bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the Possibility of Using New Types of Protective Coatings and Abrasion-Resistant Linings under the Operating Conditions of the Spiral Classifier at KGHM Polska Miedź S.A. Ore Concentration Plant
Authors: Czekajło Marcin , Zakowski Krzysztof , Krakowiak Stefan , Kierepa Sławomir
Published: September 2021

A study was carried out to select the appropriate coatings for corrosion protection of the spiral classifier working at KGHM Polska Miedź S.A. Ore Concentration Plant. The abrasion resistance of selected protective coatings and wear-resistant linings was investigated using a DT-523 rotary abrasion tester with Taber CS-10 rubber abrasive discs. The average weight loss of the coatings after a cycle of 2000 revolutions was determined. Tests of protective coatings using the electrochemical impedance spectroscopy (EIS) technique were carried out to determine the suitability of coatings in the highly saline environment of the aqueous suspension of ground copper ore. During the measurements, changes in resistance, polarising current and capacitance were determined as a function of time for the tested coatings. The linings selected on the basis of laboratory tests were also tested under industrial conditions. Their degrees of wear were characterised. The results obtained indicated the highest abrasion resistance of materials from the polyolefin group (polyethylenes), where the average weight loss did not exceed 5 g/dm2. In the case of protective coatings, the highest durability was demonstrated by coatings with additives of ceramic aggregates, phenol-epoxy, and an elastomeric coating based on polyurea, whose average weight loss during the test cycle did not exceed 19 g/dm2. EIS measurements showed that the tested coatings were resistant to the aggressive environment of the feedstock. Tests under cathodic polarisation conditions of the samples at a potential below the protection potential showed that they were resistant to a highly saline environment and were also resistant to its alkalinisation resulting from the application of cathodic protection, which will be used to protect the classifier together with protective coatings. Tests carried out under industrial conditions using wear-resistant linings made of plastics have made it possible to analyse the mechanism and degree of wear of the various materials during the operation of the classifier. Measurements of lining wear were made in relation to baseline volumes. Polyurethane, a polymer lining based on MDI and PTMG, and those made of ultra-high-molecular-weight polyethylene with anti-stick additives showed the lowest wear rates.
Coupling Effect of Salt Freeze-Thaw Cycles and Carbonation on the Mechanical Performance of Quick Hardening Sulphoaluminate Cement-Based Reactive Powder Concrete with Basalt Fibers
Authors: Huang Guoping , Wang Hui , Shi Feiting
Published: September 2021

The effect of salt freeze-thaw cycles coupled with carbonation on the mechanical performance of quick hardening sulphoaluminate cement-based reactive powder concrete combined with basalt fibers was investigated. The ratios of basalt fibers in sulphoaluminate cement-based reactive powder concrete (SAC-RPC) were 1%, 2%, 3% and 4% by the volume of concrete. The mechanical strengths (compressive strength, flexural strength and bonding strength) of SAC-RPC were investigated after curing for 5 h, 1 d, 14 d and 28 d, respectively. Meanwhile, the mechanical strengths of resultant concrete were detected, when different NaCl freeze-thaw cycles and carbonation were adopted. Results showed that the addition of basalt fibers could effectively improve the mechanical strengths, especially the flexural strength of SAC-RPC. The dosage of 3.0% was the threshold value affected mechanical strengths. The flexural, compressive and bonding strengths of SAC-RPC were higher than 8.53 MPa, 34 MPa and 3.21 MPa, respectively. The mass loss and mechanical strengths loss of SAC-RPC increased in the form of quadratic function with the increasing number of NaCl freeze-thaw cycles and varied in the form of quadratic decreasing function. Meanwhile, the effect of carbonation on the mechanical strengths of SAC-RPC can be ignored. Additionally, the coupling effect of salt freeze-thaw cycles and carbonation could accelerate the attenuation of concrete strength. The mechanical strengths loss demonstrated a decreased quadratic function with the increasing volume of basalt fibers.
360°-Based Virtual Field Trips to Waterworks in Higher Education
Authors: Wolf Mario , Wehking Florian , Montag Michael , Söbke Heinrich
Published: September 2021

360° models are a form of virtual reality (VR) that allow the viewer to view and explore a photorealistic object from multiple locations within the model. Hence, 360° models are an option to perform virtual field trips (VFT) independent of time and location. Thanks to recent technical progress, 360° models are creatable with little effort. Due to their characteristics of visualization and explorability, 360° models appear as excellent learning tools, especially when additional didactic features, such as annotations, are used. The subject of this explorative field study is a 360° model of a waterworks that has been annotated for learning purposes. Data are collected from a total of 55 learners in four cohorts from study programs in environmental engineering and urban studies using a questionnaire that included standardized measurement instruments on motivation, emotion, and usability. Furthermore, the eight learners of cohort 1 are surveyed using semi-structured interviews on learning, operation and features of the 360° model. Overall, a very positive view on learning suitability of 360° models in VFTs is revealed. In addition, further potential for development of the 360° model could be identified. The results indicate that VTFs based on 360° models might be valuable learning tools, because of their applicability without great effort on the part of either the lecturers or the students. VFTs based on 360° models might serve as a supplement to conventional learning activities or in self-directed learning activities.
Mechanical Properties of Pack Carburized SCM 420 Steel Processed Using Natural Shell Powders and Extended Carburization Time
Authors: Ramli  , Wu Chung-Chun , Shaaban Adel
Published: September 2021

