bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and Performance Evaluation of a Novel Slave System for Endovascular Tele-Surgery
Authors: Shi Chaochao , Guo Shuxiang , Kawanishi Masahiko
Published: September 2022

Vascular interventional robots have attracted growing attention in recent years. However, current vascular interventional robot systems generally lack force feedback and cannot quickly clamp the catheter/guidewire. The structure of slave systems is unstable and the power transmission is imprecise, increasing the system’s safety hazards. Vascular intervention robots generally do not follow traditional surgeons’ operation habits and, thus, it is not easy for them to understand and learn how to operate. Therefore, a novel vascular intervention system is proposed. The slave system can quickly clamp the catheter/guidewire, is compatible with various standard catheter/guidewire sizes, has precise power transmission, and has a stable structure. The surface of the catheter/guidewire is clamped without damage. Whether it is on the master side or the slave side, it follows the habits of traditional operators to a great extent. The results show that the measurement accuracy of the axial force meets the requirements of robot-assisted surgery and the system can track the designed position of the catheter/guidewire in real time. This study makes a certain contribution to the development of master–slave systems for endovascular tele-surgery.
Reliability-Based Robust Design Optimization for Maximizing the Output Torque of Brushless Direct Current (BLDC) Motors Considering Manufacturing Uncertainty
Authors: Jeon Kyunghun , Yoo Donghyeon , Park Jongjin , Lee Ki-Deok , Lee Jeong-Jong , Kim Chang-Wan
Published: September 2022

In recent years, the deterministic design optimization method has been widely used to improve the output performance of brushless direct current (BLDC) motors. However, it does not contribute to reducing the failure rate and performance variation of products because it cannot determine the manufacturing uncertainty. In this study, we proposed reliability-based robust design optimization to improve the output torque of a BLDC motor while reducing the failure rate and performance variation. We calculated the output torque and vibration response of the BLDC motor using the electromagnetic–structural coupled analysis. We selected the tooth thickness, slot opening width, slot radius, slot depth, tooth width, magnet thickness, and magnet length as the design variables related to the shape of the stator and rotor that affect the output torque. We considered the distribution of design variables with manufacturing tolerances. We performed a reliability analysis of the BLDC motor considering the distribution of design variables with manufacturing tolerances. Using the reliability analysis results, we performed reliability-based robust design optimization (RBRDO) to maximize the output torque; consequently, the output torque increased by 8.8% compared to the initial BLDC motor, the standard deviation in output performance decreased by 46.9% with improved robustness, and the failure rate decreased by 99.2% with enhanced reliability. The proposed reliability-based robust design optimization is considered to be useful in the actual product design field because it can evaluate both the reliability and robustness of the product and improve its performance in the design stage.
Hydrodynamic Characteristic-Based Adaptive Model Predictive Control for the Spherical Underwater Robot under Ocean Current Disturbance
Authors: Li Ao , Guo Shuxiang , Liu Meng , Yin He
Published: September 2022

In the navigation of underwater robots, large ocean current disturbance often causes significant tracking errors. To better resist ocean current disturbance, the hydrodynamic characteristics of the spherical underwater robot are studied, and a model predictive control strategy based on adaptive model parameters is proposed, according to these characteristics. Firstly, the hydrodynamic characteristics of the robot under static water and constant flow disturbance were obtained and analyzed by the computational fluid dynamics method. Then, the dynamic models of the robot under different disturbances could be calculated from the data obtained, based on the least square method. Finally, an adaptive model predictive control (AMPC) strategy, with an ocean current observer, was designed, based on the dynamic models. When the current disturbance velocity was twice the robot velocity, the proposed strategy reduced the tracking error by 39% and 42% in X and Y directions, respectively. In addition, the hydrodynamic characteristics were verified by experiments.
A Novel Numerical Method for Theoretical Tire Model Simulation
Authors: Liu Qianjin , Lu Dang , Ma Yao , Xia Danhua
Published: September 2022

Theoretical tire models are often used in tire dynamics analysis and tire design. In the past, scholars have carried out a lot of research on theoretical model modeling; however, little progress has been made on its solution. This paper focuses on the numerical solution of the theoretical model. New force and moment calculation matrix equations are constructed, and different iterative methods are compared. The results show that the modified Richardson iteration method proposed in this paper has the best convergence-stability in the steady and unsteady state calculation, which mathematically solves the problem of nonconvergence of discrete theoretical models in the published reference. A novel discrete method for solving the total deformation of tires is established based on the Euler method. The unsteady characteristics of tire models are only related to the path frequency without changing its parameters, so the unsteady state ability of the tire model can be judged based on this condition. It shows that the method in the references have significant differences at different speeds with the same path frequency under turn slip or load variations input, but the method proposed in this paper has good results.
Energy Harvesting Performance of a Novel Nonlinear Quad-Stable Piezoelectric Energy Harvester with Only One External Magnet
Authors: Sun Shuailing , Leng Yonggang , Hur Sunghoon , Sun Fei , Su Xukun , Song Hyun-Cheol , Kang Chong-Yun
Published: September 2022

