Miracle-dz/UniFAR-FTUs huggingface dataset:
Recurrence coefficients for discrete orthonormal polynomials and the Painlevé equations

We investigate semi-classical generalizations of the Charlier and Meixner polynomials, which are discrete orthogonal polynomials that satisfy three-term recurrence relations. It is shown that the coefficients in these recurrence relations can be expressed in terms of Wronskians of modified Bessel functions and confluent hypergeometric functions, respectively for the generalized Charlier and generalized Meixner polynomials. These Wronskians arise in the description of special function solutions of the third and fifth Painlevé equations.
Pairwise optimal coupling of multiple random variables

We generalize the optimal coupling theorem to multiple random variables: Given a collection of random variables, it is possible to couple all of them so that any two differ with probability comparable to the total-variation distance between them. In a number of cases we show that the disagreement probability we achieve is the best possible. The proofs of sharpness rely on new results in extremal combinatorics, which may be of independent interest.
Prescribing patterns and pharmacoeconomic analysis of antihypertensive drugs in South Indian population: A cross-sectional study

Background: Global evidence-based recommendations for hypertension management are periodically updated, and ensuring adherence to the guidelines is imperative. Furthermore, the current high prevalence of hypertension effectuates a high health-care cost. Purpose: To evaluate the prescribing patterns of antihypertensive drugs and other factors affecting blood pressure (BP) with the objective of assessing the proportion of patients achieving the target BP and to perform a pharmacoeconomic analysis in a South Indian population. Materials and Methods: In a cross-sectional study, 650 patients previously diagnosed with hypertension and already on treatment with one or more drugs were included. A prospective interview of patients was done using a prevalidated questionnaire on various factors in BP control. Prescribing patterns and pharmacoeconomic analyses, namely, cost acquisition, cost of illness, and cost-effectiveness analyses were carried out. Results: Of 650 subjects, 257 (39.54%) achieved the target BP, while 393 (60.46%) did not. A significant association of age, occupational status, monthly family income, and area of residence in addition to physical activity and diet scores, with achieving target BP was noted. A significantly higher cost of anti-hypertensive drug treatment in achieving target BP (P = 0.02) was observed. Among patients who achieved target BP, 37.35% were on monotherapy and 48.25% on multiple drug therapy compared to 46.31% and 35.62%, respectively, in patients who did not. Average cost-effectiveness ratio were found to be Rs. 20.45 and Rs. 57.27, respectively, for single and multiple drug therapies, with incremental cost-effectiveness of Rs. 194.14 per additional patient treated with multiple free drug combinations. Conclusion: This study identified the anti-hypertensive prescribing pattern and provided insight into the various pharmacoeconomic factors that play a significant role in attaining target BP in the treated population.
Remote Sensing and Machine Learning techniques for acreage estimation of mango (Mangifera indica)

Mango (Mangifera indica) is the most important commercially grown fruit crop in India. Uttar Pradesh, Andhra Pradesh, Karnataka, Bihar, Gujarat and Tamil Nadu are the major producers of mango. It covers around 42% total area accounting for 40% of total production in the country. Hence, development of reliable and timely estimates of area under mango at national level is essential for policymakers and planners for market planning and export. Earlier only survey technologies were used for area estimation which was a time consuming and laborious process. Modern space technology like remote sensing can be used as an alternative. Therefore, a study was carried out for acreage estimation of mango in West Godavari district of Andhra Pradesh using Sentinel 2 satellite data in the year 2017. Acreage estimation of mango was done after the preparation of land use and land cover map. Three supervised classification techniques, viz. Maximum Likelihood Classification (MLC), Support Vector Machine (SVM) and Artificial Neural Network (ANN) were used for land use and land cover map preparation. Support Vector Machine using three different kernel functions, viz. Radial Basis Function (RBF), Sigmoid kernel and Polynomial kernel were used to improve the classification accuracy. SVMRBF was found to be the best classification technique with overall accuracy of 94.44 and kappa coefficient 0.9218. The mango area obtained from the classified satellite image using SVMRBF was 9372.96 ha.
K-theory and logarithmic Hodge-Witt sheaves of formal schemes in characteristic p

