bluuebunny/crossref_metadata_2025 huggingface dataset:
Adolescent Knowledge, Attitudes and Practices of Healthy Eating: Findings of Qualitative Interviews among Hong Kong Families
Authors: Liu Kiki S. N. , Chen Julie Y. , Sun Kai-Sing , Tsang Joyce P. Y. , Ip Patrick , Lam Cindy L. K.
Published: July 2022

To tackle unhealthy eating among adolescents, it is crucial to understand the dietary knowledge, attitudes, and practices (KAP) on which adolescent eating habits are based. This qualitative study identifies the gaps in KAP by exploring what Chinese adolescents know, perceive, and practice regarding healthy eating to better inform targeted interventions for this important health problem. Parent–adolescent dyads were purposively sampled based on, for example, the dietary intake, age, and gender of the adolescent and household income, and each completed a 30 to 60 min interview. Twelve themes were synthesized: knowledge: (1) dietary recommendations, (2) health outcomes of healthy eating, (3) nutrition content in food, and (4) access to healthy meals; attitudes: (5) outcome expectation for healthy eating, (6) food preferences, and (7) self-efficacy regarding adopting healthy eating; and practices: (8) going grocery shopping for healthy food, (9) eating home-prepared meals. (10) eating out in restaurants or consuming takeaway food, (11) fruit and vegetable consumption, and (12) snacking, perceived unhealthy eating to be low risk, made unhealthy choices regarding snacking and eating out, and had insufficient fruit and vegetable intake. Programs should emphasize the positive short-term health outcomes of healthy eating and empower adolescents to acquire food preparation skills to sustain healthy eating habits.
De-Implementation of Detrimental Feeding Practices in Childcare: Mixed Methods Evaluation of Community Partner Selected Strategies
Authors: Swindle Taren , Rutledge Julie M. , Zhang Dong , Martin Janna , Johnson Susan L. , Selig James P. , Yates Amy M. , Gaulden Daphne T. , Curran Geoffrey M.
Published: July 2022

This pilot evaluated strategies to decrease detrimental feeding practices in early care and education, which are hypothesized to compete with evidence-based feeding and obesity prevention practices. This study made two key comparisons: (1) a between-site comparison of sites receiving (a) no implementation or de-implementation strategies (i.e., Basic Support; B), (b) implementation strategies only (i.e., Enhanced Support; E), and (c) implementation and de-implementation strategies (i.e., De-implementation + Enhanced Support; D + E) and (2) a within-site pre-post comparison among sites with D + E. At nutrition lessons, the D + E group had more Positive Comments (Hedege’s g = 0.60) and higher Role Model fidelity (Hedege’s g = 1.34) compared to the E group. At meals, assistant teachers in the D + E group had higher Positive Comments than in the B group (g = 0.72). For within-group comparisons, the D + E group decreased Negative Comments (t(19) = 2.842, p = 0.01), increased Positive Comments (t(20) = 2.314, p = 0.031), and improved use of the program mascot at nutrition lessons (t(21) = 3.899, p = 0.001). At meals, lead teachers’ Negative Comments decreased (t(22) = 2.73, p = 0.01). Qualitative data identified strengths and opportunities for iteration. Despite a COVID interruption, mid-point comparisons and qualitative feedback suggest promise of the de-implementation strategy package.
Fabrication, In Vitro and In Vivo Evaluation of Non-Ordered Mesoporous Silica-Based Ternary Solid Dispersions for Enhanced Solubility of Flurbiprofen
Authors: Munir Muhammad Usman , Ikraam Mahnoor , Nadeem Muhammad , Khalid Syed Haroon , Asghar Sajid , Khalid Ikrima , Irfan Muhammad , Islam Nayyer , Ajaz Nyla , Khan Ikram Ullah
Published: July 2022

The aim of this study was to improve the solubility and prevent the ulcerogenic effect of flurbiprofen. Initially, binary and ternary solid dispersions (BSDs and TSDs) of flurbiprofen were prepared by using non-ordered mesoporous silica and gelucire. After preformulation testing (solubility, flow properties, % yield, and entrapment efficiency), four formulations were selected for further detailed studies. Solid-state characterization of optimized formulations (S1, S6, S7, and S12) showed successful drug incorporation in the solid dispersion at the molecular state without any noticeable interactions. The in vitro solubility and release study showed an increase in solubility and 98–100% of drug release in 30–45 min. The in vivo gastro-protective effect of the optimized formulations containing flurbiprofen and silica (1:1) with 25% w/w gelucire (S6 and S12) showed a reduction in the gastric lesion index (GLI) after four days of treatment. Moreover, histological images of the stomach lining (S6 and S12) illustrated normal epithelial cells and a partially protected mucosal membrane. Thus, TSD exhibited a significant increase in solubility and the dissolution rate and reduced the gastric ulceration. Therefore, TSDs are dubbed as efficacious carriers to enhance the bioavailability of flurbiprofen while simultaneously reducing its side effects.
Design and Synthesis of New Hydantoin Acetanilide Derivatives as Anti-NSCLC Targeting EGFRL858R/T790M Mutations
Authors: Hassanin Moamen A. , Mustafa Muhamad , Abourehab Mohammed A. S. , Hassan Heba A. , Aly Omar M. , Beshr Eman A. M.
Published: July 2022

