bluuebunny/crossref_metadata_2025 huggingface dataset:
Oxidative Chemical Stressors Alter the Physiological State of the Nasal Olfactory Mucosa of Atlantic Salmon
Authors: Lazado Carlo C. , Voldvik Vibeke , Breiland Mette W. , Osório João , Hansen Marianne H. S. , Krasnov Aleksei
Published: November 2020

The olfactory organs of fish have vital functions for chemosensory and defence. Though there have been some ground-breaking discoveries of their involvement in immunity against pathogens in recent years, little is known about how they respond to non-infectious agents, such as exogenous oxidants, which fish encounter regularly. To this end, we employed Atlantic salmon (Salmo salar) as a model to study the molecular responses at the nasal olfactory mucosa of a teleost fish when challenged with oxidants. Microarray analysis was employed to unravel the transcriptional changes at the nasal olfactory mucosa following two types of in vivo exposure to peracetic acid (PAA), a highly potent oxidative agent commonly used in aquaculture: Trial 1: periodic and low dose (1 ppm, every 3 days over 45 days) to simulate a routine disinfection; and Trial 2: less frequent and high dose (10 ppm for 30 min, every 15 days, 3 times) to mimic a bath treatment. Furthermore, leukocytes from the olfactory organ were isolated and exposed to PAA, as well as to hydrogen peroxide (H2O2) and acetic acid (AA)—the two other components of PAA trade products—to perform targeted cellular and molecular response profiling. In the first trial, microarrays identified 32 differentially expressed genes (DEG) after a 45-day oxidant exposure. Erythrocyte-specific genes were overly represented and substantially upregulated following exogenous oxidant exposure. In Trial 2, in which a higher dose was administered, 62 DEGs were identified, over 80% of which were significantly upregulated after exposure. Genes involved in immune response, redox balance and stress, maintenance of cellular integrity and extracellular matrix were markedly affected by the oxidant. All chemical stimuli (i.e., PAA, H2O2, AA) significantly affected the proliferation of nasal leukocytes, with indications of recovery observed in PAA- and H2O2-exposed cells. The migration of nasal leukocytes was promoted by H2O2, but not much by PAA and AA. The three chemical oxidative stressors triggered oxidative stress in nasal leukocytes as indicated by an increase in the intracellular reactive oxygen species level. This resulted in the mobilisation of antioxidant defences in the nasal leukocytes as shown by the upregulation of crucial genes for this response network. Though qPCR revealed changes in the expression of selected cytokines and heat shock protein genes following in vitro challenge, the responses were stochastic. The results from the study advance our understanding of the role that the nasal olfactory mucosa plays in host defence, particularly towards oxidative chemical stressors.
Oxidative Stress in Endurance Cycling Is Reduced Dose-Dependently after One Month of Re-Esterified DHA Supplementation
Authors: de Salazar Lydia , Contreras Carlos , Torregrosa-García Antonio , Luque-Rubia Antonio , Ávila-Gandía Vicente , Domingo Joan , López-Román Francisco
Published: November 2020

Docosahexaenoic acid (DHA) supplementation can reduce exercise-induced oxidative stress generated during long aerobic exercise, with the minimum dose yet to be elucidated for physically active subjects. In this study, we performed a dose finding with re-esterified DHA in triglyceride form in a randomized double-blind parallel trial at different doses (350, 1050, 1750, and 2450 mg a day) for 4 weeks in males engaged in regular cycling (n = 100, 7.6 ± 3.7 h/week). The endogenous antioxidant capacity of DHA was quantified as a reduction in the levels of the oxidative stress marker 8-hydroxy-2′-deoxyguanosine (8-OHdG) recollected in 24-h urine samples after 90 min of constant load cycling before and after intervention. To ascertain incorporation of DHA, erythrocyte polyunsaturated fatty acid (PUFA) composition was compared along groups. We found a dose-dependent antioxidant capacity of DHA from 1050 mg with a trend to neutralization for the highest dose of 2450 mg (placebo: n = 13, F = 0.041; 350 mg: n = 10, F = 0.268; 1050 mg: n = 11, F = 7.112; 1750 mg: n = 12, F = 9.681; 2450 mg: n = 10, F = 15.230). In the erythrocyte membrane, the re-esterified DHA increased DHA and omega-3 percentage and decreased omega 6 and the omega-6 to omega-3 ratio, while Eicosapentaenoic acid (EPA) and PUFA remained unchanged. Supplementation of re-esterified DHA exerts a dose-dependent endogenous antioxidant property against moderate-intensity long-duration aerobic exercise in physically active subjects when provided at least 1050 mg a day for 4 weeks.
Systematic Review and Meta-Analysis of the Blood Glutathione Redox State in Chronic Obstructive Pulmonary Disease
Authors: Sotgia Salvatore , Paliogiannis Panagiotis , Sotgiu Elisabetta , Mellino Sabrina , Zinellu Elisabetta , Fois Alessandro G. , Pirina Pietro , Carru Ciriaco , Mangoni Arduino A. , Zinellu Angelo
Published: November 2020

