bluuebunny/crossref_metadata_2025 huggingface dataset:
Deciphering Codon Usage Patterns in Genome of Cucumis sativus in Comparison with Nine Species of Cucurbitaceae
Authors: Niu Yuan , Luo Yanyan , Wang Chunlei , Liao Weibiao
Published: November 2021

Cucumber is the most important vegetable crop in the Cucurbitaceae family. Condon usage bias (CUB) is a valuable character of species evolution. However, there is little research on the CUB of cucumber. Thus, this study analyzes the codon usage patterns of cucumber and its relatives within Cucurbitaceae on the genomic level. The analysis of fundamental indicators of codon characteristics shows that it was slightly GC poor, and there was weak codon usage bias in cucumber. We conduct the analysis of neutrality plot, ENC plot, P2 index, and COA indicates that the nucleotide composition, mutation pressure, and translational selection might play roles in CUB in cucumber and its relatives. Among these factors, nucleotide composition might play the most critical role. Based on these analyses, 30 optimal codons were identified in cucumber, most of them ending with U or A. Meanwhile, based on the RSCU values of species, a cluster tree was constructed, in which the situation of cucumber is consistent with the current taxonomic and evolutionary studies in Cucurbitaceae. This study systematically compared the CUB patterns and shaping factors of cucumber and its relatives, laying a foundation for future research on genetic engineering and evolutionary mechanisms in Cucurbitaceae.
Matrix-Bound Zolzoledronate Enhances the Biofilm Colonization of Hydroxyapatite: Effects on Osteonecrosis
Authors: Elsayed Ranya , El-Awady Ahmed , Cutler Christopher , Kurago Zoya , Elashiry Mahmoud , Sun Christina , Bloomquist Ryan , Meghil Mohamed M. , Elsalanty Mohammed E.
Published: November 2021

(1) Background: The aim of this study was to test whether matrix-bound zoledronate (zol) molecules enhanced the oral biofilm colonization of a mineralized matrix, rendering the alveolar bone more susceptible to medication-related osteonecrosis of the jaw (MRONJ) following invasive dental procedures. (2) Methods: We tested the effect of matrix-bound zol on the growth and attachment of Porphyromonas gingivalis (Pg), Fusobacterium nucleatum (Fn) and Actinomyces israelii (Ai), and whether the nitrogen-containing component of zol contributed to such effect. The role of oral bacteria in the induction of osteonecrosis was then tested using an extra-oral bone defect model. (3) Results: The attachment of biofilm to hydroxyapatite discs increased when the discs were pre-treated with zol. Bacterial proliferation was not affected. Matrix-bound zol was more potent than non-nitrogen-containing etidronate in enhancing the colonization. Stimulation was dampened by pre-treating the bacteria with histidine. The delivery of oral biofilm to a tibial defect caused osteonecrosis in zol-treated rats. (4) Conclusions: We conclude that matrix-bound zol enhances the oral biofilm colonization of hydroxyapatite. This enhancement depended on the presence of the nitrogen-containing group. The oral biofilm rendered the extra-oral bone susceptible to medication-related osteonecrosis, suggesting that it has an important role in the induction of MRONJ.
Effect of Ursolic and Oleanolic Acids on Lipid Membranes: Studies on MRSA and Models of Membranes
Authors: Verstraeten Sandrine , Catteau Lucy , Boukricha Laila , Quetin-Leclercq Joelle , Mingeot-Leclercq Marie-Paule
Published: November 2021

Staphylococcus aureus is an opportunistic pathogen and the major causative agent of life-threatening hospital- and community-acquired infections. A combination of antibiotics could be an opportunity to address the widespread emergence of antibiotic-resistant strains, including Methicillin-Resistant S. aureus (MRSA). We here investigated the potential synergy between ampicillin and plant-derived antibiotics (pentacyclic triterpenes, ursolic acid (UA) and oleanolic acid (OA)) towards MRSA (ATCC33591 and COL) and the mechanisms involved. We calculated the Fractional Inhibitory Concentration Index (FICI) and demonstrated synergy. We monitored fluorescence of Bodipy-TR-Cadaverin, propidium iodide and membrane potential-sensitive probe for determining the ability of UA and OA to bind to lipoteichoic acids (LTA), and to induce membrane permeabilization and depolarization, respectively. Both pentacyclic triterpenes were able to bind to LTA and to induce membrane permeabilization and depolarization in a dose-dependent fashion. These effects were not accompanied by significant changes in cellular concentration of pentacyclic triterpenes and/or ampicillin, suggesting an effect mediated through lipid membranes. We therefore focused on membranous effects induced by UA and OA, and we investigated on models of membranes, the role of specific lipids including phosphatidylglycerol and cardiolipin. The effect induced on membrane fluidity, permeability and ability to fuse were studied by determining changes in fluorescence anisotropy of DPH/generalized polarization of Laurdan, calcein release from liposomes, fluorescence dequenching of octadecyl-rhodamine B and liposome-size, respectively. Both UA and OA showed a dose-dependent effect with membrane rigidification, increase of membrane permeabilization and fusion. Except for the effect on membrane fluidity, the effect of UA was consistently higher compared with that obtained with OA, suggesting the role of methyl group position. All together the data demonstrated the potential role of compounds acting on lipid membranes for enhancing the activity of other antibiotics, like ampicillin and inducing synergy. Such combinations offer an opportunity to explore a larger antibiotic chemical space.
A Survey of Spontaneous Antibiotic-Resistant Mutants of the Halophilic, Thermophilic Bacterium Rhodothermus marinus
Authors: Silvia Sophia , Donahue Samantha A. , Killeavy Erin E. , Jogl Gerwald , Gregory Steven T.
Published: November 2021

