bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and Implementation of Fast Locking All-Digital Duty Cycle Corrector Circuit with Wide Range Input Frequency
Authors: Kao Shao-Ku
Published: January 2021

This paper presents a fast locking and wide range input frequency all-digital duty cycle corrector (ADDCC). The proposed ADDCC circuit comprises a pulse generator and a clock generator. The pulse generator is edge-triggered by an input signal to produce a 0 degree and 180 degree phase. The clock generator uses a 0 degree and 180 degree phase to produce the 50% duty cycle output signal. It corrects the duty cycle of the input signal in six clock cycles. The proposed ADDCC is implemented in a 0.35 µm CMOS process. The circuit can operate from 10 MHz to 100 MHz, and accommodates a wide range of input duty cycles ranging from 30% to 70%. The duty-cycle error of the output signal is less than ±1%.
Layer-Wise Network Compression Using Gaussian Mixture Model
Authors: Lee Eunho , Hwang Youngbae
Published: January 2021

Due to the large number of parameters and heavy computation, the real-time operation of deep learning in low-performance embedded board is still difficult. Network Pruning is one of effective methods to reduce the number of parameters without additional network structure modification. However, the conventional method prunes redundant parameters up to the same rate for all layers. It may cause a bottleneck problem, which leads to the performance degradation, because the minimum number of optimal parameters is different according to the each layer. We propose a layer adaptive pruning method based on the modeling of weight distribution. We can measure the amount of weights close to zero accurately by applying Gaussian Mixture Model (GMM). Until the target compression rate is reached, the layer selection and pruning are iteratively performed. The layer selection in each iteration considers the timing to reach the target compression rate and the degree of weight pruning. We apply the proposed network compression method for image classification and semantic segmentation to show the effectiveness of the proposed method. In the experiments, the proposed method shows higher compression rate during maintaining the accuracy compared with previous methods.
A Hybrid Optimization Approach for the Enhancement of Efficiency of a Piezoelectric Energy Harvesting System
Authors: Sarker Mahidur R. , Mohamed Ramizi , Saad Mohamad Hanif Md , Tahir Muhammad , Hussain Aini , Mohamed Azah
Published: January 2021

This paper presents a hybrid optimization approach for the enhancement of performance of a piezoelectric energy harvesting system (PEHS). The existing PEHS shows substantial power loss during hardware implementation. To overcome the problem, this study proposes a hybrid optimization technique to improve the PEHS efficiency. In addition, the converter design as well as controller technique are enhanced and simulated in a MATLAB/Simulink platform. The controller technique of the proposed structure is connected to the converter prototype through the dSPACE DS1104 board (dSPACE, Paderborn, Germany). To enhance the proportional-integral voltage controller (PIVC) based on hybrid optimization method, a massive enhancement in reducing the output error is done in terms of power efficiency, power loss, rising time and settling time. The results show that the overall PEHS converter efficiency is about 85% based on the simulation and experimental implementations.
Design and Implementation of LoRa Based IoT Scheme for Indonesian Rural Area
Authors: Prakosa Setya Widyawan , Faisal Muhamad , Adhitya Yudhi , Leu Jenq-Shiou , Köppen Mario , Avian Cries
Published: January 2021

The development of the Internet of Things (IoT) in electronics, computer, robotics, and internet technology is inevitable and has rapidly accelerated more than before as the IoT paradigm is a promising solution in terms of solving real world problems, especially for digitizing and monitoring in real time. Various IoT schemes have successfully been applied to some areas such as smart health and smart agriculture. Since the agriculture areas are getting narrow, the development of IoT in agriculture should be prioritized to enhance crop production. This paper proposes the IoT scheme for long range communication based on Long Range (LoRa) modules applied to smart agriculture. The scheme utilizes the low power modules and long-distance communication for monitoring temperature, humidity, soil moisture, and pH soil. Our IoT design has successfully been applied to agriculture areas which have unstable network connections. The design is analyzed to obtain the maximum coverage using different spreading factors and bandwidths. We show that as the spreading factor increases to 12, the maximum coverage can be transmitted to 1000 m. However, the large coverage also comes with the disadvantages of the increased delays.
LSTM Networks for Overcoming the Challenges Associated with Photovoltaic Module Maintenance in Smart Cities
Authors: Vicente-Gabriel Jorge , Gil-González Ana-Belén , Luis-Reboredo Ana , Chamoso Pablo , Corchado Juan M.
Published: January 2021

Predictive maintenance is a field of research that has emerged from the need to improve the systems in place. This research focuses on controlling the degradation of photovoltaic (PV) modules in outdoor solar panels, which are exposed to a variety of climatic loads. Improved reliability, operation, and performance can be achieved through monitoring. In this study, a system capable of predicting the output power of a solar module was implemented. It monitors different parameters and uses automatic learning techniques for prediction. Its use improved reliability, operation, and performance. On the other hand, automatic learning algorithms were evaluated with different metrics in order to optimize and find the best configuration that provides an optimal solution to the problem. With the aim of increasing the share of renewable energy penetration, an architectural proposal based on Edge Computing was included to implement the proposed model into a system. The proposed model is designated for outdoor predictions and offers many advantages, such as monitoring of individual panels, optimization of system response, and speed of communication with the Cloud. The final objective of the work was to contribute to the smart Energy system concept, providing solutions for planning the entire energy system together with the identification of suitable energy infrastructure designs and operational strategies.
An Accuracy Improvement Method Based on Multi-Source Information Fusion and Deep Learning for TSSC and Water Content Nondestructive Detection in “Luogang” Orange
Authors: Xu Sai , Lu Huazhong , Ference Christopher , Zhang Qianqian
Published: January 2021

