bluuebunny/crossref_metadata_2025 huggingface dataset:
Pregnancy Complications Can Foreshadow Future Disease—Long-Term Outcomes of a Complicated Pregnancy
Authors: Panaitescu Anca Maria , Popescu Mihaela Roxana , Ciobanu Anca Marina , Gica Nicolae , Cimpoca-Raptis Brindusa Ana
Published: December 2021

During gestation, the maternal body should increase its activity to fulfil the demands of the developing fetus as pregnancy progresses. Each maternal organ adapts in a unique manner and at a different time during pregnancy. In an organ or system that was already vulnerable before pregnancy, the burden of pregnancy can trigger overt clinical manifestations. After delivery, symptoms usually reside; however, in time, because of the age-related metabolic and pro-atherogenic changes, they reappear. Therefore, it is believed that pregnancy acts as a medical stress test for mothers. Pregnancy complications such as gestational hypertension, preeclampsia and gestational diabetes mellitus foreshadow cardiovascular disease and/or diabetes later in life. Affected women are encouraged to modify their lifestyle after birth by adjusting their diet and exercise habits. Blood pressure and plasmatic glucose level checking are recommended so that early therapeutic intervention can reduce long-term morbidity. Currently, the knowledge of the long-term consequences in women who have had pregnancy-related syndromes is still incomplete. A past obstetric history may, however, be useful in determining the risk of diseases later in life and allow timely intervention.
Effects of Bacteroides-Based Microecologics against Antibiotic-Associated Diarrhea in Mice
Authors: Guo Hang , Yu Leilei , Tian Fengwei , Zhao Jianxin , Zhang Hao , Chen Wei , Zhai Qixiao
Published: December 2021

Antibiotic-associated diarrhea (AAD) is a self-limiting disease mediated by antibiotic therapy. In clinical practice, several types of probiotics are used in treating AAD, but minimal research has been done on Bacteroides-based microecologics. Our aim was to evaluate the therapeutic effects of Bacteroidetes uniformis FGDLZ48B1, B. intestinalis FJSWX61K18, Bifidobacterium adolescentis FHNFQ48M5, and B. bifidum FGZ30MM3 and their mixture on AAD in mice. The lincomycin hydrochloride-induced AAD models were gavaged with a single strain or a probiotic mixture for a short period to assess the changes in colonic histopathology and cytokine concentrations, intestinal epithelial permeability and integrity, short-chain fatty acids (SCFAs), and the diversity of intestinal microbiota. Our data indicated that both the sole use of Bacteroides and the combination of Bacteroides and Bifidobacterium beneficially weakened systemic inflammation, increased the recovery rate of tissue structures, increased the concentrations of SCFAs, and restored the gut microbiota. Moreover, the probiotic mixture was more effective than the single strain. Specifically, B. uniformis FGDLZ48B1 combined with the B. adolescentis FHNFQ48M5 group was more effective in alleviating the pathological features of the colon, downregulating the concentrations of interleukin (IL)-6, and upregulating the expression of occludin. In summary, our research suggests that administration of a mixture of B. uniformis FGDLZ48B1 and B. adolescentis FHNFQ48M5 is an effective approach for treating AAD.
Metagenome-Scale Metabolic Network Suggests Folate Produced by Bifidobacterium longum Might Contribute to High-Fiber-Diet-Induced Weight Loss in a Prader–Willi Syndrome Child
Authors: Xiang Baoyu , Zhao Liping , Zhang Menghui
Published: December 2021

Gut-microbiota-targeted nutrition intervention has achieved success in the management of obesity, but its underlying mechanism still needs extended exploration. An obese Prader–Willi syndrome boy lost 25.8 kg after receiving a high-fiber dietary intervention for 105 days. The fecal microbiome sequencing data taken from the boy on intervention days 0, 15, 30, 45, 60, 75, and 105, along with clinical indexes, were used to construct a metagenome-scale metabolic network. Firstly, the abundances of the microbial strains were obtained by mapping the sequencing reads onto the assembly of gut organisms through use of reconstruction and analysis (AGORA) genomes. The nutritional components of the diet were obtained through the Virtual Metabolic Human database. Then, a community model was simulated using the Microbiome Modeling Toolbox. Finally, the significant Spearman correlations among the metabolites and the clinical indexes were screened and the strains that were producing these metabolites were identified. The high-fiber diet reduced the overall amount of metabolite secretions, but the secretions of folic acid derivatives by Bifidobacterium longum strains were increased and were significantly relevant to the observed weight loss. Reduced metabolites might also have directly contributed to the weight loss or indirectly contribute by enhancing leptin and decreasing adiponectin. Metagenome-scale metabolic network technology provides a cost-efficient solution for screening the functional microbial strains and metabolic pathways that are responding to nutrition therapy.
Effect of Protracted Free-Choice Chlortetracycline-Medicated Mineral for Anaplasmosis Control on Escherichia coli Chlortetracycline Resistance Profile from Pastured Beef Cattle
Authors: Toillion Alyssa R. , Reppert Emily J. , Amachawadi Raghavendra G. , Olson K. C. , Coetzee Johann F. , Kang Qing , Reif Kathryn E.
Published: December 2021

