bluuebunny/crossref_metadata_2025 huggingface dataset:
Caregiver Perspective on the Impact of COVID-19 on the Psychosocial and Behavioral Health of Children with ASD in the United States: A Questionnaire-Based Survey
Authors: Schwartz Dominique , Sachdev Prageet K. , Hewitson Laura
Published: July 2022

Children with Autism Spectrum Disorder (ASD) were particularly vulnerable to disruptions caused by the COVID-19 pandemic. In this study we conducted an anonymous caregiver survey to assess the impact of the COVID-19 pandemic on the psychosocial and behavioral health of children with ASD. Data from 700 responses identified several significant factors predicting greater difficulties for the child including pre-existing behavioral challenges (OR = 5.179; 95% CI: 2.696, 9.951), disrupted sleep (OR = 2.618; 95% CI 1.341, 5.112), and a diagnosis of depression (OR = 3.425; 95% CI: 1.1621, 4.116). Greater difficulties for caregivers in managing their child’s behaviors were associated with sleep disturbances (OR = 1.926; 95% CI: 1.170, 3.170), self-injurious behavior (OR = 3.587; 95% CI: 1.767, 7.281), and managing the child’s school activities (OR = 3.107; 95% CI: 1.732, 5.257) and free time (OR = 3.758; 95% CI: 2.217, 6.369). However, being under the care of a neuropsychiatrist was associated with less difficulty in managing the child’s behaviors (OR = 2.516; 95% CI: −1.046, −5.382). Finally, the presence of comorbidities (OR = 2.599; 95% CI: 1.053, 4.067) and a greater difficulty in managing the child’s school activities (OR = 2.531; 95% CI: 1.655, 3.868) and free time (OR = 1.651; 95% CI: 1.101, 2.478) were associated with an increased likelihood of caregiver desire for their child to return to in-person school in the fall. The COVID-19 pandemic had a wide-ranging impact on the behaviors of children with ASD and challenges for their caregivers.
Light Weight Authentication Scheme for Smart Home IoT Devices
Authors: Kumar Vipin , Malik Navneet , Singla Jimmy , Jhanjhi N. Z. , Amsaad Fathi , Razaque Abdul
Published: July 2022

In today’s world, the use of computer networks is everywhere, and to access the home network we use the Internet. IoT networks are the new range of these networks in which we try to connect different home appliances and try to give commands from a remote place. Access to any device over an insecure network invites various types of attacks. User authentication can be performed using some password or biometric technique. However, when it comes to authenticating a device, it becomes challenging to maintain data security over a secure network such as the Internet. Many encryptions and decryption algorithms assert confidentiality, and hash code or message authentication code MAC is used for authentication. Traditional cryptographic security methods are expensive in terms of computational resources such as memory, processing capacity, and power consumption. They are incompatible with the Internet of Things devices that have limited resources. Although automatic Device-to-Device communication enables new potential applications, the limited resources of the networks’ machines and devices impose various constraints. This paper proposes a home device authentication scheme when these are accessed from a remote place. An authentication device is used for the home network and controller device to control home appliances. Our scheme can prevent various attacks such as replay attacks, server spoofing, and man-in-the-middle attack. The proposed scheme maintains the confidentiality and authenticity of the user and devices in the network. At the same time, we check the system in a simulated environment, and the results show that the network’s performance does not degrade much in terms of delay, throughput, and energy consumed.
A Study of Song Dynasty Polychrome Statue-Making Techniques and Materials in the Sage Mother Hall of the Jinci Temple, Shanxi, China
Authors: Li Jizhang , Zha Jianrui , Pan Xiaoxuan , Zhao Tao , Li Jinfang , Guo Hong
Published: July 2022

The polychrome statues of the Sage Mother Hall at the Jinci Temple in Taiyuan city are recognized as one of the three masterpieces of the Jinci Temple. They are also regarded as an outstanding representative of ancient Chinese temple statues. These statues possess great historical, artistic, scientific, cultural and social values, and they are an important physical material for the study of ancient Chinese history, culture, religion, politics and economy, as well as science and technology. The internal structure, plaster layer samples and surface pigments of the polychrome statues of the Sage Mother Hall were analyzed by optical microscope (OM) scanning electron microscopy coupled with energy-dispersive X-ray spectrometry (SEM–EDS), X-ray powder diffraction (XRD), Raman spectroscopy (Raman), X-radiography and other analytical methods in order to gain an understanding of the production process and pigment composition of the polychrome statues of the Sage Mother Hall. According to the findings, the following steps were taken during the production of the polychrome statues that decorate the Sage Mother Hall at Jinci Temple: building a wooden skeleton, fixing the skeleton with rivets or twine, shaping the clay form with coarse clay, shaping the appearance with fine clay, refining the molded appearance, and white substrate layer painting. The majority of the pigments are inorganic mineral pigments: the red pigments include cinnabar and minium; the blue pigments include ultramarine; the green pigments include lavendulan; the yellow pigments include yellow ochre; the black pigments include carbon black; and the white pigments and substrate layers include white lead and lead sulfate. Some of the pigment layers can be seen in multiple layers, which indicates that over the history of the painted statues of the Sage Mother Hall, they have been subject to a series of repainting, with the more recent repainting time perhaps having taken place during the late Qing Dynasty and the following time period.
Evaluation of Climate Change Impacts on the Global Distribution of the Calliphorid Fly Chrysomya albiceps Using GIS
Authors: Hosni Eslam M. , Al-Khalaf Areej A. , Naguib Randa M. , Afify Abdalrahman E. , Abdalgawad Ashraf A. , Faltas Ehab M. , Hassan Mohamed A. , Mahmoud Mohamed A. , Naeem Omar M. , Hassan Yossef M. , Nasser Mohamed G.
Published: July 2022

