bluuebunny/crossref_metadata_2025 huggingface dataset:
Penetration and Cratering of Steel Target by Jets from Titanium Alloy Shaped Charge Liners
Authors: Gao Dacheng , Li Wenbin , Yao Wenjin , Zhang Kebin , Li Yiming , Song Ping , Pu Bo
Published: July 2022

In order to enlarge the crater diameter of shaped charge jet penetration into steel targets, this paper investigates the penetration and cratering characteristics of steel targets by shaped charge jets from titanium alloy liners. Titanium alloy shaped charge liners are prepared separately with mechanical processing and selective laser melting (SLM), and pulsed X-ray radiography is used to identify jet formation characteristics. Jet formation is numerically simulated by AUTODYN-3D, and steel target penetration tests are carried out at a short jet stand-off distance. The results show that AUTODYN-3D can realistically simulate jet formation from titanium alloy liners and that the SLM-processed liner exhibits better penetration performance than the mechanically processed liner. The existing cratering formula of jet penetration is modified to make it consistent with the aperture variations of jet penetration from titanium alloy-lined shaped charges at a short stand-off distance. The findings of this study are expected to provide technical and theoretical support for research on the penetration characteristics of the jets from titanium alloy-lined shaped charges.
New Chalcogenide Glass-Ceramics Based on Ge-Zn-Se for IR Applications
Authors: Velea Alin , Sava Florinel , Badica Petre , Burdusel Mihail , Mihai Claudia , Galca Aurelian-Catalin , Matei Elena , Buruiana Angel-Theodor , El Khouja Outman , Calvez Laurent
Published: July 2022

The consumer market requests infrared (IR) optical components, made of relatively abundant and environmentally friendly materials, to be integrated or attached to smartphones. For this purpose, three new chalcogenides samples, namely Ge23.3Zn30.0Se46.7 (d_GZSe-1), Ge26.7Zn20.0Se53.3 (d_GZSe-2) and Ba4.0Ge12.0Zn17.0Se59.0I8.0 (d_GZSe-3) were obtained by mechanical alloying and processed by spark plasma sintering into dense bulk disks. Obtaining a completely amorphous and homogeneous material proved to be difficult. d_GZSe-2 and d_GZSe-3 are glass-ceramics with the amount of the amorphous phase being 19.7 and 51.4 wt. %, while d_GZSe-1 is fully polycrystalline. Doping with barium and iodine preserves the amorphous phase formed by milling and lowers the sintering temperature from 350 °C to 200 °C. The main crystalline phase in all of the prepared samples is cubic ZnSe or cubic Zn0.5Ge0.25Se, while in d_GZSe-3 the amorphous phase contains GeSe4 clusters. The color of the first two sintered samples is black (the band gap values are 0.42 and 0.79 eV), while d_GZSe-3 is red (Eg is 1.37 eV) and is transparent in IR domain. These results are promising for future research in IR materials and thin films.
Efficient Activation of Peroxymonosulfate by Cobalt Supported Used Resin Based Carbon Ball Catalyst for the Degradation of Ibuprofen
Authors: Zhou Guangzhen , Xu Yanhua , Zhang Xiao , Sun Yongjun , Wang Cheng , Yu Peng
Published: July 2022

The extensive use of ibuprofen (IBU) and other pharmaceuticals and personal care products (PPCPs) causes them widely to exist in nature and be frequently detected in water bodies. Advanced catalytic oxidation processes (AOPs) are often used as an efficient way to degrade them, and the research on heterogeneous catalysts has become a hot spot in the field of AOPs. Among transitional metal-based catalysts, metal cobalt has been proved to be an effective element in activating peroxymonosulfate (PMS) to produce strong oxidizing components. In this study, the used D001 resin served as the matrix material and through simple impregnation and calcination, cobalt was successfully fixed on the carbon ball in the form of cobalt sulfide. When the catalyst was used to activate persulfate to degrade IBU, it was found that under certain reaction conditions, the degradation rate in one hour could exceed 70%, which was far higher than that of PMS and resin carbon balls alone. Here, we discussed the effects of catalyst loading, PMS concentration, pH value and temperature on IBU degradation. Through quenching experiments, it was found that SO4− and ·OH played a major role in the degradation process. The material has the advantages of simple preparation, low cost and convenient recovery, as well as realizing the purpose of reuse and degrading organic pollutants efficiently.
Vibration Analysis and Active Control of Rotor Shaft in Magnetically Suspended Air-Blower
Authors: Zheng Lingbo , Nie Wansheng , Xiang Biao
Published: July 2022

