bluuebunny/crossref_metadata_2025 huggingface dataset:
Functionalized Nanoparticles Activated by Photodynamic Therapy as an Antimicrobial Strategy in Endodontics: A Scoping Review
Authors: Betancourt Pablo , Brocal Nadia , Sans-Serramitjana Eulàlia , Zaror Carlos
Published: September 2021

The eradication of endodontic pathogens continues to be the focus of the search for new root canal system (RCS) disinfection strategies. This scoping review provides a comprehensive synthesis of antimicrobial photodynamic therapy (aPDT) using nanoparticles (NPs) as an alternative to optimize RCS disinfection. A systematic search up to March 2021 was carried out using the MEDLINE, EMBASE, Scopus, Lilacs, Central Cochrane Library, and BBO databases. We included studies focused on evaluating the activation of NPs by aPDT in inoculated root canals of human or animal teeth or bacterial cultures in the laboratory. The selection process and data extraction were carried out by two researchers independently. A qualitative synthesis of the results was performed. A total of seventeen studies were included, of which twelve showed a substantial antibacterial efficacy, two assessed the substantivity of the disinfection effect, and three showed low cytotoxicity. No adverse effects were reported. The use of functionalized NPs with photosensitizer molecules in aPDT has been shown to be effective in reducing the bacteria count, making it a promising alternative in endodontic disinfection. Further studies are needed to assess the development of this therapy in in vivo conditions, with detailed information about the laser parameters used to allow the development of safe and standardized protocols.
Antibiotic-Resistant Genes and Bacteria as Evolving Contaminants of Emerging Concerns (e-CEC): Is It Time to Include Evolution in Risk Assessment?
Authors: Vassallo Alberto , Kett Steve , Purchase Diane , Marvasi Massimiliano
Published: September 2021

The pressing issue of the abundance of antibiotic resistance genes and resistant bacteria in the environment (ARGs and ARB, respectively) requires procedures for assessing the risk to health. The chemo-centric environmental risk assessment models identify hazard(s) in a dose–response manner, obtaining exposure, toxicity, risk, impact and policy. However, this risk assessment approach based on ARGs/ARB evaluation from a quantitative viewpoint shows high unpredictability because ARGs/ARB cannot be considered as standard hazardous molecules: ARB duplicate and ARGs evolve within a biological host. ARGs/ARB are currently listed as Contaminants of Emerging Concern (CEC). In light of such characteristics, we propose to define ARGs/ARB within a new category of evolving CEC (or e-CEC). ARGs/ARB, like any other evolving determinants (e.g., viruses, bacteria, genes), escape environmental controls. When they do so, just one molecule left remaining at a control point can form the origin of a new dangerous and selection-responsive population. As a consequence, perhaps it is time to acknowledge this trait and to include evolutionary concepts within modern risk assessment of e-CEC. In this perspective we analyze the evolutionary responses most likely to influence risk assessment, and we speculate on the means by which current methods could measure evolution. Further work is required to implement and exploit such experimental procedures in future risk assessment protocols.
New Technique for Custom-Made Spacers in Septic Two-Stage Revision of Total Hip Arthroplasties
Authors: Mederake Moritz , Hofmann Ulf Krister , Fink Bernd
Published: September 2021

The choice of spacer in the interim phase of two-stage revision hip arthroplasty is crucial. Conventional concepts like a Girdlestone situation, handformed or preformed bone cement spacers show complications like soft-tissue contractions, abrasion of bone cement particles, dislocation, breakage and a low level of mobility in the interim phase. To address these disadvantages, the senior author developed a new technique for custom-made spacers in septic two-stage revision of total hip arthroplasties using prosthetic implants with individualized antibiotic mixture in the cement applying a mechanical inferior cementation method. The aim of this study was to evaluate the results of these spacers with respect to their non-inferiority in terms of reinfection and survival-rate of the new implant and to describe the complications associated with this procedure. Our collective consisted of 130 patients with a median follow-up of nearly five years. With a reinfect-free rate of 92% and a spacer-related complication rate of 10% (8% articular dislocation, 1% periprosthetic joint fracture, 1% breakage), this procedure seems to be safe and superior regarding complications compared to conventional concepts. Further studies are necessary to show the clinical benefit of this procedure.
Mucormycosis in Indian COVID-19 Patients: Insight into Its Patho-Genesis, Clinical Manifestation, and Management Strategies
Authors: Sahu Ram Kumar , Salem-Bekhit Mounir M. , Bhattacharjee Bedanta , Almoshari Yosif , Ikbal Abu Md Ashif , Alshamrani Meshal , Bharali Alakesh , Salawi Ahmad , Widyowati Retno , Alshammari Abdulrahman , Elbagory Ibrahim
Published: September 2021

