In this paper, we introduce generalized entropy, the acceleration of its entropy and its the partial entropy. We assume that generalized entropy can be expressed as a second-order polynomial by applying the idea of logistics function to its entropy. In other words, we assume that the acceleration of generalized entropy is a constant. Besides, we show that the negative inverse of the partial entropy can express Newton's classical gravity, which is an inverse square law. By applying these concepts, we attempt to explain that 1) Gravity is constant within small distances with some conditions. It is possible that gravity have 5-states within small distance. Furthermore, within small distance, we show the possibility that the gravitational potential and the Coulomb potential can be treated in the same way, that 2) The rotation speed of a galaxy does not depend on its radius if the radius is within the size level of the universe. (The galaxy rotation curve problem), and that 3) The gravitational acceleration toward the center changes at long distances compared to the classical theory of gravity. We show that it is an extension of Newton's classical theory of gravity. Furthermore, we show that the possibility of the existence of some constants which controls gravity and the speed of galaxies, and that gravity may relate on entropy.

According to evolutionary cancer cell biology ECCB, cancer stem cells do not arise from normal stem cells, but rather from the functional ACD phenotype of the germline. This phenotype proliferates through asymmetric cell division, producing self-renewing cells and non-proliferating daughter cells with cancer stem cell qualities (CSCs). ECCB posits that cancer stem cells themselves do not proliferate. Similar to protists, there is a close reciprocal relationship between both sister cells that collectively form a germ and stem cell lineage. These sister cells share functional roles: the proliferating cancer germline cells generate stem cells, while the non-proliferating cancer stem cells accumulate progenitor cells for new germline clones. ECCB distinguishes between primary CSCs, which are associated with carcinogenesis and primary tumors, and secondary CSCs, which are linked to metastases. This unicellular stem cell system is homologous to that of parasitic protists, such as amoebae. Both cancer stem cells and amoebae stem cells are generated by an oxygen-sensitive germline and are vulnerable to damage when oxygen levels exceed 6.0% (germline hyperoxia). Oxygen concentrations above this threshold can damage the germline genome. Dysfunctional germline cells do not undergo senescence; instead, they continue to cycle through defective symmetric cell cycles However, to regain functionality, the germline genome requires repair by hyperpolyploid giant cells known as native PGCCs, which are homologous to the multinucleated genome repair structures MGRS found in protists. Native PGCCs differ in some respects from genotoxic-induced PGCCs

This paper is devoted to the study of multi-dimensional integral transform with Fox H-function in the kernel in weighted spaces integrable functions in the domain R+n with positive coordinates. Mapping properties such as the boundedness, the range, the representations of the considered transformation are established.

Background: 3D virtual reality (VR) Motionless Imagery Exercise through Avatar (MIEA) was developed to improve elderly’s psychological (cognitive and emotional) and physical health. This study observed the impact of this program on the cognitive functions and emotional well-being and the electrophysiological changes in older adults. Methods: This study was conducted using a randomized controlled trial design. The participants included 38 adults, 65 to 84 years of age, who were physically mobile and neurologically healthy. Among them, 19 participants were assigned to the experimental group, who underwent exercises using elderly avatars in a VR virtual exercise program. The other 19 participants were assigned to the control group who underwent the VR program. Both groups engaged in the VR intervention for 20 minutes three times a week, over six weeks. Results: The cognitive functions, including attention restraint, working memory, and phonemic fluency, of the experimental group showed significant improvements compared to the control group. Regarding emotional well-being, the experimental group showed greater self-efficacy. The electrophysiological changes revealed similar patterns to exercise-induced reactions in electromyography of the experimental group after intervention. Conclusions: These findings confirm that participation in 3D VR MIEA enhances cognitive functions and physical self-efficacy among the elderly. Therefore, 3D VR MIEA can be utilized in the rehabilitation therapy of patients or elderly with limited physical activity.

This paper proposes training improvement methods of artificial neural networks (ANN) trajectory predictors. First, a dynamic power system time-series trajectory is split into several different segments to simplify the original ANN training problem. Moreover, the time-derivative of the trajectory is included to obtain an augmented loss function. Compared to previous studies which mainly focused on increasing the prediction accuracy, the aim of these novel techniques is to reduce the computational burden where the ANN output performance is still acceptable. The effectiveness of the developed methods is validated based on the WSCC three-machine nine-bus and IEEE 39-bus system models. The mean absolute error (MAE) and trajectory prediction results are analyzed, in which the numbers of neurons, hidden layers, and training epochs are constrained during the ANN training process. Rotor-angle difference between generators and the system frequency are investigated as the dynamic trajectories of the power system models. It is revealed that when the ANN architecture and epochs are constrained, the MAE results can be reduced, and the ANN training results can better reflect the original trajectory using the improvement approaches.

The purpose of the study was to identify factors characterizing a decrease in LV global systolic function in patients with ST-segment elevation myocardial infarction (STEMI) after revascularization using cardiac magnetic resonance imaging (MRI)-based ischemic injury pattern and laboratory parameters sensu left ventricular global systolic function. A total of 109 STEMI patients were examined. The patients underwent contrast-enhanced cardiac MRI with a 1.5 Tesla GE SIGNA Voyager (GE HealthCare, USA) on the 7th-10th days from the onset of the disease. According to cardiac MRI analysis, the patients were divided into the following groups with regard to left ventricular ejection fraction (LVEF) values: group 1 – patients with LVEF ≥50%; group 2 – patients with mildly reduced LVEF 40-49%; group 3 – patients with low LVEF <40%. A predominance of most parameters of the ischemic injury pattern was noted in patients with mildly reduced and low LVEF versus patient group with LVEF ≥50%. Some risk factors for a decrease in LVEF <50% systolic function in STEMI patients after revascularization were revealed: male gender; time from the onset of the anginal attack to revascularization; coronary artery status; several LV parameters; ischemic injury characteristics; natriuretic peptide and troponin I levels.

Here, we describe the bicomplex (p,q)- Fibonacci numbers and the bicomplex (p,q)- Fibonacci quaternions that are based on these numbers and give some of their equations, including the Binet formula, generating function, Catalan, Cassini, d’Ocagne’s identities, and some summation formulas for both of them. Finally, we create a matrix for bicomplex (p,q)- Fibonacci quaternions, and we obtain a determinant of a special matrix that gives the terms of that quaternion.

This paper addresses the Collatz Conjecture, an open question in mathematics that postulates all positive integers will eventually reach one when a pair of specific operations are repeatedly applied. Despite its apparent simplicity, the conjecture lacks a formal proof. To tackle this enigma, we introduce Algebraic Inverse Trees (AITs), data structures that trace inverse operations of the Collatz sequence. This new approach not only elaborates our unique methodology but also sheds light on the underlying complexities of the Collatz Conjecture.

Omega-3 polyunsaturated fatty acids (PUFA) play a pivotal role in health, wellbeing, and inflammatory diseases in humans. Lack of omega-3 consumption is associated with diseases. Specialized Pro-resolving Mediators (SPM) are produced from Omega-3-PUFAs and accelerate resolution of inflammation. They are classified as resolvins, maresins, protectins, and lipoxins. SPMs actions in resolution consist in limiting neutrophilic infiltration, promote the clearance of apoptotic cell and cellular debris, enhancing efferocytosis and phagocytosis, counter regulate the production of pro-inflammatory mediators such as chemokines and cytokines, and promote pro-resolving macrophage phenotype. We identified temporal plasma and serum increases of SPMs after 6 g of oral supplementation of SPM-enriched emulsion in ten healthy subjects. We also described temporal increases of omega-3, as well as pharmacokinetics fundamentals in plasma and serum using LC-MS/MS lipid profiling. These results provide evidence of temporal increases of SPMs that together support the idea that given oral supplementation is a good source of essential bioactive SPMs.

An overview of the link between nonequilibrium thermodynamics and complexity theory is offered. It is shown how the rate of entropy production can be quantified through the spectrum of the Lyapunov exponents. It was shown how the entropy production per unit of time meets the necessary and sufficient conditions to be a Lyapunov function and constitutes per se an extremal principle. The entropy production fractal dimension conjecture was established. It is shown how the rate of entropy production as a non-extremal criterion represents an alternative way of sensitivity analysis of differential equations. Finally, an extension to biophysical-chemical systems, on the one hand, the use of the dissipation function is shown, as a thermodynamic potential out of equilibrium, in the characterization of biological phase transitions. On the other hand, it was evidenced how the rate of entropy production represents a physical quantity to evaluate the complexity and robustness of cancer.

Objective: To examine the effect of bilateral total lobectomy and unilateral total lobectomy on improving thyroid function in patients with thyroid micropapillary carcinoma treated with euthyrox. Methods: The study was conducted on 68 patients with thyroid micro papillary carcinoma treated with euthyroxwho had been surgically treated with euthyrox in our hospital between January 2018 and December 2019. On the basis of random number grouping, they were divided into control groups (n = 34, bilateral total lobectomy) and observation groups (n = 34, unilateral total lobectomy plus isthmectomy). Thyroid function, free triiodothyronine (FT3), thyroid hormone (TSH), and voice function (VHI score) of the two groups were compared.Results: In comparison to the control group, the observation group had shorter incision lengths, shorter operation times, and shorter hospital stays, as well as less intraoperative bleeding and drainage volume, and the difference was statistically significant (P < 0.05); As compared with the control group, the observation group had higher FT4 and FT3 levels as well as lower TSH levels, a statistically significant difference (P < 0.05).VHI scores of emotions, function, physiology, and other voice functions were significantly lower among the observation group than those of the control group (P < 0.05).Conclusion: A unilateral total lobectomy with adjacent isthmus resection in patients with thyroid micro papillary carcinoma can yield ideal results, accelerate the time taken for surgical rehabilitation, improve thyroid function, thereby improving voice quality, as well as improve the overall prognosis of the patient.

Visual signals are the upmost important source for robots, vehicles or machines to achieve human-like intelligence. Human beings heavily depend on binocular vision to understand the dynamically changing world. Similarly, intelligent robots or machines must also have the innate capabilities of perceiving knowledge from visual signals. Until today, one of the biggest challenges faced by intelligent robots or machines is the matching in stereovision. In this paper, we present the details of a new principle toward achieving a robust matching solution which leverages on the use and integration of top-down image sampling strategy, hybrid feature extraction, and RCE neural network for incremental learning (i.e., cognition) as well as robust match-maker (i.e., recognition). A preliminary version of the proposed solution has been implemented and tested with data from Maritime RobotX Challenge (www.robotx.org). The contribution of this paper is to attract more research interest and effort toward this new direction which may eventually lead to the development of robust solutions expected by future stereovision systems in intelligent robots, vehicles and machines.

A series of water diversion projects to address the uneven distribution of water resources in China involve the construction of a large number of hydraulic tunnels. As the lining structure that maintains the stability and durability of the tunnels, it is prone to durability damage during the operation process, which in turn affects the water transmission safety and water supply capacity. Therefore, it is important to evaluate the durability of hydraulic tunnel lining structure. Considering the randomness and fuzziness of the factors affecting the durability of hydraulic tunnel lining structure, this paper proposes a comprehensive evaluation model based on the coupling of set-pair analysis and extension. The G1 method and the simple correlation function method are used to determine the subjective and objective weights of the evaluation indexes respectively, and the combination weight is assigned based on the principle of minimum entropy; the set-pair analysis principle is used to establish the linkage affiliation function, calculate the comprehensive linkage affiliation of the object to be evaluated, and the maximum affiliation principle is used to judge the durability level of the hydraulic tunnel lining structure. Finally, taking a section of hydraulic tunnel as an example, the model proposed in this paper is used to calculate its durability grade as Class III, with the set-pair potential SHI(H) = 7.5856, which is consistent with the actual engineering practice, and a comparative study is done in combination with the AHP-Extenics method. It is verified that the evaluation model can scientifically and reasonably evaluate the durability of hydraulic tunnel lining structure, providing a basis for subsequent maintenance and reinforcement.