An air-blower with active magnetic bearings could improve working efficiency and reduce energy consumption by avoiding contact between the rotor shaft and the stator part. The structure and prototype of a magnetically suspended air-blower are herein introduced, and the force models of active magnetic bearings developed. Furthermore, the dynamic models of a rotor shaft with unbalance terms were established to investigate the vibration characteristics of the magnetically suspended air-blower. The vibration characteristics of the rotor shaft with unbalance terms were analyzed, and the complex-field cross-feedback control was designed to suppress the vibration amplitude. Finally, experiments were conducted to verify the theoretical models, and the results indicated that the vibration amplitude of the rotor shaft with unbalance terms could be intensified by the rotating frequency, and the nutation vibration was reduced by 50% through increasing the high-frequency nutation coefficient of the complex-field cross-feedback control model. The results indicated that the vibration analysis of the rotor shaft was meaningful to the design and control of the magnetically suspended air-blower.
Virtual Neuromuscular Control for Robotic Ankle Exoskeleton Standing Balance
Authors: Yin Kaiyang , Jin Yantao , Du Haojie , Xue Yaxu , Li Pengfei , Ma Zhengsen
Published: July 2022

The exoskeleton is often regarded as a tool for rehabilitation and assistance of human movement. The control schemes were conventionally implemented by developing accurate physical and kinematic models, which often lack robustness to external variational disturbing forces. This paper presents a virtual neuromuscular control for robotic ankle exoskeleton standing balance. The robustness of the proposed method was improved by applying a specific virtual neuromuscular model to estimate the desired ankle torques for ankle exoskeleton standing balance control. In specialty, the proposed control method has two key components, including musculoskeletal mechanics and neural control. A simple version of the ankle exoskeleton was designed, and three sets of comparative experiments were carried out. The experimentation results demonstrated that the proposed virtual neuromuscular control could effectively reduce the wearer’s lower limb muscle activation, and improve the robustness of the different external disturbances.
An End-to-End Deep Learning Method for Dynamic Job Shop Scheduling Problem
Authors: Chen Shifan , Huang Zuyi , Guo Hongfei
Published: July 2022

Job shop scheduling problem (JSSP) is essential in the production, which can significantly improve production efficiency. Dynamic events such as machine breakdown and job rework frequently occur in smart manufacturing, making the dynamic job shop scheduling problem (DJSSP) methods urgently needed. Existing rule-based and meta-heuristic methods cannot cope with dynamic events in DJSSPs of different sizes in real time. This paper proposes an end-to-end transformer-based deep learning method named spatial pyramid pooling-based transformer (SPP-Transformer), which shows strong generalizability and can be applied to different-sized DJSSPs. The feature extraction module extracts the production environment features that are further compressed into fixed-length vectors by the feature compression module. Then, the action selection module selects the simple priority rule in real time. The experimental results show that the makespan of SPP-Transformer is 11.67% smaller than the average makespan of dispatching rules, meta-heuristic methods, and RL methods, proving that SPP-Transformer realizes effective dynamic scheduling without training different models for different DJSSPs. To the best of our knowledge, SPP-Transformer is the first application of an end-to-end transformer in DJSSP, which not only improves the productivity of industrial scheduling but also provides a paradigm for future research on deep learning in DJSSP.
An IPMSM Control Structure Based on a Model Reference Adaptive Algorithm
Authors: Guo Tong , Chen Yongjie , Chen Qihuai , Lin Tianliang , Ren Haoling
Published: July 2022

Traditional construction machinery has the disadvantages of low energy efficiency and poor emissions, which do not meet the requirements of environmentally friendly industrial development. Electric construction machinery has attracted more and more attention because of its advantages of zero emissions and high energy efficiency, which are considered to be important factors in the future development of construction machinery. Preliminary attempts to introduce electric motors into construction machinery usually only adopt the motor for simulating the working mode of the engine, with it providing power for the system. Because the output power of the motor needs to be matched with the actual load through the transmission of the hydraulic torque converter, it is difficult to maximize the advantages of high energy efficiency for the electric drive. This paper studied the direct drive technology within electric construction machinery and presents a model reference adaptive algorithm (MRAA) based on maximum torque per ampere (MTPA)-vector control of an internal permanent magnet synchronous motor (IPMSM). The reference motor model was established, and the real-time dynamic reference value of the motor was obtained based on a model with the motor voltage and current as inputs. Simulations based on MATLAB/Simulink verified the feasibility of this control method. The results indicate that the MRAA can identify the motor flux linkage value and the d-q axis inductance within 50 ms in real time, with the error controlled within 2%. Additionally, when the motor operates at low speed, compared with the traditional MTPA algorithm under fixed-parameter control, the starting torque ripple of the IPMSM control method based on reference model adaptation was reduced to 23.8%, which proves that the MRAA can achieve good low-speed response characteristics and stability.
Study on the Temperature Rise Characteristics of Successive Clutch Shifting Considering the Disengaged Friction Pair Gaps
Authors: Zheng Liangjie , Ma Biao , Chen Man , Yu Liang , Wang Qian , Xue Jiaqi
Published: July 2022