Mucormycosis in patients who have COVID-19 or who are otherwise immunocompromised has become a global problem, causing significant morbidity and mortality. Infection is debilitating and fatal, leading to loss of organs and emotional trauma. Radiographic manifestations are not specific, but diagnosis can be made through microscopic examination of materials collected from necrotic lesions. Treatment requires multidisciplinary expertise, as the fungus enters through the eyes and nose and may even reach the brain. Use of the many antifungal drugs available is limited by considerations of resistance and toxicity, but nanoparticles can overcome such limitations by reducing toxicity and increasing bioavailability. The lipid formulation of amphotericin-B (liposomal Am-B) is the first-line treatment for mucormycosis in COVID-19 patients, but its high cost and low availability have prompted a shift toward surgery, so that surgical debridement to remove all necrotic lesions remains the hallmark of effective treatment of mucormycosis in COVID-19. This review highlights the pathogenesis, clinical manifestation, and management of mucormycosis in patients who have COVID-19.
Formation Mechanism of Metro Rail Corrugation Based on Wheel–Rail Stick–Slip Behaviors
Authors: Wang Zhiqiang , Lei Zhenyu
Published: September 2021

Field investigation shows that most corrugations occur on the inner rail surface of curved tracks with a radius of less than 700 m. In order to explore the formation mechanism of metro corrugation, the relationship between wheel–rail stick–slip characteristics and rail corrugation is studied by combining single wheelset curving and a rigid–flexible coupling model. The numerical results illustrate that the lateral torsional stick–slip vibration of inner rail–inner wheel of the guiding wheelset on the small radius curve eventually leads to the generation of inner rail corrugation, and the lateral torsional stick–slip vibration of outer rail–outer wheel of the driven wheelset may also occur, but the intensity is weak and the probability is low. The lateral torsional stick–slip vibration of inner rail–inner wheel of the guiding wheelset on the large radius curve is also easy to cause inner rail corrugation, but the degree of inner rail corrugation is lower than that on the small radius curve; the outer rail on the large radius curve is still not easy to produce corrugation. The formation mechanism of rail corrugation on the straight track is different from that on the curve track, which is mainly related to the wheel–rail longitudinal torsional stick–slip vibration.
Analysis of the Current State of Automation of Hazard Detection Processes in BIM in Slovakia
Authors: Mayer Pavol , Funtík Tomáš , Gašparík Jozef , Makýš Peter
Published: September 2021

Building information modeling (BIM) brings several benefits to design and construction companies, especially in higher efficiency and quality of work. Several companies also use common data environment (CDE) systems, which speed up communication and collaboration between project participants. These can be used for occupational health and safety (HS) purposes and to increase the level of HS on construction sites. The first part of the article presents the state-of-the-art possibilities and approaches to implementing BIM in automatic or semi-automatic health and safety hazard detection. The following parts analyze the interviews with experts in BIM coordination, project management and health and safety in Slovakia and their answers to a survey, that covers the topic of safety hazard detection in BIM. The analysis shows that BIM is a suitable tool for increasing safety on construction sites, but there are several obstacles to achieving its full potential. The survey brings readers closer to the current state of the topic and the possibilities offered by BIM and CDE software in Slovakia. This paper, through the requirements and opinions of experts in BIM, project management and HS management, points out areas for further research and development of BIM software.
Spin Transport in a Quantum Hall Insulator
Authors: Zagitova Azaliya Azatovna , Zhuravlev Andrey Sergeevich , Kulik Leonid Viktorovich , Umansky Vladimir
Published: September 2021

A novel experimental optical method, based on photoluminescence and photo-induced resonant reflection techniques, is used to investigate the spin transport over long distances in a new, recently discovered collective state—magnetofermionic condensate. The given Bose–Einstein condensate exists in a purely fermionic system (ν = 2 quantum Hall insulator) due to the presence of a non-equilibrium ensemble of spin-triplet magnetoexcitons—composite bosons. It is found that the condensate can spread over macroscopically long distances of approximately 200 μm. The propagation velocity of long-lived spin excitations is measured to be 25 m/s.
Efficiency of Bromelain-Enriched Enzyme Mixture (NexoBrid™) in the Treatment of Burn Wounds
Authors: Pertea Mihaela , Poroch Vladimir , Ciobanu Petru , Filip Alexandru , Velenciuc Natalia , Lunca Sorinel , Panuta Andrian , Buna-Arvinte Mihaela , Luca Stefana , Veliceasa Bogdan
Published: September 2021

Background: The use of bromelain for the removal of eschar in deep burns is considered to be effective because it does not affect the unaffected skin and leaves a clean dermis after use. The main objective of this study is to find out whether bromelain is a good alternative to surgical debridement. In order to achieve that, we aim to evaluate its indications, limitations, and safety measures. Methods: The current study was conducted on a group of 30 patients with deep burn lesions, aged 20 to 56 years, from which 15 underwent enzymatic debridement and 15 patients acted as a control group in which primary surgical debridement was used. The mixture of enzymes enriched in bromelain, meant to dissolve burn eschar, was provided by NexoBrid™. The inclusion criteria were in agreement with the manufacturer’s protocols, but the application protocol was slightly modified in order to implement a better intern protocol and to assess its efficiency. Results: Complete eschar debridement was obtained in 13 of the 15 cases, from which 10 patients went through spontaneous healing and 3 needed to be covered with a skin graft. In the other 2 cases, partial eschar debridement was associated with surgical debridement and coverage with split-thickness skin graft in the same operation. The results obtained in the two groups were assessed with the Vancouver Scar Scale. Conclusions: Even though early excision followed by coverage with split-thickness skin graft remains the gold standard for the treatment of deep burns, enzymatic debridement can provide a series of advantages when the inclusion and exclusion criteria are respected. Bromelain is an alternative to surgical debridement that provides speed, tissue selectivity, safety, and less blood loss.
Enhanced Heat Transfer Performance of the Tube Heat Exchangers Using Carbon-Based Nanofluids
Authors: Yu Shang-Pang , Lue Yeou-Feng , Teng Tun-Ping , Hsieh Hsiang-Kai , Huang Chia-Cing
Published: September 2021