Climate change is expected to influence the geographic distribution of many taxa, including insects. Chrysomya albiceps is one of the most pervasive calliphorid fly with apparent ecological, forensic, and medical importance. However, the global habitat suitability is varied due to climate change. Models that forecast species spatial distribution are increasingly being used in wildlife management, highlighting the need for trustworthy techniques to assess their accuracy. So, we used the maximum entropy implemented in Maxent to predict the current and future potential global geographic distribution of C. albiceps and algorithms of DIVA-GIS to confirm the predicted current model. The Maxent model was calibrated using 2177 occurrence records. Based on the Jackknife test, four bioclimatic variables along with altitude were used to develop the final models. For future models, two representative concentration pathways (RCPs), 2.6 and 8.5, for 2050 and 2070 were used. The area under curve (AUC) and true skill statistics (TSS) were used to evaluate the resulted models with values equal to 0.92 (±0.001) and 0.7, respectively. Two-dimensional niche analysis illustrated that the insect can adapt to low and high temperatures (9 °C to 27 °C), and the precipitation range was 0 mm to 2500 mm. The resulted models illustrated the global distribution of C. albiceps with alteration to its distribution in the future, especially on the Mediterranean coasts of Europe and Africa, Florida in the USA, and the coasts of Australia. Such predicted shifts put decision makers against their responsibilities to prevent destruction in economic, medical, and ecological sectors.
Habitat Suitability Assessment of Black-Necked Crane (Grus nigricollis) in the Zoige Grassland Wetland Ecological Function Zone on the Eastern Tibetan Plateau
Authors: Bai Junjun , Hou Peng , Jin Diandian , Zhai Jun , Ma Yutiao , Zhao Jiajun
Published: July 2022

Habitat suitability assessment is critical for wildlife population conservation and management planning. The MaxEnt model is widely used in species habitat suitability modeling. In order to investigate the habitat status of the black-necked crane in the Zoige grassland wetland ecological function area, this study evaluated the habitat suitability of the black-necked crane using the MaxEnt model with 152 occurrence records and 13 environmental variables. Based on the Akaike information criterion corrected for the small sample size, the best optimal parameter combination (feature class LQPHT, regularization multiplier 3.0) was selected. The results show that the Maxent model had good accuracy with an area under the curve (AUC) value of 0.895. Distance to roads, average summer precipitation, distance to lakes, and altitude are the dominant environmental variables affecting the potential distribution of black-necked cranes, with the contribution rates of 31.6%, 29.8%, 14.3%, and 8.2%, respectively. The suitable habitat area of black-necked cranes is mainly distributed in and around the Zoige Wetland National Nature Reserve, accounting for 46.49% of the Zoige Grassland Wetland National Key Ecological Function Zone. The potential distribution area has a tendency to spread to Hongyuan County in the south of the functional zone, and the unsuitable habitat is mainly distributed in the high-altitude area in the southwest of the functional zone. This study recommends focusing on the distribution area of black-necked cranes around Zoige Wetland National Nature Reserve and Hongyuan County to improve conservation strategies and strengthen protection efforts.
When Ring Sideroblasts on Bone Marrow Smears Are Inconsistent with the Diagnosis of Myelodysplastic Neoplasms
Authors: Girard Sandrine , Genevieve Franck , Rault Emmanuelle , Fenneteau Odile , Lesesve Jean-François
Published: July 2022

Ring sideroblasts are commonly seen in myelodysplastic neoplasms and are a key condition for identifying distinct entities of myelodysplastic neoplasms according to the WHO classification. However, the presence of ring sideroblasts is not exclusive to myelodysplastic neoplasms. Ring sideroblasts are as well either encountered in non-clonal secondary acquired disorders, such as exposure to toxic substances, drug/medicine, copper deficiency, zinc overload, lead poison, or hereditary sideroblastic anemias related to X-linked, autosomal, or mitochondrial mutations. This review article will discuss diseases associated with ring sideroblasts outside the context of myelodysplastic neoplasms. Knowledge of the differential diagnoses characterized by the presence of ring sideroblasts in bone marrow is essential to prevent any misdiagnosis, which leads to delayed diagnosis and subsequent management of patients that differ in the different forms of sideroblastic anemia.
Desquamative Gingivitis in the Context of Autoimmune Bullous Dermatoses and Lichen Planus—Challenges in the Diagnosis and Treatment
Authors: Sciuca Ana Maria , Toader Mihaela Paula , Stelea Carmen Gabriela , Maftei George Alexandru , Ciurcanu Oana Elena , Stefanescu Ovidiu Mihail , Onofrei Bianca-Andreea , Popa Cristina
Published: July 2022

