Miracle-dz/UniFAR-FTUs huggingface dataset:
Degenerate Hopf bifurcation and nerve impulse, part II

The bifurcation from equilibrium of periodic solutions of the Hodgkin and Huxley equations for the nerve impulse is studied. In earlier work singularity theory techniques were used to establish that these equations have a branch of periodic solutions undergoing two Hopf bifurcations, and the equations were conjectured to be equivalent to a member of a one-parameter family of generalized Hopf bifurcation problems. Here the invariants for equivalence to this family and the value of the modal parameter are computed (see [W. W. Farr et al., “Degenerate Hopf bifurcation formulas and Hilbert’s 16th problem,” SIAM J. Math. Anal., 20 (1989), pp. 13–30]). The value of this parameter determines the type of bifurcation, and in this way it is decided which of the proposed bifurcation diagrams are actually to be found. Thus a topological description of periodic orbits of the Hodgkin and Huxley equations near the equilibrium solution is obtained. In this way, a periodic solution branch is found that does not arise thro.
ON THE POSITIVITY OF THE RICCI CURVATURE, OF THE SECTIONAL CURVATURE AND OF THE CURVATURE OPERATOR

Abstract We show that the positivity of the the Ricci curvature Ric of an n-dimensional Riemannian manifold (M; g) is equivalent to the positivity of the higher scalar curvatures scalk : M → ℝ, k = 1, 2, . ,n. Then we introduce higher Ricci curvatures Rick : S(TM) → ℝ, k = 1; 2, . ,n - 1 which are homogeneous symmetric forms of order 2k on the tangent unit shere bundle, and show that the positivity of the sectional curvature K is equivalent to the positivity of the Rick. At last we show that the curvature operator O is positive definite if and only if certain scalar operator curvature invariants σk(O) : M → ℝ are positive for all k = 1; 2, . , [xxx].
Search boundaries of the truncated discrete sequential test

The theme of this paper is improved planning of binomial sequential probability ratio tests in the context of comparison of two objects as to their time between failures or to failure, assumed to be exponentially distributed. The authors’ earlier works established that the probabilities of I- and II- type errors (α and β) are discrete in character and do not lend themselves to analytical expression. Accordingly, the choice of the optimal parameters for the decision boundaries necessitates a search for extrema in discrete sets. The present work outlines a procedure that involves application of the continued-fractions theory, and permits finding the set of boundary positions in which the test characteristics undergo changes. It was established, that in the domains described in the earlier papers, the relationships of α and β versus these positions are close to planar and – within narrow limits – stepwise. The step sizes are highly variable, so that the standard minimum search procedures are either cumbersome or actually useless. On the basis of these relationships~– and others – a search algorithm is proposed for the optimal test boundaries. An example is presented – planning and implementation of this test in the integrated-circuit industry.
Climate change and the middle atmosphere. I - The doubled CO2 climate

Abstract The impact of doubled atmospheric CO2 on the climate of the middle atmosphere is investigated using the GISS global climate/middle atmosphere model. In the standard experiment, the CO2 concentration is doubled both in the stratosphere and troposphere, and the sea surface temperatures are increased to match those of the doubled CO2 run of the GISS 9 level climate model. Additional experiments are run to determine how the middle atmospheric effects are influenced by tropospheric changes, and to separate the dynamic and radiative influences. These include the use of the greater high latitude/low latitude surface warming ratio generated by the Geophysical Fluid Dynamics Laboratory doubled CO2 experiments, doubling the CO2 only in either the troposphere or stratosphere, and allowing the middle atmosphere to react only radiatively. As expected, doubled CO2 produces warmer temperatures in the troposphere, and generally cooler temperatures in the stratosphere. The net result is a decrease of static stabi.
Multiple UAVs Trajectory Optimization in Multicell Networks With Adjustable Overlapping Coverage

