bluuebunny/crossref_metadata_2025 huggingface dataset:
Forging of Mg-Al-Zn Magnesium Alloys on Screw Press and Forging Hammer
Authors: Gontarz Andrzej , Drozdowski Krzysztof , Michalczyk Jacek , Wiewiórowska Sylwia , Pater Zbigniew , Tomczak Janusz , Samołyk Grzegorz , Winiarski Grzegorz , Surdacki Piotr
Published: December 2020

Magnesium alloys are highly strain rate sensitive and exhibit good workability in a narrow forging temperature range. Consequently, parts made of these materials are usually forged with low-speed hydraulic presses, using specially designed tool heating systems in order to ensure near-isothermal conditions. This study investigates whether popular magnesium alloys such as Mg-Al-Zn can be forged in forging machines equipped with high-speed forming tools. Experimental upset forging tests on AZ31B, AZ61A and AZ80A specimens were conducted, using a screw press with a ram speed of 0.5 m/s and a die forging hammer with a ram speed at stroke of about 5 m/s. Test specimens were preheated to 350 °C, 410 °C and 450 °C. After the upset forging process, they were air- or water-cooled and then examined for their workability, hardness and grain size. To validate the results, a forging process for a producing handle was designed and modelled by the finite element method. Distributions of strain, temperature and fracture criterion were analysed, and energy and force parameters of the forging process were calculated. After that, experimental tests were performed on AZ31B and AZ61A specimens in order to determine mechanical properties of forged parts and examine their micro- and macrostructure. Results have demonstrated that AZ80A is not suitable for forging with either the screw press or the die forging hammer, that AZ61A can be press- and hammer-forged but to a limited extent, and that AZ31B can be subjected to forging in both forging machines analysed in the study.
Monotonic Tension-Torsion Experiments and FE Modeling on Notched Specimens Produced by SLM Technology from SS316L
Authors: Kořínek Michal , Halama Radim , Fojtík František , Pagáč Marek , Krček Jiří , Krzikalla David , Kocich Radim , Kunčická Lenka
Published: December 2020

The aim of this work was to monitor the mechanical behavior of 316L stainless steel produced by 3D printing in the vertical direction. The material was tested in the “as printed” state. Digital Image Correlation measurements were used for 4 types of notched specimens. The behavior of these specimens under monotonic loading was investigated in two loading paths: tension and torsion. Based on the experimental data, two yield criteria were used in the finite element analyses. Von Mises criterion and Hill criterion were applied, together with the nonlinear isotropic hardening rule of Voce. Subsequently, the load-deformation responses of simulations and experiments were compared. Results of the Hill criterion show better correlation with experimental data. The numerical study shows that taking into account the difference in yield stress in the horizontal direction of printing plays a crucial role for modeling of notched geometries loaded in the vertical direction of printing. Ductility of 3D printed specimens in the “as printed” state is also compared with 3D printed machined specimens and specimens produced by conventional methods. “As printed” specimens have 2/3 lower ductility than specimens produced by a conventional production method. Machining of “as printed” specimens does not affect the yield stress, but a significant reduction of ductility was observed due to microcracks arising from the pores as a microscopic surface study showed.
4-(Phenylsulfanyl) Butan-2-One Attenuates the Inflammatory Response Induced by Amyloid-β Oligomers in Retinal Pigment Epithelium Cells
Authors: Varinthra Peeraporn , Huang Shun-Ping , Chompoopong Supin , Wen Zhi-Hong , Liu Ingrid Y.
Published: December 2020

Age-related macular degeneration (AMD) is a progressive eye disease that causes irreversible impairment of central vision, and effective treatment is not yet available. Extracellular accumulation of amyloid-beta (Aβ) in drusen that lie under the retinal pigment epithelium (RPE) has been reported as one of the early signs of AMD and was found in more than 60% of Alzheimer’s disease (AD) patients. Extracellular deposition of Aβ can induce the expression of inflammatory cytokines such as IL-1β, TNF-α, COX-2, and iNOS in RPE cells. Thus, finding a compound that can effectively reduce the inflammatory response may help the treatment of AMD. In this research, we investigated the anti-inflammatory effect of the coral-derived compound 4-(phenylsulfanyl) butan-2-one (4-PSB-2) on Aβ1-42 oligomer (oAβ1-42) added to the human adult retinal pigment epithelial cell line (ARPE-19). Our results demonstrated that 4-PSB-2 can decrease the elevated expressions of TNF-α, COX-2, and iNOS via NF-κB signaling in ARPE-19 cells treated with oAβ1-42 without causing any cytotoxicity or notable side effects. This study suggests that 4-PSB-2 is a promising drug candidate for attenuation of AMD.
Outcome Predictive Value of Serum Ferritin in ICU Patients with Long ICU Stay
Authors: Rusu Daniel , Blaj Mihaela , Ristescu Irina , Patrascanu Emilia , Gavril Laura , Lungu Olguța , Siriopol Ianis , Buzincu Iulian , Grigoraș Ioana
Published: December 2020

