bluuebunny/crossref_metadata_2025 huggingface dataset:
Interfacial Debonding Detection in Concrete-Filled Steel Tubular (CFST) Columns with Modal Curvature-Based Irregularity Detection Indices
Authors: Khanahmadi Mohtasham , Khalighi Masoud
Published: September 2023

This study investigates the effect of concrete-steel debonding on the modal dynamic properties, i.e. frequency values and vibration mode shapes, and deals with the identification of interfacial debonding zones in CFST columns. In this context, debonding, defined as a decrease in concrete stiffness at the connection with the steel tube by a depth of 3 mm, was analyzed through the frequency analysis of the column. The findings indicate that debonding results in a discernible disparity between the primary and secondary mode shapes, as assessed by the Modal Assurance Criterion (MAC). Furthermore, there is a reduction in the frequency values across all modes. This paper proposes the irregularity detection indices of the Modal Curvature Index (MCI), Modal Curvature-Slope Index (MCSI) and Modal Curvature-Curvature Index (MCCI) using the concept of curvature to detect the debonding zones. These indices indicate the relative extreme values of irregularities in debonding zones for all modes, such that the MCSI and MCCI show an increase in the height of irregularities regardless of negative or positive signs in a debonding zone as the damage severity in that zone increases.
The subfield metric and its application to quantum error correction
Authors: Grassl Markus , Horlemann Anna-Lena , Weger Violetta
Published: September 2023

We introduce a new weight and corresponding metric over finite extension fields for asymmetric error correction. The weight distinguishes between elements from the base field and the ones outside of it, which is motivated by asymmetric quantum codes. We set up the theoretic framework for this weight and metric, including upper and lower bounds, asymptotic behavior of random codes, and we show the existence of an optimal family of codes achieving the Singleton-type upper bound.
Characterization of the unit group of ℤ[G × C2n]
Authors: Sharma R. K. , Gupta Abhinay Kumar
Published: September 2023

Let [Formula: see text] be a group and [Formula: see text] be the cyclic group of order 2. We characterize the unit group [Formula: see text] of the integral group ring [Formula: see text] in terms of the unit group [Formula: see text], for every positive integer [Formula: see text]. As a consequence, for each [Formula: see text], we determine conditions on some class of matrices [Formula: see text]s, to be in GL[Formula: see text]. Using this we calculate the integer solutions of some specific class of symmetric polynomial [Formula: see text] with integer coefficients.
Linear codes invariant under cyclic endomorphisms
Authors: Ou-azzou Hassan , Najmeddine Mustapha , Aydin Nuh
Published: September 2023

In this paper, we study linear codes invariant under a cyclic endomorphism [Formula: see text] called [Formula: see text]-cyclic codes. Since every cyclic endomorphism can be represented by a cyclic matrix with respect to a given basis, all of these matrices are similar. For simplicity we restrict ourselves to linear codes invariant under the right multiplication by a cyclic matrix [Formula: see text] that we call [Formula: see text]-cyclic codes, and when [Formula: see text] is the companion matrix [Formula: see text] of a given nonzero polynomial [Formula: see text] we call them [Formula: see text]-cyclic codes. The similarity relation between matrices helps us find connections between [Formula: see text]-cyclic codes and [Formula: see text]-cyclic codes, where [Formula: see text] is the minimal polynomial of [Formula: see text] The class of [Formula: see text]-cyclic codes contains cyclic codes and their various generalizations such as constacyclic codes, right and left polycyclic codes, monomial codes, and others. As common in the study of cyclic codes and their generalizations, we make use of the one-to-one correspondence between [Formula: see text]-cyclic codes and ideals of the polynomial ring [Formula: see text] where [Formula: see text] is the minimal polynomial of [Formula: see text] This correspondence leads to some basic characterizations of these codes such as generator and parity check polynomials among others. Next, we study the duality of these codes, where we show that the [Formula: see text]-dual of an [Formula: see text]-cyclic code is an [Formula: see text]-cyclic code, where [Formula: see text] is the adjoint matrix of [Formula: see text] with respect to [Formula: see text] and we explore some important results on the duality of these codes. Finally, we give examples as applications of some of the results and we construct some optimal codes.
DEVELOPMENT OF SMART 1RM MEASUREMENT SYSTEM FOR IMPROVEMENT OF SKELETAL MUSCLE FUNCTION OF THE ELDERLY
Authors: SEO SHIN-BAE , KANG SEUNG-ROK , JEONG HO-CHOON , YU MI , KWON TAE-KYU
Published: September 2023