Anaplasmosis is an economically-significant, hemolytic, tick-borne disease of cattle caused by Anaplasma marginale which can cause clinical anemia and death. Current control options are limited, and FDA-approved antimicrobial control options do not have a defined duration of use. A practical and routinely used anaplasmosis control method involves feeding free-choice chlortetracycline (CTC)-medicated mineral to pastured cattle for several months. Constant antimicrobial use poses the risk of expediting the development and dissemination of antimicrobial resistance in off-target commensal bacteria in the bovine gastrointestinal tract. The objective of this study was to determine the CTC-susceptibility of Escherichia coli isolated from anaplasmosis endemic beef cattle herds provided different FDA-approved free-choice CTC-medicated mineral formulations, all intended to provide cattle a dosage of 0.5 to 2.0 mg CTC/lb bodyweight per day. A closed-herd, comprised of Hereford-Angus cows, naturally endemic for anaplasmosis, were grazed in five different pastures with one herd serving as an untreated control group. The other cattle herds were randomly assigned one of four FDA-approved CTC-medicated mineral formulations (700, 5000, 6000, and 8000 g CTC/ton) labeled for “the control of active anaplasmosis” and provided their respective CTC-medicated mineral formulation for five consecutive months. Fecal samples were collected monthly from a subset of cows (n = 6 or 10) per pasture. Fecal samples were cultured for E. coli isolates and the minimal inhibitory concentration of CTC was determined. Baseline CTC-susceptibility of E. coli was variable among all treatment and control groups. The susceptibility of E. coli isolates was significantly different between study herds over the treatment period (p = 0.0037 across time and 0.009 at the final sampling time). The interaction between study herds and treatment period was not significant (p = 0.075).
Efficacy of Selenourea Organocatalysts in Asymmetric Michael Reactions under Standard and Solvent-Free Conditions
Authors: Zielińska-Błajet Mariola , Mała Żaneta A. , Kowalczyk Rafał
Published: December 2021

By varying the steric and electronic surroundings of the hydrogen-bonding motif, the novel chiral Cinchona-alkaloid based selenoureas were developed. Acting as bifunctional catalysts, they were applied in the Michael reactions of dithiomalonate and nitrostyrene providing chiral adducts with up to 96% ee. The asymmetric Michael–-hemiacetalization reaction of benzylidene pyruvate and dimedone, performed with the assistance of 5 mol% of selenoureas, furnished the product with up to 93% ee and excellent yields. The effectiveness of the new hydrogen-bond donors was also proved in solvent-free reactions under ball mill conditions, supporting the sustainability of the devised catalytic protocol.
The Implication of Low Dose Dimethyl Sulfoxide on Mitochondrial Function and Oxidative Damage in Cultured Cardiac and Cancer Cells
Authors: Sangweni Nonhlakanipho F. , Dludla Phiwayinkosi V. , Chellan Nireshni , Mabasa Lawrence , Sharma Jyoti R. , Johnson Rabia
Published: December 2021

Although numerous studies have demonstrated the biological and multifaceted nature of dimethyl sulfoxide (DMSO) across different in vitro models, the direct effect of “non-toxic” low DMSO doses on cardiac and cancer cells has not been clearly explored. In the present study, H9c2 cardiomyoblasts and MCF-7 breast cancer cells were treated with varying concentrations of DMSO (0.001–3.7%) for 6 days. Here, DMSO doses < 0.5% enhanced the cardiomyoblasts respiratory control ratio and cellular viability relative to the control cells. However, 3.7% DMSO exposure enhanced the rate of apoptosis, which was driven by mitochondrial dysfunction and oxidative stress in the cardiomyoblasts. Additionally, in the cancer cells, DMSO (≥0.009) led to a reduction in the cell’s maximal respiratory capacity and ATP-linked respiration and turnover. As a result, the reduced bioenergetics accelerated ROS production whilst increasing early and late apoptosis in these cells. Surprisingly, 0.001% DMSO exposure led to a significant increase in the cancer cells proliferative activity. The latter, therefore, suggests that the use of DMSO, as a solvent or therapeutic compound, should be applied with caution in the cancer cells. Paradoxically, in the cardiomyoblasts, the application of DMSO (≤0.5%) demonstrated no cytotoxic or overt therapeutic benefits.
Natural Xanthine Oxidase Inhibitor 5-O-Caffeoylshikimic Acid Ameliorates Kidney Injury Caused by Hyperuricemia in Mice
Authors: Zhang Dong , Zhao Mojiao , Li Yumei , Zhang Dafang , Yang Yong , Li Lijing
Published: December 2021