Nonlinear multi-stable piezoelectric energy harvesters show broadband frequency spectra and excellent energy harvesting performance, owing to their high output power related to inter-well transitions. However, existing quad-stable piezoelectric energy harvesters contain too many structural parameters, which makes the systems clumsy, and increases the difficulties of dynamic analysis and structural optimization. Herein, a nonlinear quad-stable piezoelectric energy harvester, with only one external magnet, is proposed based on the magnetic force characteristics between a ring magnet and a rectangular magnet. Under selected structural parameters, as the magnet spacing increases, the stability characteristic of the harvester changes from quad-stability to bi-stability, and then to mono-stability. The transformation of the stability characteristic results from the changes in the variation rate of the vertical magnetic force. Subsequently, under the filtered Gaussian white noise within the frequency range of 0–120 Hz, the energy harvesting performance of the harvester is simulated by the classic fourth-order Runge-Kutta method. Simulation results show that the performance of the harvester under the quad-stable structural parameters is better than that under the bi-stable structural parameters, independent of whether the excitation acceleration is small or large. This result is related to the potential well characteristics under the quad-stable and bi-stable structural parameters. More specifically, the potential well depths under the quad-stable and bi-stable structural parameters are almost the same, but the distance between the two outer potential wells under the quad-stable structural parameters is larger than that under the bi-stable structural parameters. Finally, a fabricated prototype is used to measure the experimental performance of the harvester. The experimental data and the estimated data share the same trend. This study provides a new conception and technical method for the design, optimization, and application of quad-stable piezoelectric energy harvesters.
Dynamic Analysis of Gear Rattling of a Certain Type of Dual-Clutch Transmission
Authors: Guo Dong , Ning Qinfeng , Ge Shuaishuai , Zhou Yi , Luo Ruitian
Published: September 2022

In order to accurately explore the transmission rattling phenomenon and the influence of different factors on the dynamic characteristics of the gear rattling of the dual-clutch transmission under the condition of preselected gears, this paper establishes the gear rattling dynamics model of the transmission with the 1st gear without preselection and the preselected 4th gear, respectively; The model takes into account factors such as time-varying mesh stiffness, mesh damping, nonlinear oil film force, nonlinear backlash, and the drag torque generated by the clutch in the unengaged state. In addition, the feasibility of the dynamic model was verified by the bench test. On this basis, we took the gear meshing power and system power loss as quantitative indexes to analyze the influence of the preselected gear state and different parameters on the rattle vibration of the transmission. The results show that the pre-selected gear will not have a significant effect on the gears that have been rattled in the non-pre-selected state, and the torque fluctuation of the non-power flow shaft is aggravated by the influence of the transmission power flow branch and transmission ratio at different levels, which makes the overall rattling strength increase. In order to improve the transmission efficiency of the gear, the torque fluctuation of the input end of the system should be reduced as much as possible, and a larger lubricant viscosity can be appropriately selected, the inertia of the empty gear can be properly reduced, and the tooth clearance can be relaxed for selection.
CNN-Hyperparameter Optimization for Diabetic Maculopathy Diagnosis in Optical Coherence Tomography and Fundus Retinography
Authors: Atteia Ghada , Abdel Samee Nagwan , El-Kenawy El-Sayed M. , Ibrahim Abdelhameed
Published: September 2022

Diabetic Maculopathy (DM) is considered the most common cause of permanent visual impairment in diabetic patients. The absence of clear pathological symptoms of DM hinders the timely diagnosis and treatment of such a critical condition. Early diagnosis of DM is feasible through eye screening technologies. However, manual inspection of retinography images by eye specialists is a time-consuming routine. Therefore, many deep learning-based computer-aided diagnosis systems have been recently developed for the automatic prognosis of DM in retinal images. Manual tuning of deep learning network’s hyperparameters is a common practice in the literature. However, hyperparameter optimization has shown to be promising in improving the performance of deep learning networks in classifying several diseases. This study investigates the impact of using the Bayesian optimization (BO) algorithm on the classification performance of deep learning networks in detecting DM in retinal images. In this research, we propose two new custom Convolutional Neural Network (CNN) models to detect DM in two distinct types of retinal photography; Optical Coherence Tomography (OCT) and fundus retinography datasets. The Bayesian optimization approach is utilized to determine the optimal architectures of the proposed CNNs and optimize their hyperparameters. The findings of this study reveal the effectiveness of using the Bayesian optimization for fine-tuning the model hyperparameters in improving the performance of the proposed CNNs for the classification of diabetic maculopathy in fundus and OCT images. The pre-trained CNN models of AlexNet, VGG16Net, VGG 19Net, GoogleNet, and ResNet-50 are employed to be compared with the proposed CNN-based models. Statistical analyses, based on a one-way analysis of variance (ANOVA) test, receiver operating characteristic (ROC) curve, and histogram, are performed to confirm the performance of the proposed models.
Activation Energy Performance through Magnetized Hybrid Fe3O4–PP Nanofluids Flow with Impact of the Cluster Interfacial Nanolayer
Authors: Qureshi M. Zubair Akbar , Raza Qadeer , Ramzan Aroosa , Faisal M. , Ali Bagh , Shah Nehad Ali , Weera Wajaree
Published: September 2022