The aim of this systematic review and meta-analysis was to assess the blood concentrations of the total and reduced forms of the low-molecular-weight antioxidant thiol glutathione (GSH) in chronic obstructive pulmonary disease (COPD) patients in comparison to healthy individuals. A literature search was conducted in the PubMed and Web of Science databases from inception until June 2020. In the 18 studies identified (involving a total of 974 COPD patients and 631 healthy controls), the pooled reduced GSH concentrations were significantly lower in patients with COPD than controls (SMD  =  −3.04, 95% CI = −4.42 to −1.67; p  <  0.001). By contrast, the pooled total GSH concentrations were significantly higher in patients with COPD than controls (SMD = 0.42, 95% CI = 0.11 to 0.73; p = 0.009). Our meta-analysis showed that the blood concentrations of reduced GSH, even in the presence of higher total GSH concentrations, were significantly lower in patients with COPD when compared to healthy controls. This suggests that an impaired antioxidant defense system plays an important role in the pathogenesis of COPD.
GPON PLOAMd Message Analysis Using Supervised Neural Networks
Authors: Tomasov Adrian , Holik Martin , Oujezsky Vaclav , Horvath Tomas , Munster Petr
Published: November 2020

This paper discusses the possibility of analyzing the orchestration protocol used in gigabit-capable passive optical networks (GPONs). Considering the fact that a GPON is defined by the International Telecommunication Union Telecommunication sector (ITU-T) as a set of recommendations, implementation across device vendors might exhibit few differences, which complicates analysis of such protocols. Therefore, machine learning techniques are used (e.g., neural networks) to evaluate differences in GPONs among various device vendors. As a result, this paper compares three neural network models based on different types of recurrent cells and discusses their suitability for such analysis.
An Energy Saving Road Sweeper Using Deep Vision for Garbage Detection
Authors: Donati Luca , Fontanini Tomaso , Tagliaferri Fabrizio , Prati Andrea
Published: November 2020

Road sweepers are ubiquitous machines that help preserve our cities cleanliness and health by collecting road garbage and sweeping out dirt from our streets and sidewalks. They are often very mechanical instruments, needing to operate in harsh conditions dealing with all sorts of abandoned trash and natural garbage. They are usually composed of rotating brushes, collector belts and bins, and sometimes water or air streams. All of these mechanical tools are usually high in power demand and strongly subject to wear and tear. Moreover, due to the simple working logic often implied by these cleaning machines, these tools work in an “always on”/“max power” state, and any further regulation is left to the pilot. Therefore, adding artificial intelligence able to correctly operate these tools in a semi-automatic way would be greatly beneficial. In this paper, we propose an automatic road garbage detection system, able to locate with great precision most types of road waste, and to correctly instruct a road sweeper in order to handle them. With this simple addition to an existing sweeper, we will be able to save more than 80% electrical power currently absorbed by the cleaning systems and reduce by the same amount brush weariness (prolonging their lifetime). This is done by choosing when to use the brushes and when not to, with how much strength, and where. The only hardware components needed by the system will be a camera and a PC board able to read the camera output (and communicate via CanBus). The software of the system will be mainly composed of a deep neural network for semantic segmentation of images, and a real-time software program to control the sweeper actuators with the appropriate timings. To prove the claimed results, we run extensive tests onboard of such a truck, as well as benchmark tests for accuracy, sensitivity, specificity and inference speed of the system.
FEM Analysis and Sensor-Based Measurement Scheme of Current Distribution for Grounding Electrode
Authors: Zhu Li , Jiang Hui , Yang Fan , Luo Hanwu , Li Wenzhen , Han Jianjun
Published: November 2020

The current distribution of the grounding electrode in a high-voltage direct current (HVDC) transmission system affects the state of power equipment in its vicinity, which depends on the soil resistivity and shape of the grounding electrode. In this paper, current distribution in the vicinity of an ±800 kV grounding electrode is investigated by simulation and experiments. Firstly, the model to calculate the current distribution with two typical frozen soils is set up, and simulation models and experimental platforms are established; meanwhile, the finite element method (FEM) is used to calculate the current and potential dispersion of linear, cross-shaped, and ring-shaped grounding electrodes in the simulation models. After obtaining the lab current data from the simulation, an innovative method based on a “drainage wire” with a Hall sensor is proposed to measure the current in an experimental setup. The results show that current and potential distribution characteristics are related to the shape of the grounding electrode and soil resistivity. Meanwhile, the current measurement scheme can measure the current in soil with a lower error. This article concludes that these two typical models can reduce the complexity of frozen soil analysis, and the measurement scheme can accurately monitor the current to reduce the damage to the surrounding power equipment.
Data-Driven Test Scenario Generation for Cooperative Maneuver Planning on Highways
Authors: Knies Christian , Diermeyer Frank
Published: November 2020