Epidermal Growth Factor Receptor (EGFR), its wild type and mutations L858R/T790M, is overexpressed in non-small cell lung cancer (NSCLC) patients and is considered an inevitable oncology target. However, while the potential EGFR inhibitors have been represented in the literature, their cellular activity failed to establish broad potency against EGFR and its mutations. This study identifies a new series of EGFRL858R/T790M inhibitors bearing hydantoin acetanilides. Most compounds revealed strong antiproliferative activity in a range of NSCL cancer models (A549, H1975, and PC9), in which 5a and 5f were the most potent. Compounds 5a and 5f possessed potent anticancer activity on H1975 cells with IC50 values of 1.94 and 1.38 µM, respectively, compared to 9.70 µM for erlotinib. Favorably, 5a and 5f showed low activity on WI-38 normal cells. Western blotting and an EGFR kinase assay test proved the significant EGFR inhibitory activity of 5a. Besides, active hydantoin derivative 5a strongly arrested the cell cycle at the sub G1 and S phases and triggered apoptosis in A549 cells. These results imply that 5a could be considered a promising lead compound for additional development as a potential active agent for anticancer therapy.
Glioblastoma Multiforme Selective Nanomedicines for Improved Anti-Cancer Treatments
Authors: Duskey Jason Thomas , Rinaldi Arianna , Ottonelli Ilaria , Caraffi Riccardo , De Benedictis Chiara Alessia , Sauer Ann Katrin , Tosi Giovanni , Vandelli Maria Angela , Ruozi Barbara , Grabrucker Andreas Martin
Published: July 2022

Glioblastoma Multiforme (GBM) is a devastating disease with a low survival rate and few efficacious treatment options. The fast growth, late diagnostics, and off-target toxicity of currently used drugs represent major barriers that need to be overcome to provide a viable cure. Nanomedicines (NMeds) offer a way to overcome these pitfalls by protecting and loading drugs, increasing blood half-life, and being targetable with specific ligands on their surface. In this study, the FDA-approved polymer poly (lactic-co-glycolic) acid was used to optimise NMeds that were surface modified with a series of potential GBM-specific ligands. The NMeds were fully characterised for their physical and chemical properties, and then in vitro testing was performed to evaluate cell uptake and GBM cell specificity. While all targeted NMeds showed improved uptake, only those decorated with the-cell surface vimentin antibody M08 showed specificity for GBM over healthy cells. Finally, the most promising targeted NMed candidate was loaded with the well-known chemotherapeutic, paclitaxel, to confirm targeting and therapeutic effects in C6 GBM cells. These results demonstrate the importance of using well-optimised NMeds targeted with novel ligands to advance delivery and pharmaceutical effects against diseased cells while minimising the risk for nearby healthy cells.
Simultaneous LC-ESI-MS/MS Quantification of Levosimendan and Its Metabolites for Therapeutic Drug Monitoring of Cardiac Surgery Patients
Authors: Kipka Hannah , Tomasi Roland , Hübner Max , Liebchen Uwe , Hagl Christian , Wanner Klaus T. , Mannell Hanna , Höfner Georg
Published: July 2022

Levosimendan is used in severe chronic cardiac insufficiency, also within the peri-operative setting. Real-life pharmacokinetic data in surgical patients is lacking, making therapeutic drug monitoring (TDM) of levosimendan, its pharmacologically active metabolite OR-1896, and its intermediate OR-1855 important. A simultaneous highly sensitive quantification of levosimendan and its metabolites in small-volume samples has not yet been described. Here, levosimendan (LLOQ 0.450 nM), OR-1896, and OR-1855 (LLOQ both 1.0 nM) were successfully quantified by LC-ESI-MS/MS after liquid-liquid extraction in 300 µL of blood. A short C8 column under reversed-phase conditions enabled simultaneous and fast quantification of levosimendan in the negative and the metabolites in the positive ionization mode in a single run within 2 min. Interestingly and unexpectedly, constitutional isomers of levosimendan metabolites with identical mass transitions and similar retention times were observed in surgical patients’ samples, which we identified as the metamizole metabolites 4-aminoantipyrine and 4-acetamidoantipyrine. A longer C8 column and a modified mobile phase enabled selective quantification of all analytes in a single run within 7 min. We developed, validated, and applied highly sensitive LC-ESI-MS/MS methods for simultaneous quantification of levosimendan and its metabolites, enabling efficient TDM of cardiac surgery patients even with additional metamizole administration.
Mono and Multiple Tumor-Targeting Ligand-Coated Ultrasmall Gadolinium Oxide Nanoparticles: Enhanced Tumor Imaging and Blood Circulation
Authors: Ho Son Long , Yue Huan , Lee Sangyeol , Tegafaw Tirusew , Ahmad Mohammad Yaseen , Liu Shuwen , Saidi Abdullah Khamis Ali Al , Zhao Dejun , Liu Ying , Nam Sung-Wook , Chae Kwon Seok , Chang Yongmin , Lee Gang Ho
Published: July 2022