The current work investigated the mass and heat transfer of the MHD hybrid nanofluid flow subject to the impact of activation energy and cluster interfacial nanolayer. The heat transport processes related to the interfacial nanolayer between nanoparticles and base fluids enhanced the base fluid’s thermal conductivity. The tiny particles of Fe3O4 and PPy were considered due to the extraordinary thermal conductivity which is of remarkable significance in nanotechnology, electronic devices, and modern shaped heat exchangers. Using the similarity approach, the governing higher-order nonlinear coupled partial differential equation was reduced to a system of ordinary differential equations (ODEs). Fe3O4–PPy hybrid nanoparticles have a considerable influence on thermal performance, and when compared to non-interfacial nanolayer thermal conductivity, the interfacial nanolayer thermal conductivity model produced substantial findings. The increase in nanolayer thickness from level 1 to level 5 had a significant influence on thermal performance improvement. Further, the heat and mass transfer rate was enhanced with higher input values of interfacial nanolayer thickness.
Morphology of Hybrid MHD Nanofluid Flow through Orthogonal Coaxial Porous Disks
Authors: Raza Qadeer , Qureshi M. Zubair Akbar , Ali Bagh , Hussein Ahmed Kadhim , Khan Behzad Ali , Shah Nehad Ali , Weera Wajaree
Published: September 2022

In this article, we study the novel features of morphological effects for hybrid nanofluid flow subject to expanding/contracting geometry. The nanoparticles are incorporated due to their extraordinary thermal conductivity and innovative work for hybrid nanofluids, which are assembled of aluminum oxides, Al2O3 metallic oxides, and metallic copper Cu. Cu nanoparticles demonstrate very strong catalytic activity, while Al2O3 nanoparticles perform well as an electrical insulator. The governing partial differential equations of the elaborated model are transformed into a system of nonlinear ordinary differential equations with the use of similarity variables, and these equations are numerically solved through a shooting technique based on the Runge–Kutta method. We develop a hybrid correlation for thermophysical properties based on a single-phase approach. A favorable comparison between shape and size factors for metallic and metallic-oxide nanoparticles is discussed via tables and figures. Moreover, the effect of embedding flow factors on concentration, velocity, and temperature is shaped in line with parametric studies, such as the permeable Reynolds number, nanoparticle volume fractions, and expansion/contraction parameters. The fluid velocity, temperature, and concentration are demonstrated in the presence of hybrid nanoparticles and are discussed in detail, while physical parameters such as the shear stress, flow of heat, and mass transfer at the lower and upper disks are demonstrated in a table. The hybrid nanoparticles show significant results as compared to the nanofluids. If we increase the nanoparticle volume fraction, this increases the thermal performance for an injection/suction case as well. The above collaborative research provides a strong foundation in the field of biomedical equipment and for the development of nanotechnology-oriented computers.
Advanced Analytic Self-Similar Solutions of Regular and Irregular Diffusion Equations
Authors: Barna Imre Ferenc , Mátyás László
Published: September 2022

We study the diffusion equation with an appropriate change of variables. This equation is, in general, a partial differential equation (PDE). With the self-similar and related Ansatz, we transform the PDE of diffusion to an ordinary differential equation. The solutions of the PDE belong to a family of functions which are presented for the case of infinite horizon. In the presentation, we accentuate the physically reasonable solutions. We also study time-dependent diffusion phenomena, where the spreading may vary in time. To describe the process, we consider time-dependent diffusion coefficients. The obtained analytic solutions all can be expressed with Kummer’s functions.
On Some Improved Class of Estimators by Using Stratified Ranked Set Sampling
Authors: Bhushan Shashi , Kumar Anoop , Shahzad Usman , Al-Omari Amer Ibrahim , Almanjahie Ibrahim Mufrah
Published: September 2022

In this manuscript, we propose the combined and separate difference and ratio type estimators of population mean using stratified ranked set sampling. Additionally, several well-known estimators are identified as the sub-class of the suggested estimators. The characteristics of the suggested estimators have been analyzed and their effective performances are compared with the prominent estimators existing till date. Moreover, to prove the credibility of the theoretical findings, an extensive empirical study is administered over some real and hypothetically yielded symmetric and asymmetric populations.
Power-Law Nanofluid Flow over a Stretchable Surface Due to Gyrotactic Microorganisms
Authors: Nabwey Hossam A. , A. Khan Waqar , Rashad A. M. , Mabood Fazal , Salah Taha
Published: September 2022