Future automated vehicles will have to meet the challenge of anticipating the intentions of other road users in order to plan their own behavior without compromising safety and efficiency of the surrounding road traffic. Therefore, the research area of cooperative driving deals with maneuver-planning algorithms that enable vehicles to behave cooperatively in interactive traffic scenarios. To prove the functionality of these algorithms, single test scenarios are used in the current body of literature. The use of a single, exemplary scenario bears the risk that the presented approach only works in the presented scenario and thus no general statement can be made about the performance of the algorithm. Furthermore, there is a risk that fictitious traffic scenarios may be solved which do not occur in reality. Therefore, we present a procedure for generating test scenarios based on real-world traffic datasets that require cooperation of at least one of the involved vehicles and thus are challenging from the perspective of cooperation. This procedure is applied to a large highway traffic dataset, resulting in a test scenario catalog that allows a comprehensive performance evaluation. The extracted scenarios are clustered according to the cooperative actions used to solve the respective scenario, which enables a more detailed understanding of the underlying cooperative mechanisms. In order to serve as a basis for making comparisons between different behavior planners and thus contribute to the development of future maneuver planning algorithms, a tool to extract the test scenarios from the used traffic dataset is made publicly available.
Effect of Bioactivity of Surface Topography and Coating Forming by Infrared Light-Induced on Titanium for Bone Repair
Authors: Tang Cheng-Ming , Fan Fang-Yu , Lin Wei-Ting , Wang Liping , Lin Wei-Chun
Published: November 2020

Calcium ions and phosphate ions are usually present in biological organisms and human bodies. Different ratios of calcium to phosphorus result in different types of calcium-to-phosphorus crystals. Hydroxyapatite (HA) is the main component of human hard bony tissues. It has good biocompatibility and is often used in bone repair. With the addition of cobalt ions, it can act as a hypoxia-inducing factor to accelerate the regeneration of hard bony tissues. At present, the laser-assisted biomimetic (LAB) method can very quickly deposit calcium phosphate coatings, which can be used on polymer and titanium surfaces. In this study, we first used anodization treatment (with TiO2 nanotubes (TNTs)), alkali treatment (with NaOH), and acid treatment (with HCl) to form nanopore structures on titanium surfaces in the laboratory. Subsequently, LAB treatment was used to deposit calcium phosphate and cobalt-substituted hydroxyapatite onto titanium pieces with different surface treatments. The results showed that smaller holes resulted in better deposition (TNTs), and controlling the pH value in the solution changed the crystal morphology. LAB treatment imbued the titanium surface with super-hydrophilic properties and improved biocompatibility. A human osteoblast cell line (MG-63) used for the cell viability test showed that LAB treatment can improve cell growth. In particular, TNT-CoHA (cobalt-substituted hydroxyapatite) cells grew the best. Immersion in simulated bodily fluid confirmed that LAB treatment with a CoHA solution improved the hydrophilicity, biocompatibility, and bioactivity of titanium surfaces. It is hoped that this study provides useful information for surface coating of biomedical materials in the future.
An Attention-Based Graph Neural Network for Spam Bot Detection in Social Networks
Authors: Zhao Chensu , Xin Yang , Li Xuefeng , Zhu Hongliang , Yang Yixian , Chen Yuling
Published: November 2020

With the rapid development of social networks, spam bots and other anomaly accounts’ malicious behavior has become a critical information security problem threatening the social network platform. In order to reduce this threat, the existing research mainly uses feature-based detection or propagation-based detection, and it applies machine learning or graph mining algorithms to identify anomaly accounts in social networks. However, with the development of technology, spam bots are becoming more advanced, and identifying bots is still an open challenge. This paper proposes a new semi-supervised graph embedding model based on a graph attention network for spam bot detection in social networks. This approach constructs a detection model by aggregating features and neighbor relationships, and learns a complex method to integrate the different neighborhood relationships between nodes to operate the directed social graph. The new model can identify spam bots by capturing user features and two different relationships among users in social networks. We compare our method with other methods on real-world social network datasets, and the experimental results show that our proposed model achieves a significant and consistent improvement.
An Estimator of the Resistance of Large Grounding Electrodes from Its Geometric Characterization
Authors: Denche Gregorio , Faleiro Eduardo , Asensio Gabriel , Moreno Jorge
Published: November 2020

An estimator of the grounding resistance of large extension electrodes from the total length and geometric properties of the electrode is proposed in this work. The approximation is valid for electrodes buried in a soil that can be assumed as homogeneous and it will be verified that the resistance estimation improves as electrode size increases. Both the burial depth and the radius of the conductors, within certain practical limits, have little effect on the value of the grounding resistance. The shape and size of the electrode are defined by a geometric index that measures the degree of compaction of the conductors that make it up, which has the greatest weight in the final value of the resistance. The expression obtained to quantify the estimate of the grounding resistance is tested in several numerical examples and in a currently operating grounding electrode, obtaining in all cases an estimated value of the resistance reasonably close to the true value.
Macro-Modelling Approach for the In-Plane Cyclic Response of Cold-Formed Steel Partition Walls
Authors: Shin Dong-Hyeon , Kim Hyung-Joon
Published: November 2020

