bluuebunny/crossref_metadata_2025 huggingface dataset:
Special Issue Recurrent Pregnancy Loss: Etiology, Diagnosis, and Therapy
Authors: Christiansen Ole Bjarne
Published: October 2021

The definition of recurrent pregnancy losses (RPL) varies between guidelines from different national and international scientific societies, but overall, a history of two or more (or alternatively, three or more) confirmed pregnancy losses is required for the diagnosis [...]
Can We Improve the Functional Threshold Power Test by Adding High-Intensity Priming Arm-Crank?
Authors: Valiulin Dmitri , Purge Priit , Hofmann Peter , Mäestu Jarek , Jürimäe Jaak
Published: October 2021

The aim of the present study was to evaluate the effects of arm-crank induced priming on subsequent 20 min Functional Threshold Power Test among 11 well-trained male cyclists (18.8 ± 0.9 years; 182 ± 5 cm; 73.0 ± 6.6 kg; V˙O2max 67.9 ± 5.1 mL·kg−1·min−1). Participants completed an incremental test and two maximal performance tests (MPTs) in a randomized order. Warm-up prior to MPTlow consisted of 20 min aerobic exercise and 25 s high-intensity all-out arm crank effort was added to warm-up in MPThigh. Constant intensities for the first 17 min of MPT were targeting to achieve a similar relative fatigue according to participants’ physiological capacity before the last 3 min all-out spurt. Final 3 min all-out spurt power was 4.94 ± 0.27 W·kg−1 and 4.85 ± 0.39 W·kg−1 in MPTlow and MPThigh, respectively (not statistically different: p = 0.116; d = 0.5). Blood lactate [La] levels just before the start were higher (p < 0.001; d = 2.6) in MPThigh (5.6 ± 0.5 mmol·L−1) compared to MPTlow (1.1 ± 0.1 mmol·L−1). According to V˙CO2 and net [La] data, significantly higher anaerobic energy production was detected among MPTlow condition. In conclusion, priming significantly reduced anaerobic energy contribution but did neither improve nor decrease group mean performance although effects were variable. We suggest priming to have beneficial effects based on previous studies; however, the effects are individual and additional studies are needed to distinguish such detailed effects in single athletes.
Properties of Diamond-Based Neutron Detectors Operated in Harsh Environments
Authors: Angelone Maurizio , Verona Claudio
Published: October 2021

Diamond is widely studied and used for the detection of direct and indirect ionizing particles because of its many physical and electrical outstanding properties, which make this material very attractive as a fast-response, high-radiation-hardness and low-noise radiation detector. Diamond detectors are suited for detecting almost all types of ionizing radiation (e.g., neutrons, ions, UV, and X-ray) and are used in a wide range of applications including ones requiring the capability to withstand harsh environments (e.g., high temperature, high radiation fluxes, or strong chemical conditions). After reviewing the basic properties of the diamond detector and its working principle detailing the physics aspects, the paper discusses the diamond as a neutron detector and reviews its performances in harsh environments.
Physicochemical Study of the Self-Disintegration of Calcium Orthosilicate (β→γ) in the Presence of the C12A7 Aluminate Phase
Authors: Pyzalski Michał , Dąbek Jarosław , Adamczyk Anna , Brylewski Tomasz
Published: October 2021

The β-γ polymorphic transition of calcium orthosilicate (C2S) is a key phenomenon in cement chemistry. During this transition, the compound expands due to structural changes and a significant reduction in its density is observed, leading to its disintegration into a powder with a very high specific surface area. Owing to this tendency of the C2S material to “self-disintegrate”, its production is energy-efficient and thus environmentally friendly. A physicochemical study of the self-disintegration process was conducted with the aim of determining how the amount of dodecacalcium hepta-aluminate (C12A7) in calcium orthosilicate (C2S) affects the temperature at which the polymorphic transi-tions from α’L-C2S to β-C2S and from β-C2S to γ-C2S undergo stabilization. The applied techniques included differential thermal analysis (DTA), calorimetry and X-ray diffraction (XRD), and they made it possible to determine what C2S/C12A7 phase ratio in the samples and what cooling rate constitute the optimal conditions of the self-disintegration process. The optimal cooling rate for C2S materials with a C12A7 content of up to 60 wt% was determined to be 5 K·min−1. The optimal mass ratio of C2S/C12A7 was found to be 70/30, which ensures both efficient self-disintegration and desirable grain size distribution.
Fracture Resistance and Failure Mode of Mandibular Molar Restored by Occlusal Veneer: Effect of Material Type and Dental Bonding Surface
Authors: Al-Zordk Walid , Saudi Alaa , Abdelkader Abdelraheem , Taher Mansoura , Ghazy Mohamed
Published: October 2021

