bluuebunny/crossref_metadata_2025 huggingface dataset:
Regular Two-Dimensional Packing of Congruent Objects: Cognitive Analysis of Honeycomb Constructions
Authors: Klevanskiy Nikolay N. , Tkachev Sergey I. , Voloshchuk Ludmila A. , Nourgaziev Rouslan B. , Mavzovin Vladimir S.
Published: June 2021

A new approach to investigate the two-dimensional, regular packing of arbitrary geometric objects (GOs), using cognitive visualization, is presented. GOs correspond to congruent non-convex polygons with their associated coordinate system. The origins of these coordinate systems are accepted by object poles. The approach considered is based on cognitive processes that are forms of heuristic judgments. According to the first heuristic judgment, regular packing of congruent GOs on the plane have a honeycomb structure, that is, each GO contacts six neighboring GO, the poles of which are vertices of the pole hexagon in the honeycomb construction of packing. Based on the visualization of the honeycomb constructions a second heuristic judgment is obtained, according to which inside the hexagon of the poles, there are fragments of three GOs. The consequence is a third heuristic judgment on the plane covering density with regular packings of congruent GOs. With the help of cognitive visualization, it is established that inside the hexagon of poles there are fragments of exactly three objects. The fourth heuristic judgment is related to the proposal of a triple lattice packing for regular packing of congruent GOs.
Flame Detection Using Appearance-Based Pre-Processing and Convolutional Neural Network
Authors: Ryu Jinkyu , Kwak Dongkurl
Published: June 2021

It is important for fire detectors to operate quickly in the event of a fire, but existing conventional fire detectors sometimes do not work properly or there are problems where non-fire or false reporting occurs frequently. Therefore, in this study, HSV color conversion and Harris Corner Detection were used in the image pre-processing step to reduce the incidence of false detections. In addition, among the detected corners, the vicinity of the corner point facing the upper direction was extracted as a region of interest (ROI), and the fire was determined using a convolutional neural network (CNN). These methods were designed to detect the appearance of flames based on top-pointing properties, which resulted in higher accuracy and higher precision than when input images were still used in conventional object detection algorithms. This also reduced the false detection rate for non-fires, enabling high-precision fire detection.
Threat Modelling and Beyond-Novel Approaches to Cyber Secure the Smart Energy System
Authors: Vallant Heribert , Stojanović Branka , Božić Josip , Hofer-Schmitz Katharina
Published: June 2021

Smart Grids (SGs) represent electrical power systems that incorporate increased information processing and efficient technological solutions. The integration of local prosumers, demand response systems and storage allows novel possibilities with regard to energy balancing and optimization of grid operations. Unfortunately, the dependence on IT leaves the SG exposed to security violations. In this paper, we contribute to this challenge and provide a methodology for systematic risk assessment of cyber attacks in SG systems. We propose a threat model and identify possible vulnerabilities in low-voltage distribution grids. Then, we calculate exploitation probabilities from realistic attack scenarios. Lastly, we apply formal verification to check the stochastic model against attack properties. The obtained results provide insight into potential threats and the likeliness of successful attacks. We elaborate on the effects of a security violation with regard to security and privacy of energy clients. In the aftermath, we discuss future considerations for improving security in the critical energy sector.
A Gas Chromatography-Mass Spectrometry Method for the Determination of Fatty Acids and Sterols in Yeast and Grape Juice
Authors: Williams Cody , Mbuyane Lethiwe L. , Bauer Florian F. , Mokwena Lucky , Divol Benoit , Buica Astrid
Published: June 2021

Lipids are essential components of all living cells. In an oenological context, the supply of unsaturated lipids in grape juice allows the yeasts to grow and ferment, despite very low levels of oxygen. The current study proposes a systematic optimization procedure for the analysis of fatty acids and sterols relevant to the grape fermentation process, including both extracellular and intracellular (i.e., yeast cells) lipids. Even though it was extensive, the sample preparation yielded reproducible results for all compounds of interest. The stability of the analyzed compounds was also tested to offer some implementation flexibility for the extensive procedure. The performance parameters (i.e., selectivity, linearity, limit of detection and quantitation, accuracy, and precision) indicated that the method was suitable for future practical implementation. The proof of concept also suggests that the list of compounds of interest can be expanded if additional peaks are identified. Given the large variation in concentrations, the dilution of the matrix needs to be carefully considered in order to ensure that the lipids of interest are still within the dynamic range and not below the limit of detection and/or quantification.
Using Amorphous CoB Alloy as Transducer to Detect Acoustic Propagation and Heat Transport at Interface
Authors: Jian Liu , Choi Gyung-Min
Published: June 2021

Acoustic oscillation provides useful information regarding the interfacial coupling between metal transducer layers and substrate materials. The interfacial coupling can be significantly reduced by a mechanically soft layer between the transducer and substrate. However, preserving a thin, soft layer at the interface during fabrication is often challenging. In this study, we demonstrate that an amorphous CoB alloy on top of a sapphire substrate can substantially amplify acoustic oscillations. By analyzing the attenuation of acoustic oscillations, we show that a thin, soft layer with a thickness of >2 ± 1 Å exists at the interface. The intermediate layer at the interface is further verified by investigating heat transport. By analyzing the slow decrease of the temperature of the transducer layer, we determine a thermal conductance of 35 ± 5 MW m−2 K−1 at the transducer/substrate interface. This low value supports the existence of a thin, soft layer at the interface. Our results demonstrate that an amorphous metal with B alloying effectively preserves the soft nature at the interface and detects the acoustic propagation and heat transport across it.
Chances and Risks of Artificial Intelligence—A Concept of Developing and Exploiting Machine Intelligence for Future Societies
Authors: Hutter Reinhard , Hutter Marcus
Published: June 2021