The clutch temperature rise characteristics in successive shifting conditions are crucial to its thermal stability and thermal safety. In the present paper, a comprehensive numerical model is proposed to investigate the temperature change of separator discs during successive shifting with the consideration of convection heat transfer in disengaged friction pair gaps, which is validated by repeated shifting experiments on the SAE#2 test bench. Since the second separator disc near the piston has the widest disengaged gaps and double-sided heat input, its temperature rise and temperature drop are the highest. The temperature rise gradually equals the temperature drop with the increasing working cycle, then the maximum clutch temperature no longer increases. The longer the shifting interval, the better the heat dissipation is, thus the lower the accumulated temperature rise. Moreover, the increasing lubrication oil temperature reduces the convection heat transfer and increases the temperature rise in an engaging process, but the accumulated temperature rise does not increase due to the widened friction pair gaps. This paper can obtain the temperature rise characteristics of a wet multi-disc clutch concerning its disengaged gaps during successive shifting, which is a promising candidate for investigating its overall performance.
Stiffness-Tuneable Segment for Continuum Soft Robots with Vertebrae
Authors: Liu Zhipeng , Xu Linsen , Liang Xingcan , Liu Jinfu
Published: July 2022

In addition to high compliance to unstructured environments, soft robots can be further improved to gain the advantages of rigid robots by increasing stiffness. Indeed, realizing the adjustable stiffness of soft continuum robots can provide safer interactions with objects and greatly expand their application range. To address the above situation, we propose a tubular stiffening segment based on layer jamming. It can temporarily increase the stiffness of the soft robot in a desired configuration. Furthermore, we also present a spine-inspired soft robot that can provide support in tubular segments to prevent buckling. Theoretical analysis was conducted to predict the stiffness variation of the robot at different vacuum levels. Finally, we integrated the spine-inspired soft robot and tubular stiffening segment to obtain the tuneable-stiffness soft continuum robot (TSCR). Experimental tests were performed to evaluate the robot’s shape control and stiffness tuning effectiveness. Experimental results showed that the bending stiffness of the initial TSCR increased by more than 15× at 0°, 30× at 90°, and 60× in compressive stiffness.
Thruster Fault Diagnostics and Fault Tolerant Control for Autonomous Underwater Vehicle with Ocean Currents
Authors: Tian Qunhong , Wang Tao , Liu Bing , Ran Guangtao
Published: July 2022

Autonomous underwater vehicle (AUV) is one of the most important exploration tools in the ocean underwater environment, whose movement is realized by the underwater thrusters, however, the thruster fault happens frequently in engineering practice. Ocean currents perturbations could produce noise for thruster fault diagnosis, in order to solve the thruster fault diagnostics, a possibilistic fuzzy C-means (PFCM) algorithm is proposed to realize the fault classification in this paper. On the basis of the results of fault diagnostics, a fuzzy control strategy is proposed to solve the fault tolerant control for AUV. Considering the uncertainty of ocean currents, it proposes a min-max robust optimization problem to optimize the fuzzy controller, which is solved by a cooperative particle swarm optimization (CPSO) algorithm. Simulation and underwater experiments are used to verify the accuracy and feasibility of the proposed method of thruster fault diagnostics and fault tolerant control.
An Application of Miller–Ross-Type Poisson Distribution on Certain Subclasses of Bi-Univalent Functions Subordinate to Gegenbauer Polynomials
Authors: Amourah Ala , Frasin Basem Aref , Seoudy Tamer M.
Published: July 2022

The Miller–Ross-type Poisson distribution is an important model for plenty of real-world applications. In the present analysis, we study and introduce a new class of bi-univalent functions defined by means of Gegenbauer polynomials with a Miller–Ross-type Poisson distribution series. For functions in each of these bi-univalent function classes, we have derived and explored estimates of the Taylor coefficients a2 and a3 and Fekete-Szegö functional problems for functions belonging to these new subclasses.
Uniform Asymptotics of Solutions of Second-Order Differential Equations with Meromorphic Coefficients in a Neighborhood of Singular Points and Their Applications
Authors: Korovina Maria V. , Matevossian Hovik A.
Published: July 2022

In this paper, we consider the problem of obtaining the asymptotics of solutions of differential operators in a neighborhood of an irregular singular point. More precisely, we construct uniform asymptotics for solutions of linear differential equations with second-order meromorphic coefficients in a neighborhood of a singular point and apply the results obtained to the equations of mathematical physics. The main results related to the construction of uniform asymptotics are obtained using resurgent analysis methods applied to differential equations with irregular singularities. These results allow us to construct asymptotics for any second-order equations with meromorphic coefficients—that is, with an arbitrary order of degeneracy. This also allows one to determine the type of a singular point and highlight the cases where the point is non-singular or regular.
Indirect Neural-Enhanced Integral Sliding Mode Control for Finite-Time Fault-Tolerant Attitude Tracking of Spacecraft
Authors: Yao Qijia , Jahanshahi Hadi , Bekiros Stelios , Mihalache Sanda Florentina , Alotaibi Naif D.
Published: July 2022