We describe the mod $p^r$ pro $K$-groups $\{K_n(A/I^s)/p^r\}_s$ of a regular local $\mathbb F_p$-algebra $A$ modulo powers of a suitable ideal $I$, in terms of logarithmic Hodge-Witt groups, by proving pro analogues of the theorems of Geisser-Levine and Bloch-Kato-Gabber. This is achieved by combining the pro Hochschild-Kostant-Rosenberg theorem in topological cyclic homology with the development of the theory of de Rham-Witt complexes and logarithmic Hodge-Witt sheaves on formal schemes in characteristic $p$. Applications include the following: the infinitesimal part of the weak Lefschetz conjecture for Chow groups; a $p$-adic version of Kato-Saito's conjecture that their Zariski and Nisnevich higher dimensional class groups are isomorphic; continuity results in $K$-theory; and criteria, in terms of integral or torsion \'etale-motivic cycle classes, for algebraic cycles on formal schemes to admit infinitesimal deformations. Moreover, in the case $n=1$, we compare the \'etale cohomology of $W_r\Omega^1_\text{log}$ and the fppf cohomology of $\mathbf\mu_{p^r}$ on a formal scheme, and thus present equivalent conditions for line bundles to deform in terms of their classes in either of these cohomologies.
Immediate Effects of Fine-Motor Training on Coordination and Dexterity of the Non-Dominant Hand in Healthy Adults: A Randomized Controlled Trial

Several studies have demonstrated the beneficial effects of mirror training; however, only a few studies in Eastern countries have investigated fine-motor exercises using chopsticks, which have numerous advantages. We aimed to compare changes in coordination and dexterity of the non-dominant hand in healthy adults after conducting fine-motor training with the dominant hand using a mirror. We divided 100 healthy adults (age: 20–40 years) into experimental and control groups (each n = 50). The experimental group placed the non-dominant hand in a mirror box and indirectly imitated the fine-motor exercises conducted with the dominant hand using chopsticks. The control group performed the task with the non-dominant hand using chopsticks. We conducted the Chopsticks Manipulation Test and the Purdue Pegboard Test to assess the pre- and post-intervention coordination and dexterity of the non-dominant hand. Both groups showed a significant post-intervention improvement in coordination and dexterity (p < 0.01). There was no significant between-group difference in the functional improvement of coordination and dexterity (p > 0.05). Fine-motor training using mirrors and chopsticks significantly improved coordination and dexterity of the non-dominant hand. This training could be used to improve activity in brain regions associated with the non-dominant hand in healthy adults.
Rational Design of a Peptidomimetic Inhibitor of Gelsolin Amyloid Aggregation

Gelsolin amyloidosis (AGel) is characterized by multiple systemic and ophthalmic features resulting from pathological tissue deposition of the gelsolin (GSN) protein. To date, no cure is available for the treatment of any form of AGel. More than ten single-point substitutions in the GSN gene are responsible for the occurrence of the disease and, among them, D187N/Y is the most widespread variant. These substitutions undergo an aberrant proteolytic cascade, producing aggregation-prone peptides of 5 and 8 kDa, containing the Gelsolin Amyloidogenic Core, spanning residues 182–192 (GAC182–192). Following a structure-based approach, we designed and synthesized three novel sequence-specific peptidomimetics (LB-5, LB-6, and LB-7) built on a piperidine-pyrrolidine unnatural amino acid. LB-5 and LB-6, but not LB-7, efficiently inhibit the aggregation of the GAC182–192 amyloidogenic peptides at sub-stoichiometric concentrations. These peptidomimetics resulted also effective in vivo, in a C. elegans-based assay, in counteracting the proteotoxicity of aggregated GAC182–192. These data pave the way to a novel pharmacological strategy against AGel and also validate a toolbox exploitable in other amyloidogenic diseases.
Large random simplicial complexes, I