The wet ball milling method was used and a dispersant (gum Arabic) was added to prepare various concentrations (0.05 and 0.2 wt%) of carbon-based nanofluids (CBNFs) by a two-step synthesis method as working fluids for heat exchange. CBNFs were actually used in a tube heat exchanger (THE) for heat transfer performance experiments. The heat transfer performance of water and CBNFs was estimated under different heating powers and flow rates of working fluid. The pump power consumption (Ppe) of 0.05 wt% CBNF was found to be similar to that of water, but the Ppe of 0.2 wt% CBNF was higher than that of water. The convective heat transfer coefficient (HTC) of CBNF in the was higher than that of water, and the HTC of 0.05 wt% and 0.2 wt% CBNF was optimal at the heating power of 120 W and 80 W, respectively. The average HTC of 0.05 wt% CBNFs at 120 W heating power was about 3.33% higher than that of water, while that of 0.2 wt% CBNFs at 80 W heating power was about 4.52% higher than that of water. Considering the Ppe and HTC concomitantly, the best overall system performance was exhibited by 0.05 wt% CBNFs.
Anti-Genotoxicity Evaluation of Ellagic Acid and Curcumin—An In Vitro Study on Zebrafish Blood Cells
Authors: Mottola Filomena , Finelli Renata , Iovine Concetta , Carannante Maria , Santonastaso Marianna , Rocco Lucia
Published: September 2021

Genotoxicity is the ability of specific substances to cause DNA damage, affecting development, physiology, and reproduction. This is often mediated by induction of oxidative stress. This in vitro study aims to test the ability of two antioxidants, ellagic acid (EA, 100 µM) and curcumin (Cur, 40 µM) to protect zebrafish blood cells from the genotoxic action of benzene (10 µL/mL). Cells were treated for 30, 60, and 90 min with EA or Cur alone and in combination with benzene. The antigenotoxic role of antioxidants was evaluated in terms of cytotoxicity by trypan blue dye, genome stability by RAPD-PCR technique, DNA fragmentation and percentage of apoptotic cells using Comet and Diffusion assay, respectively. The results did not show statistical differences in terms of cell viability, genome stability, DNA damage and apoptosis between cells treated with antioxidants. When zebrafish blood cells were co-incubated with individual antioxidants and benzene, a significant improvement of these parameters was observed in comparison with cells incubated in benzene. Our results suggested that EA and Cur are able to protect zebrafish blood cells against DNA damage and apoptosis caused by mutagenic substance, and laid the foundation for future studies investigating their antigenotoxic potential in DNA oxidative damage therapy.
Disentangling Human–Plant–Animal Dynamics at the Microscale: Geo-Ethnoarchaeological Case Studies from North Africa and the Near East
Authors: Portillo Marta , García-Suárez Aroa
Published: September 2021

Livestock dung is a suitable material for delineating the complexity of interactions between people, plants and animals as it contains critical information on environmental and ecological issues as well as socio-economic dynamics and cultural lifeways. However, animal faecal remains and other coprogenic materials are commonly overlooked in most archaeological research programs due, in part, to methodological challenges in its recovery and identification. This paper evaluates the contribution of integrated geoarchaeological approaches, together with comparative reference ethnoarchaeological records, to interdisciplinary microscopic analyses on the identification of animal dung and its archaeological significance within farming built environments. It brings together records from a selection of recent geo-ethnoarchaeological case studies across the Near East, one of the heartlands of plant and animal domestication, and from northern Africa, an understudied key area with critical implications for neighbouring regions such as the Sahara. This article examines the state-of-the-art of dung material identifications within agricultural and pastoral settlements and their potential for tracing ecological diversity, animal management strategies, penning, grazing and foddering, seasonality, and dung use. This review highlights the value of modern reference frameworks of livestock dung as a primary source of information for disentangling human–plant–animal dynamics through time and space.
Model Predictive Control for Flexible Job Shop Scheduling in Industry 4.0
Authors: Wenzelburger Philipp , Allgöwer Frank
Published: September 2021