The objective of this study was to find an efficient method for measuring the total soluble solid content (TSSC) and water content of “Luogang” orange. Quick, accurate, and nondestructive detection tools (VIS/NIR spectroscopy, NIR spectroscopy, machine vision, and electronic nose), four data processing methods (Savitzky–Golay (SG), genetic algorithm (GA), multi-source information fusion (MIF), convolutional neural network (CNN) as the deep learning method, and a partial least squares regression (PLSR) modeling method) were compared and investigated. The results showed that the optimal TSSC detection method was based on VIS/NIR and machine vision data fusion and processing and modeling by SG + GA + CNN + PLSR. The R2 and RMSE of the TSSC detection results were 0.8580 and 0.4276, respectively. The optimal water content detection result was based on VIS/NIR data and processing and modeling by SG + GA + CNN + PLSR. The R2 and RMSE of the water content detection results were 0.7013 and 0.0063, respectively. This optimized method largely improved the internal quality detection accuracy of “Luogang” orange when compared to the data from a single detection tool with traditional data processing method, and provides a reference for the accuracy improvement of internal quality detection of other fruits.
Adaptive View Sampling for Efficient Synthesis of 3D View Using Calibrated Array Cameras
Authors: Kim Geonwoo , Lee Deokwoo
Published: January 2021

Recovery of three-dimensional (3D) coordinates using a set of images with texture mapping to generate a 3D mesh has been of great interest in computer graphics and 3D imaging applications. This work aims to propose an approach to adaptive view selection (AVS) that determines the optimal number of images to generate the synthesis result using the 3D mesh and textures in terms of computational complexity and image quality (peak signal-to-noise ratio (PSNR)). All 25 images were acquired by a set of cameras in a 5×5 array structure, and rectification had already been performed. To generate the mesh, depth map extraction was carried out by calculating the disparity between the matched feature points. Synthesis was performed by fully exploiting the content included in the images followed by texture mapping. Both the 2D colored images and grey-scale depth images were synthesized based on the geometric relationship between the images, and to this end, three-dimensional synthesis was performed with a smaller number of images, which was less than 25. This work determines the optimal number of images that sufficiently provides a reliable 3D extended view by generating a mesh and image textures. The optimal number of images contributes to an efficient system for 3D view generation that reduces the computational complexity while preserving the quality of the result in terms of the PSNR. To substantiate the proposed approach, experimental results are provided.
Smaller and Isolated Grassland Fragments Are Exposed to Stronger Seed and Insect Predation in Habitat Edges
Authors: Kuli-Révész Kitti , Korányi Dávid , Lakatos Tamás , Szabó Ágota Réka , Batáry Péter , Gallé Róbert
Published: January 2021

Habitat fragmentation threatens terrestrial arthropod biodiversity, and thereby also leads to alterations of ecosystem functioning and stability. Predation on insects and seeds by arthropods are two very important ecological functions because of their community-structuring effects. We addressed the effect of fragment connectivity, fragment size, and edge effect on insect and seed predation of arthropods. We studied 60 natural fragments of two grassland ecosystems in the same region (Hungarian Great Plain), 30 forest-steppes, and 30 burial mounds (kurgans). The size of fragments were in the range of 0.16–6.88 ha for forest-steppe and 0.01–0.44 ha for kurgan. We used 2400 sentinel arthropod preys (dummy caterpillars) and 4800 seeds in trays for the measurements. Attack marks on dummy caterpillars were used for predator identification and calculation of insect predation rates. In the case of seeds, predation rates were calculated as the number of missing or damaged seeds per total number of exposed seeds. Increasing connectivity played a role only in generally small kurgans, with a negative effect on insect and seed predation rates in the edges. In contrast, fragment size moderated edge effects on insect and seed predation rates in generally large forest-steppes. The difference between edges and centres was more pronounced in small than in large fragments. Our study emphasizes the important role of landscape and fragment-scale factors interacting with edge effect in shaping ecosystem functions in natural grassland fragments of modified landscapes. Managing functional landscapes to optimize the assessment of ecosystem functions and services needs a multispatial scale approach.
Source Criticism as a Technology of Government in the Swedish Psychological Defence: The Impact of Humanistic Knowledge on Contemporary Security Policy
Authors: Bertilsson Fredrik
Published: January 2021

“Source criticism” (källkritik) has become an essential part of the Swedish government’s activities against false information, deception campaigns, and propaganda, which are viewed as fundamentally destabilising forces that can potentially undermine the democratic system, the public debate, and political decision-making. The purpose of this article is to explore source criticism as a technology of government focusing on the Swedish Psychological Defence. I analyse the way in which source criticism is brought to bear on Swedish national security policy in the light of Foucauldian theories about modern governmentality and technologies of the self. Source criticism is seen as an example of a contemporary form of government that entails a redistribution of responsibility from the state to the individual, who is provided with certain “technologies of self” to master an unpredictable political environment. With this case study as empirical example, the aim of the article is to contribute to the research on the influence of humanistic knowledge in security and defence policy domains. This prompts further discussion about what happens with the democratic and critical potential of humanistic knowledge as it is enrolled in government operations.
Impact of Body Mass Index on the Development of Inflammatory Bowel Disease: A Systematic Review and Dose-Response Analysis of 15.6 Million Participants
Authors: Bhagavathula Akshaya Srikanth , Clark Cain C.T. , Rahmani Jamal , Chattu Vijay Kumar
Published: January 2021