Hydrophilic and biocompatible PAA-coated ultrasmall Gd2O3 nanoparticles (davg = 1.7 nm) were synthesized and conjugated with tumor-targeting ligands, i.e., cyclic arginylglycylaspartic acid (cRGD) and/or folic acid (FA). FA-PAA-Gd2O3 and cRGD/FA-PAA-Gd2O3 nanoparticles were successfully applied in U87MG tumor-bearing mice for tumor imaging using T1 magnetic resonance imaging (MRI). cRGD/FA-PAA-Gd2O3 nanoparticles with multiple tumor-targeting ligands exhibited higher contrasts at the tumor site than FA-PAA-Gd2O3 nanoparticles with mono tumor-targeting ligands. In addition, the cRGD/FA-PAA-Gd2O3 nanoparticles exhibited higher contrasts in all organs, especially the aorta, compared with those of the FA-PAA-Gd2O3 nanoparticles, because of the blood cell hitchhiking effect of cRGD in the cRGD/FA-PAA-Gd2O3 nanoparticles, which prolonged their circulation in the blood.
Silencing of a Cotton Actin-Binding Protein GhWLIM1C Decreases Resistance against Verticillium dahliae Infection
Authors: Cao Tingyan , Qin Minghui , Zhu Shuai , Li Yuanbao
Published: July 2022

LIM proteins are widely spread in various types of plant cells and play diversely crucial cellular roles through actin cytoskeleton assembly and gene expression regulation. Till now, it has not been clear whether LIM proteins function in plant pathogen defense. In this study, we characterized a LIM protein, GhWLIM1C, in upland cotton (Gossypium hirsutum). We found that GhWLIM1C could bind and bundle the actin cytoskeleton, and it contains two LIM domains (LIM1 and LIM2). Both the two domains could bind directly to the actin filaments. Moreover, the LIM2 domain additionally bundles the actin cytoskeleton, indicating that it possesses a different biochemical activity than LIM1. The expression of GhWLIM1C responds to the infection of the cotton fungal pathogen Verticillium dahliae (V. dahliae). Silencing of GhWLIM1C decreased cotton resistance to V. dahliae. These may be associated with the down regulated plant defense response, including the PR genes expression and ROS accumulation in the infected cotton plants. In all, these results provide new evidence that a plant LIM protein functions in plant pathogen resistance and the assembly of the actin cytoskeleton are closely related to the triggering of the plant defense response.
Grapevine Pinot Gris Virus Is Present in Different Non-Vitis Hosts
Authors: Demian Emese , Jaksa-Czotter Nikoletta , Varallyay Eva
Published: July 2022

Grapevine Pinot gris virus (GPGV) was described in Italy using a metagenomic approach: next-generation sequencing of the virus-derived small RNAs. Since that time, it has been reported all over the world. The presence of GPGV is associated with grapevine disease, but most of the time, the disease is asymptomatic. Although the host range of this virus has not been investigated, it has been found in the non-Vitis hosts, Silene latifolia and Chenopodium album. We investigated the presence of GPGV in grapevine and other plant species growing as weeds in the vineyard. Using RT-PCR, we identified GPGV in seven non-Vitis hosts: Ailanthus, Asclepias, Crataegus, Fraxinus, Rosa, Rubus, and Sambucus. In the case of Rosa and Rubus, this finding was supported by Northern blot detection of the virus. GPGV strains in non-Vitis hosts belong to the asymptomatic clade, and are clustered according to their original geographic locations. The presence of GPGV in species other than grapevine shows that besides well-known vector and propagating material-based infections, other possible entry sites for the virus can exist, which have to be taken into consideration when developing reliable regulation strategies.
Understanding the Interaction of Lignosulfonates for the Separation of Molybdenite and Chalcopyrite in Seawater Flotation Processes
Authors: Quiroz Consuelo , Murga Romina , Giraldo Juan David , Gutierrez Leopoldo , Uribe Lina
Published: July 2022

The selective separation of molybdenite from copper sulfide concentrate in flotation process is realized using sodium hydrosulfide (NaHS) to depress the chalcopyrite and permit only the flotation of the molybdenite. However, this reagent is a highly toxic and flammable gas. The objective of this research was to study the feasible application of commercial lignosulfonates (LSs) in the separation by froth flotation process of molybdenite and chalcopyrite in seawater to present a novel application for LSs, as well as an alternative reagent to sodium hydrosulfide (NaHS). To achieve this, microflotation, absorbance tests and zeta potential measures were performed at pH 8 in seawater and 0.01 M NaCl. The results obtained in this study showed that it is possible to achieve selective separation of copper and molybdenum in both aqueous media due to high depressant effect of molybdenite and low depression of chalcopyrite in microflotation tests at 10 ppm of LSs, when the collector, PAX, is added prior to the addition of LSs. Absorbance study and zeta potential measurements showed that LSs adhere more to the molybdenite surface in seawater than in freshwater. This is related to the high ionic charge of the media that influences a greater interaction of LSs with the mineral surface.
On the Use of Dolomite as a Mineral Filler and Co-Filler in the Field of Polymer Composites: A Review
Authors: Ahmad Fauzi Asfa Amalia , Osman Azlin Fazlina , Alrashdi Awad A. , Mustafa Zaleha , Abdul Halim Khairul Anwar
Published: July 2022