In this study, we aimed to provide safe exercises with automatic service for easy access to active seniors, develop Smart One Repetition Maximum (1RM) measurement system applying electronic load that can reduce injuries, and optimize exercise effects by accurately evaluating physical functions and exercise effects. In this study, a smart, customized exercise and 1RM measurement system was developed to improve and maintain the daily living ability of healthy older adults. This system applies a power brake to provide a safe and detailed exercise load for older adults and consists of six types of exercises, including leg extension, leg press, long pull, in and out thigh, abdominal, and chest press exercises. The subjects of this study were 30 adults aged 65 years or older who had no history of musculoskeletal or nervous system disorders in the past 6 months and who attended an elderly fitness center in Gwangju city. Whole-body aerobic exercise was performed using a sedentary bicycle for 20[Formula: see text]min before exercise. Exercise load was performed by converting the weight of 30RM based on the 1RM measured before evaluation. The exercises were chest press, long pull, abdominal flexion, hip adduction, leg extension, and leg press. All the exercises were performed 30 times in a set, three sets a day, 3–5 times a week, with 5[Formula: see text]min of rest between workouts. As a result of the experiment, the maximum muscle strength for all exercise modes increased significantly ([Formula: see text]), and a safe muscle strength enhancement effect for the elderly was observed. These results suggest that the smart, customized exercise system developed in this study can positively result in a safe increase in the muscle strength of the elderly.
A SENTIMENT ANALYSIS MODEL FOR ELECTROENCEPHALOGRAM SIGNALS OF STUDENTS IN UNIVERSITIES USING A CONVOLUTIONAL NEURAL NETWORK AND SUPPORT VECTOR MACHINE MODELS
Authors: FAN XUEZHI , ZHANG JIE , YANG MENGTING
Published: September 2023

Sentiment analysis in teaching evaluation has significant implications. By analyzing students’ sentiments toward instructors, educational institutions can gain valuable insights into teaching effectiveness. These data can guide curriculum development, instructional improvements, and faculty training initiatives. Positive sentiment indicates effective teaching methods, engagement, and student satisfaction; negative sentiment flags areas that need attention. Sentiment analysis can help identify patterns, trends, and outliers, aiding in targeted interventions and personalized support. It also enables comparisons across different courses, instructors, and departments. However, it is crucial to ensure the accuracy and fairness of sentiment analysis algorithms, considering potential biases and the contextual nature of the feedback. This study proposes a sentiment classification model CNN–SVM that combines a convolutional neural network (CNN) and a support vector machine (SVM). Taking students majoring in art in comprehensive colleges and universities as the research object, by collecting the electroencephalogram (EEG) signals of students during teaching evaluation. CNN–SVM is used as the emotional analysis model to obtain the emotional analysis of teaching evaluation results. EEG is a typical physiological signal, and data based on this signal can more truly reflect student emotions. The adaptive CNN feature extraction function and the super generalization classification performance of SVM can reduce the individual differences and data noise between data, thereby improving sentiment classification performance. The experimental results demonstrate that using technology to analyze sentiment can assist educational institutions in more properly comprehending the feedback and opinions of students on instruction. With regard to sentiment analysis, the CNN–SVM method that is derived to produce the fusion algorithm has solid performance.
PROTECTIVE MECHANISM OF ALLEVIATING LUNG INJURY BY INHIBITING NF-κB PATHWAY
Authors: LIU NA , MA WEI-XING , QI JING , WANG YAN-XIA , REN GUI-FANG , YU PEI , XIE YU-HAN , XIAO LIN , LI ZONG-RUN
Published: September 2023

This review is to summarize the reports published in the past 10 years on the protective mechanism of 74 different intervention methods on lung injury through restraining nuclear factor kappa-B (NF-[Formula: see text]B) signaling pathway. We summarized the experimental studies on animal lung injury models of NF-[Formula: see text]B, MAPK/NF-[Formula: see text]B, PI3K/Akt/NF-[Formula: see text]B, TLR4/NF-[Formula: see text]B, NF-[Formula: see text]B/NALP3, NF-[Formula: see text]B/NLRP3 and other NF-[Formula: see text]B-related signal pathways. Lung injury leads to high mortality worldwide. Many potential mechanisms for the treatment and prevention of lung injury are still unclear. In addition to the use of lung protection strategies, currently, there are no effective drugs for lung injury treatment. Preemptive NF-[Formula: see text]B inhibition protects cells from damage, but inhibition at the decomposition stage delays tissue repair. Therefore, we think there is a need to conduct further studies that can provide more insights for future treatment and prevention of lung injury.
THE EFFECTS OF THE SLEEP THREE-NEEDLE ACUPUNCTURE TECHNIQUE ON ACUPOINT TEMPERATURE VARIATIONS IN PATIENTS WITH CHRONIC PRIMARY INSOMNIA: A RESEARCH PROTOCOL FOR A RANDOMIZED CONTROLLED TRIAL
Authors: LIU JIN , JIN YAN , FENG XIAOLAN , HUANG HUIXIA , CHANG SHAOQIONG , XU HONGWEI , CHEN XINGHUA
Published: September 2023