In the context of Industry 4.0, flexible manufacturing systems play an important role. They are designed to provide the possibility to adapt the production process by reacting to changes and enabling customer specific products. The versatility of such manufacturing systems, however, also needs to be exploited by advanced control strategies. To this end, we present a novel scheduling scheme that is able to flexibly react to changes in the manufacturing system by means of Model Predictive Control (MPC). To introduce flexibility from the start, the initial scheduling problem, which is very general and covers a variety of special cases, is formulated in a modular way. This modularity is then preserved during an automatic transformation into a Petri Net formulation, which constitutes the basis for the two presented MPC schemes. We prove that both schemes are guaranteed to complete the production problem in closed loop when reasonable assumptions are fulfilled. The advantages of the presented control framework for flexible manufacturing systems are that it covers a wide variety of scheduling problems, that it is able to exploit the available flexibility of the manufacturing system, and that it allows to prove the completion of the production problem.
Data-Driven Control Algorithm for Snake Manipulator
Authors: Hu Kai , Tian Lang , Weng Chenghang , Weng Liguo , Zang Qiang , Xia Min , Qin Guodong
Published: September 2021

In some environments where manual work cannot be carried out, snake manipulators are instead used to improve the level of automatic work and ensure personal safety. However, the structure of the snake manipulator is diverse, which renders it difficult to establish an environmental model of the control system. It is difficult to obtain an ideal control effect by using the traditional manipulator control method. In view of this, this paper proposes a data-driven snake manipulator control algorithm. After collecting data, the algorithm uses the strong learning and decision-making ability of the deep deterministic strategy gradient to learn these system data. A data-driven controller based on the deep deterministic policy gradient was trained in order to solve the manipulator system control problem when the control system environment model is uncertain or even unknown. The data of simulation experiments show that the control algorithm has good stability and accuracy in the case of model uncertainty.
AOT + Polyethylene Glycol Eutectics for Enhanced Oil Recovery
Authors: Gallego Cristina , Somoza Alba , Rodríguez Héctor , Soto Ana
Published: September 2021

Eutectic solvents are currently being proposed as useful chemicals for enhanced oil recovery (EOR). In this work, for the first time, the preparation of eutectics based on surfactants and polymers was proposed for this application. These chemicals can be tailored to offer the most desired properties for oil recovery: water/oil interfacial tension reduction and increase of the aqueous phase viscosity, while concomitantly facilitating their handling due to their liquid character at ambient conditions. Sodium bis(2-ethylhexyl)sulfosuccinate (AOT) and polyethylene glycol (PEG) of three different molecular weights (namely 600, 1000, and 2000 g/mol) were paired in a search for eutectic behaviors. Melting temperatures for all the systems were determined by differential scanning calorimetry. The most promising combination was AOT + PEG-600, which exhibited a melting point of 275 K and thermal stability up to 473 K at a 40:60 molar ratio. A promising value of 5.1 × 10−2 mN/m was obtained for the interfacial tension between the optimized formulation and crude oil. The formulation was tested in core-holder experiments to extract oil from a sandstone rock at room temperature, achieving an encouraging 34% of additional oil recovery after the secondary extraction.
Automatic System for the Detection of Defects on Olive Fruits in an Oil Mill
Authors: Cano Marchal Pablo , Satorres Martínez Silvia , Gómez Ortega Juan , Gámez García Javier
Published: September 2021

The ripeness and sanitary state of olive fruits are key factors in the final quality of the virgin olive oil (VOO) obtained. Since even a small number of damaged fruits may significantly impact the final quality of the produced VOO, the olive inspection in the oil mill reception area or in the first stages of the productive process is of great interest. This paper proposes and validates an automatic defect detection system that utilizes infrared images, acquired under regular operating conditions of an olive oil mill, for the detection of defects on individual fruits. First, the image processing algorithm extracts the fruits based on the iterative application of the active contour technique assisted with mathematical morphology operations. Second, the defect detection is performed on the segmented olives using a decision tree based on region descriptors. The final assessment of the algorithm suggests that it works effectively with a high detection rate, which makes it suitable for the VOO industry.
Special Issue on “Anticancer Drugs Activity and Underlying Mechanisms”
Authors: Iacopetta Domenico
Published: September 2021

Cancer is a reputed non-communicable disease, namely a non-transmittable illness affecting humankind, which represents a major public health issue and is one of the leading causes of death worldwide [...]
Characterization of Sonic Events Present in Natural-Urban Hybrid Habitats Using UMAP and SEDnet: The Case of the Urban Wetlands
Authors: Poblete Víctor , Espejo Diego , Vargas Víctor , Otondo Felipe , Huijse Pablo
Published: September 2021