Rhodothermus marinus is a halophilic extreme thermophile, with potential as a model organism for studies of the structural basis of antibiotic resistance. In order to facilitate genetic studies of this organism, we have surveyed the antibiotic sensitivity spectrum of R. marinus and identified spontaneous antibiotic-resistant mutants. R. marinus is naturally insensitive to aminoglycosides, aminocylitols and tuberactinomycins that target the 30S ribosomal subunit, but is sensitive to all 50S ribosomal subunit-targeting antibiotics examined, including macrolides, lincosamides, streptogramin B, chloramphenicol, and thiostrepton. It is also sensitive to kirromycin and fusidic acid, which target protein synthesis factors. It is sensitive to rifampicin (RNA polymerase inhibitor) and to the fluoroquinolones ofloxacin and ciprofloxacin (DNA gyrase inhibitors), but insensitive to nalidixic acid. Drug-resistant mutants were identified using rifampicin, thiostrepton, erythromycin, spiramycin, tylosin, lincomycin, and chloramphenicol. The majority of these were found to have mutations that are similar or identical to those previously found in other species, while several novel mutations were identified. This study provides potential selectable markers for genetic manipulations and demonstrates the feasibility of using R. marinus as a model system for studies of ribosome and RNA polymerase structure, function, and evolution.
Antimicrobial Resistance and Genomic Characterization of Six New Sequence Types in Multidrug-Resistant Pseudomonas aeruginosa Clinical Isolates from Pakistan
Authors: Irum Sidra , Naz Kanwal , Ullah Nimat , Mustafa Zeeshan , Ali Amjad , Arslan Muhammad , Khalid Kashaf , Andleeb Saadia
Published: November 2021

Pseudomonas aeruginosa (P. aeruginosa) is a major bacterial pathogen associated with a variety of infections with high mortality rates. Most of the clinical P. aeruginosa isolates belong to a limited number of genetic subgroups characterized by multiple housekeeping genes’ sequences (usually 5–7) through the Multi-Locus Sequence Typing (MLST) scheme. The emergence and dissemination of novel multidrug-resistant (MDR) sequence types (ST) in P. aeruginosa pose serious clinical concerns. We performed whole-genome sequencing on a cohort (n = 160) of MDR P. aeruginosa isolates collected from a tertiary care hospital lab in Pakistan and found six isolates belonging to six unique MLST allelic profiles. The genomes were submitted to the PubMLST database and new ST numbers (ST3493, ST3494, ST3472, ST3489, ST3491, and ST3492) were assigned to the respective allele combinations. MLST and core-genome-based phylogenetic analysis confirmed the divergence of these isolates and positioned them in separate branches. Analysis of the resistome of the new STs isolates revealed the presence of genes blaOXA-50, blaPAO, blaPDC, blaVIM-2, aph(3′)-IIb, aac(6′)-II, aac(3)-Id, fosA, catB7, dfrB2, crpP, merP and a number of missense and frame-shift mutations in chromosomal genes conferring resistance to various antipseudomonal antibiotics. The exoS, exoT, pvdE, rhlI, rhlR, lasA, lasB, lasI, and lasR genes were the most prevalent virulence-related genes among the new ST isolates. The different genotypic features revealed the adaptation of these new clones to a variety of infections by various mutations in genes affecting antimicrobial resistance, quorum sensing and biofilm formation. Close monitoring of these antibiotic-resistant pathogens and surveillance mechanisms needs to be adopted to reduce their spread to the healthcare facilities of Pakistan. We believe that these strains can be used as reference strains for future comparative analysis of isolates belonging to the same STs.
In Silico Detection of Antimicrobial Resistance Integrons in Salmonella enterica Isolates from Countries of the Andean Community
Authors: Torres-Elizalde Lilibeth , Ortega-Paredes David , Loaiza Karen , Fernández-Moreira Esteban , Larrea-Álvarez Marco
Published: November 2021

Antimicrobial resistance genes are often associated with integrons, which promote their movement between and within DNA molecules. IntFinder 1.0 and I-VIP v1.2 were used for the detection of integrons and their associated resistance genes in assembled sequences and raw reads. A dataset comprising 1688 sequenced Salmonella enterica isolates from countries of the Andean Community was developed. A total of 749 and 680 integrons were identified by IntFinder 1.0 and I-VIP v1.2, respectively; class 2 integrons were the most abundant followed by class 1, whereas no class 3 integrons were detected. These elements were mainly associated with isolates from animal sources. S. Infantis ST32 contained the majority of integrons. Trimethoprim resistance genes (dfrA) were found in greater numbers than others, including aadA and bla genes. The presence of these resistance integrons may come as a response to antibiotic misuse, especially of co-trimoxazole. This represents a public health risk as novel resistant strains might appear due to gene dissemination. The information gathered from in silico studies not only contributes to our understanding of integron dynamics in pathogenic Salmonella, but also helps identify potential emergent patterns of resistance in the region, which is fundamental for developing pertinent antibiotic surveillance programs.
Size Matters: The Influence of Patient Size on Antibiotics Exposure Profiles in Critically Ill Patients on Continuous Renal Replacement Therapy
Authors: Jang Soo-Min , Shaw Alex R. , Mueller Bruce A.
Published: November 2021