Background: Chronic primary insomnia (CPI) is a commonly encountered clinical disease, the incidence of which has been rising in recent years. In theoretical contexts, the temperature of acupoints in CPI patients is higher than that in unaffected individuals together with concomitant increases in fatigue index and intracranial arterial velocity. Acupuncture has long been used to treat insomnia, and the sleep three-needle acupuncture (STA) approach represents one promising such treatment for this condition. However, no studies to date have assessed the ability of this technique to lower acupoint temperature values or to improve the Insomnia Severity Index (ISI) in treated individuals. Methods: The present exploration is a prospective, randomized, assessor-blind, controlled trial. Totally, 102 adult patients with CPI will be recruited with varying levels of insomnia severity (mild, moderate, severe) and randomized into six equally sized groups. Patients in these groups will then undergo STA together with cognitive-behavioral therapy (CBT) or CBT alone. Acupuncture will be administered for 30[Formula: see text]min per treatment 2–3 times per week (7 days per cycle) for a maximum of 10 sessions in 4 cycles. All patients underwent CBT for 4 weeks. In addition, 17 patients will be recruited for a healthy control group. Primary outcomes will include acupoint temperature variations and ISI values, while secondary outcomes will include fatigue index values, intracranial arterial velocity, and Pittsburgh Sleep Quality Index (PSQI) values. Discussion: This study aims to test the theory that STA can lower acupoint temperatures and improve ISI values in CPI patients. Trial registration: Chinese Clinical Trial Registry ( http://www.chictr.org.cn ), ID: ChiCTR2100048704. Registered on 13/07/2021.
AUGMENTED REALITY-BASED NASAL ENDOSCOPE VIDEO RECONSTRUCTION AND REGISTRATION
Authors: FAN SIHAN , DAI XIAOKUN , JI XUEQIN , CHEN XINRONG
Published: September 2023

Neuroendoscopic surgery is a minimally invasive surgical technique commonly used to remove a tumor through the patient’s mouth or nose, which requires the surgeon to avoid important neural and vascular structures. Augmented reality-based surgical navigation can provide surgeons with more information and visual aids, clarifying the structure and details of the surgical area. It requires real-time registration of intraoperative endoscopic video with pre-operative CT models. However, 3D reconstruction and camera tracking from nasal endoscopic video are challenging due to the narrow nasal cavity and the lack of texture. Besides, the nasal endoscopic datasets that can be used for deep learning-based depth estimation are scarce and hard to elaborate. To this end, a style-augmented module (SAM) is proposed in this study to minimize discrepancies between different endoscopic datasets. An unsupervised approach was trained to generate depth maps and camera motion paths, which were used to reconstruct the nasal scene’s 3D model. The obtained reconstruction was aligned with a pre-operative CT model for augmented reality-based surgical navigation. The results showed that the proposed SAM improved the generalization of the depth estimation model on nasal endoscopy data. The proposed approach to combining augmented reality technology with surgical navigation is considered instrumental in furnishing surgeons with richer information on the nasal endoscopic surgical scene.
SUPER-RESOLUTION OF DIFFUSION MRI VIA JOINT CONSIDERATION OF SPATIAL AND ANGULAR SPACES USING GRAPH CNN
Authors: ZHU ZILU , MA JIQUAN , ZHANG CHI
Published: September 2023

Diffusion magnetic resonance imaging (dMRI) is an essential technique for studying brain white matter. However, its application suffers from the tradeoff between resolution, signal-to-noise ratio (SNR), and scanning time. Under a given setting, post-acquisition super-resolution (SR) has displayed the exciting performance of increasing the spatial or angular resolution of dMRI without prolonging the acquisition time. dMRI is acquired from a heterogeneous space composed of the spatial domain (x-space) and the diffusion wave vector domain (q-space). We introduced a graph convolution neural network (GCNN) to fit the mapping from low-resolution (LR) dMRI to high-resolution (HR) counterpart by jointly considering x-space and q-space to make an effective learning in this non-Euclidean space to increase the spatial resolution. Real brain dMRI data were downloaded from the Human Connectome Project (HCP). Comparisons were made between different spaces, including x-space, q-space, and xq-space. The results indicated that the best performance was obtained when two spaces were considered jointly using GCNN. Compared with the traditional methods, our network fully used spatio-angular information to improve the quality of dMRI SR. Furthermore, some feature metrics, including fractional anisotropic mapping, fiber orientation distribution (FOD), and fiber tractography, were presented to support the improvement. The cross-phantom test on synthetic data generated by the Phantomas tool was performed to further evaluate our model. Extended experiments revealed that GCNN might serve as a new way of enhancing dMRI.
STUDIES ON MENTAL HEALTH RECOGNITION BASED ON DATA MINING AND TWIN LEARNING NETWORK
Authors: MA LIN , MA SHICHAO
Published: September 2023

This study was envisaged to develop a recognition method based on the data mining and twin network deep learning, in view of the recognition problems of the mental health data. Initially, the survey dataset was preprocessed using K-Means clustering and improved Apriori data mining methods. The Apriori data mining method was improvised, which significantly improved the pruning efficiency of the Apriori algorithm by introducing cumulative counting and address mapping tables. Subsequently, under the deep learning framework of the twin network, the reference dataset was included in the upper branch network and the survey dataset after clustering analysis, and data mining was included in the lower branch network. The upper branch network further integrated the channel self-attention mechanism, while the lower branch network further integrated the spatial self-attention mechanism. Based on various types of mental health data and reference datasets, identification experiments were conducted. The experimental results showed that the proposed method outperformed the Decision Tree (DT), Support Vector Machine (SVM), Convolutional Neural Network (CNN), and RNN methods using the four evaluation indicators of Precision, Recall, F1, and AUC. Furthermore, the developed method has higher pruning efficiency in data mining and higher accuracy in discriminating mental health.
Microstructural Characterization and Wear Studies of T6 Heat-Treated A6082 Composite Reinforced with Yttria-Stabilized Zirconia
Authors: Madhukumar K. , Balakumar G. , Chikkanna N. , Thyagaraj N. R.
Published: September 2023