The feasibility of using coconut shell powder (CSP) and dog conch shell powder (DCSP) as carburizing media in the pack carburization of SCM 420 steel was investigated. The carbon content and surface hardness of the carburized specimens prepared with different CSP:DCSP ratios and carburizing durations were examined and compared. A CSP:DCSP ratio of 60%:40% and an extended carburizing time of 12 h were found to increase the carbon content of the carburized specimens to 1.14 ± 0.007 wt%. Furthermore, the surface hardness was significantly improved to 961.3 ± 4.918 HV following water quenching. Finally, the thickness of the carburized layer of the quenched specimens increased by around 2.5 times as the carburizing duration was increased from 3 to 12 h.
Physicochemical, Photocatalytic, Antibacterial, and Antioxidant Screening of Bergenia Ciliata Mediated Nickel Oxide Nanoparticles
Authors: Rehman Fazal Ur , Mahmood Rashid , Ali Manel Ben , Hedfi Amor , Mezni Amine , Haq Sirajul , Din Salah Ud , Ehsan Rimsha
Published: September 2021

This study was planned to synthesize a multifunctional nanomaterial that can effectively encounter the organic pollutants, multidrug-resistant bacteria and reactive free radicals. The Bergenia ciliate (B. ciliate) leaves extract was used as a reducing and capping agent for the synthesis of nickel oxide nanoparticles (NiO NP). The physicochemical properties were studied through X-ray diffractometre (XRD), energy dispersive X-ray (EDX), scanning electron microscopy (SEM), transmission electron microscopy (TEM), UV-visible and Fourier transform infrared (FTIR) spectroscopies. The highly crystalline monoclinic NiO NPs were synthesized with crystallite size of 27.45 nm. The average particle size derived from TEM micrograph was 49.35 nm whereas the calculated band gap for NiO NPs was 3.78 eV. The photocatalytic study shows that 92.17% of the rhodamine 6G (Rh-6G) was efficiently degraded in the presence of NiO NPs. The agar well diffusion method was applied to examine the antibacterial activity of NiO NPs and the activity was found higher against Gram-negative bacteria (GNB) as compared to Gram-positive bacteria (GPB). The ABTS free radical scavenging activity was also performed, however, the activity was found less than the standard.
Pressure- and Temperature-Dependent Crystallization Kinetics of Isotactic Polypropylene under Process Relevant Conditions
Authors: Spoerer Yvonne , Boldt Regine , Androsch René , Kuehnert Ines
Published: September 2021

In this study, a non-nucleated homopolymer (HP) and random copolymer (RACO), as well as a nucleated HP and heterophasic copolymer (HECO) were investigated regarding their crystallization kinetics. Using pvT-measurements and fast scanning chip calorimetry (FSC), the crystallization behavior was analyzed as a function of pressure, cooling rate and temperature. It is shown that pressure and cooling rate have an opposite influence on the crystallization temperature of the materials. Furthermore, the addition of nucleating agents to the material has a significant effect on the maximum cooling rate at which the formation of α-crystals is still possible. The non-nucleated HP and RACO materials show significant differences that can be related to the sterically hindering effect of the comonomer units of RACO on crystallization, while the nucleated materials HP and HECO show similar crystallization kinetics despite their different structures. The pressure-dependent shift factor of the crystallization temperature is independent of the material. The results contribute to the description of the relationship between the crystallization kinetics of the material and the process parameters influencing the injection-molding induced morphology. This is required to realize process control in injection molding in order to produce pre-defined morphologies and to design material properties.
Understanding of Photophysical Processes in DIO Additive-Treated PTB7:PC71BM Solar Cells
Authors: Su Xiaojun , Hu Rong , Wen Guanzhao , Zou Xianshao , Qing Mengyao , Peng Jun , He Xiaochuan , Zhang Wei
Published: September 2021

1,8-diiodooctane (DIO) additive is an important method for optimizing the morphology and device performance of polythieno[3,4-b]-thiophene-co-benzodithiophene (PTB7)-based polymer solar cells. However, the effect of DIO additive on charge photogeneration dynamics of PTB7-based polymer solar cells is still poorly understood. In this work, the effect of DIO additive on the carrier photogeneration dynamics, as well as device performance of PTB7: [6,6]-phenyl-C71-butyric acid methyl ester (PC71BM) solar cells was studied. Bias-dependent photoluminescence (PL) experiments of a neat PTB7 device show that the exciton cannot be dissociated by the electric field in the device within the operating voltage range, but it can be effectively dissociated by the high electric field. PL and time-resolved PL studies show that DIO additive reduces the phase size of PTB7 in the blend film, resulting in an increased exciton dissociation efficiency. The carrier recombination processes were studied by transient absorption, which shows geminate carrier recombination was suppressed in the DIO-treated PTB7:PC71BM device in ultrafast time scale. The increased exciton dissociation efficiency and suppressed carrier recombination in ultrafast time scale play an important role for DIO-treated PTB7:PC71BM solar cells to attain a higher power conversion efficiency.
Fabrication and Evaluation of Low-Cost CrSi2 Thermoelectric Legs
Authors: Le Tonquesse Sylvain , Matsushita Yoshitaka , Jood Priyanka , Ohta Michihiro , Mori Takao , Berthebaud David
Published: September 2021