Background: A growing trove of literature describes the effect of malnutrition and underweight on the incidence of inflammatory bowel disease (IBD). However, evidence regarding the association between underweight or obesity and IBD is limited. The study aimed to assess the association of body mass index (BMI) with a risk of IBD (Crohn’s disease (CD) and ulcerative colitis (U.C.)) incidence. Methods: We systematically searched PubMed/Medline, Cochrane, Web of Science, and Scopus for observational studies assessing the association between BMI and IBD that were published up to 30 June 2020. We estimated pooled hazard ratios (HR) with corresponding 95% confidence intervals (CI). Random effect dose-response meta-analysis was performed using the variance weighted least-squares regression (VWLS) models to identify non-linear associations. Results: A total of ten studies involving 15.6 million individuals and 23,371 cases of IBD were included. Overall, obesity was associated with an increased IBD risk (HR: 1.20, 95% CI: 1.08–1.34, I2 = 0%). Compared to normal weight, underweight (BMI < 18.5 kg/m2) and obesity (BMI ≥ 30 kg/m2) were associated with a higher risk of CD, and there was no difference in the risk of U.C. among those with BMI < 18.5 kg/m2 and BMI ≥ 30 kg/m2. There was a significant non-linear association between being underweight and obesity and the risk of development of CD (Coef1 = −0.0902, p1 < 0.001 Coef2 = 0.0713, p2 < 0.001). Conclusions: Obesity increases the risk of IBD development. Underweight and obesity are independently associated with an increased risk of CD, yet there is no evident association between BMI and the risk of U.C. Further studies are needed to clarify the underlying mechanism for these findings, particularly in CD.
Modeling the Dynamics of Drug Spreading in China
Authors: Tang Haoxiang , Li Mingtao , Yan Xiangyu , Lu Zuhong , Jia Zhongwei
Published: January 2021

Drug abuse remains one of the major public health issues at the global level. In this article, we propose a drug epidemic model with a complete addiction–rehabilitation–recovery process, which allows the initiation of new users under the influence of drug addicts undergoing treatment and hidden drug addicts. We first conduct qualitative analyses of the dynamical behaviors of the model, including the existence and positivity of the solutions, the basic reproduction number, global asymptotic stabilities of both the drug-free and the drug-persistent equilibria, as well as sensitivity analysis. Then we use the model to predict the drug epidemic in China during 2020–2030. Finally, we numerically simulate the potential impact of intervention strategies on different drug users. The results show that the drug epidemic will decrease significantly during 2020−2030, and the most effective intervention strategy to eliminate drug epidemics is to strengthen the investigation and rehabilitation admission of hidden drug users.
Spatiotemporal Distribution of Zika Virus and Its Spatially Heterogeneous Relationship with the Environment
Authors: Li Jie , Jia Kun , Liu Yanxu , Yuan Bo , Xia Mu , Zhao Wenwu
Published: January 2021

Infectious diseases have caused some of the most feared plagues and greatly harmed human health. However, despite the qualitative understanding that the occurrence and diffusion of infectious disease is related to the environment, the quantitative relations are unknown for many diseases. Zika virus (ZIKV) is a mosquito-borne virus that poses a fatal threat and has spread explosively throughout the world, impacting human health. From a geographical perspective, this study aims to understand the global hotspots of ZIKV as well as the spatially heterogeneous relationship between ZIKV and environmental factors using exploratory special data analysis (ESDA) model. A geographically weighted regression (GWR) model was used to analyze the influence of the dominant environmental factors on the spread of ZIKV at the continental scale. The results indicated that ZIKV transmission had obvious regional and seasonal heterogeneity. Population density, GDP per capita, and landscape fragmentation were the dominant environmental factors affecting the spread of ZIKV, which indicates that social factors had a greater influence than natural factors on the spread of it. As SARS-CoV-2 is spreading globally, this study can provide methodological reference for fighting against the pandemic.
A Network Analysis of Research Topics and Trends in End-of-Life Care and Nursing
Authors: Kim Kisook , Jang Seung Gyeong , Lee Ki-Seong
Published: January 2021

This study identified the trends in end-of-life care and nursing through text network analysis. About 18,935 articles published until September 2019 were selected through searches on PubMed, Embase, Cochrane, Web of Science, and Cumulative Index to Nursing and Allied Health Literature. For topic modeling, Latent Dirichlet Allocation (K = 8) was applied. Most of the top ranked topic words for the degree and betweenness centralities were consistent with the top 1% through the semantic network diagram. Among the important keywords examined every five years, “care” was unrivaled. When analyzing the two- and three-word combinations, there were many themes representing places, roles, and actions. As a result of performing topic modeling, eight topics were derived as ethical issues of decision-making for treatment withdrawal, symptom management to improve the quality of life, development of end-of-life knowledge education programs, life-sustaining care plan for elderly patients, home-based hospice, communication experience, patient symptom investigation, and an analysis of considering patient preferences. This study is meaningful as it analyzed a large amount of existing literature and considered the main trends of end-of-life care and nursing research based on the core subject control and semantic structure.
Research and Implementation of Scheduling Strategy in Kubernetes for Computer Science Laboratory in Universities
Authors: Wang Zhe , Liu Hao , Han Laipeng , Huang Lan , Wang Kangping
Published: January 2021