Past earthquakes demonstrate that non-structural elements could be vulnerable to a relatively low intensity ground shaking which induces negligible structural damage. The study aims to improve previously developed macro-models of cold-formed steel (CFS) partition walls to properly capture their in-plane cyclic response and damage states of important components in a CFS partition wall under imposed excitation. An effective analytical modelling approach is adopted for a simple modelling procedure and less computational effort. The proposed analysis model of partition walls consisting of several lumped spring elements is verified using direct comparison with two full scale CFS partition wall tests. The analytical and experimental results are compared in terms of force–displacement relations, dissipated energy, and an influential damage mechanism of components consisting of partition walls. The comparison shows that the analytical model well captures the experimental response such as the overall strength and stiffness degradation and pinching behavior. Moreover, the damage mechanism predicted by the analytical model is in good agreement with that observed during the tests.
Antioxidant and Potentially Anti-Inflammatory Properties in Pasta Fortified with Onion Skin
Authors: Michalak-Majewska Monika , Złotek Urszula , Szymanowska Urszula , Szwajgier Dominik , Stanikowski Piotr , Matysek Małgorzata , Sobota Aldona
Published: November 2020

In recent years, food industries have produced a large volume of waste, which is an ecological and economic problem. Fruit and vegetable by-products can also be promising sources of functional compounds, with documented pro-health potential. The goal of the study was to evaluate the impact of the addition of various concentrations of onion skin powder on the antioxidant and anti-inflammatory properties associated with changes in the quercetin content in uncooked and cooked pastas. The total contents of phenolic acids, quercetin, and antioxidant activity were determined. The anti-inflammatory activity was demonstrated by inhibitory effects on lipoxygenase (LOX) in vitro activity. Dry onion skin is the source of quercetin in analyzed pastas. The concentrations of these compounds gradually and significantly increased with increases in the vegetable component in fortified pastas. Additionally, a positive correlation between the content of phenolic compounds and antioxidant activity of pastas fortified with onion skin powder was noted. The process of cooking caused enhancement in the antioxidant and anti-inflammatory potential. These qualities of pastas resulted from the presence of dry onion skin with high pro-health activities. Fortification of pasta with onion skin powder could be a starting point to benefit onion industrial by-products and produce new healthy food products.
A Game Theoretic Approach for Energy Sharing in the Italian Renewable Energy Communities
Authors: Moncecchi Matteo , Meneghello Stefano , Merlo Marco
Published: November 2020

With the Clean Energy Package, the European Union introduced the concept of Renewable Energy Communities: groups of citizens, small and medium enterprises and local authorities that decide to join forces to equip themselves with systems to produce and share energy from renewable energy sources. The Italian legislation recently started an experimental phase in which renewable energy communities receive an incentivising tariff for the energy produced and shared within the community. This paper faces the problem of creating a new renewable energy community in two steps. First, a mathematical model of the energy flows among the members of the community is characterised according to the Italian schema. This model is used to find the optimal portfolio for the energy community, given energy requests and local source availability. Secondly, the Shapley value, a particular solution of cooperative games known to be the most fair method to allocate costs and profits of shared infrastructures, is proposed to distribute benefits among community members. The methodology has been applied to a case study based on a real low voltage network, and the economics for consumers and producers in participating to the project have been evaluated. The proposed solution, simulated adopting real economic parameters defined in the Italian regulatory framework, results to be economically viable from the point of view of the investors with a profitability index of 1.36 and, at the same time, aligned with the social purposes of the energy communities.
Personality Trait Analysis in Social Networks Based on Weakly Supervised Learning of Shared Images
Authors: Rodríguez Pau , Velazquez Diego , Cucurull Guillem , Gonfaus Josep M. , Roca F. Xavier , Ozawa Seiichi , Gonzàlez Jordi
Published: November 2020

Social networks have attracted the attention of psychologists, as the behavior of users can be used to assess personality traits, and to detect sentiments and critical mental situations such as depression or suicidal tendencies. Recently, the increasing amount of image uploads to social networks has shifted the focus from text to image-based personality assessment. However, obtaining the ground-truth requires giving personality questionnaires to the users, making the process very costly and slow, and hindering research on large populations. In this paper, we demonstrate that it is possible to predict which images are most associated with each personality trait of the OCEAN personality model, without requiring ground-truth personality labels. Namely, we present a weakly supervised framework which shows that the personality scores obtained using specific images textually associated with particular personality traits are highly correlated with scores obtained using standard text-based personality questionnaires. We trained an OCEAN trait model based on Convolutional Neural Networks (CNNs), learned from 120K pictures posted with specific textual hashtags, to infer whether the personality scores from the images uploaded by users are consistent with those scores obtained from text. In order to validate our claims, we performed a personality test on a heterogeneous group of 280 human subjects, showing that our model successfully predicts which kind of image will match a person with a given level of a trait. Looking at the results, we obtained evidence that personality is not only correlated with text, but with image content too. Interestingly, different visual patterns emerged from those images most liked by persons with a particular personality trait: for instance, pictures most associated with high conscientiousness usually contained healthy food, while low conscientiousness pictures contained injuries, guns, and alcohol. These findings could pave the way to complement text-based personality questionnaires with image-based questions.
Dual-Kernel-Based Aggregated Residual Network for Surface Defect Inspection in Injection Molding Processes
Authors: Lee Hwaseop , Ryu Kwangyeol
Published: November 2020