Desquamative gingivitis (DG) is a clinical term that describes erythema, desquamation and erosions of the gingiva, of various etiologies. Although the clinical aspect is not specific for a certain disease, an accurate diagnosis of the underlying disorder is necessary because the disease course, prognosis and treatment vary according to the cause. DG may inflict significant oral discomfort, which is why patients typically present to the dentist for a first consultation, rendering it important for these specialists to be informed about this condition. Our paper aims to review the ethiopatogenesis and diagnostic approach of DG, focusing on the most common underlying disorders (autoimmune bullous dermatoses and lichen planus) and on the management of these patients. Potential etiological agents leading to an inflammatory immune response in the oral mucosa and DG appearance include genetic predisposition, metabolic, neuropsychiatric, infectious factors, medication, dental materials, graft-versus-host reaction and autoimmunity. A thorough anamnesis, a careful clinical examination, paraclinical explorations including histopathological exam and direct immunofluorescence are necessary to formulate an appropriate diagnosis. Proper and prompt management of these patients lead to a better prognosis and improved quality of life, and must include management in the dental office with sanitizing the oral cavity, instructing the patient for rigorous oral hygiene, periodic follow-up for bacterial plaque detection and removal, as well as topical and systemic therapy depending on the underlying disorder, based on treatment algorithms. A multidisciplinary approach for the diagnosis and follow-up of DG in the context of pemphigus vulgaris, bullous pemphigoid, cicatricial pemhigoid or lichen planus is necessary, including consultations with dermatologists, oral medicine specialists and dentists.
Immunological Effects of Dimethyldioctadecylammonium Bromide and Saponin as Adjuvants for Outer Membrane Vesicles from Neisseria meningitidis
Authors: Correa Victor Araujo , Portilho Amanda Izeli , De Gaspari Elizabeth
Published: July 2022

The meningococcal disease is a global health threat, but is preventable through vaccination. Adjuvants improve meningococcal vaccines and are able to trigger different aspects of the immune response. The present work evaluated the immune response of mice against Neisseria meningitidis outer membrane vesicles (OMV) complexed with the adjuvants aluminium hydroxide (AH), via subcutaneous route; and dimethyldioctadecylammonium bromide (DDA) or Saponin (Sap), via intranasal/subcutaneous routes. ELISA demonstrated that all adjuvants increased IgG titers after the booster dose, remaining elevated for 18 months. Additionally, adjuvants increased the avidity of the antibodies and the bactericidal titer: OMVs alone were bactericidal until 1:4 dilution but, when adjuvanted by Alum, DDA or Sap, it increased to 1/32. DDA and Sap increased all IgG isotypes, while AH improved IgG1 and IgG2a levels. Thus, Sap led to the recognition of more proteins in Immunoblot, followed by DDA and AH. Sap and AH induced higher IL-4 and IL-17 release, respectively. The use of adjuvants improved both cellular and humoral immune response, however, each adjuvant contributed to particular parameters. This demonstrates the importance of studying different adjuvant options and their suitability to stimulate different immune mechanisms, modulating the immune response.
Urban Air Mobility: Systematic Review of Scientific Publications and Regulations for Vertiport Design and Operations
Authors: Schweiger Karolin , Preis Lukas
Published: July 2022

Novel electric aircraft designs coupled with intense efforts from academia, government and industry led to a paradigm shift in urban transportation by introducing UAM. While UAM promises to introduce a new mode of transport, it depends on ground infrastructure to operate safely and efficiently in a highly constrained urban environment. Due to its novelty, the research of UAM ground infrastructure is widely scattered. Therefore, this paper selects, categorizes and summarizes existing literature in a systematic fashion and strives to support the harmonization process of contributions made by industry, research and regulatory authorities. Through a document term matrix approach, we identified 49 Scopus-listed scientific publications (2016–2021) addressing the topic of UAM ground infrastructure with respect to airspace operation followed by design, location and network, throughput and capacity, ground operations, cost, safety, regulation, weather and lastly noise and security. Last listed topics from cost onwards appear to be substantially under-represented, but will be influencing current developments and challenges. This manuscript further presents regulatory considerations (Europe, U.S., international) and introduces additional noteworthy scientific publications and industry contributions. Initial uncertainties in naming UAM ground infrastructure seem to be overcome; vertiport is now being predominantly used when speaking about vertical take-off and landing UAM operations.
Drones for Area-Wide Larval Source Management of Malaria Mosquitoes
Authors: Mukabana Wolfgang , Welter Guido , Ohr Pius , Tingitana Leka , Makame Makame , Ali Abdullah , Knols Bart
Published: July 2022