(1) Purpose of this study: To determine whether patient weight influences the probability of target attainment (PTA) over 72 h of initial therapy with beta-lactam (cefepime, ceftazidime, piperacillin/tazobactam) and carbapenem (imipenem, ertapenem, meropenem) antibiotics in the critical care setting. This is the first paper to address the question of whether patient size affects antibiotic PTA in the ICU. (2) Methods: We performed a post hoc analysis of Monte Carlo simulations conducted in virtual critically ill patients receiving antibiotics and continuous renal replacement therapy. The PTA was calculated for each antibiotic on the following pharmacodynamic (PD) targets: (a) were above the target organism’s minimum inhibitory concentration (≥%fT≥1×MIC), (b) were above four times the MIC (≥%fT≥4×MIC), and (c) were always above the MIC (≥100%fT≥MIC) for the first 72 h of antibiotic therapy. The PTA was analyzed in patient weight quartiles [Q1 (lightest)-Q4 (heaviest)]. Optimal doses were defined as the lowest dose achieving ≥90% PTA. (3) Results: The PTA for fT≥1×MIC led to similarly high rates regardless of weight quartiles. Yet, patient weight influenced the PTA for higher PD targets (100%fT≥MIC and fT≥4×MIC) with commonly used beta-lactams and carbapenems. Reaching the optimal PTA was more difficult with a PD target of 100%fT≥MIC compared to fT≥4×MIC. (4) Conclusions: The Monte Carlo simulations showed patients in lower weight quartiles tended to achieve higher antibiotic pharmacodynamic target attainment compared to heavier patients.
Calcium Dobesilate Modulates PKCδ-NADPH Oxidase- MAPK-NF-κB Signaling Pathway to Reduce CD14, TLR4, and MMP9 Expression during Monocyte-to-Macrophage Differentiation: Potential Therapeutic Implications for Atherosclerosis
Authors: Njau Florence , Haller Hermann
Published: November 2021

Monocyte-to-macrophage differentiation results in the secretion of various inflammatory mediators and oxidative stress molecules necessary for atherosclerosis pathogenesis. Consequently, this differentiation represents a potential clinical target in atherosclerosis. Calcium dobesilate (CaD), an established vasoactive and angioprotective drug in experimental models of diabetic microvascular complications reduces oxidative stress and inhibits inflammation via diverse molecular targets; however, its effect on monocytes/macrophages is poorly understood. In this study, we investigated the anti-inflammatory mechanism of CaD during phorbol 12-myristate 13-acetate (PMA)-induced monocyte-to-macrophage differentiation in in vitro models of sepsis (LPS) and hyperglycemia, using THP-1 monocytic cell line. CaD significantly suppressed CD14, TLR4, and MMP9 expression and activity, lowering pro-inflammatory mediators, such as IL1β, TNFα, and MCP-1. The effects of CaD translated through to studies on primary human macrophages. CaD inhibited reactive oxygen species (ROS) generation, PKCδ, MAPK (ERK1/2 and p38) phosphorylation, NOX2/p47phox expression, and membrane translocation. We used hydrogen peroxide (H2O2) to mimic oxidative stress, demonstrating that CaD suppressed PKCδ activation via its ROS-scavenging properties. Taken together, we demonstrate for the first time that CaD suppresses CD14, TLR4, MMP9, and signature pro-inflammatory cytokines, in human macrophages, via the downregulation of PKCδ/NADPH oxidase/ROS/MAPK/NF-κB-dependent signaling pathways. Our data present novel mechanisms of how CaD alleviates metabolic and infectious inflammation.
Redox Dysregulation in Aging and COPD: Role of NOX Enzymes and Implications for Antioxidant Strategies
Authors: Schiffers Caspar , Reynaert Niki L. , Wouters Emiel F. M. , van der Vliet Albert
Published: November 2021

With a rapidly growing elderly human population, the incidence of age-related lung diseases such as chronic obstructive pulmonary disease (COPD) continues to rise. It is widely believed that reactive oxygen species (ROS) play an important role in ageing and in age-related disease, and approaches of antioxidant supplementation have been touted as useful strategies to mitigate age-related disease progression, although success of such strategies has been very limited to date. Involvement of ROS in ageing is largely attributed to mitochondrial dysfunction and impaired adaptive antioxidant responses. NADPH oxidase (NOX) enzymes represent an important enzyme family that generates ROS in a regulated fashion for purposes of oxidative host defense and redox-based signalling, however, the associations of NOX enzymes with lung ageing or age-related lung disease have to date only been minimally addressed. The present review will focus on our current understanding of the impact of ageing on NOX biology and its consequences for age-related lung disease, particularly COPD, and will also discuss the implications of altered NOX biology for current and future antioxidant-based strategies aimed at treating these diseases.
Integration of Choline Chloride-Based Natural Deep Eutectic Solvents and Macroporous Resin for Green Production of Enriched Oil Palm Flavonoids as Natural Wound Healing Agents
Authors: Che Zain Mohamad Shazeli , Yeoh Jen Xen , Lee Soo Yee , Afzan Adlin , Shaari Khozirah
Published: November 2021