Xanthine oxidase (XOD) inhibition has long been considered an effective anti-hyperuricemia strategy. To identify effective natural XOD inhibitors with little side effects, we performed a XOD inhibitory assay-coupled isolation of compounds from Smilacis Glabrae Rhizoma (SGR), a traditional Chinese medicine frequently prescribed as anti-hyperuricemia agent for centuries. Through the in vitro XOD inhibitory assay, we obtained a novel XOD inhibitor, 5-O-caffeoylshikimic acid (#1, 5OCSA) with IC50 of 13.96 μM, as well as two known XOD inhibitors, quercetin (#3) and astilbin (#6). Meanwhile, we performed in silico molecular docking and found 5OCSA could interact with the active sites of XOD (PDB ID: 3NVY) with a binding energy of −8.6 kcal/mol, suggesting 5OCSA inhibits XOD by binding with its active site. To evaluate the in vivo effects on XOD, we generated a hyperuricemia mice model by intraperitoneal injection of potassium oxonate (300 mg/kg) and oral gavage of hypoxanthine (500 mg/kg) for 7 days. 5OCSA could inhibit both hepatic and serum XOD in vivo, together with an improvement of histological and multiple serological parameters in kidney injury and HUA. Collectively, our results suggested that 5OCSA may be developed into a safe and effective XOD inhibitor based on in vitro, in silico and in vivo evidence.
Mathematical Analysis of Reaction–Diffusion Equations Modeling the Michaelis–Menten Kinetics in a Micro-Disk Biosensor
Authors: Khan Naveed Ahmad , Alshammari Fahad Sameer , Romero Carlos Andrés Tavera , Sulaiman Muhammad , Laouini Ghaylen
Published: December 2021

In this study, we have investigated the mathematical model of an immobilized enzyme system that follows the Michaelis–Menten (MM) kinetics for a micro-disk biosensor. The film reaction model under steady state conditions is transformed into a couple differential equations which are based on dimensionless concentration of hydrogen peroxide with enzyme reaction (H) and substrate (S) within the biosensor. The model is based on a reaction–diffusion equation which contains highly non-linear terms related to MM kinetics of the enzymatic reaction. Further, to calculate the effect of variations in parameters on the dimensionless concentration of substrate and hydrogen peroxide, we have strengthened the computational ability of neural network (NN) architecture by using a backpropagated Levenberg–Marquardt training (LMT) algorithm. NNs–LMT algorithm is a supervised machine learning for which the initial data set is generated by using MATLAB built in function known as “pdex4”. Furthermore, the data set is validated by the processing of the NNs–LMT algorithm to find the approximate solutions for different scenarios and cases of mathematical model of micro-disk biosensors. Absolute errors, curve fitting, error histograms, regression and complexity analysis further validate the accuracy and robustness of the technique.
When Preschoolers Interact with an Educational Robot, Does Robot Feedback Influence Engagement?
Authors: de Haas Mirjam , Vogt Paul , Krahmer Emiel
Published: December 2021

In this paper, we examine to what degree children of 3–4 years old engage with a task and with a social robot during a second-language tutoring lesson. We specifically investigated whether children’s task engagement and robot engagement were influenced by three different feedback types by the robot: adult-like feedback, peer-like feedback and no feedback. Additionally, we investigated the relation between children’s eye gaze fixations and their task engagement and robot engagement. Fifty-eight Dutch children participated in an English counting task with a social robot and physical blocks. We found that, overall, children in the three conditions showed similar task engagement and robot engagement; however, within each condition, they showed large individual differences. Additionally, regression analyses revealed that there is a relation between children’s eye-gaze direction and engagement. Our findings showed that although eye gaze plays a significant role in measuring engagement and can be used to model children’s task engagement and robot engagement, it does not account for the full concept and engagement still comprises more than just eye gaze.
New Applications of Lipid and Polymer-Based Nanoparticles for Nucleic Acids Delivery
Authors: Niculescu Adelina-Gabriela , Bîrcă Alexandra Cătălina , Grumezescu Alexandru Mihai
Published: December 2021

Nucleic acids represent a promising lead for engineering the immune system. However, naked DNA, mRNA, siRNA, and other nucleic acids are prone to enzymatic degradation and face challenges crossing the cell membrane. Therefore, increasing research has been recently focused on developing novel delivery systems that are able to overcome these drawbacks. Particular attention has been drawn to designing lipid and polymer-based nanoparticles that protect nucleic acids and ensure their targeted delivery, controlled release, and enhanced cellular uptake. In this respect, this review aims to present the recent advances in the field, highlighting the possibility of using these nanosystems for therapeutic and prophylactic purposes towards combatting a broad range of infectious, chronic, and genetic disorders.
A Novel Self-Assembled Graphene-Based Flame Retardant: Synthesis and Flame Retardant Performance in PLA
Authors: Yang Peixin , Wu Hanguang , Yang Feifei , Yang Jie , Wang Rui , Zhu Zhiguo
Published: December 2021

In this study, a novel flame retardant (PMrG) was developed by self-assembling melamine and phytic acid (PA) onto rGO, and then applying it to the improvement of the flame resistance of PLA. PMrG simultaneously decreases the peak heat release rate (pHRR) and the total heat release (THR) of the composite during combustion, and enhances the LOI value and the time to ignition (TTI), thus significantly improving the flame retardancy of the composite. The flame retardant mechanism of the PMrG is also investigated. On one hand, the dehydration of PA and the decomposition of melamine in PMrG generate non-flammable volatiles, such as H2O and NH3, which dilute the oxygen concentration around the combustion front of the composite. On the other hand, the rGO, melamine, and PA components in PMrG create a synergistic effect in promoting the formation of a compact char layer during the combustion, which plays a barrier role and effectively suppresses the release of heat and smoke. In addition, the PMrGs in PLA exert a positive effect on the crystallization of the PLA matrix, thus playing the role of nucleation agent.
Effect of Ultra-High-Molecular-Weight Molecular Chains on the Morphology, Crystallization, and Mechanical Properties of Polypropylene
Authors: Kida Takumitsu , Kimura Takeyoshi , Eno Ayaka , Janchai Khunanya , Yamaguchi Masayuki , Otsuki Yasuhiko , Kimura Tokutaro , Mizukawa Tomoaki , Murakami Tomoya , Hato Kazuki , Okawa Tomoya
Published: December 2021