Given the stagnating progress in the fight against malaria, there is an urgent need for area-wide integrated vector management strategies to complement existing intra-domiciliary tools, i.e., insecticide-treated bednets and indoor residual spraying. In this study, we describe a pilot trial using drones for aerial application of Aquatain Mosquito Formulation (AMF), a monomolecular surface film with larvicidal activity, against the African malaria mosquito Anopheles arabiensis in an irrigated rice agro-ecosystem in Unguja island, Zanzibar, Tanzania. Nine rice paddies were randomly assigned to three treatments: (a) control (drone spraying with water only), (b) drone spraying with 1 mL/m2, or (c) drone spraying with 5 mL/m2 of AMF. Compared to control paddies, AMF treatments resulted in highly significant (p < 0.001) reductions in the number of larvae and pupae and >90% fewer emerging adults. The residual effect of AMF treatment lasted for a minimum of 5 weeks post-treatment, with reductions in larval densities reaching 94.7% in week 5 and 99.4% in week 4 for the 1 and 5 mL/m2 AMF treatments, respectively. These results merit a review of the WHO policy regarding larval source management (LSM), which primarily recommends its use in urban environments with ‘few, fixed, and findable’ breeding sites. Unmanned aerial vehicles (UAVs) can rapidly treat many permanent, temporary, or transient mosquito breeding sites over large areas at low cost, thereby significantly enhancing the role of LSM in contemporary malaria control and elimination efforts.
Regge Models of Proton Diffractive Dissociation Based on Factorisation and Structure Functions
Authors: Jenkovszky László , Schicker Rainer , Szanyi István
Published: July 2022

Recent results by the authors on proton diffractive dissociation (single, double and central) in the low-mass resonance region with emphasis on the LHC kinematics are reviewed and updated. Based on the previous ideas that the contribution of the inelastic proton–Pomeron vertex can be described by the proton structure function, the contribution of the inelastic Pomeron–Pomeron vertex appearing in central diffraction is now described by a Pomeron structure function.
Robust Self-Testing of Four-Qubit Symmetric States
Authors: Bao Daipengwei , Tan Xiaoqing , Xu Qingshan , Wang Haozhen , Huang Rui
Published: July 2022

Quantum verification has been highlighted as a significant challenge on the road to scalable technology, especially with the rapid development of quantum computing. To verify quantum states, self-testing is proposed as a device-independent concept, which is based only on the observed statistics. Previous studies focused on bipartite states and some multipartite states, including all symmetric states, but only in the case of three qubits. In this paper, we first give a criterion for the self-testing of a four-qubit symmetric state with a special structure and the robustness analysis based on vector norm inequalities. Then we generalize the idea to a family of parameterized four-qubit symmetric states through projections onto two subsystems.
Application of Statistical K-Means Algorithm for University Academic Evaluation
Authors: Yu Daohua , Zhou Xin , Pan Yu , Niu Zhendong , Sun Huafei
Published: July 2022

With the globalization of higher education, academic evaluation is increasingly valued by the scientific and educational circles. Although the number of published papers of academic evaluation methods is increasing, previous research mainly focused on the method of assigning different weights for various indicators, which can be subjective and limited. This paper investigates the evaluation of academic performance by using the statistical K-means (SKM) algorithm to produce clusters. The core idea is mapping the evaluation data from Euclidean space to Riemannian space in which the geometric structure can be used to obtain accurate clustering results. The method can adapt to different indicators and make full use of big data. By using the K-means algorithm based on statistical manifolds, the academic evaluation results of universities can be obtained. Furthermore, through simulation experiments on the top 20 universities of China with the traditional K-means, GMM and SKM algorithms, respectively, we analyze the advantages and disadvantages of different methods. We also test the three algorithms on a UCI ML dataset. The simulation results show the advantages of the SKM algorithm.
Science Teachers’ Pedagogical Scientific Language Knowledge—A Systematic Review
Authors: Mönch Corinna , Markic Silvija
Published: July 2022

Since students’ knowledge of scientific language can be one of the main difficulties when learning science, teachers must have adequate knowledge of scientific language as well as the teaching and learning of it. Currently, little is known about teachers’ practices and, thus, teachers’ knowledge of scientific language, in general, and the teaching and learning of it (Pedagogical Scientific Language Knowledge, PSLK) in particular. For this reason, with this systematic review, we seek to identify elements of pre- and in-service primary and secondary science teachers’ PSLK. The search was conducted on the database Education Resources Information Center (ERIC) and resulted in 35 articles with empirical evidence after the selection process. The results have been deductively and inductively categorized following the framework of the Refined Consensus Model of Pedagogical Content Knowledge, elaborating elements of different knowledge categories that shape PSLK, as well as PSLK itself (e.g., knowledge of (i) scientific language role models, (ii) making scientific terms and language explicit, (iii) providing a discursive classroom, and (iv) providing multiple representations and resources). We can conclude that more research on PSLK is needed as analyzed articles are mainly based on case studies. Additionally, this paper shows a need for a stronger focus on scientific language in teacher education programs. Implications for further research and teacher education are discussed.
How to Change Epistemological Beliefs? Effects of Scientific Controversies, Epistemological Sensitization, and Critical Thinking Instructions on Epistemological Change
Authors: Klopp Eric , Stark Robin
Published: July 2022