This study focused on investigating the wear properties of a T6 heat-treated A6082 composite reinforced with Yttria-stabilized zirconia (YSZ). The primary objective was to assess how the reinforcement and heat treatment affected the wear parameters of the composite material. The base material chosen for the composite was A6082 alloy, which possesses excellent mechanical and tribological qualities. YSZ, known for its high hardness and wear resistance, was selected as the reinforcing phase. The T6 thermal treatment was applied to the A6082 composite to enhance its mechanical properties and induce precipitation hardening. To evaluate the wear characteristics of the composite, a pin-on-disc tribometer was utilized. This test setup represents real-world sliding contact conditions that the composite material might encounter. Several parameters were measured during the wear testing, including wear loss, friction coefficient, and wear mechanism, to assess the composite’s durability under abrasion. The results of the study demonstrated that increasing the YSZ concentration in the base alloy led to a reduction in material loss and friction coefficient. This improvement can be attributed to the hardness and wear-resistant properties of YSZ. The addition of YSZ reinforcement significantly enhanced the wear resistance of the T6 heat-treated A6082 composite. Furthermore, the T6 heat treatment process also improved the wear properties of the composite. Precipitation hardening occurred, resulting in improved mechanical qualities such as strength and hardness, ultimately leading to increased wear resistance. Microscopic analysis of the worn surfaces revealed that the wear mechanism of the composite shifted from severe abrasive wear to moderate adhesive wear after undergoing the T6 heat treatment. The transformation in wear mechanism is believed to be facilitated by the formation of strengthening precipitates during the heat treatment. These precipitates limited the amount of material lost during the wear test, thereby decreasing both material loss and friction coefficient. In summary, this study demonstrates that the addition of YSZ reinforcement and the T6 heat treatment process effectively enhance the wear properties of the A6082 composite. The presence of YSZ reduces material loss and friction coefficient, while the T6 heat treatment produces precipitation hardening, leading to improved wear resistance.
Entanglement recovery by weak measurement reversal in tripartite systems
Authors: Jan Munsif , Khan Niaz Ali
Published: September 2023

Entanglement protection from noisy environments is an essential task in practical quantum information and communication. In this paper, we investigate the entanglement recovery of an amplitude-damped tripartite GHZ state by a weak-measurement reversal procedure. In particular, we emphasize the key importance of the inequivalency of probability amplitudes of the tripartite system under the recovery technique. We explore the maximal and non-maximal tripartite entangled state scenarios under amplitude damping noise in the absence and presence of weak measurement reversal procedures. Importantly, the non-maximal entangled state turns out to be a good choice for the entanglement recovery via weak-measurement reversal procedure.
Nonlinear Soil Behavior Model in Localized Lagrange Multipliers Mixed Formulation (u,p) for Dynamical Analysis of Wind Turbine Coupled Systems
Authors: da Silva Junior Francisco Ilson , Cardoso Onézimo Carlos Viana
Published: September 2023

Coupled mechanical systems can be complex, especially if there are many systems connected together and nonlinearities are present. Soil-structure interaction refers to the interaction between a structure and the soil or foundation upon which it is built. This interaction is important because it can affect the behavior of the structure, particularly during earthquakes or other dynamic events. For the wind turbine foundation design, the soil should support the weight of a wind turbine and anchor it to the ground. This paper presents a nonlinear material behavior soil coupled to elastic structure in offshore conditions. The goal of this work is to develop a coupled structural finite element procedure using Localized Lagrange Multipliers (LLM) at idealized offshore wind turbines with nonlinear poroelastic model for soil foundation. In this work, an anisotropic sand constitutive model is used to describe the soil foundation behavior. This model is based in a critical state soil mechanics and bounding surface plasticity. Classical elasto-plasticity theory is used to obtain the soil stiffness. The numerical model is validated through a fully coupled model at classical problems results. The mixed formulation [Formula: see text] is used to model the interface frames between the domains. The momentum equilibrium and mass continuity equations are solved by algebraic equation system imposed by Lagrange multipliers methodology. In order to excite the system, aerodynamic forces are imposed in random wind velocity conditions. In another numerical case, the response of coupled system during shaking is simulated by a horizontal input motion at bottom of soil foundation. Some computational aspects are discussed and the numerical model is clarified. The classical Newton Method to solve nonlinear problems is used in a finite element approach. In addition, two foundation models are tested and time dynamic responses are evaluated for a range of physical parameters including the wind nature and soil properties.
An Anisotropy Honeycomb Structure with Reinforced Deformability and Stiffness
Authors: Feng Ning , Wang Shangbin , Tie Yuanhao , Biczo Andras , Huang Chongfu , Xie Weibo
Published: September 2023