How to design efficient scheduling strategy for different environments is a hot topic in cloud computing. In the private cloud of computer science labs in universities, there are several kinds of tasks with different resource requirements, constraints, and lifecycles such as IT infrastructure tasks, course design tasks submitted by undergraduate students, deep learning tasks and and so forth. Taking the actual needs of our laboratory as an instance, these tasks are analyzed, and scheduled respectively by different scheduling strategies. The Batch Scheduler is designed to process tasks in rush time to improve system throughput. Dynamic scheduling algorithm is proposed to tackle long-term lifecycle tasks such as deep learning tasks which are hungry for GPU resources and have dynamically changing priorities. Experiments show that the scheduling strategies proposed in this paper improve resource utilization and efficiency.
Is Orius sauteri Poppius a Promising Biological Control Agent for Walnut Aphids? An Assessment from the Laboratory to Field
Authors: Wang Ting , Zhang Ping , Ma Chenyang , Yasir Ali Muhammad , Gao Guizhen , Lu Zhaozhi , Zalucki Myron P.
Published: January 2021

Walnut aphids are major pests of walnut production with few commercially available natural enemies. We conducted laboratory and field experiments to evaluate the potential of Orius sauteri Poppius (Anthocoridae), a predatory bug, as a biological control agent against two walnut aphid species: the dusky-veined aphid (Panaphis juglandis Goeze) and the walnut aphid (Chromaphis juglandicola Kaltenbach). Both species co-occur on walnut trees; P. juglandis is distributed on the upper surface (adaxial) of leaves while C. juglandicola is found on the lower surface (abaxial) of leaves. Based on functional response experiments, O sauteri had a strong capacity for consuming both aphid species. Biocontrol efficacy of O. sauteri for each species in the laboratory and field experiments was high, 77% for P. juglandis and 80% for C. juglandicola, regardless if one or two predators being present. However, biocontrol efficacy declined 15–25% for C. juglandicola and 20–50% for P. juglandis when both aphid species were present on the same leaf. The efficacy of O. sauteri under (semi)-field conditions gave similar findings based on the percentage reduction of aphids and change in population growth rates of aphids. The reduced biocontrol efficacy of the predatory bug against mixed species populations of aphids can be explained by competition between the aphid species and differences in their preferred location on leaves. Our experiments showed that O. sauteri is a promising biocontrol agent, but biocontrol efficacy may decline when both aphid species are present on walnut trees. This should be considered in the commercial release of O. sauteri in walnut orchards to promote economic and environmental benefits of walnuts production.
Bark and Wood Boring Insects—Past, Present, and the Future Knowledge We Need
Authors: Avtzis Dimitrios N. , Lakatos Ferenc
Published: January 2021

Bark and wood-boring insects represent a very diverse group of insects that includes bark and ambrosia beetles, cerambycids, weevils, jewel beetles, or even anobiids from the order of beetles (Coleoptera), but in the broader sense other insect orders like Lepidoptera (e [...]
Recent Advances in Laparoscopy
Authors: Alkatout Ibrahim , Biebl Matthias
Published: January 2021

At the end of 2019, we received reports of abnormally high rates of severe pneumonia and mortality in a city named Wuhan in the province of Hubei in China [...]
Predictors and Prognostic Implications of Cardiac Arrhythmias in Patients Hospitalized for COVID-19
Authors: Zylla Maura M. , Merle Uta , Vey Johannes A. , Korosoglou Grigorios , Hofmann Eva , Müller Michael , Herth Felix , Schmidt Werner , Blessing Erwin , Göggelmann Christoph , Weidner Norbert , Fiedler Mascha O. , Weigand Markus A. , Kälble Florian , Morath Christian , Leiner Johannes , Kieser Meinhard , Katus Hugo A. , Thomas Dierk
Published: January 2021