In this paper we introduce and develop the multi-parameter model of random simplicial complexes with randomness present in all dimensions. Various geometric and topological properties of such random simplicial complexes are characterised by convex domains in the high-dimensional parameter space (rather than by intervals, as in the usual one-parameter models). We find conditions under which a multi-parameter random simplicial complex is connected and simply connected. Besides, we give an intrinsic characterisation of the multi-parameter probability measure. We analyse links of simplexes and intersections of multi-parameter random simplicial complexes and show that they are also multi-parameter random simplicial complexes.
Growth control of GaAs nanowires using pulsed laser deposition with arsenic over-pressure

Using pulsed laser ablation with arsenic over-pressure, the growth conditions for GaAs nanowires have been systematically investigated. The single-crystal structure and geometry of the nanowires have been characterized for various growth conditions. Arsenic over-pressure with As2 molecules was introduced into the system by thermal decomposition of polycrystalline GaAs to control the stoichiometry and shape of the nanowires during growth. GaAs nanowires exhibit a variety of geometries under varying arsenic over-pressures, which can be understood by different growth processes via a vapor–liquid–solid mechanism. Without As2 over-pressure, branched growth of GaAs with uncontrollable size and geometry was observed due to the decomposition of GaAs nanowires, producing metallic Ga which serves as catalysts for the branched growth of GaAs on the nanowire surfaces. Under optimal As2 over-pressure, single-crystal GaAs nanowires with uniform diameter, small diameter distribution, length over 20 µm and thin surface oxide layer were obtained and used for I–V characterization.
Polymers for 3D printing in biomedical engineering applications

Additive manufacturing, famous as 3D printing, is a cutting-edge technology of the manufacturing process. Initially, the application of additive manufacturing was restricted to prototyping. Still, the advancement of technology and a wide choice of material for 3D printing made it affordable and applicable for many manufacturing industries. Presently, 3D printing is accurate, automated, affordable and thoroughly customizable for batch and continuous manufacturing of complex geometrical structures. The application of 3D printing in biomedical engineering is growing well. Multiple choices of 3D printing technology and a wide range of biomaterial provide a healthy platform for biomedical application. In this study, principles of additive manufacturing technologies, printing methods, and suitable material has been discussed to provide depth overview of the current scenario of 3D printing and provide a glimpse of the possible future of 3D printing.
An Erbium-Doped EDFA Amplifier Pump with a 1550-Nm Pumped Erbium-Doped Fibre

To take full use of the large bandwidth given by fibre optics and the flexibility afforded by wireless broadcasting on a widespread scale, RoF -based optical-wireless networks are widely regarded as the most important approach for improving capability, coverage, bandwidth, and mobility. WDM-RoF-PON architectures are described and demonstrated in this document. In order to verify the viability of the associated designs, a number of approaches including injection locking, direct/external modulation, re-modulation, and homodyne detection were used. The goal of this study is to create a WDM-RoF -PON using a reflective semiconductor optical amplifier (RSOA) to transmit 2.5 Gb/s baseband (BB) and 1.25 Gb/s wireless signalling downlink and 1 Gb/s (BB) signal in uplink over a 25 km single mode fibre (SMF) and wireless downlink signal over a 25 km SMF and 5.2 m free-spread fibre (FSF) link. This research also aims Downlink wired and remote communications may be successfully sent using both the confused light infusion plan and the twofold sideband optical transporter concealment (DSBCS) approach. In order to reuse the downlink carrier for uplink transmission, RSOA is employed.
Trustworthy Announcement Dissemination Scheme With Blockchain-Assisted Vehicular Cloud

Vehicular ad hoc network (VANET) is an emerging technology that can significantly improve the efficiency of transportation systems and mitigate traffic accidents by exchanging traffic-related messages or announcements. Nevertheless, there has not been a consensus on how to generate, distribute, and validate trustworthy announcements in such an untrusted wireless environment. Security and privacy, inspiration mechanism, and resource integration are significant challenges for announcement generation and dissemination. In this paper, a secure and trustworthy announcement dissemination scheme is realized for location-based service (LBS) application in VANET. A blockchain-assisted vehicular cloud (VC) architecture is proposed to harvest underutilized heterogeneous resources of vehicles participating in VANET. Moreover, the technologies of blockchain and smart contract are adopted to classify vehicles into different levels automatically by bidding for bonuses. What’s more, vehicles can generate trustworthy announcements with the help of neighbor vehicles by adopting the technology of threshold signature. Meanwhile, the reputation of announcements is evaluated for trust management. Formal security analysis shows that the proposed scheme satisfies fundamental security and privacy requirements in VANET. Experimental results show that the proposed scheme is robust and efficient.
Carburization Kinetics of Zircalloy-4 and Its Implication for Small Modular Reactor Performance