Artificial Intelligence (AI): Boon or Bane for societies? AI technologies and solutions—as most revolutionary technologies have done in the past—offer negative implications on the one hand and considerable positive potential on the other. Avoiding the former and fostering the latter will require substantial investments in future societal concepts, research and development, and control of AI-based solutions in AI security while avoiding abuse. Preparation for the future role of AI in societies should strive towards the implementation of related methods and tools for risk management, models of complementary human–machine cooperation, strategies for the optimization of production and administration, and innovative concepts for the distribution of the economic value created. Two extreme possible “end states” of AI impact (if there is ever an end state) that are being discussed at present may manifest as (a) uncontrolled substitution by AI of major aspects of production, services, and administrative and decision-making processes, leading to unprecedented risks such as high unemployment, and devaluation and the underpayment of people in paid work, resulting in inequality in the distribution of wealth and employment, diminishing social peace, social cohesion, solidarity, security, etc., or, on the contrary, (b) the freeing of people from routine labor through increased automation in production, administration and services, and changing the constitution of politics and societies into constituencies with high ethical standards, personal self-determination, and the general dominance of humane principles, as opposed to pure materialism. Any mix of these two extremes could develop, and these combinations may vary among different societies and political systems.
Sildenafil Counteracts the In Vitro Activation of CXCL-9, CXCL-10 and CXCL-11/CXCR3 Axis Induced by Reactive Oxygen Species in Scleroderma Fibroblasts
Authors: Antinozzi Cristina , Sgrò Paolo , Marampon Francesco , Caporossi Daniela , Del Galdo Francesco , Dimauro Ivan , Di Luigi Luigi
Published: June 2021

Oxidative stress plays a key role in systemic sclerosis (SSc) pathogenesis, and an altered redox homeostasis might be responsible for abnormal inflammatory status, fibrosis and tissue damage extension. In this study, we explored the effect of the phosphodiesterase type 5 inhibitor sildenafil in modulating the activation of the CXCL-9, -10, -11/CXCR3 axis, which is fundamental in the perpetuation of inflammation in different autoimmune diseases, in the cell culture of SSc human dermal fibroblasts exposed to a pro-oxidant environment. We observed that sildenafil significantly reduced gene expression and release of CXCL-9, -10 and -11, inhibited the CXCR3 action and suppressed the activation of STAT1-, JNK- and p38MAPK pathways. This in vitro study on dermal fibroblasts supports clinical studies to consider the efficacy of sildenafil in preventing tissue damage and fibrosis in SSc by targeting central biomarkers of disease progression, vascular injuries and fibrosis and reducing the pro-inflammatory activation induced by oxidative stress.
Harvest Season Significantly Influences the Fatty Acid Composition of Bee Pollen
Authors: Al-Kahtani Saad N. , Taha El-Kazafy A. , Farag Soha A. , Taha Reda A. , Abdou Ekram A. , Mahfouz Hatem M
Published: June 2021

Seasonal variations in the fatty acid (FA) compositions of pollen loads collected from the Al-Ahsa Oasis in eastern Saudi Arabia throughout one year were determined to identify the optimal season for harvesting bee pollen rich in essential fatty acids (EFAs) and unsaturated fatty acids (UFAs). The highest values (%) of lipids, linolenic acid (C18:3), stearic acid (C18:0), linoleic acid (C18:2), arachidic acid (C20:0), the sum of the C18:0, C18:1, C18:2, and C18:3 concentrations, and EFAs were obtained from bee pollen harvested during autumn. The maximum values (%) of oleic acid (C18:1), palmitic acid (C16:0), UFAs, and the UFA/saturated fatty acid (SFA) ratio were found in bee pollen harvested during summer. The highest concentrations (%) of behenic acid (C22:0), lignoceric acid (C24:0), and SFAs were found in bee pollen harvested during winter. Bee pollen harvested during spring ranked second in its oleic, palmitic, linolenic, stearic, arachidic, behenic, and lignoceric acid concentrations and for EFAs, UFAs, and the UFA/SFA ratio. The lowest SFA concentration was found in bee pollen harvested during summer. Oleic, palmitic, and linolenic acids were the most predominant FAs found in bee pollen. It was concluded that the FA composition of bee pollen varied among the harvest seasons due to the influence of the dominant botanical origins. We recommend harvesting pollen loads during spring and summer to feed honeybee colonies during periods of scarcity and for use as a healthy, nutritious food for humans.
Resveratrol Production in Yeast Hosts: Current Status and Perspectives
Authors: Ibrahim Gehad G. , Yan Jinyong , Xu Li , Yang Min , Yan Yunjun
Published: June 2021