Background: Cardiac manifestation of COVID-19 has been reported during the COVID pandemic. The role of cardiac arrhythmias in COVID-19 is insufficiently understood. This study assesses the incidence of cardiac arrhythmias and their prognostic implications in hospitalized COVID-19-patients. Methods: A total of 166 patients from eight centers who were hospitalized for COVID-19 from 03/2020–06/2020 were included. Medical records were systematically analyzed for baseline characteristics, biomarkers, cardiac arrhythmias and clinical outcome parameters related to the index hospitalization. Predisposing risk factors for arrhythmias were identified. Furthermore, the influence of arrhythmia on the course of disease and related outcomes was assessed using univariate and multiple regression analyses. Results: Arrhythmias were detected in 20.5% of patients. Atrial fibrillation was the most common arrhythmia. Age and cardiovascular disease were predictors for new-onset arrhythmia. Arrhythmia was associated with a pronounced increase in cardiac biomarkers, prolonged hospitalization, and admission to intensive- or intermediate-care-units, mechanical ventilation and in-hospital mortality. In multiple regression analyses, incident arrhythmia was strongly associated with duration of hospitalization and mechanical ventilation. Cardiovascular disease was associated with increased mortality. Conclusions: Arrhythmia was the most common cardiac event in association with hospitalization for COVID-19. Older age and cardiovascular disease predisposed for arrhythmia during hospitalization. Whereas in-hospital mortality is affected by underlying cardiovascular conditions, arrhythmia during hospitalization for COVID-19 is independently associated with prolonged hospitalization and mechanical ventilation. Thus, incident arrhythmia may indicate a patient subgroup at risk for a severe course of disease.
Patient-Related Risk Factors for Unplanned 30-Day Hospital Readmission Following Primary and Revision Total Knee Arthroplasty: A Systematic Review and Meta-Analysis
Authors: Gould Daniel , Dowsey Michelle M , Spelman Tim , Jo Olivia , Kabir Wassif , Trieu Jason , Bailey James , Bunzli Samantha , Choong Peter
Published: January 2021

Total knee arthroplasty (TKA) is a highly effective procedure for advanced osteoarthritis of the knee. Thirty-day hospital readmission is an adverse outcome related to complications, which can be mitigated by identifying associated risk factors. We aimed to identify patient-related characteristics associated with unplanned 30-day readmission following TKA, and to determine the effect size of the association between these risk factors and unplanned 30-day readmission. We searched MEDLINE and EMBASE from inception to 8 September 2020 for English language articles. Reference lists of included articles were searched for additional literature. Patients of interest were TKA recipients (primary and revision) compared for 30-day readmission to any institution, due to any cause, based on patient risk factors; case series were excluded. Two reviewers independently extracted data and carried out critical appraisal. In-hospital complications during the index admission were the strongest risk factors for 30-day readmission in both primary and revision TKA patients, suggesting discharge planning to include closer post-discharge monitoring to prevent avoidable readmission may be warranted. Further research could determine whether closer monitoring post-discharge would prevent unplanned but avoidable readmissions. Increased comorbidity burden correlated with increased risk, as did specific comorbidities. Body mass index was not strongly correlated with readmission risk. Demographic risk factors included low socioeconomic status, but the impact of age on readmission risk was less clear. These risk factors can also be included in predictive models for 30-day readmission in TKA patients to identify high-risk patients as part of risk reduction programs.
Validity and Reliability of a Tool for Accelerometric Assessment of Balance in Scholar Children
Authors: García-Liñeira Jesús , Leirós-Rodríguez Raquel , Romo-Pérez Vicente , García-Soidán Jose L.
Published: January 2021

In Pediatrics, balance is assessed through low-sensitivity clinical tests which identify developmental alterations at already advanced stages that cannot be detected at earlier stages. Therefore, the aim of this study was to develop an easily applicable quantitative tool that can be used to evaluate postural control. Consequently, a cross-sectional study was carried out with 91 healthy children. All of them performed a series of six accelerometric functional tests and four clinical tests of balance (Modified Flamingo Test, Bar Test, Babinski–Weil Test, and Fukuda Stepping Test). The Bar Test obtained mild inverse correlations with accelerations produced in the mediolateral axis and the root mean square of all the tests in monopodal support. The Flamingo Test obtained direct correlations with the root mean square of the tests in monopodal support and with the mediolateral axis of the monopodal tests and gait. The pediatric balance assessment scale consists of three factors and eleven items extracted from five accelerometric functional tests: the monopodal balance test with six items, normal gait test with three items, and bipodal balance test with two items. This tool is easy to apply and allows analysis in the evaluation of the balance state based on the accelerations of the center of mass.
Virtual Body Ownership Illusions for Mental Health: A Narrative Review
Authors: Matamala-Gomez Marta , Maselli Antonella , Malighetti Clelia , Realdon Olivia , Mantovani Fabrizia , Riva Giuseppe
Published: January 2021

Over the last 20 years, virtual reality (VR) has been widely used to promote mental health in populations presenting different clinical conditions. Mental health does not refer only to the absence of psychiatric disorders but to the absence of a wide range of clinical conditions that influence people’s general and social well-being such as chronic pain, neurological disorders that lead to motor o perceptual impairments, psychological disorders that alter behaviour and social cognition, or physical conditions like eating disorders or present in amputees. It is known that an accurate perception of oneself and of the surrounding environment are both key elements to enjoy mental health and well-being, and that both can be distorted in patients suffering from the clinical conditions mentioned above. In the past few years, multiple studies have shown the effectiveness of VR to modulate such perceptual distortions of oneself and of the surrounding environment through virtual body ownership illusions. This narrative review aims to review clinical studies that have explored the manipulation of embodied virtual bodies in VR for improving mental health, and to discuss the current state of the art and the challenges for future research in the context of clinical care.
Nanocellulose from Unbleached Hemp Fibers as a Filler for Biobased Photocured Composites with Epoxidized Cardanol
Authors: Dalle Vacche Sara , Karunakaran Vijayaletchumy , Ronchetti Silvia Maria , Vitale Alessandra , Bongiovanni Roberta
Published: January 2021