Huge quantities of oil palm (Elaeis guineensis Jacq.) leaves (OPL) are generated as agricultural biomass from oil palm plantations. OPL are known to contain significant amounts of flavonoids. For maximal exploitation of these valuable antioxidant compounds, an innovative and sustainable extraction method employing natural deep eutectic solvents (NaDES) combined with ultrasonic assisted extraction was developed. Various NaDES composed of choline chloride as the hydrogen bond donor (HBD) and 1,2 propanediol (PD), 1,4 butanediol (BD), glycerol (GLY), glucose (GLU), maltose (MAL), and lactic acid (LA) as the hydrogen bond acceptor (HBA) were synthesized. The influence of these compositions, the methods of their synthesis, molar ratios, and water contents on their capacity to extract flavonoids from OPL was evaluated. Based on the results, it was found that methods which incorporate a heating step produced NaDES with the best capacity to extract OPL flavonoids. These thermal methods combined with molar ratios of 1:3 or 1:4 and water contents of 17 to 50% were found to be the optimal conditions for preparing NaDES, specifically when applied to the PD, BD, and GLY NaDES. Subsequently, UHPLC-UV/PDA-MS/MS analysis revealed NaDES extracts recovered by macroporous adsorption resin XAD7HP were able to optimally extract at least twelve luteolin and apigenin derivatives in OPL NaDES extracts prepared from glycerol and 1,4-butanediol demonstrated better and comparable efficiency as aqueous methanol in extracting flavonoids from OPL. The in vitro studies of antioxidant and wound healing properties supported these findings by exhibiting good free radical scavenging, cell proliferation, and migration activities. Additionally, the NaDES extracts also showed non-cytotoxicity effects at 1000 µg/mL and below on 3T3 fibroblast cells. Results of the study showed that NaDES could be a promising eco-friendly green solvent to extract bioactive OPL flavonoids that have great potential for applications as wound healing agents.
Event Monitoring and Intelligence Gathering Using Twitter Based Real-Time Event Summarization and Pre-Trained Model Techniques
Authors: Lee Chung-Hong , Yang Hsin-Chang , Chen Yenming J. , Chuang Yung-Lin
Published: November 2021

Recently, an emerging application field through Twitter messages and algorithmic computation to detect real-time world events has become a new paradigm in the field of data science applications. During a high-impact event, people may want to know the latest information about the development of the event because they want to better understand the situation and possible trends of the event for making decisions. However, often in emergencies, the government or enterprises are usually unable to notify people in time for early warning and avoiding risks. A sensible solution is to integrate real-time event monitoring and intelligence gathering functions into their decision support system. Such a system can provide real-time event summaries, which are updated whenever important new events are detected. Therefore, in this work, we combine a developed Twitter-based real-time event detection algorithm with pre-trained language models for summarizing emergent events. We used an online text-stream clustering algorithm and self-adaptive method developed to gather the Twitter data for detection of emerging events. Subsequently we used the Xsum data set with a pre-trained language model, namely T5 model, to train the summarization model. The Rouge metrics were used to compare the summary performance of various models. Subsequently, we started to use the trained model to summarize the incoming Twitter data set for experimentation. In particular, in this work, we provide a real-world case study, namely the COVID-19 pandemic event, to verify the applicability of the proposed method. Finally, we conducted a survey on the example resulting summaries with human judges for quality assessment of generated summaries. From the case study and experimental results, we have demonstrated that our summarization method provides users with a feasible method to quickly understand the updates in the specific event intelligence based on the real-time summary of the event story.
Novel Approaches and Technologies for Heritage Buildings Conservation: Editorial
Authors: Coli Massimo , Iwasaki Yoshi
Published: November 2021

Conservation of heritage buildings deserves special attention, because these buildings are not only a distinctive feature of the wisdom and creativity of the ancients, conveying abundant historic and technical information, but often they are also the symbol of a culture and represent the local community as a whole [...]
Grain Refinement and Improved Mechanical Properties of EUROFER97 by Thermo-Mechanical Treatments
Authors: Stornelli Giulia , Di Schino Andrea , Mancini Silvia , Montanari Roberto , Testani Claudio , Varone Alessandra
Published: November 2021