Variable-DOF (or kinematotropic) mechanisms are a class of reconfigurable mechanisms. The number of variable-DOF multi-loop planar mechanisms proposed so far is very limited. This paper proposes a novel 8-link variable-DOF planar mechanism with five motion modes. Firstly, a description of the 8-link variable-DOF planar mechanism is presented. Reconfiguration analysis of the 8-link mechanism is then carried out using an elimination and algebraic geometry hybrid approach. The analysis shows that the 8-link mechanism has one 2-DOF motion mode and four 1-DOF motion modes and can switch among three motion modes at four transition configurations and between two motion modes at the remaining four transition configurations. Geometric characteristics of the mechanism in different motion modes are also revealed. Unlike the variable-DOF planar mechanisms found in literature, the proposed 8-link mechanism has two inactive joints in one of its 1-DOF motion modes, and both 4R kinematic sub-chains of the mechanism must appear as parallelograms in a pair or anti-parallelograms in a pair in the same motion mode. As a by-product, a method for factoring trigonometric functions in two angles is proposed.

This paper presents the symmetries of differential equations associated with one-variable and Bivariate Hermite polynomials by proposing a representation of Lie algebra for these differential operators. Applying the Baker-Campbell-Hausdorff formula to these algebras, results in new relations and generating functions in one-variable and Bivariate Hermite polynomials. A general form of representation for other orthogonal polynomials such as Laguerre polynomials is introduced.

Taking care of stroke survivors can be taxing, however, it was understudied in Malaysia. This study aims to describe the burden of informal stroke caregivers within three months after hospital discharge. A longitudinal study design was conducted. Acute stroke survivors and their informal caregivers were recruited prior to hospital discharge, and the caregivers were interviewed by phone. Self-reported caregiver burdens were measured with Zarit Caregiver Burden Interview – Malay version (MZBI) and Caregiver Assessment of Function and Upset – Malay version (Malay-CAFU). The MZBI and Malay-CAFU scores were collected four times within three months. A total of 85 stroke survivors and 155 informal caregivers were recruited, with 58.1% of the caregivers were female. The stroke survivors had two caregivers on average. The mean (SD) scores for the three scales show a reduction, from 27.42 (12.73) in the first week to 17.77 (11.20) in the third month for MZBI, from 1.14 (0.94) to 0.62 (0.64) for instrumental activities of daily livings (IADL) of Malay-CAFU upset scale and 1.36 (1.00) to 0.78 (0.65) for activities of daily living (ADL) of Malay-CAFU upset scale in the same period. Stroke survivors may have several caregivers, usually their spouses or children. Within a short period, the caregiver’s burden was reduced. Early psychosocial support to alleviate the caregiver burden may be necessary.

The age of information (AoI) metric was proposed to measure the freshness of messages obtained at the terminal node of a status updating system. In this paper, the AoI of discrete time status updating system with probabilistic packet preemption is investigated by analyzing the steady state of a three-dimensional discrete stochastic process. Assuming the queue used in system is Ber/Geo/1/2*/η, which represents that the system size is 2 and the packet in buffer can be preempted by fresher packet with probability η. Instead of considering system’s AoI separately, we use a three-dimensional state vector (n,m,l) to simultaneously track the real time changes of the AoI, the age of packet in server, and the age of packet waiting in buffer. We give the explicit expression of system’s average AoI, and show that the average AoI of system without packet preemption is obtained by letting η=0. When η is set to 1, the mean of AoI of system having Ber/Geo/1/2* queue is obtained as well. Combining the results we have obtained and comparing them with corresponding average continuous AoIs, we propose a possible relationship between average discrete AoI with Ber/Geo/1/c queue and the average continuous AoI with M/M/1/c queue. For each of two extreme cases where η=0 and η=1, we also determine the stationary distribution of AoI using the probability generation function (PGF) method. The relations between average AoI and the packet preemption probability η, as well as AoI’s distribution curves in two extreme cases are illustrated by numerical simulations. Notice that the probabilistic packet preemption may occur, for example, in an energy harvest (EH) node of wireless sensor network, where the packet in buffer can be replaced only when the node collects enough energy. In particular, to exhibit the usefulness of our idea and methods and highlight the merits of considering discrete time systems, in this paper we give much more explanations showing that how the results about continuous AoI is derived by analyzing the corresponding discrete time system, and how the discrete age analysis is generalized to the system with multiple sources. In terms of packet service process, we also propose our idea to analyze system’s AoI when the service time distribution is relaxed to be arbitrary.

We study the connection between the phase and the amplitude of the wave function and the conditions under which this relationship exists. For this we use model of particle in a box. We have shown that the amplitude can be calculated from the phase and vice versa if the log Analytical uncertainty relations are satisfied.

Authors such as Schnoebelen (2012: 12) suggest that in some languages (cf. Navajo) certain dependent clauses are frequently used independently to “mark emotional evaluation and background information”. Evans (2007) uses the term insubordination to refer to this phenomenon. Our study focuses on a particular insubordinate construction introduced by the sequence ni que in Spanish, as in the example [¡Una carta cada día!] Ni que yo fuese Umbral. (CORPES 100), used as an independent clause with a sociopragmatic meaning which is different from that of its subordinate counterpart (cf. No escribiría una carta cada día ni que yo fuese Umbral). Our research questions ask about the potential for ni que to be used as a discourse marker fulfilling an expressive function when it introduces this type of construction, and the derived hypothesis is then oriented to test whether Schnoebelen's (2012) observation about insubordinate constructions applies also to this Spanish construction. In order to test this hypothesis, we performed a functional-discourse analysis of more than 2000 concordances (and their extended contexts) in Mark Davies' Corpus del Español and the Real Academia CORPES XXI. Our findings show that the insubordinate construction differs in function and meaning from its subordinate counterpart, the former fulfilling a stronger emotive function, often combined with other discourse-pragmatic functions, such as evaluation or the organization of discourse.

In this work, quantum dynamics of a spin-0 particle under the effects of Lorentz symmetry violation in the presence of Coulombtype non-electromagnetic potential $(S(r) ∝ \frac{1}{r})$ is investigated. The non-electromagnetic (or scalar) potential is introduced by modifying the mass term via transformation $M → M + \frac{η_c}{r}$ in the relativistic wave equation. The linear central potential induced by the Lorentz symmetry violation is a linear radial electric and constant magnetic field and, analyze the effects on the spectrum of energy and the wave function

We firstly discuss classical stability for a dynamical system of two ions levitated in a 3D Radio-Frequency (RF) trap, assimilated with two coupled oscillators. We obtain the solutions of the coupled system of equations that characterizes the associated dynamics. In addition, we supply the modes of oscillation and demonstrate the weak coupling condition is inappropriate in practice, while for collective modes of motion (and strong coupling) only a peak of the mass can be detected. Phase portraits and power spectra are employed to illustrate how the trajectory executes quasiperiodic motion on the surface of torus, namely a Kolmogorov-Arnold-Moser (KAM) torus. In an attempt to better describe dynamical stability of the system, we introduce a model that characterizes dynamical stability and the critical points based on the Hessian matrix approach. The model is then applied to investigate quantum dynamics for many-body systems consisting of identical ions, levitated in 2D and 3D ion traps. Finally, the same model is applied to the case of a combined 3D Quadrupole Ion Trap (QIT) with axial symmetry, for which we obtain the associated Hamilton function. The ion distribution can be described by means of numerical modeling, based on the Hamilton function we assign to the system. The approach we introduce is effective to infer the parameters of distinct types of traps by applying a unitary and coherent method, and especially for identifying equilibrium configurations, of large interest for ion crystals or quantum logic.

Maxwell equation for the electric field has been solved for any medium by suggesting the wavenumber and angular frequency be complex quantities. This accounts for the field decay by interaction with the medium.This expression for the time and special decay of the electric field in a medium is used to construct a new wave function sensitive to the medium physical properties. This new wave function, unlike the conventional one, differentiates between a beam of particles in a vacuum and that enters a medium which is an attenuated due to the scattering effect.Another expression for time decaying electric field was obtained using Newton’s laws for frictional medium. This expression shows that the electric field diminishes due to friction.Fortunately, this time decaying part of the electric field is typical to that derived from Maxwell’s equations. Finally, a new Schrodinger equation sensitive to the medium properties was derived. This equation, fortunately, describes some scattering processes for Protein scattering, scattering of x-rays, opto-acoustic phonons, and Raman scattering for some materials successfully .

Soil CO2 efflux (FCO2) plays a dominant role in the terrestrial carbon (C) cycle but interpreting constraints on local observations is impeded by challenges in disentangling belowground CO2 sources. Trees contribute most C to forest soils, so linking aboveground properties to FCO2 could open new avenues to study plant-soil feedbacks and facilitate scaling; furthermore, FCO2 responds dynamically to meteorological conditions, complicating predictions of total FCO2 and forest C balance. We tested for proximity effects of individual Acer saccharum Marsh. trees on FCO2, comparing FCO2 within 1 m of mature stems to background fluxes before and after an intense rainfall event. Wetting significantly increased background FCO2 (6.4±0.3 vs. 8.6±0.6 s.e. μmol CO2 m-2s-1), with a much larger enhancement near tree stems (6.3±0.3 vs. 10.8±0.4 μmol CO2 m-2s-1). FCO2 varied significantly among individual trees and post-rain values increased with tree diameter (with a slope of 0.058 μmol CO2 m-2s-1 cm-1). Post-wetting amplification of FCO2 (the ‘Birch effect’) in root zones often results from the improved mobility of labile carbohydrates and further metabolization of recalcitrant organic matter, which may both occur at higher densities near larger trees. Our results indicate that plant-soil feedbacks change through tree ontogeny and provide evidence for a novel link between whole-system carbon fluxes and forest structure.

In this paper, the existence of two nontrivial stationary solutions for the nonlinear Gilpin Ayala two species competition model is given by using the mountain pass lemma, and the local stability criterion of the trivial solution is given by using Lyapunov function method. Based on the local stability criterion, we give some suggestions on how to avoid the population extinction. This is, when the population is on the verge of extinction, we should try our best to avoid the diffusion behavior and reduce the diffusion coefficient, otherwise the species are easy to go extinct. Numerical example shows the effectiveness of the proposed method.

A vast majority of the countries is under the economic and health crises due to the current epidemic of coronavirus disease 2019 (COVID-19). The present study analyzes the COVID-19 using time series, which is an essential gizmo for knowing the enlargement of infection and its changing behavior, especially the trending model. We have considered an autoregressive model with a non-linear time trend component that approximately converted into the linear trend using the spline function. The spline function split the COVID-19 series into different piecewise segments between respective knots and fitted the linear time trend. First, we obtain the number of knots with its locations in the COVID-19 series and then the estimation of the best-fitted model parameters are determined under Bayesian setup. The results advocate that the proposed model/methodology is a useful procedure to convert the non-linear time trend into a linear pattern of newly coronavirus case for various countries in the pandemic situation of COVID-19.

Drylands are arid and semiarid ecosystems, where the lack of rains imposes harsh conditions for the survival of organisms. These ecosystems are also susceptible to degradation and desertification, and their conservation depends on the understanding of the ecological functioning of vegetation and soil. In drylands, the vegetation is spatially structured as a mosaic of patches (vegetation) and interpatches (bare soil), a consequence of plant-plant interactions (facilitation and competition). Empirical data and modeling approaches reinforce the role of ecological facilitation for the maintenance of all organisms in drylands. However, the actual range of facilitation is still poorly known. Here, we explored data of meso- and micro-arthropods found in soil as bioindicators to infer the range of facilitation provided by plants to soil. We regarded data of abundances and species densities (independent samples) collected in random patches and bare soil places as dependent variables. Data of patch size and distances between bare soil and patches were arranged in a single shuffle, producing a 1-d coordinate system centered at the border of the patch. Discrete portions of this system are taken to calculate averages and variances of abundance and species density, and we investigated how soil communities variate across the patch border. We employ techniques of signal analysis to reduce the data noise and obtain a smooth and continuous behavior, which allowed us to fit a logistic function. Our findings indicate that soil communities suddenly change from simple patterns to numerous and diverse communities in bare soil regions, meaning that the influence of vegetation on soil goes beyond the patch border. We interpreted the variations in fauna as a consequence of the positive influence provided by plants (or its lack) on surrounding bare soil. We observe a fast decaying of fauna quantities at 0.35 m outside the patch border, a threshold that reveals the mean range of facilitation provided by plants. However, the changes in soil communities outside the patches seem not necessarily related to the efficiency of soil processes mediated by arthropods, which seem to be more active inside large patches. Concluding, we found a minimum patch-size (radius ~ 0.5 m) able to maintain high diverse communities in soil, and an average distance of vegetation influence along the patch border (halo between 0.35 and 0.50 m). This information can be interpreted in terms of facilitation provided by plants to soil conditions, which seems to differ from the quantitative functionality of soil processes. Our findings contribute to the general understanding of the ecological functioning of drylands, as well as to better plan conservation actions.