Biobased composites were successfully prepared using raw materials derived from biomass waste, i.e., an epoxy resin obtained from cardanol and nanocellulose from unbleached hemp fibers. The composites were prepared by solvent exchange and an impregnation of the cellulosic mat with the resin, followed by photocuring. Quantitative conversion was obtained, despite the high amount of fibers (30 wt%) and their absorbance in the UV region of the light spectrum. X-ray diffraction confirmed that the crystalline structure of cellulose did not change during the impregnation and curing process. The cured composites were flexible, hydrophobic, water resistant, transparent with a yellow/brown color, and in the rubbery state at room temperature.
Chilblain-Like Lesions during COVID-19 Pandemic: The State of the Art
Authors: Bassi Andrea , Russo Teresa , Argenziano Giuseppe , Mazzatenta Carlo , Venturini Elisabetta , Neri Iria , Piccolo Vincenzo
Published: January 2021

SARS-CoV-2 infection has spread all over the world in the last year, causing millions of COVID-19 cases among humans with a large variability of symptoms and signs, including those on the skin. Among these, a contemporary cluster of chilblain-like lesions with no certain relationship with the infection has been reported. The aim of this paper is to delineate a profile of chilblain-like lesions and to establish the state-of-the-art knowledge about this new phenomenon.
Prospects and Limitations Related to the Use of MicroRNA as a Biomarker of Epilepsy in Children: A Systematic Review
Authors: Rzepka-Migut Beata , Paprocka Justyna
Published: January 2021

Epilepsy is one of the most common neurological diseases in children. There is an unmet need for new objective methods that would facilitate and accelerate the diagnostic process, thus improving the prognosis. In many studies, the participation of microRNA in epileptogenesis has been confirmed. Therefore, it seems to be a promising candidate for this role. Scientists show the possibility of using microRNAs as diagnostic and predictive biomarkers as well as novel therapeutic targets. Children with epilepsy would benefit particularly from the use of this innovative method. However, the number of studies related to this age group is very limited. This review is based on 10 studies in children and summarizes the information collected from studies on animal models and the adult population. A total of 136 manuscripts were included in the analysis. The aim of the review was to facilitate the design of studies in children and to draw attention to the challenges and traps related to the analysis of the results. Our review suggests a high potential for the use of microRNAs and the need for further research.
Convergence and Stability of a Parametric Class of Iterative Schemes for Solving Nonlinear Systems
Authors: Cordero Alicia , Villalba Eva G. , Torregrosa Juan R. , Triguero-Navarro Paula
Published: January 2021

A new parametric class of iterative schemes for solving nonlinear systems is designed. The third- or fourth-order convergence, depending on the values of the parameter being proven. The analysis of the dynamical behavior of this class in the context of scalar nonlinear equations is presented. This study gives us important information about the stability and reliability of the members of the family. The numerical results obtained by applying different elements of the family for solving the Hammerstein integral equation and the Fisher’s equation confirm the theoretical results.
Changepoint in Error-Prone Relations
Authors: Pešta Michal
Published: January 2021

Linear relations, containing measurement errors in input and output data, are considered. Parameters of these so-called errors-in-variables models can change at some unknown moment. The aim is to test whether such an unknown change has occurred or not. For instance, detecting a change in trend for a randomly spaced time series is a special case of the investigated framework. The designed changepoint tests are shown to be consistent and involve neither nuisance parameters nor tuning constants, which makes the testing procedures effortlessly applicable. A changepoint estimator is also introduced and its consistency is proved. A boundary issue is avoided, meaning that the changepoint can be detected when being close to the extremities of the observation regime. As a theoretical basis for the developed methods, a weak invariance principle for the smallest singular value of the data matrix is provided, assuming weakly dependent and non-stationary errors. The results are presented in a simulation study, which demonstrates computational efficiency of the techniques. The completely data-driven tests are illustrated through problems coming from calibration and insurance; however, the methodology can be applied to other areas such as clinical measurements, dietary assessment, computational psychometrics, or environmental toxicology as manifested in the paper.
Removal of Trace Organic Contaminants by Parallel Operation of Reverse Osmosis and Granular Activated Carbon for Drinking Water Treatment
Authors: Konradt Norbert , Kuhlen Jan Gerrit , Rohns Hans-Peter , Schmitt Birgitt , Fischer Uwe , Binder Timo , Schumacher Vera , Wagner Christoph , Kamphausen Stefan , Müller Uwe , Sacher Frank , Janknecht Peter , Hobby Ralph , ElSherbiny Ibrahim M. A. , Panglisch Stefan
Published: January 2021