Trajectory optimization of unmanned aerial vehicles (UAVs) operating as flying base stations (FBSs) evolved as a novel integration component in beyond 5G (B5G) networks and has recently received significant research attention. Notably, the vast majority of previous research has mainly concentrated on the case of a single terrestrial macro base station (BS) which is used as a depot for multiple FBSs. In this article, we focus on the more general use case where multiple FBSs located at different macro-BSs used as a depot serve ground users (GUs) at cluster points (CPs). To this end, we formulate the FBSs trajectory optimization problem using a mixed-integer linear programming (MILP) formulation with the aim to minimize the total travel time (TTT) of the FBSs in a multicell network in which their cell coverage or boundary is adjustable for the FBSs deployment; creating in that sense virtual cells for the FBSs. Furthermore, heuristic algorithms are proposed to provide competitive solutions and reduce the computational time in view of the curse of dimensionality of the original problem. Numerical investigations reveal that the proposed FBSs path planning optimization solutions decrease the TTT and increase the efficiency of offloading collected data for the FBSs deployment with gains up to approximately 23% and 19%, respectively, compared to nominal schemes that consider the predefined coverage range of the cells or no cell boundaries. Aside from the above, compared to previously proposed nominal strategies, the proposed schemes achieve an almost 27% improvement in terms of fairness (Jain’s index) on the FBS traveling time.
Effects of rotating magnetic field and temperature field on comminution of magnetic particles

Abstract This study examines the movement patterns and comminution of magnetic Ni particles in pure water in a flask. This flask is on top of an actuator which contains a rotating bar magnet, and is surrounded by circulating water at a constant temperature. A digital camera, a particle size analyzer and a field emission electron microscope were adopted to record the moving patterns, particle size distributions and micrographs of magnetic Ni particles. A thermocouple was employed to measure the temperature of pure water in the flask during Ni particle attrition. The effect of the temperature of the water that circulated around the periphery of the flask and the effect of the shape of the flask were analyzed. This study also investigated the effects of the water‐to‐particulate mass ratio and the placement of a bar magnet with an interface between the positive and negative poles in a bar magnet at an inclination angle on the shrinking and the moving pattern of the Ni particles.
Layer width control in robotic pulsed gas tungsten arc additive manufacturing through composite sensing of vision and arc

ABSTRACT Monitoring and control of layer geometry in robotic-pulsed gas tungsten arc additive manufacturing (GTA AM) are essential and challenging issues. This study attempts to realize controllable layer width via imposing a closed-loop controller based on a composite sensing of vision and arc. A vision sensor is utilized to monitor the layer width, and an arc voltage sensor capable of characterizing the arc length is introduced to calibrate the vision sensor. The image acquisition time for layer width is determined via analyzing the features of successive molten pool images, i.e. 80 ms after the rising edge from the base current to the peak current. Image processing procedures are developed to determine the layer width. A parameter self-adjusting Fuzzy (PSA-Fuzzy) controller is designed to control the layer width by adjusting the peak current. Closed-loop tests confirm that the PSA-Fuzzy controller can significantly increase the layer width consistency in robotic pulsed GTA AM.
Aprendizado de Máquina para a Previsão do Comportamento de Preços da Criptomoeda Ethereum

Elaboração de algoritmos de aprendizado de máquina para a previsão do comportamento de preços da criptomoeda Ethereum, utilizando-se uma base de dados pública (Kaggle). Os modelos elaborados foram do tipo linear (ARIMA, séries temporais) e nãolinear (três modelos de redes neurais LTSM). Como melhor resultado, verificou-se que um dos modelos não lineares foi capaz de realizar previsões distantes em média de 4,32% dos preços reais.
Illness Perception and Medication Adherence among Adult Patients with Type 2 Diabetes Mellitus: A Scoping Review