Gas Path Analysis and matching turbine engine models to experimental data are inverse problems of mathematical modelling which are characterized by parametric uncertainty. This results from the fact that the number of measured parameters is significantly lower than the number of components’ performance parameters needed to describe the real engine. In these conditions, even small measurement errors can result in a high variation of results, and obtained efficiency, loss factors etc. can appear out of the physical range. The current methods of engine model identification have developed considerably to provide stable, precise and physically adequate solutions. Presented in this work is an estimation method of engine components’ parameters based on multi-criteria identification which provides stable estimations of parameters and their confidence intervals with the known measurement errors. A priori information about the engine, its parameters and performance is used directly in the regularised identification procedure. The mathematical basis for this approach is the fuzzy sets theory. Forming objective functions and scalar convolutions synthesis of these functions is used to estimate gas-path components’ parameters. A comparison of the proposed approach with traditional methods showed that its main advantage is high stability of estimation in the parametric uncertainty conditions. Regularization reduces scattering, excludes incorrect solutions which do not correspond to a priori assumptions, and also helps to implement the Gas Path Analysis at the limited number of measured parameters. The method can be used for matching thermodynamic models to experimental data, Gas Path Analysis and also adapting dynamic models for the needs of the engine control system.

A new strategy to nanoengineer gold/fluorocarbon multilayer (ML) nanostructures is reported. We have investigated the morphological changes occuring at the metal-polymer interface in multilayer structures with varying volume fraction of gold (Au) and the kinetic growth aspect of the microscale properties of nano-sized Au in plasma polymer fluorocarbon (PPFC). Investigations were carried out at various temperatures and annealing time by means of grazing incidence small-angle and wide-angle X-ray scattering (GISAXS and GIWAXS). We have fabricated a series of multilayers with variying volume fraction (0.12, 0.27, 0.38) of Au and bilayer periodicity in ML structure. They show an interesting granular structure consisting of nearly spherical shaped nanoparticles within the polymer layer. The nanoparticle (NP) morphology changes due to the collective effects of NPs diffusion within ensembles in the in-plane vicinity and inter-layer with increasing temperature. The in-plane NPs size distinctly increases (from 1.9 to 4 nm) with increasing temperature. The NPs become more spherical thus reducing the surface energy. Linear growth of NPs with temperature and time shows diffusion-controled growth of NPs in the ML structure. The structural stability of the multilayer is controlled by the volume ratio of the metal in polymer. At room temperature UV-Vis shows a blueshift of the plasmon peak from 560 nm in ML Au/PTFE_1 to 437 nm in Au/PTFE_3. We have identified the fabrication and post-deposition annealing conditions to limit the Local Surface Plasmon resonance (LSPR) shift (from 〖∆λ〗_LSPR=180 nm (Au/PTFE_1) to 〖∆λ〗_LSPR=67 nm (Au/PTFE_3 ML)) and their optical response over a wide visible wavelength range. A variation in the dielectric constant of the polymer in precence of varying Au inclusion is found to be the main factor affecting the LSPR frequency. Our finding may provide insights in Nano engineering ML structure can be useful to systematically control the growth of NPs in polymer matrix.

This paper presents a control algorithm for soft-switching series LC converters. The conventional voltage-to-voltage controller is split into a master and a slave controller. The master controller implements constant-current-constant-voltage (CCCV) control, required for demanding applications, i.e. lithium battery charging or laboratory power supplies. It defines the set-current for the open-loop current slave controller, which generates the PWM parameters. The power supply achieves fast large-signal responses, e.g. from 5 V to 24 V, where 95% of the target value is reached in less than 400 µs. The design is evaluated extensively in simulation and on a prototype. A consensus between simulation and measurement is achieved.

Non-destructive testing of metallic objects that may contain embedded defects of different sizes is an important application in many industrial branches for quality control. Most of these techniques allow defect detection and its approximate localization, but very few give enough information for its 3D reconstruction. Here we present a hybrid laser – transducer system that combines remote laser-generated ultrasound excitation and non-contact ultrasonic transducer detection. This fully non-contact method gives access to separating scan areas on different object’s faces and defect details from different angles/perspectives can be analysed. This hybrid system can analyse the whole object’s volume data and allow a 3D reconstruction image of the embedded defects. As a novelty for the signal processing improvement, we use a 2D apodization window filtering technique, applied along with the synthetic aperture focusing algorithm in order to remove the undesired effects of side lobes and wide-angle reflections of propagating ultrasound waves, thus, enhancing the resulting 3D image of the defect. We provide both qualitative and quantitative volumetric results with high accuracy and resolution compared with conventional techniques.

In this paper we define a continuous wavelet transform of a Schwartz tempered distribution $f \in S^{'}(\mathbb R^n)$ with wavelet kernel $\psi \in S(\mathbb R^n)$ and derive the corresponding wavelet inversion formula interpreting convergence in the weak topology of $S^{'}(\mathbb R^n)$. It turns out that the wavelet transform of a constant distribution is zero and our wavelet inversion formula is not true for constant distribution, but it is true for a non-constant distribution which is not equal to the sum of a non-constant distribution with a non-zero constant distribution.

Inverse Sumudu transform multiple shifting properties are used to design methodology for solving ordinary differential equations. Then algorithm applied to solve Whittaker and Zettl equations to get their new exact solutions and profiles which shown through Maple complex graphicals. Table of inverse Sumudu transforms for elementary functions given for supporting the differential equations solving using inverse Sumudu transform.

Single valued neutrosophic set has king power to express uncertainty characterized by indeterminacy, inconsistency and incompleteness. Most of the existing single valued neutrosophic cross entropy bears an asymmetrical behavior and produce an undefined phenomenon in some situations. In order to deal with these disadvantages, we propose a new cross entropy measure under single valued neutrosophic set (SVNS) environment namely SN- cross entropy and prove its basic properties. Also we define weighted SN-cross entropy measure and investigate its basic properties. We develop a new multi attribute group decision making (MAGDM) strategy for ranking of the alternatives based on the proposed weighted SN-cross entropy measure between each alternative and the ideal alternative. Finally, a numerical example of MAGDM problem of investment potential is solved to show the validity and efficiency of proposed decision making strategy. We also present comparative anslysis of the obtained result with the results obtained form the existing solution strategies in the solution.

A radial basis function network (RBFN) method is proposed to reconstruct daily Sea surface temperatures (SSTs) with limited SST samples. For the purpose of evaluating the SSTs using this method, non-biased SST samples in the Pacific Ocean (10°N–30°N, 115°E–135°E) are selected when the tropical storm Hagibis arrived in June 2014, and these SST samples are obtained from the OISST products according to the distribution of AVHRR L2p SST and in-situ SST data. Furthermore, an improved nearest neighbor cluster (INNC) algorithm is designed to search the optimal hidden knots for RBFNs from both the SST samples and the background fields. Then the reconstructed SSTs from the RBFN method are compared with the results from the optimum interpolation (OI) method. The statistical results show that the RBFN method has a better performance of reconstructing SST than the OI method in the study, and the average RMSE is 0.48°C for the RBFN method, which is quite smaller than the value of 0.69°C for the OI method. Additionally, the RBFN methods with different basis functions and clustering algorithms are tested, and we discover that the INNC algorithm with multi-quadric function is quite suitable for the RBFN method to reconstruct SSTs when the SST samples are sparsely distributed.

In the dynamic and evolving tourism industry, engaging of stakeholders is essential for fostering innovation and improving service quality. However, tourism companies often struggle to meet expectations for customer satisfaction through interactivity and real-time feedback. While new digital technologies can address the challenge of providing personalized travel experiences, they can also increase the workload for travel agencies due to the maintenance and updates required to keep travel details current. Intelligent chatbots and other Generative Artificial Intelligence (GAI) tools can help mitigate these obstacles by transforming tourism and travel-related services, offering interactive guidance for both tourism companies and travellers. In this study, we explore and compare the main characteristics of existing responsive AI instruments, applicable in tourism and hospitality scenarios. Then, we propose a new theoretical framework for decision-making in the tourism industry, integrating GAI technologies to enable agencies to create and manage itineraries, and tourists to interact online with these innovative instruments. The advantages of the proposed framework are as follows: 1) providing a comprehensive understanding of the transformative potential of new generation AI tools in tourism and facilitates their effective implementation; 2) offering a holistic methodology to enhance the tourist experience; 3) unifying the applications of contemporary AI instruments in tourism activities and paves their further development. The study contributes to the expanding literature on tourism modernization and offers recommendations for industry practitioners, consumers, and local, regional, and national tourism bodies to adopt a more user-centric approach to enhancing travel services.

It has been more than a century since Erlang published his paper in 1909. The classical queueing system for the M/D/c queue has been investigated by many authors. The key is to find the roots of an equation using explicit or numerical methods. We present an alternate form of explicit solution(s) of this/these root(s) using the Lambert-W function in this paper. In addition, the unsaturated probabilities of the number of customers in the system is derived explicitly in terms of this/these root(s). Finally, the mean number of customers in the system and the mean queueing delay are obtained from these probabilities. The exact queueing delay formula for the M/D/c queue is expressed in closed-form in terms of the root(s). Numerical results show that they are in excellent agreement with the numerical results published by Seelen, Tijms and Van Hoorn.

The pervasive presence of atmospheric pollution, particularly polycyclic aromatic hydrocarbons such as 7,12-dimethylbenz(a)anthracene, instigates aberrant cellular and tissue conditions, precipitating oxidative damage and inflammatory cascades conducive to the onset of cancer, notably mammary cancer. Given the hepatic metabolism of 7,12-dimethylbenz(a)anthracene, the imperative of employing natural antioxidants becomes apparent. In this study, we delve into the antioxidant and hepato-protective properties of Pistacia lentiscus against 7,12-dimethylbenz(a)anthracene-induced toxicity, alongside exploring its potential anticancer attributes. Our investigations unveil Pistacia lentiscus's anti-proliferative efficacy against human breast cancer cell lines. Notably, 7,12-dimethylbenz(a)anthracene-intoxication escalates body weight, disrupts lipid profiles, and incites serum oxidative damage. Concurrently, hepatic and renal oxidative stress ensue, accompanied by heightened antioxidant enzyme activity in the 7,12-dimethylbenz(a)anthracene-exposed-group compared to controls (p&lt;0.05). Nonetheless, Pistacia lentiscus co-administration rectifies biochemical imbalances, significantly attenuates oxidative stress aberrations, and augments antioxidant enzyme responses (p&lt;0.05). Importantly, histological analysis evinces Pistacia lentiscus's shielding effect against 7,12-dimethylbenz(a)anthracene induced hepatocyte injury and steatosis. Our findings underscore Pistacia lentiscus's robust anti-proliferative, antioxidant, and hepato-protective capacities, mitigating metabolic disturbances, oxidative stress propagation in liver and kidney functions, and potential histological alterations, thereby impeding 7,12-dimethylbenz(a)anthracene-induced mammary cancer initiation. We posit that Pistacia lentiscus may serve as a prophylactic agent against breast cancer instigated by this carcinogen.

Objective To analyze the influence of HIV in penitentiary institutions through an exhaustive lexiconmetric and sentiment analysis of news in the Spanish written press related to HIV and prison. Material an method observational, descriptive, and retrospective design based on news published in Spanish newspapers from 1981 to 2020, linking HIV infection with penitentiary institutions. Natural language processing and lexiconmetry techniques were used, using the Python programming language and ATLAS Ti v.9 software. Result: 318 articles were analyzed, with 10,502 distinct words. The sentiment of news was evaluated in three different periods: the discovery of HIV, and the periods before and after the existence of antiretroviral treatments. N-gram analysis and word cloud creation were carried out for each period. In the initial phase, ignorance predominated, and prominent terms such as "homosexual," "isolate," "test," "trial," or "confirm" were observed. In the period before antiretroviral treatments, news reflected negative feelings and criticism of prison policy, with keywords such as "give birth," "drug," "carrier," or "disease." With the arrival of treatments, news showed an evolution towards a more positive tone, highlighting terms such as "treatment," "release," or "syringes”.Conclusions: The presence of HIV in Spanish prisons has experienced a significant evolution from an alarming situation to an improvement in the care of inmates, driven by institutional adaptation and advances in antiretroviral treatments.