The present study investigates the combination of an epistemological sensitization and two different critical thinking instructions, i.e., the general and infusion approach, in the context of epistemological change induced by the presentation of resolvable scientific controversies. In a randomized study, we tested the hypothesis that the presentation of resolvable controversies generally reduces absolutism and multiplicism and increases evaluativism. We assume that these effects are strongest when the controversies are presented with an epistemological sensitization and the infusion approach. The results indicate an increase in absolutism when the general approach is employed without an epistemological sensitization. Combined with an epistemological sensitization, the increase in absolutism is only detected when the infusion approach is used. Concerning multiplicism, there is a reduction in all conditions, but the reduction is more effective without an epistemological sensitization. The general approach yields a larger increase in evaluativism without an epistemological sensitization, while the infusion approach fosters evaluativism only in combination with the sensitization. However, an argumentation task revealed that the desired level of an evaluativist argumentation only seems to emerge without an epistemological sensitization in combination with the infusion approach. In sum, the results show that there is no general way to reduce absolutism and multiplicism and increase evaluativism.
Design of Miniaturized Antipodal Vivaldi Antennas for Wideband Microwave Imaging of the Head
Authors: Parveen Farhana , Wahid Parveen
Published: July 2022

Many wideband applications, e.g., microwave imaging of the head, require low-frequency (~1–6 GHz) operation using small antennas. Vivaldi antennas are extensively used in multifarious wideband applications; however, the physical dimensions of the antenna become very large for covering low-frequency bands. Hence, the miniaturization of Vivaldi antennas, while maintaining proper matching and radiation characteristics, is essential for these applications. In this work, two miniaturized Vivaldi antennas are proposed, and several miniaturization techniques are presented for reducing the size of the antennas without the need for being immersed into any matching liquid, while maintaining desired performance. The novelty of the designs lies in the use of two half-cut superstrates, which help in achieving low-frequency operation with end-fire radiation. Two prototype antennas are fabricated, and the performances of the antennas are analyzed from both simulation and measurement results. The antennas show an FBW of 45.26% and 95.9% with a gain of ~1.9–5.2 dB and ~1.5–5.5 dB, respectively, while having a radiation efficiency above 80% within the resonant bandwidth. A comparison of the proposed antennas with several other state-of-the-art Vivaldi antennas is included to demonstrate the viability of the proposed antennas in achieving the desired performance with comparatively small dimensions.
An Efficient Real-Time FPGA-Based ORB Feature Extraction for an UHD Video Stream for Embedded Visual SLAM
Authors: Wasala Mateusz , Szolc Hubert , Kryjak Tomasz
Published: July 2022

The detection and description of feature points are important components of many computer vision systems. For example, in the field of autonomous unmanned aerial vehicles (UAV), these methods form the basis of so-called Visual Odometry (VO) and Simultaneous Localisation and Mapping (SLAM) algorithms. In this paper, we present a hardware feature points detection system able to process a 4K video stream in real-time. We use the ORB algorithm—Oriented FAST (Features from Accelerated Segment Test) and Rotated BRIEF (Binary Robust Independent Elementary Features)—to detect and describe feature points in the images. We make numerous modifications to the original ORB algorithm (among others, we use the RS-BRIEF instead of classic R-BRIEF) to adapt it to the high video resolution, make it computationally efficient, reduce the resource utilisation and achieve lower power consumption. Our hardware implementation supports a 4 ppc (pixels per clock) format (with simple adaptation to 2 ppc, 8 ppc, and more) and real-time processing of a 4K video stream (UHD—Ultra High Definition, 3840×2160 pixels) @ 60 frames per second (150 MHz clock). We verify our system using simulations in the Vivado IDE and implement it in hardware on the ZCU 104 evaluation board with the AMD Xilinx Zynq UltraScale+ MPSoC device. The proposed design consumes only 5 watts.
Convolution Neural Networks for the Automatic Segmentation of 18F-FDG PET Brain as an Aid to Alzheimer’s Disease Diagnosis
Authors: Pasini Elena , Genovesi Dario , Rossi Carlo , De Santi Lisa Anita , Positano Vincenzo , Giorgetti Assuero , Santarelli Maria Filomena
Published: July 2022

Our work aims to exploit deep learning (DL) models to automatically segment diagnostic regions involved in Alzheimer’s disease (AD) in 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) volumetric scans in order to provide a more objective diagnosis of this disease and to reduce the variability induced by manual segmentation. The dataset used in this study consists of 102 volumes (40 controls, 39 with established Alzheimer’s disease (AD), and 23 with established mild cognitive impairment (MCI)). The ground truth was generated by an expert user who identified six regions in original scans, including temporal lobes, parietal lobes, and frontal lobes. The implemented architectures are the U-Net3D and V-Net networks, which were appropriately adapted to our data to optimize performance. All trained segmentation networks were tested on 22 subjects using the Dice similarity coefficient (DSC) and other similarity indices, namely the overlapping area coefficient (AOC) and the extra area coefficient (EAC), to evaluate automatic segmentation. The results of each labeled brain region demonstrate an improvement of 50%, with DSC from about 0.50 for V-Net-based networks to about 0.77 for U-Net3D-based networks. The best performance was achieved by using U-Net3D, with DSC on average equal to 0.76 for frontal lobes, 0.75 for parietal lobes, and 0.76 for temporal lobes. U-Net3D is very promising and is able to segment each region and each class of subjects without being influenced by the presence of hypometabolic regions.
Improved Performance and Bias Stability of Al2O3/IZO Thin-Film Transistors with Vertical Diffusion
Authors: Lee Se-Hyeong , Bak So-Young , Yi Moonsuk
Published: July 2022