Polymers are being used in many applications all around the world. However, there are some drawbacks in the properties of polymers that could hamper their usage in certain applications. Therefore, a new material polymer composite was introduced. A polymer composite is a polymer-based material with the addition of a filler. Many researchers have reported the improvement in the properties of a polymer when a filler was introduced. This helps minimize the disadvantages of using a polymer. As a result, polymer composite products can be used in many industries, such as automobile, aerospace, biomedical, and packaging. Fillers derived from natural minerals, such as dolomite, are among the best reinforcement materials for polymeric materials because they are plentiful and low cost, have high rigidity and hardness, and even have tailorable surface chemistry. The use of dolomite as a filler in a polymer composite system has gained increasing attention in recent years after researchers successfully proved that it is capable of improving the mechanical, physical, and thermal properties of various polymeric materials. However, chemical or physical treatment/modification of raw dolomite is needed in order to prepare it as an efficient reinforcing filler. This procedure helps to improve the performance of the resultant polymer composites. This article reviews the usage of dolomite as a filler in a variety of polymeric materials and how it improved the performance of the polymer composite materials. It also highlights several methods that have been used for the purpose dolomite’s treatment/modification. Furthermore, the role of dolomite as a co-filler or a hybrid filler in a polymer composite system is also discussed, revealing the great potential and prospect of this mineral filler in the field of polymer composites for advanced applications.
Microbial Remediation: A Promising Tool for Reclamation of Contaminated Sites with Special Emphasis on Heavy Metal and Pesticide Pollution: A Review
Authors: Tarfeen Najeebul , Nisa Khair Ul , Hamid Burhan , Bashir Zaffar , Yatoo Ali Mohd , Dar Mohd Ashraf , Mohiddin Fayaz Ahmad , Amin Zakir , Ahmad Rabi’atul Adawiyah , Sayyed R. Z.
Published: July 2022

Heavy metal and pesticide pollution have become an inevitable part of the modern industrialized environment that find their way into all ecosystems. Because of their persistent nature, recalcitrance, high toxicity and biological enrichment, metal and pesticide pollution has threatened the stability of the environment as well as the health of living beings. Due to the environmental persistence of heavy metals and pesticides, they get accumulated in the environs and consequently lead to food chain contamination. Therefore, remediation of heavy metals and pesticide contaminations needs to be addressed as a high priority. Various physico-chemical approaches have been employed for this purpose, but they have significant drawbacks such as high expenses, high labor, alteration in soil properties, disruption of native soil microflora and generation of toxic by-products. Researchers worldwide are focusing on bioremediation strategies to overcome this multifaceted problem, i.e., the removal, immobilization and detoxification of pesticides and heavy metals, in the most efficient and cost-effective ways. For a period of millions of evolutionary years, microorganisms have become resistant to intoxicants and have developed the capability to remediate heavy metal ions and pesticides, and as a result, they have helped in the restoration of the natural state of degraded environs with long term environmental benefits. Keeping in view the environmental and health concerns imposed by heavy metals and pesticides in our society, we aimed to present a generalized picture of the bioremediation capacity of microorganisms. We explore the use of bacteria, fungi, algae and genetically engineered microbes for the remediation of both metals and pesticides. This review summarizes the major detoxification pathways and bioremediation technologies; in addition to that, a brief account is given of molecular approaches such as systemic biology, gene editing and omics that have enhanced the bioremediation process and widened its microbiological techniques toward the remediation of heavy metals and pesticides.
Influence of Charcoal Production on Forest Degradation in Zambia: A Remote Sensing Perspective
Authors: Sedano Fernando , Mizu-Siampale Abel , Duncanson Laura , Liang Mengyu
Published: July 2022

A multitemporal dataset of medium-resolution imagery was used to document a tree cover loss process in three forest reserves of Zambia. This degradation process was attributed to charcoal production with a high degree of certainty, as evidence of kiln scars was found in more than 85% of sites sampled with high-resolution imagery across the study areas. The spatial and temporal pattern of mapped kiln scars exposed an intense and fast-paced degradation process, with kiln densities reaching 2.3 kiln/ha, removal of about 79.3% of the aboveground biomass and reductions of 74.2% of tree cover. The analysis revealed that this forest degradation process progressively moves further away from urban centers. In the year 2010, charcoal production took place around 190 km away from Lusaka, whereas extraction areas in 2020 were located around 350 km from this city. These results underline the negative impact of charcoal production on forest resources and question its characterization as localized and periurban. The post-disturbance LCLUC trajectories of degraded woodlands in forest reserves revealed a partial conversion to agricultural land over time, with less than 25% of these woodlands cultivated seven years after charcoal production. The disaggregation of the supply sources of charcoal for the city of Lusaka based on consumption figures and remote sensing deforestation records showed that the charcoal generated as a byproduct of agricultural expansion is not enough to meet the annual charcoal demand of Lusaka. On the contrary, the majority (65%) of this charcoal is the result of a forest degradation process that alters 197.4 km2 of miombo woodlands annually. These findings highlight the role of charcoal production as a direct driver of forest degradation and suggest that forest degradation resulting from charcoal production has surpassed deforestation due to agricultural expansion as the main tree cover loss process in Zambia. These results provide data-driven evidence to improve the characterization of forest degradation resulting from charcoal production across the woodlands of southern Africa and aid the REDD + monitoring, reporting and verification systems in compliance with international reporting commitments.
Improved Adaptive Multi-Objective Particle Swarm Optimization of Sensor Layout for Shape Sensing with Inverse Finite Element Method
Authors: Li Xiaohan , Niu Shengtao , Bao Hong , Hu Naigang
Published: July 2022