In this article, a neural integral sliding mode control strategy is presented for the finite-time fault-tolerant attitude tracking of rigid spacecraft subject to unknown inertia and disturbances. First, an integral sliding mode controller was developed by originally constructing a novel integral sliding mode surface to avoid the singularity problem. Then, the neural network (NN) was embedded into the integral sliding mode controller to compensate the lumped uncertainty and replace the robust switching term. In this way, the chattering phenomenon was significantly suppressed. Particularly, the mechanism of indirect neural approximation was introduced through inequality relaxation. Benefiting from this design, only a single learning parameter was required to be adjusted online, and the computation burden of the proposed controller was extremely reduced. The stability argument showed that the proposed controller could guarantee that the attitude and angular velocity tracking errors were regulated to the minor residual sets around zero in a finite time. It was noteworthy that the proposed controller was not only strongly robust against unknown inertia and disturbances, but also highly insensitive to actuator faults. Finally, the effectiveness and advantages of the proposed control strategy were validated using simulations and comparisons.
A Mathematical Modeling Approach of Target Damage Strategy on the Intersection Confrontation
Authors: Li Hanshan , Zhang Xiaoqian , Chen Jingxin
Published: July 2022

The efficiency of target damage is to measure the effect of projectile attacks. Because there is antagonism at the intersection of projectiles and targets, it is very difficult to establish scientific damage assessment strategy model and a numerical calculation method. To scientifically evaluate the target damage effect when the projectile attacks the aircraft target, this paper introduces a game confrontation mechanism and proposes a numerical calculation method of aircraft target damage game strategy under the intersection confrontation. According to the theory of two-person non-cooperative games, the projectile is regarded as one of the players in the confrontation damage game, and the aircraft target is regarded as the other player. The damage gain model and gain function of the intersection confrontation of both sides are established. The effective expectation function and the minimum and maximum theorem are used to obtain the optimal Nash equilibrium solution of the game matrix strategy, and the Nash equilibrium point of the strategy space set is derived. Through calculation and comparative analysis, the results show that the optimal gain degree composed of the damage strategy selected by both the projectile and aircraft target under the Nash equilibrium solution brings the greatest gain. The proposed hybrid game strategy of damage assessment can be an effective reference for air combat decision making in the state of intersection confrontation.
An Optimized Decision Support Model for COVID-19 Diagnostics Based on Complex Fuzzy Hypersoft Mapping
Authors: Saeed Muhammad , Ahsan Muhammad , Saeed Muhammad Haris , Rahman Atiqe Ur , Mehmood Asad , Mohammed Mazin Abed , Jaber Mustafa Musa , Damaševičius Robertas
Published: July 2022

COVID-19 has shaken the entire world economy and affected millions of people in a brief period. COVID-19 has numerous overlapping symptoms with other upper respiratory conditions, making it hard for diagnosticians to diagnose correctly. Several mathematical models have been presented for its diagnosis and treatment. This article delivers a mathematical framework based on a novel agile fuzzy-like arrangement, namely, the complex fuzzy hypersoft (CFHS) set, which is a formation of the complex fuzzy (CF) set and the hypersoft set (an extension of soft set). First, the elementary theory of CFHS is developed, which considers the amplitude term (A-term) and the phase term (P-term) of the complex numbers simultaneously to tackle uncertainty, ambivalence, and mediocrity of data. In two components, this new fuzzy-like hybrid theory is versatile. First, it provides access to a broad spectrum of membership function values by broadening them to the unit circle on an Argand plane and incorporating an additional term, the P-term, to accommodate the data’s periodic nature. Second, it categorizes the distinct attribute into corresponding sub-valued sets for better understanding. The CFHS set and CFHS-mapping with its inverse mapping (INM) can manage such issues. Our proposed framework is validated by a study establishing a link between COVID-19 symptoms and medicines. For the COVID-19 types, a table is constructed relying on the fuzzy interval of [0,1]. The computation is based on CFHS-mapping, which identifies the disease and selects the optimum medication correctly. Furthermore, a generalized CFHS-mapping is provided, which can help a specialist extract the patient’s health record and predict how long it will take to overcome the infection.
Inferences of the Multicomponent Stress–Strength Reliability for Burr XII Distributions
Authors: Lio Yuhlong , Tsai Tzong-Ru , Wang Liang , Cecilio Tejada Ignacio Pascual
Published: July 2022

Multicomponent stress–strength reliability (MSR) is explored for the system with Burr XII distributed components under Type-II censoring. When the distributions of strength and stress variables have Burr XII distributions with common or unequal inner shape parameters, the existence and uniqueness of the maximum likelihood estimators are investigated and established. The associated approximate confidence intervals are obtained by using the asymptotic normal distribution theory along with the delta method and parametric bootstrap procedure, respectively. Moreover, alternative generalized pivotal quantities-based point and confidence interval estimators are developed. Additionally, a likelihood ratio test is presented to diagnose the equivalence of both inner shape parameters or not. Conclusively, Monte Carlo simulations and real data analysis are conducted for illustration.
Preface to the Special Issue “Natural Language Processing (NLP) and Machine Learning (ML)—Theory and Applications”
Authors: Hristea Florentina , Caragea Cornelia
Published: July 2022