Several studies on amorphous oxide semiconductor thin-film transistors (TFTs) applicable to next-generation display devices have been conducted. To improve the poor switching characteristics and gate bias stability of co-sputtered aluminum–indium–zinc oxide (AIZO) TFTs, we fabricate Al2O3/indium–zinc oxide (IZO) dual-active-layer TFTs. By varying the Al2O3 target power and oxygen partial pressure in the chamber during Al2O3 back-channel deposition, we optimize the electrical characteristics and gate bias stability of the Al2O3/IZO TFTs. The Al2O3/IZO TFTs, which are fabricated under 50 W Al2O3 target power and 13% oxygen partial pressure conditions, exhibit a high electron mobility of 23.34 cm2/V·s, a low threshold voltage of 0.96 V, an improved on–off current ratio of 6.8 × 107, and a subthreshold swing of 0.61 V/dec. Moreover, by increasing the oxygen partial pressure in the chamber, the positive and negative bias stress values improve to +0.32 V and −2.08 V, respectively. X-ray photoelectron spectroscopy is performed to reveal the cause of these improvements.
A Robust Bayesian Optimization Framework for Microwave Circuit Design under Uncertainty
Authors: De Witte Duygu , Qing Jixiang , Couckuyt Ivo , Dhaene Tom , Vande Ginste Dries , Spina Domenico
Published: July 2022

In modern electronics, there are many inevitable uncertainties and variations of design parameters that have a profound effect on the performance of a device. These are, among others, induced by manufacturing tolerances, assembling inaccuracies, material diversities, machining errors, etc. This prompts wide interests in enhanced optimization algorithms that take the effect of these uncertainty sources into account and that are able to find robust designs, i.e., designs that are insensitive to the uncertainties early in the design cycle. In this work, a novel machine learning-based optimization framework that accounts for uncertainty of the design parameters is presented. This is achieved by using a modified version of the expected improvement criterion. Moreover, a data-efficient Bayesian Optimization framework is leveraged to limit the number of simulations required to find a robust design solution. Two suitable application examples validate that the robustness is significantly improved compared to standard design methods.
Adaptive Fuzzy Control for Flexible Robotic Manipulator with a Fixed Sampled Period
Authors: Zhang Jiaming , Dai Xisheng
Published: July 2022

In this paper, a backstepping sampled data control method is developed for a flexible robotic manipulator whose internal dynamic is completely unknown. To address the internal uncertainties, the fuzzy logical system (FLS) is considered. Moreover, considering the limited network bandwidth, the designed controller and adaptive laws only contain the sampled data with a fixed sampled period. By invoking the Lyapunov stability theory, all signals of the flexible robotic manipulator are semi-global uniformly ultimately bounded (SGUUB). Ultimately, an application to a flexible robotic manipulator is given to verify the validity of the sampled data controller.
CTF-PARCS Core Multi-Physics Computational Framework for Efficient LWR Steady-State, Depletion and Transient Uncertainty Quantification
Authors: Delipei Gregory K. , Rouxelin Pascal , Abarca Agustin , Hou Jason , Avramova Maria , Ivanov Kostadin
Published: July 2022

Best Estimate Plus Uncertainty (BEPU) approaches for nuclear reactor applications have been extensively developed in recent years. The challenge for BEPU approaches is to achieve multi-physics modeling with an acceptable computational cost while preserving a reasonable fidelity of the physics modeled. In this work, we present the core multi-physics computational framework developed for the efficient computation of uncertainties in Light Water Reactor (LWR) simulations. The subchannel thermal-hydraulic code CTF and the nodal expansion neutronic code PARCS are coupled for the multi-physics modeling (CTF-PARCS). The computational framework is discussed in detail from the Polaris lattice calculations up to the CTF-PARCS coupling approaches. Sampler is used to perturb the multi-group microscopic cross-sections, fission yields and manufacturing parameters, while Dakota is used to sample the CTF input parameters and the boundary conditions. Python scripts were developed to automatize and modularize both pre- and post-processing. The current state of the framework allows the consistent perturbation of inputs across neutronics and thermal-hydraulics modeling. Improvements to the standard thermal-hydraulics modeling for such coupling approaches have been implemented in CTF to allow the usage of 3D burnup distribution, calculation of the radial power and the burnup profile, and the usage of Santamarina effective Doppler temperature. The uncertainty quantification approach allows the treatment of both scalar and functional quantities and can estimate correlation between the multi-physics outputs of interest and up to the originally perturbed microscopic cross-sections and yields. The computational framework is applied to three exercises of the LWR Uncertainty Analysis in Modeling Phase III benchmark. The exercises cover steady-state, depletion and transient calculations. The results show that the maximum fuel centerline temperature across all exercises is 2474K with 1.7% uncertainty and that the most correlated inputs are the 238U inelastic and elastic cross-sections above 1 MeV.
Investigating Drillstring Vibration and Stability in Coring Drilling
Authors: Sun Yuchen , Liu Yongsheng , Qin Xing , Dou Zijun , Feng Zibo , Yang Gansheng
Published: July 2022