Resveratrol is a plant secondary metabolite known for its therapeutic applications as an antioxidant, anti-cancer, anti-inflammatory, anti-aging, cardio-protective, and neuroprotective agent. Topical formulas of resveratrol are also used for skin disease management and in cosmetic industries. Due to its importance, high resveratrol production is urgently required. Since the last decade, intensive efforts have been devoted to obtaining resveratrol from microorganisms by pathway and metabolic engineering. Yeasts were proven to be excellent host candidates for resveratrol production. In addition to the similar intracellular compartments between yeasts and plants, yeasts exhibit the ability to express genes coding for plant-derived enzymes and to perform post-translational modification. Therefore, this review summarizes the attempts to use yeasts as a platform for resveratrol synthesis as the next promising route in producing high titers of resveratrol from genetically engineered strains.
Sialic Acids as Receptors for Pathogens
Authors: Burzyńska Patrycja , Sobala Łukasz , Mikołajczyk Krzysztof , Jodłowska Marlena , Jaśkiewicz Ewa
Published: June 2021

Carbohydrates have long been known to mediate intracellular interactions, whether within one organism or between different organisms. Sialic acids (Sias) are carbohydrates that usually occupy the terminal positions in longer carbohydrate chains, which makes them common recognition targets mediating these interactions. In this review, we summarize the knowledge about animal disease-causing agents such as viruses, bacteria and protozoa (including the malaria parasite Plasmodium falciparum) in which Sias play a role in infection biology. While Sias may promote binding of, e.g., influenza viruses and SV40, they act as decoys for betacoronaviruses. The presence of two common forms of Sias, Neu5Ac and Neu5Gc, is species-specific, and in humans, the enzyme converting Neu5Ac to Neu5Gc (CMAH, CMP-Neu5Ac hydroxylase) is lost, most likely due to adaptation to pathogen regimes; we discuss the research about the influence of malaria on this trait. In addition, we present data suggesting the CMAH gene was probably present in the ancestor of animals, shedding light on its glycobiology. We predict that a better understanding of the role of Sias in disease vectors would lead to more effective clinical interventions.
Silicene Quantum Capacitance Dependent Frequency Readout to a Label-Free Detection of DNA Hybridization— A Simulation Analysis
Authors: Rahman Md. Sazzadur , Naima Rokaia Laizu , Shetu Khatuna Jannatun , Hossain Md. Mahabub , Kaiser M. Shamim , Hosen A. S. M. Sanwar , Sarker Md. Abdul Latif , Ooi Kelvin J. A.
Published: June 2021

The use of deoxyribonucleic acid (DNA) hybridization to detect disease-related gene expression is a valuable diagnostic tool. An ion-sensitive field-effect transistor (ISFET) with a graphene layer has been utilized for detecting DNA hybridization. Silicene is a two-dimensional silicon allotrope with structural properties similar to graphene. Thus, it has recently experienced intensive scientific research interest due to its unique electrical, mechanical, and sensing characteristics. In this paper, we proposed an ISFET structure with silicene and electrolyte layers for the label-free detection of DNA hybridization. When DNA hybridization occurs, it changes the ion concentration in the surface layer of the silicene and the pH level of the electrolyte solution. The process also changes the quantum capacitance of the silicene layer and the electrical properties of the ISFET device. The quantum capacitance and the corresponding resonant frequency readout of the silicene and graphene are compared. The performance evaluation found that the changes in quantum capacitance, resonant frequency, and tuning ratio indicate that the sensitivity of silicene is much more effective than graphene.
Kriging Metamodel-Based Seismic Fragility Analysis of Single-Bent Reinforced Concrete Highway Bridges
Authors: Hoang Phuong Hoa , Phan Hoang Nam , Nguyen Duy Thao , Paolacci Fabrizio
Published: June 2021

Uncertainty quantification is an important issue in the seismic fragility analysis of bridge type structures. However, the influence of different sources of uncertainty on the seismic fragility of the system is commonly overlooked due to the costly re-evaluation of numerical model simulations. This paper aims to present a framework for the seismic fragility analysis of reinforced concrete highway bridges, where a data-driven metamodel is developed to approximate the structural response to structural and ground motion uncertainties. The proposed framework to generate fragility curves shows its efficiency while using a few finite element simulations and accounting for various modeling uncertainties influencing the bridge seismic fragility. In this respect, a class of single-bent bridges available in the literature is taken as a case study, whose three-dimensional finite element model is established by the OpenSees software framework. Twenty near-source records from different sources are selected and the Latin hypercube method is applied for generating the random samples of modeling and ground motion parameters. The Kriging metamodel is then driven on the structural response obtained from nonlinear time history analyses. Component fragility curves of the reinforced concrete pier column are derived for different damage states using the Kriging metamodel whose parameters are established considering different modeling parameters generated by Monte Carlo simulations. The results demonstrate the efficiency of the proposed framework in interpolating the structural response and deriving the fragility curve of the case study with any input conditions of the random variables.
Towards Computer-Aided Graphene Covered TiO2-Cu/(CuxOy) Composite Design for the Purpose of Photoinduced Hydrogen Evolution
Authors: Lewandowski Łukasz , Gajewicz-Skretna Agnieszka , Klimczuk Tomasz , Trykowski Grzegorz , Nikiforow Kostiantyn , Lisowski Wojciech , Gołąbiewska Anna , Zaleska-Medynska Adriana
Published: June 2021