The inverse finite element method (iFEM) is one of the most effective deformation reconstruction techniques for shape sensing, which is widely applied in structural health monitoring. The distribution of strain sensors affects the reconstruction accuracy of the structure in iFEM. This paper proposes a method to optimize the layout of sensors rationally. Firstly, this paper constructs a dual-objective model based on the accuracy and robustness indexes. Then, an improved adaptive multi-objective particle swarm optimization (IAMOPSO) algorithm is developed for this model, which introduces initialization strategy, the adaptive inertia weight strategy, the guided particle selection strategy and the external candidate solution (ECS) set maintenance strategy to multi-objective particle swarm optimization (MOPSO). Afterwards, the performance of IAMOPSO is verified by comparing with MOPSO applied on the existing inverse beam model. Finally, the IAMOPSO is employed to the deformation reconstruction of complex plate-beam model. The numerical and experimental results demonstrate that the IAMOPSO is an excellent tool for sensor layout in iFEM.
Enhanced Angle-of-Arrival and Polarization Parameter Estimation Using Localized Hybrid Dual-Polarized Arrays
Authors: Yu Xiaolu , Li Hang , Zhang Jian Andrew , Huang Xiaojing , Cheng Zhiqun
Published: July 2022

The millimeter wave (mmWave) channel is dominated by line-of-sight propagation. Therefore, the acquisition of angle-of-arrival (AoA) and polarization state of the wave is of great significance to the receiver. In this paper, we investigate AoA and polarization estimation in a mmWave system employing dual-polarized antenna arrays. We propose an enhanced AoA estimation method using a localized hybrid dual-polarized array for a polarized mmWave signal. The use of dual-polarized arrays greatly improves the calibration of differential signals and the signal-to-noise ratio (SNR) of the phase offset estimation between adjacent subarrays. Given the estimated phase offset, an initial AoA estimate can be obtained, and is then used to update the phase offset estimation. This leads to a recursive estimation with improved accuracy. We further propose an enhanced polarization estimation method, which uses the power of total received signals at dual-polarized antennas to compute the cross-correlation-to-power ratio instead of using only one axis dipole. Thus the accuracy of polarization parameter estimation is improved. We also derive a closed-form expression for mean square error lower bounds of AoA estimation and present an average SNR analysis for polarization estimation performance. Simulation results demonstrate the superiority of the enhanced AoA and polarization parameter estimation methods compared to the state of the art.
Object-of-Interest Perception in a Reconfigurable Rolling-Crawling Robot
Authors: Semwal Archana , Lee Melvin Ming Jun , Sanchez Daniela , Teo Sui Leng , Wang Bo , Mohan Rajesh Elara
Published: July 2022

Cebrenus Rechenburgi, a member of the huntsman spider family have inspired researchers to adopt different locomotion modes in reconfigurable robotic development. Object-of-interest perception is crucial for such a robot to provide fundamental information on the traversed pathways and guide its locomotion mode transformation. Therefore, we present a object-of-interest perception in a reconfigurable rolling-crawling robot and identifying appropriate locomotion modes. We demonstrate it in Scorpio, our in-house developed robot with two locomotion modes: rolling and crawling. We train the locomotion mode recognition framework, named Pyramid Scene Parsing Network (PSPNet), with a self-collected dataset composed of two categories paths, unobstructed paths (e.g., floor) for rolling and obstructed paths (e.g., with person, railing, stairs, static objects and wall) for crawling, respectively. The efficiency of the proposed framework has been validated with evaluation metrics in offline and real-time field trial tests. The experiment results show that the trained model can achieve an mIOU score of 72.28 and 70.63 in offline and online testing, respectively for both environments. The proposed framework’s performance is compared with semantic framework (HRNet and Deeplabv3) where the proposed framework outperforms in terms of mIOU and speed. Furthermore, the experimental results has revealed that the robot’s maneuverability is stable, and the proposed framework can successfully determine the appropriate locomotion modes with enhanced accuracy during complex pathways.
A Sustainable Business Model for a Neutral Host Supporting 5G and beyond (5GB) Ultra-Dense Networks: Challenges, Directions, and Architecture
Authors: Allawi Yazan M. , Mohammed Alaelddin F. Y. , Lee Joohyung , Choi Seong Gon
Published: July 2022

With the deployment of the fifth generation (5G) mobile network systems and the envisioned heterogeneous ultra-dense networks (UDNs), both small cell (SmC) and distributed antenna system (DAS) technologies are required by mobile network operators (MNOs) and venue owners to support multiple spectrum bands, multiple radio access technologies (RATs), multiple optical central offices (COs), and multiple MNOs. As a result, the neutral host business model representing a third party responsible for managing the network enterprise on behalf of multiple MNOs has emerged as a potential solution, mainly influenced by the desire to provide a high user experience without significantly increasing the total cost of ownership (TCO). However, designing a sustainable business model for a neutral host is a nontrivial task, especially when considered in the context of 5G and beyond (5GB) UDNs. In this paper, under an integrated optical wireless network infrastructure, we review how SmC and DAS technologies are evolving towards the adoption of the neutral host business model and identify key challenges and requirements for 5GB support. Thus, we explore recent candidate advancements in heterogeneous network integration technologies for the realization of an efficient 5GB neutral host business model design capable of accommodating both SmC and DAS. Furthermore, we propose a novel design architecture that relies on virtual radio access network (vRAN) to enable real-time dynamic resource allocation and radio over Ethernet (RoE) for flexible and reconfigurable fronthaul. The results from our simulations using MATLAB over two real-life deployment scenarios validate the feasibility of utilizing switched RoE considering end-to-end delay requirements of 5GB under different switching schemes, as long as the queuing delay is kept to a minimum. Finally, the results show that incorporating RoE and vRAN technologies into the neutral host design results in substantial TCO reduction by about 81% in an indoor scenario and 73% in an outdoor scenario.
Neural Network Based IRSs-UEs Association and IRSs Optimal Placement in Multi IRSs Aided Wireless System
Authors: Nor Ahmed M. , Halunga Simona , Fratu Octavian
Published: July 2022