In response to increasingly stringent restrictions for drinking water quality, a parallel operation of two common technologies, low-pressure reverse osmosis (LPRO) and activated carbon filtration (ACF), was investigated in a comprehensive five-month pilot study for the removal of 32 typical trace organic contaminants (TrOCs) from Rhine bank filtrates employing a semi- technical plant. TrOCs have been divided into three groups: polyfluorinated aliphatic compounds; pharmaceuticals, pesticides and metabolites; in addition to volatiles, nitrosamines and aminopolycarboxylic acids, which were also examined. The net pressure behavior, normalized salt passage and rejection of TrOCs by LPRO were investigated and compared with ACF operation. In addition, autopsies from the leading and last membrane modules were performed using adenosine triphosphate (ATP), total organic carbon (TOC), ICP-OES and SEM-EDX techniques. Generally, rather stable LPRO membrane performance with limited membrane fouling was observed. TrOCs with a molecular weight of ≥ 150 Da were completely retained by LPRO, while the rejection of di- and trichloro compounds improved as the filtration progressed. ACF also showed significant removal for most of the TrOCs, but without desalination. Accordingly, the ACF and LPRO can be operated in parallel such that the LPRO permeate and the ACF-treated bypass can be mixed to produce drinking water with adjustable hardness and significantly reduced TrOCs.
Preparation of Amino-Functional UiO-66/PIMs Mixed Matrix Membranes with [bmim][Tf2N] as Regulator for Enhanced Gas Separation
Authors: Lu Jiangfeng , Zhang Xu , Xu Lusheng , Zhang Guoliang , Zheng Jiuhan , Tong Zhaowei , Shen Chong , Meng Qin
Published: January 2021

Development of mixed matrix membranes (MMMs) with excellent permeance and selectivity applied for gas separation has been the focus of world attention. However, preparation of high-quality MMMs still remains a big challenge due to the lack of enough interfacial interaction. Herein, ionic liquid (IL)-modified UiO-66-NH2 filler was first incorporated into microporous organic polymer material (PIM-1) to prepare dense and defect-free mixed matrix membranes via a coating modification and priming technique. IL [bmim][Tf2N] not only improves the hydrophobicity of UiO-66-NH2 and facilitates better dispersion of UiO-66-NH2 nanoparticles into PIM-1 matrix, but also promotes the affinity between MOFs and polymer, sharply reducing interface non-selective defects of MMMs. By using this strategy, we can not only facilely synthesize high-quality MMMs ignoring non-selective interfacial voids, but also structurally regulate MOF nanoparticles in the polymer substrate and greatly improve interface compatibility and stability of MMMs. The method also gives suitable level of generality for fabrication of versatile defect-free MMMs based on different combination of MOFs and PIMs. The prepared UiO-66-NH2@IL/PIM-1 membrane exhibited outstanding gas separation behavior with large CO2 permeation of 8283.4 Barrer and high CO2/N2 selectivity of 22.5.
A Study on the Damping Capacities of Mg–Zn–Y-Based Alloys with Lamellar Long Period Stacking Ordered Phases by Preparation Process
Authors: Lu Ruopeng , Jiao Kai , Zhao Yuhong , Li Kun , Yao Keyu , Hou Hua
Published: January 2021

Mg alloys with fine mechanical properties and high damping capacities are essential in engineering applications. In this work, Mg–Zn–Y based alloys with lamellar long period stacking ordered (LPSO) phases were obtained by different processes. The results show that a more lamellar second phase can be obtained in the samples with more solid solution atoms. The density of the lamellar LPSO phase has an obvious effect on the damping of the magnesium alloy. The compact LPSO phase is not conducive to dislocation damping, but sparse lamellar phases can improve the damping capacity without significantly reducing the mechanical properties. The Mg95.3Zn2Y2.7 alloy with lamellar LPSO phases and ~100 μm grain size exhibited a fine damping property of 0.110 at ε = 10–3.
Photocatalytic Applications of Metal Oxides for Sustainable Environmental Remediation
Authors: Danish Mir Sayed Shah , Estrella Liezel L. , Alemaida Ivy Michelle A. , Lisin Anton , Moiseev Nikita , Ahmadi Mikaeel , Nazari Massoma , Wali Mohebullah , Zaheb Hameedullah , Senjyu Tomonobu
Published: January 2021

Along with industrialization and rapid urbanization, environmental remediation is globally a perpetual concept to deliver a sustainable environment. Various organic and inorganic wastes from industries and domestic homes are released into water systems. These wastes carry contaminants with detrimental effects on the environment. Consequently, there is an urgent need for an appropriate wastewater treatment technology for the effective decontamination of our water systems. One promising approach is employing nanoparticles of metal oxides as photocatalysts for the degradation of these water pollutants. Transition metal oxides and their composites exhibit excellent photocatalytic activities and along show favorable characteristics like non-toxicity and stability that also make them useful in a wide range of applications. This study discusses some characteristics of metal oxides and briefly outlined their various applications. It focuses on the metal oxides TiO2, ZnO, WO3, CuO, and Cu2O, which are the most common and recognized to be cost-effective, stable, efficient, and most of all, environmentally friendly for a sustainable approach for environmental remediation. Meanwhile, this study highlights the photocatalytic activities of these metal oxides, recent developments, challenges, and modifications made on these metal oxides to overcome their limitations and maximize their performance in the photodegradation of pollutants.
Removal of Copper, Nickel, and Iron from Lead–Tin Composite by Segregation of Intermetallic Silicon Phases
Authors: Jessen Stefan , C. Curtolo Danilo , Friedrich Bernd
Published: January 2021