CrSi2 is a promising thermoelectric material constituted of non-toxic and earth abundant elements that offer good perspectives for the mass production of inexpensive and reliable thermoelectric modules for waste heat recovery. Realization of robust metallic contacts with low electrical and thermal resistances on thermoelectric materials is crucial to maximize the conversion efficiency of such a device. In this article, the metallization of an undoped CrSi2 with Ti and Nb using a conventional Spark Plasma Sintering process is explored and discussed. These contact metals were selected because they have compatible thermal expansion coefficients with those of CrSi2, which were determined in this study by X-ray Diffraction in the temperature range 299–899 K. Ti was found to be a promising contact metal offering both strong adhesion on CrSi2 and negligible electrical contact resistance (<1 μΩ cm2). However, metallization with Nb resulted in the formation of cracks caused by large internal stress inside the sample during the fabrication process and the diffusion of Si in the metallic layer. A maximum conversion efficiency of 0.3% was measured for a sandwiched Ti/CrSi2/Ti thermoelectric leg placed inside a thermal gradient of 427 K. The preliminary results obtained and discussed in this article on a relatively simple case study aim to initiate the development of more reliable and efficient CrSi2 thermoelectric legs with an optimized design.
The Architectonics Features of Heterostructures for IR Range Detectors Based on Polycrystalline Layers of Lead Chalcogenides
Authors: Spivak Yuliya Mikhailovna , Kononova Irina Evgen’evna , Kononov Pavel Vasil’evich , Moshnikov Vyacheslav Alexeyevich , Ignat’ev Sergey Anatol’evich
Published: September 2021

A model is developed for the formation of porous intragranular architectonics of nanostructured polycrystalline layers of lead chalcogenides for photodetectors and IR emitters. The layers are obtained under the conditions of thermal evaporation in a quasi-closed volume by the “hot wall” method followed by sensitizing heat treatment in an iodine-containing atmosphere. Model concepts are developed considering the experimental results of studying the intragranular structure of lead chalcogenides through original combined AFM methods over the cross-section of porous grains (cores) encapsulated by an oxide shell (lateral force microscopy and local tunneling I–V spectroscopy).
Novel NiMgOH-rGO-Based Nanostructured Hybrids for Electrochemical Energy Storage Supercapacitor Applications: Effect of Reducing Agents
Authors: Shireesha Konda , Kumar Thida Rakesh , Rajani Tumarada , Chakra Chidurala Shilpa , Kumari Murikinati Mamatha , Divya Velpula , Raghava Reddy Kakarla
Published: September 2021

This paper describes the synthesis and characterization of NiMgOH-rGO nanocomposites made using a chemical co-precipitation technique with various reducing agents (e.g., NaOH and NH4OH) and reduced graphene oxide at 0.5, 1, and 1.5 percent by weight. UV-visible spectroscopy, Fourier-transform infrared spectroscopy, X-ray diffraction, a particle size analyzer, and cyclic voltammetry were used to characterize the composite materials. The formation of the NiMgOH-rGO nanocomposite with crystallite sizes in the range of 10–40 nm was inferred by X-ray diffraction patterns of materials, which suggested interlayers of Ni(OH)2 and Mg(OH)2. The interactions between the molecules were detected using Fourier-transform infrared spectroscopy, while optical properties were studied using UV-visible spectroscopy. A uniform average particle size distribution in the range of 1–100 nm was confirmed by the particle size analyzer. Using cyclic voltammetry and galvanostatic charge/discharge measurements in a 6 M KOH solution, the electrochemical execution of NiMgOH-rGO nanocomposites was investigated. At a 1 A/g current density, the NiMgOH-rGO nanocomposites prepared with NH4OH as a reducing agent had a higher specific capacitance of 1977 F/g. The electrochemical studies confirmed that combining rGO with NiMgOH increased conductivity.
Ab Initio Simulation of the IR Spectrum of Hydrated Kaolinite
Authors: Yavna Victor , Nazdracheva Tatiana , Morozov Andrey , Ermolov Yakov , Kochur Andrei
Published: September 2021

The hydration of the basal surfaces of kaolinite is studied by theoretical methods. The cluster method was used to simulate the positions of atoms. The positions of the atoms of the basal surfaces of dry and hydrated minerals are optimized by minimizing the total energy in the Hartree–Fock approximation. The adsorption energies of water molecules were calculated taking into account the fourth-order correlation corrections of Møller–Plesset perturbation theory. The formation of the IR spectrum of kaolinite in the range of wave numbers 2500–4500 cm−1 is studied. The experimentally observed effect of the change in relative intensity and position of the band with a change in the moisture content of the sample is interpreted.
Coronary Calcium Scoring with First Generation Dual-Source Photon-Counting CT—First Evidence from Phantom and In-Vivo Scans
Authors: Eberhard Matthias , Mergen Victor , Higashigaito Kai , Allmendinger Thomas , Manka Robert , Flohr Thomas , Schmidt Bernhard , Euler Andre , Alkadhi Hatem
Published: September 2021