A reduction of melatonin function contributes to the acceleration of Alzheimer's disease (AD), and understanding molecular processes of melatonin-related signaling is critical for intervention of AD progression. Recently, we synthesized and tested a series of melatonin derivates with donepezil fragments in silico and in vitro. In this study, one of the most potent compounds, 3c, was studied in an in vivo rat model of pinealectomy (pin) and subsequent icvAβ1-42 infusion. Melatonin was used as a referent drug. The treatment with melatonin and 3c (10 mg/kg, i.p. for 14 days) exerted a beneficial effect on memory decline and concomitant rise of Aβ1-42 and pTAU in the hippocampus in the pin + icvAβ1-42 rats. Melatonin supplementation facilitated the non-amyloidogenic signaling via a non-receptor (histone deacetylase sirtuin 1, SIRT1) and receptor-related signaling (MT/ERK/CREB). The hybrid 3c derivate up-regulated the MT1A and MT2B receptors, pERK and pCREB. Our findings strongly support the hypothesis that melatonin-related derivates may become a promising drug candidate in AD therapy.

Leishmaniasis remains a significant global health concern, with current treatments relying on outdated drugs associated with high toxicity, lengthy administration, elevated costs, and drug resistance. Consequently, the urgent need for safer and more effective therapeutic options in leishmaniasis treatment persists. Previous research has highlighted selenium compounds as promising candidates for innovative leishmaniasis therapy. In light of this, a library of 10 selenium-containing diverse compounds was designed and evaluated in this study. The compounds were subjected to screening against L. amazonensis promastigotes, and their cytotoxicity was assessed in NIH/3T3 cells. Among the tested compounds, MRK-106 and MRK-108 displayed the highest potency against L. amazonensis promastigotes while demonstrating reduced cytotoxicity. Notably, MRK-106 and MRK-108 exhibited IC50 values of 3.97 µM, 4.23 µM, respectively, and most of the tested compounds showed low cytotoxicity in NIH/3T3 cells (CC50 &gt; 200 µM). Although these results are promising, additional investigations focusing on intracellular amastigotes are required to determine the antileishmanial activity of the compounds. In conclusion, the identified selenium-containing compounds hold considerable potential as antileishmanial drug candidates and warrant further exploration in subsequent studies. These findings represent a significant step towards the development of safer and more effective therapies for leishmaniasis, addressing the pressing need for novel and improved treatments.

Organic light-emitting diodes (OLEDs) have ushered in a technological revolution with their remarkable impact on diverse sectors of our daily lives. These versatile devices known for their outstanding display and lighting capabilities, have become indispensable components in various industries including smartphones, tablets, televisions, and automotive applications. This paper delves into the development of a group of twisted donor-acceptor-donor (D-A-D) derivatives incorporating bicarbazole and benzophenone structures for potential use as blue emitters in OLEDs. The synthesized compounds, namely DB14, DB23 and DB29, were designed with various alkyl side chains to enhance their film forming properties as for blue emitters. Characterization and evaluation of these derivatives included photophysical, electrochemical, thermal, and electroluminescent analysis. Some of the OLED devices incorporating these emitters demonstrated promising performance with maximum current efficiency (CEmax) of 2.6 cd/A and external quantum efficiency (EQEmax) of 5.3%. Notably, the DB23 emitter exhibited the highest EQE among all devices. The study also emphasizes the influence of host-guest energy transfer, optimal doping concentrations, and molecular structures on device performance. This research not only contributes to the understanding of advanced OLED materials but also provides insights into designing efficient blue emitters for future display and lighting applications, thereby advancing the field of organic electronics.

The approach based on molecular modeling was developed to study dNTP derivatives characterized by new polymerase-specific properties. For this purpose, the relative efficiency of PCR amplification with modified dUTPs was studied using Taq, Tth, Pfu, Vent, Deep Vent, Vent (exo-), and Deep Vent (exo-) DNA polymerases. The efficiency of PCR amplification with modified dUTPs was compared with the results of molecular modeling using the known 3D structures of KlenTaq polymerase–DNA–dNTP complexes. The dUTPs were C5-modified with bulky functional groups (the Cy5 dye analogs) or lighter aromatic groups. Comparing the experimental data and the results of molecular modeling revealed the decrease of PCR efficiency in the presence of modified dUTPs with an increase in the number of non-covalent bonds between the substituents and the DNA polymerase (about 15% decrease per one extra non-covalent bond). Generalization of the revealed patterns to all the studied polymerases of the A and B families is discussed herein. The number of non-covalent bonds between the substituents and polymerase amino acid residues is proposed to be a potentially variable parameter for regulating enzyme activity.

Pregnancy associated plasma protein-A (PAPP-A) plays an integral role in breast cancer (BC), especially triple negative breast cancer (TNBC). This subtype accounts for the most aggressive BC, possesses high tumor heterogeneity, is least responsive to standard treatments and has the poorest clinical outcomes. There is a critical need to address the lack of effective targeted therapeutic options available. PAPP-A is a protein that is highly elevated during pregnancy. Frequently, higher PAPP-A expression is detected in tumors than in healthy tissues. The increase in expression coincides with increased rates of aggressive cancers. In BC, PAPP-A has been demonstrated to play a role in tumor initiation, progression, metastasis including epithelial-mesenchymal transition (EMT), as well as acting as a biomarker for predicting patient outcomes. In this review, we present the role of PAPP-A, with specific focus on TNBC. The structure and function of PAPP-A, belonging to the pappalysin subfamily, and its proteolytic activity are assessed. We highlight the link of BC and PAPP-A with respect to the IGFBP/IGF axis, EMT, the window of susceptibility and the impact of pregnancy. Importantly, the relevance of PAPP-A as a TNBC clinical marker is reviewed and its influence on immune-related pathways are explored. The relationship and mechanisms involving PAPP-A reveal the potential for more treatment options that can lead to successful immunotherapeutic targets and the ability to assist with better predicting clinical outcomes in TNBC.

We employ hierarchy of models (HoM) with 2, 3 and 4 parameters to reanalyze the nucleation kinetics in the electrodeposition as quantified by n(t) - “the number of nuclei vs. time” data obtained at different overvoltages from precise experiments on electrodeposition of Hg on two different types of Pt-cathodes by Ivan V. Markov and Evgenia Stoycheva [1]. The obtained two scales, nmax and , are used to rescale the original data mapping it on a master curve in coordinates . Our main result is obtained by studying further the dependence of these two scales on the overvoltage (analogue of supersaturation). Surprisingly, for one of the two cathode types - the “hemispherical single-crystal electrode” (as defined by the authors), there is discontinuity in the “ vs. overvoltage” dependence – an almost horizontal jump from 85 to 86 mV accompanied by a change in the slope of the dependence - it is ~ -1 and ~ -0.5 after. For the other cathode - “plane structureless platinum electrode”,  decreases smoothly. Combined, these two behaviors point at the so called “cusp catastrophe”. We compare our findings with published results on protein nucleation.

This paper presents an innovative testing framework, testFAILS, designed for the rigorous evaluation of AI Linguistic Systems, with a particular emphasis on various iterations of ChatGPT. Leveraging orthogonal array coverage, this framework provides a robust mechanism for assessing AI systems, addressing the critical question, "How should we evaluate AI?" While the Turing test has traditionally been the benchmark for AI evaluation, we argue that current publicly available chatbots, despite their rapid advancements, have yet to meet this standard. However, the pace of progress suggests that achieving Turing test-level performance may be imminent. In the interim, the need for effective AI evaluation and testing methodologies remains paramount. Our research, which is ongoing, has already validated several versions of ChatGPT, and we are currently conducting comprehensive testing on the latest models, including ChatGPT-4, Bard and Bing Bot, and the LLaMA model. The testFAILS framework is designed to be adaptable, ready to evaluate new bot versions as they are released. Additionally, we have tested available chatbot APIs and developed our own application, AIDoctor, utilizing the ChatGPT-4 model and Microsoft Azure AI technologies

Gravity-aided inertial navigation system (GAINS) is an important development in autonomous underwater vehicle (AUV) navigation. An effective path planning algorithm plays an important role in the performance of navigation in long-term underwater missions. By combining the gravity information obtained at each position with the error information from the INS, the posterior Cram\'er-Rao bound (PCRB) of GAINS is derived in this paper. The PCRB is the estimated lower bound of position variance for navigation along the planned trajectory. And the sum of PCRB is used as the minimum cost from the initial state to the current state in the state space, and the position error prediction variance of inertial navigation system (INS) is used as the minimum estimated cost of the path from the current state to the goal state in the A* algorithm. Thus, a path planning method with optimal navigation accuracy is proposed. According to simulation results, traveling along the path planed by the proposed method can rapidly improve the positioning accuracy while consuming just slightly more distance. Even when measuring noise changes, the planned path can still maintain optimal positioning accuracy, and high positioning accuracy is possible for any trajectory located within a certain range of the planned path.

Abstract Eye health is crucial and the onset of diseases can reduce vision and affect the quality of life of patients. The main causes of progressive and irreversible vision loss include various pathologies such as cataracts, ocular atrophy, corneal opacity, age-related macular degeneration, uncorrected refractive error, posterior capsular opacification, uveitis, glaucoma, diabetic retinopathy, retinal detachment, undetermined disease and other disorders involving oxidative stress and inflammation. The eyes are constantly exposed to the external environment and, for this reason, must be protected from damage from the outside. Many drugs, including cortisonics and antinflammatory drugs have widely been used to counteract eye disorders. However, recent advances have been obtained via supplementation of patients with natural antioxidants and nutraceuticals. In particular, evidence has been accumulated that polyphenols (mostly deriving from Citrus Bergamia) represent a reliable source of antioxidants able to counteract oxidative stress accompanying early stages of eye diseases. Luteolin, in particular, has been found to protect foto-receptors thereby improving vision in many disease states. Moreover, a consistent anti-inflammatory response was found to occur when curcumin is used alone or in combination with other nutraceuticals. On the other hand, CoQ10 has been demonstrated to produce consistent effect in reducing ocular pressure thereby leding to protection in patients undergoing glaucoma. Finally, both grape seed extract rich in anthocyanosides and polynsatured fatty acids (PUFAs) seem to contribute in the prevention of retinal disorders. Thus, combination of nutraceuticals and anti-oxidants may represent the right solution for a multiaction activity in eye protection to be associated to current drug therapies, and this will be of potential interest in early stages of eye disorders.

he paper presents an innovative method for tourist route planning inside a destination. The necessity of reorganizing the tourist routes within a destination comes as an immediate response to the Covid-19 crisis. The implementation of the method inside tourist destinations can bring an important advantage in transforming a destination into a safer destination in times of Covid-19 and post-Covid-19. The existing trend of shortening the tourist stay length has been accelerated while the epidemic became a pandemic. Moreover, the wariness for future pandemics has brought into spotlight the issue of overcrowded attractions inside a destination at certain moments. The method presented in this paper proposes a backtracking algorithm, more precisely an adaptation of the travelling salesman problem. The method presented is aimed to facilitate the navigation inside a destination and to revive certain less-visited sightseeing spots inside a destination while facilitating conformation with the social distancing measures imposed for Covid-19 control.

While the angiotensin converting enzyme 2 (ACE2) protein is defined as the primary severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptor, the viral serine molecule might be mobilized by the host's transmembrane protease serine subtype 2 (TMPRSS2) enzyme from the viral spike (S) protein and hijack the host’s N-acetyl-D-galactosamine (GalNAc) metabolism. The resulting hybrid, serologically A-like/Tn (T-nouvelle) structure potentially acts as a host–pathogen functional molecular bridge. In humans, this intermediate structure will hypothetically be replaced by ABO(H) blood group-specific, mucin-type structures, in the case of infection hybrid epitopes, implicating the phenotypically glycosidic accommodation of plasma proteins. The virus may, by mimicking the synthetic pathways of the ABO(H) blood groups, bind to the cell surfaces of the blood group O(H) by formation of a hybrid H-type antigen as the potential precursor of hybrid non-O blood groups, which does not affect the highly anti-glycan aggressive anti-A and anti-B isoagglutinin activities, exerted by the germline-encoded nonimmune immunoglobulin M (IgM). In the non-O blood groups, which have developed from the H-type antigen, these IgM activities are downregulated by phenotypic glycosylation, while adaptive immunoglobulins might arise in response to the hybrid A and B blood group structures, bonds between autologous carbohydrates and foreign peptides, suggesting the exertion of autoreactivity. The non-O blood groups thus become a preferred target for the virus, whereas blood group O(H) individuals, lacking the A/B phenotype-determining enzymes and binding the virus alone by hybrid H-type antigen formation, have the least molecular contact with the virus and maintain the critical anti-A and anti-B isoagglutinin activities, exerted by the ancestral IgM, which is considered the humoral spearhead of innate immunity.