This study aims to learn more about how the flow of a power-law nanofluid’s mixed bio-convective stagnation point flow approaching a stretchable surface behaves with the presence of a passively controlled boundary condition. The governing equations incorporate the motile bacterium and nanoparticles, and the current model includes Brownian motion and thermophoresis effects. The governing equations are transformed into ordinary differential equations, which are then numerically solved using the Runge–KuttaFehlberg (RKF) with the shooting technique. The controlling parameters are chosen as follows: the velocity ratio parameter, ε, is taken between 0.1 and 1.5; the mixed convection parameter, λ, is considered in the range 0–3; the buoyancy ratio parameter is considered in the range between 0.1 and 4; the bio-convection parameter, Rb, is taken in the range 0–1; nanofluid parameters are taken in the range 0.1–0.7; the bioconvection Schmidt number is considered in the range 0.1–3; the Prandtl number is taken between 1–4; and the Schmidt number is taken between 1 and 3. The Nusselt number, skin friction, and nanoparticle volume fraction profiles are shown graphically to observe the impact of several parameters under consideration. Both the Schmidt number and the Brownian motion parameter are shown to significantly increase the Sherwood number. Thermophoresis, however, has been proven to lower the Sherwood number. Furthermore, the bioconvection constant and Peclet number both help to slow down the rate of mass transfer. The presented theoretical investigation has a considerable role in engineering, where nanofluid flow is applied to organize a bioconvection process to develop power generation and mechanical energy. One of the more essential features of bioconvection is the aggregation of nanoparticles with motile microorganisms requested to augment the stability, heat, and mass transmission.
Effective Optimization Based on Equilibrium Optimizer for Dynamic Cutting Force Coefficients of the End-Milling Process
Authors: Tran Minh-Quang , Elsisi Mahmoud , Vu Viet Q. , Albalawi Fahad , Ghoneim Sherif S. M.
Published: September 2022

This study aims to develop an accurate dynamic cutting force model in the milling process. In the proposed model, the estimated cutting force tackles the effect of the self-excited vibration that causes machining instability during the cutting process. In particular, the square root of the residual cutting force between the prediction and the actual cutting force is considered as an objective function for optimizing the cutting force coefficients using the equilibrium optimizer (EO) approach instead of the trial-and-error approach. The results confirm that the proposed model can provide higher prediction accuracy when the EO is applied. In addition, the proposed EO has a minimum integral square error (ISE) of around 1.12, while the genetic algorithm (GA) has an ISE of around 1.14 and the trial-and-error method has an ISE of around 2.4. Moreover, the proposed method can help to investigate the cutting stability and to suspend the chatter phenomenon by selecting an optimal set of cutting parameters.
Track Utilization Optimization Method for Arrival Yard of Marshalling Station Considering Arrival and Break-Up Coordination Operation
Authors: Chen Weiya , Yang Weiting , Zhang Guangdong
Published: September 2022

The efficiency of track utilization is one of the important factors for train operation in marshalling stations, and it can not only affect the turnover efficiency of trains, but also determine the capacity of railway stations. This paper presents an optimization method for track utilization in the arrival yard of a marshalling station considering Arrival and Break-up Coordination Operation (ABCO). The interaction between the push operation of trains and track utilization efficiency is investigated. First, the case of crossing the running route for shunting locomotives is analyzed. Whether the shunting route crosses or not can greatly affect the duration of trains occupying tracks in the station. Then, a nonlinear integer programming model (NLPM) is established based on the above analysis. The ultimate goal is to minimize the number of crossovers of the shunting route by adding a constraint condition for ensuring traffic safety. A track assignment algorithm based on ABCO for solving the NLPM is proposed. Train operations in the downlink arrival yard of station A are simulated with the proposed method. The results after applying the optimization method show that the average duration of trains on the tracks is reduced by 49.1%, and the degree to which tracks utilization is balanced is also significantly improved. The proposed method optimizes and extends the current achievements that have been reported in the literature.
STSM: Spatio-Temporal Shift Module for Efficient Action Recognition
Authors: Yang Zhaoqilin , An Gaoyun , Zhang Ruichen
Published: September 2022

The modeling, computational complexity, and accuracy of spatio-temporal models are the three major foci in the field of video action recognition. The traditional 2D convolution has low computational complexity, but it cannot capture the temporal relationships. Although the 3D convolution can obtain good performance, it is with both high computational complexity and a large number of parameters. In this paper, we propose a plug-and-play Spatio-Temporal Shift Module (STSM), which is a both effective and high-performance module. STSM can be easily inserted into other networks to increase or enhance the ability of the network to learn spatio-temporal features, effectively improving performance without increasing the number of parameters and computational complexity. In particular, when 2D CNNs and STSM are integrated, the new network may learn spatio-temporal features and outperform networks based on 3D convolutions. We revisit the shift operation from the perspective of matrix algebra, i.e., the spatio-temporal shift operation is a convolution operation with a sparse convolution kernel. Furthermore, we extensively evaluate the proposed module on Kinetics-400 and Something-Something V2 datasets. The experimental results show the effectiveness of the proposed STSM, and the proposed action recognition networks may also achieve state-of-the-art results on the two action recognition benchmarks.
A Multi-Mechanism Seagull Optimization Algorithm Incorporating Generalized Opposition-Based Nonlinear Boundary Processing
Authors: Liu Xinyu , Li Guangquan , Shao Peng
Published: September 2022