This study assesses the effect of the material type (lithium disilicate, zirconia, and polymer-infiltrated ceramic) and dental bonding substrates (dentin, dentin with intra-coronal cavity, and dentin with composite filling) on the fracture resistance and failure mode of molars restored by occlusal veneers. Methods: Ninety occlusal veneers, fabricated from either lithium disilicate, zirconia, or polymer-infiltrated ceramic, were adhesively bonded to teeth prepared with either dentin, dentin with intra-coronal cavity, or dentin with composite filling. All specimens were thermally aged (5000 cycles), then load cycled (120,000 cycles). Each specimen was subjected to a compressive load through fracture, then was examined (×20) to identify the fracture type. Data were statistically analyzed. Results: Material type and dental substrate had no significant effect on the fracture resistance of adhesively retained occlusal veneer restorations. For each material, no significant differences were found between veneers bonded to dentin, dentin with intra-coronal cavity, and dentin with composite filling. Additionally, within each bonding substrate, there were no significant differences between lithium disilicate, zirconia, and polymer-infiltrated ceramic veneers. The adhesive failure was recorded mainly with zirconia occlusal veneer restorations. Conclusions: Considering the fracture results, lithium disilicate, zirconia, and polymer-infiltrated ceramic occlusal veneers perform well whatever the type of dental bonding surface. When the dental bonding surface varies, different occlusal veneer materials should be considered. Occlusal veneers bonded to dentin, dentin with composite filling, or dentin with an intra-coronal cavity exhibited a fracture resistance exceeding the average human masticatory forces in the molar area.
Utilization of Biomass to Ash: An Overview of the Potential Resources for Alternative Energy
Authors: Makul Natt , Fediuk Roman , Amran Mugahed , Al-Akwaa Mohammed , Pralat Karol , Nemova Darya , Petropavlovskii Kirill , Novichenkova Tatiana , Petropavlovskaya Victoria , Sulman Mikhail
Published: October 2021

Climate change and the potential depletion of fossil fuels have increased international demand for alternative and renewable energy sources. In terms of the energy sector, for example, most of the South-East Asian countries (SACs) have a large number of biomass sources due to their vast forest resources and agriculture-based economies. Thus, the critical review was aimed at highlighting the overview of biomass energy in South-East Asia as a dynamically developing region, in order to obtain economic and environmental benefits from the existing sources of biomass in the world. The current review analyzed the sources of biomass, as well as their energy potential, use, and management, based on reports from different countries, published studies, and scientific articles. In SAC, the main sources of biomass were found to be coconut residues, oil palm residues, sugar cane residues, rice straw, rice husks, wood waste, and firewood. The combined annual biomass potentials in the forestry and agricultural sectors in South-East Asia were approximately over 500 million tons per year and more than 8 gigajoule of total energy potentials. The study identified the challenges and barriers to using biomass in these countries to achieve sustainable use of biomass sources and recommended sustainable approaches to using biomass energy by comparing traditional uses of biomass. Smart grid technologies have ways for solutions for better electric power production and efficient ways for distribution and transmission of electricity. Smart grids require less space and can be more easily installed when compared to traditional grids because of their versatilities. Upcoming challenges include technology optimization for the following uses of biomass energy: direct combustion of woody biomass; pyrolysis and gasification of biomass; anaerobic digestion of organic waste to produce biogas; landfill gas production direct incineration of organic waste. The barriers in this technology are emissions of carbon and nitrogen oxides, unpleasant odors, as well as the uncontrolled harvesting of biomass, which can harm nature.
Cytotoxic Indole-Diterpenoids from the Marine-Derived Fungus Penicillium sp. KFD28
Authors: Dai Lu-Ting , Yang Li , Kong Fan-Dong , Ma Qing-Yun , Xie Qing-Yi , Dai Hao-Fu , Yu Zhi-Fang , Zhao You-Xing
Published: October 2021

Four new indole-diterpenoids, named penerpenes K-N (1–4), along with twelve known ones (5–16), were isolated from the fermentation broth produced by adding L-tryptophan to the culture medium of the marine-derived fungus Penicillium sp. KFD28. The structures of the new compounds were elucidated extensively by 1D and 2D NMR, HRESIMS data spectroscopic analyses and ECD calculations. Compound 4 represents the second example of paxilline-type indole diterpene bearing a 1,3-dioxepane ring. Three compounds (4, 9, and 15) were cytotoxic to cancer cell lines, of which compound 9 was the most active and showed cytotoxic activity against the human liver cancer cell line BeL-7402 with an IC50 value of 5.3 μM. Moreover, six compounds (5, 7, 10, 12, 14, and 15) showed antibacterial activities against Staphylococcus aureus ATCC 6538 and Bacillus subtilis ATCC 6633.
Genital Lymphedema and How to Deal with It: Pearls and Pitfalls from over 38 Years of Experience with Unusual Lymphatic System Impairment
Authors: Kaciulyte Juste , Garutti Leonardo , Spadoni Davide , Velazquez-Mujica Jonathan , Losco Luigi , Ciudad Pedro , Marcasciano Marco , Lo Torto Federico , Casella Donato , Ribuffo Diego , Chen Hung-Chi
Published: October 2021