We evaluated the accuracy of coronary artery calcium (CAC) scoring on a dual-source photon-counting detector CT (PCD-CT). An anthropomorphic chest phantom underwent ECG-gated sequential scanning on a PCD-CT at 120 kV with four radiation dose levels (CTDIvol, 2.0–8.6 mGy). Polychromatic images at 120 kV (T3D) and virtual monoenergetic images (VMI), from 60 to 75 keV without quantum iterative reconstruction (no QIR) and QIR strength levels 1–4, were reconstructed. For reference, the same phantom was scanned on a conventional energy-integrating detector CT (120 kV; filtered back projection) at identical radiation doses. CAC scoring in 20 patients with PCD-CT (120 kV; no QIR and QIR 1–4) were included. In the phantom, there were no differences between CAC scores of different radiation doses (all, p > 0.05). Images with 70 keV, no QIR (CAC score, 649); 65 keV, QIR 3 (656); 65 keV; QIR4 (648) and T3D, QIR4 (656) showed a <1% deviation to the reference (653). CAC scores significantly decreased at increasing QIR levels (all, p < 0.001) and for each 5 keV-increase (all, p < 0.001). Patient data (median CAC score: 86 [inter-quartile range: 38–978] at 70 keV) confirmed relationships and differences between reconstructions from the phantom. First phantom and in-vivo experience with a clinical dual-source PCD-CT system shows accurate CAC scoring with VMI reconstructions at different radiation dose levels.
Antibodies against SARS-CoV-2 Time Course in Patients and Vaccinated Subjects: An Evaluation of the Harmonization of Two Different Methods
Authors: Dittadi Ruggero , Seguso Mara , Bertoli Isabella , Afshar Haleh , Carraro Paolo
Published: September 2021

The time course of antibodies against SARS-CoV-2 is not yet well elucidated, especially in people who underwent a vaccination campaign. In this study, we measured the antibodies anti-S1 and anti-RBD with two different methods, both in patients and in vaccinated subjects. One hundred and eight specimens from 48 patients with COVID-19 (time from the onset of symptoms from 3 to 368 days) and 60 specimens from 20 vaccinated subjects (collected after 14 days from the first dose, 14 days and 3 months after a second dose of Comirnaty) were evaluated. We used an ELISA method that measured IgG against anti-Spike 1, and a chemiluminescence immunoassay that measured IgG anti-RBD. In the patients, the antibodies concentrations tended to decline after a few months, with both the methods, but they persisted relatively high up to nearly a year after the symptoms. In the vaccinated subjects, the antibodies were already detectable after the first dose, but after the booster, they showed a significant increase. However, the decrease was rapid, given that 3 months after the second vaccination, they were reduced to less than a quarter. The conversion of the results into BAU units improves the relationship between the two methods. However, in the vaccinated subjects, there was no evidence of proportional error after the conversion, while in the patients, the difference between the two methods remained significant.
Intradural Pediatric Spinal Tumors: An Overview from Imaging to Novel Molecular Findings
Authors: Marrazzo Antonio , Cacchione Antonella , Rossi Sabrina , Carboni Alessia , Gandolfo Carlo , Carai Andrea , Mastronuzzi Angela , Colafati Giovanna Stefania
Published: September 2021

Pediatric spinal tumors are rare and account for 10% of all central nervous system tumors in children. Onset usually occurs with chronic nonspecific symptoms and may depend on the intra- or extradural neoplastic location. Meningiomas, schwannomas, and neurofibromas are the most common intradural-extramedullary lesions, while astrocytomas and ependymomas represent the majority of intramedullary tumors. The new molecular discoveries regarding pediatric spinal cancer currently contribute to the diagnostic and therapeutic processes. Moreover, some familial genetic syndromes can be associated with the development of spinal tumors. Currently, magnetic resonance imaging (MRI) is the standard reference for the evaluation of pediatric spinal tumors. Our aim in this review was to describe the imaging of the most frequent intradural intra/extramedullary pediatric spinal tumors and to investigate the latest molecular findings and genetic syndromes.
MALT Lymphoma of the Tongue in a Patient with Sjögren’s Syndrome: A Case Report and Literature Review
Authors: Baik Jiyeon , Baek Hye-Jin , Ryu Kyeong-Hwa , An Hyo-Jung , Song Seulki , Lee Ho-Joon , Kang Yeonah
Published: September 2021

Sjögren’s syndrome (SS) is a systemic chronic autoimmune disorder characterized by lymphocytic infiltration of the exocrine glands, as well as oral and ocular dryness. Among the late complications, malignant lymphoma is the most serious complication of SS. The risk of lymphoma in patients with SS has been estimated to be approximately 7–19 times higher than that in a generally healthy population. Although various histologic subtypes of lymphoma can occur in patients with SS, mucosa-associated lymphoid tissue (MALT) lymphoma accounts for 48–75% of malignant lymphomas that are frequently located in the parotid gland. However, MALT lymphoma affecting the tongue in patients with SS is extremely rare. Here, we share our experience with a unique case of MALT lymphoma of the tongue, originating from the minor salivary gland tissue in a patient with SS. Through this case report, we emphasize that MALT lymphoma should be considered in the differential diagnosis of a tongue mass in patients with SS.
Comparison of Different Machine Learning Classifiers for Glaucoma Diagnosis Based on Spectralis OCT
Authors: Wu Chao-Wei , Shen Hsiang-Li , Lu Chi-Jie , Chen Ssu-Han , Chen Hsin-Yi
Published: September 2021