Background and Objectives: The simplified interpretation of serum ferritin levels, according to which low ferritin levels indicate iron deficiency and high levels indicate hemochromatosis is obsolete, as in the presence of inflammation serum ferritin levels, no longer correlate with iron stores. However, further data are needed to interpret serum ferritin levels correctly in patients with ongoing inflammation. Our study aimed to assess serum iron and ferritin dynamics in patients with long intensive care unit (ICU) stay and the possible correlations with organ dysfunction progression and outcome. Materials and Methods: We conducted a prospective study in a university hospital ICU over six months. All patients with an ICU length-of-stay of more than seven days were enrolled. Collected data included: demographics, Sequential Organ Failure Assessment (SOFA) score, admission, weekly serum iron and ferritin levels, ICU length-of-stay and outcome. Interactions between organ dysfunction progression and serum iron and ferritin levels changes were investigated. Outcome predictive value of serum ferritin was assessed. Results: Seventy-two patients with a mean ICU length-of-stay of 15 (4.4) days were enrolled in the study. The average age of patients was 62 (16.8) years. There were no significant differences between survivors (39 patients, 54%) and nonsurvivors (33 patients, 46%) regarding demographics, serum iron and ferritin levels and SOFA score on ICU admission. Over time, serum iron levels remained normal or low, while serum ferritin levels statedly increased in all patients. Serum ferritin increase was higher in nonsurvivors than survivors. There was a significant positive correlation between SOFA score and serum ferritin (r = 0.7, 95% CI for r = 0.64 to 0.76, p < 0.01). The predictive outcome accuracy of serum ferritin was similar to the SOFA score. Conclusions: In patients with prolonged ICU stay, serum ferritin dynamics reflects organ dysfunction progression and parallels SOFA score in terms of outcome predictive accuracy.
Effects of Different Doses of Caffeinated Coffee on Muscular Endurance, Cognitive Performance, and Cardiac Autonomic Modulation in Caffeine Naive Female Athletes
Authors: Karayigit Raci , Naderi Alireza , Akca Firat , Cruz Carlos Janssen Gomes da , Sarshin Amir , Yasli Burak Caglar , Ersoz Gulfem , Kaviani Mojtaba
Published: December 2020

Caffeine is widely consumed among elite athletes for its well-known ergogenic properties, and its ability to increase exercise performance. However, studies to date have predominantly focused on the anhydrous form of caffeine in male participants. The aim of the study was to investigate the effect of caffeinated coffee ingestion on lower-upper body muscular endurance, cognitive performance, and heart rate variability (HRV) in female athletes. A total of 17 participants (mean ± standard deviation (SD): age = 23 ± 2 years, body mass = 64 ± 4 kg, height = 168 ± 3 cm) in a randomized cross-over design completed three testing sessions, following the ingestion of 3 mg/kg/bm of caffeine (3COF), 6 mg/kg/bm of caffeine (6COF) provided from coffee or decaffeinated coffee (PLA) in 600 mL of hot water. The testing results included: (1) repetition number for muscular endurance performance; (2): reaction time and response accuracy for cognitive performance; (3): HRV parameters, such as standard deviation of normal-to-normal (NN) intervals (SDNN), standard deviation of successive differences (SDSD), root mean square of successive differences (RMSSD), total power (TP), the ratio of low- and high-frequency powers (LF/HF), high-frequency power (HF), normalized HF (HFnu), low-frequency power (LF), and normalized LF (LFnu). A one-way repeated measures ANOVA revealed that 3COF (p = 0.024) and 6COF (p = 0.036) improved lower body muscular endurance in the first set as well as cognitive performance (p = 0.025, p = 0.035 in the post-test, respectively) compared to PLA. However, no differences were detected between trials for upper body muscular endurance (p = 0.07). Lastly, all HRV parameters did not change between trials (p > 0.05). In conclusion, ingesting caffeinated coffee improved lower body muscular endurance and cognitive performance, while not adversely affecting cardiac autonomic function.
Influence of Mediterranean Diet on Human Gut Microbiota
Authors: Merra Giuseppe , Noce Annalisa , Marrone Giulia , Cintoni Marco , Tarsitano Maria Grazia , Capacci Annunziata , De Lorenzo Antonino
Published: December 2020

Gut microbiota changes correlate with health status. Literature data on gut microbiota show that all dietary changes can induce the alteration of gut microbiota composition. Mediterranean diet (MD) is associated with a reduction of all-cause mortality and in this review, we analyzed its interactions with human microbiota. In particular, we explored the modulation of the human microbiota, in response to MD adherence, focusing the attention on polyphenols, polyunsaturated fatty acids (PUFA) ω-3 and fiber. Evidences suggest that MD is able to modulate the gut microbiota, increasing its diversity. In fact, a Mediterranean-type dietary pattern is associated with specific gut microbiota characteristics. The available evidence, suggests that gut microbiota of subjects that follow a MD is significantly different from subjects that follow a Western diet model. In fact, the latter show an increased gut permeability, which is responsible for metabolic endotoxemia. For this reason, we can speculate that the gut microbiota of the subjects following a MD is able to prevent the onset of chronic non-communicable degenerative diseases, such as cardiovascular diseases and some types of cancer. However, in order to understand these correlations with dietary patterns, controlled intervention studies on the gut microbiota composition and activity are needed.
Association between Nutrition Policies and Student Body Mass Index
Authors: Schwartz Marlene B. , Leider Julien , Cohen Juliana F. W. , Turner Lindsey , Chriqui Jamie F.
Published: December 2020