In this work, by breaking the structural six-fold symmetry and isotropy, we propose a simple design to drastically improve the elastic deformability and stiffness of gardenia-shaped honeycomb (GSH) structures, with a lower structural relative density. In the developed structural design, the enhancement of the mechanical response is achieved by locally shortening the beams that caused the intracellular extrusion. Studies that focused on simultaneously strengthening the two above-mentioned characteristics are rarely seen. Unlike the isotropy of the previous GSH structures, the elastic modulus of the reinforced GSH (RGSH) structures in both two principal directions is investigated via performing a complete parametric study. To visualize the utterly different mechanical response between the GSH and RGSH structures, the elastic properties-comparison are presented theoretically, numerically, and experimentally. The developed structural reinforcing method, combining the stiffness and deformability regulation, provides a valuable way to redesign multifunctional lattice structures for meeting the various requirements regarding mechanical characteristics.
Discrete majorization-type inequalities, comparison of classic results with a recent result
Authors: Horváth László
Published: September 2023

In this paper, we examine the relationship between a recent new discrete majorization-type inequality and classical majorization-type inequalities. The multiplicative analog of the studied new inequality is also given, which is a wide generalization of Weyl’s inequality. As an application, we give a parametric refinement of Popoviciu’s version of the Petrović inequality.
Effect of silica morphology on rheological properties and stability of magnetorheological fluid
Authors: Chen Bingsan , Yang Minghan , Fan Chenglong , Yan Xiaoyu , Xu Yongchao , Li Chunyu
Published: September 2023

SiO2 is commonly used as an abrasive in optical devices and magnetorheological (MR) fluid. In this study, MR fluid with composite and free-state SiO2 were prepared. Composite magnetic particles of CIP@SiO2 were synthesized using the sol-gel method with tetraethyl orthosilicate (TEOS) as the silicon source. Performance test results showed that CIP@SiO2 MR fluid exhibited superior mechanical properties compared with CIP MR fluid under zero magnetic field conditions. However, under the influence of a magnetic field, the SiO2 shell weakened the response of CIP@SiO2 MR fluid to the magnetic field, whereas CIP MR fluid demonstrated better rheological properties. The addition of free-state SiO2 to CIP MR fluid significantly improved its rheological performance. At a volume fraction of 6% SiO2, the shear stress and viscosity reached their maximum values, and further increasing the volume fraction to 8% resulted in a noticeable decrease in rheological behavior. Stability improved with an increase in magnetizable particle content. The stability of CIP MR fluid at the same concentration was superior to that of CIP@SiO2 MR fluid, while free-state SiO2 had a notable enhancing effect on stability. Therefore, when SiO2 exists as a free-state abrasive, the rheological properties and stability of the MR fluid considerable improve.
Energy storage and relaxor behavior in (Pb0.8Ba0.2)[(Zn1/3Nb2/3)0.7Ti0.3]O3 ferroelectric ceramic
Authors: Peláiz-Barranco A. , Pérez-Martín Y. , García-Zaldívar O. , Gagou Y.
Published: September 2023

(Pb[Formula: see text]Ba[Formula: see text])[(Zn[Formula: see text]Nb[Formula: see text])[Formula: see text]Ti[Formula: see text]]O3 relaxor-type ferroelectric ceramics was obtained via classical solid-state reaction. The hysteresis loop results were discussed in the frame of ergodicity criterium around the characteristic ferroelectric relaxor freezing temperature. Slimer hysteresis loops were observed below the freezing temperature reflecting an ergodic relaxor behavior. Above this temperature, estimated around 223[Formula: see text]K for the studied system, larger and unsaturated like ferroelectric hysteresis loops were observed. This temperature also coincides with the slope change on maximum polarization and inflection point of remnant polarization curves. Energy storage, energy loss and efficiency values were determined in a wide temperature range. While the recoverable energy density shows relatively low values (0.23[Formula: see text]J/cm3), there are interesting behaviors for this parameter and for the efficiency, since the two physical quantities increase versus temperature and the efficiency even reaches the value of 97%.
Finite rank perturbations of heavy-tailed Wigner matrices
Authors: Diaconu Simona
Published: September 2023

One-rank perturbations of Wigner matrices have been closely studied: let [Formula: see text] with [Formula: see text] symmetric, [Formula: see text] i.i.d. with centered standard normal distributions, and [Formula: see text] It is well known [Formula: see text] the largest eigenvalue of [Formula: see text] has a phase transition at [Formula: see text]: when [Formula: see text] [Formula: see text] whereas for [Formula: see text] [Formula: see text] Under more general conditions, the limiting behavior of [Formula: see text] appropriately normalized, has also been established: it is normal if [Formula: see text] or the convolution of the law of [Formula: see text] and a Gaussian distribution if [Formula: see text] is concentrated on one entry. These convergences require a finite fourth moment, and this paper considers situations violating this condition. For symmetric distributions [Formula: see text] heavy-tailed with index [Formula: see text] the fluctuations are shown to be universal and dependent on [Formula: see text] but not on [Formula: see text] whereas a subfamily of the edge case [Formula: see text] displays features of both the light- and heavy-tailed regimes: two limiting laws emerge and depend on whether [Formula: see text] is localized, each presenting a continuous phase transition at [Formula: see text] respectively. These results build on our previous work which analyzes the asymptotic behavior of [Formula: see text] in the aforementioned subfamily.
New insights from nanoscale in-depth investigation into wettability modification in oil-wet porous media
Authors: Khosravi Vahid , Mahmood Syed Mohammad , Jeffry Lizrina Ludai Anak , Yeap Swee Pin , Ganat Tarek Al Arbi Omar , Rostami Amir
Published: September 2023