Early detection is important in glaucoma management. By using optical coherence tomography (OCT), the subtle structural changes caused by glaucoma can be detected. Though OCT provided abundant parameters for comprehensive information, clinicians may be confused once the results conflict. Machine learning classifiers (MLCs) are good tools for considering numerous parameters and generating reliable diagnoses in glaucoma practice. Here we aim to compare different MLCs based on Spectralis OCT parameters, including circumpapillary retinal nerve fiber layer (cRNFL) thickness, Bruch’s membrane opening-minimum rim width (BMO-MRW), Early Treatment Diabetes Retinopathy Study (ETDRS) macular thickness, and posterior pole asymmetry analysis (PPAA), in discriminating normal from glaucomatous eyes. Five MLCs were proposed, namely conditional inference trees (CIT), logistic model tree (LMT), C5.0 decision tree, random forest (RF), and extreme gradient boosting (XGBoost). Logistic regression (LGR) was used as a benchmark for comparison. RF was shown to be the best model. Ganglion cell layer measurements were the most important predictors in early glaucoma detection and cRNFL measurements were more important as the glaucoma severity increased. The global, temporal, inferior, superotemporal, and inferotemporal sites were relatively influential locations among all parameters. Clinicians should cautiously integrate the Spectralis OCT results into the entire clinical picture when diagnosing glaucoma.
Diagnosis of Early Mycosis Fungoides
Authors: Miyagaki Tomomitsu
Published: September 2021

Mycosis fungoides (MF), the most common type of cutaneous T-cell lymphomas, generally has a favorable clinical course. Early MF typically presents erythematous patches and/or plaques and lasts for many years without affecting the life expectancy. Only limited cases progress to develop skin tumors, with subsequent lymph nodes and rarely visceral organ involvement. One of the clinical problems in early MF is the difficulty in differentiating the disease from benign inflammatory disorders (BIDs), such as atopic dermatitis, chronic eczema, and psoriasis. In some MF cases, clinical and pathological findings are similar to those of BIDs. However, the accurate diagnosis of early MF is quite important, as inappropriate treatment including immunosuppressants can cause unfavorable or even fatal outcomes. This article focuses on general methods and novel tools for diagnosis of early MF.
Artificial Intelligence in Capsule Endoscopy: A Practical Guide to Its Past and Future Challenges
Authors: Kim Sang Hoon , Lim Yun Jeong
Published: September 2021

Artificial intelligence (AI) has revolutionized the medical diagnostic process of various diseases. Since the manual reading of capsule endoscopy videos is a time-intensive, error-prone process, computerized algorithms have been introduced to automate this process. Over the past decade, the evolution of convolutional neural network (CNN) enabled AI to detect multiple lesions simultaneously with increasing accuracy and sensitivity. Difficulty in validating CNN performance and unique characteristics of capsule endoscopy images make computer-aided reading systems in capsule endoscopy still on a preclinical level. Although AI technology can be used as an auxiliary second observer in capsule endoscopy, it is expected that in the near future, it will effectively reduce the reading time and ultimately become an independent, integrated reading system.
The TVGH-NYCU Thal-Classifier: Development of a Machine-Learning Classifier for Differentiating Thalassemia and Non-Thalassemia Patients
Authors: Fu Yi-Kai , Liu Hsueng-Mei , Lee Li-Hsuan , Chen Ying-Ju , Chien Sheng-Hsuan , Lin Jeong-Shi , Chen Wen-Chun , Cheng Ming-Hsuan , Lin Po-Heng , Lai Jheng-You , Chen Chyong-Mei , Liu Chun-Yu
Published: September 2021

Thalassemia and iron deficiency are the most common etiologies for microcytic anemia and there are indices discriminating both from common laboratory simple automatic counters. In this study a new classifier for discriminating thalassemia and non-thalassemia microcytic anemia was generated via combination of exciting indices with machine-learning techniques. A total of 350 Taiwanese adult patients whose anemia diagnosis, complete blood cell counts, and hemoglobin gene profiles were retrospectively reviewed. Thirteen prior established indices were applied to current cohort and the sensitivity, specificity, positive and negative predictive values were calculated. A support vector machine (SVM) with Monte-Carlo cross-validation procedure was adopted to generate the classifier. The performance of our classifier was compared with original indices by calculating the average classification error rate and area under the curve (AUC) for the sampled datasets. The performance of this SVM model showed average AUC of 0.76 and average error rate of 0.26, which surpassed all other indices. In conclusion, we developed a convenient tool for primary-care physicians when deferential diagnosis contains thalassemia for the Taiwanese adult population. This approach needs to be validated in other studies or bigger database.
Not All Structure and Dynamics Are Equal
Authors: Mindt Garrett
Published: September 2021