The seagull optimization algorithm (SOA), a well-known illustration of intelligent algorithms, has recently drawn a lot of academic interest. However, it has a variety of issues including slower convergence, poorer search accuracy, the single path for pursuing optimization, and the simple propensity to slip into local optimality. This paper suggests a multi-mechanism seagull optimization algorithm (GEN−SOA) that incorporates the generalized opposition-based, adaptive nonlinear weights, and evolutionary boundary constraints to address these demerits further. These methods are balanced and promoted the population variety and the capability to conduct global and local search. Compared with SOA, PSO, SCA, SSA, and BOA on 12 well-known test functions, the experimental results demonstrate that GEN-SOA has a higher accuracy and faster convergence than the other five algorithms, and it can find the global optimal solution beyond the local optimum. Furthermore, to verify the capability of GEN−SOA to solve practical problems, this paper applied GEN−SOA to solve two standard engineering optimization design problems including a welding optimization and a pressure vessel optimization, and the experimental results showed that it has significant advantages over SOA.
Influence of the Electromagnetic Energy Due to Cellular Devices in a Multi-Layer Human Head under Two-Temperature Heat Conduction Model
Authors: Abbas Ibrahim A. , Youssef Hamdy M. , El-Bary Alaa A.
Published: September 2022

In this study, a mathematical model of a human head with three layers of skin, bone, and brain for both children and adults was created. The phase-lag time definition was used to evaluate the internal thermal reaction that is created via the human head as a result of chemical processes. In the framework of the two-temperature heat conduction model, the governing equations were developed. The inversions were numerically derived using an approximation approach after applying Laplace transforms. When the human head is exposed to cellular devices that emit an electromagnetic wave, the dynamic and conductive temperature increments distributions have been calculated and discussed with various values of the two-temperature parameter, time, relaxation time, power transmission frequency, and power density. Each layer of the human cranium is affected by all of the characteristics analysed. The impacts of electromagnetic waves emitted by cellular devices were more detrimental to the bones of children’s heads than they are to the bones of adults’ heads.
Research on the Multilayer Network of Relations of Western Agricultural Trade along the Belt and Road
Authors: Xie Fengjie , Yin Xiaoxiao , Sun Ruifen
Published: September 2022

This paper defines the weighted super adjacency matrix based on the existing super adjacency matrix. This paper, for the first time, combines the trade network, competitive network, and complementary network to construct the trade multilayer network, and innovatively defines the interlayer connections. Based on this, we build trade multilayer networks for three major agricultural products in the western region along the “Belt and Road”. The paper then proposes analytical methods, including a classification algorithm for local network relations and a comparative analysis of trade development priorities based on the local network relations. The former is used to identify and categorize key trading countries and potential trading countries for western agricultural products along the “Belt and Road”. The latter is used to examine the western regions’ order of priority in developing trade relations with the classified countries. According to the findings, category I agricultural trade has 37 key trading countries among the “Belt and Road” countries. Their local network relationships are classified into six groups, and their trade development priorities are classified into four levels. There are 49 key trading countries in category II agricultural trade. Their local network relations can be classified into three groups, and their trade development priorities can be classified into two levels. There are 62 key trading countries in category IV agricultural trade. Their local network relationships are classified into six groups, and their trade development priorities are classified into four levels. Furthermore, only Chile is a potential trading partner in category I agricultural trade. Finally, this paper offers policy recommendations for the development of agricultural trade along the “Belt and Road” in the western region.
Algorithmic Trading and Financial Forecasting Using Advanced Artificial Intelligence Methodologies
Authors: Cohen Gil
Published: September 2022

Artificial Intelligence (AI) has been recently recognized as an essential aid for human traders. The advantages of the AI systems over human traders are that they can analyze an extensive data set from different sources in a fraction of a second and perform actual high-frequency trading (HFT) that can take advantage of market anomalies and price differences. This paper reviews the most important papers published in recent years that use the most advanced techniques to forecast financial asset trends and answer the question of whether those techniques can be used to successfully trade the complex financial markets. All systems use deep learning (DL) and machine learning (ML) protocols to explore nonobvious correlations and phenomena that influence the probability of trading success. Their predictions are based on linear or nonlinear models often combined with social media investors’ sentiment derivations or pattern recognitions. Most of the reviewed papers have proven the successful ability of their developed system to trade the financial markets.
On Several Bounds for Types of Angular Distances
Authors: Raţiu Augusta , Minculete Nicuşor
Published: September 2022

In this study, we introduce the expression dλ(x,y):=λ∥x∥+(1−λ)∥y∥−∥λx+(1−λ)y∥ on the real normed space X(X,∥·∥), where x,y∈X and λ∈R. We characterize this expression and find various estimates of it. We also obtain a generalization and some refinements of Maligranda’s inequality. Finally, we give some relations between dλ(x,y) and several types of angular distances between two nonzero vectors in a real normed space.
Sustainable Fuzzy Portfolio Selection Concerning Multi-Objective Risk Attitudes in Group Decision
Authors: Huang Yin-Yin , Tsaur Ruey-Chyn , Huang Nei-Chin
Published: September 2022