EUROFER97 steel plates for nuclear fusion applications are usually manufactured by hot rolling and subsequent heat treatments: (1) austenitization at 980 °C for 30 min, (2) rapid cooling and (3) tempering at 760 °C for 90 min. An extended experimental campaign was carried out with the scope of improving the strength of the steel without a loss of ductility. Forty groups of samples were prepared by combining cold rolling with five cold reduction ratios (20, 40, 50, 60 and 80%) and heat treatments at eight different temperatures in the range 400–750 °C (steps of 50 °C). This work reports preliminary results regarding the microstructure and mechanical properties of all the cold-rolled samples and the effects of heat treatments on the samples deformed with the greater CR ratio (80%). The strength of deformed samples decreased as heat treatment temperature increased and the change was more pronounced in the samples cold-rolled with greater CR ratios. After heat treatments at temperature up to 600 °C yield stress (YS) and ultimate tensile strength (UTS) of samples deformed with CR ratio of 80% were significantly larger than those of standard EUROFER97 but ductility was lower. On the contrary, the treatment at 650 °C produced a fully recrystallized structure with sub-micrometric grains which guarantees higher strength and comparable ductility. The work demonstrated that EUROFER97 steel can be strengthened without compromising its ductility; the most effective process parameters will be identified by completing the analyses on all the prepared samples.
Development and Validation of an ICP-AES Method for the Determination of Toxic and Nutrient Metals in Candies: Application for the Analysis of Different Samples from the Greek Market
Authors: Manousi Natalia , Zachariadis George A.
Published: November 2021

In this study, we present the development and validation of an inductively coupled plasma-atomic emission spectrometric (ICP-AES) method for the determination of Ag, Ba, Bi, Ca, Cd, Co, Cr, Cu, Fe, Mg, Mn, Ni, Pb and Zn in different candies. Various wet digestion protocols were examined in order to ensure minimum consumption of chemicals and sample preparation time. Under optimized conditions, less than 10 min were required for complete sample decomposition. The ICP-AES method was validated in terms of linearity, accuracy, precision, limits of detection (LODs) and limits of quantification (LOQs). The relative recoveries for the proposed method ranged between 80.0% and 119.0%, while the relative standard deviation values were lower than 9.0%, indicating good method accuracy and precision, respectively. The LODs for the examined analytes were 0.04–2.25 mg kg−1. Finally, the proposed method was successfully employed for the analysis of hard candies, jellies and lollipops that are sold in the Greek market, which are highly likely to be consumed by children.
Topic Recommendation to Expand Knowledge and Interest in Question-and-Answer Agents
Authors: Yang Albert Deok-Young , Noh Yeo-Gyeong , Hong Jin-Hyuk
Published: November 2021

By providing a high degree of freedom to explore information, QA (question and answer) agents in museums are expected to help visitors gain knowledge on a range of exhibits. Since information exploration with a QA agent often involves a series of interactions, proper guidance is required to support users as they find out what they want to know and broaden their knowledge. In this paper, we validate topic recommendation strategies of system-initiative QA agents that suggest multiple topics in different ways to influence users’ information exploration, and to help users proceed to deeper levels in topics on the same subject, to offer them topics on various subjects, or to provide them with selections at random. To examine how different recommendations influence users’ experience, we have conducted a user study with 50 participants which has shown that providing recommendations on various subjects expands their interest on subjects, supports longer conversations, and increases willingness to use QA agents in the future.
Modular Model Composition for Rapid Implementations of Embedded Economic Model Predictive Control in Microgrids
Authors: Kull Tobias , Zeilmann Bernd , Fischerauer Gerhard
Published: November 2021

Economic model predictive control in microgrids combined with dynamic pricing of grid electricity is a promising technique to make the power system more flexible. However, to date, each individual microgrid requires major efforts for the mathematical modelling, the implementation on embedded devices, and the qualification of the control. In this work, a field-suitable generalised linear microgrid model is presented. This scalable model is instantiated on field-typical hardware and in a modular way, so that a class of various microgrids can be easily controlled. This significantly reduces the modelling effort during commissioning, decreases the necessary qualification of commissioning staff, and allows for the easy integration of additional microgrid devices during operation. An exemplary model, derived from an existing production facility microgrid, is instantiated, and the characteristics of the results are analysed.
Damage Identification in Warren Truss Bridges by Two Different Time–Frequency Algorithms
Authors: Bernardini Lorenzo , Carnevale Marco , Collina Andrea
Published: November 2021

Recently, a number of authors have been focusing on drive-by monitoring methods, exploiting sensors mounted on the vehicle rather than on the bridge to be monitored, with clear advantages in terms of cost and flexibility. This work aims at further exploring the feasibility and effectiveness of novel tools for indirect health monitoring of railway structures, by introducing a higher level of accuracy in damage modelling, achieve more close-to-reality results. A numerical study is carried out by means of a FE 3D model of a short span Warren truss bridge, simulating the dynamic interaction of the bridge/track/train structure. Two kinds of defects are simulated, the first one affecting the connection between the lower chord and the side diagonal member, the second one involving the joint between the cross-girder and the lower chord. Accelerations gathered from the train bogie in different working conditions and for different intensities of the damage level are analyzed through two time-frequency algorithms, namely Continuous Wavelet and Huang-Hilbert transforms, to evaluate their robustness to disturbing factors. Compared to previous studies, a complete 3D model of the rail vehicle, together with a 3D structural scheme of the bridge in place of the 2D equivalent scheme widely adopted in the literature, allow a more detailed and realistic representation of the effects of the bridge damage on the vehicle dynamics. Good numerical results are obtained from both the two algorithms in the case of the time-invariant track profile, whereas the Continuous Wavelet Transform is found to be more robust when a deterioration of track irregularity is simulated.
Forklift Tracking: Industry 4.0 Implementation in Large-Scale Warehouses through UWB Sensor Fusion
Authors: Motroni Andrea , Buffi Alice , Nepa Paolo
Published: November 2021