We investigated whether the use of technological tools can effectively help in manipulating the increasing volume of audio data available through the use of long field recordings. We also explored whether we can address, by using these recordings and tools, audio data analysis, feature extraction and determine predominant patterns in the data. Similarly, we explored whether we can visualize feature clusters in the data and automatically detect sonic events. Our focus was primarily on enhancing the importance of natural-urban hybrid habitats within cities, which benefit communities in various ways, specifically through the natural soundscapes of these habitats that evoke memories and reinforce a sense of belonging for inhabitants. The loss of sonic heritage can be a precursor to the extinction of biodiversity within these habitats. By quantifying changes in the soundscape of these habitats over long periods of time, we can collect relevant information linked to this eventual loss. In this respect, we developed two approaches. The first was the comparison among habitats that progressively changed from natural to urban. The second was the optimization of the field recordings’ labeling process. This was performed with labels corresponding to the annotations of classes of sonic events and their respective start and end times, including events temporarily superimposed on one another. We compared three habitats over time by using their sonic characteristics collected in field conditions. Comparisons of sonic similarity or dissimilarity among patches were made based on the Jaccard coefficient and uniform manifold approximation and projection (UMAP). Our SEDnet model achieves a F1-score of 0.79 with error rate 0.377 and with the area under PSD-ROC curve of 71.0. In terms of computational efficiency, the model is able to detect sound events from an audio file in a time of 14.49 s. With these results, we confirm the usefulness of the methods used in this work for the process of labeling field recordings.
Global Dynamics and Implications of an HBV Model with Proliferating Infected Hepatocytes
Authors: Hews Sarah , Eikenberry Steffen , Nagy John D. , Phan Tin , Kuang Yang
Published: September 2021

Chronic hepatitis B (HBV) infection is a major cause of human suffering, and a number of mathematical models have examined the within-host dynamics of the disease. Most previous models assumed that infected hepatocytes do not proliferate; however, the effect of HBV infection on hepatocyte proliferation is controversial, with conflicting data showing both induction and inhibition of proliferation. With a family of ordinary differential equation (ODE) models, we explored the dynamical impact of proliferation among HBV-infected hepatocytes. Here, we show that infected hepatocyte proliferation in this class of models generates a threshold that divides the dynamics into two categories. Sufficiently compromised proliferation in infected cells produces complex dynamics characterized by oscillating viral loads, whereas higher proliferation generates straightforward dynamics that always results in chronic infection, sometimes with liver failure. A global stability result of the liver failure state was included as it is unique to this class of models. Finally, the model analysis motivated a testable biological hypothesis: Healthy hepatocytes are present in chronic HBV infection if and only if the proliferation of infected hepatocytes is severely impaired.
Evaluation of the Simultaneous Operation of the Mechanisms for Cross-Border Interchange and Activation of the Regulating Reserves
Authors: Topler Marcel , Polajžer Boštjan
Published: September 2021

This article examines the mechanisms for cross-border interchange of the regulating reserves (RRs), i.e., the imbalance-netting process (INP) and the cross-border activation of the RRs (CBRR). Both mechanisms are an additional service of frequency restoration reserves in the power system and connect different control areas (CAs) via virtual tie-lines to release RRs and reduce balancing energy. The primary objective of the INP is to net the demand for RRs between the cooperating CAs with different signs of interchange power variation. In contrast, the primary objective of the CBRR is to activate the RRs in the cooperating CAs with matching signs of interchange power variation. In this way, the ancillary services market and the European balancing system should be improved. However, both the INP and CBRR include a frequency term and thus impact the frequency response of the cooperating CAs. Therefore, the impact of the simultaneous operation of the INP and CBRR on the load-frequency control (LFC) and performance is comprehensively evaluated with dynamic simulations of a three-CA testing system, which no previous studies investigated before. In addition, a function for correction power adjustment is proposed to prevent the undesirable simultaneous activation of the INP and CBRR. In this way, area control error (ACE) and scheduled control power are decreased since undesired correction is prevented. The dynamic simulations confirmed that the simultaneous operation of the INP and CBRR reduced the balancing energy and decreased the unintended exchange of energy. Consequently, the LFC and performance were improved in this way. However, the impact of the INP and CBRR on the frequency quality has no unambiguous conclusions.
Acoustic, Myoelectric, and Aerodynamic Parameters of Euphonic and Dysphonic Voices: A Systematic Review of Clinical Studies
Authors: Puig-Herreros Clara , Sanz José Luis , Barona Luz , Rosell-Clari Vicent
Published: September 2021

Background: At present, there is no clinical consensus on the concept of normal and dysphonic voices. For many years, the establishment of a consensus on the terminology related to normal and pathological voices has been studied, in order to facilitate the communication between professionals in the field of the voice. Aim: systematically review the literature to compare and learn more precisely the measurable and objective characteristics of the acoustic, aerodynamic and surface electromyographic parameters of the normal and dysphonic voices. Methods: The PRISMA 2020 methodology was used as a review protocol together with the PICO procedure to answer the research question through six databases. Results: In total, 467 articles were found. After duplicate records were removed from the selection, the inclusion and exclusion criteria were applied and 19 articles were eligible. A qualitative synthesis of the included studies is presented in terms of their methodology and results. Conclusions: Studying the acoustic, aerodynamic, and electromyographic parameters with more precision, in both normal and dysphonic voices, will allow health professionals working in the field of voice (speech therapy, otorhinolaryngology, phoniatrics, etc.) to establish a diagnostic and detailed consensus of the vocal pathology, enhancing the communication and generalization of results worldwide.
Comparison of Manual versus Semi-Automatic Segmentations of the Stenotic Carotid Artery Bifurcation
Authors: Csippa Benjamin , Mihály Zsuzsanna , Czinege Zsófia , Németh Márton Bence , Halász Gábor , Paál György , Sótonyi Péter
Published: September 2021