Natural language processing (NLP) is one of the most important technologies in use today, especially due to the large and growing amount of online text, which needs to be understood in order to fully ascertain its enormous value [...]
On the Throughput of the Common Target Area for Robotic Swarm Strategies
Authors: dos Passos Yuri Tavares , Duquesne Xavier , Marcolino Leandro Soriano
Published: July 2022

A robotic swarm may encounter traffic congestion when many robots simultaneously attempt to reach the same area. This work proposes two measures for evaluating the access efficiency of a common target area as the number of robots in the swarm rises: the maximum target area throughput and its maximum asymptotic throughput. Both are always finite as the number of robots grows, in contrast to the arrival time at the target per number of robots that tends to infinity. Using them, one can analytically compare the effectiveness of different algorithms. In particular, three different theoretical strategies proposed and formally evaluated for reaching a circular target area: (i) forming parallel queues towards the target area, (ii) forming a hexagonal packing through a corridor going to the target, and (iii) making multiple curved trajectories towards the boundary of the target area. The maximum throughput and the maximum asymptotic throughput (or bounds for it) for these strategies are calculated, and these results are corroborated by simulations. The key contribution is not the proposal of new algorithms to alleviate congestion but a fundamental theoretical study of the congestion problem in swarm robotics when the target area is shared.
Mathematical Model and Numerical Simulation Study of the Mining Area with Multiple Air Leakage Paths
Authors: Zhang Jiuling , Ruan Gaoyang , Bai Yang , Ning Tao
Published: July 2022

The natural fire in the mining area is the main source of mine fires, and the distribution of spontaneous combustion “three zones” is a key issue in mine fire prevention and suppression. In order to study the change law of spontaneous combustion “three zones” in the mining area with multiple air leakage paths, a segmented numerical simulation method is proposed. In order to consider the common influence of various factors, we firstly establish the coupled model of oxygen consumption rate of coal relics, the regional fluidity model of the porous medium and the three-dimensional distribution model of void rate in the mining area. Then, based on this, the corresponding conditions of air leakage speed, air leakage location and oxygen concentration are set in each stage of numerical simulation. The mathematical model shows that: the oxygen consumption rate of coal shows an approximate exponential growth trend with the increase in temperature, which is proportional to the original oxygen concentration; the void rate of the mining area shows a logarithmic distribution with a tendency of “double hump” proportional coupling. The numerical simulation results show that: the width of the “oxidation zone” decreases gradually along the tendency when there is only air leakage from the working face; the smaller airflow and lower oxygen concentration in the overlying mining area will increase the width of the “oxidation zone” in the coverage area; air leakage from the shelf road will form an “oxidation zone” near the entrance of the shelf road. The leakage of air from the shelf road will form an “oxidized zone” near the entrance of the shelf road; the leakage of air from the adjacent mining area will increase the width of the overall “dispersal zone” and “oxidized zone” due to the larger air flow and higher oxygen concentration. The comparison with the monitoring data of the downhole bundle tube verifies the rationality of the mathematical model and the accuracy of the numerical simulation results.
Service Level Constrained Distribution-Free Newsvendor Problem with Balking Penalty
Authors: Lee Yongho , Cheong Taesu
Published: July 2022

This study extends the newsvendor model to address customer balking and its penalty under service-level constraints. The model designed in this study determines the optimal order quantity to derive the maximum expected profit when a customer is reluctant to buy a product and the available inventory falls below a certain threshold. In addition, the service level is introduced into the procedure to determine the optimal order quantity, thus facilitating the process. Under these circumstances, we also propose a corresponding distribution-free model to determine tight lower bounds on expected profits under the worst-case scenario. To quantitatively evaluate our model’s performance, we compared profits based on the presence or absence of demand distribution, and demonstrated the effect of varying balking penalty costs and probabilities. Introducing a practical service level that can be used as a trade-off tool to help determine reasonable estimates and profitable decisions is beneficial when determining order quantity by comparing goodwill and holding costs.
Neural Network-Based Approximation Model for Perturbed Orbit Rendezvous
Authors: Huang Anyi , Wu Shenggang
Published: July 2022

An approximation of orbit rendezvous is usually used in the global optimization of multi-target rendezvous missions, which can greatly affect the efficiency of optimization process. A fast neural network-based surrogate model is proposed to approximate the optimal velocity increment of perturbed orbit rendezvous in low Earth orbits. According to a dynamic analysis, the initial and target orbits together with the flight time are transformed into a nine-dimensional normalized vector that is used as the input layer of the neural network. An existing approximation method is introduced to quickly generate the training data. In simulations, different numbers of layer nodes and hidden layers are tested to choose the best parameters. The proposed neural network model demonstrates high precision and high efficiency compared with previous approximation methods and neural network models. The mean relative error is less than 1%. Finally, a case of an optimization of a multi-target rendezvous mission is tested to prove the potential application of the neural network model.
Magnetorheological Fluid of High-Speed Unsteady Flow in a Narrow-Long Gap: An Unsteady Numerical Model and Analysis
Authors: Zheng Pengfei , Hou Baolin , Zou Mingsong
Published: July 2022