In response to concerns about childhood obesity, many US states have implemented policies to limit the sale of unhealthy foods and beverages (e.g., snacks, desserts, and sugary drinks) sold in competition with school meal programs (i.e., competitive foods) in order to improve the nutritional environment of schools and support student health. This study measured state-level competitive food and beverage policies that require foods and beverages sold in à la carte lines, vending machines, and school stores to meet strong nutrition standards and tested the hypothesis that students living in states with stronger laws would have lower body mass index (BMI)-for-age percentiles. BMI data from a national sample of 1625 students attending 284 schools from the School Nutrition and Meal Cost Study were linked to state laws coded as part of the National Wellness Policy Study. A survey-adjusted linear regression model accounting for student and school-level characteristics showed that stronger state nutrition policies were associated with lower student BMI scores (coefficient: −0.06, 95% CI: −0.12, −0.00). Additional models indicated that stronger state policies were significantly associated with fewer unhealthy foods and beverages available in schools. These findings suggest that strong regulations on competitive foods and beverages may lead to improvements in the nutritional quality of the school environment and student BMI. Thus, current federal standards regulating snacks in US schools (i.e., Smart Snacks) are an important element of a comprehensive strategy to improve the school nutrition environment and reduce rates of childhood obesity.
Calorie-Restricted Mediterranean and Low-Fat Diets Affect Fatty Acid Status in Individuals with Nonalcoholic Fatty Liver Disease
Authors: Ristic-Medic Danijela , Kovacic Marijana , Takic Marija , Arsic Aleksandra , Petrovic Snjezana , Paunovic Marija , Jovicic Maja , Vucic Vesna
Published: December 2020

Lifestyle modifications are the main support of nonalcoholic fatty liver disease (NAFLD) therapy. Weight loss is one of the primary goals in NAFLD, but the effects of different calorie-restricted diets remain unclear. Thus, we evaluated the effects of two calorie-restricted diets—the Mediterranean diet (Med diet) and low-fat diet—on liver status, cardiometabolic markers, and fatty acid profiles in patients with NAFLD. Twenty-four overweight/moderately obese men were randomly assigned to consume one of these diets. Lipid levels, glucose, insulin, liver enzymes, steatosis, and fatty acid profiles of serum and erythrocytes phospholipids were assessed. After 3 months, all participants had a significant weight loss (>9%), with improvements in waist circumference, body fat %, index of visceral adiposity (VAI), lipid accumulation product, fatty liver (FLI), and hepatic steatosis (HSI) index (p < 0.001). Both diets significantly lowered triglycerides, total and LDL-cholesterol, liver enzymes, fasting glucose, insulin, and HOMA-IR index. Fatty acid profiles were enhanced after both diets, with a significantly decreased n-6/n-3 ratio. Participants on the Med diet had higher levels of HDL-cholesterol and monounsaturated and n-3 docosahexaenoic acids in serum phospholipids and lower levels of saturated fatty acids, triglycerides, TG/HDL ratio, and FLI when compared to participants on the low-fat diet. Our results indicate that dietary patterns and calorie restriction represent central therapeutic issues in the improvement of obesity-related cardiometabolic alterations that are involved in the mechanism of hepatic steatosis. The Med diet may contribute to disease treatment even more than the low-fat diet since it leads to decreased saturated and increased monounsaturated and n-3 polyunsaturated fatty acid status and improved FLI in NAFLD patients.
Perspectives on Larval Behaviour in Biophysical Modelling of Larval Dispersal in Marine, Demersal Fishes
Authors: Leis Jeffrey M.
Published: December 2020

Biophysical dispersal models for marine fish larvae are widely used by marine ecologists and managers of fisheries and marine protected areas to predict movement of larval fishes during their pelagic larval duration (PLD). Over the past 25 years, it has become obvious that behaviour—primarily vertical positioning, horizontal swimming and orientation—of larvae during their PLD can strongly influence dispersal outcomes. Yet, most published models do not include even one of these behaviours, and only a tiny fraction include all three. Furthermore, there is no clarity on how behaviours should be incorporated into models, nor on how to obtain the quantitative, empirical data needed to parameterize models. The PLD is a period of morphological, physiological and behavioural change, which presents challenges for modelling. The present paper aims to encourage the inclusion of larval behaviour in biophysical dispersal models for larvae of marine demersal fishes by providing practical suggestions, advice and insights about obtaining and incorporating behaviour of larval fishes into such models based on experience. Key issues are features of different behavioural metrics, incorporation of ontogenetic, temporal, spatial and among-individual variation, and model validation. Research on behaviour of larvae of study species should be part of any modelling effort.
Immune Checkpoint Inhibitors in Hepatocellular Carcinoma: An Overview
Authors: van Doorn Diederick J. , Takkenberg Robert Bart , Klümpen Heinz-Josef
Published: December 2020