Implementing intelligent reflecting surfaces (IRSs), in high frequency based beyond 5G networks, has become a necessity to overcome the harsh blockage issues that exist in these bands. IRSs can supply user equipment (UEs) with multi alternative virtual line of sight (LOS) links, hence enhancing the spectral efficiency (SE) of the system. As a result of deploying multi IRSs as communication assistants, the step of IRSs-UEs association is required to optimally assign each UE to its best IRS; consideration of the interference between different links is needed, to maximize the system performance. However, this process will be a time and power consuming problem, if conventional schemes, which exhaustively search all possible association patterns to find the optimum one for communication, is adapted. Although iterative search based schemes can reduce this complexity, they still need feedback signaling in real time. Hence, they will be inefficient in terms of power consumption and delay. Moreover, optimal placement of the multi-IRSs in the network, to enlarge the system performance, is still an open issue and needs to be studied. Consequently, in this paper, to handle the IRSs-UEs association problem, we propose a neural network (NN) based scheme using a multi-IRSs aided multi input multi output (MIMO) system. In this system, the estimated angles of arrival (AoAs) of UEs are used as input features for the NN, which is trained to associate each UE to its best IRS based on this information; then, within each IRS, passive beamforming is performed. Adapting this NN in online mode guarantees obtaining better performance while relaxing the complexity of association and increasing response time, giving a performance comparable to the exhaustive and iterative search based schemes. The proposed NN based scheme determines the association pattern without searching or feedback signals. Moreover, the proposed approach maintains the system SE nearly similar to the optimum performance obtained by the conventional scheme. Secondly, a criterion is suggested for optimal deployment of multi IRSs in the network, depending on maximizing the average summation UEs signal-to-interference-plus-noise ratio (SINR). Numerical results prove that this strategy outperforms a reference one, which aims to guarantee certain performance by maximizing minimum UE SINR. In contrast the proposed strategy achieves better system and per UE spectral efficiency.
A Computationally Efficient and Virtualization-Free Two-Dimensional DOA Estimation Method for Nested Planar Array: RD-Root-MUSIC Algorithm
Authors: Han Shengxinlai , Lai Xin , Zhang Yu , Zhang Xiaofei
Published: July 2022

To address the problem of expensive computation in traditional two-dimensional (2D) direction of arrival (DOA) estimation, in this paper, we propose a 2D DOA estimation method based on a reduced dimension and root-finding MUSIC algorithm for nested planar arrays (NPAs). Specifically, the algorithm proposed in this paper transforms the problem based on 2D spectral peak search into two one-dimensional estimation problems by reducing the dimension, and then transforms the one-dimensional estimation problem into a problem of polynomial root finding. Finally the parameters are paired to realize the 2D DOA estimation. The proposed algorithm not only performs two root finding operations directly according to the 2D spectral function transformation, avoiding the performance degradation caused by intermediate operations, but can also fully exploit the enlarged array aperture offered by NPAs with reduced computational complexity and no need for virtualization. The superiorities of the proposed algorithm in terms of estimation accuracy and complexity are verified by simulations.
Effect of Education on the Economic Income of Households in Peru, Application of the Mincer Theory in Times of Pandemic (COVID-19)
Authors: Quispe-Mamani Julio Cesar , Hancco-Gomez Miriam Serezade , Carpio-Maraza Amira , Aguilar-Pinto Santotomas Licimaco , Mamani-Flores Adderly , Flores-Turpo Giovana Araseli , Velásquez-Velásquez Wily Leopoldo , Cutipa-Quilca Balbina Esperanza , Alegre-Larico Maria Isabel
Published: July 2022

The objective was to determine the effect of education on the economic income of households in Peru in times of the pandemic (COVID-19), for which a quantitative research approach was applied, of a non-experimental type and of descriptive-correlational design; the econometric model of log-linear type was used, based on the Mincer equation, with the information from the database of the National Household Survey, for the period of 2021. The economic income on average was 275.96 soles, with a standard deviation of 1451.41 soles, with high variability, identifying very precarious economic income ranging from 15.00 to 15,000.00 soles/month per worker; the years of schooling of the worker on average were 12 years, showing the scope of complete secondary training, with a population without years of education, and on the contrary, there are workers with postgraduate education, with the variability of 4 years. Finally, the effect of education measured through years of schooling on economic income is positive, or direct, since education explains 14.34% of economic income; the experience of the worker, gender, area of residence, age and marital status, in the same way, have a positive effect on economic income, strongly highlighting gender and area of residence which explain 19.86% and 30.45% of the economic income in the household in Peru.
How Do Gendered Labour Market Trends and the Pay Gap Translate into the Projected Gender Pension Gap? A Comparative Analysis of Five Countries with Low, Middle and High GPGs
Authors: Dekkers Gijs , Van den Bosch Karel , Barslund Mikkel , Kirn Tanja , Baumann Nicolas , Kump Nataša , Liégeois Philippe , Moreira Amílcar , Stropnik Nada
Published: July 2022