To investigate the unsteady flow field generated by magnetorheological (MR) fluid of a high-speed unsteady laminar boundary layer flow in a narrow-long gap of the magnetorheological absorber (MRA), a new unsteady numerical model is proposed. The gap has magnetic-field-activated and inactivated regions, with MR fluid flowing as bi-viscous (non-Newtonian) and Newtonian fluid. The unsteady flow field is described by the unsteady incompressible governing partial differential equation (PDE) and initial-boundary conditions with the moving boundary. The space-time solution domain is discretized using the finite difference method, and the governing PDE is transformed into implicit partial difference equations. The volume flow rate function is constructed to solve numerical solutions of pressure gradient and fluid velocity based on mass conservation, the continuity equation, and the bisection method. The accuracy of unsteady numerical model is validated by the experiment data. The results show that the fluid acceleration profiles along the gap’s height are non-uniform distribution. Further, the volume flow rate and excitation current has a significant impact on the dynamic distribution of fluid velocity profiles, and the moving boundary makes the flow field asymmetric about the central plane. Furthermore, as the transition stress increases, the thickness of the pre-yield region in the activated region increases. There is also a transition flow phenomenon in the activated region as the volume flow rate increases. Finally, the unsteady numerical model has good stability and convergence.
Leveraging Geographically Distributed Data for Influenza and SARS-CoV-2 Non-Parametric Forecasting
Authors: Boullosa Pablo , Garea Adrián , Area Iván , Nieto Juan J. , Mira Jorge
Published: July 2022

The evolution of some epidemics, such as influenza, demonstrates common patterns both in different regions and from year to year. On the contrary, epidemics such as the novel COVID-19 show quite heterogeneous dynamics and are extremely susceptible to the measures taken to mitigate their spread. In this paper, we propose empirical dynamic modeling to predict the evolution of influenza in Spain’s regions. It is a non-parametric method that looks into the past for coincidences with the present to make the forecasts. Here, we extend the method to predict the evolution of other epidemics at any other starting territory and we also test this procedure with Spanish COVID-19 data. We finally build influenza and COVID-19 networks to check possible coincidences in the geographical distribution of both diseases. With this, we grasp the uniqueness of the geographical dynamics of COVID-19.
Multisensor Fusion Estimation for Systems with Uncertain Measurements, Based on Reduced Dimension Hypercomplex Techniques
Authors: Fernández-Alcalá Rosa M. , Jiménez-López José D. , Navarro-Moreno Jesús , Ruiz-Molina Juan C.
Published: July 2022

The prediction and smoothing fusion problems in multisensor systems with mixed uncertainties and correlated noises are addressed in the tessarine domain, under Tk-properness conditions. Bernoulli distributed random tessarine processes are introduced to describe one-step randomly delayed and missing measurements. Centralized and distributed fusion methods are applied in a Tk-proper setting, k=1,2, which considerably reduce the dimension of the processes involved. As a consequence, efficient centralized and distributed fusion prediction and smoothing algorithms are devised with a lower computational cost than that derived from a real formalism. The performance of these algorithms is analyzed by using numerical simulations where different uncertainty situations are considered: updated/delayed and missing measurements.
Multi-Gear Bandits, Partial Conservation Laws, and Indexability
Authors: Niño-Mora José
Published: July 2022

This paper considers what we propose to call multi-gear bandits, which are Markov decision processes modeling a generic dynamic and stochastic project fueled by a single resource and which admit multiple actions representing gears of operation naturally ordered by their increasing resource consumption. The optimal operation of a multi-gear bandit aims to strike a balance between project performance costs or rewards and resource usage costs, which depend on the resource price. A computationally convenient and intuitive optimal solution is available when such a model is indexable, meaning that its optimal policies are characterized by a dynamic allocation index (DAI), a function of state–action pairs representing critical resource prices. Motivated by the lack of general indexability conditions and efficient index-computing schemes, and focusing on the infinite-horizon finite-state and -action discounted case, we present a verification theorem ensuring that, if a model satisfies two proposed PCL-indexability conditions with respect to a postulated family of structured policies, then it is indexable and such policies are optimal, with its DAI being given by a marginal productivity index computed by a downshift adaptive-greedy algorithm in AN steps, with A+1 actions and N states. The DAI is further used as the basis of a new index policy for the multi-armed multi-gear bandit problem.
Contactless Determination of a Permanent Magnet’s Stable Position within Ferrofluid
Authors: Trbušić Mislav , Hamler Anton , Goričan Viktor , Jesenik Marko
Published: July 2022

The paper deals with the contactless detection of a rod permanent magnet’s position within a ferrofluid. The working principle of the proposed approach is grounded on the solenoidal nature of the field lines. For the line detection technique analyzed in this article, where the magnetic field is scanned along the line parallel to the magnet’s axial direction, the center of the magnet corresponds to the point on the line where the radial component of the magnetic field vanished. The concept introduced here was evaluated numerically, where the results showed a promising perspective for the technique to be employed in practice. In contrast to the X-ray or Vernier-caliper-based technique, the one proposed here is somewhat more suitable for employment in applications where simplicity and robustness are of vital importance.
Introduction to the Class of Prefractal Graphs
Authors: Kochkarov Rasul , Kochkarov Azret
Published: July 2022