Patients with hepatocellular carcinoma (HCC) face a common type of cancer, which is amongst the most deadly types of cancer worldwide. The therapeutic options range from curative resection or ablation to loco regional therapies in palliative setting and last but not least, systemic treatment. The latter group underwent major changes in the last decade and a half. Since the introduction of sorafenib in 2007, many other systemic treatments have been investigated. Most without success. It took more than ten years before lenvatinib could be added as alternative first-line treatment option. Just recently a new form of systemic treatment, immunotherapy, entered the field of therapeutic options in patients with HCC. Immune checkpoint inhibitors are becoming the new standard of care in patients with HCC. Several reviews reported on the latest phase 1/2 studies and discussed the higher response rates and better tolerability when compared to current standard of care therapies. This review will focus on elaborating the working mechanism of these checkpoint inhibitors, give an elaborate update of the therapeutic agents that are currently available or under research, and will give an overview of the latest trials, as well as ongoing and upcoming trials.
Modelling and Measurement of Magnetically Soft Nanowire Arrays for Sensor Applications
Authors: Ripka Pavel , Grim Vaclav , Mirzaei Mehran , Hrakova Diana , Uhrig Janis , Emmerich Florian , Thielemann Christiane , Hejtmanek Jiri , Kaman Ondrej , Tesar Roman
Published: December 2020

Soft magnetic wires and microwires are currently used for the cores of magnetic sensors. Due to their low demagnetization, they contribute to the high sensitivity and the high spatial resolution of fluxgates, Giant Magnetoimpedance (GMI), and inductive sensors. The arrays of nanowires can be prepared by electrodeposition into predefined pores of a nanoporous polycarbonate membrane. While high coercivity arrays with square loops are convenient for information storage and for bistable sensors such as proximity switches, low coercivity cores are needed for linear sensors. We show that coercivity can be controlled by the geometry of the array: increasing the diameter of nanowires (20 µm in length) from 30 nm to 200 nm reduced the coercivity by a factor of 10, while the corresponding decrease in the apparent permeability was only 5-fold. Finite element simulation of nanowire arrays is important for sensor development, but it is computationally demanding. While an array of 2000 wires can be still modelled in 3D, this is impossible for real arrays containing millions of wires. We have developed an equivalent 2D model, which allows us to solve these large arrays with acceptable accuracy. Using this tool, we have shown that as a core of magnetic sensors, nanowires are efficiently employed only together with microcoils with diameter comparable to the nanowire length.
Optimization of All-Polymer Optical Fiber Oxygen Sensors with Antenna Dyes and Improved Solvent Selection Using Hansen Solubility Parameters
Authors: Inglev Rune , Møller Emil , Højgaard Jonas , Bang Ole , Janting Jakob
Published: December 2020

We present an all-polymer optical fiber sensor for the sensing of dissolved oxygen by phase-fluorometry. The sensing matrix is applied as a film on the fiber end-surface, and consists of poly-methylmethacrylate (PMMA), the oxygen quenchable luminophore platinum-octaethylporphyrin (PtOEP) and the luminophore coumarin 545T for increasing the brightness of PtOEP by way of resonance energy transfer (RET), also called light harvesting. We show that by using Hansen Solubility Parameters (HSPs), it is possible to quantitatively formulate a solvent mixture with a good solubility of the polymer matrix and the luminophores simultaneously. Our approach can readily be extended to other polymers and luminophores and is therefore a valuable tool for researchers working with photoluminescence and polymeric matrices.
Correlations in Joint Spectral and Polarization Imaging
Authors: Courtier Guillaume , Lapray Pierre-Jean , Thomas Jean-Baptiste , Farup Ivar
Published: December 2020

Recent imaging techniques enable the joint capture of spectral and polarization image data. In order to permit the design of computational imaging techniques and future processing of this information, it is interesting to describe the related image statistics. In particular, in this article, we present observations for different correlations between spectropolarimetric channels. The analysis is performed on several publicly available databases that are unified for joint processing. We perform global investigation and analysis on several specific clusters of materials or reflection types. We observe that polarization channels generally have more inter-channel correlation than the spectral channels.
Programable Active Fixator System for Systematic In Vivo Investigation of Bone Healing Processes
Authors: Barcik Jan , Ernst Manuela , Dlaska Constantin E. , Drenchev Ludmil , Zeiter Stephan , Epari Devakara R. , Windolf Markus
Published: December 2020

This manuscript introduces a programable active bone fixator system that enables systematic investigation of bone healing processes in a sheep animal model. In contrast to previous systems, this solution combines the ability to precisely control the mechanical conditions acting within a fracture with continuous monitoring of the healing progression and autonomous operation of the system throughout the experiment. The active fixator system was implemented on a double osteotomy model that shields the experimental fracture from the influence of the animal’s functional loading. A force sensor was integrated into the fixator to continuously measure stiffness of the repair tissue as an indicator for healing progression. A dedicated control unit was developed that allows programing of different loading protocols which are later executed autonomously by the active fixator. To verify the feasibility of the system, it was implanted in two sheep with different loading protocols, mimicking immediate and delayed weight-bearing, respectively. The implanted devices operated according to the programmed protocols and delivered seamless data over the whole course of the experiment. The in vivo trial confirmed the feasibility of the system. Hence, it can be applied in further preclinical studies to better understand the influence of mechanical conditions on fracture healing.
Construction of a Sensitive and Speed Invariant Gearbox Fault Diagnosis Model Using an Incorporated Utilizing Adaptive Noise Control and a Stacked Sparse Autoencoder-Based Deep Neural Network
Authors: Nguyen Cong Dai , Prosvirin Alexander E. , Kim Cheol Hong , Kim Jong-Myon
Published: December 2020