This article explores how the Gender Pension Gap (GPG)—the relative difference in average pension received by men and women—might evolve in the future in various European countries, given past, current, and projected future labour market behaviour and earnings of women and men, and current pension regulations. The GPG reflects career inequalities between women and men, though these are partly mitigated by the redistributive impact of the public retirement pensions. They are further mitigated by survivor benefits. This study aims to document both mechanisms in the projections of the GPG. As the GPG varies widely across European countries, we analyse countries with a high (Luxembourg), high and low middle (Belgium and Switzerland Portugal), and low (Slovenia) GPG. We find that the GPG will fall significantly in all five countries over the coming decades. The fundamental drivers behind this development are discussed. In addition to the base scenario, we simulate two variants to show the impact of the Gender Pension Coverage Gap and of survivor pensions. Additionally, we project the GPG if current labour market gender gaps were to remain at their present level, and, conversely, if these were to disappear overnight. These alternative scenarios, one of which also serves as a robustness test, suggest that the future decline of the GPG is largely the result of labour market developments that have already happened during the past decades.
Quality-Based Supplier Selection Model for Products with Multiple Quality Characteristics
Authors: Chen Kuen-Suan , Huang Ming-Chieh , Yu Chun-Min , Chen Hsuan-Yu
Published: July 2022

The concept of Industry 4.0 was first proposed by the German government in 2011. As the Internet of Things (IoT) becomes more prevalent and big data analysis technology becomes more mature, it is beneficial for the manufacturing industry to integrate and apply the related technologies to pursue the goal of smart manufacturing. Taiwan’s machine tool industry and downstream machine-tool purchasers, who are scattered around the world, have formed a machine-tool industry chain. To help the machine-tool industry and the suppliers of important components boost their process capabilities, ensure the final product quality of machine tools and improve the process capabilities of the entire industry chain, this study used radar charts to present the statistical testing information of the process capabilities of all quality characteristics, so that managers could have more complete information when evaluating and selecting appropriate suppliers. As noted in many studies, improving product quality and availability can reduce not only the rate of reworking and scrappage during production but also the frequency of maintenance or replacement of components after purchase. As a result, the loss of costs caused by reworking, scrappage, and maintenance can be diminished, carbon emissions can be lowered, and environmental pollution can be reduced as well, which will help to achieve sustainable operation in the entire machine tool industry chain.
An Integrated Assessment Framework for Transition to Water Circularity
Authors: Afghani Nof , Hamhaber Johannes , Frijns Jos
Published: July 2022

Changing our unsustainable linear water management pattern is necessary to face growing global water challenges. This article proposes an integrated framework to analyse and understand the role of different contextual conditions in the possible transition towards water circularity. Our framework combines a systematic multi-level perspective to explore the water system and the institutional work theory for technology legitimation. The framework consists of the following stages: (1) describing and understanding the water context, (2) assessment of the selected technologies’ circularity level, (3) assessment of the alternative circular technologies’ legitimacy, and (4) identification of the legitimation actions to support the upscale of alternative circular technologies. The practical applicability of the integrated assessment framework and its four assessment stages was demonstrated in the exploration of circular water technologies for the horticulture sector in Westland, the Netherlands. The results revealed the conditions that hinder or enable the legitimation of the circular water technologies, such as political environmentalism, trust in water governing authorities, and technical, financial, and knowledge capabilities.
Non-Destructive Testing of Pipe Conveyor Belts Using Glass-Coated Magnetic Microwires
Authors: Semrád Karol , Draganová Katarína
Published: July 2022

Belt conveyors have been used in a wide range of applications because in comparison to the alternative solutions represented by the rail or road transportation, their operation is typically more cost effective, with lower energy demands and the possibility of utilizing renewable energy sources, and during their operation, less noise and air pollution is produced. The presented article is focused on pipe belt conveyors that are even more sustainable and in harmony with the environment, especially considering transportation of fine and dusty materials. More specifically, pipe belt conveyors have the possibility of utilizing microwires as a sensing element for microwire-based sensors for the pipe belt conveyor diagnostics from a mechanical loading point of view. This is because during the enclosing of the pipe conveyor belt, periodical cyclical mechanical loading is applied due to the bending. From the results of the performed set of FEM (Finite Element Method) analyses of the glass-coated magnetic microwires, it can be concluded that during the selection process of the microwires, emphasis should be directed the thickness of the glass coating, which can affect the lifetime of the microwire significantly. The microwire length has negligible influence on the estimated number of bending cycles until the damage or crack occurs.
The Neuromarketing Concept in Artificial Neural Networks: A Case of Forecasting and Simulation from the Advertising Industry
Authors: Ahmed Rizwan Raheem , Streimikiene Dalia , Channar Zahid Ali , Soomro Hassan Abbas , Streimikis Justas , Kyriakopoulos Grigorios L.
Published: July 2022