The hard problem of consciousness has been a perennially vexing issue for the study of consciousness, particularly in giving a scientific and naturalized account of phenomenal experience. At the heart of the hard problem is an often-overlooked argument, which is at the core of the hard problem, and that is the structure and dynamics (S&D) argument. In this essay, I will argue that we have good reason to suspect that the S&D argument given by David Chalmers rests on a limited conception of S&D properties, what in this essay I’m calling extrinsic structure and dynamics. I argue that if we take recent insights from the complexity sciences and from recent developments in Integrated Information Theory (IIT) of Consciousness, that we get a more nuanced picture of S&D, specifically, a class of properties I’m calling intrinsic structure and dynamics. This I think opens the door to a broader class of properties with which we might naturally and scientifically explain phenomenal experience, as well as the relationship between syntactic, semantic, and intrinsic notions of information. I argue that Chalmers’ characterization of structure and dynamics in his S&D argument paints them with too broad a brush and fails to account for important nuances, especially when considering accounting for a system’s intrinsic properties. Ultimately, my hope is to vindicate a certain species of explanation from the S&D argument, and by extension dissolve the hard problem of consciousness at its core, by showing that not all structure and dynamics are equal.
A High-Efficiency Spectral Method for Two-Dimensional Ocean Acoustic Propagation Calculations
Authors: Ma Xian , Wang Yongxian , Zhu Xiaoqian , Liu Wei , Xiao Wenbin , Lan Qiang
Published: September 2021

The accuracy and efficiency of sound field calculations highly concern issues of hydroacoustics. Recently, one-dimensional spectral methods have shown high-precision characteristics when solving the sound field but can solve only simplified models of underwater acoustic propagation, thus their application range is small. Therefore, it is necessary to directly calculate the two-dimensional Helmholtz equation of ocean acoustic propagation. Here, we use the Chebyshev–Galerkin and Chebyshev collocation methods to solve the two-dimensional Helmholtz model equation. Then, the Chebyshev collocation method is used to model ocean acoustic propagation because, unlike the Galerkin method, the collocation method does not need stringent boundary conditions. Compared with the mature Kraken program, the Chebyshev collocation method exhibits a higher numerical accuracy. However, the shortcoming of the collocation method is that the computational efficiency cannot satisfy the requirements of real-time applications due to the large number of calculations. Then, we implemented the parallel code of the collocation method, which could effectively improve calculation effectiveness.
Energy Loss and Radial Force Variation Caused by Impeller Trimming in a Double-Suction Centrifugal Pump
Authors: Deng Qifan , Pei Ji , Wang Wenjie , Lin Bin , Zhang Chenying , Zhao Jiantao
Published: September 2021

Impeller trimming is an economical method for broadening the range of application of a given pump, but it can destroy operational stability and efficiency. In this study, entropy production theory was utilized to analyze the variation of energy loss caused by impeller trimming based on computational fluid dynamics. Experiments and numerical simulations were conducted to investigate the energy loss and fluid-induced radial forces. The pump’s performance seriously deteriorated after impeller trimming, especially under overload conditions. Energy loss in the volute decreased after trimming under part-load conditions but increased under overload conditions, and this phenomenon made the pump head unable to be accurately predicted by empirical equations. With the help of entropy production theory, high-energy dissipation regions were mainly located in the volute discharge diffuser under overload conditions because of the flow separation and the mixing of the main flow and the stalled fluid. The increased incidence angle at the volute’s tongue after impeller trimming resulted in more serious flow separation and higher energy loss. Furthermore, the radial forces and their fluctuation amplitudes decreased under all the investigated conditions. The horizontal components of the radial forces in all cases were much higher than the vertical components.
Enhanced Directed Random Walk for the Identification of Breast Cancer Prognostic Markers from Multiclass Expression Data
Authors: Nies Hui Wen , Mohamad Mohd Saberi , Zakaria Zalmiyah , Chan Weng Howe , Remli Muhammad Akmal , Nies Yong Hui
Published: September 2021

Artificial intelligence in healthcare can potentially identify the probability of contracting a particular disease more accurately. There are five common molecular subtypes of breast cancer: luminal A, luminal B, basal, ERBB2, and normal-like. Previous investigations showed that pathway-based microarray analysis could help in the identification of prognostic markers from gene expressions. For example, directed random walk (DRW) can infer a greater reproducibility power of the pathway activity between two classes of samples with a higher classification accuracy. However, most of the existing methods (including DRW) ignored the characteristics of different cancer subtypes and considered all of the pathways to contribute equally to the analysis. Therefore, an enhanced DRW (eDRW+) is proposed to identify breast cancer prognostic markers from multiclass expression data. An improved weight strategy using one-way ANOVA (F-test) and pathway selection based on the greatest reproducibility power is proposed in eDRW+. The experimental results show that the eDRW+ exceeds other methods in terms of AUC. Besides this, the eDRW+ identifies 294 gene markers and 45 pathway markers from the breast cancer datasets with better AUC. Therefore, the prognostic markers (pathway markers and gene markers) can identify drug targets and look for cancer subtypes with clinically distinct outcomes.
Preservice Biology Teachers’ Scientific Reasoning Skills and Beliefs about Nature of Science: How Do They Develop and Is There a Mutual Relationship during the Development?
Authors: Mahler Daniela , Bock Denise , Bruckermann Till
Published: September 2021

Scientific reasoning (SR) skills and nature of science (NOS) beliefs represent important characteristics of biology teachers’ professional competence. In particular, teacher education at university is formative for the professionalization of future teachers and is thus the focus of the current study. Our study aimed to examine the development of SR skills and NOS beliefs and their mutual relationship during teacher education. We applied paper-and-pencil tests to measure SR skills and NOS beliefs of 299 preservice biology teachers from 25 universities in Germany. The results of linear mixed models and planned comparisons revealed that both SR skills and NOS beliefs develop over the course of the study. Nevertheless, the development of SR skills and multiple aspects of NOS beliefs proceeds in different trajectories. Cross-lagged models showed a complex picture concerning the mutual relationship between SR skills and NOS beliefs during their development (both positive and negative). The current study contributes to the existing research because it is based on longitudinal data and allows—in contrast to cross-sectional research—conclusions about the development of SR skills and NOS beliefs.
Unsupervised Object Segmentation Based on Bi-Partitioning Image Model Integrated with Classification
Authors: Choi Hyun-Tae , Hong Byung-Woo
Published: September 2021