Background and Objectives: Conservative treatment represents an essential pillar of lymphedema management, along with debulking and physiologic surgeries. Despite the consistent number of treatment options, there is currently no agreement on their indications and possible combinations. When dealing with unusual lymphedema presentation as in the genitalia (Genital Lymphedema—GL), treatment choice becomes even more difficult. The authors aimed to present their targeted algorithm of single and combined treatment modalities for rare GL in order to face this paucity of information. Materials and Methods: Data were collected from a prospectively maintained database since January 1983, and cases of GL that were managed in the authors’ department were selected. Only patients that were treated in the authors’ institution and presented a minimum follow-up of 3 months were admitted to the current study. Results: From January 1983 to July 2021, 19 patients with GL were recruited. All the patients were male, and their ages ranged from 21 to 73 years old (average: 52). Ten cases (52.6%) presented with ISL (International Society of Lymphology) stage I, five (26.3%) were stage II and four (21.1%) were stage III. GL was managed with conservative treatment (12 cases), LVA (LymphaticoVenous Anastomosis) (3) or surgical excision (4). In a mean follow-up of 7.5 years (range: 3 months—11 years), no major complications occurred, and all cases reached improvements in functional and quality of life terms. Conclusions: Contrary to the predominant thought of the necessity to avoid surgery in unusual lymphedema presentations such as GL, they can be managed using targeted multimodal approaches or by adapting well-known procedures in unusual ways to achieve control of disease progression and improve patients’ quality of life.
Research Progress and Application of Single-Atom Catalysts: A Review
Authors: He He , Wang Hudson Haocheng , Liu Junjian , Liu Xujun , Li Weizun , Wang Yannan
Published: October 2021

Due to excellent performance properties such as strong activity and high selectivity, single-atom catalysts have been widely used in various catalytic reactions. Exploring the application of single-atom catalysts and elucidating their reaction mechanism has become a hot area of research. This article first introduces the structure and characteristics of single-atom catalysts, and then reviews recent preparation methods, characterization techniques, and applications of single-atom catalysts, including their application potential in electrochemistry and photocatalytic reactions. Finally, application prospects and future development directions of single-atom catalysts are outlined.
Enhanced Electrocatalytic Detection of Choline Based on CNTs and Metal Oxide Nanomaterials
Authors: Uwaya Gloria E. , Fayemi Omolola E.
Published: October 2021

Choline is an officially established essential nutrient and precursor of the neurotransmitter acetylcholine. It is employed as a cholinergic activity marker in the early diagnosis of brain disorders such as Alzheimer’s and Parkinson’s disease. Low levels of choline in diets and biological fluids, such as blood plasma, urine, cerebrospinal and amniotic fluid, could be an indication of neurological disorder, fatty liver disease, neural tube defects and hemorrhagic kidney necrosis. Meanwhile, it is known that choline metabolism involves oxidation, which frees its methyl groups for entrance into single-C metabolism occurring in three phases: choline oxidase, betaine synthesis and transfer of methyl groups to homocysteine. Electrocatalytic detection of choline is of physiological and pathological significance because choline is involved in the physiological processes in the mammalian central and peripheral nervous systems and thus requires a more reliable assay for its determination in biological, food and pharmaceutical samples. Despite the use of several methods for choline determination, the superior sensitivity, high selectivity and fast analysis response time of bioanalytical-based sensors invariably have a comparative advantage over conventional analytical techniques. This review focuses on the electrocatalytic activity of nanomaterials, specifically carbon nanotubes (CNTs), CNT nanocomposites and metal/metal oxide-modified electrodes, towards choline detection using electrochemical sensors (enzyme and non-enzyme based), and various electrochemical techniques. From the survey, the electrochemical performance of the choline sensors investigated, in terms of sensitivity, selectivity and stability, is ascribed to the presence of these nanomaterials.
Toward Understanding the Molecular Recognition of Fungal Chitin and Activation of the Plant Defense Mechanism in Horticultural Crops
Authors: García Yaima Henry , Zamora Orlando Reyes , Troncoso-Rojas Rosalba , Tiznado-Hernández Martín Ernesto , Báez-Flores María Elena , Carvajal-Millan Elizabeth , Rascón-Chu Agustín
Published: October 2021

Large volumes of fruit and vegetable production are lost during postharvest handling due to attacks by necrotrophic fungi. One of the promising alternatives proposed for the control of postharvest diseases is the induction of natural defense responses, which can be activated by recognizing molecules present in pathogens, such as chitin. Chitin is one of the most important components of the fungal cell wall and is recognized through plant membrane receptors. These receptors belong to the receptor-like kinase (RLK) family, which possesses a transmembrane domain and/or receptor-like protein (RLP) that requires binding to another RLK receptor to recognize chitin. In addition, these receptors have extracellular LysM motifs that participate in the perception of chitin oligosaccharides. These receptors have been widely studied in Arabidopsis thaliana (A. thaliana) and Oryza sativa (O. sativa); however, it is not clear how the molecular recognition and plant defense mechanisms of chitin oligosaccharides occur in other plant species or fruits. This review includes recent findings on the molecular recognition of chitin oligosaccharides and how they activate defense mechanisms in plants. In addition, we highlight some of the current advances in chitin perception in horticultural crops.
Application of Molecularly Imprinted Polymers in the Analysis of Waters and Wastewaters
Authors: Metwally Mahmoud , Benhawy Abdelaziz , Khalifa Reda , El Nashar Rasha , Trojanowicz Marek
Published: October 2021