The effects of the ultra-high-molecular-weight (UHMW) component of polypropylene (PP) on its rheological properties, crystallization behavior, and solid-state mechanical properties were investigated using various measurement techniques. The terminal relaxation time—determined by measuring the linear viscoelasticity—was increased by adding the UHMW component. The increase in the melt elasticity produced by adding the UHMW component was observed by measuring the steady-state shear flow, although the shear viscosity was not greatly affected. Owing to the long characteristic time of the Rouse relaxation of the UHMW component, PP with the UHMW component formed highly oriented structures through a shear-induced crystallization process. The addition of the UHMW component enhanced the orientation and regularity of crystalline structure for extruded films. Therefore, the Young′s modulus, yield stress, and strength were higher in the PP film containing the UHMW component than in one without the UHMW component, irrespective of the direction of tensile deformation.
Integration and Application of Multimodal Measurement Techniques: Relevance of Photogrammetry to Orthodontics
Authors: Pojda Dariusz , Tomaka Agnieszka Anna , Luchowski Leszek , Tarnawski Michał
Published: December 2021

Multimodal imaging, including 3D modalities, is increasingly being applied in orthodontics, both as a diagnostic tool and especially for the design of intraoral appliances, where geometric accuracy is very important. Laser scanners and other precision 3D-imaging devices are expensive and cumbersome, which limits their use in medical practice. Photogrammetry, using ordinary 2D photographs or video recordings to create 3D imagery, offers a cheaper and more convenient alternative, replacing the specialised equipment with handy consumer cameras. The present study addresses the question of to what extent, and under what conditions, this technique can be an adequate replacement for the 3D scanner. The accuracy of simple surface reconstruction and of model embedding achieved with photogrammetry was verified against that obtained with a triangulating laser scanner. To roughly evaluate the impact of image imperfections on photogrammetric reconstruction, the photographs for photogrammetry were taken under various lighting conditions and were used either raw or with a blur-simulating defocus. Video footage was also tested as another 2D-imaging modality feeding data into photogrammetry. The results show the significant potential of photogrammetric techniques.
Sound Source Localization Using a Convolutional Neural Network and Regression Model
Authors: Tan Tan-Hsu , Lin Yu-Tang , Chang Yang-Lang , Alkhaleefah Mohammad
Published: December 2021

In this research, a novel sound source localization model is introduced that integrates a convolutional neural network with a regression model (CNN-R) to estimate the sound source angle and distance based on the acoustic characteristics of the interaural phase difference (IPD). The IPD features of the sound signal are firstly extracted from time-frequency domain by short-time Fourier transform (STFT). Then, the IPD features map is fed to the CNN-R model as an image for sound source localization. The Pyroomacoustics platform and the multichannel impulse response database (MIRD) are used to generate both simulated and real room impulse response (RIR) datasets. The experimental results show that an average accuracy of 98.96% and 98.31% are achieved by the proposed CNN-R for angle and distance estimations in the simulation scenario at SNR = 30 dB and RT60 = 0.16 s, respectively. Moreover, in the real environment, the average accuracies of the angle and distance estimations are 99.85% and 99.38% at SNR = 30 dB and RT60 = 0.16 s, respectively. The performance obtained in both scenarios is superior to that of existing models, indicating the potential of the proposed CNN-R model for real-life applications.
FRET Measurement of Polymer Response under Shear
Authors: Iwao Ryo , Yamaguchi Hiroki , Obata Makoto , Matsuda Yu
Published: December 2021

Polymer solutions under shear flow are often observed in manufacturing processes. Classically, polymer behavior is represented by Kuhn’s bead-spring model, in which only the elongation of polymer chains is assumed. In recent years, the compression of polymer chains under shear flow has been reported. In this study, we investigated the behavior of polymer chains dissolved in various concentrations under shear flow. We measured the time variation of the fluorescence intensity emitted from a FRET (fluorescence resonance energy transfer) polymer, which enabled us to study the change in the distance between both ends of a polymer chain. The polymer chains appeared to stretch and compress depending on the concentration of the polymer solution. The results showed that the deformation of polymer chains was different from the classical theory. The FRET measurement is a promising diagnostic method for understanding the dynamics of polymer chains.
Closing Connectivity Gap: An Overview of Mobile Coverage Solutions for Not-Spots in Rural Zones
Authors: Cabrera-Castellanos Diego Fernando , Aragón-Zavala Alejandro , Castañón-Ávila Gerardo
Published: December 2021

Access to broadband communications in different parts of the world has become a priority for some governments and regulatory authorities around the world in recent years. Building new digital roads and pursuing a connected society includes looking for easier access to the internet. In general, not all areas where people congregate are fully covered, especially in rural zones, thus restricting access to data communications and inducing inequality. In the present review article, we have comprehensively surveyed the use of three platforms to deliver broadband services to such remote and low-income areas, and they are proposed as follows: unmanned aerial vehicles (UAV), altitude platforms (AP), and low-Earth orbit (LEO) satellites. These novel strategies support the connected and accessible world hypothesis. Hence, UAVs are considered a noteworthy solution since their efficient maneuverability can solve rural coverage issues or not-spots.
AI-Enabled Framework for Fog Computing Driven E-Healthcare Applications
Authors: Sodhro Ali Hassan , Zahid Noman
Published: December 2021