Automated quality inspection has been receiving increasing attention in manufacturing processes. Since the introduction of convolutional neural networks (CNNs), many researchers have attempted to apply CNNs to classification and detection of defect images. However, injection molding processes have not received much attention in this field of research because of product diversity, difficulty in obtaining uniform-quality product images, and short cycle times. In this study, two types of dual-kernel-based aggregated residual networks are proposed by utilizing a fixed kernel and a deformable kernel to detect surface and shape defects of molded products. The aggregated residual network is selected as a backbone, and a fixed-size, deformable kernel is applied for extracting surface and geometric features simultaneously. Comparative studies are conducted by including the existing research using the Weakly Supervised Learning for Industrial Optical Inspection dataset, which is a DAGM dataset. A case study reveals that the proposed method is applicable for inspecting the quality of injection molding products with excellent performance.
The VIRTUALDiver Project. Making Greece’s Underwater Cultural Heritage Accessible to the Public
Authors: Pehlivanides George , Monastiridis Kostas , Tourtas Alexandros , Karyati Elli , Ioannidis Giotis , Bejelou Konstantina , Antoniou Varvara , Nomikou Paraskevi
Published: November 2020

Reaching the underwater world is undoubtedly an incomparable adventure. Impressive geological structures, flourishing ecosystems, shipwrecks, and submerged landscapes lie beneath the sea surface in wait for discovery. However, this world is accessible only to those who have the chance to dive or to scientists conducting underwater research. By means of a dynamically developing sector of informatics utilizing Virtual (VR) and Augmented Reality (AR) practices, the VIRTUALDiver project intends to provide access to all the aforementioned hidden “treasures” through the creation of an innovative platform providing unique interactive experiences. More specifically, specialized guided tours in natural and virtual environments covering areas of touristic, cultural, and environmental interest. VIRTUALDiver is an experience, design and content presentation platform, a custom-made add-on environment within the Unity 3D authoring tool, offering the ability to manage multimedia content in a simplified way. No specialized programming knowledge is required, enabling the project’s interdisciplinary consortium to easily collaborate and exchange ideas. The expected result is the establishment of a successful educational and entertaining cultural product to support businesses and professionals operating in the field of culture-tourism. Above all, VIRTUALDiver aspires to become a novel form of storytelling, immersing the user into unique experiences under the waves.
Revisiting Two Simulation-Based Reliability Approaches for Coastal and Structural Engineering Applications
Authors: García-Soto Adrián-David , Calderón-Vega Felícitas , Mösso César , Valdés-Vázquez Jesús-Gerardo , Hernández-Martínez Alejandro
Published: November 2020

The normality polynomial and multi-linear regression approaches are revisited for estimating the reliability index, its precision, and other reliability-related values for coastal and structural engineering applications. In previous studies, neither the error in the reliability estimation is mathematically defined nor the adequacy of varying the tolerance is investigated. This is addressed in the present study. First, sets of given numbers of Monte Carlo simulations are obtained for three limit state functions and probabilities of failure are computed. Then, the normality polynomial approach is applied to each set and mean errors in estimating the reliability index are obtained, together with its associated uncertainty; this is defined mathematically. The data is also used to derive design points and sensitivity factors by multi-linear regression analysis for given tolerances. Results indicate that power laws define the mean error of the reliability index and its standard deviation as a function of the number of simulations for the normality polynomial approach. Results also indicate that the multi-linear regression approach accurately predicts reliability-related values if enough simulations are performed for a given tolerance. It is concluded that the revisited approaches are a valuable option to compute reliability-associated values with reduced simulations, by accepting a quantitative precision level.
Hydrogeological Behaviour and Geochemical Features of Waters in Evaporite-Bearing Low-Permeability Successions: A Case Study in Southern Sicily, Italy
Authors: Rizzo Pietro , Cappadonia Chiara , Rotigliano Edoardo , Iacumin Paola , Sanangelantoni Anna Maria , Zerbini Giulia , Celico Fulvio
Published: November 2020

Knowledge about the hydrogeological behaviour of heterogeneous low-permeability media is an important tool when designing anthropogenic works (e.g., landfills) that could potentially have negative impacts on the environment and on people’s health. The knowledge about the biogeochemical processes in these media could prevent “false positives” when studying groundwater quality and possible contamination caused by anthropogenic activities. In this research, we firstly refined knowledge about the groundwater flow field at a representative site where the groundwater flows within an evaporite-bearing low-permeability succession. Hydraulic measurements and tritium analyses demonstrated the coexistence of relatively brief to very prolonged groundwater pathways. The groundwater is recharged by local precipitation, as demonstrated by stable isotopes investigations. However, relatively deep groundwater is clearly linked to very high tritium content rainwater precipitated during the 1950s and 1960s. The deuterium content of some groundwater samples showed unusual values, explained by the interactions between the groundwater and certain gases (H2S and CH4), the presences of which are linked to sulfate-reducing bacteria and methanogenic archaea detected within the saturated medium through biomolecular investigations in the shallow organic reach clayey deposits. In a wider, methodological context, the present study demonstrates that interdisciplinary approaches provide better knowledge about the behaviour of heterogeneous low-permeability media and the meaning of each data type.
Measuring the Hyperfine Splitting and Deriving the Hyperfine Interaction Constants of the Cesium 5p67d 2D5/2 Excited State
Authors: Wang Zerong , Hou Xiaokai , Bai Jiandong , Wang Junmin
Published: November 2020