Gearbox fault diagnosis based on the analysis of vibration signals has been a major research topic for a few decades due to the advantages of vibration characteristics. Such characteristics are used for early fault detection to guarantee the enhanced safety of complex systems and their cost-effective operation. There exist many fault diagnosis models that have been developed for classifying various fault types in gearboxes. However, the classification results of the conventional fault classification models degrade when they are applied to gearbox systems with multi-level tooth cut gear (MTCG) faults operating under variable shaft speeds. These conditions cause difficulty in discriminating the gear fault types. Due to the improved computational capabilities of modern systems, the application of deep neural networks (DNNs) is getting popular in a variety of research fields, such as image and natural language processing. DNNs are capable of improving the classification results even when addressing complex problems such as diagnosing gearbox MTCG faults. In this research, an adaptive noise control (ANC) and a stacked sparse autoencoder–based deep neural network (SSA-DNN) are used to construct a sensitive fault diagnosis model that can diagnose a gearbox system with MTCG fault types under varying shaft rotation speeds, despite its complicatedness. An ANC is applied to gear vibration characteristics to remove a significant level of noise along the frequency spectrum of vibration signals to fix the most fault-informative components of each fault case. Next, the autoencoder learns the gear faults characteristic features from these fault-informative components to separate the fault types considered in this study. Furthermore, the implementation of the SSA-DNN is substituted for feature extraction, feature selection, and the classification processes in traditional fault diagnosis schemes by high-performance unity. The experimental results show that the proposed model outperforms conventional methodologies with higher classification accuracy.
Detection and Localization of Partial Discharge in Connectors of Air Power Lines by Means of Ultrasonic Measurements and Artificial Intelligence Models
Authors: Samaitis Vykintas , Mažeika Liudas , Jankauskas Audrius , Rekuvienė Regina
Published: December 2020

According to the statistics, 40% of unplanned disruptions in electricity distribution grids are caused by failure of equipment in high voltage (HV) transformer substations. These damages in most cases are caused by partial discharge (PD) phenomenon which progressively leads to false operation of equipment. The detection and localization of PD at early stage can significantly reduce repair and maintenance expenses of HV assets. In this paper, a non-invasive PD detection and localization solution has been proposed, which uses three ultrasonic sensors arranged in an L shape to detect, identify and localize PD source. The solution uses a fusion of ultrasonic signal processing, machine learning (ML) and deep learning (DL) methods to classify and process PD signals. The research revealed that the support vector machines classifier performed best among two other classifiers in terms of sensitivity and specificity while classifying discharge and surrounding noise signals. The proposed ultrasonic signal processing methods based on binaural principles allowed us to achieve an experimental lateral source positioning error of 0.1 m by using 0.2 m spacing between L shaped sensors. Finally, an approach based on DL was suggested, which allowed us to detect a single PD source in optical images and, in such a way, to provide visual representation of PD location.
Unconventionally Designed Tracking Loop Adaptable to Plasma Sheath Channel for Hypersonic Vehicles
Authors: Shi Lei , Yuan Shurong , Yao Bo
Published: December 2020

An aircraft that moves through the atmosphere at hypersonic speed is covered by plasma sheath, which causes random and fast time-varying amplitude attenuation and phase fluctuation in received signals. This paper comprehensively analyzes the mechanism of the amplitude attenuation effects on a traditional phase-locked loop (PLL), which is always ignored in traditional scenarios (such as satellite telemetry and vehicle communication). Simulation results and theoretical analysis showed that traditional PLL does not work reliably for signal carrier tracking with the severe time-varying amplitude attenuation of the plasma sheath channel. In this paper, an unconventionally designed Kalman filter (KF) tracking loop that is aware of phase dynamics and amplitude attenuation fluctuation for hypersonic vehicles is proposed. To introduce time-varying amplitude attenuation into the proposed KF-based tracking loop, the amplitude attenuation is first modeled with an autoregressive model. The statistical characteristics of the amplitude and phase fluctuation are then incorporated into the state equation and observation equation. Simulation results indicate that the proposed tracking loop is stable when the signal-to-noise ratio is −10 dB with the Ka band, even in the most severe flight environment for hypersonic vehicles.
A Blockchain-Based Multi-Mobile Code-Driven Trust Mechanism for Detecting Internal Attacks in Internet of Things
Authors: Tariq Noshina , Asim Muhammad , Khan Farrukh Aslam , Baker Thar , Khalid Umair , Derhab Abdelouahid
Published: December 2020