Artificial Intelligence (AI) is the revolutionary paradigm to empower sixth generation (6G) edge computing based e-healthcare for everyone. Thus, this research aims to promote an AI-based cost-effective and efficient healthcare application. The cyber physical system (CPS) is a key player in the internet world where humans and their personal devices such as cell phones, laptops, wearables, etc., facilitate the healthcare environment. The data extracting, examining and monitoring strategies from sensors and actuators in the entire medical landscape are facilitated by cloud-enabled technologies for absorbing and accepting the entire emerging wave of revolution. The efficient and accurate examination of voluminous data from the sensor devices poses restrictions in terms of bandwidth, delay and energy. Due to the heterogeneous nature of the Internet of Medical Things (IoMT), the driven healthcare system must be smart, interoperable, convergent, and reliable to provide pervasive and cost-effective healthcare platforms. Unfortunately, because of higher power consumption and lesser packet delivery rate, achieving interoperable, convergent, and reliable transmission is challenging in connected healthcare. In such a scenario, this paper has fourfold major contributions. The first contribution is the development of a single chip wearable electrocardiogram (ECG) with the support of an analog front end (AFE) chip model (i.e., ADS1292R) for gathering the ECG data to examine the health status of elderly or chronic patients with the IoT-based cyber physical system (CPS). The second proposes a fuzzy-based sustainable, interoperable, and reliable algorithm (FSIRA), which is an intelligent and self-adaptive decision-making approach to prioritize emergency and critical patients in association with the selected parameters for improving healthcare quality at reasonable costs. The third is the proposal of a specific cloud-based architecture for mobile and connected healthcare. The fourth is the identification of the right balance between reliability, packet loss ratio, convergence, latency, interoperability, and throughput to support an adaptive IoMT driven connected healthcare. It is examined and observed that our proposed approaches outperform the conventional techniques by providing high reliability, high convergence, interoperability, and a better foundation to analyze and interpret the accuracy in systems from a medical health aspect. As for the IoMT, an enabled healthcare cloud is the key ingredient on which to focus, as it also faces the big hurdle of less bandwidth, more delay and energy drain. Thus, we propose the mathematical trade-offs between bandwidth, interoperability, reliability, delay, and energy dissipation for IoMT-oriented smart healthcare over a 6G platform.
The Development of Digital Image Colorimetric Quantitative Analysis of Multi-Explosives Using Polymer Gel Sensors
Authors: Thipwimonmas Yudtapum , Thiangchanya Adul , Phonchai Apichai , Thainchaiwattana Sittipoom , Jomsati Wachirawit , Jomsati Sunisa , Tayayuth Kunanunt , Limbut Warakorn
Published: December 2021

Polymer gel sensors on 96-well plates were successfully used to detect four different multi-explosives, including 2,4,6-trinitrotoluene (TNT), 2,4-dinitrotoluene (DNT), nitrite, and perchlorate. The products of reactions between the explosives and the polymer gel sensors were digitally captured, and the images were analyzed by a developed Red–Green–Blue (RGB) analyzer program on a notebook computer. RGB color analysis provided the basic color data of the reaction products for the quantification of the explosives. The results provided good linear range, sensitivity, limit of detection, limit of quantitation, specificity, interference tolerance, and recovery. The method demonstrated great potential to detect explosives by colorimetric analysis of digital images of samples on 96-well plates. It is possible to apply the proposed method for quantitative on-site field screening of multi-explosives.
Assessing Patient-Specific Microwave Breast Imaging in Clinical Case Studies
Authors: O’Loughlin Declan , Elahi Muhammad Adnan , Lavoie Benjamin R. , Fear Elise C. , O’Halloran Martin
Published: December 2021

Microwave breast imaging has seen increasing use in clinical investigations in the past decade with over eight systems having being trialled with patients. The majority of systems use radar-based algorithms to reconstruct the image shown to the clinician which requires an estimate of the dielectric properties of the breast to synthetically focus signals to reconstruct the image. Both simulated and experimental studies have shown that, even in simplified scenarios, misestimation of the dielectric properties can impair both the image quality and tumour detection. Many methods have been proposed to address the issue of the estimation of dielectric properties, but few have been tested with patient images. In this work, a leading approach for dielectric properties estimation based on the computation of many candidate images for microwave breast imaging is analysed with patient images for the first time. Using five clinical case studies of both healthy breasts and breasts with abnormalities, the advantages and disadvantages of computational patient-specific microwave breast image reconstruction are highlighted.
Review of Optical Humidity Sensors
Authors: Rao Xing , Zhao Lin , Xu Lukui , Wang Yuhang , Liu Kuan , Wang Ying , Chen George Y. , Liu Tongyu , Wang Yiping
Published: December 2021