(1) Background: Type 2 diabetes mellitus (T2DM) is a global disease with a compelling impact on developed and developing economies across the globe. The World Health Organization (WHO) (2020) reported a global prevalence of 8.5% in 2014 among adults aged at least 18 years. Consequently, the condition led to a 5% increase in premature mortality from 2000 to 2016. Aim: The scoping review sought to examine illness perception and medication adherence among adult patients with T2DM. (2) Methods: The study was conducted in 2021 and covered articles published in English in the last five years. PubMed, MEDLINE, CINAHL, and ScienceDirect were the primary search engines used to generate the required scholarly records. A total of 20 studies met the inclusion criteria. (3) Results: The 20 studies selected for the scoping review covered different themes on the overall concept of illness perception and medication adherence in adults with Type 2 Diabetes Mellitus. Each study presented unique implications for research and influence on the policymaking relating to the treatment or the management of type 2 diabetes mellitus in adults of different aged groups. (4) Conclusions: The studies reveal both high and low adherence to medications in adults with type 2 diabetes mellitus. The management and treatment of the condition depend on the uptake of oral hypoglycemic agents or insulin as well as the recommended therapies to enhance the clinical outcomes of the patients.
Low-level tropospheric ozone

In late April 1965, a brief episode of high ozone concentration was reported in the tobacco growing region of north Florida and Southern Georgia. Peak values of 10 pphm were recorded, and fleck damage to tobacco became evident within about 24 hours. The episode was not attributable to anthropogenic pollution, in that the area is rural. The episode was attributed to a severe thunderstorm event which was hypothesized to have drawn stratospheric ozone into the lower troposphere. 14 references, 3 figures.
A single-product network design model with lead time and safety stock considerations

Most existing network design and facility location models have focused on the trade-off between the fixed costs of locating facilities and variable transportation costs between facilities and customers. However, operational performance measures such as service levels and lead times are what motivates customers to bring business to a company and should be considered in the design of a distribution network. While some previous work has considered lead times and safety stocks separately, they are closely related in practice, since safety stocks are often set relative to the distribution of demand over the lead time. In this paper we consider a two-stage supply chain with a production facility that replenishes a single product at retailers. The objective is to locate Distribution Centers (DCs) in the network such that the sum of the location and inventory (pipeline and safety stock) costs is minimized. The replenishment lead time at the DCs depends on the volume of flow through the DC. We require the DCs to carry enough safety stock to maintain the prescribed service levels at the retailers they serve. The explicit modeling of the relationship between the flows in the network, lead times and safety stocks allows us to capture the trade-off between them. We develop a Lagrangian heuristic to obtain near-optimal solutions with reasonable computational requirements for large problem instances.
Near-Field Wireless Sensing of Plastics and Papers Using Frugal Peel-Off Passive Tag

This article presents a novel frugal approach of testing plastics and papers using a near-field microwave sensing technique with a peel-off tag. The proposed sensing technique involves two electrical entities: the sensor, which may be regarded as a reader, and a disposable tag. The reader is a modified design of a gap-coupled microstrip line (GCML) sensor, while the passive tag is a standard double-ring complementary split-ring resonator (CSRR) engraved on a commercially available copper foil using laser printing techniques. A detailed numerical study is presented for the engineered sensing methodology, showing the effect of the sample height, sensing distance, bending angle, and inclination. Empirical formulas associated with the dielectric properties of the sample under test are also given. The errors associated with a possible air gap between the peel-off tag and the sample, as well as the relative positioning of the tag and the reader, are analyzed while also considering the bending of the tag. Finally, the sensor is fabricated on a 1.5-mm-thick Rogers RT5880 laminate, and several standard samples are prepared to experimentally check the validity of the approach. The sensor provides a transmission bandwidth (BW) of 1.9 GHz with a typical insertion loss (IL) of 1 dB and a reflection loss of 20 dB. The tag engraved on the frugal peel-off copper foil is used for sensing various dielectric materials by placing it on planar and curved surfaces. The simulation and measured results are found to be in close agreement. The proposed scheme is found to be reliable and cost-effective also for the testing of microwave substrates. It provides robust results for the wireless sensing of objects located within a range of 10 mm from the reader.
Data‐driven fault‐tolerant control for SISO nonlinear system with unknown sensor fault