Background: The image reconstruction of stenotic carotid bifurcation can be managed by medical practitioners and non-medical investigators with semi-automatic or manual segmentation. The outcome of blood flow simulations may vary because of a single mean voxel difference along the examined section, possibly more in the stenotic lesions, which can lead to conflicting results regarding other research findings. The aim of our project is computational geometry reconstruction for blood flow simulations to make it suitable for comparison with plaque image analysis performed by commercially available software. In this paper, a comparison is made between the manual and semi-automatic segmentations performed by non-medical and medical investigators, respectively. Methods: 30 patients were classified into three homogeneous groups. Our group classification was based on the following parameters: plaque calcification score, thickness, extent, remodeling and plaque localization. The images in the first group were segmented individually by medical practitioners and experienced non-medical investigators, the second group was segmented collectively, and the last group was segmented individually again. Cross-sections along the centerline were extracted, then geometrical and statistical analyses were performed. Exploratory flow simulations were carried out on two patients to showcase the effect of geometrical differences on the hemodynamic flow field. Results: The largest centerline-averaged voxel difference between the medical and non-medical investigators occurred in the first group with a positive difference of 1.16 voxels. In the second and third groups, the average voxel difference decreased to 0.65 and 0.75, respectively. The example case from the first group showed that the difference in maximum wall shear stress in the middle of the stenosis is 30% with an average voxel difference of 1.73. Meanwhile, it can decrease to 4% when the average voxel difference is 0.64 for the example case from the third group. Conclusions: A collective review of the medical images should preceded the manual segmentations before applying them in computational simulations in order to ensure a proper comparison with plaque image analysis. Especially complex pathology such as calcifications should be segmented under medical supervision or after specific training. Non-significant differences in the segmentation can lead to significant differences in the computed flow field.
Parallel Makespan Calculation for Flow Shop Scheduling Problem with Minimal and Maximal Idle Time
Authors: Rudy Jarosław
Published: September 2021

In this paper, a flow shop scheduling problem with minimal and maximal machine idle time with the goal of minimizing makespan is considered. The mathematical model of the problem is presented. A generalization of the prefix sum, called the job shift scan, for computing required shifts for overlapping jobs is proposed. A work-efficient algorithm for computing the job shift scan in parallel for the PRAM model with n processors is proposed and its time complexity of O(logn) is proven. Then, an algorithm for computing the makespan in time O(mlogn) in parallel using the prefix sum and job shift scan is proposed. Computer experiments on GPU were conducted using the CUDA platform. The results indicate multi-thread GPU vs. single-thread GPU speedups of up to 350 and 1000 for job shift scan and makespan calculation algorithms, respectively. Multi-thread GPU vs. single-thread CPU speedups up to 4.5 and 14.7, respectively, were observed as well. The experiments on the Taillard-based problem instances using a simulated annealing solving method and employing the parallel makespan calculation show that the method is able to perform many more iterations in the given time limit and obtain better results than the non-parallel version.
Intelligent Control in the Application of a Rotary Dryer for Reduction in the Over-Drying of Cut Tobacco
Authors: Pang Shunpeng , Jia Junhua , Ding Xiangqian , Yu Shusong , Liu Yang
Published: September 2021

The drying process is fundamental for cut tobacco processing. However, there are some problems related to the drying process such as overheating, or inconsistent control of moisture content. This paper shows how an intelligent controller is designed for an industrial rotary drying system. This controller is applied to a tobacco production unit to reduce overdried cut tobacco and improve the overall unit performance. The proposed control system aims to keep the content of moisture at the dryer outlet as close as possible to the optimal value and improve the homogeneity of the product without any operator intervention. The study shows that, if a reduction of humidity in the cut tobacco drying process is achieved using AI, the quality of the final product improves. In particular, if compared to regulatory control, the proposed method constantly monitors and adjusts the moisture content level in order to reduce the amount of overdried product. The findings of this paper indicate that the suggested process can save at least 222.2 kg of cut tobacco for each batch in the first stage of the drying process.
Development of a MyData Platform Based on the Personal Health Record Data Sharing System in Korea
Authors: Choi Wona , Chun Ji-Won , Lee Seo-Joon , Chang Se-Hyun , Kim Dai-Jin , Choi In Young
Published: September 2021