The increase of the global population and shortage of renewable water resources urges the development of possible remedies to improve the quality and reusability of waste and contaminated water supplies. Different water pollutants, such as heavy metals, dyes, pesticides, endocrine disrupting compounds (EDCs), and pharmaceuticals, are produced through continuous technical and industrial developments that are emerging with the increasing population. Molecularly imprinted polymers (MIPs) represent a class of synthetic receptors that can be produced from different types of polymerization reactions between a target template and functional monomer(s), having functional groups specifically interacting with the template; such interactions can be tailored according to the purpose of designing the polymer and based on the nature of the target compounds. The removal of the template using suitable knocking out agents renders a recognition cavity that can specifically rebind to the target template which is the main mechanism of the applicability of MIPs in electrochemical sensors and as solid phase extraction sorbents. MIPs have unique properties in terms of stability, selectivity, and resistance to acids and bases besides being of low cost and simple to prepare; thus, they are excellent materials to be used for water analysis. The current review represents the different applications of MIPs in the past five years for the detection of different classes of water and wastewater contaminants and possible approaches for future applications.
Identification of Potent Natural Resource Small Molecule Inhibitor to Control Vibrio cholera by Targeting Its Outer Membrane Protein U: An In Silico Approach
Authors: Rahaman Abdul , Almalki Abdulraheem Ali , Rafeeq Misbahuddin M. , Akhtar Omar , Anjum Farah , Mashraqi Mutaib M. , Sain Ziaullah M. , Alzamami Ahmad , Ahmad Varish , Zeng Xin-An , Jamal Qazi Mohammad Sajid
Published: October 2021

Vibrio cholerae causes the diarrheal disease cholera which affects millions of people globally. The outer membrane protein U (OmpU) is the outer membrane protein that is most prevalent in V. cholerae and has already been recognized as a critical component of pathogenicity involved in host cell contact and as being necessary for the survival of pathogenic V. cholerae in the host body. Computational approaches were used in this study to screen a total of 37,709 natural compounds from the traditional Chinese medicine (TCM) database against the active site of OmpU. Following a sequential screening of the TCM database, we report three lead compounds—ZINC06494587, ZINC85510056, and ZINC95910434—that bind strongly to OmpU, with binding affinity values of −8.92, −8.12, and −8.78 kcal/mol, which were higher than the control ligand (−7.0 kcal/mol). To optimize the interaction, several 100 ns molecular dynamics simulations were performed, and the resulting complexes were shown to be stable in their vicinity. Additionally, these compounds were predicted to have good drug-like properties based on physicochemical properties and ADMET assessments. This study suggests that further research be conducted on these compounds to determine their potential use as cholera disease treatment.
Benzothiazoles from Condensation of o-Aminothiophenoles with Carboxylic Acids and Their Derivatives: A Review
Authors: García-Báez Efrén V. , Padilla-Martínez Itzia I. , Tamay-Cach Feliciano , Cruz Alejandro
Published: October 2021

Nowadays, organic chemists are interested in the field of heterocyclic chemistry due to its use in the synthesis of a great variety of biologically active compounds. Heterocyclic compounds are widely found in nature and are essential for life. Among these, some natural nitrogen containing heterocyclic compounds have been used as chemotherapeutic agents. Their attachment to sugar molecules either as thioglycosides or as nucleosides analogues plays an important role in vital biological processes as well as in synthetic organic chemistry. Molecules containing benzothiazole (BT) nuclei are of this interesting class of compounds because some of them have been found to have a wide variety of biological activities. In this sense, we selected this topic to review and to then summarize the procedures related to the condensation reactions of o-aminothiophenoles (ATPs) as well as their disulfides with carboxylic acids, esters, orthoesters, acyl chlorides, amides, and nitriles. The condensation reactions with carbon dioxide (CO2) are included. Conventional methods with the use of acid and metal catalysts as well as recent green techniques, such as microwave irradiation, the use of ionic liquids, and ultrasound (US) chemistry, which have proven to have many advantages, were found in the review.
The Use of High Surface Area Mesoporous-Activated Carbon from Longan Seed Biomass for Increasing Capacity and Kinetics of Methylene Blue Adsorption from Aqueous Solution
Authors: Lawtae Panuwat , Tangsathitkulchai Chaiyot
Published: October 2021

Microporous- and mesoporous-activated carbons were produced from longan seed biomass through physical activation with CO2 under the same activation conditions of time and temperature. The specially prepared mesoporous carbon showed the maximum porous properties with the specific surface area of 1773 m2/g and mesopore volume of 0.474 cm3/g which accounts for 44.1% of the total pore volume. These activated carbons were utilized as porous adsorbents for the removal of methylene blue (MB) from an aqueous solution and their effectiveness was evaluated for both the adsorption kinetics and capacity. The adsorption kinetic data of MB were analyzed by the pseudo-first-order model, the pseudo-second-order model, and the pore-diffusion model equations. It was found that the adsorption kinetic behavior for all carbons tested was best described by the pseudo-second-order model. The effective pore diffusivity (De) derived from the pore-diffusion model had the values of 4.657 × 10−7–6.014 × 10−7 cm2/s and 4.668 × 10−7–19.920 × 10−7 cm2/s for the microporous- and mesoporous-activated carbons, respectively. Three well-known adsorption models, namely the Langmuir, Freundlich and Redlich–Peterson equations were tested with the experimental MB adsorption isotherms, and the results showed that the Redlich–Peterson model provided the overall best fitting of the isotherm data. In addition, the maximum capacity for MB adsorption of 1000 mg/g was achieved with the mesoporous carbon having the largest surface area and pore volume. The initial pH of MB solution had virtually no effect on the adsorption capacity and removal efficiency of the methylene blue dye. Increasing temperature over the range from 35 to 55 °C increased the adsorption of methylene blue, presumably caused by the increase in the diffusion rate of methylene blue to the adsorption sites that could promote the interaction frequency between the adsorbent surface and the adsorbate molecules. Overall, the high surface area mesoporous carbon was superior to the microporous carbon in view of the adsorption kinetics and capacity, when both carbons were used for the removal of MB from an aqueous solution.
Death for a Buddhist Dreamer: Identity and Mortality in Jetsun Drakpa Gyaltsen’s Autobiographical Dream Narrative
Authors: Lindsay Rory
Published: October 2021