Optical humidity sensors have evolved through decades of research and development, constantly adapting to new demands and challenges. The continuous growth is supported by the emergence of a variety of optical fibers and functional materials, in addition to the adaptation of different sensing mechanisms and optical techniques. This review attempts to cover the majority of optical humidity sensors reported to date, highlight trends in design and performance, and discuss the challenges of different applications.
The CODYSUN Approach: A Novel Distributed Paradigm for Dynamic Spectrum Sharing in Satellite Communications
Authors: Jabandžić Irfan , Firyaguna Fadhil , Giannoulis Spilios , Shahid Adnan , Mukhopadhyay Atri , Ruffini Marco , Moerman Ingrid
Published: December 2021

With a constant increase in the number of deployed satellites, it is expected that the current fixed spectrum allocation in satellite communications (SATCOM) will migrate towards more dynamic and flexible spectrum sharing rules. This migration is accelerated due to the introduction of new terrestrial services in bands used by satellite services. Therefore, it is important to design dynamic spectrum sharing (DSS) solutions that can maximize spectrum utilization and support coexistence between a high number of satellite and terrestrial networks operating in the same spectrum bands. Several DSS solutions for SATCOM exist, however, they are mainly centralized solutions and might lead to scalability issues with increasing satellite density. This paper describes two distributed DSS techniques for efficient spectrum sharing across multiple satellite systems (geostationary and non-geostationary satellites with earth stations in motion) and terrestrial networks, with a focus on increasing spectrum utilization and minimizing the impact of interference between satellite and terrestrial segments. Two relevant SATCOM use cases have been selected for dynamic spectrum sharing: the opportunistic sharing of satellite and terrestrial systems in (i) downlink Ka-band and (ii) uplink Ka-band. For the two selected use cases, the performance of proposed DSS techniques has been analyzed and compared to static spectrum allocation. Notable performance gains have been obtained.
Impact of Cyclone Yaas 2021 Aggravated by COVID-19 Pandemic in the Southwest Coastal Zone of Bangladesh
Authors: Subhani Rizwana , Saqib Shahab E. , Rahman Md. Anishur , Ahmad Mokbul Morshed , Pradit Siriporn
Published: December 2021

The severe tropical Cyclone Yaas hit on 26 May 2021 in 16 coastal districts of Bangladesh and affected 1.30 million people. Moreover, the study areas are highly affected by the COVID-19 pandemic, which has increased the vulnerability of the people. Therefore, the objective of this study is to assess the impact of cyclone Yass aggravated by the COVID-19 pandemic in the southwest coastal zone of Bangladesh. COVID-19-aggregated Cyclone Yaas impact data at the household level were collected from Kalapara Upozilla of Potuakhali district, the area most affected by Cyclone Yaas. A total of 196 households were surveyed, and a quantitative approach was applied to analyse the data. The results show that households in the study area were severely affected by Cyclone Yaas in terms of income, housing, food consumption patterns, and water sanitation and hygiene. The outcome also revealed that the affected households received relief from the government, international/non-government organizations, donor agencies, as well as adopted coping strategies such as obtaining credit, selling assets, reducing daily meal intake, and tapping into savings. These strategies may be useful for a temporary recovery but not for the long term. The results of the study will help policymakers to reform policies.
Internal Change Mechanism of Integrated Reporting: A Field Study
Authors: Akbas Ahmet , Coskun Ali , Demirkan Sebahattin , Karamustafa Osman
Published: December 2021

Integrated reporting has a considerable impact on the decision-making of all stakeholders in firms. Moreover, the increasing importance of integrated reporting has brought about changes in the reporting process. The purpose of this study is to analyze the internal changes in the integrated reporting process in Turkish business entities. To achieve this purpose, a semi-structured interview with managers of these entities was conducted. The data obtained from the interviews were analyzed then the results were evaluated. We find that entities undergo a structural internal change that affects all components of firms in their reporting process, due to the impact of integrated reporting implementation and expectations.
Understanding Consumer Travel Behavior during COVID-19
Authors: Chen Xianglan , Duan Yachao , Ali Laiba , Duan Yahui , Ryu Kisang
Published: December 2021

Since the COVID-19 outbreak worldwide, the global tourism industry has taken a severe hit. To fully understand the impact of the pandemic on tourists’ travel behavior, an intercultural survey was carried out through a large-scale online questionnaire. This survey aims to determine whether cultural differences and different ages might play a role in tourists’ behavior during the COVID-19. Data collected from 942 respondents from mainland China and overseas through different age groups were subjected to data analysis. The results demonstrate cognition and consumer behavior differentiate culturally and significantly between different ages, which is highlighted when they choose travel modes, transportation, and companions. The implications of the study are also provided in the end.
Data-Driven Remaining Useful Life Prediction for Lithium-Ion Batteries Using Multi-Charging Profile Framework: A Recurrent Neural Network Approach
Authors: Ansari Shaheer , Ayob Afida , Hossain Lipu Molla Shahadat , Hussain Aini , Saad Mohamad Hanif Md
Published: December 2021