In search a hydrogen source, we synthesized TiO2-Cu-graphene composite photocatalyst for hydrogen evolution. The catalyst is a new and unique material as it consists of copper-decorated TiO2 particles covered tightly in graphene and obtained in a fluidized bed reactor. Both, reduction of copper from Cu(CH3COO) at the surface of TiO2 particles and covering of TiO2-Cu in graphene thin layer by Chemical Vapour Deposition (CVD) were performed subsequently in the flow reactor by manipulating the gas composition. Obtained photocatalysts were tested in regard to hydrogen generation from photo-induced water conversion with methanol as sacrificial agent. The hydrogen generation rate for the most active sample reached 2296.27 µmol H2 h−1 gcat−1. Combining experimental and computational approaches enabled to define the optimum combination of the synthesis parameters resulting in the highest photocatalytic activity for water splitting for green hydrogen production. The results indicate that the major factor affecting hydrogen production is temperature of the TiO2-Cu-graphene composite synthesis which in turn is inversely correlated to photoactivity.
Preliminary Investigation of the Mechanical and Physical Properties of Natural Hydraulic Lime Grouts with Nano-Silica
Authors: Baltazar Luis G. , Cardoso João
Published: June 2021

Natural hydraulic lime-based grouts are often used in the structural consolidation of old stone masonry walls, mainly to re-establish the monolithic behaviour of masonry constructions. To ensure an adequate grouting operation, it is essential to have good fresh and hardened grout properties. The motivation of the present study was to examine the fresh and hardened properties of natural hydraulic lime grouts with nano-silica (NS) and silica fume (SF). The contribution of these materials and the dosage of a high range water reducer admixture (HRWR) were investigated on the rheological properties, water capillarity, open porosity and mechanical strength of injection grouts. The effects on rheology were analysed through plastic viscosity and yield stress. The results indicated that, even for reduced NS content, an increase in plastic viscosity and yield stress occurred, which required a higher HRWR content in order to not compromise the grout’s rheological performance. The results also showed that, when NS and SF were combined, a beneficial joint effect occurred, resulting in a substantial and positive change on the mechanical strength and microstructure of the hardened injection grouts. Taguchi’s method was used to optimize the grout’s formulation and to fulfil the required performance concerning the fresh and hardened state.
Theophylline in Treatment of COVID-19 Induced Sinus Bradycardia
Authors: Sawalha Khalid , Habash Fuad J. , Vallurupalli Srikanth , Paydak Hakan
Published: June 2021

This is a retrospective case series of two patients with laboratory-confirmed coronavirus 2 (SARS-CoV-2) infection, presented to the University of Arkansas for Medical Sciences in January 2021. Medical records of these patients were reviewed using the EPIC electronic health record system. Clinical, laboratory, and treatment data were reviewed against periods of bradycardia in each patient. Both of the patients presented with dizziness and presyncope related to sinus bradycardia in which they received treatment with 1 mg of IV atropine and theophylline 200 mg orally. We share these two cases of theophylline treatment in COVID-19 induced sinus bradycardia. The first patient was a 39-year-old female, with a past medical history of polycystic ovarian syndrome, who presented to the emergency department with lightheadedness and dizziness. Two weeks prior to her presentation, she was tested positive for COVID-19 infection that was treated with azithromycin, dexamethasone and aspirin. Upon presentation, her ECG showed sinus bradycardia at a rate of 48 bpm. The second patient, a 21-year-old female with no significant past medical history, presented with presyncope. Three weeks prior to her presentation, she tested positive for COVID-19 infection that was treated symptomatically at her home. Upon presentation, her ECG showed junctional rhythm at a heart rate of 51 bpm.
Radiomics Score Combined with ACR TI-RADS in Discriminating Benign and Malignant Thyroid Nodules Based on Ultrasound Images: A Retrospective Study
Authors: Luo Peng , Fang Zheng , Zhang Ping , Yang Yang , Zhang Hua , Su Lei , Wang Zhigang , Ren Jianli
Published: June 2021

This study aimed to explore the ability of combination model of ultrasound radiomics score (Rad-score) and the thyroid imaging, reporting and data system by the American College of Radiology (ACR TI-RADS) in predicting benign and malignant thyroid nodules (TNs). Up to 286 radiomics features were extracted from ultrasound images of TNs. By using the lowest probability of classification error and average correlation coefficients (POE + ACC) and the least absolute shrinkage and selection operator (LASSO), we finally selected four features to establish Rad-score (Vertl-RLNonUni, Vertl-GLevNonU, WavEnLH-s4 and WavEnHL-s5). DeLong’s test and decision curve analysis (DCA) showed that the method of combining Rad-score and ACR TI-RADS had the best performance (the area under the receiver operating characteristic curve (AUC = 0.913 (95% confidence interval (CI), 0.881–0.939) and 0.899 (95%CI, 0.840–0.942) in the training group and verification group, respectively), followed by ACR TI-RADS (AUC = 0.898 (95%CI, 0.863–0.926) and 0.870 (95%CI, 0.806–0.919) in the training group and verification group, respectively), and followed by Rad-score (AUC = 0.750 (95%CI, 0.704–0.792) and 0.750 (95%CI, 0.672–0.817) in the training group and verification group, respectively). We concluded that the ability of ultrasound Rad-score to distinguish benign and malignant TNs was not as good as that of ACR TI-RADS, and the ability of the combination model of Rad-score and ACR TI-RADS to discriminate benign and malignant TNs was better than ACR TI-RADS or Rad-score alone. Ultrasound Rad-score might play a potential role in improving the differentiation of malignant TNs from benign TNs.
UAV Forensics: DJI Mini 2 Case Study
Authors: Stanković Miloš , Mirza Mohammad Meraj , Karabiyik Umit
Published: June 2021