The measurement of the cesium (Cs) 5p67d2D5/2 excited state’s hyperfine splitting intervals and hyperfine interaction constants was experimentally investigated using a ladder-type (852 nm + 698 nm) three-level Cs system (5p66s2S1/2–5p66p2P3/2–5p67d2D5/2) with a room-temperature Cs atomic vapor cell. By scanning the 698 nm coupling laser’s frequency, the Doppler-free high-resolution electromagnetically-induced transparency (EIT)-assisted double-resonance optical pumping (DROP) spectra were demonstrated via transmission enhancement of the locked 852 nm probe laser. The EIT-assisted DROP spectra were employed to study the hyperfine splitting intervals for the Cs 5p67d2D5/2 excited state with a room-temperature Cs atomic vapor cell, and the radio-frequency modulation sideband of a waveguide-type electro-optic phase modulator (EOPM) was introduced for frequency calibration to improve the accuracy of frequency interval measurement. The existence of EIT makes the DROP spectral linewidth much narrower, and it is very helpful to significantly improve the spectroscopic resolution. Benefiting from the higher signal-to-noise ratio (SNR) and much better resolution of the EIT-assisted DROP spectra, the hyperfine splitting intervals between the hyperfine folds of (F” = 6), (F” = 5), and (F” = 4) of the Cs 5p67d2D5/2 state (HFS6″–5″ = −10.60(17) MHz and HFS5″–4″ = −8.54(15) MHz) were measured and, therefore, the magnetic dipole hyperfine interaction constant (A = −1.70(03) MHz) and the electrical quadrupole hyperfine interaction constant (B = −0.77(58) MHz) were derived for the Cs 5p67d2D5/2 state. These constants constitute an important reference value for an improvement of the precise measurement and determination of basic physical constants.
Error Caused by Damping Formulating in Multiple Support Excitation Problems
Authors: Qin Han , Li Luyu
Published: November 2020

The effect of multiple support excitation is an important issue in studying large-span structures. Researchers have shown that the damping related terms in the equation of motion can induce errors in the analysis. Wrongly modelling the damping matrix can induce false damping forces between the structure and the reference coordinates. In multiple support excitation problems, this error is increased when absolute coordinates are used. In this paper, this part of the error is defined as virtual damping error. The error caused by using Rayleigh damping instead of Modal damping is called damping truncation error. This study focuses on the virtual damping error and the damping truncation error that exist in the modeling methods widely used in multiple support excitation problems, namely, large mass method (LMM), relative motion method (RMM), and absolute displacement method (ADM). A new Rayleigh damping formula is proposed for LMM to prevent virtual damping error. A form of equation of motion derived from the converged LMM was proposed in the authors’ previous work. This equation of motion is proved in this paper to be equivalent to RMM when modal damping and the new Rayleigh damping formula are used. RMM is proved free from the virtual damping error. The influence of multiple support excitation effect on the damping formulating errors is studied by spectral analysis. One simplified spring-mass model and two bridge models are used for numerical simulation. The results from the numerical simulation testify to the conclusions from the spectral analysis.
Automatic Fire and Smoke Detection Method for Surveillance Systems Based on Dilated CNNs
Authors: Valikhujaev Yakhyokhuja , Abdusalomov Akmalbek , Cho Young Im
Published: November 2020

The technologies underlying fire and smoke detection systems play a crucial role in ensuring and delivering optimal performance in modern surveillance environments. In fact, fire can cause significant damage to lives and properties. Considering that the majority of cities have already installed camera-monitoring systems, this encouraged us to take advantage of the availability of these systems to develop cost-effective vision detection methods. However, this is a complex vision detection task from the perspective of deformations, unusual camera angles and viewpoints, and seasonal changes. To overcome these limitations, we propose a new method based on a deep learning approach, which uses a convolutional neural network that employs dilated convolutions. We evaluated our method by training and testing it on our custom-built dataset, which consists of images of fire and smoke that we collected from the internet and labeled manually. The performance of our method was compared with that of methods based on well-known state-of-the-art architectures. Our experimental results indicate that the classification performance and complexity of our method are superior. In addition, our method is designed to be well generalized for unseen data, which offers effective generalization and reduces the number of false alarms.
Assessing the Impact of Land Use and Land Cover Data Representation on Weather Forecast Quality: A Case Study in Central Mexico
Authors: López-Espinoza Erika Danaé , Zavala-Hidalgo Jorge , Mahmood Rezaul , Gómez-Ramos Octavio
Published: November 2020