This article examines the role of dreams in the life of the Tibetan Buddhist master Jetsun Drakpa Gyaltsen (1147–1216). Focusing on The Lord’s Dreams (Rje btsun pa’i mnal lam), Drakpa Gyaltsen’s only autobiographical text, along with the first biography of him written by his influential nephew Sakya Paṇḍita Kunga Gyaltsen (1182–1251), this paper explores the work of dreams in negotiating issues of identity and mortality. It argues that dreams were important sources of knowledge about the past, the future, and the dead in this context, creating intermediate spaces in which access to these times and individuals became possible.
Human–Machine Differentiation in Speed and Separation Monitoring for Improved Efficiency in Human–Robot Collaboration
Authors: Himmelsbach Urban B. , Wendt Thomas M. , Hangst Nikolai , Gawron Philipp , Stiglmeier Lukas
Published: October 2021

Human–robot collaborative applications have been receiving increasing attention in industrial applications. The efficiency of the applications is often quite low compared to traditional robotic applications without human interaction. Especially for applications that use speed and separation monitoring, there is potential to increase the efficiency with a cost-effective and easy to implement method. In this paper, we proposed to add human–machine differentiation to the speed and separation monitoring in human–robot collaborative applications. The formula for the protective separation distance was extended with a variable for the kind of object that approaches the robot. Different sensors for differentiation of human and non-human objects are presented. Thermal cameras are used to take measurements in a proof of concept. Through differentiation of human and non-human objects, it is possible to decrease the protective separation distance between the robot and the object and therefore increase the overall efficiency of the collaborative application.
Isolating the Unique and Generic Movement Characteristics of Highly Trained Runners
Authors: Hoitz Fabian , Fraeulin Laura , von Tscharner Vinzenz , Ohlendorf Daniela , Nigg Benno M. , Maurer-Grubinger Christian
Published: October 2021

Human movement patterns were shown to be as unique to individuals as their fingerprints. However, some movement characteristics are more important than other characteristics for machine learning algorithms to distinguish between individuals. Here, we explored the idea that movement patterns contain unique characteristics that differentiate between individuals and generic characteristics that do not differentiate between individuals. Layer-wise relevance propagation was applied to an artificial neural network that was trained to recognize 20 male triathletes based on their respective movement patterns to derive characteristics of high/low importance for human recognition. The similarity between movement patterns that were defined exclusively through characteristics of high/low importance was then evaluated for all participants in a pairwise fashion. We found that movement patterns of triathletes overlapped minimally when they were defined by variables that were very important for a neural network to distinguish between individuals. The movement patterns overlapped substantially when defined through less important characteristics. We concluded that the unique movement characteristics of elite runners were predominantly sagittal plane movements of the spine and lower extremities during mid-stance and mid-swing, while the generic movement characteristics were sagittal plane movements of the spine during early and late stance.
On–Off Scheduling for Electric Vehicle Charging in Two-Links Charging Stations Using Binary Optimization Approaches
Authors: Zdunek Rafał , Grobelny Andrzej , Witkowski Jerzy , Gnot Radosław Igor
Published: October 2021

In this study, we deal with the problem of scheduling charging periods of electrical vehicles (EVs) to satisfy the users’ demands for energy consumption as well as to optimally utilize the available power. We assume three-phase EV charging stations, each equipped with two charging ports (links) that can serve up to two EVs in the scheduling period but not simultaneously. Considering such a specification, we propose an on–off scheduling scheme wherein control over an energy flow is achieved by flexibly switching the ports in each station on and off in a manner such as to satisfy the energy demand of each EV, flatten the high energy-consuming load on the whole farm, and to minimize the number of switching operations. To satisfy these needs, the on–off scheduling scheme is formulated in terms of a binary linear programming problem, which is then extended to a quadratic version to incorporate the smoothness constraints. Various algorithmic approaches are used for solving a binary quadratic programming problem, including the Frank–Wolfe algorithm and successive linear approximations. The numerical simulations demonstrate that the latter is scalable, efficient, and flexible in a charging procedure, and it shaves the load peak while maintaining smooth charging profiles.
Conical Statistical Optimal Near-Field Acoustic Holography with Combined Regularization
Authors: Cheng Wei , Ni Jinglei , Song Chao , Ahsan Muhammad Mubashir , Chen Xuefeng , Nie Zelin , Liu Yilong
Published: October 2021