Transverse vibration of drillpipe in coring drilling is undesirable. Here, the influence of the core on drillpipe vibration is considered for the first time. Attention is focused on the vibrations of the coring drillpipe as these vibrations lead to contact and collision between drillpipe and core. A reduced-order model of drill string motion is established considering fluid load and core constraints. This model considers fluid action as distributed load and drillpipe as beam structure. The constraint of the core on lateral vibration of the drillpipe is simplified as a nonlinear force. The method of multiple scales is used to analyze the disturbance of the drillpipe’s primary resonance and harmonic resonance, and the influence law of different parameters on the drillpipe resonance is obtained. The results show that damping inhibits resonance vibration, and external excitation determines the resonance type. The existence of the core will aggravate the resonance vibration of the drillpipe. The analysis results are helpful in understanding the resonance of the drillpipe in coring drilling. Some measures to suppress resonance are given in this paper. This study can provide guidance for further research on drillpipe resonance in core drilling.
Dynamic Response Analysis of a Novel Anti-Impact Pressure Balance Jack
Authors: Wan Lirong , Yu Xuehui , Ma Dejian , Meng Zhaosheng , Zeng Qingliang , Qi Guoqing
Published: July 2022

Coal resources perform an important role in China’s energy structure. Hydraulic support is the main supporting equipment of fully mechanized mining face in coal mines. Because the hydraulic support frequently bears the impact pressure from the working face, it is very easy to cause failure of the balance jack. In order to solve the problem that the balance jack easily damaged by impact and improve the impact resistance of the hydraulic support, an improved fast response balance jack with multiple adaptive buffers was proposed in this paper. The energy dissipation characteristics of the balance jack were analyzed by establishing the mathematical model of the multiple buffering process of it. Based on ADAMS, the dynamic simulation model of the hydraulic support was constructed, and the mechanical response characteristics of the proposed balance jack and the traditional balance jack under different impact loads were compared and analyzed. By changing the equivalent stiffness of the novel balance jack system, the influence of different initial inflation pressure and length of the buffer cavity on the dynamic performance of the novel balance jack was discussed. The results show that compared with the traditional balance jack, the multi-adaptive response balance jack proposed in this paper can reduce the peak force of the hinge point by about 24.6% and the fluctuation frequency was also significantly reduced under the ultimate load condition at the front end of the top beam, which has better impact resistance. When the initial inflation pressure of the buffer cavity is 40~45 MPa and the initial length is less than 105 mm, a better buffer effect can be achieved. This study provides a new solution to solve the failure problem of the balance jack under the underground impact pressure and improve the safety and reliability of hydraulic support.
Energy Flow Modelling Method of Energy Efficiency Improvement for Power-Using Electromechanical Products
Authors: Wang Xiang , Xiang Dong
Published: July 2022

As a crucial factor in the improvement of energy efficiency for power-using electromechanical products, the flow, conversion and distribution of energy are closely related to design variables of products. Simultaneously, performance is the constraint of energy efficiency and is strongly affected by design variables. In order to improve a product’s energy efficiency without compromising performance, an energy flow model with a basic energy flow element (EFE) was built on a functional basis and its modelling procedure is presented in this paper. Containing function, design variable and characteristic energy in EFEs, as well as the interface parameters between EFEs and environment, the model contributes to logically clarifying the relationship between design variables and performance. With the refrigerator as an example, the effectiveness of the energy flow model is verified by a comparison between simulation, based on an energy flow model, and experimentation. Furthermore, five critical design variables of a 265 L refrigerator were screened with the model. Test results of the improved prototype meet the requirements of operating rate and temperature uniformity, and the daily electricity consumption was reduced by about 9%. Comparison between the design results of the energy flow model and the testing results of the prototype demonstrates that the energy efficiency improvement method based on energy flow model is effective.
ADRC-Based Habituating Control of Double-Heater Heat Source
Authors: Nowak Pawel , Fratczak Michal , Grelewicz Patryk , Czeczot Jacek
Published: July 2022