I want to meaningfully average a pathalogical function (i.e., an everywhere surjective function whose graph has zero Hausdorff measure in its dimension). In case this impossible, we wish to average a nowhere continuous function defined on the rationals. We do this by taking the most generalized, satisfying extension of the expected value, w.r.t the Hausdorff measure in its dimension, on bounded functions with domains of finite measure, which takes finite values only. As of now, I’m unable to solve this due to limited knowledge of advanced math and most people are too busy to help. Therefore, I’m wondering if anyone knows a research paper which solves my doubts. Unlike the previous paper, “Finding a Research Paper Which Meaningfully Averages Pathalogical Functions”) we add motivations, examples, and change parts of the original paper.

Body-centered cubic bismuth (Bi) is considered an enticing pressure marker, and therefore it is highly desirable to command its accurate equation of state (EOS). However, significant discrepancies are noted among the previous experimental EOSs. In the present work, the EOS up to 300 GPa is theoretically obtained by direct solving the partition function via a direct integral approach (DIA). The calculated results nearly reproduce the hydrostatic experimental measurements below 75 GPa, and the deviations from the measurements gradually get larger with increasing pressure. Based on the ensemble theory of equilibrium state, DIA works with high precision particularly in high-pressure conditions, so the hydrostatic EOS presented in this work is expected to be a reliable pressure standard.

The microalgae Phaeodactylum tricornutum (PT) is distinguished by its rich nutrient profile, characterized by well-documented neuroprotective activities, including fucoxanthin (FX), a major carotenoid, and polyunsaturated omega-3 fatty acids (n-3 PUFA). The current study aims to evaluate the protective effects of a standardized extract of PT (Mi136) containing 2% FX on cognitive function, oxidative stress, and inflammation parameters in a mouse model of accelerated aging. Seventy-two (72) male mice were randomly assigned to the blank control group (BC), negative control group (NC), and four similar microalgae extract of PT groups (branded as BrainPhytTM) with different human equivalent doses. From day 01 to day 51, mice in the BC group were injected with a 0.9% normal saline solution, while mice in all other groups were subcutaneously injected with D-galactose (D-Gal) at a dose of 150 mg/kg once per day, five days per week. Results indicated that, for the three higher microalgae extract of PT dose groups, spatial cognitive function, swim latency, and step-through latency impairments induced by chronic D-Gal intoxication were significantly and fully inhibited, with mean values similar to those in the BC group during each day of testing. Similar benefits were observed in biochemical analysis, specifically regarding brain and plasma levels of lipid peroxidation, TNF-α, and IL-6 markers. These data underscore the positive effects of a standardized extract of PT containing 2% FX on cognitive function parameters such as spatial working memory, long-term memory, and short-term memory through the regulation of oxidative stress and inflammation pathways.

Memristors are state-of-the-art, nano-sized, two-terminal, passive electronic elements with very good switching and memory characteristics. Owing to their very low power usage and a good compatibility to the existing CMOS ultra-high-density integrated circuits and chips, they are po-tentially applicable in artificial and spiking neural networks, memory arrays, and many other de-vices and circuits for artificial intelligence. In this paper, a complete electronic realization of ana-log circuit model of modified neural net with memristor-based synapses and transfer function with memristors and MOS transistors in LTSPICE is offered. Each synaptic weight is realized by only one memristor, providing enormously reduced circuit complexity. The summing and scaling implementation is founded on op-amps and memristors. The logarithmic-sigmoidal activation function is based on a simple scheme with MOS transistors and memristors. The functioning of the suggested memristor-based neural network for pulse input signals is evaluated both analytically in MATLAB-SIMULINK and in LTSPICE environment. The obtained results are compared one to another and are successfully verified. The realized memristor-based neural network is an im-portant step towards the forthcoming design of complex memristor-based neural networks for ar-tificial intelligence, for implementation in very high-density integrated circuits and chips.

Nitric oxide (NO) is synthesized and is involved in various physiological and developmental process regulation in all kingdoms of life. Fungi have been less explored in terms of endogenous NO biology than mammals, plants, and bacteria. In this review, we summarize and discuss the studies to date on intracellular NO biosynthesis and function in fungi. Two mechanisms for NO biosynthesis, NO synthase (NOS)-mediated arginine oxidation, and nitrate and nitrite reductase-mediated nitrite reduction, are most frequently reported. Furthermore, we summarize the multifaceted functions of NO in fungi, as well as its role as a signaling molecule in fungal growth regulation, development, abiotic stress, virulence regulation, and metabolism. Finally, we present potential directions for future research on fungal NO biology.

The article proposes asymptotic methods for calculating Sommerfeld integrals, which enable us to calculate the integral using the expansion of a function into an infinite power series at the saddle point, where the role of a rapidly oscillating function under the integral can be fulfilled either by an exponential or by its product by the Hankel function. The proposed types of Sommerfeld integrals are generalized on the basis of integral representations of the Hertz radiator fields in the form of the inverse Hankel transform with the subsequent replacement of the Bessel function by the Hankel function. It is shown that the numerical values of the saddle point are complex. During integration, auxiliary or so-called standard integrals, which contain the main features of the integrand function, were used. As a demonstration of the accuracy of the technique, a previously known asymptotic formula for the Hankel functions was obtained in the form of an infinite series. The proposed method for calculating Sommerfeld integrals can be useful in solving the half-space Sommerfeld problem. An example is the expression in the form of an infinite series for the magnetic field of reflected waves, obtained directly through the Sommerfeld integral (SI).

Widely used estimates of food-insecure populations are likely to be biased upwards, lacking adjustment for global increases in sedentary behavior in recent decades. We first construct a household model to account for sedentary choices during leisure and work time decisions. The model rationalizes increasing sedentary behavior from the household by accounting for increasing returns to cognitive human capital vs physical capital, alongside increased productivity of more sedentary activities both at work and at home. The household model then informs an empirical model that makes use of our unique international pseudo-panel data on sitting time, which serves as a proxy for sedentarism. We econometrically estimate a transfer function linking sedentarism to widely available covariates, which then are used to make out-of-sample predictions and can be applied to a large set of countries. The estimated sedentary time can be used to adjust the physical activity level reflected in the minimum dietary energy requirement used to determine a cutoff for food insecurity.

Ageing may be characterized by progressive loss of cognitive function as well as decrease in physical activities, in addition to change in appearance. Previously, we reported that intracerebroventricular transplantation of a human neural stem cell (NSC) line (F3) over-expressing choline acetyltransferase (F3.ChAT) gene, an enzyme responsible for acetylcholine synthesis, markedly improved cognitive function and physical activity of aged animals by enhancing acetylcholine and growth factors (GFs) and neurotrophic factors (NFs). In the present study, 10-month-old F344 rats were intravenously transplanted with F3 or F3.ChAT NSCs (1 x 106 cells) once a month to 21st month of age when the cumulative mortality reached 20%, and physical activity and learning/memory function were investigated, in addition to the analyses of brain acetylcholine concentration, and cholinergic and dopaminergic system restoration. Neuroprotective and neuroregenerative activities of stem cells were also confirmed by analyzing oxidative damages, neuronal skeletal protein, angiogenesis, brain and muscle weights, and proliferating host stem cells. Stem cells markedly improved both the cognitive (passive avoidance and water-maze performances) and physical (locomotor and rota-rod activities) functions, in parallel with the elevation of acetylcholine levels in cerebrospinal fluid and in muscles, in which F3.ChAT cells were superior to F3 parental cells. Stem cell transplantation down-regulated CCL11, leading to restoration of microtubule-associated protein 2 as well as functional markers of cholinergic and dopaminergic systems, and preserved brain and muscular capillaries, recovering muscle mass. In addition, stem cells enhanced antioxidative capacity, attenuating oxidative damage of multiple organs including muscles and the brain. The results indicate that NSCs over-expressing ChAT gene improve cognitive function and physical activity of ageing animals by protecting and recovering functions of multiple organs including cholinergic and dopaminergic systems as well as muscles from oxidative injuries through secretion of acetylcholine and GFs/NFs, increased antioxidant elements, and enhanced blood flow.

Judo is a popular Japanese martial art and an Olympic sport. Recently, an increasing interest has been observed in the application of judo as a multicomponent exercise, with a growing body of evidence showing that multicomponent exercise improves physical and cognitive performance in older adults. Therefore, this review highlights the benefits of judo training in preventing physical and cognitive decline in older adults. Specifically, first, this review outlines the basic characteristics of judo (philosophy, match, and training). Next, previous studies investigating the effects of judo training on physical and cognitive aspects of older adults are reviewed. Thereafter, the brain mechanisms underlying the effects of judo training in improving physical and cognitive performance are discussed. Throughout this review, judo training demonstrated some positive effects on physical (gait and balance, among others) and cognitive (memory and executive function) function in older adults. These positive effects are attributed to a variety of changes in the brain (e.g., increased neurotrophic factor expression and increased cerebral blood flow, among others), that affect different brain regions and networks both functionally and structurally. From these findings, this review concludes that judo training can be an effective way to maintain and prevent physical and cognitive decline in older adults.

This study was designed to extend the literature on multicomponent interventions for the children of deaf adults (CODA) population. This study used two evidence-based behavior intervention strategies: pre-session pairing (PSP) and independent group contingency (GC). These strategies have been successfully used to decrease off-task behavior in elementary school children with various abilities and diverse backgrounds. However, the research on multicomponent interventions has yet to examine their effects on the CODA population in inclusive classrooms. This study used a concurrent multiple baseline design across participants with an ABC sequence to examine teacher-implemented PSP with independent GC in reducing the off-task behavior of three CODAs in an inclusive classroom at a public elementary school. The results show that the intervention successfully decreased off-task behavior for all participating CODAs. The results suggest that CODAs can adapt to classroom rules and expectations when PSP and independent GC are systematically applied to them in classrooms.

This study presents the solution of the second type of a two-dimensional nonlinear integral equation in Banach space. Also, the existence and uniqueness of this equation’s solution are discussed. We utilize a numerical approach involving hybrid and block-pulse functions to obtain the approximate solution of a two-dimensional nonlinear integral equation. Nonlinear integral equation in two dimensions is reduced numerically to a system of nonlinear algebraic equations that can be solved using numerical methods. This study focuses on showing the convergence analysis for the numerical approach and obtaining an error estimate. Some numerical examples have been provided to demonstrate the approach’s viability and efficacy

The Internet of Medical Things (IoMT) is playing a pivotal role in the healthcare sector by allowing faster and more informed hospital care, personalized treatment, and medical solutions. A very effective and trustworthy solution for resource-constrained medical devices is provided by Physical Unclonable Functions (PUF) - based identity and authentication systems, however they are not yet entirely reliable. This paper proposes VXorPUF, a Vedic Principles - Based Hybrid XOR Arbiter PUF. Modeling attacks were performed on the proposed architecture and an accuracy of 49.80 % was achieved. Uniqueness, Reliability and Randomness were the figures of merit used to evaluate PUF.

Anomaly Detection in real time data is accepted as a vital research area. Clustering has effectively been tried for this purpose. As the datasets are real time, the time of generating of the data is also important. In this article, we introduce a mixture of partitioning and agglomerative hierarchical approach to detect anomalies from such datasets. It is a two-phase method which follows partitioning approach first and then agglomerative hierarchical approach. The dataset can have mixed attributes. In phase-1, a unified metric defined on mixed attributes is used. The same is also used for merging of similar clusters in phase-2. Also, we have kept the track of time attribute of each data instance which produces the clusters with their lifetimes in phase-1. Then in phase-2, we merge the similar clusters. While merging, the similar clusters, the lifetimes of the corresponding clusters with overlapping cores are to be superimposed producing fuzzy time intervals. This way, each cluster will have an associated fuzzy lifetime. The data instances either belonging sparse clusters or not belonging to any of the clusters can be treated as anomalies. The efficacy of the algorithms can be established using both complexity analysis as well as experimental studies.