Rapid technology advancements, especially in the past decade, have allowed off-the-shelf unmanned aerial vehicles (UAVs) that weigh less than 250 g to become available for recreational use by the general population. Many well-known manufacturers (e.g., DJI) are now focusing on this segment of UAVs, and the new DJI Mini 2 drone is one of many that falls under this category, which enables easy access to be purchased and used without any Part 107 certification and Remote ID registration. The versatility of drones and drone models is appealing for customers, but they pose many challenges to forensic tools and digital forensics investigators due to numerous hardware and software variations. In addition, different devices can be associated and used for controlling these drones (e.g., Android and iOS smartphones). Moreover, according to the Federal Aviation Administration (FAA), the adoption of Remote ID is not going to be required for people without the 107 certifications for this segment at least until 2023, which creates finding personally identifiable information a necessity in these types of investigations. In this research, we conducted a comprehensive investigation of DJI Mini 2 and its data stored across multiple devices (e.g., SD cards and mobile devices) that are associated with the drone. The aim of this paper is to (1) create several criminal-like scenarios, (2) acquire and analyze the created scenarios using leading forensics software (e.g., Cellebrite and Magnet Axiom) that are commonly used by law enforcement agencies, (3) and present findings associated with potential criminal activities.
An Empirical Performance Evaluation of Multiple Intel Optane Solid-State Drives
Authors: Han Jaehyun , Zhu Guangyu , Lee Sangmook , Son Yongseok
Published: June 2021

Cloud computing as a service-on-demand architecture has grown in importance over the last few years. The storage subsystem in cloud computing has undergone enormous innovation to provide high-quality cloud services. Emerging Non-Volatile Memory Express (NVMe) technology has attracted considerable attention in cloud computing by delivering high I/O performance in latency and bandwidth. Specifically, multiple NVMe solid-state drives (SSDs) can provide higher performance, fault tolerance, and storage capacity in the cloud computing environment. In this paper, we performed an empirical evaluation study of performance on recent NVMe SSDs (i.e., Intel Optane SSDs) with different redundant array of independent disks (RAID) environments. We analyzed multiple NVMe SSDs with RAID in terms of different performance metrics via synthesis and database benchmarks. We anticipate that our experimental results and performance analysis will have implications for various storage systems. Experimental results showed that the software stack overhead reduced the performance by up to 75%, 52%, 76%, 91%, and 92% in RAID 0, 1, 10, 5, and 6, respectively, compared with theoretical and expected performance.
Data-Driven Channel Pruning towards Local Binary Convolution Inverse Bottleneck Network Based on Squeeze-and-Excitation Optimization Weights
Authors: Feng Duo , Ren Fuji
Published: June 2021

This paper proposed a model pruning method based on local binary convolution (LBC) and squeeze-and-excitation (SE) optimization weights. We first proposed an efficient deep separation convolution model based on the LBC kernel. By expanding the number of LBC kernels in the model, we have trained a larger model with better results, but more parameters and slower calculation speed. Then, we extract the SE optimization weight value of each SE module according to the data samples and score the LBC kernel accordingly. Based on the score of each LBC kernel corresponding to the convolution channel, we performed channel-based model pruning, which greatly reduced the number of model parameters and accelerated the calculation speed. The model pruning method proposed in this paper is verified in the image classification database. Experiments show that, in the model using the LBC kernel, as the number of LBC kernels increases, the recognition accuracy will increase. At the same time, the experiment also proved that the recognition accuracy is maintained at a similar level in the small parameter model after channel-based model pruning by the SE optimization weight value.
Performance Assessment of Linux Kernels with PREEMPT_RT on ARM-Based Embedded Devices
Authors: Adam George K. , Petrellis Nikos , Doulos Lambros T.
Published: June 2021

This work investigates the real-time performance of Linux kernels and distributions with a PREEMPT_RT real-time patch on ARM-based embedded devices. Experimental measurements, which are mainly based on heuristic methods, provide novel insights into Linux real-time performance on ARM-based embedded devices (e.g., BeagleBoard and RaspberryPi). Evaluations of the Linux real-time performance are based on specific real-time software measurement modules, developed for this purpose, and the use of a standard benchmark tool, cyclictest. Software modules were designed upon the introduction of a new response task model, an innovative aspect of this work. Measurements include the latency of response tasks at user and kernel space, the response on the execution of periodic tasks, the maximum sustained frequency and general latency performance metrics. The results show that in such systems the PREEMPT_RT patch provides more improved real-time performance than the default Linux kernels. The latencies and particularly the worst-case latencies are reduced with real-time support, thus making such devices running Linux with PREEMPT_RT more appropriate for use in time-sensitive embedded control systems and applications. Furthermore, the proposed performance measurements approach and evaluation methodology could be applied and deployed on other Linux-based real-time platforms.
Social Media Toxicity Classification Using Deep Learning: Real-World Application UK Brexit
Authors: Fan Hong , Du Wu , Dahou Abdelghani , Ewees Ahmed A. , Yousri Dalia , Elaziz Mohamed Abd , Elsheikh Ammar H. , Abualigah Laith , Al-qaness Mohammed A. A.
Published: June 2021