A multitude of smart things and wirelessly connected Sensor Nodes (SNs) have pervasively facilitated the use of smart applications in every domain of life. Along with the bounties of smart things and applications, there are hazards of external and internal attacks. Unfortunately, mitigating internal attacks is quite challenging, where network lifespan (w.r.t. energy consumption at node level), latency, and scalability are the three main factors that influence the efficacy of security measures. Furthermore, most of the security measures provide centralized solutions, ignoring the decentralized nature of SN-powered Internet of Things (IoT) deployments. This paper presents an energy-efficient decentralized trust mechanism using a blockchain-based multi-mobile code-driven solution for detecting internal attacks in sensor node-powered IoT. The results validate the better performance of the proposed solution over existing solutions with 43.94% and 2.67% less message overhead in blackhole and greyhole attack scenarios, respectively. Similarly, the malicious node detection time is reduced by 20.35% and 11.35% in both blackhole and greyhole attacks. Both of these factors play a vital role in improving network lifetime.
Evaluation of Structurally Distorted Split GFP Fluorescent Sensors for Cell-Based Detection of Viral Proteolytic Activity
Authors: Guerreiro Miguel R. , Fernandes Ana R. , Coroadinha Ana S.
Published: December 2020

Cell-based assays are essential for virus functional characterization in fundamental and applied research. Overcoming the limitations of virus-labelling strategies while allowing functional assessment of critical viral enzymes, virus-induced cell-based biosensors constitute a powerful approach. Herein, we designed and characterized different cell-based switch-on split GFP sensors reporting viral proteolytic activity and virus infection. Crucial to these sensors is the effective—yet reversible—fluorescence off-state, through protein distortion. For that, single (protein embedment or intein-mediated cyclization) or dual (coiled-coils) distortion schemes prevent split GFP self-assembly, until virus-promoted proteolysis of a cleavable sequence. All strategies showed their applicability in detecting viral proteolysis, although with different efficiencies depending on the protease. While for tobacco etch virus protease the best performing sensor was based on coiled-coils (signal-to-noise ratio, SNR, 97), for adenovirus and lentivirus proteases it was based on GFP11 cyclization (SNR 3.5) or GFP11 embedment distortion (SNR 6.0), respectively. When stably expressed, the sensors allowed live cell biosensing of adenovirus infection, with sensor fluorescence activation 24 h post-infection. The structural distortions herein studied are highly valuable in the development of cellular biosensing platforms. Additionally highlighted, selection of the best performing strategy is highly dependent on the unique properties of each viral protease.
Comparative Analysis of Kinect-Based and Oculus-Based Gaze Region Estimation Methods in a Driving Simulator
Authors: González-Ortega David , Díaz-Pernas Francisco Javier , Martínez-Zarzuela Mario , Antón-Rodríguez Míriam
Published: December 2020

Driver’s gaze information can be crucial in driving research because of its relation to driver attention. Particularly, the inclusion of gaze data in driving simulators broadens the scope of research studies as they can relate drivers’ gaze patterns to their features and performance. In this paper, we present two gaze region estimation modules integrated in a driving simulator. One uses the 3D Kinect device and another uses the virtual reality Oculus Rift device. The modules are able to detect the region, out of seven in which the driving scene was divided, where a driver is gazing at in every route processed frame. Four methods were implemented and compared for gaze estimation, which learn the relation between gaze displacement and head movement. Two are simpler and based on points that try to capture this relation and two are based on classifiers such as MLP and SVM. Experiments were carried out with 12 users that drove on the same scenario twice, each one with a different visualization display, first with a big screen and later with Oculus Rift. On the whole, Oculus Rift outperformed Kinect as the best hardware for gaze estimation. The Oculus-based gaze region estimation method with the highest performance achieved an accuracy of 97.94%. The information provided by the Oculus Rift module enriches the driving simulator data and makes it possible a multimodal driving performance analysis apart from the immersion and realism obtained with the virtual reality experience provided by Oculus.
Morphological Effects in SnO2 Chemiresistors for Ethanol Detection: A Review in Terms of Central Performances and Outliers
Authors: Ponzoni Andrea
Published: December 2020

SnO2 is one of the most studied materials in gas sensing and is often used as a benchmark for other metal oxide-based gas sensors. To optimize its structural and functional features, the fine tuning of the morphology in nanoparticles, nanowires, nanosheets and their eventual hierarchical organization has become an active field of research. In this paper, the different SnO2 morphologies reported in literature in the last five years are systematically compared in terms of response amplitude through a statistical approach. To have a dataset as homogeneous as possible, which is necessary for a reliable comparison, the analysis is carried out on sensors based on pure SnO2, focusing on ethanol detection in a dry air background as case study. Concerning the central performances of each morphology, results indicate that none clearly outperform the others, while a few individual materials emerge as remarkable outliers with respect to the whole dataset. The observed central performances and outliers may represent a suitable reference for future research activities in the field.
Exploring New Potential Applications for Hand Exoskeletons: Power Grip to Assist Human Standing
Authors: Diez Jorge A. , Santamaria Victor , Khan Moiz I. , Catalán José M. , Garcia-Aracil Nicolas , Agrawal Sunil K.
Published: December 2020