Objectives: recently, there has been a government-level movement to guarantee the rights of individual entities regarding the use of their personal data worldwide. This movement has been specifically named as ‘MyData’ in South Korea and has variants such as ‘Self data’, ‘Midata’, ‘MesInfos’, ‘Personal Information Management Services’, ‘Personal Data Economy’ and ‘Internet of Me’ in other countries. This research project aimed to establish and demonstrate a system called ‘HiMD’, which allows individuals to select data sharing institutions and control a range of data utilization parameters under the MyData ecosystem. Method: we developed the MyData Platform, a personal health record data sharing system. The HiMD included several user-empowerment functions such as self-determination for data sharing. Actual platform users were recruited from three university-level hospitals for system assessment. Result: females comprised the majority of users with 991 participants (78.1%). Additionally, data consensus results revealed a decrease in given user permissions (from 94.9% to 79.4%) as the range and depth of permissions increased. Most users agreed to open their medical data for commercial uses (n = 1007, 79.4%) and most of those users were interested in DNA analysis (n = 888, 81.2%). Finally, all results for the five questions presented positive answers. All average values on the five questions scored above three on the Likert scale. In other words, over 50% participants gave point 4 and point 5. Conclusion: the contribution of this study is that it developed and demonstrated a MyData system that reflects the right to data portability. It means that the users can proactively make decisions regarding sharing and transferring their own data. These results are expected to contribute to developing future personal health record (PHR) systems of user-oriented and utilization of personal health data.
A Study on Building a “Real-Time Vehicle Accident and Road Obstacle Notification Model” Using AI CCTV
Authors: Lee Chaeyoung , Kim Hyomin , Oh Sejong , Doo Illchul
Published: September 2021

This research produced a model that detects abnormal phenomena on the road, based on deep learning, and proposes a service that can prevent accidents because of other cars and traffic congestion. After extracting accident images based on traffic accident video data by using FFmpeg for model production, car collision types are classified, and only the head-on collision types are processed by using the deep learning object-detection algorithm YOLO (You Only Look Once). Using the car accident detection model that we built and the provided road obstacle-detection model, we programmed, for when the model detects abnormalities on the road, warning notification and photos that captures the accidents or obstacles, which are then transferred to the application. The proposed service was verified through application notification simulations and virtual experiments using CCTVs in Daegu, Busan, and Gwangju. By providing services, the goal is to improve traffic safety and achieve the development of a self-driving vehicle sector. As a future research direction, it is suggested that an efficient CCTV control system be introduced for the transportation environment.
Polyaspartic Acid-Coated Paramagnetic Gadolinium Oxide Nanoparticles as a Dual-Modal T1 and T2 Magnetic Resonance Imaging Contrast Agent
Authors: Marasini Shanti , Yue Huan , Ghazanfari Adibehalsadat , Ho Son Long , Park Ji Ae , Kim Soyeon , Cha Hyunsil , Liu Shuwen , Tegafaw Tirusew , Ahmad Mohammad Yaseen , Saidi Abdullah Khamis Ali Al , Zhao Dejun , Liu Ying , Chae Kwon-Seok , Chang Yongmin , Lee Gang Ho
Published: September 2021

Surface-coating polymers contribute to nanoparticle-based magnetic resonance imaging (MRI) contrast agents because they can affect the relaxometric properties of the nanoparticles. In this study, polyaspartic acid (PASA)-coated ultrasmall Gd2O3 nanoparticles with an average particle diameter of 2.0 nm were synthesized using the one-pot polyol method. The synthesized nanoparticles exhibited r1 and r2 of 19.1 and = 53.7 s−1mM−1, respectively, (r1 and r2 are longitudinal and transverse water–proton spin relaxivities, respectively) at 3.0 T MR field, approximately 5 and 10 times higher than those of commercial Gd-chelate contrast agents, respectively. The T1 and T2 MR images could be obtained due to an appreciable r2/r1 ratio of 2.80, indicating their potential as a dual-modal T1 and T2 MRI contrast agent.
Deep Learning Model for the Inspection of Coffee Bean Defects
Authors: Chang Shyang-Jye , Huang Chien-Yu
Published: September 2021

The detection of coffee bean defects is the most crucial step prior to bean roasting. Existing defect detection methods used in the specialty coffee bean industry entail manual screening and sorting, require substantial human resources, and are not standardized. To solve these problems, this study developed a deep learning algorithm to detect defects in coffee beans. The results reveal that when the pooling layer was used to enhance features and reduce neural dimensionality, some of the coffee been features were lost or misclassified. Therefore, a novel dimensionality reduction method was adopted to increase the ability of feature extraction. The developed model also overcame the drawbacks of padding causing blurred image boundaries and the dead neurons causing impeding feature propagation. Images of eight types of coffee beans were used to train and test the proposed detection model. The proposed method was verified to reduce the bias when classifying defects in coffee beans. The detection accuracy rate of the proposed model was 95.2%. When the model was only used to detect the presence of defects, the accuracy rate increased to 100%. Thus, the proposed model is highly accurate in coffee bean defect detection in the classification of eight types of coffee beans.
Time–Frequency Domain Characteristics of Acoustic Emission Signals and Critical Fracture Precursor Signals in the Deep Granite Deformation Process
Authors: Zhang Le , Ji Hongguang , Liu Liyuan , Zhao Jiwei
Published: September 2021