This article addresses the problem of determining the location of pallets carried by forklifts inside a warehouse, which are recognized thanks to an onboard Radio Frequency IDentification (RFID) system at the ultra-high-frequency (UHF) band. By reconstructing the forklift trajectory and orientation, the location of the pallets can be associated with the forklift position at the time of unloading events. The localization task is accomplished by means of an easy-to-deploy combination of onboard sensors, i.e., an inertial measurement unit (IMU) and an optical flow sensor (OFS), with a commercial ultra-wideband (UWB) system through an Unscented Kalman Filter (UKF) algorithm, which estimates the forklift pose over time. The proposed sensor fusion approach contributes to the localization error mitigation by preventing drifts in the trajectory reconstruction. The designed methos was at first evaluated by means of a simulation framework and then through an experimental analysis conducted in a large warehouse with a size of about 4000 m2.
Experimental Comparison of Direct and Active Throttle Control of a 7 kW Turboelectric Power System for Unmanned Aircraft
Authors: Burgess Johnathan , Runnels Timothy , Johnsen Joshua , Drake Joshua , Rouser Kurt
Published: November 2021

This article compares direct turbine throttle control and active turbine throttle control for a turboelectric system; the featured turboprop is rated for 7 kW of shaft output power. The powerplant is intended for applications in unmanned aerial systems and requires a control system to produce different amounts of power for varying mission legs. The most straightforward control scheme explored is direct turbine control, which is characterized by the pilot controlling the throttle of the turbine engine. In contrast, active control is characterized by the turbine reacting to the power demanded by the electric motors or battery recharge cycle. The transient response to electric loads of a small-scale turboelectric system is essential in identifying and characterizing such a system’s safe operational parameters. This paper directly compares the turbogenerator’s transient behavior to varying electric loads and categorizes its dynamic response. A proportional, integral, and derivative (PID) control algorithm was utilized as an active throttle controller through a microcontroller with battery power augmentation for the turboelectric system. This controller manages the turbine’s throttle reactions in response to any electric load when applied or altered. By comparing the system’s response with and without the controller, the authors provide a method to safely minimize the response time of the active throttle controller for use in the real-world environment of unmanned aircraft.
Multi-Classifier of DDoS Attacks in Computer Networks Built on Neural Networks
Authors: Chartuni Andrés , Márquez José
Published: November 2021

The great commitment in different areas of computer science for the study of computer networks used to fulfill specific and major business tasks has generated a need for their maintenance and optimal operability. Distributed denial of service (DDoS) is a frequent threat to computer networks because of its disruption to the services they cause. This disruption results in the instability and/or inoperability of the network. There are different classes of DDoS attacks, each with a different mode of operation, so detecting them has become a difficult task for network monitoring and control systems. The objective of this work is based on the exploration and choice of a set of data that represents DDoS attack events, on their treatment in a preprocessing phase, and later, the generation of a model of sequential neural networks of multi-class classification. This is done to identify and classify the various types of DDoS attacks. The result was compared with previous works treating the same dataset used herein. We compared their classification method, against ours. During this research, the CIC DDoS2019 dataset was used. Previous works carried out with this dataset proposed a binary classification approach, our approach is based on multi-classification. Our proposed model was capable of achieving around 94% in metrics such as precision, accuracy, recall and F1 score. The added value of multiclass classification during this work is identified and compared with binary classifications using the models presented in the previous.
Public Transportation Operational Health Assessment Based on Multi-Source Data
Authors: Zhou Xuemei , Guan Zhen , Xi Jiaojiao , Wei Guohui
Published: November 2021

In order to solve the problem of inefficient long-term operation of urban public transport vehicles and the difficulty of finding the cause of the disease, a new analysis idea was designed using machine learning methods. This study aimed to provide a rapid, accurate, and convenient solution model and algorithm to address the drawbacks of traditional analysis tools that are incapable of handling multiple sources of public transport data. Based on a full process analysis of the bus operation status, the influencing factors and calculation methods were defined. Afterwards, the calculation results were used to construct a training set with a Random Forest regression model to obtain the weight ranking of different influencing factors. The results of the simulation validation proved that the model can use the basic data of bus operation to quickly find out the primary factors affecting the operation condition and pinpoint to the bottleneck interval. The method has high accuracy and feasibility. It can be universally applied to the analysis of regular bus scenarios to provide strong decision support for the operation level.
Hardware Reliability Analysis of a Coal Mine Gas Monitoring System Based on Fuzzy-FTA
Authors: Xu Jingtian , Yang Man , Li Shugang
Published: November 2021

The hardware reliability of a gas monitoring system was investigated using the fuzzy fault tree analysis method. A fault tree was developed considering the hardware failure of the gas monitoring system as a top event. Two minimum path sets were achieved through qualitative analysis using the ascending method. The concept of fuzzy number of the fuzzy set theory was applied to describe the probability of basic event occurrence in the fault tree, and the fuzzy failure probabilities of the middle and top events were calculated using fuzzy AND and OR operators. The results show that the proposed fuzzy fault tree is an effective method of reliability analysis for gas monitoring systems. Results of calculations using this method are more reasonable than those obtained with the conventional fault tree method.
Analyzing Determinants for Adoption of Intelligent Personal Assistant: An Empirical Study
Authors: Sun Chia-Chi
Published: November 2021