The first years of an infant’s life represent a sensitive period for neurodevelopment and see the emergence of nascent forms of executive function (EF), which are required to support complex cognition. Few tests exist for measuring EF during infancy, and the available tests require painstaking manual coding of infant behaviour. In modern clinical and research practice, human coders collect data on EF performance by manually labelling video recordings of infant behaviour during toy or social interaction. Besides being extremely time-consuming, video annotation is known to be rater-dependent and subjective. To address these issues, starting from existing cognitive flexibility research protocols, we developed instrumented toys as a new task instrumentation and data collection tool suitable for infant use. A commercially available device comprising a Barometer and Inertial Measurement Unit (IMU) embedded in a 3D-printed lattice structure was used to detect when and how the infant interacts with the toy. The data collected using the instrumented toys provides a rich dataset describing the sequence of toy interaction and individual toy interaction patterns, from which EF-relevant aspects of infant cognition may be inferred. Such a tool potentially provides an objective, reliable, and scalable method of collecting early developmental data in socially interactive contexts.

The synchronous generator, as the main component of power systems, plays a key role in these system’s stability. Therefore, utilizing the most effective control strategy for modeling and control the synchronous generator results in the best outcomes in power systems’ performances. The advantage of using a powerful controller is to have the synchronous generator modeled and controlled as well as its main task i.e. stabilizing power systems. Since the synchronous generator is known as a complicated nonlinear system, modeling and control of it is a difficult task. This paper presents a sum of squares (SOS) approach to modeling and control the synchronous generator using polynomial fuzzy systems. This method as an efficacious control strategy has numerous superiorities to the well-known T–S fuzzy controller, due to the control framework is a polynomial fuzzy model, which is more general and effectual than the well-known T–S fuzzy model. In this case, a polynomial Lyapunov function is used for analyzing the stability of the polynomial fuzzy system. Then, the number of rules in a polynomial fuzzy model is less than in a T-S fuzzy model. Besides, derived stability conditions are represented in terms of the SOS approach, which can be numerically solved via the recently developed SOSTOOLS. This approach avoids the difficulty of solving LMI (Linear Matrix Inequality). The Effectiveness of the proposed control strategy is verified by using the third-part Matlab toolbox, SOSTOOLS.

We develop the process of discounting when underlying rates follow a jump-diffusion process, that is, when, in addition of diffusive behavior, rates suffer a series of finite discontinuities located at random Poissonian times. Jump amplitudes are also random and governed by an arbitrary density. Such a model may describe the economic evolution specially when extreme situations occur (pandemics, global wars, etc.). When between jumps the dynamical evolution is governed by an Ornstein-Uhlenbeck diffusion process, we obtain exact and explicit expressions for the discount function and the long-run discount rate and show that the presence of discontinuities may drastically reduce the discount rate, a fact that has significant consequences for environmental planning. We also discuss as a specific example the case when rates are described by the continous time random walk.

It is quite easy to stochastically distort an original count variable to obtain a new count variable with relatively more variability than in the original variable. Many popular overdispersion models (variance greater than mean) can indeed be obtained by mixtures, compounding or randomlystopped sums. There is no analogous stochastic mechanism for the construction of underdispersed count variables (variance less than mean), starting from an original count distribution of interest. This work proposes a generic method to stochastically distort an original count variable to obtain a new count variable with relatively less variability than in the original variable. The proposed mechanism, termed condensation, attracts probability masses from the quantiles in the tails of the original distribution and redirect them toward quantiles around the expected value. If the original distribution can be simulated, then the simulation of variates from a condensed distribution is straightforward. Moreover, condensed distributions have a simple mean-parametrization, a characteristic useful in a count regression context. An application to the negative binomial distribution resulted in a distribution allowing under, equi and overdispersion. In addition to graphical insights, fields of applications of special cases of condensed Poisson and condensed negative binomial distributions were pointed out as an indication of the potential of condensation for a flexible analysis of count data

Lattice and code cryptography can replace existing schemes such as Elliptic Curve Cryptography because of their resistance to quantum computers. In support of public key infrastructures, the distribution, validation and storage of the cryptographic keys is then more complex to handle longer keys. This paper describes practical ways to generate keys from physical unclonable functions, for both lattice and code based cryptography. Handshakes between client devices containing the PUFs and a server are used to select sets of addressable positions in the PUFs, from which streams of bits called seeds are generated on demand. The public and private cryptographic key pairs are computed from these seeds together with additional streams of random numbers. The method allows the server to independently validate the public key generated by the PUF, and act as a certificate authority in the network. Technologies such as High performance computing, and graphic processing units can further enhance security by preventing attackers to make this independent validation when only equipped with less powerful computers.

Recently, the conformable derivative and its properties have been introduced. In this paper, we propose and prove some new results on conformable Boundary Value Problems. First, we introduce a conformable version of classical Sturm´s separation, and comparison theorems. For a conformable Sturm-Liouville problem, Green's function is constructed, and its properties are also studied. In addition, we propose the applicability of the Green´s Function in solving conformable inhomogeneous linear differential equations with homogeneous boundary conditions, whose associated homogeneous boundary value problem has only trivial solution. Finally, we prove the generalized Hyers-Ulam stability of the conformable inhomogeneous boundary value problem.

Serum transferrin (sTf) plays a pivotal role in regulating iron biodistribution and homeostasis within the body. The molecular details of sTf Fe(III) binding, blood transport, and cellular delivery through transferrin receptor-mediated endocytosis are generally well-understood. Emerging interest exists in exploring sTf complexation of nonferric metals as it facilitates the therapeutic potential and toxicity of several of them. This review explores recent X-ray structural and physiologically relevant metal speciation studies to understand how sTf partakes in the bioactivity of key non-redox active hard Lewis acidic metals. It challenges preconceived notions of sTf structure function correlations that were based exclusively on the Fe(III) model by revealing distinct coordination modalities that nonferric metal ions can adopt and different modes of binding to metal-free and Fe(III)-bound sTf that can directly influence how they enter into cells and, ultimately, how they may impact human health. This knowledge informs on biomedical strategies to engineer sTf as a delivery vehicle for metal-based diagnostic and therapeutic agents in the cancer field. It is the intention of this work to open new avenues for characterizing the functionality and medical utility of nonferric-bound sTf and to expand the significance of this protein in the context of bioinorganic chemistry.

The boundary layer height (BLH) distinguishes the interface between the lower and free atmosphere, which is a key variable in numerical simulation, aerosol, and environmental pollution studies. Thus, the goal of this work is to propose a novel method conjuncting with numerical regularization to analyze climate characteristics of the marine boundary layer height (MBLH) using 2007-2011 GPS-RO data from the COSMIC mission. While traditionally, the difference method has been used to achieve this aim, herein, we propose an innovative method, in which the bending angle profile gradient was calculated using the numerical regulation method where the regulation parameters are determined by the double-parameter model function method. Then, the MBLH was determined by employing the maximum gradient method to ascertain the height corresponding to the smallest gradient. The results show a correlation between currents and the MBLH—a relationship that has not been previously demonstrated. A low MBLH is associated with seasons and regions where cold ocean currents are prevailing; whereas a high MBLH is observed in the seasons and places where warm currents are prevailing. This correlation was validated by comparing the obtained results with different occultation data—i.e., atmprf and echprf—which also established that atmprf is more sensitive to convective cloud top capture. In seas with active convection, the armprf calculated bending angle is higher than that from echprf. Subsequently, the standard deviation was used to express the MBLH confidence level. The results show that the MBLH standard deviation is highest in low latitudes and lowest in the middle and high latitudes. Furthermore, we analyzed the interannual MBLH variation trend, which displayed a seasonal variation and spatial distribution corresponding with the current and subsolar point. Finally, we conducted a case study in the South China Sea, and identified a distinctive seasonal change and downward trend.

The main purpose of this paper is to introduce and investigate degenerate Poisson distrib- ution which is a new extension of the Poisson distribution including the degenerate expo- nential function. We then provide several properties of the degenerate Poisson distribution such as the first and the second raw moments and di¤erence operator property. Moreover, we acquired the skewness and the kurtosis for the degenerate Poisson distribution. We also derive its moment generating function by which we define the degenerate Bell polynomials and give a connection for these polynomials related to the unsigned Stirling numbers of the …rst kind.

Single-molecule fluorescence detection (SMFD) experiments are useful in distinguishing sub-populations of molecular species when measuring heterogeneous samples. One experimental platform for SMFD is based on a confocal microscope, where molecules randomly traverse an effective detection volume. The non-uniformity of the excitation profile and the random nature of Brownian motion, produce fluctuating fluorescence signals. For these signals to be distinguished from the background, burst analysis is frequently used. Yet, the relation between the results of burst analyses and the underlying information of the diffusing molecules is still obscure and requires systematic assessment. In this work we performed three-dimensional Brownian motion simulations of SMFD, and tested the positions at which molecules emitted photons that passed the burst analysis criteria for different values of burst analysis parameters. The results of this work verify which of the burst analysis parameters and experimental conditions influence both the position of molecules in space when fluorescence is detected and taken into account, and whether these bursts of photons arise purely from single molecules, or not entirely. Finally, we show, as an example, the effect of bursts that are not purely from a single molecule on the accuracy in single-molecule Förster resonance energy transfer measurements.

The complete-lattice approach to optimization problems with a vector- or even set-valued objective already produced a variety of new concepts and results and was successfully applied in finance, statistics and game theory. For example, the duality issue for multi-criteria and vector optimization problems could be solved using the complete-lattice approach, compare [11]. So far, it has been applied to set-valued dynamic risk measures (in the stochastic case), as discussed in Feinstein, Rudloff etc. (see [11], for example), but it has not been applied to deterministic calculus of variations and optimal control problems. In this paper, the following problem of set-valued optimization is considered: minimize the functional $$ \overline J_t[y]=\int_0^t \overline L(s,y(s),\dot y(s))\ ds + U_0(y(0)) $$ over all admissible arcs $y$, where $\overline L$ is the associated multifunction to a vector-valued Lagrangian $L$, the integral is in the Aumann sense and $U_0$ is the initial cost. A new concept of \emph{value function}, for which a Bellman's optimality principle holds, is introduced. Also the classical result of the Hopf-Lax formula holds for the generalized value function. Finally, a derivative with respect to the time $t$ and a directional derivative with respect to $x$ of the value function are defined, based on ideas close to the concepts in [12]. The value function is proved to be solution of a suitable Hamilton-Jacobi equation.

In this paper, we will revisit the derivation of Heisenberg's uncertainty principle. We will see how the Heisenberg principle collapses at the Planck scale by introducing a minor modification. The beauty of our suggested modification is that it does not change the main equations in quantum mechanics; it only gives them a Planck scale limit where uncertainty collapses. We suspect that Einstein could have been right after all, when he stated, ``God does not throw dice." His now-famous saying was an expression of his skepticism towards the concept that quantum randomness could be the ruling force, even at the deepest levels of reality. Here we will explore the quantum realm with a fresh perspective, by re-deriving the Heisenberg principle in relation to the Planck scale. We will show how this idea also leads to an upper boundary on uncertainty, in addition to the lower boundary. These upper and lower boundaries are identical for the Planck mass particle; in fact, they are zero, and this highlights the truly unique nature of the Planck mass particle. Further, there may be a close connection between light and the Planck mass particle: In our model, the standard relativistic energy momentum relation also seems to apply to light, while in modern physics light generally stands outside the standard relativistic momentum energy relation. We will also suggest a new way to look at elementary particles, where mass and time are closely related, consistent with some of the recent work in experimental physics. Our model leads to a new time operator that does not appear to be in conflict with the Pauli objection. This indicates that both mass and momentum come in quanta, which are perfectly correlated to an internal Compton `clock' frequency in elementary particles.