Carburization of cladding materials has long been a concern for the nuclear industry and has led to the restricted use of high-thermal conductivity fuels such as uranium carbides. With the rise of small modular reactors (SMRs) that frequently implement a graphite core-block, carburization of reactor components is once more in the foreground as a potential failure mechanism. To ensure commercial viability for SMRs, neutron-friendly cladding materials such as Zr-based alloys are required. In this work, the carburization kinetics of Zircaloy-4 (Zry-4), for the temperature range 1073–1673 K (covering typical operating temperatures and off-normal scenarios) are established. The following Arrhenius relationship for the parabolic constant describing ZrC growth is derived: Kp (in μm2/s) = 609.35 exp(−1.505 × 105/RT)). Overall, the ZrC growth is sluggish below 1473 K which is within the operational temperature range of SMRs. In all cases the ZrC that forms from solid state reaction is hypo-stoichiometric, as confirmed through XRD. The hardness and elastic modulus of carburized Zry-4 are also examined and it is shown that despite the formation of a ZrC layer, C ingress in the Zry-4 bulk does not impact the mechanical response after carburization at 1073 K and 1473 K for 96 h.
A different look at controllability

We explore further controllability problems through a standard least square approach. By setting up a suitable error functional $E$, and putting $m(\ge0)$ for the infimum, we interpret approximate controllability by asking $m=0$, while exact controllability corresponds, in addition, to demanding that $m$ is attained. We also provide a condition, formulated entirely in terms of the error $E$, which turns out to be equivalent to the unique continuation property, and to approximate controllability. Though we restrict attention here to the 1D, homogeneous heat equation to explain the main ideas, they can be extended in a similar way to many other scenarios some of which have already been explored numerically, due to the flexibility of the procedure for the numerical approximation.
SOC Estimation for a Li-ion battery based on the AEKF optimized by GA-BP Neural Network

The state of charge (SOC) displays the remaining power of the vehicle battery, its accurate estimation benefits the protection of the battery and determines the adjustment of the operating state. In this paper, a genetic algorithm-optimized back propagation neural network (GA-BP) for optimization of the Adaptive Extended Kalman Filter (AEKF) is proposed to estimate the SOC of li-ion batteries. The 2-order RC equivalent model is established. Based on the 2-order RC equivalent model and Hybrid Pulse Power Characterization (HPPC), parameters of the NCR18650B lithium battery is identified. Preliminarily estimated SOC, using EKF and battery parameters. In order to improve the accuracy of SOC estimation, a BP neural network optimization method based on genetic algorithm (GA-BP) is proposed. The AEKF is obtained by optimizing the EKF through an adaptive sampling strategy. The SOC estimated by GA-BP is converted into the input of the AEKF, which further improves the accuracy of the vehicle battery SOC estimation. The simulation and experimental results show that, compared with EKF, the maximum SOC estimation error of AEKF optimized by GA-BP neural network is reduced from 2.3% to 0.7%, and the average SOC estimation error is reduced from 1.28% to 0.41%. The latter has better convergence and robustness.
ournal of Statistical Mechanics: J Theory and Experiment Integrable deformations of the XXZ spin chain

We consider integrable deformations of the XXZ spin chain for periodic and open boundary conditions. In particular, we classify all long-range deformations and study their impact on the spectrum. As compared to the XXX case, we have the z -spin at our disposal, which induces two additional deformations: the short-range magnetic twist and a new long-range momentum-dependent twist.
Nonlinear Effects in NOMA-OFDM Systems: Analytical Signal Characterization and Receiver Design