With the accelerating advances in artificial intelligence (AI) technologies, the rising demand for the intelligent personal assistant is expected to rapidly increase in the following decades. As customer loyalty has become a critical element in gaining a competitive advantage and many marketers pay great attention to it, this research aims to explore the factors that directly affect customer loyalty toward the intelligent personal assistant. The main motivation is to investigate and identify the direct effects that variables such as customer innovativeness and perceived value have on customer loyalty. Additionally, both product knowledge and corporate image will be examined as moderators. The results obtained demonstrate that perceived value has a positive influence on customer loyalty. Furthermore, product knowledge moderates the influence of functional and hedonic innovativeness on customer satisfaction. The study’s main contributions provide a better understanding of customer loyalty. This research aims to be viewed as a specific guide to provide effective practices that companies should implement to help them reallocate resources appropriately and enhance customer value creation. The results indicate that the higher the level of customer perceived value, the better the customer loyalty will be. The findings represent that corporate image has a positive moderating effect on the influence of customer innovativeness on perceived value. This study draws on the outcomes of administrative suggestions and recommends a few observational strategies to improve the monetary administration in the intelligent personal assistant industry.
Analysis of Modular Design Applicable in Prosumer Scope. Guideline in the Creation of a New Modular Design Model
Authors: Asión-Suñer Laura , López-Forniés Ignacio
Published: November 2021

Modular design is the design based on independent and connectable modules to achieve product variety. It is an ideal tool that could facilitate the inclusion of prosumers in the creative process. However, its evolution has focused on product development and not on end users. The creation of a new modular design model for prosumers could respond to their needs while exploiting the advantages of modularity. The present work analyzes the applicability of modular design in the prosumer scope and defines a guideline for the creation of the new model. To this end, prosumer and modular design methods are collected and analyzed throughout the previously defined design process. The intersection between both terms is analyzed through a series of real cases and design methods that show what the objectives of prosumers are and if the present products and methods meet their needs. These results will establish the current and potential link between modular design and prosumers. Finally, the objectives and stages to develop the design model based on previous results are presented. The paper presents relevant findings such as the lack of methods in the conceptual design phases and a guideline to ensure that the prosumer benefits from modular design.
Effects of Different Seat Pressures and Rowing Cadences on Muscle Oxygenation and Physiological Parameter Responses
Authors: Chien Kuei-Yu , Chen Wei-Han , Chang Feng-Yi , Yang Yong , Chang Hsiao-Yun , Wang En-Tzu , Chen Wan-Chin
Published: November 2021

This study investigated the effects of rowing with different seat cushion and cadence conditions on oxyhemoglobin (O2Hb) and total hemoglobin (tHb) levels of the erector spinae (ES) as well as the effects on heart rate (HR) and ratings of perceived exertion (RPE). Thirty healthy adults completed tests under three unstable air seat cushion pressure levels (0, 80, and 140 mmHg) and three rowing cadences (slow: 18 bpm, medium: 30 bpm, and fast: 36 bpm) on a rowing machine, for a total of nine test conditions. During the exercise period, rowing on cushions set to 80 mmHg resulted in greater O2Hb and tHb changes than did rowing at 0 mmHg (p < 0.05). When rowing cadence increased, the O2Hb and tHb decreased during the exercise period, whereas HR and RPE increased (p < 0.05). During the recovery period, O2Hb and tHb on cushions set to 140 mmHg during slow rowing were higher than those at 0 mmHg during slow rowing and 140 mmHg during fast rowing (p < 0.05). Rowing on an appropriate pressure of seat cushion and using a slow cadence contribute to increasing muscle oxygenation of low back during exercise.
Evaluation of Stress Distribution of Isotropic, Composite, and FG Beams with Different Geometries in Nonlinear Regime via Carrera-Unified Formulation and Lagrange Polynomial Expansions
Authors: Carrera Erasmo , Demirbas Munise Didem , Augello Riccardo
Published: November 2021

In this study, the geometrically nonlinear behaviour caused by large displacements and rotations in the cross sections of thin-walled composite beams subjected to axial loading is investigated. Newton–Raphson scheme and an arc length method are used in the solution of nonlinear equations by finite element method to determine the mechanical effect. The Carrera-Unified formulation (CUF) is used to solve nonlinear, low or high order kinematic refined structure theories for finite beam elements. In the study, displacement area and stress distributions of composite structures with different angles and functionally graded (FG) structures are presented for Lagrange polynomial expansions. The results show the accuracy and computational efficiency of the method used and give confidence for new research.
Design and Fabrication Technology of Metal Mirrors Based on Additive Manufacturing: A Review
Authors: Zhang Kai , Qu Hemeng , Guan Haijun , Zhang Jizhen , Zhang Xin , Xie Xiaolin , Yan Lei , Wang Chao
Published: November 2021