Physical Unclonable Functions (PUFs) based on the retention times of the cells of a Dynamic Random Access Memory (DRAM) can be utilised for the implementation of cost-efficient and lightweight cryptographic protocols. However, as recent work has demonstrated, the times needed in order to generate their responses may prohibit their widespread usage. In order to address this issue, the Row Hammer PUF has been proposed by Schaller et al. [1], which leverages the row hammer effect in DRAM modules to reduce the retention times of their cells and, therefore, significantly speed up the generation times for the responses of PUFs based on these retention times. In this work, we extend the work of Schaller et al. by presenting a run-time accessible implementation of this PUF and further reducing the time required for the generation of its responses. Additionally, we also provide a more thorough investigation of the effects of temperature variations on the the Row Hammer PUF and briefly discuss potential statistical relationships between the cells used to implement it. As our results prove, the Row Hammer PUF could potentially provide an adequate level of security for Commercial Off-The-Shelf (COTS) devices, if its dependency on temperature is mitigated, and, may therefore, be commercially adopted in the near future.

In this paper, we define a (p,v)-extension of Hurwitz-Lerch Zeta function by considering an extension of beta function defined by Parmar et al. [J. Classical Anal. 11 (2017) 81–106]. We obtain its basic properties which include integral representations, Mellin transformation, derivative formulas and certain generating relations. Also, we establish the special cases of the main results.

Recently, cloud technology has become popular for smart societies. The Cloud technology has made dynamical network changes by enabling the construction of a logical network without building a physical network. Despite recent research on the cloud, it is necessary to study security functions for the identification of fake VNFs and the encryption of communication between entities. In this paper, we proposed an LW_PKI mechanism that detects a fake VNF and guarantees data security through mutual authentication between VNFs. To evaluate the LW_PKI, we built a MANO environment to test the performance of authentication and key generation for data security. In addition, we applied the artificial intelligence algorithm to detect abnormal behavior by using real attack data in the MANO environment. The LW_PKI guaranteed the reliability of a smart service by enhancing the security of the cloud environment.

In this paper, we introduce a new generalization of the r-Stirling numbers of the second kind based on the q-numbers via an exponential generating function. We investigate their some properties and derive several relations among q-Bernoulli numbers and polynomials, and newly de…ned (q, r, w)-Stirling numbers of the second kind. We also obtain q-Bernstein polynomials as a linear combination of (q, r, w)-Stirling numbers of the second kind and q-Bernoulli polynomials in w.

In the present paper, we introduce (p, q)-extension of Apostol type Frobenius-Euler polynomials and numbers and investigate some basic identities and properties for these polynomials and numbers, including addition theorems, difference equations, derivative properties, recurrence relations and so on. Then, we provide integral representations, explicit formulas and relations for these polynomials and numbers. Moreover, we discover (p, q)-extensions of Carlitz's result [L. Carlitz, Mat. Mag., 32 (1959), 247–260] and Srivastava and Pintér addition theorems in [H. M. Srivastava, A. Pinter, Appl. Math. Lett., 17 (2004), 375–380].

In the paper, the authors find two explicit formulas and recover a recursive formula for the generalized Motzkin numbers. Consequently, the authors deduce two explicit formulas and a recursive formula for the Motzkin numbers, the Catalan numbers, and the restricted hexagonal numbers respectively.

In the paper, the authors consider the generating functions of the Hermite polynomials and their squares, present explicit formulas for higher order derivatives of the generating functions of the Hermite polynomials and their squares, which can be viewed as ordinary differential equations or derivative polynomials, find differential equations that the generating functions of the Hermite polynomials and their squares satisfy, and derive explicit formulas and recurrence relations for the Hermite polynomials and their squares.

Hydraulic fracturing has enabled production from unconventional reservoirs in the U.S., but production rates often decline sharply, limiting recovery factors to under 10%. This study optimizes the CO2 huff-n-puff process for multistage-fractured horizontal wells in Wolfcamp A formation in the Delaware Basin. The potential for enhanced oil recovery and CO2 sequestration simultaneously was addressed using a coupled geomechanics-reservoir simulation. Geomechanical properties were derived from a 1D mechanical earth model and integrated into reservoir simulation to replicate hydraulic fracture geometries. The fracture model was validated using a robust production history matching. Fluid phase behavior analysis refined the equation of state, and 1D slim tube simulations determined a minimum miscibility pressure of 4300 psi for CO2 injection. After the primary production phase, various CO2 injection rates were tested from 1 to 25 MMSCFD/well, resulting in incremental oil recovery ranging from 6.3% to 69.3%. Different injection, soaking, and production cycles were analyzed to determine the ideal operating condition. The optimal scenario improved cumulative oil recovery by 68.8% while keeping the highest CO2 storage efficiency. The simulation approach proposed by this study provides a systematic workflow for evaluating and optimizing CO2 huff-n-puff in hydraulically fractured wells, enhancing the recovery factor of unconventional reservoirs.

Droplet-based microfluidics has revolutionized numerous fields such as biomedical research, pharmaceuticals, drug discovery, food engineering, flow chemistry, and cosmetics. This paper presents a comprehensive study focusing on the detection and characterization of droplets with volumes in the nanoliter range. Leveraging the precise control of minute liquid volumes, we introduced a novel spectroscopic On-Chip microsensor equipped with integrated microfluidic channels for droplet generation, characterization, and sensing, simultaneously. The microsensor, designed with Interdigitated-Ring-Shaped Electrodes (IRSE) and seamlessly integrated with microfluidic channels, offers enhanced capacitance and impedance signal amplitudes, reproducibility, and reliability in droplet analysis. We were able to make analyses of droplets length in the range 1.0-6.0 mm, velocity 0.66-2.51 mm/s, droplet volume 1.07nL-113.46nL. Experimental results demonstrated that the microsensor's has a great performance in terms of droplet size, velocity, and length, with a significant signal amplitude of capacitance and impedance, and real-time detection capabilities, thereby highlighting its potential for facilitating microcapsule reactions and enabling on-site real-time detection for chemical and biosensor analyses on-chip.

Noninvasive brain stimulation technique can be used for modulation of motor behaviors such as reaction time (RT). The main aim of this study was to investigate whether RT during a sequential visual isometric pinch task (SVIPT) can be affected by anodal transcranial direct current stimulation (a-tDCS) over three different stimulation sites such as dorsolateral prefrontal cortex (DLPFC), primary motor cortex (M1) or posterior parietal cortex (PPC). We also aimed to assess if stimulation of these cortical sites affect the transfer of learning during SVIPT. A total of 48 right-handed healthy participants were randomly assigned to one of the four a-tDCS groups: 1) left M1, 2) left DLPFC, 3) left PPC and 4) sham. A-tDCS was applied concurrent with SVIPT in which the participants were precisely controlled their forces to reach seven different target forces from 10 to 40% of maximum voluntary contraction (MVC) presenting on a computer screen with right dominant hand. Four test blocks were randomly performed at baseline and 15 min after the intervention including sequence and random blocks with either hand. Our results showed significant differences between a-tDCS groups on ratio RT in the sequence blocks of both the right trained (P = .041) and left untrained hands (P = .023) for target forces of 15% and 30 % of MVC, respectively. In sequence blocks, M1 showed significant elongation in ratio RT for the target force of 15% and 30 % MVC compared to PPC and Sham groups in the right hand. In sequence blocks with left hand, this negative effect were found between M1-DLPFC and M1-Sham groups. In random blocks, no significant differences were found among four groups at each target forces for the left hand while there were significant differences for 15% (P =. 04) and 40% MVC (P =. 035) in the right hand. Our findings suggest that three different stimulation sites (DLPFC, M1 or PPC) were differentially affected by a single session of a-tDCS at some target forces during SVIPT. The effects of a-tDCS on ratio RT were transferred in the left untrained hand for sequence blocks but not random blocks. Further research is needed to understand fundamental aspects of these main areas of the brain on temporal processing in a precision control task such as SVIPT.

Heterotopic ossification (HO) is most dramatically manifested in the rare and severely debilitating disease, fibrodysplasia ossificans progressiva (FOP), in which heterotopic bone progressively accumulates in skeletal muscles and associated soft tissues. The great majority of FOP cases are caused by a single amino acid substitution in the type 1 bone morphogenetic protein (BMP) receptor ACVR1, a mutation that imparts responsiveness to activin A. Although it is well-established that biological sex is a critical variable in a range of physiological and disease processes, the impact of sex on HO in animal models of FOP has not been explored. We show that female FOP mice exhibit both significantly greater and more variable HO responses after muscle injury. Additionally, the incidence of spontaneous HO was significantly greater in female mice. This sex dimorphism is not dependent on gonadally-derived sex hormones, and reciprocal cell transplantations indicate that apparent differences in osteogenic activity are intrinsic to the sex of the transplanted cells. By circumventing the absolute requirement for activin A using an agonist of mutant ACVR1, we show that the female-specific response to muscle injury or BMP2 implantation is dependent on activin A. These data identify sex as a critical variable in basic and preclinical studies of FOP.

In this work, an evanescent Bragg grating sensor inscribed in a few-mode planar polymer waveguide was integrated in microchannel structures and characterized with various chemical applications. The planar waveguide and the microchannels consisted of epoxide-based polymers. The Bragg grating structure was post-processed using point-by-point direct inscription technology. By monitoring the central wavelength shift of the reflected Bragg signal, the sensor showed a temperature sensitivity of -47.75 pm/K. Moreover, the functionality of the evanescent field-based measurements is demonstrated with two application examples: refractive index sensing of different aqueous solutions and gas-phase hydrogen concentration detection. For the latter application, the sensor was additionally coated with a functional layer based on palladium nanoparticles. During the refractive index sensing measurement, the sensor achieved a sensitivity of 6.5 nm/RIU from air to 99.9% pure isopropyl alcohol. For the gas-phase hydrogen detection, the coated sensor achieved a reproducible concentration detection up to 4 vol% hydrogen. According to the reported experimental results, the integrated Bragg grating-based waveguide sensor demonstrates high potential for applications based on lab-on-a-chip concept.

We propose a phenomenological theory of spin behavior in a magnetic field, which explains from the point of view of classical physics the two-valued result of the Stern-Gerlach experiment. The behavior of the spin and intrinsic magnetic moment of an electron wave of an atom in an external magnetic field is considered. We show that in a weak magnetic field, the intrinsic magnetic moment of an electron wave is always oriented parallel to the magnetic field strength vector, while in a strong magnetic field, depending on the initial orientation of the intrinsic magnetic moment, two orientations are realized: either parallel or antiparallel to the magnetic field strength vector. Within the framework of classical electrodynamics, the calculation of the motion of an atomic beam in an inhomogeneous magnetic field is carried out, which reproduces the results of the Stern-Gerlach experiment.

Bacillus veleznesis RB.EK7 was recently found as a potent rhizobacterial strain for effective management of black pepper root-knot nematodes. This work aimed to produce, purify, and elucidate the chemical structures of antinematode compounds (ANCs). Concerning cost-effectiveness and environmental issues, this study used organic wastes for the bioproduction of ANCs. Among various substrates, shrimp shells powder was the most suitable carbon/nitrogen source to produce ANCs. The fermentation process for enhancement of antinematode activity was investigated. The targeting ANCs were purified from the fermented culture broth, and their structures were elucidated. Two active compounds were thymine (1) and hexahydropyrrolo [1,2-a]pyrazine-1,4-dione (2). Notably, for the first time, these purified compounds showed potential and moderate anti- J2 nematodes and anti-eggs hatching, respectively. The docking study results indicated that the potent antinematode effect of these compounds may be possibly due to the inhibition of the targeting enzyme acetylcholinesterase. The data of this work suggest that organic waste SSP can be potentially reused for the production of thymine and hexahydropyrrolo [1,2-a] pyrazine-1,4-dione with promising use for the management of black pepper nematodes.

Since its inception in the late 2000s, blockchain has emerged as a powerful tool for creating trust without intermediaries to incentivize global communities for working for a common goal, such as the improvement of its very ecosystem, its applications and community adoption. While first blockchains were mainly devised for confirming transactions of their innate cryptocurrencies like Bitcoin, smart-contract blockchains like Ethereum can interface with the real-world through so-called “oracles”, which feed trustful off-chain information. This paper introduces digital twins of physical objects and processes as computational oracles to effectively unleash the tremendous opportunity offered by blockchain to the realm of fundamental science, research and technology development (RTD). The crowdsourcing concept is illustrated with the example of centrifugal flow control in microfluidic “Lab-on-a-Disc” (LoaD) systems.