In the reduction stage of the secondary copper production process, copper, nickel, lead, and tin are collected in a “black copper”, while zinc is volatilized and precipitated as ZnO in the flue dust. The slag coming from this reduction stage is low in valuable metals and is disposed. In the conversion stage, lead and tin are oxidized and incorporated in the slag phase; in accordance with the oxygen potential, this “converter slag” also contains higher contents of copper and nickel. This slag is then reduced in two stages. From the first stage, a copper–nickel metal is returned to the converter stage, and in the second stage, a crude PbSn composite with copper contents of around 10% and nickel contents of around 2.5%, as well as a further usable slag, is obtained from the “secondary” slag. Iron is used as a reducing agent, so that the metal obtained can contain iron of up to over 10%, depending on the reduction duration. The motivation of this investigation is to provide a method for the subsequent refining of the raw PbSn composite, with the aim of obtain a saleable PbSn composite as well as returning the copper and nickel contents quantitatively to the main copper route or to sell them as an alloy. Therefore, the present work aims to investigate the refining of the raw PbSn composite by the separation of the copper, nickel, and iron via the segregation of intermetallic phases. For that, a series of experiments were performed on the formation and subsequent segregation of intermetallic phases, by introduction of an additional element to the system. The results indicated sharper separation of PbSn composite and copper, nickel, and iron due to the higher thermodynamic stability of these phases (selectivity).
Effect of Niobium on Inclusions in Fe-Mn-C-Al Twinning-Induced Plasticity Steel
Authors: Lan Fangjie , Du Wenhui , Zhuang Changling , Li Changrong
Published: January 2021

The effect of Nb addition on the composition, morphology, quantity, and size of inclusions in Fe-Mn-C-Al steel was studied by SEM, EDS, and thermodynamic analysis. The research shows that the number of inclusions in Fe-Mn-C-Al high manganese steel decreases obviously after adding 0.04% element Nb, and some inclusions in the steel evolve into complex niobium inclusions. When the niobium content increases to 0.08%, the influence of niobium on inclusions in steel becomes more obvious. The precipitation temperature of inclusions in Fe-Mn-C-Al steel was analyzed by thermodynamics. The results show that the nucleation core of the composite inclusions is AlN, and then NbC and MnS precipitate locally on its surface. With the increase of Nb, the amount and volume fraction of NbC inclusions precipitated in steel increase.
Microstructure and Fracture Toughness of Fe–Nb Dissimilar Welded Joints
Authors: Chu Qiaoling , Zhang Lin , Xia Tuo , Cheng Peng , Zheng Jianming , Zhang Min , Li Jihong , Yan Fuxue , Yan Cheng
Published: January 2021

The relation between the microstructure and mechanical properties of the Fe–Nb dissimilar joint were investigated using nanoindentation. The weld metal consists mainly of Fe2Nb, α-Fe + Fe2Nb, Nb (s,s) and Fe7Nb6 phases. Radial cracks initiate from the corners of the impressions on the Fe2Nb phase (~20.5 GPa) when subjected to a peak load of 300 mN, whereas the fine lamellar structures (α-Fe + Fe2Nb) with an average hardness of 6.5 GPa are free from cracks. The calculated fracture toughness of the Fe2Nb intermetallics is 1.41 ± 0.53 MPam1/2. A simplified scenario of weld formation together with the thermal cycle is proposed to elaborate the way local phase determined the mechanical properties.
Post-Moore Memory Technology: Sneak Path Current (SPC) Phenomena on RRAM Crossbar Array and Solutions
Authors: Chen Ying-Chen , Lin Chao-Cheng , Chang Yao-Feng
Published: January 2021

The sneak path current (SPC) is the inevitable issue in crossbar memory array while implementing high-density storage configuration. The crosstalks are attracting much attention, and the read accuracy in the crossbar architecture is deteriorated by the SPC. In this work, the sneak path current problem is observed and investigated by the electrical experimental measurements in the crossbar array structure with the half-read scheme. The read margin of the selected cell is improved by the bilayer stacked structure, and the sneak path current is reduced ~20% in the bilayer structure. The voltage-read stress-induced read margin degradation has also been investigated, and less voltage stress degradation is showed in bilayer structure due to the intrinsic nonlinearity. The oxide-based bilayer stacked resistive random access memory (RRAM) is presented to offer immunity toward sneak path currents in high-density memory integrations when implementing the future high-density storage and in-memory computing applications.
Marble Waste Valorization through Alkali Activation
Authors: Komnitsas Konstantinos , Soultana Athanasia , Bartzas Georgios
Published: January 2021

In the present study, the valorization potential of marble waste in the presence of metakaolin via alkali activation was explored. The activating solution used consisted of NaOH and sodium silicate solutions. The effects of marble waste to metakaolin ratio, particle size of raw materials, curing temperature, and Na2O/SiO2 and H2O/Na2O molar ratios present in the activating solution on the main properties and the morphology of the produced alkali-activated materials (AAMs) was evaluated. The durability and structural integrity of the AAMs after firing at temperatures between 200 and 600 °C, immersion in deionized water and 1 mol/L NaCl solution for different time periods and subjection to freeze–thaw cycles were also investigated. Characterization techniques including Fourier transform infrared spectroscopy, X-ray diffraction, mercury intrusion porosimetry and scanning electron microscopy were used in order to study the structure of the produced AAMs. Τhe highest compressive strength (~36 MPa) was achieved by the AAMs prepared with marble waste to metakaolin mass ratio of 0.3 after curing at 40 °C. The results indicated that the utilization of marble waste in the presence of metakaolin enables the production of AAMs with good physical (porosity, density and water absorption) and mechanical properties, thus contributing to the valorization of this waste type and the reduction of the environmental footprint of the marble industry.