In recent years, much progress has been made on the development of metal mirrors based on additive manufacturing (AM). The sandwich mirror is well known for its excellent mechanical properties and challenging machining. Now, AM can be used to fabricate this complex structure and reduce the processing time and cost. In addition, with the aid of some new design methods for additive manufacturing, such as lattice, topology optimization (TO), and Voronoi, the freedom of mirror structure design is enormously improved. The common materials of mirrors include ceramics (SiC), glasses (glass ceramics, fused silica), and metals (aluminum, beryllium). Among them, the AM technology of metals is the most mature and widely used. Researchers have recently extensively developed the new-generation metal mirror to improve performance and lightweight rate. This review focuses on the following topics: (1) AM technologies and powder materials for metal mirrors, (2) recent advances in optomechanical design methods for AM metal mirrors, (3) challenges faced by AM metal mirrors in fabricating, and (4) future trends in AM metal mirrors.
A Decentralized Framework for Managing Task Allocation in Distributed Software Engineering
Authors: Gupta Chetna , Gupta Varun
Published: November 2021

In distributed software development, planning and managing fair and transparent task allocation is both critical and challenging. The objective of this paper is to propose a decentralized blockchain-oriented, transparent task allocation framework to improve the quality of the task allocation process. It addresses the concerns of (i) enhancing collaboration, (ii) inhibiting knowledge vaporization, and (iii) reducing documentation problems. The proposed method is a novel two-fold process: First, it identifies and categorizes tasks exhibiting different dependencies and complexities to create equal task clusters based on their dependency type, difficulty, cost, and time. Second, it uses a blockchain-oriented framework to broadcast, check bid validity, allow developers to bid on tasks matching their roles and expertise, evaluate, and announce the winner for task allocation using smart contracts. Results of experimentation, surveys, and interviews with software practitioners conclude that the proposed solution is transparent and effective in allocating tasks (with Cranach’s alpha of 0.894) at a low cost of contract execution in a distributed software development environment. Overall, the proposed approach will have a positive and significant impact in industrial settings.
Control Design and Assessment for a Reversing Tractor–Trailer System Using a Cascade Controller
Authors: Aldughaiyem Abdullah , Bin Salamah Yasser , Ahmad Irfan
Published: November 2021

In recent years, control design for unmanned systems, especially a tractor–trailer system, has gained popularity among researchers. The emergence of such interest is caused by the potential reduction in cost and shortage of number of workers and labors. Two industries will benefit from the advancements of these types of systems: agriculture and cargo. By using the unmanned tractor–trailer system, harvesting and cultivating plants will become a safe and easy task. It will also cause a reduction in cost which in turn reduces the price on the end consumers. On the other hand, by using the unmanned tractor–trailer system in the cargo industry, shipping cost and time for the item delivery will be reduced. The work presented in this paper focuses on the development of a path tracking and a cascaded controller to control a tractor–trailer in reverse motion. The path tracking controller utilizes the Frenet–Serret frame to control the kinematics of the tractor–trailer system on a desired path, while the cascade controller’s main objective is to stabilize the system and to perform commands issued by the path tracker. The controlled parameters in this proposed design are the lateral distance to a path, trailer’s heading angel, articulated angel, and articulated angle’s rate. The main goal of such controller is to follow a path while the tractor–trailer system is moving in reverse and controlling the stability of the articulated vehicle to prevent the occurrence of a jackknife incident (uncontrolled state). The proposed controller has been tested in a different scenario where a successful implementation has been shown.
An Efficient Stochastic Constrained Path Planner for Redundant Manipulators
Authors: Gil Aparicio Arturo , Valls Miro Jaime
Published: November 2021

This brief proposes a novel stochastic method that exploits the particular kinematics of mechanisms with redundant actuation and a well-known manipulability measure to track the desired end-effector task-space motion in an efficient manner. Whilst closed-form optimal solutions to maximise manipulability along a desired trajectory have been proposed in the literature, the solvers become unfeasible in the presence of obstacles. A manageable alternative to functional motion planning is thus proposed that exploits the inherent characteristics of null-space configurations to construct a generic solution able to improve manipulability along a task-space trajectory in the presence of obstacles. The proposed Stochastic Constrained Optimization (SCO) solution remains close to optimal whilst exhibiting computational tractability, being an attractive proposition for implementation on real robots, as shown with results in challenging simulation scenarios, as well as with a real 7R Sawyer manipulator, during surface conditioning tasks.
Updates on the Mobile Divider and Its Use in Calabria Region to Monitor and Control Aethina tumida Infestation
Authors: Di Ruggiero Camilla , Mezher Ziad , Mutinelli Franco , De Carolis Alessandra , Pocci Naomi , Formato Giovanni
Published: November 2021

The small hive beetle (SHB), Aethina tumida was first detected in the Calabria and Sicily region (Southern Italy) in 2014. In this regard, a more effective and faster inspection method than the Official one (Ministry of Health) was tested to detect the beetle in the hive. In collaboration with Calabria beekeepers’ association, a “mobile divider”-based method was tested, in order to facilitate the detection of A. tumida and save time during hive inspection. In this short communication, we provide an update on the mobile divider technique and its related inspection procedure, which was first proposed and used in Calabria (Southern Italy) from 2014 to 2016. We report preliminary data concerning the number of detected SHBs and the time spent for their detection, based on the inspection of two apiaries in Calabria region, using both methods (official method and mobile divider method). The preliminary data presented here show that, on average, the mobile divider method seems to be able to recover a slightly higher number of beetles (0.9 adults) per inspected hive, in a shorter time (25 s).