For the sound field reconstruction of large conical surfaces, current statistical optimal near-field acoustic holography (SONAH) methods have relatively poor applicability and low accuracy. To overcome this problem, conical SONAH based on cylindrical SONAH is proposed in this paper. Firstly, elementary cylindrical waves are transformed into those suitable for the radiated sound field of the conical surface through cylinder-cone coordinates transformation, which forms the matrix of characteristic elementary waves in the conical spatial domain. Secondly, the sound pressure is expressed as the superposition of those characteristic elementary waves, and the superposition coefficients are solved according to the principle of superposition of wave field. Finally, the reconstructed conical pressure is expressed as a linear superposition of the holographic conical pressure. Furthermore, to overcome ill-posed problems, a regularization method combining truncated singular value decomposition (TSVD) and Tikhonov regularization is proposed. Large singular values before the truncation point of TSVD are not processed and remaining small singular values representing high-frequency noise are modified by Tikhonov regularization. Numerical and experimental case studies are carried out to validate the effectiveness of the proposed conical SONAH and the combined regularization method, which can provide reliable evidence for noise monitoring and control of mechanical systems.
Electrochemical Determination of Kynurenine Pathway Metabolites—Challenges and Perspectives
Authors: Sadok Ilona , Staniszewska Magdalena
Published: October 2021

In recent years, tryptophan metabolism via the kynurenine pathway has become one of the most active research areas thanks to its involvement in a variety of physiological processes, especially in conditions associated with immune dysfunction, central nervous system disorders, autoimmunity, infection, diabetes, and cancer. The kynurenine pathway generates several metabolites with immunosuppressive functions or neuroprotective, antioxidant, or toxic properties. An increasing body of work on this topic uncovers a need for reliable analytical methods to help identify and quantify tryptophan metabolites at physiological concentrations in biological samples of different origins. Recent methodological advances in the fabrication and application of electrochemical sensors promise a rise in the future generation of novel analytical systems. This work summarizes current knowledge and provides important suggestions with respect to direct electrochemical determinations of kynurenine pathway metabolites (kynurenines) in complex biological matrices. Measurement challenges, limitations, and future opportunities of electroanalytical methods to advance study of the implementation of kynurenines in disease conditions are discussed.
Suppression of Continuous Wave Interference in Loran-C Signal Based on Sparse Optimization Using Tunable Q-Factor Wavelet Transform and Discrete Cosine Transform
Authors: Ma Wenwen , Gao Jiuxiang , Yuan Yanning , Shi Zhensheng , Xi Xiaoli
Published: October 2021

Loran-C is the most essential backup and supplementary system for the global navigation satellite system (GNSS). Continuous wave interference (CWI) is one of the main interferences in the Loran-C system, which will cause errors in the measurement of the time of arrival, thereby affecting positioning performance. The traditional adaptive notch filter method needs to know the frequency of CWI when removing it, and the number is limited. This paper presents a method based on sparseness to suppress the CWI in the Loran-C signal. According to the different morphological characteristics of the Loran-C signal and the CWI, we construct dictionaries suitable for the two components, respectively. We use the tunable Q-factor wavelet transform and the discrete cosine transform to make the two components obtain a good sparse representation in their respective dictionaries. Then, the two components are separated using the morphological component analysis theory. We illustrate this method using both synthetic data and actual data. A huge advantage of the proposed method is that there is no need to know the frequencies of the CWI for it can better cope with frequency changes of the CWI in the actual environments. Compared with the adaptive notch filter method, the results of the proposed method show that our approach is more effective and convenient.
Data Protection by Design in the Context of Smart Cities: A Consent and Access Control Proposal
Authors: Daoudagh Said , Marchetti Eda , Savarino Vincenzo , Bernabe Jorge Bernal , García-Rodríguez Jesús , Moreno Rafael Torres , Martinez Juan Antonio , Skarmeta Antonio F.
Published: October 2021

The growing availability of mobile devices has lead to an arising development of smart cities services that share a huge amount of (personal) information and data. Without accurate and verified management, they could become severe back-doors for security and privacy. In this paper, we propose a smart city infrastructure able to integrate a distributed privacy-preserving identity management solution based on attribute-based credentials (p-ABC), a user-centric Consent Manager, and a GDPR-based Access Control mechanism so as to guarantee the enforcement of the GDPR’s provisions. Thus, the infrastructure supports the definition of specific purpose, collection of data, regulation of access to personal data, and users’ consents, while ensuring selective and minimal disclosure of personal information as well as user’s unlinkability across service and identity providers. The proposal has been implemented, integrated, and evaluated in a fully-fledged environment consisting of MiMurcia, the Smart City project for the city of Murcia, CaPe, an industrial consent management system, and GENERAL_D, an academic GDPR-based access control system, showing the feasibility.
Closed-Form Pseudolinear Estimators for DRSS-AOA Localization
Authors: Li Jun , Dogancay Kutluyil , Hmam Hatem
Published: October 2021