In atmospheric modeling, an accurate representation of land cover is required because such information impacts water and energy budgets and, consequently, the performance of models in simulating regional climate. This study analyzes the impact of the land cover data on an operational weather forecasting system using the Weather Research and Forecasting (WRF) model for central Mexico, with the aim of improving the quality of the operative forecast. Two experiments were conducted using different land cover datasets: a United States Geological Survey (USGS) map and an updated North American Land Change Monitoring System (NALCMS) map. The experiments were conducted as a daily 120 h forecast for each day of January, April, July, and September of 2012, and the near-surface temperature, wind speed, and hourly precipitation were analyzed. Both experiments were compared with observations from meteorological stations. The statistical analysis of this study showed that wind speed and near-surface temperature prediction may be further improved with the updated and more accurate NALCMS dataset, particularly in the forecast covering 48 to 72 h. The Root Mean Square Error (RMSE) of the average wind speed reached a maximum reduction of up to 1.2 m s−1, whereas for the near-surface temperature there was a reduction of up to 0.6 °C. The RMSE of the average hourly precipitation was very similar between both experiments, however the location of precipitation was modified.
Study of Electron and Positron Elastic Scattering from Hydrogen Sulphide Using Analytically Obtained Static Potential
Authors: Mahato Dibyendu , Sharma Lalita , Srivastava Rajesh
Published: November 2020

A detailed study of elastic scattering of electrons and positrons from a hydrogen sulphide (H2S) molecule is presented using the method of partial wave phase shift analysis with suitably chosen complex optical potentials. The important aspect of our present work is that we uniquely obtain static potential in an analytical form and use it along with exchange (only for electron), polarization and purely imaginary absorption potentials to define the complex optical potential. The static potential is evaluated by obtaining charge density from the H2S molecule using the molecular wavefunction represented through an accurate analytical form of the Gaussian orbitals. The primary aim of our study is to test our present approach, as applied to the electron and positron scattering from H2S. Therefore, the results for electron and positron impact differential, integral, momentum-transfer, absorption and total cross sections are obtained for the incident energies in the range of 10–500 eV. Comparisons of these different types of cross section results with the available measurements and other calculations show good agreement, which suggests the applicability of our present approach.
Proteomics Answers Which Yeast Genes Are Specific for Baking, Brewing, and Ethanol Production
Authors: Davydenko Svetlana , Meledina Tatiana , Mittenberg Alexey , Shabelnikov Sergey , Vonsky Maksim , Morozov Artyom
Published: November 2020

Yeast strains are convenient models for studying domestication processes. The ability of yeast to ferment carbon sources from various substrates and to produce ethanol and carbon dioxide is the core of brewing, winemaking, and ethanol production technologies. The present study reveals the differences among yeast strains used in various industries. To understand this, we performed a proteomic study of industrial Saccharomyces cerevisiae strains followed by a comparative analysis of available yeast genetic data. Individual protein expression levels in domesticated strains from different industries indicated modulation resulting from response to technological environments. The innovative nature of this research was the discovery of genes overexpressed in yeast strains adapted to brewing, baking, and ethanol production, typical genes for specific domestication were found. We discovered a gene set typical for brewer’s yeast strains. Baker’s yeast had a specific gene adapted to osmotic stress. Toxic stress was typical for yeast used for ethanol production. The data obtained can be applied for targeted improvement of industrial strains.
Allergies to Titanium Dental Implants: What Do We Really Know about Them? A Scoping Review
Authors: Comino-Garayoa Rubén , Cortés-Bretón Brinkmann Jorge , Peláez Jesús , López-Suárez Carlos , Martínez-González Jose María , Suárez María Jesús
Published: November 2020

The purpose of this scoping review was to describe the current state of knowledge and understanding of allergies to titanium dental implants. A scoping review was conducted following the Prisma Extension for Scoping Reviews checklist. An electronic search was performed in five databases complemented by manual and grey literature searches. Fifty-two relevant papers were included for final review. Titanium particles can be released from the surfaces of dental implants in a process called tribocorrosion, which may contribute to bone loss due to inflammatory reaction. Diverse mechanisms have been described that may trigger allergy to titanium, as well as the clinical signs that manifest as the allergy develops. Allergies to titanium are uncommon but represent a real possibility that should not be overlooked in patients requiring prosthodontic rehabilitation with dental implants. Allergy can trigger a range of symptoms. Patients who have already been diagnosed with allergies to other metals will be more predisposed to suffering an allergy to titanium. Further investigation is needed in order to measure the true scope of these allergies.
Organismal Fructose Metabolism in Health and Non-Alcoholic Fatty Liver Disease
Authors: Skenderian Shea , Park Grace , Jang Cholsoon
Published: November 2020

NAFLD has alarmingly increased, yet FDA-approved drugs are still lacking. An excessive intake of fructose, especially in liquid form, is a dietary risk factor of NAFLD. While fructose metabolism has been studied for decades, it is still controversial how fructose intake can cause NAFLD. It has long been believed that fructose metabolism solely happens in the liver and accordingly, numerous studies have investigated liver fructose metabolism using primary hepatocytes or liver cell lines in culture. While cultured cells are useful for studying detailed signaling pathways and metabolism in a cell-autonomous manner, it is equally important to understand fructose metabolism at the whole-body level in live organisms. In this regard, recent in vivo studies using genetically modified mice and stable isotope tracing have tremendously expanded our understanding of the complex interaction between fructose-catabolizing organs and gut microbiota. Here, we discuss how the aberrant distribution of fructose metabolism between organs and gut microbiota can contribute to NAFLD. We also address potential therapeutic interventions of fructose-elicited NAFLD.
Transcriptional Profiling Reveals Ribosome Biogenesis, Microtubule Dynamics and Expression of Specific lncRNAs to be Part of a Common Response to Cell-Penetrating Peptides
Authors: Venit Tomas , Dowaidar Moataz , Gestin Maxime , Mahmood Syed Raza , Langel Ülo , Percipalle Piergiorgio
Published: November 2020