In the context of fluid-surface studies of oil reservoirs, wettability alteration plays an important role, especially in carbonate reservoirs. This investigation, utilizing molecular dynamics simulation, delves into the effect of oil movement during interactions with brine ions. The calculation of adsorption energy, radial distribution function, diffusion coefficient, and configurational changes of the NaCl brine molecules allowed for an examination of the role of ions in oil movement from an oil-wet calcite surface. Findings indicate that the polarity of oil has a marked influence on oil detachment, as evidenced by the more than 30% adsorption energy for the acrylic acid system compared to the decane system. The diffusion coefficient of Na[Formula: see text] ions in the acrylic acid system was found to be five times as high as in the decane system. Configuration changes showed that brine ions are more active — in a regular eight shape — in interacting with the acrylic acid-wet surface as opposed to the decane-wet surface. The hierarchical significance of oil polarity [Formula: see text] brine ions [Formula: see text] mineral surface in altering the wettability of the system demonstrates the significance of sodium ions in the presence of the polar oil component. The findings greatly contribute to the development of effective Smart Water flooding technology.
South Korea–Vietnam–India Trilateral Economic Cooperation: Prospects and Policy Implications
Authors: TRUONG HOAN QUANG , NGUYEN HUONG THI THU
Published: September 2023

Great attention has been paid to the bilateral economic relations between India, Vietnam, and South Korea; however, only scant research has focused on the prospects of triangular economic cooperation among the three countries. Given the advantage and demand for the cooperation of each party, there is significant potential for trilateral economic cooperation among South Korea, Vietnam, and India. In this paper, we discover the prospects for their triangular economic cooperation in three aspects. First, this study examines the potential for cooperation in production networks and supply chains between the three countries in the context of reconfiguring the global value chains (GVCs), with a focus on the leading role of South Korean multinational enterprises (MNEs). Second, the study explores trilateral cooperation in the digital economy and connectivity, focusing on how South Korea and India can collaborate on investment projects in Vietnam. Third, this study discusses the rationale and possibility of forming a regional trade agreement (RTA) between the three countries. South Korea, Vietnam, and India have extant bilateral trade agreements between two of the three countries; however, there is no regional integration among the three countries discussed in specific. Considering the bilateral relations and domestic and external factors, the paper reckons that an RTA for starters between the three countries would be mutually beneficial to each of the corresponding economies.
South Korea’s Economic Security: Prospects for Greater Cooperation with India
Authors: PACHECO PARDO RAMON
Published: September 2023

The economic security of middle powers across the world is being challenged by great power rivalry and, more recently, Russia’s invasion of Ukraine. One of the largest trade and investment countries globally, South Korea is amongst the middle powers most affected by these developments. In this context, South Korea needs to finetune its economic security strategy. One way of doing so is by diversifying its economic relations. In this respect, India, a fellow middle power and also one of the biggest economies in the world, is a key partner. Supply chains, trade, investment and human capital have all been benefiting from strengthening links between South Korea and India, and will be key moving forward as the former seeks to further boost its economic security. Indeed, South Korea and India have been strengthening their links in the intertwined areas of maritime security, cyber security, and economic security in recent years. This suggests that economic security is part of broader security cooperation between the two partners.
Locally and Structurally Private Graph Neural Networks
Authors: Joshi Rucha Bhalchandra , Mishra Subhankar
Published: September 2023

Graph Neural Networks (GNNs) are known to address such tasks over graph-structured data, which is widely used to represent many real-world systems. The collection and analysis of graph data using GNNs raise significant privacy concerns regarding disclosing sensitive information. Existing works in privacy-preserving GNNs ensure the privacy of nodes’ features and labels. However, its structure also needs to be privatized. To address this problem, we provide a method, Local Structural Perturbation Graph Neural Network, that adds noise to the neighborhood data of the node along with its features and label. Here, we perturb the graph structure by sampling non-neighboring nodes and randomizing them along with the neighborhood. We use differentially private mechanisms to perturb the structure of graphs with theoretical guarantees. This introduces the challenge of reducing the impact of noise in the neighborhood on accuracy. In this view, we use the
p
-hop neighborhood to compensate for the loss of actual neighbors in randomization.