This paper studies the adaptive fault‐tolerant control problem for a general nonlinear discrete‐time SISO system with unknown system model and sensor fault. First, utilizing the input‐output (I/O) data, an equivalent full‐form dynamic linearization (FFDL) data model is to be constructed by introducing a pseudo‐gradient vector. Then, to estimate the system's actual output from the sensor measurements corrupted by unknown faults, a nonlinear autoregressive with external input neural network (NARXNN) is employed and well‐trained, by which the compensation of the fault signal can hence be derived indirectly. Based on the optimality criterion, an adaptive fault‐tolerant control (FTC) strategy is therefore proposed, which promises the convergence of tracking error and the boundedness of system signals. The effectiveness of the proposed FTC algorithm is illustrated by simulation results.
The 18‐cm light curves of the luminous radio supernova candidates in Arp 220

We present multi-epoch observations of Arp 220 with the VLBA and focus on the continuum emission from the luminous radio supernovae (RSNe) whose 1.6-GHz light curves are shown. The supernovae seem to be generally stable or only slowly decaying in flux with time, a result which deviates from the model of Type IIn RSNe. Hints of new eruptions confirm that they are indeed new sources and not supernova remnants, which could be several hundred years old. The slow decay of the sources for which monitoring data were available forces us to reconsider the starburst model for Arp 220 and adopt a more modest value of 0.7 yr -1 for the supernova rate based on these new eruptions. The starburst efficiency should also be modified accordingly which gives rise to the issue of an active nucleus once more. The question is raised whether it is the starburst which creates this active nucleus, something which could affect the evolution of starburst galaxies as a group.
An Adaptive Lagrangian-Based Scheme for Nonconvex Composite Optimization

This paper develops a novel adaptive, augmented, Lagrangian-based method to address the comprehensive class of nonsmooth, nonconvex models with a nonlinear, functional composite structure in the objective. The proposed method uses an adaptive mechanism for the update of the feasibility penalizing elements, essentially turning our multiplier type method into a simple alternating minimization procedure based on the augmented Lagrangian function from some iteration onward. This allows us to avoid the restrictive and, until now, mandatory surjectivity-type assumptions on the model. We establish the iteration complexity of the proposed scheme to reach an ε-critical point. Moreover, we prove that the limit point of every bounded sequence generated by a procedure that employs the method with strictly decreasing levels of precision is a critical point of the problem. Our approach provides novel results even in the simpler composite linear model, in which the surjectivity of the linear operator is a baseline assumption. Funding: N. Hallak’s research was partially supported by the Israel Science Foundation [Grant 637/21]. M. Teboulle’s research was partially supported by the Israel Science Foundation [Grants 1844-16 and 2619-20].
Cyber-Security of Embedded IoTs in Smart Homes: Challenges, Requirements, Countermeasures, and Trends

Connected computers and sensors transmit data across the Internet to solve problems and generate new services (IoT). Smart homes use IoT, for example. Smart home technology can monitor temperature, detect smoke, regulate lighting automatically, and install smart locks. It also poses additional security and privacy problems, such as accessing user data through surveillance equipment or false fire alarms. Smart homes are vulnerable to numerous sorts of assaults. This survey emphasizes IoT. We discuss IoT's design, objects, and standards. We also address the tiered Internet of Things framework and smart home security concerns. In this article, researchers examine IoT-based smart home difficulties and offer solutions.
Push and Pull Factors: Contextualising Biological Maturation and Relative Age in Talent Development Systems

In this conceptual paper, we contextualise ongoing attempts to manage challenge dynamics in talent systems in sport. Firstly, we review the broad literature base related to biological maturation, relative age, and the proposed interventions to mitigate effects. We suggest that the relative age effect may be a population level effect, indicative of deeper phenomena, rather than having a direct effect on challenge levels. In contrast, we suggest that biological maturation has a direct effect on challenge at the individual level. Therefore, our main critique of many existing approaches to the management of challenge is a lack of individual nuance and flexibility. We suggest the necessity for talent systems to adopt a more holistic approach, conceptualising biological maturation and relative age within a broader field of “push and pull factors” that impact challenge dynamics in talent development in sport. Finally, we provide practical guidance for talent systems in their approach to relative age and biological maturation, recognising that there is no “gold standard”. Instead, there is a need to recognize the highly individual and contextual nature of these concepts, focusing on strategic coherence through talent systems for the management of selection and development processes.
Electric Wave Propagation on Non-Uniform Coupled Transmission Lines