Social media has become an essential facet of modern society, wherein people share their opinions on a wide variety of topics. Social media is quickly becoming indispensable for a majority of people, and many cases of social media addiction have been documented. Social media platforms such as Twitter have demonstrated over the years the value they provide, such as connecting people from all over the world with different backgrounds. However, they have also shown harmful side effects that can have serious consequences. One such harmful side effect of social media is the immense toxicity that can be found in various discussions. The word toxic has become synonymous with online hate speech, internet trolling, and sometimes outrage culture. In this study, we build an efficient model to detect and classify toxicity in social media from user-generated content using the Bidirectional Encoder Representations from Transformers (BERT). The BERT pre-trained model and three of its variants has been fine-tuned on a well-known labeled toxic comment dataset, Kaggle public dataset (Toxic Comment Classification Challenge). Moreover, we test the proposed models with two datasets collected from Twitter from two different periods to detect toxicity in user-generated content (tweets) using hashtages belonging to the UK Brexit. The results showed that the proposed model can efficiently classify and analyze toxic tweets.
Finite-Time Adaptive Higher-Order SMC for the Nonlinear Five DOF Active Magnetic Bearing System
Authors: Saha Sudipta , Amrr Syed Muhammad , Saidi Abdelaziz Salah , Banerjee Arunava , Nabi M.
Published: June 2021

The active magnetic bearings (AMB) play an essential role in supporting the shaft of fast rotating machines and controlling the displacements in the rotors due to the deviation in the shaft. In this paper, an adaptive integral third-order sliding mode control (AITOSMC) is proposed. The controller suppresses the deviations in the rotor and rejects the system uncertainties and unknown disturbances present in the five DOF AMB system. The application of AITOSMC alleviates the problem of high-frequency switching called chattering, which would otherwise restrict the practical application of sliding mode control (SMC). Moreover, adaptive laws are also incorporated in the proposed approach for estimating the controller gains. Further, it also prevents the problem of overestimation and avoids the use of a priori assumption about the upper bound knowledge of total disturbance. The Lyapunov and homogeneity theories are exploited for the stability proof, which guarantees the finite-time convergence of closed-loop and output signals. The numerical analysis of the proposed strategy illustrates the effective performance. Furthermore, the comparative analysis with the existing control schemes demonstrates the efficacy of the proposed controller.
Time in Range for Closed-Loop Systems versus Standard of Care during Physical Exercise in People with Type 1 Diabetes: A Systematic Review and Meta-Analysis
Authors: Eckstein Max L. , Weilguni Benjamin , Tauschmann Martin , Zimmer Rebecca T. , Aziz Faisal , Sourij Harald , Moser Othmar
Published: June 2021

The aim of this systematic review and meta-analysis was to compare time in range (TIR) (70–180 mg/dL (3.9–10.0 mmol/L)) between fully closed-loop systems (CLS) and standard of care (including hybrid systems) during physical exercise in people with type 1 diabetes (T1D). A systematic literature search was conducted in EMBASE, PubMed, Cochrane Central Register of Controlled Trials, and ISI Web of Science from January 1950 until January 2020. Randomized controlled trials including studies with different CLS were compared against standard of care in people with T1D. The meta-analysis was performed using the random effects model and restricted maximum likelihood estimation method. Six randomized controlled trials involving 153 participants with T1D of all age groups were included. Due to crossover test designs, studies were included repeatedly (a–d) if CLS or physical exercise interventions were different. Applying this methodology increased the comparisons to a total number of 266 participants. TIR was higher with an absolute mean difference (AMD) of 6.18%, 95% CI: 1.99 to 10.38% in favor of CLS. In a subgroup analysis, the AMD was 9.46%, 95% CI: 2.48% to 16.45% in children and adolescents while the AMD for adults was 1.07% 95% CI: −0.81% to 2.96% in favor of CLS. In this systematic review and meta-analysis CLS moderately improved TIR in comparison to standard of care during physical exercise in people with T1D. This effect was particularly pronounced for children and adolescents showing that the use of CLS improved TIR significantly compared to standard of care.
Ideal Cardiovascular Health in Former Smokers
Authors: Leopold Jane A. , Antman Elliott M.
Published: June 2021

Former smokers remain at increased risk for cardiovascular diseases compared to never smokers, but have lower risk than current smokers. We therefore hypothesized that former smokers would have an ideal cardiovascular health phenotype that was intermediate between current and never smokers. Differences in ideal cardiovascular health between never (n = 1025), former (n = 428), and current (n = 108) smokers were evaluated in the My Research Legacy study, which collected cardiovascular health data from the Life’s Simple 7 survey and digital health devices. Former smokers had a higher burden of prevalent cardiovascular disease, hypertension, diabetes mellitus, and hypercholesterolemia compared to current and never smokers (all p < 0.01). Former smokers’ Life’s Simple 7 Health Scores, a measure of ideal cardiovascular health, were intermediate between current and never smokers (4.9 ± 1.3 vs. 6.3 ± 1.5 vs. 7.0 ± 1.4, p < 0.01). As former smokers shared similarities with both current and never smokers, we performed a cluster analysis, which identified two phenogroups of former smokers. The phenogroups differed significantly across all 7 cardiovascular health and behavior categories (all p < 0.01). These findings suggest that former smokers are a heterogeneous group and increased attention to cardiovascular health factors and behaviors is warranted to achieve ideal cardiovascular health.
Aligned Collagen-CNT Nanofibrils and the Modulation Effect on Ovarian Cancer Cells
Authors: Li Wen , Chi Naiwei , Clutter Elwin , Zhu Bofan , Wang Rong
Published: June 2021