We use the node and label privacy as implemented in the previous methods for privacy in GNNs. We conduct extensive experiments over real-world datasets to show the impact of perturbation on the graph structure. We also perform the theoretical analysis of our proposed method.
A Highly Efficient Photoelectrochemical Sensor for Detection of Salicylic Acid Based on CuS-NiFe-LDH/rGO
Authors: Zhang Youjian , Wu Yuguo , Xue Ming , Chen Pei , Li Dandan
Published: September 2023

Salicylic acid (SA) is effective in the treatment of coronary heart disease. In this study, a novel PEC sensor was prepared to specifically detect SA, and copper sulfide-layered double hydroxide/reduced graphene oxide (CuS-LDH/rGO) with visible light activity was chosen as the identification element and photoactive material. The photocurrent response of CuS-LDH/rGO shows linear relationship with SA concentration over a range of 1–80 μM and 160–5760 μM, with a low limit of detection (LOD) (S/N = 3) of 0.35 μM. Therefore, the novel PEC-sensing strategy proposed in this study represents an ultra-sensitive method with high selectivity and stability for the detection of SA.
Experienced Nurses’ Motivation, Intention to Leave, and Reasons for Turnover: A Qualitative Survey Study
Authors: Hörberg Anna , Gadolin Christian , Skyvell Nilsson Maria , Gustavsson Petter , Rudman Ann
Published: September 2023

There is a global nurse shortage, and researchers have made great efforts in trying to unveil the reasons for turnover and how to increase retention. However, such research has had a tendency to study variables related to intention to leave (ITL) or turnover as isolated phenomena. Objective. To simultaneously explore what factors motivate experienced nurses in the workplace and the underlying reasons for strong ITL and high staff turnover within the profession. Design. An inductive qualitative content analysis was used based on data from open-ended survey questions. The data originated from the longitudinal analyses of nursing education/employment/entry (LANE) in work-life study. The qualitative data analyzed in this study were distributed in October 2017–January 2018, to all nurses in three cohorts corresponding to 11-, 13- and 15-year postgraduation. Of the 2,474 nurses answering the survey, 1,146 (46%) responded to one or more of the open-ended questions. Results. The result showed that what motivates experienced nurses, their intention to leave (ITL), and reasons for turnover could be described in the form of five broad categories, namely, organizational characteristics, work characteristics, relationships at work, work recognition, and health issues. There was rarely a one single reason described, rather several reasons needed to be experienced over time for nurses to stay motivated or leave the profession. Conclusions. There is no single reason that makes nurses leave the profession, nor is there one single reason that makes them motivated to stay. Retention and turnover are complex processes and need to be addressed as this, not as a single isolated phenomenon.
Mercury and Parkinson’s Disease: Promising Leads, but Research Is Needed
Authors: Torrey E. Fuller , Simmons Wendy
Published: September 2023

Environmental toxicants are thought to play a major role in the pathogenesis of Parkinson’s disease. In reviewing the literature on heavy metals known to be toxicants, we noted several recent studies on mercury suggesting a possible role in the etiology of some cases of this disease. We therefore undertook a review of this association, focusing especially on peer-reviewed articles to avoid the bias inherent in much of the literature regarding mercury. For most people, our contemporary exposure to mercury comes from dental amalgam tooth restorations and from eating fish contaminated with mercury. In both cases, mercury is known to get into the brain in utero and at all ages. It remains in the brain for many years and is known to produce permanent neuropsychological deficits. Mercury toxicity can produce tremors and other Parkinsonian clinical symptoms. It can also produce neurochemical and neuropathological changes similar to those found in Parkinson’s disease, including the loss of dopamine neurons, degeneration of tubulin and axons, dysfunction of mitochondria, and the aggregation of alpha-synuclein. Relatively few studies have assessed mercury in parkinsonian patients, but almost all reported a statistically significant association. Published studies suggest some promising leads in the relationship between mercury exposure and Parkinson’s disease. However, studies of patients are relatively few, and the need for research is clear. A search of Parkinsonian research studies currently funded by the US National Institutes of Health, Parkinson’s Foundation, and the Michael J Fox Foundation yielded no studies on mercury. We believe such studies should be supported.
The Existence and Multiplicity of Solutions for
p

x

-Laplacian-Like Neumann Problems
Authors: Chu Changmu , Tang Ying
Published: September 2023

In the present paper, in view of the variational approach, we discuss the Neumann problems with

p

x

-Laplacian-like operator and nonstandard growth condition, originated from a capillary phenomena. By using the least action principle and fountain theorem, we prove the existence and multiplicity of solutions to the class of Neumann problems under suitable assumptions.
Subspace-Based Anomaly Detection for Large-Scale Campus Network Traffic
Authors: Zhao Xiaofeng , Wu Qiubing
Published: September 2023

With the continuous development of information technology and the continuous progress of traffic bandwidth, the types and methods of network attacks have become more complex, posing a great threat to the large-scale campus network environment. To solve this problem, a network traffic anomaly detection model based on subspace information entropy flow matrix and a subspace anomaly weight clustering network traffic anomaly detection model combined with density anomaly weight and clustering ideas are proposed. Under the two test sets of public dataset and collected campus network data information of a university, the detection performance of the proposed anomaly detection method is compared with other anomaly detection algorithm models. The results show that the proposed detection model is superior to other models in speed and accuracy under the open dataset. And the two traffic anomaly detection models proposed in the study can well complete the task of network traffic anomaly detection under the large-scale campus network environment.
Response Characteristics and Suppression of Transverse Vibrations of Mine Hoisting Conveyances Excited by Multiple Faults
Authors: Yao Jiannan , Liu Di , Deng Xiaojie
Published: September 2023