Abstract : The propagation of electric currents and voltages along a pair of wires over a ground plane is studied. The system is assumed to be non-uniform; I. e. , the self and mutual inductances and capacitances vary along the wires. The existence and uniqueness of an electric wave having prescribed initial values is shown to follow from recent results of the author on symmetric hyperbolic systems of partial differential equations. A construction for this solution is given in the case of a coupler (i. e., a pair of wires which are non-uniform and coupled over a portion of their length only). This coupler problem is reduced to a two-point boundary value problem, and the latter is reduced to a pair of initial value problems, one of which involves a matrix Riccati equation. A novel feature of the work is an "a priori" estimate which guarantees that a solution of the (non-linear) matrix Riccati equation exists on the whole line.
Synthesis, X-Ray, Spectroscopic Characterization, Hirshfeld Surface Analysis, Molecular Docking, and DFT Calculations of a New Series of 3-Hydrazono and 3-Phenylhydrazono Isatin Derivatives

Abstract Two novel N-alkylated isatin derivatives (2–3) were synthesized under phase-transfer catalysis conditions. Their condensation with hydrazine hydrate and phenylhydrazine in refluxing ethanol as solvent generates two series of isatin derivatives (3-hydrazono and 3-phenylhydrazono) (4–7). The structures synthesized are elucidated using UV/Vis, FTIR, 13C-NMR, 1H-NMR, and single crystal X-ray diffraction techniques of 2, 3, and 5. The experimental data were compared with the predicted ones obtained at the B3LYP/6-31G(d,p) level of theory. Relatively, good agreements were found between the calculated and experimental results. The intermolecular contacts in 2, 3, and 5 were investigated through the Hirshfeld surface analysis. The expected inhibitory efficiency of 2, 3, and 5 against cyclooxygenase-2 (COX-2) are investigated by their molecular docking into the binding site of COX-2, which revealed that 2 might have strong inhibition efficacy against COX-2 compared to 3.
Efficient approach to early detection of lithographic hotspots using machine learning systems and pattern matching

Early lithographic hotspot detection has become increasingly important in achieving lithography-friendly designs and manufacturability closure. Fast physical verification tools employing pattern matching or machine learning techniques have emerged as great options for detecting hotspots in the early design stages. In this work, we propose a characterization methodology that provides measurable quantification of a given hotspot detection tool's capability to capture a previously seen or unseen hotspot pattern. Using this methodology, we conduct a side-by-side comparison of two hotspot detection methods-one using pattern matching and the other based on machine learning. The experimental results reveal that machine learning classifiers are capable of predicting unseen samples but may mispredict some of its training samples. On the other hand, pattern matching-based tools exhibit poorer predictive capability but guarantee full and fast detection on all their training samples. Based on these observations, we propose a hybrid detection solution that utilizes both pattern matching and machine learning techniques. Experimental results show that the hybrid solution combines the strengths of both algorithms and delivers improved detection accuracy while sacrificing little runtime efficiency.
Lattice Vibrations in Vanadium

The phonon dispersion curves, frequency spectrum and specific heat of vanadium have been calculated on the basis of the lattice dynamical model of Sharma and Joshi (1963). The frequency distribution has been derived according to Blackman's (1937, 1955) root-sampling technique by the numerical sampling of 192000 frequencies corresponding to 64000 points considered in the first Brillouin zone. This computed frequency distribution has then been used to calculate the lattice specific heat of vanadium. The resulting values of the specific heat have been compared with experimental measurements in terms of the Debye characteristic temperatures.