Cell-penetrating peptides (CPPs) are short peptides that are able to efficiently penetrate cellular lipid bilayers. Although CPPs have been used as carriers in conjugation with certain cargos to target specific genes and pathways, how rationally designed CPPs per se affect global gene expression has not been investigated. Therefore, following time course treatments with 4 CPPs-penetratin, PepFect14, mtCPP1 and TP10, HeLa cells were transcriptionally profiled by RNA sequencing. Results from these analyses showed a time-dependent response to different CPPs, with specific sets of genes related to ribosome biogenesis, microtubule dynamics and long-noncoding RNAs being differentially expressed compared to untreated controls. By using an image-based high content phenotypic profiling platform we confirmed that differential gene expression in CPP-treated HeLa cells strongly correlates with changes in cellular phenotypes such as increased nucleolar size and dispersed microtubules, compatible with altered ribosome biogenesis and cell growth. Altogether these results suggest that cells respond to different cell penetrating peptides by alteration of specific sets of genes, which are possibly part of the common response to such stimulus.
Detection Rate of 68Ga-PSMA Ligand PET/CT in Patients with Recurrent Prostate Cancer and Androgen Deprivation Therapy
Authors: Brumberg Joachim , Beckl Melanie , Dierks Alexander , Schirbel Andreas , Krebs Markus , Buck Andreas , Kübler Hubert , Lapa Constantin , Seitz Anna Katharina
Published: November 2020

Prostate-specific membrane antigen (PSMA) ligand PET/CT enables the localization of tumor lesions in patients with recurrent prostate cancer, but it is unclear whether androgen deprivation therapy (ADT) influences diagnostic accuracy. The aim of this study was to evaluate the effect of ADT on the detection rate of 68Ga-PSMA ligand PET/CT. Thus, 399 patients with initial radical prostatectomy and 68Ga-PSMA ligand PET/CT during PSA relapse were retrospectively evaluated. Propensity score matching was used to create two balanced groups of 62 subjects who either did or did not receive ADT within six months before imaging. All 68Ga-PSMA ligand PET/CT were evaluated visually and with semiquantitative measures. The detection rate of tumor recurrence was significantly higher in the group with ADT (88.7% vs. 72.6%, p = 0.02) and improved with increasing PSA-levels in both groups. In subjects with pathological PET/CT and ADT, whole-body total lesion PSMA (p < 0.01) and PSMA-derived tumor volume (p < 0.01) were significantly higher than in those without ADT. More PSMA-positive lesions and higher PSMA-derived volumetric parameters in patients with ADT suggest that a better detection rate is related to a (biologically) more advanced disease stage. Due to high detection rates in patients with PSA-levels < 2 ng/mL, the withdrawal of ADT before PSMA ligand PET/CT cannot be recommended.
Gingival Crevicular Fluid Cytokines in Moderate and Deep Sites of Stage III Periodontitis Patients in Different Rates of Clinical Progression
Authors: Romano Federica , Del Buono Wilma , Bianco Laura , Arena Martina , Mariani Giulia Maria , Di Scipio Federica , Berta Giovanni Nicolao , Aimetti Mario
Published: November 2020

Clinical criteria are inappropriate to measure the degree of susceptibility to progression of periodontal damage. Thus, the aim of this study was to assess whether gingival crevicular fluid (GCF) levels of cytokines could discriminate patients suffering from stage III periodontitis with moderate (Grade B) and rapid rates of progression (Grade C) prior to and 6 months after non-surgical periodontal treatment. GCF samples were obtained from moderate and deep sites of 20 patients diagnosed as Grade B and 20 patients as grade C stage III periodontitis and analyzed for interleukin (IL)-1β, IL-9, tumor necrosis factor (TNF)-α, and vascular endothelial growth factor (VEGF) using a high-sensitivity Bio-Plex Suspension Array System. At baseline, higher IL-1β but lower IL-9 GCF levels were observed in moderate sites of the grade C compared to the grade B group. In spite of comparable clinical improvement, this difference maintained after treatment, suggesting a residual pro-inflammatory state. In deep sites, no differences were observed between periodontitis groups except for VEGF levels that decreased more in Grade B periodontitis at 6 months post-therapy. A mathematical model was constructed to identify Grade C periodontitis patients based on the subjects’ GCF levels of IL-1β and IL-9, which achieved an area under the receiver-operating characteristic (ROC) curve of 0.94. This study can contribute to the early assessment of risk of future breakdown in periodontitis patients.