To study the crack evolution law and failure precursory characteristics of deep granite rocks in the process of deformation and failure under high confining pressure, granite samples obtained from a depth of 1150 m are tested using a TAW-2000 triaxial hydraulic servo testing machine and a PCI-II acoustic emission monitoring system. Based on the stress–strain curve and IET function, the loading process of the sample is divided into five stages: crack closure, linear elastic deformation, microcrack generation and development, macroscopic fracture generation and energy surge, and post-peak failure. The evolution trend and fracture evolution law of the acoustic emission signal event interval function in different stages are analyzed. In particular, the signals with an amplitude greater than 85 dB, a peak frequency greater than 350 kHz, and a frequency centroid greater than 275 kHz are defined as the failure precursor signals before the rock reaches the peak stress. The defined precursor signal conditions agree well with the experimental results. The time–frequency analysis and wavelet packet decomposition of the precursor signal are performed on the extracted characteristic signal of the failure precursor. The results show that the time-domain signal is in the form of a continuous waveform, and the frequency-domain waveform has multi-peak coexistence that is mainly concentrated in the high-frequency region. The energy distribution obtained by the wavelet packet decomposition of the characteristic signal is verified with the frequency-domain waveform. The energy distribution of the signal is mainly concentrated in the 343.75–375 kHz frequency band, followed by the 281.25–312.5 kHz frequency band. The energy proportion of the high-frequency signal increases with the confining pressure.
Sample Reduction for Physiological Data Analysis Using Principal Component Analysis in Artificial Neural Network
Authors: Adolfo Cid Mathew Santiago , Chizari Hassan , Win Thu Yein , Al-Majeed Salah
Published: September 2021

With its potential, extensive data analysis is a vital part of biomedical applications and of medical practitioner interpretations, as data analysis ensures the integrity of multidimensional datasets and improves classification accuracy; however, with machine learning, the integrity of the sources is compromised when the acquired data pose a significant threat in diagnosing and analysing such information, such as by including noisy and biased samples in the multidimensional datasets. Removing noisy samples in dirty datasets is integral to and crucial in biomedical applications, such as the classification and prediction problems using artificial neural networks (ANNs) in the body’s physiological signal analysis. In this study, we developed a methodology to identify and remove noisy data from a dataset before addressing the classification problem of an artificial neural network (ANN) by proposing the use of the principal component analysis–sample reduction process (PCA–SRP) to improve its performance as a data-cleaning agent. We first discuss the theoretical background to this data-cleansing methodology in the classification problem of an artificial neural network (ANN). Then, we discuss how the PCA is used in data-cleansing techniques through a sample reduction process (SRP) using various publicly available biomedical datasets with different samples and feature sizes. Lastly, the cleaned datasets were tested through the following: PCA–SRP in ANN accuracy comparison testing, sensitivity vs. specificity testing, receiver operating characteristic (ROC) curve testing, and accuracy vs. additional random sample testing. The results show a significant improvement in the classification of ANNs using the developed methodology and suggested a recommended range of selectivity (Sc) factors for typical cleaning and ANN applications. Our approach successfully cleaned the noisy biomedical multidimensional datasets and yielded up to an 8% increase in accuracy with the aid of the Python language.
Optimal Generation Start-Up Methodology for Power System Restoration Considering Conventional and Non-Conventional Renewable Energy Sources
Authors: Pardo-Martínez Ricardo Andrés , López-Lezama Jesús M. , Muñoz-Galeano Nicolás
Published: September 2021

Power system restoration must be accomplished as soon as possible after a blackout. In this process, available black-start (BS) units are used to provide cranking power to non-black-start (NBS) units so as to maximize the overall power system generation capacity. This procedure is known as the generation start-up problem, which is intrinsically combinatorial with complex non-linear constraints. This paper presents a new mixed integer linear programming (MILP) formulation for the generation start-up problem that integrates non-conventional renewable energy sources (NCRES) and battery energy storage systems (BESS). The main objective consists of determining an initial starting sequence for both BS and NBS units that would maximize the generation capacity of the system while meeting the non-served demand of the network. The nature of the proposed model leads to global optimal solutions, clearly outperforming heuristic and enumerative approaches, since the latter may take higher computational time while the former do not guarantee global optimal solutions. Several tests were carried out on the IEEE 39-bus test system considering BESS as well as wind and solar generation. The results showed the positive impact of NCRES in the restoration processes and evidenced the effectiveness and applicability of the proposed approach. It was found that including NCRES and BESS in the restoration process allows a reduction of 24.4% of the objective function compared to the classical restoration without these technologies.
Risk-Based Virtual Power Plant Implementation Strategy for Smart Energy Communities
Authors: Oh Eunsung
Published: September 2021

This paper focuses on a virtual power plant (VPP) implementation strategy for smart local energy communities (SECs) with energy service providers. It is difficult to balance energy in the implementation stage due to uncertainties in demand and resources. Therefore, VPP implementation was modeled using the risk factor of energy balance. Using this risk factor, it was shown that the temporal correlation between demand and resources was the dominant factor involved in VPP implementation. Based on this, two risk-based VPP implementation strategies are proposed: an optimization-based strategy and a simple strategy that is solved in an iterative way. To minimize VPP implementation costs, the proposed strategies select the resources that have high correlation coefficients with demand and low correlation coefficients with other resources. Experimental results using real data sets show that the proposed strategies based on the risk factor are effective means of VPP implementation for commercial and residential SECs. The results imply that VPPs for commercial SECs are possible when PV is used as the main resource and is supplemented by wind, and it is effective to configure VPPs for residential SECs using wind according to the correlation between demand and resources.