Fuzzy portfolio selection has resulted in many researchers to focus on this field. Based on the risk attitudes, this study discusses the risk attitudes in a decision group for portfolio selection. Therefore, we adopt the risk attitudes to describe the experts’ risk preferences and subjective judgments, and then we suppose that the risk seeker considers a higher return for an excess investment based on the selected guaranteed rate of return; the risk averter considers a shortage in investment for the securities whose return rates are smaller than the selected guaranteed rate of return; and finally, the risk neutral pursues the regular return rate. In order to solve the multi-objective return rate functions under the corresponding investment risks, the SMART-ROC weighting method is used to hybridize the multi-objective programming model to a linear programming model for solving the portfolio selection. Finally, we illustrate a numerical example and two risk scenarios to show the optimal portfolio selection under different investment risks. The results show that the proposed model can obtain a more robust portfolio than the compared models under different risk priorities in a decision group.
Secure Reversible Data Hiding in Images Based on Linear Prediction and Bit-Plane Slicing
Authors: Nasir Maham , Jadoon Waqas , Khan Iftikhar Ahmed , Gul Nosheen , Shah Sajid , ELAffendi Mohammed , Muthanna Ammar
Published: September 2022

Reversible Data Hiding (RDH) should be secured as per requirements to protect content in open environments such as the cloud and internet. Integrity and undetectability of steganographic images are amongst the main concerns in any RDH scheme. As steganographic encryption using linear prediction over bit-planes is challenging, so the security and embedding capacity of the existing RDH techniques could not be adequate. Therefore, a new steganographic technique is proposed which provides better security, higher embedding capacity and visual quality to the RDH scheme. In this technique, the cover image is divided into n-bit planes (nBPs) and linear prediction is applied to it. Next, the histogram of the residual nBPs image is taken, and secret data bits are encrypted using the RC4 cryptographic algorithm. To embed the encrypted secret data bits, the histogram shifting process is applied. This is achieved by using peak and zero pairs of residual nBPs images. This scheme provides security to the cover image and hidden data. The proposed RDH scheme is capable of extracting the embedded secret data accurately and recovering the original cover or residual nBPs image.
Rare Gene Mutations in Romanian Hypoacusis Patients: Case Series and a Review of the Literature
Authors: Neagu Alexandra-Cristina , Budișteanu Magdalena , Gheorghe Dan-Cristian , Mocanu Adela-Ioana , Mocanu Horia
Published: September 2022

(1) Background: In this paper, we report on three cases of hypoacusis as part of a complex phenotype and some rare gene variants. An extensive review of literature completes the newly reported clinical and genetic information. (2) Methods: The cases range from 2- to 11-year-old boys, all with a complex clinical picture and hearing impairment. In all cases, whole exome sequencing (WES) was performed, in the first case in association with mitochondrial DNA study. (3) Results: The detected variants were: two heterozygous variants in the TWNK gene, one likely pathogenic and another of uncertain clinical significance (autosomal recessive mitochondrial DNA depletion syndrome type 7—hepatocerebral type); heterozygous variants of uncertain significance PACS2 and SYT2 genes (autosomal dominant early infantile epileptic encephalopathy) and a homozygous variant of uncertain significance in SUCLG1 gene (mitochondrial DNA depletion syndrome 9). Some of these genes have never been previously reported as associated with hearing problems. (4) Conclusions: Our cases bring new insights into some rare genetic syndromes. Although the role of TWNK gene in hearing impairment is clear and accordingly reflected in published literature as well as in the present article, for the presented gene variants, a correlation to hearing problems could not yet be established and requires more scientific data. We consider that further studies are necessary for a better understanding of the role of these variants.
Caesarean Section on Maternal Request-Ethical and Juridic Issues: A Narrative Review
Authors: Sorrentino Felice , Greco Francesca , Palieri Tea , Vasciaveo Lorenzo , Stabile Guglielmo , Carlucci Stefania , Laganà Antonio Simone , Nappi Luigi
Published: September 2022

In recent decades, the rate of caesarean deliveries has increased worldwide. The reasons for this trend are still largely misunderstood and controversial among researchers. The decision often depends on the obstetrician, his beliefs and experience, the characteristics of the patients, the hospital environment and its internal protocols, the increasing use of induction of labor, the medico-legal implications, and, finally, the mother’s ability to request delivery by caesarean section without medical indication. This review aims to describe the reasons behind the increasing demand for caesarean sections by patients (CDMR) and strategies aimed at reducing caesarean section rates and educating women about the risks and benefits of CS.
Juxtapapillary Choroidal Neovascularization in a Young Woman with Tubulointerstitial Nephritis and Uveitis (TINU) Syndrome with Onset in Pediatric Age
Authors: Paroli Maria , Cappiello Daniele , Staccini Davide , Tamburrelli Anna , Paroli Marino , Iannetti Ludovico
Published: September 2022