Fractals are already firmly rooted in modern science. Research continues on the fractal properties of objects in physics, chemistry, biology and many other scientific fields. Fractal graphs as a discrete representation are used to model and describe the structure of various objects and processes, both natural and artificial. The paper proposes an introduction to prefractal graphs. The main definitions and notation are proposed—the concept of a seed, the operations of processing a seed, the procedure for generating a prefractal graph. Canonical (typical) and non-canonical (special) types of prefractal graphs are considered separately. Important characteristics are proposed and described—the preservation of adjacency of edges for different ranks in the trajectory. The definition of subgraph-seeds of different ranks is given separately. Rules for weighting a prefractal graph by natural numbers and intervals are proposed. Separately, the definition of a fractal graph as infinite is given, and the differences between the concepts of fractal and prefractal graphs are described. At the end of the work, already published works of the authors are proposed, indicating the main backlogs, as well as a list of directions for new research. This work is the beginning of a cycle of works on the study of the properties and characteristics of fractal and prefractal graphs.
A Semiparametric Approach to Test for the Presence of INAR: Simulations and Empirical Applications
Authors: Palazzo Lucio , Ievoli Riccardo
Published: July 2022

The present paper explores the application of bootstrap methods in testing for serial dependence in observed driven Integer-AutoRegressive (models) considering Poisson arrivals (P-INAR). To this end, a new semiparametric and restricted bootstrap algorithm is developed to ameliorate the performance of the score-based test statistic, especially when the time series present small or moderately small lengths. The performance of the proposed bootstrap test, in terms of empirical size and power, is investigated through a simulation study even considering deviation from Poisson assumptions for innovations, i.e., overdispersion and underdispersion. Under non-Poisson innovations, the semiparametric bootstrap seems to “restore” inference, while the asymptotic test usually fails. Finally, the usefulness of this approach is shown via three empirical applications.
Surgical Treatment Following Failed Medical Treatment of an Interstitial Pregnancy
Authors: Restaino Stefano , De Gennaro Elena , Floris Stefano , Stabile Guglielmo , Zinicola Giulia , Sorrentino Felice , Vizzielli Giuseppe , Driul Lorenza
Published: July 2022

Interstitial pregnancy (IP) is a type of ectopic pregnancy in which the embryo implants in the interstitial part of the Fallopian tube. It accounts for 2% of all ectopic pregnancies. Signs and symptoms appear later than the other forms of ectopic pregnancies because of its peculiar location. The gold standard for its diagnosis is transvaginal ultrasound. The treatment can be medical or surgical. Medical treatment is based on the systemic or local injection of methotrexate (MTX); a dose of mifepristone can be added with a reported 85–90% success rate. The surgical option is laparoscopic unilateral cornuostomy or unilateral salpingectomy. The therapeutic choice is based on symptoms, serum β-human chorionic gonadotropin (β-hCG) values, and sonographic features. Furthermore, the patient’s fertility perspectives should be considered. We report a case of IP in a Caucasian woman of 29 years old, with a previous salpingectomy for ectopic pregnancy medically treated by a double dose of intramuscular MTX 50 mg/m2 combined with a single dose of leucovorin 15 mg and a single dose of mifepristone 600 mg orally. Medical therapy failed as suggested by the sudden onset of intense pelvic pain after 10 days. Because of the clinical symptoms and the sonographic suspicious of pregnancy rupture due to the modest amount of fluid in the pouch of Douglas, clinicians decided on an urgent unilateral laparoscopic salpingectomy. The hemoperitoneum was drained. The patient was discharged two days later and β-hCG serum levels became negative after 45 days. The advantages of fertility sparing should be weighted according to the patient’s reproductive perspectives. Appropriate counseling is therefore key in managing the treatment of interstitial pregnancy.
Partial Removal of Sugar from Apple Juice by Nanofiltration and Discontinuous Diafiltration
Authors: Gaglianò Martina , Conidi Carmela , De Luca Giuseppina , Cassano Alfredo
Published: July 2022

Partial removal of sugars in fruit juices without compromising their biofunctional properties represents a significant technological challenge. The current study was aimed at evaluating the separation of sugars from phenolic compounds in apple juice by using three different spiral-wound nanofiltration (NF) membranes with a molecular weight cut-off (MWCO) in the range of 200–500 Da. A combination of diafiltration and batch concentration processes was investigated to produce apple juice with reduced sugar content and improved health properties thanks to the preservation and concentration of phenolic compounds. For all selected membranes, permeate flux and recovery rate of glucose, fructose, and phenolic compounds, in both diafiltration and concentration processes, were evaluated. The concentration factor of target compounds as a function of the volume reduction factor (VRF) as well as the amount of adsorbed compound on the membrane surface from mass balance analysis were also evaluated. Among the investigated membranes a thin-film composite membrane with an MWCO of 200–300 Da provided the best results in terms of the preservation of phenolic compounds in the selected operating conditions. More than 70% of phenolic compounds were recovered in the retentate stream while the content of sugars was reduced by about 60%.
Intravenous Nanocarrier for Improved Efficacy of Quercetin and Curcumin against Breast Cancer Cells: Development and Comparison of Single and Dual Drug–Loaded Formulations Using Hemolysis, Cytotoxicity and Cellular Uptake Studies
Authors: Rahman Mohammad Akhlaquer , Mittal Vineet , Wahab Shadma , Alsayari Abdulrhman , Bin Muhsinah Abdullatif , Almaghaslah Dalia
Published: July 2022