The failures of steel guides can excite complex and intense transverse oscillations of hoisting containers in the mine hoisting process. The present paper mainly contributes to reveal the response characteristics of the transverse oscillations of mine conveyances excited by various faults such as interface misalignment, local bulge, orbital gap, bending deformation, and orbital tilt. First, a rigid-flexible coupled virtual prototype model between the conveyance and the steel guide was established. Subsequently, the vibration response characteristics of the container under various single and coupling excitations were simulated and analyzed. Eventually, a new type of roller cage shoe with a magnetorheological damper was put forward to decrease the transverse impact responses. Based on the hyperbolic tangent model of magnetorheological dampers, a semiactive fuzzy PID method was studied to explore the vibration suppression of the container. The results showed the fuzzy PID method can play a good role in the vibration reduction. This paper can give a fine scheme for the virtual simulation and semiactive vibration control of the mine hoisting system.
Determination of Methanol, Acetaldehyde, and Ethyl Acetate in Thousand Folds of Ethanol Sample by Headspace Gas Chromatography with Mass Spectrometry
Authors: Thang Nguyen Quoc , Tan Le Van
Published: September 2023

Alcohol beverages have been widely consumed in several parts of the world. In this study, volatile organic compounds in alcoholic beverages including acetaldehyde, ethyl acetate, methanol, and higher ethanol were investigated and evaluated using a headspace gas chromatograph equipped with a mass spectrometer. This study evaluated the suitability of the chromatographic system, linearity, limit of detection, and limit of quantification, accuracy, and precision of the single and simultaneous determination of acetaldehyde, ethyl acetate, and methanol in thousand folds of ethanol. Results showed that the acetaldehyde concentration in local beer samples and local manual product liqueur samples ranged from 4.65 to 13.22 mg/L and from 5.55 to 75.96 mg/L, respectively, but in local industrial product liqueur samples, acetaldehyde was not detected. Methanol was only detected in a few local beer samples and locally manually produced liqueur samples within low concentrations. Ethyl acetate was only detected in all local beer samples, but it was not present in local industrial product liqueur samples.
Unveiling Neuroprotective Potential of Spice Plant-Derived Compounds against Alzheimer’s Disease: Insights from Computational Studies
Authors: Alom Md. Murshid , Bonna Rejwana Parvin , Islam Ariful , Alom Md. Wasim , Rahman Md. Ekhtiar , Faruqe Md Omar , Khalekuzzaman Md. , Zaman Rashed , Islam Md. Asadul
Published: September 2023

Alzheimer’s disease (AD) is a serious threat to the global health care system and is brought on by a series of factors that cause neuronal dysfunction and impairment in memory and cognitive decline. This study investigated the therapeutic potential of phytochemicals that belong to the ten regularly used spice plants, based on their binding affinity with AD-associated proteins. Comprehensive docking studies were performed using AutoDock Vina in PyRx followed by molecular dynamic (MD) simulations using AMBER 14. The docking study of the chosen molecules revealed the binding energies of their interactions with the target proteins, while MD simulations were carried out to verify the steadiness of bound complexes. Through the Lipinski filter and admetSAR analysis, the chosen compounds’ pharmacokinetic characteristics and drug likeness were also examined. The pharmacophore mapping study was also done and analyzed for best selected molecules. Additionally, principal component analysis (PCA) was used to examine how the general motion of the protein changed. The results showed quercetin and myricetin to be potential inhibitors of AChE and alpha-amyrin and beta-chlorogenin to be potential inhibitors of BuChE, exhibiting best binding energies comparable to those of donepezil, used as a positive control. The multiple descriptors from the simulation study, root mean square deviation (RMSD), root mean square fluctuation (RMSF), hydrogen bond, radius of gyration (Rg), and solvent-accessible surface areas (SASA), confirm the stable nature of the protein-ligand complexes. Molecular mechanic Poisson-Boltzmann surface area (MM-PBSA) binding free energy calculations indicated the energetically favorable binding of the ligands to the protein. Finally, according to pharmacokinetic properties and drug likeness, characteristics showed that quercetin and myricetin for AChE and alpha-amyrin and beta-chlorogenin for BuChE were found to be the most effective agents for treating the AD.
An ensemble based data mining model for contingency analysis of power system under STLO
Authors: Angadi Ravi V. , Mangai J. Alamelu , Manohar V. Joshi , Daram Suresh Babu , Rao Paritala Venkateswara
Published: September 2023

In a large, interconnected power system, contingency analysis is a useful tool for pinpointing the potential consequences of post-event scenarios on the system's safety. In this work, the Newton-Raphson technique is applied to every single outage of a transmission line to compute the load flows. For the static security classification of the power system, the line voltage stability performance index (LVSI) is used. There are three levels of static security of power system namely: non-critical (the least severe), semi-critically insecure (the next lowest severe), and critical (the next highest severe). The various data mining techniques such as decision trees, bagging-based ensemble methods, and boosting-based ensemble methods were applied to assess the severity of the line under various loading and contingency conditions. Test systems based on the IEEE 30 bus system were used with the proposed machine learning classifiers. The experimental results proved that bagging based ensemble method provided better accuracy compared to the decision tree and the AdaBoost ensemble method for predicting the power system security assessment. The bagging-based ensemble method has a predictive accuracy of 85% and an AUC of 0.94.