We describe the unusual case of a young woman with tubulointerstitial nephritis and uveitis (TINU) with bilateral diffuse uveitis and optic nerve inflammatory involvement since she was a child in the 1990s. Imaging diagnostic tools such as fluorescein angiography, indocyanine green angiography, optical coherence tomography (OCT), and OCT angiography revealed inactive juxtapapillary choroidal neovascularization (CNV) after 25 years of follow-up. After treatment, uveitis went into remission with BCVA 20/20 in both eyes and CNV lesions became inactive. Although anterior uveitis is more frequently reported in TINU, posterior uveitis with inflammatory involvement of the optic nerve should be accurately investigated to rule out juxtapapillary CNV, both at the time of active uveitis and during follow-up, since TINU may be complicated by CNV even at the later stages of the inflammatory process.
Post-ERCP Pancreatitis: Prevention, Diagnosis and Management
Authors: Cahyadi Oscar , Tehami Nadeem , de-Madaria Enrique , Siau Keith
Published: September 2022

Endoscopic retrograde cholangiopancreatography (ERCP) carries a post-ERCP pancreatitis (PEP) rate of 2–10%, which could be as high as 30–50% in high-risk cases. PEP is severe in up to 5% of cases, with potential for life-threatening complications, including multi-organ failure, peripancreatic fluid collections, and death in up to 1% of cases. The risk of PEP is potentially predictable and may be modified with pharmacological measures and endoscopist technique. This review covers the definition, epidemiology and risk factors for PEP, with a focus on the latest evidence-based medical and endoscopic strategies to prevent and manage PEP.
Clinical Presentations, Predictive Factors, and Outcomes of Clostridioides difficile Infection among COVID-19 Hospitalized Patients—A Single Center Experience from the COVID Hospital of the University Clinical Center of Vojvodina, Serbia
Authors: Kovačević Nadica , Lendak Dajana , Popović Milica , Plećaš Đuric Aleksandra , Pete Maria , Petrić Vedrana , Sević Siniša , Tomić Slavica , Alargić Jelica , Damjanov Dimitrije , Kosjer Dijana , Lekin Milica
Published: September 2022

Background: This study aimed to investigate the clinical form, risk factors, and outcomes of patients with COVID-19 and Clostridioides difficile co-infections. Methods: This retrospective study (2 September 2021–1 April 2022) included all patients with Clostridioides difficile infection (CDI) and COVID-19 infection who were admitted to the Covid Hospital of the University Clinical Center of Vojvodina. Results: A total of 5124 COVID-19 patients were admitted to the Covid Hospital, and 326 of them (6.36%) developed hospital-onset CDI. Of those, 326 of the CDI patients (88.65%) were older than 65 years. The median time of CDI onset was 12.88 days. Previous hospitalizations showed 69.93% of CDI patients compared to 38.81% in the non-CDI group (p = 0.029). The concomitant antibiotics exposure was higher among the CDI group versus the non-CDI group (88.65% vs. 68.42%, p = 0.037). Albumin levels were ≤ 25 g/L among 39.57% of the CDI patients and 21.71% in the non-CDI patients (p = 0.021). The clinical manifestations of CDI ranged from mild diarrhea (26.9%) to severe diarrhea (63.49%) and a complicated form of colitis (9.81%). Regarding outcomes, 79.14% of the CDI patients recovered and 20.86% had fatal outcomes in-hospital. Although a minority of the patients were in the non-CDI group, the difference in mortality rate between the CDI and non-CDI group was not statistically significant (20.86% vs. 15.13%, p = 0.097). Conclusions: Elderly patients on concomitant antibiotic treatments with hypoalbuminemia and with previous healthcare exposures were the most affected by COVID-19 and CD co-infections.
Deformation Behavior of Two-Phase Gradient Nanograined Fe95Ni5 Alloys under Different Types of Loading
Authors: Korchuganov Aleksandr , Kryzhevich Dmitrij , Zolnikov Konstantin
Published: September 2022

In this paper, we used molecular dynamics simulations to study the atomic mechanisms of phase transformations, plasticity features, and mechanical properties of two-phase Fe95Ni5 (at. %) samples with a gradient nanograined structure under uniaxial deformation and shear. The simulated samples with a uniform distribution of Ni atoms are composed of fcc grains from 10 to 30 nm in size, which in turn contain bcc interlayers in the form of lamellae of various distribution and size. It was shown that uniaxial loading or shear causes the bcc-fcc phase transformation in the lamellae. In the vast majority of cases, phase transformations are initiated at the junction of lamellae and grain boundaries. Deformation-induced phase transformations in lamellae occur at the front of bands propagating from grain boundaries. Grains larger than ~15 nm can have several bands or regions with differently orientated fcc lattices, whose meeting results in grain fragmentation. It was found that the atomic volume increases abruptly during the bcc-fcc structural phase transformation. The Kurdyumov–Sachs orientation relation is valid between the initial bcc and formed fcc structures. It was shown that the volume fraction and spatial distribution of the bcc phase significantly affect the yield stress of the sample. The yield stress can be increased by forming the bcc phase only in large-grained layers. This behavior is associated with the fragmentation of large grains, and consequently with grain refinement, which, in accordance with the Hall–Petch relation, improves the strength of the material.
A Cohort Study of the Effects of Daily-Diet Water-Soluble Dietary Fiber on Butyric Acid-Producing Gut Microbiota in Middle-Aged and Older Adults in a Rural Region
Authors: Sato Satoshi , Chinda Daisuke , Shimoyama Tadashi , Iino Chikara , Kudo Sae , Sawada Kaori , Mikami Tatsuya , Nakaji Shigeyuki , Sakuraba Hirotake , Fukuda Shinsaku
Published: September 2022