The development of convolutional neural networks for deep learning has significantly contributed to image classification and segmentation areas. For high performance in supervised image segmentation, we need many ground-truth data. However, high costs are required to make these data, so unsupervised manners are actively being studied. The Mumford–Shah and Chan–Vese models are well-known unsupervised image segmentation models. However, the Mumford–Shah model and the Chan–Vese model cannot separate the foreground and background of the image because they are based on pixel intensities. In this paper, we propose a weakly supervised model for image segmentation based on the segmentation models (Mumford–Shah model and Chan–Vese model) and classification. The segmentation model (i.e., Mumford–Shah model or Chan–Vese model) is to find a base image mask for classification, and the classification network uses the mask from the segmentation models. With the classifcation network, the output mask of the segmentation model changes in the direction of increasing the performance of the classification network. In addition, the mask can distinguish the foreground and background of images naturally. Our experiment shows that our segmentation model, integrated with a classifier, can segment the input image to the foreground and the background only with the image’s class label, which is the image-level label.
Modeling of Occupancy-Based Energy Consumption in a Campus Building Using Embedded Devices and IoT Technology
Authors: Soetedjo Aryuanto , Sotyohadi Sotyohadi
Published: September 2021

Since occupancy affects energy consumption, it is common to model and simulate occupancy using simulation software. One drawback of simulation software is that it cannot provide data transmission information from the sensors, which is essential for real-time energy monitoring systems. This paper proposes an approach to integrating an occupancy model and a real-time monitoring system for real-time modeling. The integration was performed by implementing a model on embedded devices and employing an IoT-based real-time monitoring application. The experimental results showed that the proposed approach effectively configured and monitored the model using a smartphone. Moreover, the data generated by the model were stored in an IoT cloud server for monitoring and further analysis. The evaluation result showed that the model ran perfectly in real-time embedded devices. The assessment of the IoT data transmission performances yielded a maximum latency of 9.0348 s, jitter of 0.9829 s, inter-arrival time of 5.5085 s, and packet loss of 10.8%, which are adequate for real-time modeling of occupancy-based energy consumption.
Holistic 1D Electro-Thermal Model Coupled to 3D Thermal Model for Hybrid Passive Cooling System Analysis in Electric Vehicles
Authors: Karimi Danial , Behi Hamidreza , Akbarzadeh Mohsen , Mierlo Joeri Van , Berecibar Maitane
Published: September 2021

Thermal management is the most vital element of electric vehicles (EV) to control the maximum temperature of module/pack for safety reasons. This paper presents a novel passive thermal management system (TMS) composed of a heat sink (HS) and phase change materials (PCM) for lithium-ion capacitor (LiC) technology under the premise that the cell is cycled with a continuous 150 A fast charge/discharge current rate. The experiments are validated against numerical analysis through a computational fluid dynamics (CFD) model. For this purpose, a comprehensive electro-thermal model based on an equivalent circuit model (ECM) is designed. The designed electro-thermal model combines the ECM model with the thermal model since the performance of the LiC cell highly depends on the temperature. Then, the robustness of the model is evaluated using a precise second-order ECM. The extracted parameters of the electro-thermal model are verified by the experimental results in which the voltage and temperature errors are less than ±5% and ±4%, respectively. Finally, the thermal performance of the HS-assisted PCM TMS is studied under the fast charge/discharge current rate. The 3D CFD results exhibit that the temperature of the LiC when using the PCM-HS as the cooling system was reduced by 38.3% (34.1 °C) compared to the natural convection case study (55.3 °C).
Numerical Analysis of GDI Flash Boiling Sprays Using Different Fuels
Authors: Payri Raul , Marti-Aldaravi Pedro , Abboud Rami , Bautista Abian
Published: September 2021

Modeling the fuel injection process in modern gasoline direct injection engines plays a principal role in characterizing the in–cylinder mixture formation and subsequent combustion process. Flash boiling, which usually occurs when the fuel is injected into an ambient pressure below the saturation pressure of the liquid, is characterized by fast breakup and evaporation rates but could lead to undesired behaviors such as spray collapse, which significantly effects the mixture preparation. Four mono–component fuels have been used in this study with the aim of achieving various flashing behaviors utilizing the Spray G injector from the Engine Combustion Network (ECN). The numerical framework was based on a Lagrangian approach and was first validated for the baseline G1 condition. The model was compared with experimental vapor and liquid penetrations, axial gas velocity, droplet sizes and spray morphology and was then extended to the flash boiling condition for iso–octane, n–heptane, n–hexane, and n–pentane. A good agreement was achieved for most of the fuels in terms of spray development and shape, although the computed spray morphology of pentane was not able to capture the spray collapse. Overall, the adopted methodology is promising and can be used for engine combustion modeling with conventional and alternative fuels.
Integration of Safety Aspects in Modeling of Superheated Steam Flash Drying of Tobacco
Authors: Adamski Robert , Siuta Dorota , Kukfisz Bożena , Frydrysiak Michał , Prochoń Mirosława
Published: September 2021