This research aims to examine a neural network (artificial intelligence) as an alternative model to examine the neuromarketing phenomenon. Neuromarketing is comparatively new as a technique for designing marketing strategies, especially advertising campaigns. Marketers have used a variety of different neuromarketing tools, for instance functional magnetic resonance imaging (fMRI), eye tracking, electroencephalography (EEG), steady-state probe topography (SSPT), and other expensive gadgets. Similarly, researchers have been using these devices to carry out their studies. Therefore, neuromarketing has been an expensive project for both companies and researchers. We employed 585 human responses and used the neural network (artificial intelligence) technique to examine the predictive consumer buying behavior of an effective advertisement. For this purpose, we employed two neural network applications (artificial intelligence) to examine consumer buying behavior, first taken from a 1–5 Likert scale. A second application was run to examine the predicted consumer buying behavior in light of the neuromarketing phenomenon. The findings suggest that a neural network (artificial intelligence) is a unique, cost-effective, and powerful alternative to traditional neuromarketing tools. This study has significant theoretical and practical implications for future researchers and brand managers in the service and manufacturing sectors.
Models of Dynamic Systems in Diagnostic Tasks
Authors: Lukoyanov Egor , Kolesov Nikolai , Gruzlikov Alexander , Tolmacheva Marina
Published: July 2022

Models of dynamic systems are considered with regard to the tasks of diagnosing real-time complex information processing and control systems. The problem of diagnosing is one of the most important in the practice of development technical systems. It is important to note that symmetry principles are used in this work, in particular, to formulate the basic approach to diagnosing complex systems. This approach assumes that the components of a system are allocated to the levels based on inclusion relations. In this case, level-based diagnostic tools with their own models can be synthesized, and the relations between them are characterized by the symmetry feature. Problems of both functional and test-based diagnostic methods are discussed. Particular diagnostic methods may also involve symmetry principles since, in a certain sense, they operate with symmetric notions of observability and controllability of a dynamic system. The implementation of the proposed methods is illustrated by an example of their application to a navigation system of an autonomous underwater vehicle.
Clinical Presentations and Predictors of In-Hospital Mortality in Illicit Drug Users in the New Psychoactive Substances (NPS) Endemic Era in Taiwan
Authors: Yeh Hsin-Tzu , Chen Hsien-Yi , Liu Sung-Wei , Weng Te-I , Fang Cheng-Chung , Yu Jiun-Hao , Chen Yen-Chia , Su Yu-Jang , Gao Shi-Ying , Lin Chih-Chuan
Published: July 2022

Predictors of mortality in illicit drug users involving Novel Psychoactive Substances (NPS) and multiple substances have not been elucidated. We aimed to define predictors of mortality in the NPS endemic era’s illicit drug users to strengthen patient care in emergency treatment. This was a retrospective study. LC-MS/MS-confirmed positive illicit drug users who visited the emergency departments (ED) of six medical systems were enrolled. Demographic information, physical examinations, and laboratory data were abstracted for mortality analysis. There were 16 fatalities in 355 enrolled patients. The most frequently used illicit drugs were amphetamines, followed by opioids, cathinones, and ketamine. The most frequently detected cathinones among the 16 synthetic cathinones were eutylone, followed by mephedrone. The combined use of cathinones and ketamine was most commonly observed in our results. Univariate analysis revealed that the mortality patients were older, with deep coma, faster heart rate and respiratory rate, lower blood pressures and O2 room air saturation, more seizures, abnormal breath sounds, and had urine incontinence compared to the survivor patients. The mortality patients also had acute kidney injury, higher potassium, blood sugar, liver function test, and lactate level. The results of multiple logistic regression demonstrated that SBP < 90 mmHg, dyspnea, blood sugar > 140 mg/dl, and HCO3 < 20.6 mmHg were independent predictors of in-hospital mortality. Regardless of the pattern of the use of illicit drugs, the predictors allow for risk stratification and determining the optimal treatment.
RETRACTED: Environmental Impact of Pharmaceutical Pollutants: Synergistic Toxicity of Ivermectin and Cypermethrin
Authors: Paola Davide , Iaria Carmelo , Marino Fabio , Gugliandolo Enrico , Piras Cristian , Crupi Rosalia , Cuzzocrea Salvatore , Spanò Nunziacarla , Britti Domenico , Peritore Alessio
Published: July 2022

Veterinary antiparasitic pharmaceuticals as well as pesticides have been detected in surface waters, and they may cause several toxic effects in this environmental compartment. In the present study, we evaluated the toxicity after exposure of different concentration of ivermectin (IVM; 50, 100, and 200 μg L−1) and cypermethrin (CYP; 5, 10, and 25 μg L−1) and the combination of these two compounds at non-toxic concentration (IVM 100 + CYP 5 μg L−1) in zebrafish embryos. Combination of IVM at 100 μg L−1 with CYP at 5 μg L−1 exposure induced hatching delay and malformations at 96 hpf in zebrafish larvae as well as significant induction of cell death in zebrafish larvae. At the same time, the two single concentrations of IVM and CYP did not show a toxic effect on zebrafish development. In conclusion, our study suggests that IVM and CYP show a synergistic effect at common, ineffective concentrations, promoting malformation and cell death in fish development.