The present work highlights the suitability of an oil-based nanocarrier to deliver quercetin (Q) and curcumin (C) through the intravenous route for treatment of breast cancer. The nanoemulsion prepared by the modified emulsification-solvent evaporation method resulted in particle size (<30 nm), polydispersity index (<0.2), zeta potential (<10 mV), optimum viscosity, high encapsulation efficiency and drug loading for both drugs. The pH and osmolarity of the nanoemulsion were about 7.0 and 280 mOsm, respectively, demonstrated its suitability for intravenous administration. In-vitro release of drugs from all the formulations demonstrated initial fast release followed by sustained release for a period of 48 h. The fabricated single and dual drug–loaded nanoemulsion (QNE, CNE, QC-NE) exhibited moderate hemolysis at a concentration of 50 μg/mL. The % hemolysis caused by all the formulations was similar to their individual components (p ˃ 0.05) and demonstrated the biocompatibility of the nanoemulsion with human blood. In vitro cytotoxic potential of single and dual drug–loaded nanoemulsions were determined against breast cancer cells (MF-7). The IC50 value for QNE and CNE were found to be 40.2 ± 2.34 µM and 28.12 ± 2.07 µM, respectively. The IC50 value for QC-NE was 21.23 ± 2.16 µM and demonstrated the synergistic effect of both the drugs. The internalization of the drug inside MF-7 cells was detected by cellular uptake study. The cellular uptake of QNE and CNE was approximately 3.9-fold higher than free quercetin and curcumin (p < 0.0001). This strategically designed nanoemulsion appears to be a promising drug delivery system for the proficient primary preclinical development of quercetin and curcumin as therapeutic modalities for the treatment of breast cancer.
Morphology and Structure of Electrolytically Synthesized Tin Dendritic Nanostructures
Authors: Nikolić Nebojša D. , Lović Jelena D. , Maksimović Vesna M. , Živković Predrag M.
Published: July 2022

The formation of tin dendritic nanostructures by electrolysis from the alkaline electrolyte has been investigated. Morphology and structure of Sn dendrites produced applying both potentiostatic and galvanostatic regimes of the electrolysis are characterized by SEM and XRD, respectively. Depending on the applied cathodic potentials, three types of Sn dendrites were obtained: (a) needle-like and spear-like, (b) fern-like, and (c) stem-like dendrites. The very branchy dendrites with branches of the prismatic shape obtained by the galvanostatic regime of electrolysis represented a novel type of Sn dendrites, not previously reported in the literature. To explain the formation of various dendritic forms, correlation with the polarization characteristics for this electrodeposition system is considered. The needle-like and the spear-like dendrites represented monocrystals of (200),(400) preferred orientation, the fern-like dendrites exhibited the predominant (220),(440) preferred orientation, while in the stem-like particles Sn crystallites were oriented to a greater extent in the (440) crystal plane than in other planes. The galvanostatically synthesized Sn particles possessed the strong (200),(400) preferred orientation. The strong influence of parameters and regimes of electrodeposition on structural characteristics of Sn dendrites is explained by the fundamental laws of electrocrystallization taking into consideration the concept of slow-growing and fast-growing crystal planes.
Effect of HIP Defects on the Mechanical Properties of Additive Manufactured Ti6Al4V Alloy
Authors: Dolev Ohad , Ron Tomer , Aghion Eli , Shirizly Amnon
Published: July 2022

The expanding use of Additive Manufacturing (AM) technology enables engineers and designers to plan and manufacture highly complex geometries that are impossible to manufacture with any other conventional technology. When comparing this with building parts using powder bed technology, the main differences found in the quality of the products concern fracture toughness, fatigue, and inferiority in tensile tests. To overcome these issues, the Hot Isostatic Press (HIP) procedure may be used to improve the material quality by reducing product porosity. Regarding fatigue, the standard procedure consists of HIP and the machining of specimens to their final geometry. However, in many AM parts, geometrical complexity does not enable complementary machining. Recently, some AM vendors integrated in-process milling capabilities into their machines, in an attempt to address this challenge. In this study, the authors examine the effect of the HIP procedure on representative samples in order to demonstrate its effect on the final products of TI-6Al-4V parts. The results indicate that the fatigue limit of HIPed parts can increase by 12%; however, a dramatic decrease in the fatigue limit was observed if any failure in the HIP process occurred. The authors suggest an optional procedure to improve performance in such cases.