This theoretical article provides a brief description of the model of living systems' functioning by defining them as resource flows patterns. It reviews the living systems growth limitation between their development cycles by the Fibonacci sequence. Besides, there are presented systems resource base criteria, necessary for accumulating the resources and their investment. The article also considers the conditions for the formation of various systems strategies. Then we reviewed the principles of elemental analysis of information by a person as a living system according to the considered model. The study also shows the possibility of forming priorities in analyzing information for 16 combinations as maximum. At that, it remains crucial to divide a human's information analysis between the two hemispheres of the brain. The described combinations of priorities in a person's information analysis are compared with the existing differential personality models, such as the big five personality traits, the Myers-Briggs type indicator, temperaments model and Honey and Mumford Learning styles.

The ongoing revolution in Deep Learning is redefining the nature of computing that is driven by the increasing amount of pattern classification and cognitive tasks. Specialized digital hardware for deep learning still holds its predominance due to the flexibility offered by the software implementation and maturity of algorithms. However, it is being increasingly desired that cognitive computing occurs at the edge, i.e. on hand-held devices that are energy constrained, which is energy prohibitive when employing digital von Neumann architectures. Recent explorations in digital neuromorphic hardware have shown promise, but offer low neurosynaptic density needed for scaling to applications such as intelligent cognitive assistants (ICA). Large-scale integration of nanoscale emerging memory devices with Complementary Metal Oxide Semiconductor (CMOS) mixed-signal integrated circuits can herald a new generation of Neuromorphic computers that will transcend the von Neumann bottleneck for cognitive computing tasks. Such hybrid Neuromorphic System-on-a-chip (NeuSoC) architectures promise machine learning capability at chip-scale form factor, and several orders of magnitude improvement in energy efficiency. Practical demonstration of such architectures has been limited as performance of emerging memory devices falls short of the expected behavior from the idealized memristor-based analog synapses, or weights, and novel machine learning algorithms are needed to take advantage of the device behavior. In this work, we review the challenges involved and present a pathway to realize ultra-low-power mixed-signal NeuSoC, from device arrays and circuits to spike-based deep learning algorithms, with ‘brain-like’ energy-efficiency.

The concept of sustainable management in culture has been recognised in global strategic documents on sustainable development for more than a decade. It is also increasingly reflected in the cultural polices of particular states, and – very importantly –cultural managers responsible for shaping the cultural offer in cities are becoming more interested in this concept. Despite the increasing attention being paid to this topic among both practitioners and theoreticians of management, in none of these documents or other works can we find any content directly related to the possibility of applying this concept in a town which, due to political turmoil, has been divided by a national border. Hence, this gap was the direct impulse for taking up research in this field. In the article, by using different notions of the market, our own definition of a cross-border market for cultural services was developed, and the conditions for the functioning of this market were presented based on the example town of Cieszyn (Poland) and Český Těšín (Czech Republic). In the opinion of the authors of the article, the development and functioning of a cross-border market for cultural services is essential for the application of the concept of sustainable management of the cultural offer in a town divided by a border. For the purpose of the article, a survey and individual interviews with experts shaping the cultural offer in Cieszyn and Český Těšín were conducted. The results of the research prove that despite numerous cross-border Czech-Polish projects carried out by cultural institutions, there are still many barriers in the town which make it difficult for the residents to benefit from the cultural offer available on the other side of the border. These barriers limit the full implementation and application of the concept of sustainable management of the cultural offer.

The present study was aimed to evaluate the levels of oxidative stress markers in breast diseases by measuring the 8-hydoxy-2-deoxyguanosine (8-OHdG), vitamin A, vitamin C, vitamin E and total antioxidant status (TAS) alterations in relation to cell proliferation activity and disease progression. Significant increases in the level of oxidative damage marker 8-OHdG and cell proliferation activity were observed in breast carcinoma patients in comparison to benign and normal controls, which were accompanied by significant decrease in non enzymatic antioxidants and TAS concentrations. 8-OHdG and cell proliferation level were negatively correlated with non enzymatic antioxidants viz., Vitamin A, Vitamin C, vitamin E level and total antioxidant activity. Altered levels of biomarkers of oxidative stress and cell proliferation activity amongst the malignant, benign and controls suggest a correlation of increased oxidative stress and cell proliferation activity in the progression of disease in breast carcinoma patients. Among the oxidative stress markers and cell proliferation index, decreased level of vitamin A, vitamin C, vitamin E, TAS and increased level of 8-OHdG, cell proliferation index emerged as best predicted biomarkers for subjects with malignancy and benign breast disease.

Hypertrophic cardiomyopathy (HCM) is a common form of cardiomyopathy in cats, and heart failure occurs as diastolic dysfunction progresses. HCM in cats is broadly classified as non-obstructive and obstructive hypertrophic cardiomyopathy, depending on the presence or absence of outflow tract obstruction. Measurement of the intraventricular pressure differences (IVPD) using Color M-mode (CMM) has attracted attention as a reliable diastolic index as it correlates with catheterization, the gold standard for assessment of diastolic performance. Since, IVPD is affected by the size of the heart, the intraventricular pressure gradient (IVPG) index, which is unaffected by heart size, is used by dividing IVPD be LV length. In the present study, CMM IVPG was used to non-invasively assess diastolic impairment in cats with obstructive hypertrophic cardiomyopathy. This study was conducted on ten control cats and 18 cats in the HCM group. Although no severe left atrial enlargement was observed in the HCM group, the Basal IVPG was significantly increased in the HOCM group compared to the control group. While IVPD typically suggests impaired diastolic function and reduced ventricular compliance, the significant increase observed in the HOCM group compared to controls may suggest an indirect elevation in left atrial pressure, likely secondary to left ventricular outflow tract obstruction. The increase in IVPG in HOCM, as shown in this study, is a pathological effect of left ventricular outflow tract obstruction that cannot be detected by conventional echocardiographic indices, and evaluating IVPG is useful for evaluating cardiac function from a different perspective than conventional methods.

Indoleamine 2,3-dioxygenase 1 (IDO1) and IDO2, originated from gene duplication before vertebrate diver-gence. While IDO1 has a well-defined role in immune regulation, the biological role of IDO2 remains unclear. Discovered in 2007, IDO2 is located near the IDO1 gene. Because of their high sequence similarity, IDO2 was initially thought to be a tryptophan (Trp)-degrading enzyme like IDO1. Differently from what expected, IDO2 displays extremely low catalytic activity toward Trp. Nevertheless, many studies, often contradictory, tried to demonstrate that IDO2 modulates immune responses by catabolizing Trp into kynurenine, a hypothesis un-convincing and, let’s say, linked to the first life of IDO2. Here, we review its “new life”, the one in which IDO2 has a functional role beyond Trp metabolism. The IDO2’s evolutionary persistence across species, despite be-ing almost inactive as an enzyme, suggests it has some relevant biological importance. IDO2 expression in human normal cells is poor, but significant in various cancers, with two prevalent SNPs. Overall, the com-parison of IDO2 to IDO1 as a Trp-degrading enzyme may have led to misunderstandings about IDO2’s true physiological and pathological roles. New insights suggest that IDO2 might function more as a signaling molecule, particularly in cancer contexts, and further studies could reveal its potential as a target for cancer therapy.

The biological function of rapid eye movement (or REM) sleep—one of the great mysteries of neuroscience—remains unknown. Here, I demonstrate that the biological function of REM sleep is to heighten brain alertness, significantly reducing the high vulnerability of deep sleep. Every organism with a nervous system must undergo deep sleep: a necessity that comes with substantial vulnerability. Deep sleep, by lowering alertness, compromises the organism's safety, putting its survival at risk. Therefore, REM sleep is a necessary adaptation for any organism that must sleep. My primary goal here is to present a comprehensive conceptual framework—supported by extensive empirical evidence—to connect numerous disparate empirical findings under a unified theory of the biological function of REM sleep. Additionally, I also provide a historical narrative to explain its origin and subsequent evolution. The theory I developed to explain the function of REM sleep is not only widely corroborated but has also resisted numerous attempts at refutation. This allows me to claim that I solved this great enigma of neuroscience.

A methodology for selecting rational parameters of atmospheric aircrafts at the initial stages of design using an optimization algorithm of differential evolution and numerical mathematical modeling of aerodynamics problems is proposed. The technique involves the implementation of weight and aerodynamic balance in the main flight modes, has the ability to consider atmospheric aircrafts with one or two lifting surfaces, apply parallel calculations and automatically generate a three-dimensional geometric model of aircraft appearance based on the optimization results. A method for accelerating the process of optimizing the parameters of an aircraft in terms of take-off weight by more than three times by introducing a objective function into a set of design variables is proposed and demonstrated. The results of assessing the reliability of the used mathematical models of aerodynamics and the correctness of the calculation the objective function, taking into account various constraints, are presented. A comprehensive test of the performance and efficiency of the methodology is considered by solving demonstration problems to optimize more than ten main design parameters the appearance of two existing heavy-class unmanned aerial vehicles with known characteristics from open sources.

In the context of evolving perceptions of sexuality, particularly within the realm of health and disability, this study investigates the impact of multiple sclerosis (MS) on female sexual function and quality of life. A quantitative study involving 130 female MS patients aged 35 to 50 was conducted, employing measures such as The Female Sexual Function Index (FSFI), The Multiple Sclerosis Intimacy and Sexuality Questionnaire-19 (MSISQ-19), and The Fatigue Severity Scale (FSS). Results indicate a significant association between greater sexual dysfunction and poorer quality of sex life, alongside the correlation of increased fatigue with diminished sexual satisfaction. Factors such as education level, time of diagnosis, and treatment regimen also influenced outcomes. Findings underscore the importance of supportive interventions, including counseling, to enhance the quality of sex life for women with disabilities, particularly those with MS.

High dimensional datasets are highly likely to have redundant, irrelevant, and noisy features that negatively affect the performance of the classification algorithms. Selecting the most relevant features and reducing the dimensions of datasets by removing the undesired features is a dimensional reduction technique called Feature Selection (FS). In this paper, we propose an FS approach based on the Black Hole Algorithms (BHO) with a mutation technique called MBHO. Generally, BHO contains two major phases. At the exploitation phase, a set of stars are modified based on some rule and according to some objective function, the best star is selected as the black hole which attracts other stars. Furthermore, when a star gets closer to the event horizon, it will be swallowed and a new one will be randomly generated in the search space which thus is the exploration phase. However, randomness may cause the algorithm to fall into the trap of local optima, and to overcome such complications, inversion mutation is used. Furthermore, we modify a widely utilized objective function in most of the proposed works for wrapper feature selection by combining two new terms that are based on the correlation among the selected subset of features and the features and the classification label. We also utilize a transfer function, known as the V2 transfer function, to convert continuous values into discrete ones to enhance search. We assess our approach via extensive evaluation experiments using fourteen benchmark datasets. We benchmark the performance of a wrapper FS approach called Binary Cuckoo Search (BCS), and three filter-based FS approaches (namely Mutual Information Maximisation (MIM), Joint Mutual Information (JMI), and minimum Redundancy Maximum Relevance (mRMR)). Our evaluation has shown that the proposed model is an effective approach for FS, in selecting better features that enhance the performance metrics on the classifiers. Thus, MBHO can be utilized as one alternative to the existing state-of-art-approaches. We release the source codes of our implementation for the community to build on with new methods and datasets.

Because it can make exact double-strand breaks in DNA, CRISPR-Cas9 can help almost every species and type of cell. It is a powerful way to change the DNA code. CRISPR-Cas9 can be used for a lot more than just changing genes. We are close to being able to do high-throughput gene screening, epigenome editing, in-vivo cell tagging, and RNA change. With the help of CRISPR-Cas9, the function of genes can be studied better, and more realistic disease models can be made. The revolutionary new discipline of gene editing has the potential to profoundly impact healthcare and the life sciences. By simplifying the process of creating double-strand breaks in the DNA of almost any species or kind of cell, CRISPR-Cas9 has revolutionized gene editing. Numerous applications have been found for the CRISPR-Cas9 system. High-throughput gene screening, RNA modification, live-cell chromosome marking, and epigenome editing are all examples. CRISPR-Cas9 facilitates gene research, leading to the development of CRISPR-based disease models. CRISPR-Cas9-based methods of altering the genome will aid researchers in learning more about sickness and discovering better ways to cure it, despite the fact that there are still many questions and large difficulties to answer.