Fibrillar collagen is a one-dimensional biopolymer and is the most abundant structural protein in the extracellular matrix (ECM) of connective tissues. Due to the unique properties of carbon nanotubes (CNTs), considerable attention has been given to the application of CNTs in developing biocomposite materials for tissue engineering and drug delivery. When introduced to tissues, CNTs inevitably interact and integrate with collagen and impose a discernible effect on cells in the vicinity. The positive effect of the collagen-CNT (COL-CNT) matrix in tissue regeneration and the cytotoxicity of free CNTs have been investigated extensively. In this study, we aimed to examine the effect of COL-CNT on mediating the interaction between the matrix and SKOV3 ovarian cancer cells. We generated unidirectionally aligned collagen and COL-CNT nanofibrils, mimicking the structure and dimension of collagen fibrils in native tissues. AFM analysis revealed that the one-dimensional structure, high stiffness, and low adhesion of COL-CNT greatly facilitated the polarization of SKOV3 cells by regulating the β-1 integrin-mediated cell–matrix interaction, cytoskeleton rearrangement, and cell migration. Protein and gene level analyses implied that both collagen and COL-CNT matrices induced the epithelial–mesenchymal transition (EMT), and the COL-CNT matrix prompted a higher level of cell transformation. However, the induced cells expressed CD44 at a reduced level and MMP2 at an increased level, and they were responsive to the chemotherapy drug gemcitabine. The results suggested that the COL-CNT matrix induced the transdifferentiation of the epithelial cancer cells to mature, less aggressive, and less potent cells, which are inapt for tumor metastasis and chemoresistance. Thus, the presence of CNT in a collagen matrix is unlikely to cause an adverse effect on cancer patients if a controlled dose of CNT is used for drug delivery or tissue regeneration.
Prognostic Factors in Primary Biliary Cholangitis: A Retrospective Study of Joint Slovak and Croatian Cohort of 249 Patients
Authors: Gazda Jakub , Drazilova Sylvia , Janicko Martin , Grgurevic Ivica , Filipec Kanizaj Tajana , Koller Tomas , Bodorovska Beatrica , Bozin Tonci , Mijic Maja , Rob Zrinka , Mikolasevic Ivana , Madir Anita , Kucinsky Branislav , Jarcuska Peter
Published: June 2021

Objective: To identify pretreatment laboratory parameters associated with treatment response and to describe the relationship between treatment response and liver decompensation in patients with primary biliary cholangitis treated with ursodeoxycholic acid. Methods: We defined treatment response as both ALP ≤ 1.67 × ULN and total bilirubin ≤ 2 × ULN. Multiple logistic regression analyses were performed to adjust for confounding effects of sociodemographic variables. Results: Pretreatment total bilirubin ((TB); OR = 0.3388, 95%CI = 0.1671–0.6077), ALT (OR = 0.5306, 95%CI = 0.3830–0.7080), AST (OR = 0.4065, 95%CI = 0.2690–0.5834), ALP (OR = 0.3440, 95%CI = 0.2356–0.4723), total cholesterol ((TC); OR = 0.7730, 95%CI = 0.6242–0.9271), APRI (OR = 0.3375, 95%CI = 0.1833–0.5774), as well as pretreatment albumin (OR = 1.1612, 95%CI = 1.0706–1.2688) and ALT/ALP (OR = 2.4596, 95%CI = 1.2095–5.5472) were associated with treatment response after six months of treatment. Pretreatment TB (OR = 0.2777, 95%CI = 0.1288–0.5228), ALT (OR = 0.5968, 95%CI = 0.4354–0.7963), AST (OR = 0.4161, 95%CI = 0.2736–0.6076), ALP (OR = 0.4676, 95%CI = 0.3487–0.6048), APRI (OR = 0.2838, 95%CI = 0.1433–0.5141), as well as pretreatment albumin (OR = 1.2359, 95%CI = 1.1257–1.3714) and platelet count (OR = 1.0056, 95%CI = 1.0011–1.0103) were associated with treatment response after 12 months of treatment. Treatment response after 6 months of UDCA therapy is significantly associated with treatment response after 12 months of UDCA therapy (OR = 25.2976, 95% CI = 10.5881–68.4917). Treatment responses after 6 and 12 months of UDCA therapy decrease the risk of an episode of liver decompensation in PBC patients (OR = 12.1156, 95%CI = 3.7192–54.4826 and OR = 21.6000, 95%CI = 6.6319–97.3840, respectively). Conclusions: There are several pretreatment laboratory parameters associated with treatment response in patients with primary biliary cholangitis. Treatment response after six months is significantly associated with treatment response after 12 months of ursodeoxycholic acid (UDCA) therapy. Treatment responses after 6 and 12 months of UDCA decrease the risk of an episode of liver decompensation.
Spatial Fiscal Interactions in Colombian Municipalities: Evidence from Oil Price Shocks
Authors: Mainali Raju
Published: June 2021