This paper deals with the proposition of improvement in the performance of a heat source by modification of its structure and by deriving a dedicated control system. Traditional heat sources consist of a single heater of high nominal power, but slow dynamics, that is regulated by a single closed loop control system. In this paper, an existing heater serially-connected with a supplemental heater with low nominal power but fast dynamics is proposed. A dedicated control system was derived with two active disturbance rejection controllers (ADRC) implemented in the habituating control structure. The proposed solution was validated using a virtual commissioning procedure where the heating system was simulated in the SIEMENS® Simit v10.3 industrial software, and ADRC controllers were implemented in SIEMENS® PLCSIM Advanced using dedicated library function blocks. The results showed the superiority of the proposed approach in comparison with the traditional single closed loop solution. The proposed dedicated habituating control system provided better robustness to the changes in dynamics of a heat source and to the measurement noise. At the same time, it will ensure lower (or in some cases comparable) values of popular closed loop performance indices.
A Computational Method of Rotating Stall and Surge Transients in Axial Compressor
Authors: Ji Jiajia , Hu Jun , Ma Shuai , Xu Rong
Published: July 2022

The onset of rotating stall and surge in compressors limits the operating range of aero-engines. Accurately predicting the key features during these events is critical in the engine design process. In this paper, a three-dimensional computational model for transient simulation of multi-stage axial compressors during stall is proposed. The kinetic equations describing the dynamic process of the compression system are constructed, with a 3D through-flow model for the compression part and a 1D gas collector model for the outlet part. The calculation of the source term is performed using the developed body-force model, which realizes the correlation between the deviation angle and the loss coefficient with the inlet parameters in various flow regions. Validated on a single-stage compressor and a single-rotor fan, the results show that the method is capable of capturing the stall and surge features correctly and that the three-dimensional structure of the stall cell can be captured. In addition, this model could be used for the analysis of the surge load, which is significant for the structural integrity of the compressor.
Comparative Analysis of Renewable Energy Community Designs for District Heating Networks: Case Study of Corticella (Italy)
Authors: Ancona Maria Alessandra , Baldi Francesco , Branchini Lisa , De Pascale Andrea , Gianaroli Federico , Melino Francesco , Ricci Mattia
Published: July 2022

In recent years, a rapid increase in the adoption of renewable energy sources and in the transition from a centralized electricity generation system to an increasingly distributed one has occurred. Within this scenario, in line with the European directives for achieving the objectives in the field of energy transition and climate change, energy communities are seen as potential contributors. The purpose of this work is to analyze the application potential of the energy community concept associated with district heating networks, leading to better overall energy-economic performance. This was demonstrated for a specific energy community in Italy, and it can be achieved by maximizing internal energy sharing—resulting from the electricity surplus generated by the photovoltaic system—and adopting different strategies that include heat pumps in order to maximize self-consumption and self-sufficiency, as well as to evaluate the most efficient investment in economic terms by exploiting the incentive tariff on shared energy. The results show that the performance of the system can be improved with the proposed design, achieving a significant reduction in the system’s energy demand, emissions and costs: compared to the reference case, the use of photovoltaics reduces primary energy demand by approximately 11%, while the addition of the energy community configuration allows emissions to be reduced by nearly 12%, with no additional investment.
Study on the Coupling Effect of Heat Transfer and Refrigerant Distribution in the Flat Tube of a Microchannel Evaporator
Authors: Hu Wenju , Zhang Xin
Published: July 2022

Refrigerant maldistribution severely deteriorates the heat transfer performance of a microchannel evaporator. Compared with the refrigerant distribution among flat tubes along the header, refrigerant distribution among microchannels in the flat tube in the airflow direction has barely been paid attention. In this paper, a heat transfer mathematical model of a microchannel evaporator’s flat tube composed of vertically placed parallel microchannels in the airflow direction was developed. The Refrigerant distribution among the microchannels was evaluated and its influence on heat transfer between air and refrigerant was analyzed. The results showed that the refrigerant distribution and heat transfer performance between air and refrigerant were interrelated and interacted with each other. The temperature of the air leaving the microchannel evaporator changed along the microchannel because of uneven refrigerant distribution among the microchannels, and the air temperature difference between air leaving out of the bottom and the top of the evaporator was approximately 2.13 °C. Ignoring the heat transfer from adjacent microchannels will lead to a small heat transfer deviation for the flat tube; thus, heat transfer among microchannels can be neglected.
Multicriteria Decision Aiding for Planning Renewable Power Production at Moroccan Airports
Authors: Menou Abdellah , Lahdelma Risto , Salminen Pekka
Published: July 2022

This study is about multicriteria decision aiding (MCDA) for the green airports program of the Moroccan Airport Authority ONDA. The goal of the program is to develop significant amounts of renewable power at airports. In particular, ONDA wants to select airports at which large solar and wind power parks should be built. Multiple criteria, including economy, technical feasibility, and environmental concerns, must be considered simultaneously. In this study, we apply Stochastic Multicriteria Acceptability Analysis (SMAA) for ranking the candidates to be developed into green airports. The analysis is conducted in phases with different sets of criteria. This study is the first application of MCDA for developing large-scale renewable energy production at airports. As a theoretical novelty, the pairwise winning indices of SMAA are used to form stochastic partial and complete rankings of the alternatives. Based on the results, two alternatives obtain the best and second-best rank in every model, and one alternative is always last, while the ranks of the remaining alternatives vary depending on the set of criteria.