer structures

Full Adder (FA) is an important component not only in arithmetic circuits, but also in designing and development in all types of processors. The performance parameter of the one-bit full adder has been implemented to increase the speed of the system. In this paper two Carbon Nano Tube Field Effect Transistor (CNTFET) based level restorers are introduced to the sum circuit of the branch-based logic and pass transistor (BBL-PT) full adder. The proposed level restorers eliminate the existence of voltage step which is presented in the conventional full adder [1]. T.V. Rao et. al proposed level restorer circuits that have used +1.2 V supply rail voltage [2]. By using these level restorers, we could able to achieve good delay performance. The proposed 1-BIT full adder is graded high as it has less power consumption with the conventional 1-BIT full adders. The performance of the proposed CNTFET based BBL-PT FA with new level restorer structures are examined using Cadence with 32 nm CNTFET technology files with a supply rail voltage of +0.8 V.
Safety First! Overconfident CEOS and Reduced Workplace Accidents

Prior literature posits that overconfident CEOs overinvest in R&D and capital expenditure. We hypothesize that this overinvestment might have a positive externality in form of improved workplace safety. The results are strongly supportive: firms with overconfident CEOs experience significantly fewer industrial accidents. This is most pronounced in cash and capital constrained firms, where overconfident CEOs are more likely to continue to invest than are other firms notwithstanding the constraints. Regulations that blunted overconfident CEOs’ investments reduced the impact of overconfident CEOs on accidents. We ensure that our results are robust to alternative definitions of CEO overconfidence and different model specifications.
A Privacy-Preserving Approach to Identify COVID-19 Infection Origins via Volunteered Share of Health Data Records by Mobile Users

Human-beings are suffering from the rapid spread of COVID-19 throughout the world. In order to quickly identify, quarantine and cure the infected people, and to stop further infections, it is crucial to expose those origins who have been infected but are asymptomatic. However, this task is not easy, especially when the rigid security and privacy constraints on health records are taken into consideration. In this paper, we develop a new method to solve this problem. In the outbreak of a disease like COVID-19, the proposed method can find hidden infected people (or communities) through volunteered share of health data by some mobile users. Such volunteers only reveal whether they are healthy or infected e.g. through they mobile apps. This approach minimises health data disclosure and preserves privacy for the others. There are three steps in the proposed method. First, we borrow the idea from traditional epidemiology and design a novel algorithm to estimate the number of infection origins based on a Susceptible-Infected model. Second, we introduce the concept of ‘heavy centre’ to locate those origins. The probability of each node being infected will then be derived by building a spreading model based on the origins. To evaluate our method, we conduct a series of experiments on various networks with different structures. We examine the performance in estimating the number of origins as well as their origins. The results show that the proposed method yields higher accuracies than the existing methods, even when the fraction of volunteers is small.
Using Building Block Functions to Investigate a Building Block Hypothesis for Genetic

This paper presents building block functions, i.e., functions in which explicit schemas of high fitness are defined (BB functions, for short) which are useful in investigating the character of Genetic Programming (GP) search. One conjecture we believe to be answerable through experimentation with these functions is whether GP power that, when primary partial solutions are discovered, their numbers increase and GP crossover is able to combine them into increasingly larger sub-solutions and eventually find the solution? The functions should also provide insight into more detailed aspects of the roles of GP crossover and GP genotype growth.
Association between T-182C polymorphism of the norepinephrine transporter SLC6A2(NET) gene and major depressive disorder in Iraqi patients

Major sympathetic nervous system neurotransmitter that is responsible for consciousness, attention, cognitive ability, as well as the function of the majority of body systems, glands, and the immune system, is called Norepinephrine (NE). Norepinephrine transporter (NET) and norepinephrine binding sites are decreased in the brains of MDD patients, showing that dysregulated synaptic NE plays a role in the pathophysiology of MDD. Indeed, different NET polymorphism combinations may be linked to different MDD sub-phenotypes. The aim of the current work is to investigate or detect if there is a relation between T-182C gene polymorphism of SLC6A2 gene with major depressive disorder (MDD) in Iraqi patients.Materials and Methods: Blood specimens were collected from 70 individuals with MDD and 20 healthy individuals as a control group (both patients and control ages ranged between 18-65 years). DNA extracted from white blood cells (WBC), and the T-182C gene was detected and amplified by the PCR-ARMS technique. Results: The distribution of TT, TC, and CC genotype ratio of MDD group was 22.9%, 27.1%, and 50.0%, respectively. While the control group show genotype distribution as 35.0% for TT, 55.0% for TC and 10.0% for CC ratio.
Artificial Intelligence Scheme for Medical Images Classification and Prediction

Medicine is the industry where smart technologies and artificial intelligence are most commonly used. Medical imaging is usually used for tumor diagnosis; this includes Computer Tomography and Magnetic Resonance Imaging. Early tumor detection in various organs based on such images is important. This study intended to present an Adaptive Convolution Neural Networks (ACNN) based method for tumor detection in the brain. The ACNN will utilize a modified stochastic gradient descent (MSGD) training algorithm with adaptive momentum and learning rates to speed up the convergence of the error, which will speed up the classification process and improve the accuracy. MSGD is implemented such as when the loss increases, the learning rate increase, and vice versa. The proposed modifications allow the network to increase the learning rate at the beginning of the training process and slow down as the network outcomes reach stabilized conditions. The proposed method results were compared against the performance of several conventional combinations of CNN with several machine learning classifiers. The test results show that the proposed method outperformed the performance of the CNN with all the above-said adaptations. Accordingly, the contributions of this study are (1) improving the ACNN training algorithm for the tumor classification problem and (2) proposing original CNN architectures specialized for tumor classification. Keywords: artificial intelligence; convolution neural network; medical images processing; tumor classification, tumor detection.
Contrast discrimination and pattern masking: contrast gain control with fixed additive noise

We studied the visual mechanisms that serve to encode spatial contrast at threshold and supra-threshold levels. In a 2AFC contrast-discrimination task, observers had to detect the presence of a vertical 1 cycle deg-1 test grating (of contrast dc) that was superimposed on a similar vertical 1 cycle deg-1 pedestal grating, whereas in pattern masking the test grating was accompanied by a very different masking grating (horizontal 1 cycle deg-1, or oblique 3 cycles deg-1). When expressed as threshold contrast (dc at 75% correct) versus mask contrast (c) our results confirm previous ones in showing a characteristic 'dipper function' for contrast discrimination but a smoothly increasing threshold for pattern masking. However, fresh insight is gained by analysing and modelling performance (p; percent correct) as a joint function of (c, dc) - the performance surface. In contrast discrimination, psychometric functions (p versus logdc) are markedly less steep when c is above threshold, but in pattern masking this reduction of slope did not occur. We explored a standard gain-control model with six free parameters. Three parameters control the contrast response of the detection mechanism and one parameter weights the mask contrast in the cross-channel suppression effect. We assume that signal-detection performance (d') is limited by additive noise of constant variance. Noise level and lapse rate are also fitted parameters of the model. We show that this model accounts very accurately for the whole performance surface in both types of masking, and thus explains the threshold functions and the pattern of variation in psychometric slopes. The cross-channel weight is about 0.20. The model shows that the mechanism response to contrast increment (dc) is linearised by the presence of pedestal contrasts but remains nonlinear in pattern masking.