Remaining Useful Life (RUL) prediction for lithium-ion batteries has received increasing attention as it evaluates the reliability of batteries to determine the advent of failure and mitigate battery risks. The accurate prediction of RUL can ensure safe operation and prevent risk failure and unwanted catastrophic occurrence of the battery storage system. However, precise prediction for RUL is challenging due to the battery capacity degradation and performance variation under temperature and aging impacts. Therefore, this paper proposes the Multi-Channel Input (MCI) profile with the Recurrent Neural Network (RNN) algorithm to predict RUL for lithium-ion batteries under the various combinations of datasets. Two methodologies, namely the Single-Channel Input (SCI) profile and the MCI profile, are implemented, and their results are analyzed. The verification of the proposed model is carried out by combining various datasets provided by NASA. The experimental results suggest that the MCI profile-based method demonstrates better prediction results than the SCI profile-based method with a significant reduction in prediction error with regard to various evaluation metrics. Additionally, the comparative analysis has illustrated that the proposed RNN method significantly outperforms the Feed Forward Neural Network (FFNN), Back Propagation Neural Network (BPNN), Function Fitting Neural Network (FNN), and Cascade Forward Neural Network (CFNN) under different battery datasets.
Some Remarks towards a Better Understanding of the Use of Concrete Recycled Aggregate: A Review
Authors: Grabiec Anna M. , Kim Jeonghyun , Ubysz Andrzej , Bilbao Pilar
Published: December 2021

Research on recycled concrete aggregates (RCAs) has been progressively advanced. Beyond replacing natural aggregates with RCA, discussions have been held on the effect of the parent concrete and repeatedly recycled aggregate concrete. Although it has been reported that RCA can be technically used for structural concrete, due to several other factors, RCA is mainly used for sub-bases. Therefore, identifying these factors is the key to promoting the use of RCA. Therefore, this review study first briefly summarizes the physical and chemical characteristics of RCA compared to natural aggregate, and reviews the effects of parent concrete and repeatedly recycled aggregate on next generation concrete. This study also briefly discusses the RCA standards of various countries and the factors that hinder the widespread use of RCA. The results show that there is a correlation in properties between parent concrete and the next generation concrete, and the properties of concrete decrease when RCA is used repeatedly. In addition, on the basis of the literature review, factors hindering the use of RCA were found to be unstable supply and demand, economic feasibility, and negative perceptions.
An Intelligent Hybrid Sentiment Analyzer for Personal Protective Medical Equipments Based on Word Embedding Technique: The COVID-19 Era
Authors: Obiedat Ruba , Al-Qaisi Laila , Qaddoura Raneem , Harfoushi Osama , Al-Zoubi Ala’ M.
Published: December 2021

Due to the accelerated growth of symmetrical sentiment data across different platforms, experimenting with different sentiment analysis (SA) techniques allows for better decision-making and strategic planning for different sectors. Specifically, the emergence of COVID-19 has enriched the data of people’s opinions and feelings about medical products. In this paper, we analyze people’s sentiments about the products of a well-known e-commerce website named Alibaba.com. People’s sentiments are experimented with using a novel evolutionary approach by applying advanced pre-trained word embedding for word presentations and combining them with an evolutionary feature selection mechanism to classify these opinions into different levels of ratings. The proposed approach is based on harmony search algorithm and different classification techniques including random forest, k-nearest neighbor, AdaBoost, bagging, SVM, and REPtree to achieve competitive results with the least possible features. The experiments are conducted on five different datasets including medical gloves, hand sanitizer, medical oxygen, face masks, and a combination of all these datasets. The results show that the harmony search algorithm successfully reduced the number of features by 94.25%, 89.5%, 89.25%, 92.5%, and 84.25% for the medical glove, hand sanitizer, medical oxygen, face masks, and whole datasets, respectively, while keeping a competitive performance in terms of accuracy and root mean square error (RMSE) for the classification techniques and decreasing the computational time required for classification.
Space, Matter and Interactions in a Quantum Early Universe. Part II: Superalgebras and Vertex Algebras
Authors: Truini Piero , Marrani Alessio , Rios Michael , Irwin Klee
Published: December 2021

In our investigation on quantum gravity, we introduce an infinite dimensional complex Lie algebra gu that extends e9. It is defined through a symmetric Cartan matrix of a rank 12 Borcherds algebra. We turn gu into a Lie superalgebra sgu with no superpartners, in order to comply with the Pauli exclusion principle. There is a natural action of the Poincaré group on sgu, which is an automorphism in the massive sector. We introduce a mechanism for scattering that includes decays as particular resonant scattering. Finally, we complete the model by merging the local sgu into a vertex-type algebra.
Applicable Image Security Based on New Hyperchaotic System
Authors: Wang Jingya , Song Xianhua , Wang Huiqiang , Abd El-Latif Ahmed A.
Published: December 2021

Hyperchaotic systems are widely applied in the cryptography domain on account of their more complex dynamical behavior. In view of this, the greatest contribution of this paper is that a two-dimensional Sine coupling Logistic modulated Sine (2D-SCLMS) system is proposed based on Logistic map and Sine map. By a series of analyses, including Lyapunov index (LE), 0–1 test, two complexity analysis methods, and two entropy analysis methods, it is concluded that the new 2D-SCLMS map is hyperchaotic with a wider range of chaos and more complex randomness. The new system combined with two-dimensional Logistic-Sine Coupling Mapping (2D-LSCM) is further applied to an image encryption application. SHA-384 is used to generate the initial values and parameters of the two chaotic systems. Symmetric keys are generated during this operation, which can be applied to the proposed image encryption and decryption algorithms. The encryption process and the decryption process of the new image encryption approaches mainly include pixel scrambling, exclusive NOR (Xnor), and diffusion operations. Multiple experiments illustrate that this scheme has higher security and lower time complexity.
Case Study of Deep Learning Model of Temperature-Induced Deflection of a Cable-Stayed Bridge Driven by Data Knowledge
Authors: Yue Zixiang , Ding Youliang , Zhao Hanwei , Wang Zhiwen
Published: December 2021