This paper investigates the hybrid source localization problem using differential received signal strength (DRSS) and angle of arrival (AOA) measurements. The main advantage of hybrid measurements is to improve the localization accuracy with respect to a single sensor modality. For sufficiently short wavelengths, AOA sensors can be constructed with size, weight, power and cost (SWAP-C) requirements in mind, making the proposed hybrid DRSS-AOA sensing feasible at a low cost. Firstly the maximum likelihood estimation solution is derived, which is computationally expensive and likely to become unstable for large noise levels. Then a novel closed-form pseudolinear estimation method is developed by incorporating the AOA measurements into a linearized form of DRSS equations. This method eliminates the nuisance parameter associated with linearized DRSS equations, hence improving the estimation performance. The estimation bias arising from the injection of measurement noise into the pseudolinear data matrix is examined. The method of instrumental variables is employed to reduce this bias. As the performance of the resulting weighted instrumental variable (WIV) estimator depends on the correlation between the IV matrix and data matrix, a selected-hybrid-measurement WIV (SHM-WIV) estimator is proposed to maintain a strong correlation. The superior bias and mean-squared error performance of the new SHM-WIV estimator is illustrated with simulation examples.
Secure Cognitive Radio-Enabled Vehicular Communications under Spectrum-Sharing Constraints
Authors: Yadav Suneel , Pandey Anshul , Do Dinh-Thuan , Lee Byung Moo , Silva Adão
Published: October 2021

Vehicular communication has been envisioned to support a myriad of essential fifth-generation and beyond use-cases. However, the increasing proliferation of smart and intelligent vehicles has generated a lot of design and infrastructure challenges. Of particular interest are the problems of spectrum scarcity and communication security. Consequently, we considered a cognitive radio-enabled vehicular network framework for accessing additional radio spectrum and exploit physical layer security for secure communications. In particular, we investigated the secrecy performance of a cognitive radio vehicular network, where all the nodes in the network are moving vehicles and the channels between them are modeled as double-Rayleigh fading. Furthermore, adopting an underlay approach, the communication between secondary nodes can be performed by employing two interference constraint strategies at the primary receiver; (1) Strategy I: the secondary transmitter power is constrained by the interference threshold of the primary receiver, and (2) Strategy II: the secondary transmitter power is constrained by both the interference threshold of the primary receiver and the maximum transmit power of the secondary network. Under the considered strategies, we derive the exact secrecy outage probability (SOP) and ergodic secrecy capacity (ESC) expressions over double-Rayleigh fading. Moreover, by analyzing the asymptotic SOP behavior, we show that a full secrecy diversity of 1 can be achieved, when the average channel gain of the main link goes to infinity with a fixed average wiretap channel gain. From the ESC analysis, it is revealed that the ESC follows a scaling law of ΘlnΩm2Ωe2 for large Ωm and Ωe, where Ωm and Ωe are the average channel gains of the main link and wiretap link. The numerical and simulation results verify our analytical findings.
Adversarial Learning with Bidirectional Attention for Visual Question Answering
Authors: Li Qifeng , Tang Xinyi , Jian Yi
Published: October 2021

In this paper, we provide external image features and use the internal attention mechanism to solve the VQA problem given a dataset of textual questions and related images. Most previous models for VQA use a pair of images and questions as input. In addition, the model adopts a question-oriented attention mechanism to extract the features of the entire image and then perform feature fusion. However, the shortcoming of these models is that they cannot effectively eliminate the irrelevant features of the image. In addition, the problem-oriented attention mechanism lacks in the mining of image features, which will bring in redundant image features. In this paper, we propose a VQA model based on adversarial learning and bidirectional attention. We exploit external image features that are not related to the question to form an adversarial mechanism to boost the accuracy of the model. Target detection is performed on the image—that is, the image-oriented attention mechanism. The bidirectional attention mechanism is conducive to promoting model attention and eliminating interference. Experimental results are evaluated on benchmark datasets, and our model performs better than other models based on attention methods. In addition, the qualitative results show the attention maps on the images and leads to predicting correct answers.
Projections of IoT Applications in Colombia Using 5G Wireless Networks
Authors: Barrios-Ulloa Alexis , Cama-Pinto Dora , Mardini-Bovea Johan , Díaz-Martínez Jorge , Cama-Pinto Alejandro
Published: October 2021

Wireless technologies are increasingly relevant in different activities and lines of the economy, as well as in the daily life of people and companies. The advent of fifth generation networks (5G) implies a promising synergy with the Internet of Things (IoT), allowing for more automations in production processes and an increase in the efficiency of information transmission, managing to improve the efficiency in decision-making through tools such as big data and artificial intelligence. This article presents a description of the 5G implementation process in Colombia, as well as a revision of opportunities when combining with IoT in featured sectors of the departmental development plans, such as agriculture, tourism, health, the environment, and industry. Results shows that the startup of 5G in Colombia has been a slow process, but there are comparisons with similar procedures in other developed countries. Additionally, we present examples of 5G and IoT applications which can be promoted in Colombia, aimed at improving the quality of life of their habitants and promoting economic development.
Pressure-Sensitive Nano-Sheet for Optical Pressure Measurement
Authors: Matsuda Yu , Orimo Riki , Abe Yusaku , Hiraiwa Yuri , Okamura Yosuke , Sunami Yuta
Published: October 2021