Knowledge of the drying properties of tobacco in high temperatures above 100 °C and its dust are crucial in the design of dryers, both in the optimization of the superheated-steam-drying process and in the correct selection of innovative explosion protection and mitigation systems. In this study, tobacco properties were determined and incorporated into the proposed model of an expanding superheated steam flash dryer. The results obtained from the proposed model were validated by using experimental data yielded during test runs of an industrial scale of a closed-loop expansion dryer on lamina cut tobacco. Moreover, the explosion and fire properties of tobacco dust before and after the superheated steam-drying process at 160, 170, 180, and 190 °C were experimentally investigated, using a 20 L spherical explosion chamber, a hot plate apparatus, a Hartmann tube apparatus, and a Godbert–Greenwald furnace apparatus. The results indicate that the higher the drying temperature, the more likely the ignition of the dust tobacco cloud, the faster the explosion flame propagation, and the greater the explosion severity. Tobacco dust is of weak explosion class. Dust obtained by drying with superheated steam at 190 °C is characterized by the highest value of explosion index amounting to 109 ± 14 m·bar·s−1, the highest explosion pressure rate (405 ± 32 bar/s), and the maximum explosion pressure (6.7 ± 0.3 bar). The prevention of tobacco-dust accumulation and its removal from the outer surfaces of machinery and equipment used in the superheated steam-drying process are highly desirable.
Integration of Open-Source URBANopt and Dragonfly Energy Modeling Capabilities into Practitioner Workflows for District-Scale Planning and Design
Authors: Charan Tanushree , Mackey Christopher , Irani Ali , Polly Ben , Ray Stephen , Fleming Katherine , El Kontar Rawad , Moore Nathan , Elgindy Tarek , Cutler Dylan , Roudsari Mostapha Sadeghipour , Goldwasser David
Published: September 2021

High-performance districts and communities offer opportunities for reducing energy use, emissions, and costs, and can be instrumental in helping cities achieve their climate goals. The design of such communities requires identification of opportunities early on and their re-evaluation throughout the planning process. There is a need for energy modeling tools that connect 3D Computer-Aided Design (CAD) platforms to simulation engines, enabling detailed energy analysis of districts within the workflows and tools used by practitioners. This paper introduces the Dragonfly and URBANoptTM combined toolset that supports the creation of urban models from a range of geometry formats typically used by designers and planners, and provides an integrated pathway to simulate district-scale energy systems. The toolset is piloted by a global architecture and master planning firm to evaluate several key urban-scale technical questions for the design of a district in Chicago. The findings indicate that, while energy savings can be achieved through traditional architectural studies and enhancements to individual building efficiency, the modeling toolset helps identify additional savings and insights that can be achieved when considering district-scale energy systems. Finally, this study demonstrates how the Dragonfly/URBANopt toolset can integrate with master planning workflows, thereby enabling an iterative performance-based design process.
Analysis of Spatial Distribution of Sediment Pollutants Accumulated in the Vicinity of a Small Hydropower Plant
Authors: Tomczyk Paweł , Gałka Bernard , Wiatkowski Mirosław , Buta Bogna , Gruss Łukasz
Published: September 2021

Hydropower plants affect the distribution and composition of sediments. The main aim of this study was to analyze the spatial distribution of sediment pollution in the vicinity of a small hydropower plant. The grain composition of the sediments, the content of heavy metals (Cu, Ni, Cr, Zn, Pb, and Cd) and select physicochemical properties (pH, electrolytic conductivity) were tested at 14 points upstream and downstream of the hydropower plant on the Ślęza River in Poland, as well as at reference point. The interactions between the tested parameters were also verified. The results of the conducted analysis show that hydropower plants significantly affect the composition and properties of sediments. Large amounts of sediment are deposited on damming weirs, accumulating heavy metals and other substances. The differences in the concentrations of elements were significant, and Cu, Ni, Cr, Zn and Pb were 8.74, 9.53, 3.63, 8.26 and 6.33 times higher, respectively, than the median value at points upstream of the hydropower plant than downstream. It was shown that the tested parameters of the sediments interact with each other and are correlated; heavy metals showed a synergistic effect, while other parameters configurations showed an antagonistic effect. The higher content of heavy metals upstream of the hydropower plant resulted from the presence of finer sediment—classified as silt—in this section. Downstream of the hydropower plant, there were mainly sands, which showed a lower ability to absorb substances. This work contributes to improving the rational management of the worldwide issue of sediments within dams located in river valleys. Moreover, it is in line with the 2030 Sustainable Development Goals adopted by the United Nations, particularly in the fields of clean water and sanitation, clean and available energy, and responsible consumption and production.
Deep Meaningful Learning
Authors: Mystakidis Stylianos
Published: September 2021

Deep meaningful learning is the higher-order thinking and development through manifold active intellectual engagement aiming at meaning construction through pattern recognition and concept association. It includes inquiry, critical thinking, creative thinking, problem-solving, and metacognitive skills. It is a theory with a long academic record that can accommodate the demand for excellence in teaching and learning at all levels of education. Its achievement is verified through knowledge application in authentic contexts.