Hand exoskeleton potential applications reach further than grasping or assistance during manipulation. In this paper, we present a preliminary study of how this technology can be applied in order to improve performance during standing to help the user to keep balance under perturbations. Non-impaired users wearing a hand exoskeleton gripping a hand rail were pushed by a cable-driven robot, so that their standing equilibrium was perturbed. The center of pressure, surface electromyography, and interaction force data were recorded in order to assess the performance of users and their postural strategy. The results showed that users could keep their balance with the same outcomes using their bare hands and the hand exoskeleton. However, when wearing the exoskeleton, a higher muscular activity was registered in hand flexor muscles. This is also supported by the grasping force, which shows that users stretched their hand more than expected when wearing the hand exoskeleton. This paper concludes that it is possible that the lack of tactile feedback could lead to over compensation in the grasping. Therefore, the next studies will aim to check whether this effect can be reversed by training users to wear the exoskeleton.
Consistency of the Empirical Distributions of Navigation Positioning System Errors with Theoretical Distributions—Comparative Analysis of the DGPS and EGNOS Systems in the Years 2006 and 2014
Authors: Specht Mariusz
Published: December 2020

Positioning systems are used to determine position coordinates in navigation (air, land and marine). The accuracy of an object’s position is described by the position error and a statistical analysis can determine its measures, which usually include: Root Mean Square (RMS), twice the Distance Root Mean Square (2DRMS), Circular Error Probable (CEP) and Spherical Probable Error (SEP). It is commonly assumed in navigation that position errors are random and that their distribution are consistent with the normal distribution. This assumption is based on the popularity of the Gauss distribution in science, the simplicity of calculating RMS values for 68% and 95% probabilities, as well as the intuitive perception of randomness in the statistics which this distribution reflects. It should be noted, however, that the necessary conditions for a random variable to be normally distributed include the independence of measurements and identical conditions of their realisation, which is not the case in the iterative method of determining successive positions, the filtration of coordinates or the dependence of the position error on meteorological conditions. In the preface to this publication, examples are provided which indicate that position errors in some navigation systems may not be consistent with the normal distribution. The subsequent section describes basic statistical tests for assessing the fit between the empirical and theoretical distributions (Anderson-Darling, chi-square and Kolmogorov-Smirnov). Next, statistical tests of the position error distributions of very long Differential Global Positioning System (DGPS) and European Geostationary Navigation Overlay Service (EGNOS) campaigns from different years (2006 and 2014) were performed with the number of measurements per session being 900’000 fixes. In addition, the paper discusses selected statistical distributions that fit the empirical measurement results better than the normal distribution. Research has shown that normal distribution is not the optimal statistical distribution to describe position errors of navigation systems. The distributions that describe navigation positioning system errors more accurately include: beta, gamma, logistic and lognormal distributions.
Recognition of Bimolecular Logic Operation Pattern Based on a Solid-State Nanopore
Authors: Yan Han , Zhang Zhen , Weng Ting , Zhu Libo , Zhang Pang , Wang Deqiang , Liu Quanjun
Published: December 2020

Nanopores have a unique advantage for detecting biomolecules in a label-free fashion, such as DNA that can be synthesized into specific structures to perform computations. This method has been considered for the detection of diseased molecules. Here, we propose a novel marker molecule detection method based on DNA logic gate by deciphering a variable DNA tetrahedron structure using a nanopore. We designed two types of probes containing a tetrahedron and a single-strand DNA tail which paired with different parts of the target molecule. In the presence of the target, the two probes formed a double tetrahedron structure. As translocation of the single and the double tetrahedron structures under bias voltage produced different blockage signals, the events could be assigned into four different operations, i.e., (0, 0), (0, 1), (1, 0), (1, 1), according to the predefined structure by logic gate. The pattern signal produced by the AND operation is obviously different from the signal of the other three operations. This pattern recognition method has been differentiated from simple detection methods based on DNA self-assembly and nanopore technologies.
Optical Designs with Curved Detectors for Fiber Bragg Grating Interrogation Monitors
Authors: Muslimov Eduard , Pavlycheva Nadezhda , Hugot Emmanuel , Lombardo Simona , Nureev Ilnur , Morozov Oleg
Published: December 2020

In this paper, we evaluate the application of curved detectors and freeform optics technologies for fiber Bragg gratings (FBGs) interrogation monitors design. It is shown that, in a high-dispersion spectrograph scheme, the camera part operates in special conditions, which result in a field curvature change. This field curvature can be compensated by the use of a curved detector. When used together with freeform optics, the curved detectors allow for reduction of the number of optical components to two or even one element by merging their functions. Three design examples for the range of 810–860 nm reaching the spectral resolution limit of 89–139 pm at NA=0.14 are presented to demonstrate the achieved performance and the technological trade-offs.
Position Tracking Techniques Using Multiple Receivers for Anti-Drone Systems
Authors: Shin Jae-Min , Kim Yu-Sin , Ban Tae-Won , Choi Suna , Kang Kyu-Min , Ryu Jong-Yeol
Published: December 2020