Pressure-Sensitive Paint (PSP) is a powerful measurement technique to obtain pressure distribution on a model of interest by measuring the emission intensity of the PSP coating with a camera. Since a PSP coating is prepared by applying a solution containing an organic solvent, generally, by sprayer, the properties such as the pressure- and the temperature-sensitivity depends on the skill of the person applying it. This fabrication process is one of the barriers to use of the PSP technique because of the legal restrictions on the use of organic solvents. Thus, a sticker-like PSP coating is useful because it does not require the use of organic solvent and the applying skill. In this study, we have fabricated freestanding Pressure-Sensitive Nano-Sheet (PSNS) by a sacrificial layer process using a spin-coating method. We employed Pt(II) meso-tetra(pentafluorophenyl)porphine (PtTFPP) as a pressure-sensitive dye and poly(1-trimethylsilyl-propyne) (PTMSP) and poly(L-lactic acid) (PLLA) as a polymer binder; thus, the PSNS samples based on PTMSP and PLLA were prepared. The pressure- and the temperature-sensitivity, the lifetime of the luminescence, and the quantum yield of the fabricated PSNS have been investigated. The pressure-sensitivity of PTMSP-based PSNS is higher than that of PLLA-based PSNS. Conversely, the quantum yield of PLLA-based PSNS is higher than that of PTMSP-based PSNS.
Long-Term Ship Position Prediction Using Automatic Identification System (AIS) Data and End-to-End Deep Learning
Authors: Ibadurrahman  , Hamada Kunihiro , Wada Yujiro , Nanao Jota , Watanabe Daisuke , Majima Takahiro
Published: October 2021

The establishment of maritime safety and security is an important concern. Ship position prediction for maritime situational awareness (MSA), as a critical aspect of maritime safety and security, requires a longer time interval than collision avoidance and maritime traffic monitoring. However, previous studies focused mainly on shorter time-interval predictions ranging from 30 min to 10 h. A longer time-interval ship position prediction is required not only for MSA, but also for efficient allocation of ships by shipping companies in accordance with global freight demand. This study used an end-to-end tracking method that inputs the previous position of a vessel to a trained deep learning model to predict its next position with an average 24-h interval. An AIS dataset with a long-time-interval distribution in a nine-year timespan for capesize bulk carriers worldwide was used. In the first experiment, a deep learning model of the Indian Ocean was examined. Subsequently, the model performance was compared for six different oceans and six primary maritime chokepoints to investigate the influence of each area. In the third experiment, a sample location within the Malacca Strait area was selected, and the number of ships was counted daily. The results indicate that the ship position can be predicted accurately with an average time interval of 24 h using deep learning systems with AIS data.
System Identification of Conveyor Belt Microwave Drying Process of Polymer Foams Using Electrical Capacitance Tomography
Authors: Hosseini Marzieh , Kaasinen Anna , Aliyari Shoorehdeli Mahdi , Link Guido , Lähivaara Timo , Vauhkonen Marko
Published: October 2021

The microwave drying process has a wide application in industry, including drying polymer foams after the impregnation process for sealings in the construction industry. The objective of the drying process is to reach a certain moisture in the foam by adjusting the power levels of the microwave sources. A moisture controller can be designed to achieve this goal; however, a process model is required to design model-based controllers. Since complex physics governs the microwave drying process, system identification tools are employed in this paper to exploit the process input and output information and find a simplified yet accurate model of the process. The moisture content of the foam that is the process output is measured using a designed electrical capacitance tomography (ECT) sensor. The ECT sensor estimates the 2D permittivity distribution of moving foams, which correlates with the foam moisture. Experiments are conducted to collect the ECT measurements while giving different inputs to the microwave sources. A state-space model is estimated using one of the collected datasets and is validated using the other datasets. The comparison between the model response and the actual measurements shows that the model is accurate enough to design a controller for the microwave drying process.
Segmentation of Rat Brains and Cerebral Hemispheres in Triphenyltetrazolium Chloride-Stained Images after Stroke
Authors: Chang Herng-Hua , Yeh Shin-Joe , Chiang Ming-Chang , Hsieh Sung-Tsang
Published: October 2021

Ischemic stroke is one of the leading causes of death among the aged population in the world. Experimental stroke models with rodents play a fundamental role in the investigation of the mechanism and impairment of cerebral ischemia. For its celerity and veracity, the 2,3,5-triphenyltetrazolium chloride (TTC) staining of rat brains has been extensively adopted to visualize the infarction, which is subsequently photographed for further processing. Two important tasks are to segment the brain regions and to compute the midline that separates the brain. This paper investigates automatic brain extraction and hemisphere segmentation algorithms in camera-based TTC-stained rat images. For rat brain extraction, a saliency region detection scheme on a superpixel image is exploited to extract the brain regions from the raw complicated image. Subsequently, the initial brain slices are refined using a parametric deformable model associated with color image transformation. For rat hemisphere segmentation, open curve evolution guided by the gradient vector flow in a medial subimage is developed to compute the midline. A wide variety of TTC-stained rat brain images captured by a smartphone were produced and utilized to evaluate the proposed segmentation frameworks. Experimental results on the segmentation of rat brains and cerebral hemispheres indicated that the developed schemes achieved high accuracy with average Dice scores of 92.33% and 97.15%, respectively. The established segmentation algorithms are believed to be potential and beneficial to facilitate experimental stroke study with TTC-stained rat brain images.