Water-soluble dietary fiber is primarily a substrate for degradation of short chain fatty acids (SCFAs), particularly butyric acid, by gut microbiota. SCFAs have beneficial effects on the whole body. However, epidemiological studies on the association between water-soluble dietary fiber from daily food intake and butyric acid-producing bacteria are inconsistent. The purpose of this study was to determine the association between levels of water-soluble dietary fiber from daily food intake and gut microbiota, particularly butyric acid producers, in middle-aged and older adults in a rural area in Japan. We examined the effects of water-soluble dietary fiber intake on gut microbiota after adjusting for confounding factors. After propensity score matching, 520 subjects (260 in the low-intake group and 260 in the high-intake group) were selected. One year later after a follow-up survey, we re-classified the participants and again compared low- and high-intake groups. As a result, people with a high intake had a higher relative abundance of butyric acid-producing bacteria. It was also revealed that butyric acid-producing bacteria remained high in the group that maintained high intake the next year. We concluded that continuous intake of water-soluble dietary fiber from daily food is necessary to maintain sufficient amounts of butyric acid-producing bacteria.
Phylogenetic Diversity of Animal Oral and Gastrointestinal Viromes Useful in Surveillance of Zoonoses
Authors: Esposito Anthony Michael , Esposito Michelle Marie , Ptashnik Albert
Published: September 2022

Great emphasis has been placed on bacterial microbiomes in human and animal systems. In recent years, advances in metagenomics have allowed for the detection and characterization of more and more native viral particles also residing in these organisms. The digestive tracts of animals and humans—from the oral cavity, to the gut, to fecal excretions—have become one such area of interest. Next-generation sequencing and bioinformatic analyses have uncovered vast phylogenetic virome diversity in companion animals, such as dogs and cats, as well as farm animals and wildlife such as bats. Zoonotic and arthropod-borne illnesses remain major causes of worldwide outbreaks, as demonstrated by the devastating COVID-19 pandemic. This highlights the increasing need to identify and study animal viromes to prevent such disastrous cross-species transmission outbreaks in the coming years. Novel viruses have been uncovered in the viromes of multiple organisms, including birds, bats, cats, and dogs. Although the exact consequences for public health have not yet become clear, many analyses have revealed viromes dominated by RNA viruses, which can be the most problematic to human health, as these genomes are known for their high mutation rates and immune system evasion capabilities. Furthermore, in the wake of worldwide disruption from the COVID-19 pandemic, it is evident that proper surveillance of viral biodiversity is crucial. For instance, gut viral metagenomic analysis in dogs has shown close relationships between the highly abundant canine coronavirus and human coronavirus strains 229E and NL63. Future studies and vigilance could potentially save many lives.
The Effect of Anaerobically Cultivated Human Intestinal Microbiota Compared to Fecal Microbiota Transplantation on Gut Microbiota Profile and Symptoms of Irritable Bowel Syndrome, a Double-Blind Placebo-Controlled Study
Authors: Mazzawi Tarek , Hausken Trygve , Refsnes Per Førde , Hatlebakk Jan Gunnar , Lied Gülen Arslan
Published: September 2022

Fecal microbiota transplantation (FMT) from healthy donors has been shown to improve the symptoms of irritable bowel syndrome (IBS) and changes the profile of the gut microbiota for the recipients. Alternatively, anaerobically cultivated human intestinal microbiota (ACHIM) can be used to manipulate the gut microbiota. The aim of the current study was to compare the efficacy and safety of ACHIM suspension with donor-FMT and placebo (patient’s own feces) to treat IBS. Out of the 62 originally included eligible patients with diarrhea-predominant IBS and their respective donors, only 43 patients completed the study by answering the questionnaires and delivering fecal samples before transplantation and after 1, 4, 12 and 24 weeks. The patients were randomized into three subgroups for receiving ACHIM suspension (n = 17), donor-FMT (n = 11), or placebo (n = 15), and were followed up for 24 weeks. Fecal samples were analyzed by sequencing 16S rRNA gene using the GA-map Dysbiosis Test (Genetic Analysis AS, Oslo, Norway). IBS symptom questionnaires improved in all three subgroups. Bacterial strain signals in IBS patients were more significant for Actinobacteria spp. and Bifidobacteria spp. after receiving donor-FMT compared to placebo and for Alistipes onderdonkii before and after treatment in the subgroups of ACHIM and donor-FMT vs. placebo. These signals change after treatment with ACHIM suspension and donor FMT towards those measured for healthy controls, but not after placebo. IBS symptom questionnaires improved in all three forms of transplantation. Some bacterial strain signals were significantly different between ACHIM and donor-FMT vs. placebo. However, the placebo subgroup failed to change the gut microbiota towards signals measured for healthy controls. The safety and efficacy of ACHIM and donor-FMT seems similar in the current study, but further larger studies are needed.