The need for drone traffic control management has emerged as the demand for drones increased. Particularly, in order to control unauthorized drones, the systems to detect and track drones have to be developed. In this paper, we propose the drone position tracking system using multiple Bluetooth low energy (BLE) receivers. The proposed system first estimates the target’s location, which consists of the distance and angle, while using the received signal strength indication (RSSI) signals at four BLE receivers and gradually tracks the target based on the estimated distance and angle. We propose two tracking algorithms, depending on the estimation method and also apply the memory process, improving the tracking performance by using stored previous movement information. We evaluate the proposed system’s performance in terms of the average number of movements that are required to track and the tracking success rate.
Uniting Electroceutical and Cosmeceutical Interventions in Combating Coronavirus Using Ԑ-Poly-l-Lysine
Authors: Hathout Rania M. , Kassem Dina H.
Published: December 2020

Combating the COVID-19 pandemic warrants the exploitation of all the available tools and implies a major focus on both the biological and the physical properties of the causing virus (SARS-CoV2). We hereby introduce a new prophylaxis hypothesis by decreasing the viral load in the body entrances such as the nose and the mouth using pharmaceutical and cosmeceutical preparations that incorporate viral electrostatic repulsive nanofibers fabricated from an abundant marine-derived or a fermentation product polymer; Ԑ-poly-l-lysine was prepared using the electrospinning technique.
Evaluating Disruptive Innovation Project Management Capabilities
Authors: Zubizarreta Mikel , Ganzarain Jaione , Cuadrado Jesús , Lizarralde Rafael
Published: December 2020

Firms must adapt to a business environment in constant flux. Economic and political factors and the constant interruption of new technologies force firms and organizations to change and to adapt, so that they are not left behind. Over recent years, the development of disruptive innovations has completely revolutionized past scenarios. These innovations break with what is already established and firms from various sectors face no choice other than to incorporate them into their project management portfolios, so as to ensure survival and business sustainability. Using MIVES methodology as its foundation, a business sustainability management model is presented in this paper for the management of disruptive innovation projects that a firm may wish to develop within a given sector. The management model is designed to facilitate disruptive innovation project management for firms within technological-industrial sectors, by assessing the sustainability of the project. The model is applied to two firms, one from the machine-tooling sector and another from the construction sector. Finally, a sensitivity analysis was performed, the results of which verified the validity and the stability of the proposed model.
Spatial Variation in Tourism and Investment Potential in the Context of Sustainable Development—A Case Study of Staszowski County
Authors: Lisiak-Zielińska Marta , Ziernicka-Wojtaszek Agnieszka
Published: December 2020

The aim of the study was to assess spatial variation in the tourism and investment potential of Staszowski County and to indicate possibilities for sustainable development of tourism in the area. The method of synthetic measures was used for the analysis, taking into account 45 features characterizing the tourism and investment space, including tourism assets, the state and protection of the environment, transport accessibility, hotels, eating establishments and supplementary facilities, service and technical infrastructure, population relations, and commune finances. The features were analysed using geostatistical and statistical tools. The analyses, despite certain methodological limitations, indicated that there is still great potential for more sustainable development of tourism in the county. The spatial distribution of the features did not show a tendency to form clusters, but most of them were located in the centre of the study area, in two communes—Staszów and Połaniec. The most attractive commune in terms of tourism and investment was Staszów, with strong tourism assets and a well-developed service and technical infrastructure. This commune, however, has one of the lowest environmental protection indices in the county.
Sustainability, Corporate Social Responsibility, and Performance in the Spanish Wine Sector
Authors: Muñoz Rosa M. , Fernández M. Valle , Salinero Yolanda
Published: December 2020

This paper analyzes the Corporate Social Responsibility (CSR) of a sample of wineries in Spain and its effect on the companies’ performance. We used a questionnaire created with a validated scale that includes environmental and social dimensions. The final sample was made up of 127 firms that participated in the National Wine Fair (FENAVIN) in 2019, and this was analyzed using a cluster analysis and means contrast to verify whether a CSR-performance relationship exists. The performance was measured using the average return on assets (ROA) for the prior three years. The results obtained do not support the general opinion that enterprises involved with CSR achieve better results. On the contrary, we found that wineries that are more environmentally responsible are the least profitable and that those with more socially responsible behavior do not have a significant CSR-performance relationship.
Understandings, Practices and Human-Environment Relationships—A Meta-Ethnographic Analysis of Local and Indigenous Climate Change Adaptation and Mitigation Strategies in Selected Pacific Island States
Authors: von Seggern Janne
Published: December 2020

Local and Indigenous knowledge systems worldwide indicate adaptation and mitigation strategies to climate change. Particularly in regions that are massively affected by climatic changes, such as the Pacific Island States, there is a need for increased and combined research on the role which these knowledge systems can play internationally. For this reason, this article provides a synthesis of empirical results and approaches to local and Indigenous climate change adaptation and mitigation strategies in selected South Pacific Island States by using a meta-ethnographic approach. The reviewed literature is associated with the sub-disciplinary perspective of the Anthropology of Climate Change. The results of the meta-ethnographic analysis are discussed based on three thematic focal points: First, the empirical ground of local understandings of climate change and its theoretical conceptualization(s) are constituted. Second, the results of practices for adaptation to climate change are synthesized and presented in detail throughout one example. Third, the synthesis of climate change mitigation practices is outlined with a specific focus on human-environment relationships.