This study provides an empirical investigation of fiscal interactions in the context of a developing country. I examine three fiscal components—budget balance, tax revenue, and public spending—to measure spatial interactions between Colombian municipalities from 2000 to 2010. I am using variables on municipalities’ general characteristics, fiscal variables, and variables related to the conflict. I use a quasi-experimental identification strategy exploiting exogenous variation from global oil price shocks that affect Colombian municipalities to different degrees depending on local oil endowments. I find significant spatial interaction in taxes but no significant interaction concerning budget balance and total public spending. This suggests that even though there is local tax competition, municipalities do not mimic their neighbors to decide whether to offset tax changes by changes in borrowing or spending.
Assessing Matching Characteristics and Spatial Differences between Supply and Demand of Ecosystem Services: A Case Study in Hangzhou, China
Authors: Tian Peng , Li Jialin , Cao Luodan , Pu Ruiliang , Gong Hongbo , Zhang Haitao , Chen Huilin , Yang Xiaodong
Published: June 2021

Ecosystem services (ESs) is a term used to describe the foundations of the well-being of human society, and several relevant studies have been carried out in this area. However, given the fact that the complex trade-offs/synergy relationships of ESs are a challenging area, studies on matching mechanisms for ES supply and demand are still rare. In this study, using the InVEST model, ArcGIS, and other professional tools, we first mapped and quantitatively evaluated the supply and demand of five ES types (water yield, soil conservation, carbon retention, food supply, and leisure and entertainment) in Hangzhou, China, based on land use, meteorology, soil, and socio-economic data. Then, we analyzed the matching characteristics between the supply and demand of these ESs and analyzed the complex trade-offs and synergy between the supply and demand of ESs and factors affecting ESs. The results of this analysis indicate that although the ES supply and demand of carbon retention tended to be out of balance (supply was less than demand), the supply and demand of the other four ES types (i.e., water yield, soil conservation, food supply, and leisure and entertainment) were in balance (supply exceeded demand). Finally, the spatial heterogeneity of the supply and demand of ESs in Hangzhou was significant, especially in urban areas in the northeast and mountainous areas in the southwest. The supply of ESs was based on trade-offs, whereas the demand of ESs was based on synergy. Our results further show that the supply and demand of ESs in the urban area in Hangzhou were out of balance, whereas the supply and demand of ESs in the western region were coordinated. Therefore, the linkage of ES flows between this urban area and the western region should be strengthened. This innovative study could provide useful information for regional land use planning and environmental protection.
A Machine Learning Evaluation of the Effects of South Africa’s COVID-19 Lockdown Measures on Population Mobility
Authors: Whata Albert , Chimedza Charles
Published: June 2021

Following the declaration by the World Health Organisation (WHO) on 11 March 2020, that the global COVID-19 outbreak had become a pandemic, South Africa implemented a full lockdown from 27 March 2020 for 21 days. The full lockdown was implemented after the publication of the National Disaster Regulations (NDR) gazette on 18 March 2020. The regulations included lockdowns, public health measures, movement restrictions, social distancing measures, and social and economic measures. We developed a hybrid model that consists of a long-short term memory auto-encoder (LSTMAE) and the kernel quantile estimator (KQE) algorithm to detect change-points. Thereafter, we utilised the Bayesian structural times series models (BSTSMs) to estimate the causal effect of the lockdown measures. The LSTMAE and KQE, successfully detected the changepoint that resulted from the full lockdown that was imposed on 27 March 2020. Additionally, we quantified the causal effect of the full lockdown measure on population mobility in residential places, workplaces, transit stations, parks, grocery and pharmacy, and retail and recreation. In relative terms, population mobility at grocery and pharmacy places decreased significantly by −17,137.04% (p-value = 0.001 < 0.05). In relative terms, population mobility at transit stations, retail and recreation, workplaces, parks, and residential places decreased significantly by −998.59% (p-value = 0.001 < 0.05), −1277.36% (p-value = 0.001 < 0.05), −2175.86% (p-value = 0.001 < 0.05), −370.00% (p-value = 0.001< 0.05), and −22.73% (p-value = 0.001 < 0.05), respectively. Therefore, the full lockdown Level 5 imposed on March 27, 2020 had a causal effect on population mobility in these categories of places.
Sport Injuries among Amateur Women and Young Intermediate Level Female Handball Players: A Preliminary Investigation
Authors: Sanchez-Lastra Miguel A. , Vila Pedro Vicente , Ledo Arón Díaz , Ayán Carlos
Published: June 2021

Background and objectives: Handball is a popular sport among women whose practice can lead to marked health benefits but could also show a high injury risk. There is a lack of research on intermediate level female players. We aimed to identify the prevalence of sport injuries in amateur and young intermediate level female handball players and the potential influence of the sport category. Materials and Methods: A group of cadets, juvenile and senior female players of three handball clubs participating in the Spanish regional league were followed throughout the 2018–2019 season. Information on injuries and exposure was collected via questionnaires. Results: Out of 114 players (34 seniors, 33 juvenile and 47 cadets), 77 of them sustained at least one injury. Most of the injuries were either moderate or severe, regardless of the category. A total of 7.93, 5.93 and 4.16 injuries per 1000 h of exposure were registered in the senior, juvenile and cadet categories respectively. The risk of sustaining an injury was 2.14 times higher for senior players Confidence Interval (CI 95%: 1.51–3.03) and 1.92 higher for juvenile players (CI 95%: 1.32–2.78) when compared with cadets. Conclusions: Senior and young female handball athletes playing at an amateur and intermediate level, are exposed to a substantial risk of sustaining a moderate or severe injury. The players’ category does not seem to have a great impact on the injury rate and on the characteristics of the sport injuries registered.