A cable-stayed bridge is a typical symmetrical structure, and symmetry affects the deformation characteristics of such bridges. The main girder of a cable-stayed bridge will produce obvious deflection under the inducement of temperature. The regression model of temperature-induced deflection is hoped to provide a comparison value for bridge evaluation. Based on the temperature and deflection data obtained by the health monitoring system of a bridge, establishing the correlation model between temperature and temperature-induced deflection is meaningful. It is difficult to complete a high-quality model only by the girder temperature. The temperature features based on prior knowledge from the mechanical mechanism are used as the input information in this paper. At the same time, to strengthen the nonlinear ability of the model, this paper selects an independent recurrent neural network (IndRNN) for modeling. The deep learning neural network is compared with machine learning neural networks to prove the advancement of deep learning. When only the average temperature of the main girder is input, the calculation accuracy is not high regardless of whether the deep learning network or the machine learning network is used. When the temperature information extracted by the prior knowledge is input, the average error of IndRNN model is only 2.53%, less than those of BPNN model and traditional RNN. Combining knowledge with deep learning is undoubtedly the best modeling scheme. The deep learning model can provide a comparison value of bridge deformation for bridge management.
A Comparison of Two Different Light Booths for Measuring Color Difference of Metameric Pairs
Authors: Mukthy Azmary Akter , Vik Michal , Viková Martina
Published: December 2021

A standardized source of light is essential for visual color assessments, which is why lighting booths were developed. For the best results in visual assessment, it is important to consider the right choice of light source, the right viewing conditions, and the variability of the viewer. To date, many light booth technologies have been introduced to meet user demands. Since most of the light sources on the market are characterized by the designer or manufacturer, the resulting variations from booth-to-booth remain. In this study, we compared the performance of two standard light booths to assess the color difference of eleven metameric pairs. In this study, we checked an earlier technology-based light booth that is still used in the textile industry and contains illuminant A (Tungsten lamp) with CCT 2700 K, TL84 (tri-band fluorescent tube) with CCT 4000 K, and simulator D65 (CCT 6500 K) with a different light booth whose original light sources have been replaced by currently available LED retro kits from equivalent CCTs. As an inexperienced customer or industrial user, our question was, how important is this replacement? The results revealed that two different standard lighting technologies with similar CCTs cannot reproduce the same estimates because the light sources produced different SPDs. It is illustrating that caution is necessary when comparing results obtained from two different light booths containing light sources with similar CCTs but different SPDs. This comparative study suggested that the variability of the light sources’ SPDs or the observer or the sample should be modeled considering light booth’s technology to estimate its contribution to the overall variability. The close relationship between perceived and CAM02-UCS suggests that if both booths are used after the light sources have been calibrated, a formula based on color appearance models must be used to predict color appearance. To obtain better agreement between perceived and calculated color difference, one must need to avoid light booths with nominally white light sources.
Potentially Toxic Element Levels in Atmospheric Particulates and Health Risk Estimation around Industrial Areas of Maros, Indonesia
Authors: Rauf Annisa Utami , Mallongi Anwar , Lee Kiyoung , Daud Anwar , Hatta Muhammad , Al Madhoun Wesam , Astuti Ratna Dwi Puji
Published: December 2021

Air quality deterioration is a major environmental problem in Indonesia. This study evaluated the levels and health risks of potentially toxic elements (PTEs) in Maros Regency, Indonesia. Total suspended particulate matter was collected from industrial areas for PTE (Al, Pb, Cr, Cu, Ni, As and Zn) analysis using inductively coupled plasma optical emission spectrometry (ICP-OES). Samples were collected from six critical areas in the Bantimurung region as that is where marble, cement and limestone industries are located. A calculation of the non-carcinogenic and cancer risks was performed to determine the potential health exposures in adults and children. A Monte Carlo simulation with 10,000 iterations and a sensitivity analysis was carried out to identify the risk probability and the most sensitive variable contributing to cancer risk from PTE exposure in humans. The results showed that the concentration of PTEs decreased in the order of Zn > Al > Cr > Pb > Cu > Ni > As in the wet season, and Zn > Al > Pb > As > Cr > Cu > Ni in the dry season. The hazard index (HI) value for children was 2.12, indicating a high non-carcinogenic risk for children. The total cancer risk (TCR) values in adults and children were 3.11 × 10−5 and 1.32 × 10−4, respectively, implying that both are at risk for developing cancer. The variables with the most contribution to cancer risk from As, Cr and Pb exposure in adults and children were As concentration (33.9% and 41.0%); exposure duration (ED) (34.3%) and SA (40.7%); and SA (98.7 % and 45.4%), respectively. These findings could be used as the scientific basis for public health intervention and to raise awareness of the harmful health effects of particulate bound PTEs