Non orthogonal multiple access (NOMA) is being considered a key technology for future communications. In this paper, we provide an analytical characterization of downlink NOMA orthogonal frequency-division multiplexing (OFDM) in presence of nonlinear effects associated to a high power amplifier (HPA) modeled as a memoryless polynomial. Taking advantage of the Bussgang approximation and intermodulation products (IMPs) tools, we present a generalized framework to characterize the nonlinearity for digital NOMA-OFDM systems with Nyquist-sampled signals and oversampled signals. An accurate estimation for the power spectral density (PSD) and signal-to-distortion ratio (SDR) for each user is developed and discussed. Moreover, we introduce a joint iterative approach for distortion compensation and interference cancellation suitable for scenarios with strong nonlinear effects. Our performance results indicate that the proposed technique allows significant bit error rate (BER) and complexity improvements, when compared to conventional schemes.
Spectral analysis of a massless charged scalar field with spacial cut-off

The quantum system of a massless charged scalar field with a self-interaction is investigated. By introducing a spacial cut-off function, the Hamiltonian of the system is realized as a linear operator on a boson Fock space. It is proven that the Hamiltonian strongly commutes with the total charge operator. This fact implies that the state space of the charged scalar field is decomposed into the infinite direct sum of fixed total charge spaces. Moreover, under certain conditions, the Hamiltonian is bounded below, self-adjoint and has a ground ground state for an arbitrarily coupling constant. A relation between the total charge of the ground state and a number operator bound is also revealed.
Thinning and multilevel Monte Carlo methods for piecewise deterministic (Markov) processes with an application to a stochastic Morris–Lecar model

Abstract In the first part of this paper we study approximations of trajectories of piecewise deterministic processes (PDPs) when the flow is not given explicitly by the thinning method. We also establish a strong error estimate for PDPs as well as a weak error expansion for piecewise deterministic Markov processes (PDMPs). These estimates are the building blocks of the multilevel Monte Carlo (MLMC) method, which we study in the second part. The coupling required by the MLMC is based on the thinning procedure. In the third part we apply these results to a two-dimensional Morris–Lecar model with stochastic ion channels. In the range of our simulations the MLMC estimator outperforms classical Monte Carlo.
MALIBOO: When Machine Learning meets Bayesian Optimization

Bayesian optimization (BO) is an efficient method for finding optimal cloud computing configurations for several types of applications. On the other hand, Machine Learning (ML) methods can provide useful knowledge about the application at hand thanks to their predicting capabilities. In this paper, we propose a hybrid algorithm that is based on BO and integrates elements from ML techniques, to find the optimal configuration of time-constrained recurring jobs executed in cloud environments. The algorithm is tested by considering edge computing and Apache Spark big data applications. The results we achieve show that our approach reduces the amount of unfeasible executions up to 2-3 times with respect to state-of-the-art techniques.
Attractors for Damped Semilinear Wave Equations with Singularly Perturbed Acoustic Boundary Conditions

Under consideration is the damped semilinear wave equation \[ u_{tt}+u_t-\Delta u+u+f(u)=0 \] in a bounded domain $\Omega$ in $\mathbb{R}^3$ subject to an acoustic boundary condition with a singular perturbation, which we term "massless acoustic perturbation," \[ \ep\delta_{tt}+\delta_t+\delta = -u_t\quad\text{for}\quad \ep\in[0,1]. \] By adapting earlier work by S. Frigeri, we prove the existence of a family of global attractors for each $\ep\in[0,1]$. We also establish the optimal regularity for the global attractors, as well as the existence of an exponential attractor, for each $\ep\in[0,1]. $ The later result insures the global attractors possess finite (fractal) dimension, however, we cannot yet guarantee that this dimension is independent of the perturbation parameter $\ep. $ The family of global attractors are upper-semicontinuous with respect to the perturbation parameter $\ep$, a result which follows by an application of a new abstract result also contained in this article. Finally, we show that it is possible to obtain the global attractors using weaker assumptions on the nonlinear term $f$, however, in that case, the optimal regularity, the finite dimensionality, and the upper-semicontinuity of the global attractors does not necessarily hold.